Food and Beverage Stability and Shelf Life (Woodhead Publishing Series in Food Science, Technology and Nutrition)

Food and beverage stability and shelf life

ß Woodhead Publishing Limited, 2011

Related titles: Chemical deterioration and physical instability of food and beverages (ISBN 978-1-84569-495-1) For a food product to be a success in the marketplace, it must be stable throughout its shelf life. Changes due to food chemical deterioration and physical instability are not always recognised by food producers, who are more familiar with microbial spoilage, yet can be just as problematic. This book provides an authoritative review of key topics in this area. Chapters in Parts I and II focus on the chemical reactions and physical changes which negatively affect food quality. The remaining chapters outline the likely effects on different food products. Food spoilage microorganisms (ISBN 978-1-85573-966-6) Action by microorganisms is a common means of food spoilage and ensuring that a product has a suitable shelf life is a critical factor in food quality. With current trends towards less severe processing techniques, reduced use of preservatives and higher consumption of perishable foods such as fresh fruit and vegetables, the deterioration of foods by microbial spoilage is an increasing problem for the food industry. Methods to detect, analyse and manage food spoilage are reviewed in the opening parts of this collection. The following chapters focus on important yeasts, moulds and bacteria, their classification, growth characteristics and detection and the implications of these factors for their control in food products. Understanding and measuring the shelf life of food (ISBN 978-1-85573-732-7) The shelf life of a product is critical in determining both its quality and profitability. This important collection reviews the key factors in determining shelf life and how it can be measured. Part I examines the factors affecting shelf life and spoilage, including individual chapters on the major types of food spoilage, the role of moisture and temperature, spoilage yeasts, the Maillard reaction and the factors underlying lipid oxidation. Part II addresses the best ways of measuring the shelf life of foods, with chapters on modelling food spoilage, measuring and modelling glass transition, detecting spoilage yeasts, measuring lipid oxidation, the design and validation of shelflife tests and the use of accelerated shelf-life tests. Details of these books and a complete list of Woodhead titles can be obtained by: · visiting our web site at www.woodheadpublishing.com · contacting Customer Services (e-mail: [email protected]; fax: +44 (0) 1223 832819; tel.: +44 (0) 1223 499140 ext. 130; address: Woodhead Publishing Limited, 80 High Street, Sawston, Cambridge CB22 3HJ, UK) If you would like to receive information on forthcoming titles, please send your address details to: Francis Dodds (address, tel. and fax as above; e-mail: [email protected]). Please confirm which subject areas you are interested in.

ß Woodhead Publishing Limited, 2011

Woodhead Publishing Series in Food Science,Technology and Nutrition: Number 210

Food and beverage stability and shelf life

Edited by David Kilcast and Persis Subramaniam

ß Woodhead Publishing Limited, 2011

Published by Woodhead Publishing Limited, 80 High Street, Sawston, Cambridge CB22 3HJ, UK www.woodheadpublishing.com Woodhead Publishing, 1518 Walnut Street, Suite 1100, Philadelphia, PA 19102-3406, USA Woodhead Publishing India Private Limited, G-2, Vardaan House, 7/28 Ansari Road, Daryaganj, New Delhi ± 110002, India www.woodheadpublishingindia.com First published 2011, Woodhead Publishing Limited ß Woodhead Publishing Limited, 2011 The authors have asserted their moral rights. This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. Reasonable efforts have been made to publish reliable data and information, but the authors and the publisher cannot assume responsibility for the validity of all materials. Neither the authors nor the publisher, nor anyone else associated with this publication, shall be liable for any loss, damage or liability directly or indirectly caused or alleged to be caused by this book. Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming and recording, or by any information storage or retrieval system, without permission in writing from Woodhead Publishing Limited. The consent of Woodhead Publishing Limited does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from Woodhead Publishing Limited for such copying. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. ISBN 978-1-84569-701-3 (print) ISBN 978-0-85709-254-0 (online) ISSN 2042-8049 Woodhead Publishing Series in Food Science, Technology and Nutrition (print) ISSN 2042-8057 Woodhead Publishing Series in Food Science, Technology and Nutrition (online) The publisher's policy is to use permanent paper from mills that operate a sustainable forestry policy, and which has been manufactured from pulp which is processed using acidfree and elemental chlorine-free practices. Furthermore, the publisher ensures that the text paper and cover board used have met acceptable environmental accreditation standards. Typeset by Godiva Publishing Services Limited, Coventry, West Midlands, UK Printed by TJI Digital, Padstow, Cornwall, UK

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Contents

Contributor contact details

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Woodhead Publishing Series in Food Science, Technology and Nutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Preface

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Part I Deteriorative processes and factors influencing shelf life 1

Microbiological spoilage of foods and beverages . . . . . . . . . . . . . . . . G-J. E. Nychas and E. Panagou, Agricultural University of Athens, Greece 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Spoilage of foods and beverages; a microbiological approach: microbes vs indigenous enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Factors affecting the rate of microbiological spoilage of foods and beverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Evaluating, monitoring and measuring microbiological spoilage of foods and beverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Predicting microbiological spoilage of foods and beverages 1.6 Preventing microbiological spoilage of foods and beverages 1.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . 1.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chemical deterioration and physical instability of foods and beverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F. Kong and R. P. Singh, University of California, Davis, USA 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Chemical deterioration and physical instability of foods and beverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Factors affecting the rate of quality loss due to chemical deterioration and physical instability . . . . . . . . . . . . . . . . . . . . . . . 2.4 Measuring chemical deterioration and physical instability of foods and beverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Predicting and monitoring chemical deterioration and physical instability of foods and beverages . . . . . . . . . . . . . . . . . 2.6 Preventing chemical deterioration and physical instability of foods and beverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . 2.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Moisture loss, gain and migration in foods . . . . . . . . . . . . . . . . . . . . . . G. Roudaut, University of Burgundy, France and F. Debeaufort, University of Burgundy, France and IUT-Dijon, France 3.1 Introduction: moisture loss, gain and migration in foods and quality deterioration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Mechanism of the moisture transfers in food products . . . . . 3.3 Measuring, monitoring and predicting moisture loss, gain and migrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Moisture loss, gain and migration related to the shelf life . . 3.5 Conditions for moisture migration and foods affected by moisture transfer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Insect and mite penetration and contamination of packaged foods C. H. Bell, Food and Environment Research Agency, UK 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Insects and mites contaminating stored food products . . . . . . 4.3 Combating critical points in the food chain . . . . . . . . . . . . . . . . 4.4 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Sources of further information and advice . . . . . . . . . . . . . . . . . . 4.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

29 29 30 39 44 49 53 55 55 56 63

63 64 70 93 97 100 106 106 107 121 126 127 128

The influence of ingredients on product stability and shelf life . 132 N. W. G. Young, Danisco A/S, Multiple Food Applications, Denmark and University of Chester, UK and G. R. O'Sullivan, Danisco A/S, Multiple Food Applications, Denmark 5.1 Introduction to shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 ß Woodhead Publishing Limited, 2011

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Methods of shelf life extension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Movement of moisture in food systems . . . . . . . . . . . . . . . . . . . . Food spoilage due to water activity . . . . . . . . . . . . . . . . . . . . . . . . Edible moisture barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Molecular mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Preservation of foods by freezing . . . . . . . . . . . . . . . . . . . . . . . . . . Sweetener ingredients as humectants or cryoprotectants . . . . Ingredients for shelf life extension . . . . . . . . . . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of further information and advice . . . . . . . . . . . . . . . . . . Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

133 135 144 147 148 150 154 161 176 177 179

Processing and food and beverage shelf life . . . . . . . . . . . . . . . . . . . . . M. Brown, MHB Consulting, UK 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Main quality change factors and their interaction with processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Shelf life and stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Product and process design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 Unit operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 Production of low and intermediate moisture foods . . . . . . . . 6.8 Thermal processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9 Filling and packaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.10 Novel processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.11 Hygiene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.12 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.13 References and further reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Packaging and food and beverage shelf life . . . . . . . . . . . . . . . . . . . . . G. L. Robertson, University of Queensland and Food
Packaging
Environment, Australia 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Role of packaging in extending food and beverage shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Major packaging materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Key package properties related to shelf life . . . . . . . . . . . . . . . . 7.5 Predicting shelf life of packaged foods and beverages . . . . . . 7.6 Packaging migrants and food and beverage shelf life . . . . . . 7.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . 7.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contents Effects of food and beverage storage, distribution, display and consumer handling on shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Evans, London South Bank University, UK 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Overview of the cold chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Storage life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 Sectors of the cold chain and their influence on food quality and safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . 8.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Smart packaging for monitoring and managing food and beverage shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . P. S. Taoukis, National Technical University of Athens, Greece 9.1 Introduction: smart packaging ± time-temperature integrators (TTIs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Principles of the application of time-temperature integrators (TTIs) for shelf life monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Requirements and selection of time-temperature integrators (TTIs) for food and beverage products . . . . . . . . . . . . . . . . . . . . . 9.4 Use of time-temperature integrators (TTIs) for shelf life management and optimization in the cold chain ± case study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Part II

273 273 274 276 283 298 299 300 303 303 304 309 311 320 321 321

Methods for shelf life and stability evaluation

10 Food storage trials: an introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. M. D. Man, London South Bank University, UK 10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Food deterioration and spoilage . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 Storage trials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Sensory evaluation methods for food shelf life assessment . . . . . . D. Kilcast, Consultant in Food and Beverage Sensory Quality, UK 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Principles of sensory evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 Basic requirements for sensory analysis . . . . . . . . . . . . . . . . . . . . 11.4 Discrimination tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5 Quantitative descriptive tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ß Woodhead Publishing Limited, 2011

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Contents 11.6 11.7 11.8 11.9 11.10 11.11 11.12 11.13 11.14 11.15

Consumer acceptability testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Operation of sensory shelf life tests . . . . . . . . . . . . . . . . . . . . . . . . Design of sensory shelf life tests . . . . . . . . . . . . . . . . . . . . . . . . . . . Interpretation of sensory shelf life data . . . . . . . . . . . . . . . . . . . . . Instrumental methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Standardisation in sensory shelf life testing . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of further information and advice . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

12 Advances in instrumental methods to determine food quality deterioration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F. Kong and R. P. Singh, University of California, Davis, USA 12.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 Assessing food appearance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3 Measurement of relative humidity (RH), moisture, and water activity (a w) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.4 Texture evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 Evaluation of rheological properties of liquid and semi-solid foods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 Assessing lipid oxidation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7 Electronic nose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 Electronic tongue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.9 Infrared (IR) spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.10 Microbiological testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.11 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.12 Sources of further information and advice . . . . . . . . . . . . . . . . . . 12.13 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Modelling microbiological shelf life of foods and beverages . . . . A. AmeÂzquita, D. Kan-King-Yu and Y. Le Marc, Unilever R&D Colworth, UK 13.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2 Classification of predictive models by microbial response . . 13.3 Development of predictive models for microbiological safety and stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.4 Modelling approaches, applications and opportunities for shelf life prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.5 Usage considerations and access to predictive microbiology electronic resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.7 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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14 Modelling chemical and physical deterioration of foods and beverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. J. Sousa Gallagher, P. V. Mahajan and Z. Yan, University College Cork, Ireland 14.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 Factors influencing shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3 Development of mathematical models . . . . . . . . . . . . . . . . . . . . . . 14.4 Predictive mathematical models . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Accelerated shelf life testing of foods . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Mizrahi, Technion-Israel Institute of Technology, Israel 15.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 Basic principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3 Initial rate approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4 Kinetic model approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.5 Single accelerating factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.6 Glass transition models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.7 Multiple accelerating factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 Dynamic methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 The `no model' approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.10 Combination of approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.11 Problems in accelerated shelf life tests . . . . . . . . . . . . . . . . . . . . . 15.12 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.13 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Microbiological challenge testing of foods . . . . . . . . . . . . . . . . . . . . . . . E. Komitopoulou, Leatherhead Food Research, UK 16.1 Introduction: role of challenge testing in shelf life evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.2 Basic principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.3 Challenge testing limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.4 Challenge testing and the use of mathematical models . . . . . 16.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . 16.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part III

459 459 460 462 466 476 477 482 482 483 483 485 487 493 493 496 498 500 501 502 503 507 507 508 519 519 521 521 522

The stability and shelf life of particular products

17 Beer shelf life and stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G. G. Stewart and F. G. Priest, Heriot-Watt University, UK 17.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.2 Biological instability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Physical instability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flavour stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Foam stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gushing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Light stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

529 531 533 536 536 537 537

18 Shelf life of wine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. S. Jackson, Brock University, Canada 18.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.2 Factors affecting wine stability and shelf life . . . . . . . . . . . . . . . 18.3 Changes during the shelf life of wine . . . . . . . . . . . . . . . . . . . . . . 18.4 Evaluating wine shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.5 Preventing wine quality deterioration at or post-bottling . . . 18.6 Sensory significance of shelf life changes . . . . . . . . . . . . . . . . . . 18.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . 18.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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19 The stability and shelf life of fruit juices and soft drinks . . . . . . . P. Ashurst, Ashurst and Associates, UK 19.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.2 Factors influencing the stability of fruit juices and soft drinks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.3 Ensuring product stability and extending shelf life . . . . . . . . . 19.4 Shelf life determination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . 20 Practical uses of sensory evaluation for the assessment of soft drink shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. L. Rogers, Consultant, UK 20.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.2 Using a risk-based approach to shelf life for soft drinks . . . 20.3 Estimating shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.4 Determining shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.5 Monitoring shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.6 Considerations before developing the shelf life plan . . . . . . . 20.7 Developing the sensory plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.8 Case studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.9 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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21 The stability and shelf life of coffee products . . . . . . . . . . . . . . . . . . . L. Manzocco, S. Calligaris and M. C. Nicoli, University of Udine, Italy 21.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.2 Main critical events affecting the stability and shelf life of coffee products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.3 Ensuring stability and extending the shelf life of coffee . . . . 21.4 Evaluating the shelf life of coffee . . . . . . . . . . . . . . . . . . . . . . . . . . 21.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . 21.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 The stability and shelf life of fruit and vegetables . . . . . . . . . . . . . . M. J. Sousa Gallagher and P. V. Mahajan, University College Cork, Ireland 22.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.2 Stability and shelf life of fruit and vegetables . . . . . . . . . . . . . . 22.3 Extending the shelf life of fruit and vegetables . . . . . . . . . . . . . 22.4 Controlled and modified atmosphere packaging for longer shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 The stability and shelf life of bread and other bakery products S. P. Cauvain and L. S. Young, BakeTran, UK 23.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.2 A brief overview of the manufacture of bakery products . . . 23.3 The key `fresh' characteristics of bakery products . . . . . . . . . . 23.4 Factors affecting the stability of bread and other bakery products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.5 Evaluating the shelf life of bread and other bakery products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.6 Ensuring stability and extending the shelf life of bread and other bakery products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 The stability and shelf life of fats and oils . . . . . . . . . . . . . . . . . . . . . . . G. Talbot, The Fat Consultant, UK 24.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.2 Mechanisms of oxidation and hydrolysis in fats and oils . . . 24.3 Factors affecting the stability and shelf life of fats and oils 24.4 Evaluating the shelf life of fats and oils . . . . . . . . . . . . . . . . . . . . 24.5 Ensuring stability and extending the shelf life of fats and oils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ß Woodhead Publishing Limited, 2011

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Sources of further information and advice . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

714 714

25 The stability and shelf life of confectionery products . . . . . . . . . . . P. Subramaniam, Leatherhead Food Research, UK 25.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.2 Factors affecting shelf life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.3 Chocolate and chocolate products . . . . . . . . . . . . . . . . . . . . . . . . . . 25.4 Sugar glass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.5 Toffee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.6 Gums and jellies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.7 Aerated confectionery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . 25.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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26 The stability and shelf life of vitamin-fortified foods . . . . . . . . . . . . R. Burch, Leatherhead Food Research, UK 26.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.2 Factors affecting the stability and shelf life of vitaminfortified foods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.3 Ensuring stability and extending the shelf life of vitaminfortified foods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.4 Evaluating the shelf life of vitamin-fortified foods . . . . . . . . . 26.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . 26.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 The stability and shelf life of milk and milk products . . . . . . . . . . D. D. Muir, Consultant, UK 27.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.2 Chemical composition and principal reactions of milk . . . . . 27.3 Bacteria in milk and related enzyme activity . . . . . . . . . . . . . . . 27.4 Raw milk enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.5 Control of the quality of short shelf life products . . . . . . . . . . 27.6 Factors influencing the stability of long shelf life products . 27.7 Control of the stability of long life milk products . . . . . . . . . . 27.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.9 Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.10 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 The stability and shelf life of seafood . . . . . . . . . . . . . . . . . . . . . . . . . . . . F. ToldraÂ, Institute of Agro-chemical Technology and Food (CSIC), Spain and M. Reig, Universidad PoliteÂcnica de Valencia, Spain 28.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.2 Factors affecting the stability and shelf life of seafood . . . . . 28.3 Microorganisms involved in seafood spoilage . . . . . . . . . . . . . . ß Woodhead Publishing Limited, 2011

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Evaluation of the shelf life of seafood . . . . . . . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of further information and advice . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

784 787 788 788

29 The stability and shelf life of meat and poultry . . . . . . . . . . . . . . . . . M. G. O'Sullivan, University College Cork, Ireland 29.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.2 Factors affecting the stability and shelf life of meat and poultry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.3 Evaluating the shelf life of meat and poultry . . . . . . . . . . . . . . . 29.4 Ensuring stability and extending the shelf life of meat and poultry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . 29.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

793

804 808 809 809

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 1

(* = main contact)

Editors Dr David Kilcast Consultant in Food and Beverage Sensory Quality E-mail: [email protected] Persis Subramaniam Leatherhead Food Research Randalls Road Leatherhead KT22 7RY UK E-mail: psubramaniam@ leatherheadfood.com

George-John E. Nychas* and Efstathios Panagou Department of Food Science Technology & Human Nutrition Laboratory of Microbiology and Biotechnology of Foods Agricultural University of Athens Iera odos 75 Athens 11855 Greece E-mail: [email protected]

Chapters 2 and 12 Fanbin Kong and R. Paul Singh* Department of Biological and Agricultural Engineering University of California, Davis Davis, CA 95616 USA E-mail: [email protected]

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Chapter 3

Chapter 5

GaeÈlle Roudaut* Department of Water, Active Molecules, Macromolecules and Activities EMMA EA 581 AgroSup-Dijon Universite de Bourgogne 1 esplanade Erasme 21 000 Dijon France E-mail: [email protected]

Professor Niall W. G. Young* Danisco A/S, Multiple Food Applications Edwin Rahrs Vej 38 8220 Brabrand Denmark E-mail: [email protected]

FreÂdeÂric Debeaufort Department of Water, Active Molecules, Macromolecules and Activities EMMA EA 581 AgroSup-Dijon Universite de Bourgogne 1 esplanade Erasme 21 000 Dijon France and IUT-Dijon 7 Blvd Docteur Petitjean BP 17867, 21078 Dijon Cedex France

Chapter 4 Dr Christopher H. Bell Food and Environment Research Agency Sand Hutton York YO41 1LZ UK E-mail: [email protected]

and University of Chester Environmental Quality and Food Safety Research Unit Department of Biological Sciences Parkgate Road Chester CH1 4BJ UK Geoffrey R. O'Sullivan Danisco A/S, Multiple Food Applications Edwin Rahrs Vej 38 8220 Brabrand Denmark E-mail: geoffrey.royston.osullivan@ danisco.com

Chapter 6 Martyn Brown MHB Consulting 41 College Road The Historic Dockyard Chatham ME4 4JS UK E-mail: [email protected]

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Chapter 7

Chapter 11

Professor Gordon L. Robertson University of Queensland and Food
Packaging
Environment 6066 Lugano Drive Hope Island QLD 4212 Australia E-mail: [email protected]

Dr David Kilcast Consultant in Food and Beverage Sensory Quality & Leatherhead Food International E-mail: [email protected]

Chapter 8 Dr Judith Evans London South Bank University Churchill Building Langford Bristol BS40 5DU UK E-mail: [email protected]

Chapter 13 Alejandro AmeÂzquita*, Denis KanKing-Yu and Yvan Le Marc Safety & Environmental Assurance Centre Unilever R&D Colworth Sharnbrook MK44 1LQ UK E-mail: Alejandro.Amezquita@ unilever.com

Chapter 14

Chapter 9 Dr Petros S. Taoukis National Technical University of Athens School of Chemical Engineering Division IV ± Product and Process Development Laboratory of Food Chemistry and Technology Iroon Polytechniou 5 15780 Athens Greece E-mail: [email protected]

Dr Maria J. Sousa Gallagher*, Dr Pramod V. Mahajan and Dr Zhengyong Yan Department of Process & Chemical Engineering College of Science, Engineering and Food Science University College Cork, UCC College Road Cork Ireland E-mail: [email protected]

Chapter 15

Chapter 10 Dr Dominic Man London South Bank University London E-mail: [email protected]

Professor Shimon Mizrahi Technion-Israel Institute of Technology Israel E-mail: [email protected]

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Chapter 16

Chapter 20

Dr Evangelia Komitopoulou Leatherhead Food Research Randalls Road Leatherhead KT22 7RY UK E-mail: ekomitopoulou@ leatherheadfood.com

Lauren L. Rogers Consultant 17 Alma Street Leek ST13 8EH UK E-mail: [email protected]

Chapter 21

Chapter 17 Professor Graham G. Stewart* and Professor Fergus G. Priest International Centre for Brewing and Distilling Heriot-Watt University Riccarton Edinburgh EH14 4AS UK E-mail: [email protected]

Chapter 18 Dr Ronald S. Jackson Cool Climate Oenology and Viticulture Institute (CCOVI) Brock University 500 Glenridge Avenue St Catharines Ontario Canada L2S 3A1 E-mail: [email protected]

Lara Manzocco*, Sonia Calligaris and Maria Cristina Nicoli Department of Food Science University of Udine via Sondrio 2a 33100 Udine Italy E-mail: [email protected]

Chapter 22 Dr Maria J. Sousa Gallagher* and Dr Pramod V. Mahajan Department of Process & Chemical Engineering College of Science, Engineering and Food Science University College Cork, UCC College Road Cork Ireland E-mail: [email protected]

Chapter 23

Chapter 19 Dr Philip Ashurst Ashurst and Associates Reachfar Middleton-on-the-Hill Ludlow SY8 4BD UK E-mail: [email protected]

Dr Stanley P. Cauvain* and Dr Linda S. Young BakeTran 97 Guinions Road High Wycombe HP13 7NU UK E-mail: [email protected] [email protected]

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Chapter 24

Chapter 28

Geoff Talbot The Fat Consultant Suite 250 St Loyes House 20 St Loyes Street Bedford MK40 1ZL UK E-mail: [email protected]

Fidel ToldraÂ* Instituto de AgroquõÂmica y TecnologõÂa de Alimentos (CSIC) Avenue AgustõÂn Escardino 7 46980 Paterna (Valencia) Spain E-mail: [email protected]

Chapter 25 Persis Subramaniam Leatherhead Food Research Randalls Road Leatherhead KT22 7RY E-mail: [email protected]

Milagro Reig Institute of Food Engineering for Development Universidad PoliteÂcnica de Valencia Camino de Vera s/n 46022, Valencia Spain E-mail: [email protected]

Chapter 29 Chapter 26 Dr Rachel Burch Leatherhead Food Research Randalls Road Leatherhead KT22 7RY UK E-mail: [email protected]

Dr Maurice G. O'Sullivan School of Food and Nutritional Sciences University College Cork Ireland E-mail: [email protected]

Chapter 27 Professor David Donald Muir Consultant 26 Pennyvenie Way Girdle Toll Irvine KA11 1QQ UK E-mail: [email protected]

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24 Food irradiation: a reference guide V. M. Wilkinson and G. Gould 25 Kent's technology of cereals: an introduction for students of food science and agriculture Fourth edition N. L. Kent and A. D. Evers 26 Biosensors for food analysis Edited by A. O. Scott 27 Separation processes in the food and biotechnology industries: principles and applications Edited by A. S. Grandison and M. J. Lewis 28 Handbook of indices of food quality and authenticity R. S. Singhal, P. K. Kulkarni and D. V. Rege 29 Principles and practices for the safe processing of foods D. A. Shapton and N. F. Shapton 30 Biscuit, cookie and cracker manufacturing manuals Volume 1: ingredients D. Manley 31 Biscuit, cookie and cracker manufacturing manuals Volume 2: biscuit doughs D. Manley 32 Biscuit, cookie and cracker manufacturing manuals Volume 3: biscuit dough piece forming D. Manley 33 Biscuit, cookie and cracker manufacturing manuals Volume 4: baking and cooling of biscuits D. Manley 34 Biscuit, cookie and cracker manufacturing manuals Volume 5: secondary processing in biscuit manufacturing D. Manley 35 Biscuit, cookie and cracker manufacturing manuals Volume 6: biscuit packaging and storage D. Manley 36 Practical dehydration Second edition M. Greensmith 37 Lawrie's meat science Sixth edition R. A. Lawrie 38 Yoghurt: science and technology Second edition A. Y. Tamime and R. K. Robinson 39 New ingredients in food processing: biochemistry and agriculture G. Linden and D. Lorient 40 Benders' dictionary of nutrition and food technology Seventh edition D. A. Bender and A. E. Bender 41 Technology of biscuits, crackers and cookies Third edition D. Manley 42 Food processing technology: principles and practice Second edition P. J. Fellows 43 Managing frozen foods Edited by C. J. Kennedy 44 Handbook of hydrocolloids Edited by G. O. Phillips and P. A. Williams 45 Food labelling Edited by J. R. Blanchfield 46 Cereal biotechnology Edited by P. C. Morris and J. H. Bryce 47 Food intolerance and the food industry Edited by T. Dean 48 The stability and shelf life of food Edited by D. Kilcast and P. Subramaniam 49 Functional foods: concept to product Edited by G. R. Gibson and C. M. Williams 50 Chilled foods: a comprehensive guide Second edition Edited by M. Stringer and C. Dennis 51 HACCP in the meat industry Edited by M. Brown 52 Biscuit, cracker and cookie recipes for the food industry D. Manley 53 Cereals processing technology Edited by G. Owens 54 Baking problems solved S. P. Cauvain and L. S. Young 55 Thermal technologies in food processing Edited by P. Richardson 56 Frying: improving quality Edited by J. B. Rossell 57 Food chemical safety Volume 1: contaminants Edited by D. Watson 58 Making the most of HACCP: learning from others' experience Edited by T. Mayes and S. Mortimore 59 Food process modelling Edited by L. M. M. Tijskens, M. L. A. T. M. Hertog and B. M. NicolaõÈ

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100 Understanding and measuring the shelf-life of food Edited by R. Steele 101 Poultry meat processing and quality Edited by G. Mead 102 Functional foods, ageing and degenerative disease Edited by C. Remacle and B. Reusens 103 Mycotoxins in food: detection and control Edited by N. Magan and M. Olsen 104 Improving the thermal processing of foods Edited by P. Richardson 105 Pesticide, veterinary and other residues in food Edited by D. Watson 106 Starch in food: structure, functions and applications Edited by A.-C. Eliasson 107 Functional foods, cardiovascular disease and diabetes Edited by A. Arnoldi 108 Brewing: science and practice D. E. Briggs, P. A. Brookes, R. Stevens and C. A. Boulton 109 Using cereal science and technology for the benefit of consumers: proceedings of the 12th International ICC Cereal and Bread Congress, 24±26th May, 2004, Harrogate, UK Edited by S. P. Cauvain, L. S. Young and S. Salmon 110 Improving the safety of fresh meat Edited by J. Sofos 111 Understanding pathogen behaviour in food: virulence, stress response and resistance Edited by M. Griffiths 112 The microwave processing of foods Edited by H. Schubert and M. Regier 113 Food safety control in the poultry industry Edited by G. Mead 114 Improving the safety of fresh fruit and vegetables Edited by W. Jongen 115 Food, diet and obesity Edited by D. Mela 116 Handbook of hygiene control in the food industry Edited by H. L. M. Lelieveld, M. A. Mostert and J. Holah 117 Detecting allergens in food Edited by S. Koppelman and S. Hefle 118 Improving the fat content of foods Edited by C. Williams and J. Buttriss 119 Improving traceability in food processing and distribution Edited by I. Smith and A. Furness 120 Flavour in food Edited by A. Voilley and P. Etievant 121 The Chorleywood bread process S. P. Cauvain and L. S. Young 122 Food spoilage microorganisms Edited by C. de W. Blackburn 123 Emerging foodborne pathogens Edited by Y. Motarjemi and M. Adams 124 Benders' dictionary of nutrition and food technology Eighth edition D. A. Bender 125 Optimising sweet taste in foods Edited by W. J. Spillane 126 Brewing: new technologies Edited by C. Bamforth 127 Handbook of herbs and spices Volume 3 Edited by K. V. Peter 128 Lawrie's meat science Seventh edition R. A. Lawrie in collaboration with D. A. Ledward 129 Modifying lipids for use in food Edited by F. Gunstone 130 Meat products handbook: practical science and technology G. Feiner 131 Food consumption and disease risk: consumer±pathogen interactions Edited by M. Potter 132 Acrylamide and other hazardous compounds in heat-treated foods Edited by K. Skog and J. Alexander 133 Managing allergens in food Edited by C. Mills, H. Wichers and K. HoffmanSommergruber 134 Microbiological analysis of red meat, poultry and eggs Edited by G. Mead 135 Maximising the value of marine by-products Edited by F. Shahidi 136 Chemical migration and food contact materials Edited by K. Barnes, R. Sinclair and D. Watson 137 Understanding consumers of food products Edited by L. Frewer and H. van Trijp 138 Reducing salt in foods: practical strategies Edited by D. Kilcast and F. Angus 139 Modelling microorganisms in food Edited by S. Brul, S. Van Gerwen and M. Zwietering

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140 Tamime and Robinson's Yoghurt: science and technology Third edition A. Y. Tamime and R. K. Robinson 141 Handbook of waste management and co-product recovery in food processing Volume 1 Edited by K. W. Waldron 142 Improving the flavour of cheese Edited by B. Weimer 143 Novel food ingredients for weight control Edited by C. J. K. Henry 144 Consumer-led food product development Edited by H. MacFie 145 Functional dairy products Volume 2 Edited by M. Saarela 146 Modifying flavour in food Edited by A. J. Taylor and J. Hort 147 Cheese problems solved Edited by P. L. H. McSweeney 148 Handbook of organic food safety and quality Edited by J. Cooper, C. Leifert and U. Niggli 149 Understanding and controlling the microstructure of complex foods Edited by D. J. McClements 150 Novel enzyme technology for food applications Edited by R. Rastall 151 Food preservation by pulsed electric fields: from research to application Edited by H. L. M. Lelieveld and S. W. H. de Haan 152 Technology of functional cereal products Edited by B. R. Hamaker 153 Case studies in food product development Edited by M. Earle and R. Earle 154 Delivery and controlled release of bioactives in foods and nutraceuticals Edited by N. Garti 155 Fruit and vegetable flavour: recent advances and future prospects Edited by B. BruÈckner and S. G. Wyllie 156 Food fortification and supplementation: technological, safety and regulatory aspects Edited by P. Berry Ottaway 157 Improving the health-promoting properties of fruit and vegetable products Edited by F. A. TomaÂs-BarberaÂn and M. I. Gil 158 Improving seafood products for the consumer Edited by T. Bùrresen 159 In-pack processed foods: improving quality Edited by P. Richardson 160 Handbook of water and energy management in food processing Edited by J. KlemesÏ, R. Smith and J.-K. Kim 161 Environmentally compatible food packaging Edited by E. Chiellini 162 Improving farmed fish quality and safety Edited by é. Lie 163 Carbohydrate-active enzymes Edited by K.-H. Park 164 Chilled foods: a comprehensive guide Third edition Edited by M. Brown 165 Food for the ageing population Edited by M. M. Raats, C. P. G. M. de Groot and W. A. Van Staveren 166 Improving the sensory and nutritional quality of fresh meat Edited by J. P. Kerry and D. A. Ledward 167 Shellfish safety and quality Edited by S. E. Shumway and G. E. Rodrick 168 Functional and speciality beverage technology Edited by P. Paquin 169 Functional foods: principles and technology M. Guo 170 Endocrine-disrupting chemicals in food Edited by I. Shaw 171 Meals in science and practice: interdisciplinary research and business applications Edited by H. L. Meiselman 172 Food constituents and oral health: current status and future prospects Edited by M. Wilson 173 Handbook of hydrocolloids Second edition Edited by G. O. Phillips and P. A. Williams 174 Food processing technology: principles and practice Third edition P. J. Fellows 175 Science and technology of enrobed and filled chocolate, confectionery and bakery products Edited by G. Talbot

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176 Foodborne pathogens: hazards, risk analysis and control Second edition Edited by C. de W. Blackburn and P. J. McClure 177 Designing functional foods: measuring and controlling food structure breakdown and absorption Edited by D. J. McClements and E. A. Decker 178 New technologies in aquaculture: improving production efficiency, quality and environmental management Edited by G. Burnell and G. Allan 179 More baking problems solved S. P. Cauvain and L. S. Young 180 Soft drink and fruit juice problems solved P. Ashurst and R. Hargitt 181 Biofilms in the food and beverage industries Edited by P. M. Fratamico, B. A. Annous and N. W. Gunther 182 Dairy-derived ingredients: food and neutraceutical uses Edited by M. Corredig 183 Handbook of waste management and co-product recovery in food processing Volume 2 Edited by K. W. Waldron 184 Innovations in food labelling Edited by J. Albert 185 Delivering performance in food supply chains Edited by C. Mena and G. Stevens 186 Chemical deterioration and physical instability of food and beverages Edited by L. Skibsted, J. Risbo and M. Andersen 187 Managing wine quality Volume 1: viticulture and wine quality Edited by A. G. Reynolds 188 Improving the safety and quality of milk Volume 1: milk production and processing Edited by M. Griffiths 189 Improving the safety and quality of milk Volume 2: improving quality in milk products Edited by M. Griffiths 190 Cereal grains: assessing and managing quality Edited by C. Wrigley and I. Batey 191 Sensory analysis for food and beverage control: a practical guide Edited by D. Kilcast 192 Managing wine quality Volume 2: oenology and wine quality Edited by A. G. Reynolds 193 Winemaking problems solved Edited by C. E. Butzke 194 Environmental assessment and management in the food industry Edited by U. Sonesson, J. Berlin and F. Ziegler 195 Consumer-driven innovation in food and personal care products Edited by S. R. Jaeger and H. MacFie 196 Tracing pathogens in the food chain Edited by S. Brul, P. M. Fratamico and T. A. McMeekin 197 Case studies in novel food processing technologies: innovations in processing, packing and predictive modelling Edited by C. J. Doona, K. Kustin and F. E. Feeherry 198 Freeze-drying of pharmaceutical and food products T.-C. Hua, B.-L. Liu and H. Zhang 199 Oxidation in foods and beverages and antioxidant applications Volume 1: understanding mechanisms of oxidation and antioxidant activity Edited by E. A. Decker, R. J. Elias and D. J. McClements 200 Oxidation in foods and beverages and antioxidant applications Volume 2: management in different industry sectors Edited by E. A. Decker, R. J. Elias and D. J. McClements 201 Protective cultures, antimicrobial metabolites and bacteriophages of food and beverage biopreservation Edited by C. Lacroix 202 Separation, extraction and concentration processes in the food, beverage and nutraceutical industries Edited by S. S. H. Rizvi 203 Determining mycotoxins and mycotoxigenic fungi in food and feed Edited by S. De Saeger 204 Developing children's food products Edited by D. Kilcast and F. Angus

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205 Functional foods: concept to product Second edition Edited by M. Saarela 206 Postharvest biology and technology of tropical and subtropical fruits Volume 1 Edited by E. M. Yahia 207 Postharvest biology and technology of tropical and subtropical fruits Volume 2 Edited by E. M. Yahia 208 Postharvest biology and technology of tropical and subtropical fruits Volume 3 Edited by E. M. Yahia 209 Postharvest biology and technology of tropical and subtropical fruits Volume 4 Edited by E. M. Yahia 210 Food and beverage stability and shelf life Edited by D. Kilcast and P. Subramaniam 211 Processed meats: improving safety, nutrition and quality Edited by J. P. Kerry and J. F. Kerry 212 Food chain integrity: a holistic approach to food traceability, safety, quality and authenticity Edited by J. Hoorfar, K. Jordan, F. Butler and R. Prugger 213 Improving the safety and quality of eggs and egg products Volume 1 Edited by Y. Nys, M. Bain and F. Van Immerseel 214 Improving the safety and quality of eggs and egg products Volume 2 Edited by Y. Nys, M. Bain and F. Van Immerseel 215 Feed and fodder contamination: effects on livestock and food safety Edited by J. Fink-Gremmels 216 Hygiene in the design, construction and renovation of food processing factories Edited by H. L. M. Lelieveld and J. Holah 217 Technology of biscuits, crackers and cookies Fourth edition Edited by D. Manley 218 Nanotechnology in the food, beverage and nutraceutical industries Edited by Q. Huang 219 Rice quality K. R. Bhattacharya 220 Meat, poultry and seafood packaging Edited by J. P. Kerry 221 Reducing saturated fats in foods Edited by G. Talbot 222 Handbook of food proteins Edited by G. O. Phillips and P. A. Williams 223 Lifetime nutritional influences on cognition, behaviour and psychiatric illness Edited by D. Benton

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Preface

The stability of a food product and its consequent shelf life depends on many factors including the quality of ingredients, product composition and structure, processing conditions used during manufacture, packaging characteristics and finally the storage, handling and distribution conditions. All these factors need to be firstly understood and then controlled to achieve the optimal or target quality and shelf life. The food industry has a great responsibility firstly to ensure that the products it manufactures are safe at every occasion over its entire shelf life and, additionally, that the products are of a sensory quality acceptable to and expected by the consumer. Manufacturers need to address both these issues in setting the shelf life for their products. Short shelf life products that spoil due to microbial activity, such as chilled products, are marked with a `use by' date, whereas the more stable products, that degrade but do not pose a health risk, are given a `best before' date. These date marks are set by the manufacturers after much testing to determine the product shelf life. A general problem faced by manufacturers is the time constraint of the product development stage. Often when dealing with relatively stable products, real time tests cannot be performed that can run to the end of life. In these cases, the manufacturer has to rely on a combination of previous experience and results of accelerated stability tests to set the shelf life. If the shelf life is set too conservatively, there is an impact on unnecessary food waste, but if set too generously there may be an impact on loss of quality and consumer acceptability. Shelf life dating of food is currently a hot topic for both government authorities and the food industry. Industry is facing pressures from the authorities and consumer groups to reduce the amount of packaging and food waste. Consumers are better informed and more demanding with regard to products they buy and consume. The constant demand by consumers for healthier products with

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Preface

reduced fat, sugar and salt, and the removal of artificial additives, including preservatives, puts further pressure on manufacturers in terms of ensuring food safety and a target shelf life. Achieving the targets requires a good knowledge of the impact of ingredients and processing for the different categories of products. This book has been produced to provide useful information to those addressing issues relating to the stability of products. Theoretical and practical aspects of product stability are brought together in making decisions about the storage stability and setting of shelf life. The experience and help of experts are invaluable in this process as it is not possible for any one individual to hold all the knowledge and answers to all questions. It was clear at the time of publication of our first book, The Stability and Shelf-life of Food (Woodhead Publishing, 2000) with its contributions from experts in the field that there was a great need for information that specifically related to shelf life. The continued interest in this book in the ten years since publication has suggested to us that there is an ongoing need for an expanded and updated reference book dedicated to discussing food stability issues and shelf life measurement, which can be used as a resource by all those needing help or requiring reassuring advice. With this aim in mind, we have brought together contributions from individual experts in their own fields both from academia and industry to produce in a single volume a comprehensive book covering deteriorative processes, shelf life measurement techniques and specific issues related to a wide range of products. The book is structured into three parts. Part I describes the various types of deteriorative processes that can limit the shelf life of products, including physiochemical aspects, insect contamination, processing, packaging and storage and distribution. Part II describes methods for shelf life evaluation, including sensory, instrumental and microbiological tests, accelerated testing and shelf life modelling procedures. Part III covers a combination of productrelated shelf life issues and case studies related to a wide range of product categories, including beer, wine, fruit juices, soft drinks, coffee, fruit and vegetables, bread and baked products, oils and fats, confectionery products, milk and milk products, seafood and vitamin-fortified products. Users of The Stability and Shelf-life of Food will consequently find not only updated versions of essential chapters from this publication, but a much wider overview of stability and shelf life issues, and covering a much wider range of product categories. We would like to thank all the contributors to the book, each one an expert in their own field. It is our hope that you will find the book to be a useful and lasting resource on shelf life evaluation. D Kilcast, Consultant P Subramaniam, Leatherhead Food Research

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1 Microbiological spoilage of foods and beverages G-J. E. Nychas and E. Panagou, Agricultural University of Athens, Greece

Abstract: Food spoilage may be defined as a process or change which renders a product undesirable or unacceptable for consumption. This complex ecological phenomenon is the outcome of the biochemical activity of microbial chemical processes which will eventually dominate according to the prevailing ecological determinants. To ensure the safety and quality of foods and beverages, the effective monitoring of the chill chain through production, transportation, distribution and storage in retail cabinets and home refrigerators is essential. Currently, a variety of different methodologies are used for assessing food spoilage, in which microbiological methods play a decisive role. Recently, the relationship between microbial growth and the chemical changes occurring during food storage has been recognised as a potential indicator which may be useful for monitoring freshness and safety. For this purpose, interesting analytical approaches have been developed for rapid and quantitative assessment of food spoilage. These are based on biosensors, sensor arrays and spectroscopy techniques in tandem with chemometrics. Various processes have been utilised to prevent the microbiological spoilage of foods and beverages, amongst which low temperature storage and heat treatment seem to be the most effective. The application of a rich carbon dioxide atmosphere as part of a modified atmosphere packaging system is also effective in suppressing spoilage microorganisms. Key words: chill chain, ephemeral spoilage organisms, metabolomics, microbial inhibition, modified atmosphere packaging, shelf life.

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1.1

Food and beverage stability and shelf life

Introduction

Despite the technological progress made in recent decades, changes in consumer lifestyles have made it necessary for the food industry to fulfil seemingly contradictory market demands. Consumers now expect food products of superior sensory quality and increased functional and nutritional properties, combined with a traditional, wholesome image and guaranteed safety. However, there is also a demand for less heavily preserved or processed foods, for fewer additives and technological interventions, as well as for increasingly competitive prices. At the same time, consumers expect an extended product shelf life (i.e. inhibition or control of spoilage which is mainly microbiological) and a high level of convenience in preparation and use. In a recent consumer survey, `fresh/not spoiled' and `quality' were the second and third most important criteria with 37% and 33%, respectively, while `price' was the most important purchase criterion for food (mentioned by 66% of respondents) (RoÈhr et al., 2005). This is a straightforward message as to the importance of the successful management of spoilage. To date, there are no food spoilage management systems per se, food spoilage control being linked with many other safety and hygiene systems, processes and practices, the majority of which are commonplace within the food industry.

1.2 Spoilage of foods and beverages; a microbiological approach: microbes vs indigenous enzymes It must be emphasised that the contribution of indigenous food enzymes to spoilage is negligible when compared to the activity of microbial flora. This is mainly the case in food of animal origin (e.g., meat, fish and dairy) (Nychas and Tassou, 1997; Tsigarida and Nychas, 2001). For example, in meat and fish, the post-mortem glycolysis, caused by indigenous enzymes, ceases after the death of the animal when the final pH reaches a value of 5.4±5.5. On the other hand, the indigenous proteolytic and lipolytic enzymes are not sufficient to affect food spoilage. However, these enzymes or other chemical or mechanical means are utilised in the artificial tenderising of meat (Nychas et al., 2007). As far as spoilage due to proteolysis is concerned, the soluble sarcoplasmic proteins probably form the initial substrate for proteolytic attack (Hasegawa et al., 1970a,b; Jay and Shelef, 1976). The proteolytic activity of bacterial action on meat and its impact on spoilage has been clearly demonstrated (Schmitt and Schmidt-Lorenz, 1992a,b; Nychas and Tassou, 1997). Proteolytic bacteria may gain an ecological advantage through penetration which gives them access to newly available resources (e.g., nutrients) which would not be accessible or available to non- or less proteolytic bacteria (Nychas et al., 2007). There is no doubt that microbiological activity is by far the most important factor influencing the changes which cause spoilage in a food system (Nychas et al., 1998). However, it is microbial activity (growth) per se, rather than the

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activity of microbial enzymes and the accumulation of metabolic by-products that identifies food spoilage (Braun and Sutherland, 2004). In the context of meat spoilage, therefore, it is important to include interactions between microbial growth and its respective enzymatic activity.

1.3 Factors affecting the rate of microbiological spoilage of foods and beverages Generally, food spoilage may be considered to be an ecological phenomenon which encompasses changes in the available nutrients (e.g., low molecular compounds) during proliferation of the bacteria which constitute microbial processes in the product regardless of its origin (e.g., animal or plant). The dominance of a particular microbial process on these products depends upon factors which persist during processing, transportation and storage. It is a wellestablished fact that any food ecosystem includes five categories of ecological determinants: intrinsic, processing, extrinsic, implicit and the emergent effect. These influence the establishment of particular microbial processes and determine the rate at which a maximum population is attained. This is known as `ephemeral/specific spoilage micro-organisms' (E(S)SO), i.e., those which are able to adopt various ecological strategies (Koutsoumanis and Nychas, 2000; Nychas et al., 2007). These ecological strategies, developed by the ESO, are the consequence of environmental determinants (e.g., stress, the limitation or availability of nutrients and oxygen) and allow them to proliferate in all available niches. In fact, all the determinants mentioned above constitute a virtual ecological niche (n-dimensional) in which an organism is influenced in (micro) space and time (Boddy and Wimpenny, 1992). This ecological approach is pertinent to the understanding of the changes that occur in products throughout the food chain, from farm to fork. In practice, scientists and technologists involved in food industries should attempt to control or modify some or all of the parameters (e.g., temperature) noted above in order to extend the shelf life of these products. In this chapter, emphasis will be placed on implicit (intrinsic biotic parameters) as well as extrinsic factors. 1.3.1 Implicit (intrinsic biotic parameters) factors Ephemeral spoilage organisms (ESO) Among the different types of spoilage, the microbial contributes greatly to the huge amount of food which is wasted and to the associated financial losses (Kantor et al., 1997). As mentioned above, a vast number of studies in food microbiology have established that spoilage can be attributed to a relatively small group of micro-organisms existing in the microbial processes within foods (for a review, see Nychas et al., 1998). This concept has contributed significantly to our understanding of food spoilage. Microbiological spoilage

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Food and beverage stability and shelf life

of foods and beverages is caused by a great variety of bacteria, moulds and yeasts. The latter group of micro-organisms, yeasts and moulds can affect a wide range of products which have low pH or water activity. Spoilage from moulds and yeasts is often manifested by their growth on the surface of products such as cheese and meat, as well as by fermentation of sugars in liquid and semi-liquid products. Products with a high sugar or salt content or with low pH, such as soft drinks, syrups, dips, salad dressings and olives, are frequently spoiled by species of Zygosaccharomyces and Torulaspora, Brettanomyces, Saccharomyces, Debaryomyces, Yarrowia and Rhodotorula (Table 1.1). Further to the information provided in the following chapters, Fleet (1992) has provided comprehensive lists of yeast species which have been isolated from various foods and beverages. In view of this diversity of taxa, the correct identification of species is often a challenge. Yeasts also contribute to spoilage in foods of animal origin (e.g., cheese, meat and fish), but this is mainly due to bacterial activity (Table 1.2). The most important factors determining the microbiological quality of foods are: · · · · ·

the the the the the

physiological state of an animal at slaughter, condition of fruits and vegetables at harvesting, spread of contamination during slaughter, processing of both animal and plant origin raw materials, and temperature and other conditions of storage and distribution.

In most raw or fresh foods, a consortium of bacteria, commonly dominated by Pseudomonas spp., is in most cases responsible for spoilage during aerobic storage of these products at different temperatures (ÿ1 to 25 ëC). It is now well established that under aerobic storage three species of Pseudomonas spp., namely P. fragi, P. fluorescens and P. lundensis, are the most important in producing slime and odours as the main signs of spoilage (Stanbridge and Davies, 1998). Cold-tolerant Enterobacteriaceae (e.g., Hafnia alvei, Serratia liquefaciens, Enterobacter agglomerans) also occur in chilled food storage. These bacteria have been found to contribute to spoilage in fresh vegetables, dairy products and foods of animal origin. Lactic acid bacteria have been detected in the aerobic spoilage flora of chilled meat, fish, dairy and freshly cut vegetable products (Holzapfel, 1998). Both lactic acid bacteria and B. thermosphacta are the main, if not the most important, cause of spoilage, which can be recognised as souring rather than putrefaction (Table 1.2). This type of spoilage is one of the two distinct situations that occur in meat and is commonly associated with vacuum or modified atmosphere packaging (MAP) and is the result of competition between facultatively anaerobic Gram-positive flora. The second situation is that of competition between different Gram-negative flora. The physiological attributes of the organisms in the latter case, under imposed ecological determinants, are reported in Nychas et al. (1998).

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Microbiological spoilage of foods and beverages Table 1.1

7

Yeasts and moulds in various commodities

Products

Micro-organisms

Fruit juices, fruit concentrates, drinks

Alicyclobacillus acidoterrestris, Saccharomyces cerevisiae, S. bayanus, S. pastorianus, S. kluyveri, S. unisporus, S. exiguous, Z. mellis, Z. rouxii, Lachancea cidri, L. fermentati, L. thermotolerans, Torulaspora delbrueckii, T. microellipsoides, Zygosaccharomyces bailii, Z. lentus Candida albicans, Penicillium expansum, Penicillium funiculosum, Saccharomyces cerevisiae, Mucor plumbeus

Apples, apple juice, apple cider Orange juice Soft drinks Alcoholic beverages (beer, wine and cider), wine, spirits, sweet and sparkling wines High sugar products, honey Products with low sugar and high salt Dried fruit Fruits and vegetables Strawberries, pears, citrus, potatoes, carrots, sweet potatoes, cassava, guavas, yams, kola nuts Vegetable salads, salad dressing, salad vegetable with mayonnaise, condiments, ranch dressing Black olives Bakery products, bread, British bread, sourdough bread Dairy products Butter, European cheeses, cheese, yogurts Meat products

Saccharomyces cerevisiae, Hanseniaspora uvarum Z. bailii, Lachancea fermentati, Torulaspora microellipsoides, Zygosaccharomyces bisporus, Z. kombuchaensis, Z. florentinus Saccharomyces cerevisiae, S. bayanus, P. brevicompactum, A. flavus, Torulaspora delbrueckii, Zygosaccharomyces bailii, Z. lentus, Z. rouxii Zygosaccharomyces bailii, Z. mellis, Z. rouxii, S. cerevisiae, Lachancea thermotolerans, Torulaspora delbrueckii Torulaspora delbrueckii, Zygosaccharomyces bisporus, Z. rouxii Lachancea thermotolerans, Torulaspora delbrueckii, Zygosaccharomyces bailii, Z. rouxii Moulds (Penicillium and Aspergillus) Rhizopus sexualis, Mucor pirifomis, Mucor racemosus, Mucor hiemalis, Mucor circinelloides, Cunninghamella elegans Z. bailii, S. exiguust, S. dairenensis, Z. lentus, Z. bisporus, Torulaspora delbrueckii, S. bayanus, S. unisporus Candida famata Penicillium roqueforti, Hansenula anomala, Pichia anomala (and Candida guilliermondii, C. parapsilosis, Saccharomyces cerevisiae), S. cerevisiae, S. exiguus, S. unisporus, S. bayanus, S. pastorianus S. cerevisiae, S. dairenensis, S. exiguus, S. kluyver, Rhodotorula, Cryptococcus, Candida, Penicillium commune, Mucor racemosus, Mucor circinelloides, Penicillium solitum, Mucor plumbeus, Torulopsis candida, Kluyveromyces fragilis, Mucor hiemalis S. cerevisiae, S. exiguus

Sources: Arias et al. (2002); Basaran et al. (2004); Dennis and Buhagiar (1980); Elez-MartõÂnez et al. (2005); Filtenborg et al. (1996); Fleet (2006); Fleet and Mian (1987); Gouws et al. (2005); Hocking and Faedo (1992); ICMSF (1998); King and Mabbitt (1982); Kurtzman (1990); Kurtzman and Fell (1998), Kurtzman et al. (1971, 2001); Legan and Voysey (1991); Lund et al. (1995); Magan and Aldred (2006); Panagou (2006); Pitt and Hocking (1997); Rankine and Pilone (1973); Rodrigo et al. (2001); Sampedro et al. (2007); Sand and van Grinsven (1976); Spicher (1980); Steels et al. (1999); Suriyarachchi and Fleet (1981); Thomas (1993); Tran and Farid (2004); Van der Horst (2001); Waite et al. (2009) and Wiley (1994).

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Table 1.2

Microbial association in foods

Products

Conditions

Micro-organisms

Fish

Aerobic storage, 0±4 ëC

Shewanella putrefaciens, Pseudomonas spp. Brochothrix thermosphacta B. thermosphacta, S. putrefaciens Photobacterium phosphoreum, lactic acid bacteria B. thermosphacta, lactic acid bacteria Pseudomonas spp. Leuconostoc gasicomitatum Lactobacillus sakei, Brochothrix thermosphacta, Photobacterium phosphoreum, Aeromonas spp., Serratia spp. Lactobacillus alimentarius

MAP, chill storage >50% CO2 and O2, 0±4 ëC 50% CO2, 0±4 ëC <50% CO2 and O2, 0±4 ëC 100% CO2, 0±4 ëC Vacuum packed, 0±4 ëC Pickled fish Cold-smoked salmon

NaCl > 6.0%, addition of sorbate and/or benzoate, pH < 5.0 Cold-smoked fish, vacuum packed under low NaCl and light acidification Iced fish, high pH Shrimp, brined Milk

Raw Raw, refrigerated Pasteurised Bulk tank sampling From mastitis infected animal

Cream

Pasteurised

Lactobacillus spp., Carnobacterium spp., Photobacterium phosphoreum, psychrotrophic Enterobacteriaceae Shewanella putrefaciens-like organisms Lactic acid bacteria Streptococcus spp., P. fluorescens, P. putida, P. fragi, P. aeruginosa, Staphylococcus spp., Micrococcus spp. Bacillus spp., Paenibacillus spp. B. cereus, B. circulans, B. mycoides, B. licheniformis Streptococcus uberis Streptococcus agalactiae, S. uberis, S. aphaureus Alcaligenes spp., Acinetobacter spp., Aeromonas spp., Enterobacteriaceae

Butter and reduced fat dairy spreads

P. fragi, P. putrefaciens

Dairy products

P. fragi, P. fluorescens, P. hundensis

Cheese

Brine salted, hard and semihard Hard cheese Cheese rind

Clostridium tyrobutyricum, Clostridium spp. P. aeruginosa

Lettuce and ready-to-eat vegetables

Minimally processed

Pseudomonas fluorescens, Pantoea agglomerans, Rahnella aquatilis

Meat and poultry

Aerobic, chill storage

Pseudomonas spp., P. fragi, P. fluorescens, Lactobacillus sakei

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Microbiological spoilage of foods and beverages Table 1.2 Products

Continued Conditions

Micro-organisms

Vacuum/MAP packed

Lactic acid bacteria, Enterobacteriaceae, Hafnia alvei, Lactobacillus sakei, L. curvatus Pseudomonas spp., Brochothrix thermosphacta, but also Lactobacillus sakei, L. curvatus, Leuconostoc mesenteroides, Hafnia alvei, Enterobacter amnogenus Clostridium esterteticum, C. algidicarnis Clostridium gasigenes, Cl. Algidixylanolyticum Pseudomonas fragi, P. lundensis, P. fluorescens biovars A, B, C, P. lundensis-like and P. fluorescenslike bacteria Serratia liquefaciens, Hafnia alvei Shewanella putrefaciens, Bro. thermosphacta Clostridium algidicarnis Shewanella putrefaciens Acinetobacter johnsonii, A. lowfii

Beef, aerobic storage, 5 ëC

Beef and pork, vacuum packed Lamb, raw Poultry carcasses

DFD meat, vacuum/high O2/ MAP packed Pork, vacuum packed Fresh meat, high pH Fresh meat and poultry Meat products

Cooked, vacuum packed Modified atmosphere packaging Sliced ham and turkey breast fillets, vacuum packed Blood sausage (Morcilla de Burgos), vacuum/MAP packed

Lactobacillus sakei, Leuconostoc citreum Leuconostoc gasicomitatum, Lactobacillus oligofermentans Leuconostoc mesenteroides subsp. mesentaroides Lactic acid bacteria especially Leuconostoc mesenteroides

Fruit juice

Pasteurised

Alicyclobacillus acideoterrestris

Sous vide products

Mild heat treatment

Spore forming bacteria (Clostridium spp., Bacillus spp.)

Table olives Anchory stuffed

Lactobacillus brevis

Vegetable sausage

Leuconostoc gasicomitatum

Soda bread

9

Partially baked

Bacillus subtilis, B. pumilus, B. licheniformis

Sources: Ben Embarek (1994); BjoÈrkroth et al. (2000); Borch et al. (1996); Bramley et al. (1984); Brocklehurst et al. (1987); Broda et al. (1999, 2000a,b); Chai et al. (1968); Champagne et al. (1994); Chenoll et al. (2007); Cogan and Beresford (2002); Cousin (1982); Dainty and Mackey (1992); Dalgaard (2000); Dalgaard et al. (1993); Deeth et al. (2002); Drosinos and Nychas (1996); Gardner (1981); Gill and Newton (1979); Gram and Huss (1996, 2000); Harmon et al. (1987); Jùrgensen et al. (2000); Kalchayanand et al. (1993); Korkeala et al. (1988); Lafarge et al. (2004); Lahellec and Colin (1979); Legan (1993); Leroi et al. (1998); Lyhs et al. (2004); McMeekin (1977); Meer et al. (1991); Muir (1996); Nguyen-the and Carlin (1994); Ogunnariwo and Hamilton-Miller (1975); Samelis et al. (1998); Santos et al. (2005); Shaw and Latty (1988); Shay and Egan (1981); Stohr et al. (2001); Sundheim et al. (1998); Sutherland et al. (1975); Tekinsen and Rothwell (1974); Torriani et al. (1996); Truelstrup Hansen et al. (1995); Tsigarida and Nychas (2001); Walker and Stringer (1990) and Walls and Chuyate (2000).

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In general, the metabolic activity of the ephemeral microbial processes which prevail in a food ecosystem under certain aerobic conditions, or are generally introduced during processing, leads to changes or spoilage in the food. These changes or spoilage are related to (i) the type, composition and population of the microbial process, and (ii) the type and availability of the energy substrates in meat. The type and extent of spoilage are governed by the availability of low molecular weight compounds (e.g. glucose, lactate) which exist in meat (Nychas et al., 1998). By the end of this phase, changes and subsequent overt spoilage are due to the catabolism of nitrogenous compounds and amino acids as well as to secondary metabolic reactions. 1.3.2 Extrinsic factors Effect of temperature Temperature seems to be a major factor in influencing spoilage as well as the safety of foods (Nychas et al., 2008). Modern lifestyles, and the development of consumer requirements during the past decade, have led to a significant increase in demand for fresh, high quality food products. The mass consumption of fresh food products of both animal and plant origin, as well as new consumer trends such as reduced cooking times for minimal quality loss, and microwave cooking, have accentuated the need for the constant and systematic control of temperature handling of these products throughout the chill chain from production (slaughterhouse, field) to consumption. Several studies have recently been carried out to assess the importance of handling highly perishable food products at low temperatures. Additionally, emphasis has been placed on the effect which temperature fluctuations or temperature abuses during handling will have on product quality (Koutsoumanis and Taoukis, 2005; Koutsoumanis et al., 2006; McMeekin et al., 2006). Thus an important aspect of the distribution and consumption of food, whether fresh or raw, is the effective monitoring of time/temperature conditions which affect both safety and overall quality (spoilage). It is generally recognised by the European industry, retailers, food authorities and consumers, that there are stages in the chill chain, such as transfer points or storage rooms, which are likely to be the weakest link in the management of chilled or perishable food. All food products, unless appropriately packaged, transported and stored, will spoil in a relatively short time. Food chill chain The chill chain, especially of animal (e.g., fish and meat) and plant origin foods includes two main steps: the primary and secondary chilling. Both steps are important for microbiological stability, eating quality and production yield (Koutsoumanis and Taoukis, 2005). Primary chilling is the process of cooling food, e.g. meat carcasses after slaughter from body to refrigeration temperatures (ca. 3 ëC). During primary chilling, the rapid growth of both pathogenic and spoilage micro-organisms may

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occur. The rapid reduction of temperature on the food surface can prevent microbial growth and extend the shelf life of a product. It is clear that rapid chilling offers a number of other advantages in product quality and production economics. After primary chilling, any subsequent procedures, such as handling, cutting and mincing, etc., will increase food temperature, therefore secondary chilling is necessary to reduce temperature below 7 ëC. Secondary chilling is also of great importance in pre-cooked food products (e.g., meat, fish, vegetables). Different technologies used to chill food products before transportation are: (i) air chilling, (ii) immersion chilling, (iii) spray chilling, and (iv) vacuum cooling. The effectiveness of air chilling applications depends on a number of factors including air temperature and velocity, relative humidity, the weight and fat cover of the products, as well as product loading. Immersion chilling is probably the least expensive method and provides very rapid cooling with no risk of freezing. Spray chilling is an alternative method to immersion chilling which has been increasingly used, especially in the USA, for meat and meat products (Allen et al., 1987; Johnson et al., 1988). It is based on a combination of sprays and air during the initial stage of the chilling cycle, and the use of air alone in the remainder of the chilling period. Finally, vacuum cooling is a rapid batch process in which moist products (e.g., meat and bakery products, fruits and vegetables) containing free water are cooled by the evaporation of moisture in a vacuum (Mellor, 1980). Rapid cooling in a vacuum has the advantage of significantly reducing the count of phychrophile and mesophile bacteria, even after several days storage (McDonald et al., 2000). Transportation During the meat marketing (transportation) route to the final user for preparation and consumption, food products are stored in tracks, retail cabinets and home refrigerators. These points are of great concern regarding quality and safety. Industrial and track chambers differ in characteristics and performance (Koutsoumanis and Taoukis, 2005). The size of cabinets, initial temperature of the incoming food (which depends on the type of food), targeted storage temperature, temperature of the surroundings, mechanical characteristics (location of refrigeration machinery, compressors, ventilation and insulation) and energy/cost factors are all issues of the greatest importance when considering cold storage requirements. The management approach dominating most food markets is the principle of `first in±first out'. This approach is strictly adhered to in all stages of the chill chain, primarily (but not always) through properly designed handling procedures in the chill storage rooms. The different points of transportation, from cold storage to retail outlets, and then to the consumer's refrigerator, are critical for the product's overall quality and safety. The transporting vehicle must be supplied with a good refrigeration system, and another weak point in distribution is the transportation period from the product purchase to the consumer's refrigerator.

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Food and beverage stability and shelf life

1.4 Evaluating, monitoring and measuring microbiological spoilage of foods and beverages So far, a great number of different methodologies, e.g. microbiological, physical and biochemical, have been applied to evaluate food spoilage (Jay, 2000). Among these, microbiological methods have been used almost exclusively in the actual evaluation of spoilage (European Commission, 2005). Initially for the enumeration of microbial populations, the actual number of colonies grown on a Petri dish has played a critical role in the evaluation of food spoilage. Recently this evaluation has been based on existing knowledge of the microbial process which contributes to spoilage in genus (specific spoilage) or species (ephemeral spoilage) level (Nychas et al., 2008; Tassou and Boziaris, 2002; Ercolini et al., 2008). The idea of seeking correlation(s) between microbial growth and the (bio)chemical changes which occur during spoilage has been recognised throughout as a means of revealing specific substrates and/or end products which may be useful for assessing food quality (Jay, 1986; Dainty, 1996; Nychas et al., 1998; Ellis et al., 2002). The ideal indicator (microbial metabolite) should meet, among others, the following criteria (Jay, 1986): the compound (i) should be absent or at least occur at low levels in meat, (ii) should increase with storage time, and (iii) should be produced by the dominant flora and have a good correlation with organoleptic assessment. During the last two decades, numerous attempts have been made to associate certain metabolites with the microbial spoilage of various muscle and vegetable origin foods, and yet there is not a single one available to quantify spoilage/ quality of specific products. There are many reasons for this: for example, (i) the proposed methods are so slow that they give retrospective information and hence cannot be used for on- or at-line monitoring, and (ii) changes in the technology of preservation (e.g., vacuum, modified atmospheres, etc.), are quite likely to affect the application of the chosen methodology. Thus it is evident that the identification of the ideal metabolite for spoilage assessment is a difficult task for the following reasons: (a) most metabolites are specific to certain organisms (e.g. gluconate to pseudomonads) and when these organisms are not present or are inhibited by the food ecology, whether natural or man-made, incorrect spoilage information results; (b) metabolites are the result of the consumption of a specific substrate, but the absence of the given substrate or its presence in low quantities does not preclude spoilage; (c) the rate of microbial metabolite production and the metabolic pathways of these bacteria are affected by the imposed environmental conditions (e.g., pH, oxygen tension, temperature, etc.); (d) the accurate detection and measurement requires sophisticated procedures, highly educated personnel, time and equipment; and (e) many of them provide retrospective information which is not satisfactory.

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However, it could be stipulated that regardless of the methodology employed for the quantitative evaluation of spoilage, an understanding of where specific metabolites (metabolomics) originate (i.e., responsible organism, substrate), how they are regulated in cell levels (genomics ± proteomics), what is the effect on food characteristics as well as the microbial association on the rate and type of metabolite formation, it is essential to know when and how to exploit them for the benefit of the industry, authorities and consumer. In general, food industries need rapid analytical methods or tools for quantifying these indicators to determine the processing which will be suitable for their raw material and for predicting the remaining shelf life of their products. Inspection authorities need reliable methods for control purposes. Retailers and wholesalers need valid methods to ensure the freshness and safety of their products as well as for the settling of disputes between buyers and sellers. Reliable indicators of the safety and quality status of food from retail to consumption are desirable. It is therefore crucial to have valid methods to monitor freshness and safety so as to ensure what quality is, regardless of whose perspective you take, i.e. that of the consumer, the industry, the inspection authority, or the scientist. Recently, some interesting analytical approaches have been put forward for the rapid and quantitative monitoring of meat spoilage. These include: biosensors (enzymatic reactor systems), electronic noses (array of sensors), Fourier transform infra-red spectroscopy (FT-IR), integration of the FT-MIR Attenuated Total Reflectance bio-sensors or other bio-sensors in tandem with an information platform and development of an `expert system' to automatically classify the sensory input into a `diagnosis' based on extracted pre-processing features. However, the enormous amount of information provided by the last mentioned technology makes the data produced unmanageable. The application of advanced statistical methods (discriminant function analysis, clustering algorithms, chemo-metrics) and intelligent methodologies (neural networks, fuzzy logic, evolutionary algorithms and genetic programming) may be used as qualitative rather than quantitative indices since their primary aim is to distinguish objects, groups or populations (Goodacre et al., 2004). This is an unsupervised learning method (Ellis and Goodacre, 2001). Nowadays, modern machine learning procedures are based on supervised learning algorithms (Beavis et al., 2000; Goodacre, 2000; Shaw et al., 1999). The last mentioned approach, together with the development of artificial neural networks (ANN), could soon be used for evaluation of food spoilage. However, the quest of the food industry and of food scientists is for techniques and/or instruments that will either rapidly predict or detect microbial spoilage and will therefore eliminate traditional time-consuming and retrospective microbiological methods. Recently, the ability to use mathematical models which describe spoilage has been advanced by developing and validating models which quantitatively estimate the growth of these ephemeral organisms and are consequently able to predict the shelf life of various foods (Devlieghere et al., 2001; Koutsoumanis et al., 2006). However, the food environment can be

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very complex and it may be difficult to quantify or even categorise some of its features and their potential effects on microbial population dynamics or the ability to recover a target organism from a particular food. For example, food structure (e.g., gels, mayonnaise-based products, drinks, fruit juices), may affect the environmental limits for growth (Koutsoumanis et al., 2004).

1.5 Predicting microbiological spoilage of foods and beverages The perception of spoilage in foods is rather subjective partly because of the lack of general agreement on the early signs of incipient spoilage for every product and partly because of the changes in the technology of food preservation (e.g., vacuum, modified atmospheres, etc.) which makes objective evaluation a difficult task. Shelf life, an indirect measurement of spoilage, may be quantitatively predicted using mathematical models. In the last decade, a significant number of mathematical models for the growth of various spoilage bacteria such as Photobacterium phosphoreum (Dalgaard, 1995; Dalgaard et al., 1997), pseudomonads (Ratkowsky et al., 1982; 1983; Neumeyer et al., 1997; Pin and Baranyi, 1998; Koutsoumanis et al., 2000; Koutsoumanis, 2001), Shewanella putrefaciens (Dalgaard, 1995; Koutsoumanis et al., 2000) and Brochothrix thermosphacta (McClure et al., 1993; Koutsoumanis et al., 2000) have been published. However, despite this progress, predictive spoilage models remain a research tool rather than an effective industrial application (McDonald and Sun, 1999). The reasons for this include: · The lack of information required for the application of models which predict the shelf life of foods (e.g. SSO, spoilage domain, spoilage level); · The development of most models is based on observations in a well-controlled laboratory environment, using microbiological media. Predictions based on such models are not necessarily valid in complex food environments, such as meat, as significant factors for microbial growth in food structure (Robins and Wilson, 1994; Pin et al., 1999; Wilson et al., 2002), and interactions between micro-organisms (Gram and Melchiorsen, 1996; Pin et al., 1999) are not taken into account. As a result, validation of the models in food products often shows a low level of accuracy which limits their application. · The majority of developed models have focused on the effect of environmental factors on the maximum specific growth rate of a micro-organism without taking into account the lag phase. It has been shown, however, that the lag phase duration of the SSO can be a significant part of the total shelf life of foods (Koutsoumanis and Nychas, 2000; Koutsoumanis, 2001). Ignoring the lag phase may lead to an underestimation of shelf life, with significant economic losses for the food industry. · Most models are developed and validated under static temperature conditions. In practice, however, temperature fluctuations are often encountered

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during the storage and distribution of foods. Thus, validation under changing temperatures is of great importance for evaluating the performance of the model in predicting shelf life under real chill chain conditions. Predictive, or alternatively quantitative, food microbiology (McMeekin et al., 1997) involves knowledge of microbial growth responses to environmental factors expressed in quantitative terms through mathematical equations (models). Data and models can be stored in databases and used to interpret the effect of processing, distribution and storage conditions on microbial growth (McMeekin et al., 1997). This approach offers precision in estimating the shelf life of foods. In addition, the combination of data on the environmental history of the product with the mathematical models may lead to `intelligent' product management systems for the optimisation of food quality and safety at the time of consumption (Koutsoumanis et al., 2002; 2003; Giannakourou et al., 2001). Finally, to facilitate the implementation of Hazard Analysis Critical Control Point (HACCP) systems in the meat industry, recent attempts have been made to evaluate the risk in the consumption of meat and meat products contaminated with pathogens, especially E. coli O157:H7 (http://www.fsis.usda.gov/OPHS/ ecolrisk/home.htm) and L. monocytogenes. According to existing literature data on meat (specifically ground beef), risk assessments have been conducted for E. coli O157:H7 on hamburgers. These risk assessments aimed either to identify data gaps in evaluating the risk of illness by consumption of contaminated and improperly cooked hamburgers (Marks et al., 1998), or to model the exposure of consumers to this pathogen from farm to fork (Cassin et al., 1998).

1.6 Preventing microbiological spoilage of foods and beverages Various processes and methods have been applied to prevent the microbiological spoilage of foods and beverages. In fact, food preservation may be defined as the process of treating and handling food in such a way as to stop, control or greatly slow down spoilage, and of course, to minimise the possibility of food-borne illness whilst maintaining the optimum nutritional value, texture and flavour. To be effective, preservation must be equal to, or greater than, the microbial `challenge' which the food product presents. 1.6.1 Application of temperature Temperature is the main method used in the food industry for the prevention of spoilage. Low temperature Food products are generally divided into three main categories depending on storage conditions:

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· Frozen foods. These are often stored at ÿ18 ëC and have a shelf life of six months to two years. At these low temperatures (frozen foods), the growth of micro-organisms is not supported (although they may survive) and therefore the shelf life will not be limited by microbial activity. Deterioration of foods may be due to enzymatic reactions and these are also slowed down at low temperatures. The shelf life is likely to be limited by textural changes such as the formation of ice crystals, by moisture loss or by biochemical changes such as rancidity. · Chilled foods. These are generally stored at temperatures below 8 ëC and typically have a shelf life of one to six weeks, depending on the characteristics of the food product. Storage at chill temperatures will reduce the growth rates of micro-organisms but many spoilage organisms and/or pathogenic bacteria are able to grow at refrigeration temperatures. Additional factors (low pH, water activity, etc.) may be applied to control the activity of these organisms. · Ambient stable foods. These will be subjected to a suitable heat treatment, which is intended to target and destroy micro-organisms in the product. Few products (e.g., fermented, acid foods, etc.) will be sufficiently inhibitory in terms of pH, water activity or preservative level to prevent the growth of micro-organisms likely to survive the heating process. These products will typically have a shelf life of six months to two years. Heat treatment With the exception of raw products, most foods will be subjected to some heat process during manufacture. There are three main categories of heat treatment used to stabilise foods. · Pasteurisation to inactivate vegetative micro-organisms. Typically a process of 70 ëC/2 min or equivalent (z value of 7.5 ëC). The decimal reduction time (D) value is the time required at a given temperature for the surviving population to be reduced by one log cycle or 90%. The z value is the number of degrees Celsius which will result in a 10-fold change in the D value given to chilled food products. With this process, a six-log reduction (6D) in Listeria monocytogenes and other vegetative pathogens can be achieved. It is also sufficient to inactivate most spoilage bacteria such as Enterobacteriaceae, Pseudomonas spp., lactic acid bacteria and yeasts. · Pasteurisation to inactivate psychrotrophic or acid tolerant spore-formers. A process of 90 ëC/10 min or equivalent (z value of 9 ëC) is also applied to chilled food products that are vacuum packed or modified atmosphere packed and which have a shelf life of more than 10 days. With this process, the inactivation of vegetative spoilage bacteria can be achieved in parallel with a six log reduction of psychrotrophic strains of Clostridium botulinum. A process of 95 ëC/5 min or 95 ëC/10 min or equivalent (z value of 8.3 ëC) is applied to acidic ambient stable products. It is designed to inactivate acid-tolerant spore-formers that could grow and spoil the product if they remain present after heat treatment, i.e., Clostridium butyricum, Bacillus polymyxa, etc.

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· Sterilisation to achieve commercial sterility in canned goods. A process equivalent to 3 min at 121.1 ëC (Fo = 3) based on a z value of 10 ëC is used to achieve a 12-log reduction of mesophilic C. botulinum. It will also inactivate all vegetative micro-organisms and the majority of spore-forming organisms.

1.6.2 Application of carbon dioxide The addition of carbon dioxide has been used to control or inhibit the growth of spoilage micro-organisms in many raw, fresh and treated food products (e.g., pasteurised milk, olives, sausages, cottage, yoghurt and cottage cheese; Chen and Hotchkiss, 1991; Loss and Hotchkiss, 2002; Daniles et al., 1985; Roberts and Torrey, 1988; Nychas and Skandamis, 2005). The packaging system in which combinations of carbon dioxide, nitrogen, oxygen and other harmless gases are introduced within a high barrier film, is called `modified atmosphere packaging' (MAP), and can extend the shelf life and sustain the visual appearance of refrigerated food products. Trace gases such as carbon monoxide, nitrous oxide and sulphur dioxide have also been used. Carbon dioxide may be used in combination with refrigeration, pasteurisation and high barrier packaging to further extend the shelf life of processed milk products without a negative affect on quality (Loss and Hotchkiss, 2002). Much work has focused on the prevention of spoilage in animal origin muscle foods when compared with fruit and vegetables. However, in both types of products, the target organisms were pseudomonads (Nguyen-the and Carlin, 1994; Garcia-Lopez et al., 1998; Holzapfel, 1998; Francis et al., 2011). For example, in refrigerated raw milk, the addition of carbon dioxide may be a valuable technique for controlling the growth of psychrotrophic microflora (e.g. coliforms and pseudomonads) and for reducing the occurrence of heat-resistant microbial proteinases and lipases which diminish the sensory quality of the processed product (King and Mabbitt, 1982; Ruas-Madiedo et al., 1998; Espie and Madden, 1997). However, concerns have been expressed by regulatory authorities (Gill, 1988), food industry groups (Anon., 1988) and others, that this practice may represent an undue safety hazard. Indeed, despite the increasing commercial interest in the use of MAP to extend the shelf life of many perishable products such as meat and poultry, concern about the potential growth of pathogenic bacteria able to survive and grow even at refrigeration temperatures (Silliker and Wolfe, 1980; Palumbo, 1987) remains the limiting factor to further expansion of the method. This is also the case with dairy products (Hotchkiss et al., 1999; Werner and Hotchkiss, 2002).

1.7

Future trends

The introduction of converging technologies in the food industry is among the priorities of the 7th Framework Programme, which is expected to predominate

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in the future, resulting in substantial changes in the manner in which research is designed. This can be achieved through the integration of modern analytical and high throughput platforms with computational and chemo-metric techniques. Multivariate statistical analyses (e.g., partial least squares regression, discriminant function analysis, cluster analysis) and intelligent methodologies (e.g., artificial neural networks), contribute to the development of a decision support system for prompt determination of the safety and quality of meat products. They may also prevent unnecessary economic losses. Furthermore, the development of computational research platforms and online experimental databases such as ComBase (Baranyi and Tamplin, 2004) and Sym'Previus (Leporq et al., 2005), provide research scientists with a fast and efficient means of storing and exchanging knowledge, whatever their geographic location. The partial least squares analysis (PLS) and artificial neural networks (ANNs) are widely employed modelling approaches due to their ability to relate the input and output variables without pre-knowledge of the system under study, provided that an accurate and adequate amount of data on the system variables is available (Singh et al., 2009). When compared to other areas, the application of ANNs in the field of food science is still in the early development stage (Huang et al., 2007). Nevertheless, interest in using ANNs in food microbiology is increasing as promising results have been produced in several applications, such as growth parameter estimation of micro-organisms (Geeraerd et al., 1998; HervaÂs et al., 2001), bacterial heat resistance (Lou and Nakai, 2001; Esnoz et al., 2006), production of metabolites and simulation of survival curves (Palanichamy et al., 2008; Panagou, 2008). With regard to food safety, the management of food spoilage needs to be applied throughout the supply chain (from `farm to fork' and from `plough to plate'). It must also be implemented during the transition from food product development to manufacture (from `concept to consumer'). A quality assurancebased approach to identifying and controlling relevant spoilage hazards can be integrated with that for safety hazards. The use of a `stable by design' approach and implementation by means of HACCP principles, together with all the associated prerequisite programmes (PRPs), can also be harnessed to help in the management of food spoilage. Food spoilage is part of a continuum involving the identification of potential microbial, chemical and physical hazards, followed by their control to prevent a spectrum of consequences ranging from product spoilage to consumer illness, injury or even death. Consequently, food spoilage should be managed using an integrated approach, but in the context of this book, the focus of this chapter has been on microbial spoilage hazards and their control.

1.8

Sources of further information and advice

Several predictive models for spoilage micro-organisms and food-borne pathogens are available through the internet. Some useful sites include the following.

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· The Seafood Spoilage Predictor (SSP) program (provided in many languages), available at http://sssp.dtuaqua.dk/ contains predictive models for spoilage of fresh fish (Dalgaard, 1995; Gram and Dalgaard, 2002). · The Food Spoilage Predictor (FSP), which includes the Pseudomonas model of Neumeyer et al. (1997), can be found at http://www.hdl.com.au/ html.body_fsp.htm. · The Pathogen Modelling Program (PMP), for growth predictions for foodborne pathogens is available through a link at http://www.ars.usda.gov/ Services/docs.htm?docid=11550. · The basic free web-based database of food microbiology data is ComBase: www.combase.cc. The ComBase Initiative is a collaboration between the Food Standards Agency and the Institute of Food Research in the United Kingdom; the USDA Agricultural Research Service and its Eastern Regional Research Center in the United States; and the Food Safety Centre in Australia. Moreover, the growth predictor (GP), provided from the UK is available at www.ifr.ac.uk/safety/growthPredictor and the DMfit Program, which matches growth data by linear and non-linear regression with the curve of Baranyi et al. (1993) is accessible through the website of the UK Institute of Food Research at www.ifr.bbsrc.ac.uk. · Many EU-funded projects deal with predictive modelling: ± FAIR CT98-4083 project (accessible in the future through the website of London Metropolitan University (www.londonmet.ac.uk)) ± SMAS (http://smas.chemeng.ntua.gr/start.php?module=overview) ± SYMBIOSIS-EU (www.symbiosis-eu.net).

1.9

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subsp. Melibiosus subsp. nov. and Lactobacillus sake subsp. sake subsp. nov. and Lactobacillus sake subsp. carnosus subsp. nov., new subspecies of Lactobacillus curvatus Abo-Elnaga and Kandler 1965 and Lactobacillus sake Katagiri, Kitahara, and Fukami 1934 (Klein et al. 1996, emended descriptions), respectively', Int J Syst Bacteriol, 46, 1158±1163. TRAN M T T and FARID M (2004), `Ultraviolet treatment of orange juice', Innov Food Sci Emerg Technol, 5, 495±502. TRUELSTRUP HANSEN L, GILL T and HUSS H H (1995), `Effects of salt and storage temperature on chemical, microbiological and sensory changes in cold-smoked salmon', Food Res Int, 28, 123±130. TSIGARIDA E and NYCHAS G-J E (2001), `Ecophysiological attributes of a Lactobacillus sp. and a Pseudomonas sp. on sterile beef fillets in relation to storage temperature and film permeability', J Appl Microb, 90, 696±705. VAN DER HORST H C (2001), `Membrane processing', in Tamime A Y and Law B A, Mechanisation and Automation in Dairy Technology, Boca Raton, FL, CRC Press, 296±317. WAITE J G, JONES J M and YOUSEF A E (2009), `Isolation and identification of spoilage micro-organisms using food-based media combined with rDNA sequencing: ranch dressing as a model food', Food Microbiol, 26, 235±239. WALKER S J and STRINGER M F (1990), `Microbiology of chilled foods', in Comley T R, Chilled Foods: The State of the Art, Barking, Elsevier, 269±304. WALLS I and CHUYATE R (2000), `Spoilage of fruit juices by Alicyclobacillus acideoterrestris', Food Aust, 52, 286±288. WERNER B G and HOTCHKISS J H (2002), `Effect of carbon dioxide on the growth of Bacillus cereus spores in milk during storage', J Dairy Sci, 85, 15±18. WILEY R C (1994), `Introduction to minimally processed refrigerated fruits and vegetables', in Wiley R C, Minimally Processed Refrigerated Fruits and Vegetables, New York, Chapman & Hall, 1±27. WILSON P D G, BROCKLEHURST T F, ARINO S, THUAULT D, JAKOBSEN M, LANGE M, et al. (2002), `Modelling microbial growth in structured foods: towards a unique approach', Int J Food Microbiol, 73, 275±289.

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2 Chemical deterioration and physical instability of foods and beverages F. Kong and R. P. Singh, University of California, Davis, USA

Abstract: Food deterioration and spoilage during storage and distribution are a result of a variety of chemical, biochemical, and/or physical changes. These changes are often the result of product composition, environmental factors, and processing conditions. A variety of measures are available to a food technologist to obviate the deteriorative effects of extended storage on food quality. This chapter gives an overview of these chemical and physical reactions. Intrinsic and extrinsic factors affecting these reactions are summarized. Methods to measure and model these changes are discussed. Key words: chemical deterioration, physical instability, shelf life, quality evaluation.

2.1

Introduction

The quality of a food changes over time, which impacts its shelf life. Many deterioration and spoilage problems of foods are related to chemical, biochemical, and/or physical changes, such as lipid oxidation, enzymatic and non-enzymatic browning, and moisture absorption/loss. These reactions change the overall food appearance, texture, and flavor/aroma, and cause loss of nutrients such as vitamins. Some of the commonly observed deteriorative changes include offodors and rancidity developed in fatty foods, browning and darkening of meat and fruit juices, bread staling, and color fading and texture softening in fruits and vegetables (Singh and Anderson, 2004; Yang, 1998; Roos, 2001). These reactions are strongly affected by environmental conditions such as oxygen availability,

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temperature, relative humidity, as well as food composition including water content, pH, and ingredients. The quality changes can be evaluated by sensory panels, and more frequently, by using instruments, which are more cost effective and have better reproducibility. Good correlation between sensory and instrument methods can be achieved with careful selection of the instrument methods. Approaches to minimize deterioration of foods and extend shelf life include modification of formulation, processing, packaging, and storage conditions. However, foods are unstable in the thermodynamic sense, and tend to change from a low entropy, high enthalpy state to a high entropy, low enthalpy state (van Boekel, 2008). Therefore, the deterioration can slow down but will never stop. The ability to predict the deterioration rates is critical for food processors to estimate the shelf life of food under various storage conditions. Kinetic modeling is an important tool for predicting the changes in food quality. It involves the use of chemical kinetics to study the rates and mechanisms, and the Arrhenius relationship to describe the influence of temperature on the reaction rate constants (van Boekel, 2008; Kong and Chang, 2009). This chapter gives an overview of the chemical and physical reactions that cause quality loss in foods during storage thus limiting their shelf life. Intrinsic and extrinsic factors affecting these reactions are summarized. Methods to measure and model these changes are presented. More details on these topics are reviewed extensively in other articles (Singh and Anderson, 2004; Singh and Cadwallader, 2004). They are also described in other chapters in this book.

2.2 Chemical deterioration and physical instability of foods and beverages A series of chemical and physical changes can occur in foods during storage. Major chemical deterioration of foods include lipid oxidation and hydrolysis that cause rancidity and off-flavor, enzymatic degradation leading to color and texture changes, non-enzymatic browning, light-induced reactions that catalyze lipid oxidation, and protein hydrolysis and oxidation. Some of the common physical changes include mechanical damage of fruits and vegetables during harvesting and post-harvest handling, moisture migration that changes food texture and other physical properties, crystal growth due to temperature fluctuation in frozen stored food products, and viscosity changes and phase separation in emulsion systems such as mayonnaise. These changes can occur simultaneously in food systems, affecting color, flavor, aroma, and/or texture of the food product, leading to reduced shelf life of foods. Table 2.1 presents an overview of some major reactions and their influence on food quality. 2.2.1 Chemical deterioration Lipid oxidation Lipids are the least stable macro-constituents in foods. Oxidative rancidity is one of the major issues affecting the shelf life of fatty foods, especially those

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Table 2.1 Overview of reactions in foods affecting quality (adapted from van Boekel, 2008) Example

Type of reaction

Consequences

Non-enzymatic browning

Chemical reaction (Maillard reaction)

Color, taste and aroma, nutritive value, formation of toxicologically suspect compounds (acrylamide)

Fat oxidation

Chemical reaction

Loss of essential fatty acids, rancid flavor, formation of toxicologically suspect compounds

Fat oxidation

Biochemical reaction (lipoxygenase)

Off-flavors, mainly due to formation of aldehydes and ketones

Hydrolysis

Chemical reaction

Changes in flavor, vitamin content

Lipolysis

Biochemical reaction (lipase)

Formation of free fatty acids, rancid taste

Proteolysis

Biochemical reaction (proteases)

Formation of amino acids and peptides, bitter taste, flavor compounds, changes in texture

Enzymatic browning

Biochemical reaction of polyphenols

Browning

Separation

Physical reaction

Sedimentation, creaming

Gelation

Combination of chemical and physical reaction

Gel formation, texture changes

containing fatty acids with high levels of unsaturation. The susceptible food products include meats, seafood, fried foods, nuts, mayonnaise, and margarine. Other products include biscuits, cookies, ice cream powder, dried whole milk, dried fruits, milk powder, and coffee (Yang, 1998). Meat, poultry, and seafood are susceptible to oxidative reactions due to relatively high concentrations of unsaturated lipids, heme pigments, metal catalyst, and various other oxidizing agents present in the tissue. Lipid oxidation causes the development of rancidity and `warmed-over' flavors in meat. In addition to the development of off-flavor, the oxidation process also leads to loss of vitamins, alteration in color, degradation of proteins, and even the production of toxic substances (Singh and Cadwallader, 2004; Yang, 1998; Singh and Anderson, 2004). Lipid oxidation occurs when the double bonds of a fatty acid are attacked by oxygen, hydrogen, and enzymes. The general mechanisms of the oxidative processes involve three steps of autoxidation: (i) initiation, (ii) propagation, and (iii) termination, catalyzed by transition metals, enzymes, and photosensitizers. The primary products of lipid oxidation are hydroperoxides, which are unstable compounds that tend to break down into secondary oxidation products, including aldehydes, ketones, and alcohols that are the volatile products causing off-flavor in products (Rahman et al., 2009). Temperature and oxygen are the two critical factors influencing the rate of oxidation. The rate of oxidation increases exponentially with an increase in

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temperature. Storage at low temperature retards lipid oxidation. Proper package design is important for the package to act as a barrier to oxygen transmission. Fatty acid composition, especially the number and location of double bonds on the fatty acids or triglycerides, greatly affects the rate of oxidation. Light, and trace metals such as copper and iron can greatly catalyze the oxidation reaction. Enzymes such as lipoxygenase can catalyze the reaction between polyunsaturated fatty acids and oxygen to produce hydroperoxides (Gordon, 2004). Heat inactivation, e.g. pasteurization and sterilization of milk, and blanching of vegetables, is a commonly used strategy to inhibit enzyme activity. Presence of water significantly affects lipid oxidation, and the oxidation occurs at high rates at very low water activities. Antioxidants, such as -tocopherol, citric acid, and vitamin C, are able to slow or prevent oxidation by reacting with radical oxygen in a product. Application of tocopherol and oil of rosemary can extend shelf life of salted potato chips from 10 weeks to 12±14 weeks (Yang, 1998). Enzymatic degradation Another mechanism of lipid degradation involves lipolytic/hydrolytic rancidity. For example, lipolytic enzyme lipases catalyze lipolysis resulting in off-odors and off-flavors in foods such as meats and meat products. In this reaction, lipases cleave off free fatty acids (FFA) from triglyceride molecules in the presence of water. The FFAs have shorter chain lengths, lower flavor thresholds, and sometimes off or rancid flavors and odors. For example, lauric acid (C12:0) can be generated in rancid coconut and coconut oil with a strong soapy flavor. Butyric acid, often produced in butter, has a very strong and undesirable odor and flavor at lower levels. Lipid hydrolysis can occur at frozen temperatures (Rahman et al., 2009; RodrõÂguez et al., 2007). A free fatty acid test based on the titration method is commonly used to assess lipid hydrolysis of foods during storage. The lipid hydrolysis reactions can be reduced by minimizing moisture and using heat. Most lipolytic enzymes can be inactivated by heating above 60 ëC. Certain enzyme catalyzing reactions can occur in fruits and vegetables causing degradation in color and texture. Peeled ripe bananas or sliced apples, pears or some vegetables can develop unappealing brown color when exposed to the air. These reactions are catalyzed by phenoloxidase enzymes, which react with phenol compounds and oxygen to form undesirable brown pigments. These reactions take place readily when cells are fractured by bruising, cutting, or peeling (Singh and Anderson, 2004). Minimally processed vegetables are expected to maintain firm and crunchy texture attributes that are associated with freshness and wholesomeness. However, enzyme degradation often leads to a soft or limp product that gives rise to consumer rejection prior to consumption. The reactions involve enzymatic degradation of pectins, in which pectin is first partially demethylated by pectin methylesterase, and later depolymerized by polygalacturonase to polygalacturonic acid causing a loss of firmness (Rico et al., 2007).

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Non-enzymatic browning Non-enzymatic browning (Maillard reaction) occurs due to the interaction between reducing sugars and amino acids. The reaction scheme involves reactions to form an unstable Schiff's base, then transformation through the Amadori rearrangement. The reactions continue further through the Strecker degradation and polymerization reactions to form volatiles and dark pigments (Singh and Anderson, 2004). This reaction leads to the development of a brown color and the accompanying flavor in foods, which is highly desirable in the baking of bread, brewing of beer and roasting of coffee. However, the browning of foods in storage is an undesirable effect. It mostly occurs in dehydrated and semi-moist foods, such as dried fruits and vegetables, powdered eggs and milk, fruit juice concentrates, certain beverages, jams, jellies, certain canned vegetables, and meat products (Yang, 1998). In addition to the darkening of color, the Maillard reaction also leads to loss of protein solubility, bitter offflavor, textural alterations, and even the production of toxic substances (Yang, 1998; Singh and Cadwallader, 2004). Among the factors that affect browning reactions during storage are the structure of amino acids and sugars, temperature, moisture content and water activity, and pH value (Gordon and Davis, 1998; Arnoldi, 2004). The browning rate increases as water activity (aw) increases, and reaches a maximum at water activity between 0.6 and 0.8. A further increase in water activity, however, results in a decrease in rate due to reactant dilution. The Maillard browning reaction is strongly affected by pH, and tends to occur at high pH. The reaction is also catalyzed with metal ions such as copper and iron (Singh and Anderson, 2004). Light-induced chemical changes Milk, chocolate, butter, and other foods, when exposed to light, such as sunlight or fluorescent light, may develop a characteristic off-flavor caused by photooxidation. Photooxidation may occur due to photolytic free radical autoxidation and/or photosensitized lipid oxidation. Both reaction pathways may lead to formation of free lipid radicals (Mortensen et al., 2004), thus initiating autocatalytic oxidative processes. In particular, dairy products, such as milk and cheese, are very sensitive to light oxidation because of the presence of riboflavin (vitamin B2), which functions as a strong photosensitizer. A photosensitizer is able to absorb visible and UV light and transfer this energy into highly reactive forms of oxygen such as singlet oxygen, subsequently inducing a cascade of oxidation reactions, leading finally to lipid and protein oxidation, significant losses of vitamins and amino acids, discoloration, and formation of strong offflavors, and even toxic products (e.g., cholesterol oxides) (Yang, 1998; Borle et al., 2001). Light-induced oxidative processes are a major cause of deterioration in alcoholic beverages such as wines, degrading the flavor and color (Refsgaard et al., 1995). The potential of photooxidation is related to spectral distribution and intensity of a light source, its wavelength, presence of sensitizers, temperature, exposure time and the amount of available oxygen (IFST, 1993; Mortensen

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et al., 2004). Appropriate packaging material that properly protects foods from both light and oxygen is important to minimize the photooxidative deterioration of these products. Protein degradation During storage, protein degrades in various ways. Enzyme activity such as proteolysis by protease is an important contributing factor. A protease can cause hydrolysis of the peptide bonds that link amino acids together in the polypeptide chain, thus digesting long protein chains into short fragments. In milk, plasmin is a protease that can cause degradation of dairy proteins, leading to coagulation and gelation (Singh and Anderson, 2004). Oxidation of proteins is another way of protein degradation. In meats, myoglobin and oxymyoglobin can be oxidized into metmyoglobin, resulting in the meat color turning from bright red to brown. This color change can be unappealing to consumers. Protein oxidation is caused by reactive oxygen species that are generated via lipid oxidation, metal- or enzyme-catalyzed oxidative reactions, and other chemical and biological processes. Physical and chemical changes in oxidized proteins include amino acid destruction, decrease in protein solubility due to protein polymerization, loss of enzyme activity, and increases in protein digestibility (Xiong, 2000). Protein oxidation can cause formation of amino acid derivatives, such as carbonyls. Measurement of carbonyl concentration is commonly used to indicate the extent of protein oxidation. Protein oxidation is linked to lipid oxidation, and a significant correlation between carbonyl content and the thiobarbituric acid reactive substances (TBARS) values in meat has been reported (Mercier et al., 1998). 2.2.2 Physical deterioration Mechanical damage Mechanical damage (physical injury), such as bruising of fresh fruits and vegetables, and crushing or breaking of dried snack foods, represents a serious hazard that significantly reduces the value of a product. Physical injury is possibly the most important cause of loss in fruits and vegetables. It can occur during harvesting, packing house operations, handling and transportation, in which the produce is subjected to one or more types of loading compression, impact, and vibration. The damage is caused by various forces such as pressure between fruit and machinery, surface abrasion, and package handling. For most fruit, bruising is a common type of postharvest mechanical injury (PeÂrezVicente et al., 2002). Bruising takes place when the shear stress exceeds the mechanical strength of cells (i.e., yield stress) leading to cell wall ruptures, cell bursting and/or cell deflation as a result of loss of cell fluid (Szczesniak, 1998). Bruising causes water loss, and may induce color changes due to enzymatic browning and microbial growth that occur at the injury area. Damage susceptibility of fruit is determined by their mechanical properties. Studman

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(1997) noted that apple bruising can result in a typical economic loss in the 10± 25% range, even as high as 50%. Mechanical damage can also occur in other foods. Cracks can develop on the thin coat of the soybean seed during handling, leading to deterioration (Parde et al., 2002). Dry, brittle products, such as crackers, potato chips, and ready-to-eat cereals, are susceptible to breakage during transportation and distribution that can make many products unacceptable. Bruising and breakage can be minimized by the use of well-designed packaging systems which protect the products from vibrations and mechanical damage during distribution and handling. For example, fruit injury can be reduced by using cushioning in a package that will absorb much of the mechanical energy (Singh and Anderson, 2004; Szczesniak, 1998). Moisture change and glass transition Moisture content and water activity are critical factors influencing food stability and shelf life. Water activity (aw) is defined as the vapor pressure of water above a sample (p) divided by that of pure water at the same temperature (p0 ), i.e. aw ˆ p=p0 . It describes the degree to which water is free or bound to other components. Water activity depends on the composition, temperature and physical state of the compounds. For a fixed water content, the weaker the water interactions, the greater the water activity, and the product becomes more unstable (Fabra et al., 2009). The relative humidity (RH) of the immediate environment directly affects the moisture content of food. The difference between the RH of the surrounding environment and water activity (aw) of the food determines whether a food gains or loses moisture during storage. The higher the difference between aw and RH during storage, the more potential for moisture migration to or from the environment. The water migration occurs continuously until equilibrium is reached. Moisture migration and the change in the water activity directly impact food shelf life and quality when foods are consumed. Moisture loss causes fresh produce to wilt and shrivel, and experience increased senescence. Freezer burn is also a consequence of moisture migration from the surface of frozen foods. Moisture migration changes food texture. Dry products such as breakfast cereals and potato chips lose their crispness after gaining moisture above the 0.35±0.5 aw range, while dried fruits and bakery goods become unacceptably hard upon losing moisture to below 0.5±0.7 aw (Taoukis et al., 1997). For foods containing multiple domains with widely different sorption isotherms, moisture transfer can occur between components with different water activities until the same aw is reached. Staling of bread results from moisture migration from the crumb (high aw) to the crust (low aw), leading to a dryer, firmer crumb and a tougher and less crisp crust. Deli salads can also deteriorate from migration of water from the vegetable component into the dressing. Moisture transfer can cause changes in glass transition temperature (Tg), a property of food reflecting molecular mobility, significantly affecting stability

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and shelf life. Glass transition infers material changing from the glassy state to the rubbery state or vice versa, accompanied by changes in thermodynamic properties, molecular mobility, dielectric constant, and mechanical properties. As an illustration, when a flexible rubber band is put into liquid nitrogen, it will change to a solid, brittle and shatterable state; but after warming to room temperature, the rubber band will again become flexible and rubbery (rubbery state). The glass transition concept was originated from polymer science, initially appearing in the literature in the 1960s, but it has now been extensively used with foods since the 1980s (Levine and Slade, 1992). The glass transition concepts and water activity together provide a strong scientific basis for food stability during drying and freezing. Based on the glass transition theory, many low-moisture foods are in the amorphous metastable state, where the material lacks long-range molecular order. These foods include sugar-based products (hard candy, toffee, boiled sweets), dried products (milk and whey powder, fruit juice powder), starchbased products (baked products such as bread, crackers, pasta), and frozen foods. These foods can be in an amorphous glassy state or amorphous rubbery state, depending on temperature and moisture content. Foods in an amorphous glassy state have a high internal viscosity and low internal mobility, whereas in the rubbery state the foods have a viscous, more fluid-like state. Increase in temperature can cause transition of a food from glassy to rubbery state. The temperature (or range of temperatures) where the transition between glassy state and a more fluid-like rubbery state occurs is the glass transition temperature (Tg), which can be determined using differential scanning calorimetry (DSC). A major assumption in food shelf life and quality is that stability of food is maintained in the glassy state. Above Tg, various changes could occur in a food during storage, such as crystallization, collapse and increased stickiness, due to an increase in molecular mobility and decrease in viscosity. The rates of these changes are determined by the temperature difference, T ÿ Tg , i.e. how far the storage temperature T is above Tg (Kalichevsky-Dong, 2000; Meste et al., 2002). Water directly affects Tg by acting as a plasticizer. Water content determines glass transition temperatures of sugars and other carbohydrates in foods, which are common glass formers (Roos, 2010). Tg increases when the water content decreases. For low moisture foods, small amounts of water can decrease Tg tremendously. Absorption of moisture will cause crisp crackers to undergo glass transition and become tough and soggy. On the contrary, food materials can be rendered glassy by removing water. When soft bakery products lose moisture (raised Tg) to the point where they undergo glass transition, they will become glassy, hard, and brittle. Caking of food powder is closely related to its glass transition: when dry powder gains moisture, it undergoes glass transition and becomes amorphous, causing powder to stick together and cake. A recent review published on this subject is given by Roos (2010). The glass transition of food can be identified using a state diagram, a stability map showing different states and phases of a food such as freezing

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point and glass transition as a function of solids content and temperature. The state diagram defines the moisture content and temperature region at which a food domain is glassy, rubbery, crystalline, or frozen. It helps in understanding the complex changes when the water content and temperature of foods are changed, and also assists in identifying the stability of food during storage as well as selecting suitable conditions of temperature and moisture content for processing. State diagrams have been reported for different fruits, such as grape, strawberry, apple, pineapple, persimmon, and grapefruit (Rahman, 2006; Fabra et al., 2009). Starch gelatinization and retrogradation Starch retrogradation refers to the reassociation or the recrystallization of the polysaccharides in gelatinized starch, i.e. amylase and amylopectin. It occurs when starch-based foods are exposed to freeze/thaw cycles, or when moisture migration occurs in starchy foods, impacting textural and nutritional attributes of foods. Starch retrogradation is one of the main mechanisms for staling of bakery products, increasing firmness of crumb, changing flavor and aroma, and causing loss of crispiness (Morris, 1990). The retrogradation of starch also occurs during the tempering of half-products of many snack products and breakfast cereals, producing textural changes such as increased hardness and reduced stickiness (Farhat, 2000). In addition to the changes in texture and flavor, retrogradation of starch also decreases the starch digestibility. The retrogradation of starch is affected by storage temperature, compositions such as water content, sugars, lipids, salts, and anti-staling enzymes. Bread staling occurs most rapidly at 0±4 ëC. Retrogradation occurs more readily with amylose than with amylopectin since amylose is a smaller unbranched molecule; therefore the use of waxy starches (low amylose content) in foods can decrease the level of retrogradation (Singh and Anderson, 2004). Light microscope and X-ray diffraction analysis are commonly used to study the retrogradation process. Chill injury When fruits and vegetables are stored at low, but non-freezing, temperatures (generally at temperatures of 5±15 ëC), the tissues are unable to carry on with normal metabolic processes. As a result, various physiological and biochemical alterations can occur leading to the development of a variety of chilling injury symptoms, including surface pitting, discoloration, internal breakdown, failure to ripen, growth inhibition, wilting, loss of flavor, and decay (Wang, 1989). Chilling injury is affected by growing conditions, maturity, storage temperature, and storage period. The symptoms develop mainly during fruit ripening after cold storage. For fruits such as peaches and nectarines, major symptoms include mealy or woolly texture, internal browning and reddening, and flesh tissue separation and cavity formation (Lurie and Crisosto, 2005). Chilling injury can be alleviated by various methods such as temperature preconditioning, intermittent warming, chemical treatments, hormonal regula-

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tion, controlled atmosphere storage, and genetic manipulation (Wang, 1989). Lowering O2 and raising CO2 in the storage atmosphere is effective in delaying or preventing chilling injury (Crisosto et al., 1995). Fruits are injured more rapidly when stored at temperatures between 2.2 and 7.6 ëC, and can be minimized when stored at near or below 0 ëC (Lurie and Crisosto, 2005). Crystal growth Ice crystals formed during freezing affect the quality parameters of stored frozen foods. For frozen meat or fish, growth of ice crystals may lead to high drip loss during thawing and cooking. The rate of crystal growth is more severe when slow freezing processes or multiple freeze/thaw cycles are applied, due to liquid migration from inside of the cell fluids to the extracellular space that contributes to the formation of large damaging extracellular ice crystals, rupturing membranes and disrupting the ultrastructure of cells and tissues. A fast freezing rate minimizes the migration of water into the extracellular spacing and, consequently, promotes formation of smaller intracellular ice. The formation of large ice crystals can also be minimized with the addition of emulsifiers and other water-binding agents. Moreover, when the temperature of the product is kept below its glass transition temperature during frozen storage, water in the food has much less mobility and will tend not to form ice crystals (Singh and Anderson, 2004). Recent studies have indicated that pressure shift freezing (PSF) allows a large and uniform supercooling over the entire volume of the sample and subsequently a much preserved microstructure in food can be achieved. The PSF process includes cooling the sample under pressure to reach a temperature just above its freezing temperature at the applied pressure. Pressure is then released rapidly resulting in supercooling, which enhances instantaneous and homogeneous crystallization throughout the cooled material. PSF is reported to significantly reduce drip loss in seafood (Chevalier et al., 2000). Other problems related to crystal growth include sugar bloom and fat bloom. Sugar bloom occurs when chocolates experience glass transition, i.e., the glassy sugar changes to a rubbery state by uptake of moisture or by increase in temperature. The sugar crystallizes on the surface that give a gray or white appearance. Fat bloom, on the other hand, indicates migration and recrystallization of fat (e.g., cocoa butter) in chocolate which appears as a whitish, greasy haze. This defect is related to improper tempering during the manufacturing process which leads to less stable forms of fat crystals. Recent studies on fat bloom in chocolate have been published by Hodge and Rousseau (2002), and Lonchampt and Hartel (2004). Emulsion breakdown An emulsion is traditionally defined as a dispersion of droplets of one liquid in another, the two being immiscible (Dickinson and Stainsby, 1982). Foods with an emulsion system include mayonnaise, margarine, salad dressings, cake batter, and ice cream. These emulsions are either oil-in-water (O/W) emulsions (cream,

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dressings) or water-in-oil (W/O) emulsions (butter, margarine). Emulsion stabilization is usually achieved by adding emulsifying agents and thickeners to the emulsion, such as small surfactant molecules (e.g., polysorbates, phospholipids), proteins (e.g., milk proteins), and thickening agents (e.g., gums, gelatin) (Rousseau, 2000). Emulsifiers lower the interfacial tension between the oil and water phases, and/or form a mechanically cohesive interfacial film around the droplets that prevents coalescence (Dickinson, 1992). For example, egg yolk is frequently used as an emulsifier since it contains ends that are both hydrophilic and hydrophobic acting at the surface of the droplets to lower surface tension. Food emulsion is a thermodynamically unstable system. After enough time, an emulsion will collapse, leading to phase separation. The rate at which an emulsion breaks down is strongly influenced by composition, processing condition, and environmental condition (e.g., temperature and pH). Violent vibration, partial freezing or extremely high temperatures all contribute to destabilization of the emulsion. The stability of emulsion can be improved by increasing the viscosity of the continuous phase and reducing the average droplet size in emulsion via homogenization (e.g., milk). Emulsions are usually more stable at lower temperatures due to increased phase viscosity. Some recent literature in this area includes reviews given by Rousseau (2000) and McClements (2007).

2.3 Factors affecting the rate of quality loss due to chemical deterioration and physical instability The rate and extent of physical and chemical reactions depend on many factors, which can be categorized into intrinsic and extrinsic factors. Extrinsic factors are characteristics of the environment as food moves through the food chain, such as temperature, relative humidity, light exposure, and composition of gaseous atmosphere within packaging. Intrinsic factors are characteristics of the food itself, including moisture and water activity, pH and total acidity, availability of oxygen, and additives and preservatives. 2.3.1 Extrinsic factors Temperature Temperature is one of the most important factors affecting the shelf life of foods. Freeze damage can occur in fresh fruits and vegetables. Ice crystals may grow in meats and seafood causing structural disruption and drip loss. Solid fat will become liquid at higher ambient temperature and act as a solvent facilitating a faster deterioration. Increased temperature can also destabilize emulsion systems and change the crystallization characteristics of foods containing sugar syrups. Moreover, increasing temperature generally increases the rate of chemical reactions, resulting in faster deterioration. The dependence of reaction rate on temperature is described by the Arrhenius equation, which will be discussed further later.

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During storage, foods are often subjected to fluctuating ambient temperature. Storage losses under fluctuating temperature condition can be significantly greater than those at mean temperature. For example, pasta stored under a square wave fluctuating temperature condition had a faster rate for thiamine loss. This is because rates of reactions and physical processes increase exponentially with temperature, thus the average reaction rate under fluctuating temperatures is slightly higher than the reaction rate at the equivalent average temperature (Baeza et al., 2007; Ergun et al., 2010). A change in temperature in relation to Tg will change the physical state of foods and subsequently affect many different reaction rates. As discussed in the previous section, when an amorphous glassy food material is warmed above its Tg, the molecular mobility of the food increases and the food becomes rubbery. Below Tg the molecular mobility is much less and reaction rates are generally much lower, and foods can be regarded as stable (Kalichevsky-Dong, 2000). Relative humidity Relative humidity of air is defined as the ratio of the vapor pressure of air to its saturation vapor pressure. The equilibrium relative humidity (ERH) of a food product is defined as relative humidity of the air surrounding the food that is in equilibrium with its environment. When the equilibrium is obtained, the ERH (in percent) is equal to the water activity multiplied by 100, i.e. ERH (%) ˆ aw  100. When a food is exposed to a constant humidity, the product will gain or lose moisture until the ERH is reached. The moisture migration significantly affects the physical and chemical properties of the food, as previously described. Light Food products may be exposed to daylight (or artificial light) at various points in the supply chain. As described in the previous section, light accelerates the oxidation process and therefore the rate at which rancidity develops, especially for fatty foods, causing off-flavor, color fading, or degradation of vitamins. Although transparent packaging materials are generally favored by consumers due to the convenience in observing the contained product, there is an increased risk of light-induced oxidation of foods in such packaging (Mortensen et al., 2004). Packaging The use of appropriate packaging is most important in maintaining the quality of foods and achieving the required shelf life. The principal function of packaging is to protect food from light, oxygen, temperature, moisture, and microorganisms. Packaging also shields food from mechanical damage and protects foods from shock and vibration encountered during distribution. Additionally, food packaging serves to communicate to the consumer information about the food as a marketing tool, and provides consumers with ease of use and convenience (Yam et al., 2005).

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Controlled and modified atmosphere packaging (MAP), including vacuum packaging, nitrogen flushing or a gas mixture consisting of N2, O2, and CO2, are commonly used to slow down undesirable reactions by limiting the availability of oxygen. The mixture of gases in the package depends on the type of product, packaging materials, and storage temperature. For some packaged foods (such as potato chips), the gas contains 99.9% nitrogen. Fruits and vegetables are respiring products, and the gas atmosphere in a MAP package often consists of N2, O2, and CO2, with lowered level of O2 and an increased level of CO2. This atmosphere can potentially reduce respiration rate, ethylene sensitivity and production, and minimize physiological changes such as oxidation, thus extending the shelf life. The presence of other gases, especially CO2, strongly affects biological and microbial reactions in fresh meats, fruits and vegetables, partly due to increased surface acidification (Singh and Cadwallader, 2004). Comprehensive reviews of controlled and modified atmosphere packaging (CAP/MAP) technology are given by McMillin (2008), Brody et al. (2008) and Fonseca et al. (2002). Materials that have traditionally been used in food packaging include glass, metals (aluminum, foils and laminates, tinplate, and tin-free steel), paper and paperboards, and plastics. Modern food packages often combine several materials to exploit each material's functional or aesthetic properties (Marsh and Bugusu, 2007). The main considerations in selection of packaging materials are gas permeability, water vapor transmission rate, mechanical properties, transparency, and type of package and sealing reliability. Oxygen and moisture permeability of materials are crucial factors when selecting packaging films. For non-respiring products such as meat, fish, and cheese, high barrier films are used. But for fruits and vegetables, permeable films are used to allow gases to transmit from and to the package; proper permeability (for O2 and CO2) of the packaging film that is adapted to the product's respiration rate is critical to establishing a desirable equilibrium modified atmosphere in the package and increasing the shelf life of the product. Some of the new packaging technologies include active and intelligent food packaging. Active packaging allows packages to interact with food and the environment thus playing a dynamic role in food preservation; examples include carbon dioxide absorbers/emitters, odor absorbers, ethylene removers, and aroma emitters (Brody et al., 2008). Intelligent or smart packaging is capable of monitoring food properties or package environment, and informing the processor, retailer and/or consumer of the food status and the environment. Examples include time±temperature indicators (TTIs), ripeness indicators, biosensors, and use of radio frequency identification detectors (McMillin, 2008). A summary of recent innovations in food packaging materials is given by Brody et al. (2008).

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2.3.2 Intrinsic factors Moisture and water activity Moisture content and water activity (aw) are the most important factors in addition to temperature that affect microbial growth as well as the rate of chemical and physical deteriorative reactions. Water activity and moisture content are correlated through sorption isotherms. Most fresh foods can be considered as high-moisture foods, with more than 50% w/w (water and water) activity of 0.90 to 0.999. These foods include beverages, fresh meat and seafood, dairy products, and fruits and vegetables. Intermediate moisture foods (IMF) have a water content of 10±50%, and aw of 0.60±0.90. These foods include grains, nuts, dehydrated fruits, and a number of processed foods. Table 2.2 summarizes the water activity of some common foods. As described in previous section, the difference between water activity (aw) of the food and the relative humidity (RH) of the immediate environment determines whether a food gains or loses moisture during storage. Similarly, in foods with multiple domains of different aw, migration occurs between the domains until an equilibrium is reached. As mentioned earlier, moisture migration of foods can cause deterioration in texture, promote chemical deterioration reactions, and change molecular stability, thus limiting shelf life of foods. Use of improved packaging materials minimizes moisture migration to the environment. Moisture migration within multi-domain foods can be retarded through the use of edible films and/or reformulation to balance aw of the different domains (Ergun et al., 2010). In foods, water functions as a solvent, reaction medium, and reactant. Increasing aw generally enhances deteriorative reactions. Food deterioration due to microbial growth is not likely to occur at aw < 0.6. However, chemical reactions and enzymatic changes may occur at considerably lower aw values. For example, lipid oxidation occurs at aw < 0.30, and Maillard browning reaction accelerates as the aw increases above 0.25±0.3.

Table 2.2

Summary of the water activity of some common foods

aw

Typical foods

1±0.95 0.95±0.9 0.95±0.85 0.85±0.8 0.8±0.75 0.75±0.65 0.65±0.6 0.5 0.3 0.2

Fresh and canned fruits, meat, milk, breads, fish, cooked sausages Cheese, cured meat Margarine, fermented sausage, sponge cakes Salted meats, syrup, flour Jam, glace fruits Nuts, jelly, molasses Honey, caramel, toffee Pasta Cookies, crackers Dried vegetable

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The water activity concept proposed that a food product is most stable at its monolayer moisture content. Most reactions have minimal rates at the monolayer value. For example, the rate of lipid oxidation has a minimum rate at aw ˆ 0.35, corresponding to a moisture level of 8±10%, which is the water content to form a monolayer. This monolayer acts as a barrier to protect foods from oxygen attack on the unsaturated lipids, which varies with the food composition, structure, and temperature (Esse and Saari, 2004; Rahman, 2009). A food is most stable at and below its glass transition point. As described in the previous section, Tg decreases with increasing aw. The relationship between Tg and aw is often linear for foods with intermediate moisture contents (Rahman, 2009; Kalichevsky-Dong, 2000). pH and total acidity The pH of a food strongly affects protein solubility and functionality. Protein solubility has a direct effect on the reaction behavior, and the solubility of protein is usually at a minimum near the isoelectric point. Changes in food pH also change the shape or charge properties of proteins, thus significantly affecting food storage stability. pH strongly affects enzymatic activity, and each enzyme has a region of pH for optimal stability. Enzymes can completely lose activity in extremely high or low pH environments. The pH of food also impacts the stability of constituents present in the food. For example, anthocyanin, a flavonoid pigment with antioxidant capacity, is most stable under acidic condition. At high pH (e.g., pH ˆ7.01), anthocyanins are unstable and will lose color completely after 20 days' storage at ambient temperature (Pang et al., 2001). Oxygen The presence of oxygen in a package not only facilitates the growth of aerobic microbes and molds, but also triggers or accelerates oxidative reactions that result in food deterioration, developing off-odors, off-flavors, undesirable color changes, and reduced nutritional quality. Oxygen affects both the rate and apparent order of oxidative reactions (Labuza, 1971). Most food packaging is concerned with keeping oxygen out of the pack, by nitrogen flushing, vacuum packaging or modified atmospheric packaging. Oxygen scavengers can be used inside a package to reduce headspace oxygen levels to marginal levels. They are mostly agents that can react with oxygen to reduce its concentration. Ferrous oxide is the most commonly used scavenger. Other oxygen scavengers include ascorbic acid, sulfites, and enzymes such as glucose oxidase (Brody et al., 2008). Sometimes oxygen is needed to maintain desirable food quality characteristics. For beef, oxygen is needed to develop oxymyglobin that maintains the bright red color associated with freshness. The red color is due to the presence of oxymyglobin, which develops whenever the meat is exposed to air (Emblem, 2000).

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Product formulation and composition The shelf stability of a food is governed by its composition. For example, the presence of fats, especially polyunsaturated fats, will make the product prone to chemical and physical changes. Lipid oxidation of oils can be retarded by blending with other types of oils which are more resistant to reactions. RodrõÂguez et al. (2007) found that blending of Moringa oleifera oil (MOO) with sunflower oil and soybean oil significantly increased the oxidative stability of both the substrate oils. This improvement was attributed to the high contents of oleic acid (C18:1) present in MOO. Oleic acid (C18:1) is more resistant to oxidation compared with polyunsaturated fatty acids (RodrõÂguez et al., 2007). The stability of some food products is related directly to the stability of particular ingredients. Incorporating lactose into confectionery can cause premature crystallization and graining of products such as toffee (Subramaniam, 2000). The shelf life of thiamin-containing beverages can be improved by using an appropriate type of buffer based on the pH of the beverage. For example, at pH 4 and 5, thiamin stability was greater in phosphate buffer than citrate buffer. While in high pH beverages, citrate buffer is better for thiamin stability (Pachapurkar and Bell, 2005). Additives and preservatives are commonly used to maintain food quality and flavor and keep food from spoilage by bacteria and yeasts. More than 3000 food additives and preservatives are available in the market, and the most commonly used ones are salt and sugar. These additives are classified as antimicrobial agents, antioxidants, artificial colors, artificial flavors and flavor enhancers, chelating agents, and thickening and stabilizing agents. Antioxidants including vitamin C, E, butylated hydroxytoluene (BHT), and butylated hydroxyanisole (BHA) are mainly used in foods containing high fats, which are compounds that are able to inhibit oxidation reactions by interrupting the radical chain reaction. Chelating agents such as malic acid, citric acid, and tartaric acid are used to prevent flavor changes, discoloration and rancidity of the foods. Other additives are used as humectants to retain moisture, and emulsifiers to reduce separation of water and oil from products (Subramaniam, 2000). Some of the additives are manufactured from the natural sources such as corn, beet and soybean, others are artificial and man-made. Despite their wide application, the benefits and safety of many artificial food additives (including preservatives) are vigorously debated (Wuttke et al., 2007).

2.4 Measuring chemical deterioration and physical instability of foods and beverages 2.4.1 Sensory panels Sensory evaluation infers measurement, analysis and interpretation of characteristics of food materials as they are perceived by the senses of sight, smell, taste, touch and hearing. It is the most comprehensive way of assessing

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the quality of food (O'Mahony, 1979). Traditional sensory methods of texture evaluation involved assessment and grading by `expert' tasters, in which one or two trained `experts' assign quality scores on the appearance, flavor and texture of the products based on the presence or absence of predetermined defects. The shortcomings of this method include inability of predicting consumer acceptance and the lack of objectivity in quality assessment. Two products with different relative intensities of sensory characteristics may receive similar quality scores based on defects detected by the `experts' (Claassen and Lawless, 1992). Sensory evaluation by a trained panel usually gives a good estimate of the overall quality of a food. Descriptive analysis is commonly used that deals with the total profile of a food product. It refers to a collection of techniques that seek to discriminate between a range of products based on their sensory characteristics, and to determine a quantitative description of the sensory differences that can be identified. Descriptive analysis requires at least three evaluative processes: discrimination of the trait; description of the trait; and quantitation of the trait. External standards are usually used to define attributes and standardize the scale for each assessor. Developing and refining a vocabulary is an essential part of sensory profile work. Panel training is then performed to increase panelist sensitivity and memory and helps panelists to make valid, reliable judgments independent of personal preferences. Sample testing is usually carried out in replicated (commonly three) sessions, using experimental designs that minimize biases. Descriptive analysis results are subjected to univariate statistics (e.g., multi-way analysis of variance) or multivariate statistics (e.g., principal component analysis) (Hugi and Voirol, 2010; Borgognone et al., 2001). For details of the sensory technique, the reader is referred to the book by Stone and Sidel (2004). Sensory methods have been, and will be for the foreseeable future, the primary means of measuring the range of sensory characteristics of food that are important to consumer acceptance. However, the limitations of sensory testing exist that include high cost, excessive time consumption, high variability, ethical restrictions, and health risk to the panel when exposed to spoiled or potentially hazardous samples. In addition, sensory data are subjective in nature, and the testing results often lack consistency (Singh and Anderson, 2004; Singh and Cadwallader, 2004). These limitations make instrumental methods important in evaluating food quality changes during storage. 2.4.2 Instrumental methods Compared with sensory analysis, instrumental methods usually have improved accuracy and reproducibility (Gordon, 2004). Coupling sensory analysis with chemical analysis data can provide more insights than using either technique alone. A reliable instrumental technique is expected to be well correlated with relevant sensory attributes.

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Physical measurements Color is the first sensory attribute of most foods that customers can appraise. It often degrades during storage as a result of enzymatic and non-enzymtic reactions, oxidation, and physical reactions. Color is commonly measured using a tristimulus colorimeter or a reflectance spectrophotometer. The color data can be obtained in terms of tristimulus values, chromaticity coordinates, hue, and chroma (Clydesdale, 1998). Good correlation between color and food quality has been reported. For fresh produce, color measurement is one of the few instrumental tests that give results correlating well with consumer assessment of quality (Aked, 2002). Kong and Chang (2009) reported that soybean color can be used to predict soybean quality as well as tofu-making properties. Recently, machine vision systems using a conventional CCD camera have been used in color assessment as well as to categorize products with respect to size and other appearance factors (Chen et al., 2002; Kong et al., 2007b). Machine vision systems are also used to locate bruising in fruits. In particular, spectroscopy and hyperspectral imaging have emerged as powerful techniques in that they greatly enhance our ability to identify materials. These methods can detect subtle and/or minor features of an object that are only sensitive to specific wavelengths (Chen et al., 2002; Van Zeebroeck et al., 2007). Methods of measuring moisture content fall into two categories: direct measurements and indirect measurements. Direct measurement, including the oven-drying method, mostly involves weighing the sample before and after removing the water. Indirect methods measure a property of the food that is itself related to moisture content, for example, the electrical resistance and the dielectric constant of a sample. Water activity values are often obtained by either a capacitance or a dew point hygrometer (Mathlouthi, 2001). Texture is one of the most commonly used physical indicators of food quality. Texture degradation occurs due to moisture migration, enzymatic hydrolysis, and other physical or chemical deteriorations. The texture of a food is often defined based on the stress/strain or force/deformation relationship obtained when food is subjected to an instrumental determination. Most of the instrumental texture measurements involve mechanical tests quantifying the resistance of the food to applied forces, from which quality attributes such as hardness, crispness, and cohesiveness are derived. A large number of instruments are available for testing food texture, and the most popular ones include Instron universal testing machine (Yuan and Chang, 2007), and Texture Technologies' TA.XT2 Universal Texture Analyzer (Kong et al., 2007b). More sophisticated methods are also available, such as the acoustic method, involving measuring the perception of air-conducted sounds to establish its contribution to the sensation of crispness, and recording the sounds while performing a mechanical test (Juodeikiene and Basinskiene, 2004). The acoustic technique is a non-destructive test suitable for on-line texture measurement. Good correlation between sensory and instrumental results for texture can be established when the

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measurement method is carefully chosen (Rahman et al., 2007). An extensive review of the principles and appliations of texture measuring methods was published by Bourne (2002). The rheological properties of liquid and semi-solid foods are characterized in terms of viscosity, flow behavior index, and consistency index, which may experience significant change during storage. For example, the flow behavior index of concentrated milk significantly changes with storage time (VeÂlez-Ruiz and Barbosa-CaÂnovas, 1998). Rheometers and viscometers are commonly used to quantify the flow properties of the food by measuring the change in stress at either changing or constant shear rate. Glass transition plays a crucial role in modifying the physical property of a food. Glass transition temperature Tg is mostly measured by using differential scanning calorimetry (DSC). DSC defines the glass transition as a change in the heat capacity as the food matrix goes from the glass to the rubbery state. Dynamic mechanical analysis (DMA) is also commonly used as a sensitive and versatile thermal analysis technique which measures the modulus (stiffness) and damping (energy dissipation) properties of materials as the materials are deformed under periodic stress. The DMA storage and loss moduli provide valuable information on food properties, such as the softness of bread, as well as the cooking characteristics of pasta. Other methods, such as X-ray diffraction, microscopy, and dilatometry, are also used to study crystalline structure and glass transition which enable full three-dimensional characterization (Farhat, 2004). Nuclear magnetic resonance (NMR) spectroscopy is increasingly used to monitor the molecular mobility of the components of a food over a range of temperatures encompassing Tg. The principle involves proton relaxometry, which is related to the glass transition of food-related systems (Kou et al., 2000). Chemical measurements Chemical analysis is used to measure the end points of chemical reactions occurring in food during storage, or to confirm the results obtained by the sensory panels. The level of rancidity in lipids is often measured using the peroxide value (PV) and the free fatty acid content (FFA) (Singh and Anderson, 2004). The FFA method measures the liberation of fatty acids as a result of hydrolytic rancidity development. The PV method determines oxidative deterioration of oils by measuring the hydroperoxide, the primary oxidation products. As hydroperoxides quickly decompose to secondary products, PV is often combined with other measurements to reveal the whole picture of oxidation, such as thiobarbituric acid value (TBA). TBA measures malonaldehydes, one of the secondary products of lipid oxidation, representative of aldehydes. Other methods monitoring oxidative deterioration of an oil include using p-anisidine to quantify aldehydes, analyzing conjugable oxidation products (Visioli et al., 1995), and determining octanoate value (Peers and Swoboda, 1979). For all of these tests, standard

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methods of analysis have been established by several organizations such as the Association of Official Agricultural Chemists (AOAC), the American Oil Chemists' Society (AOCS), the International Union of Pure and Applied Chemistry (IUPAC) and the members of the International Standardization Organization (ISO). Analysis of volatiles in headspace of closed food containers with gas chromatography (GC) methods is a common method to monitor oxidative deterioration and determine fatty acid composition, and to correlate with offflavor. Headspace sampling is widely employed, including static, dynamic headspace or solid-phase microextraction sampling followed by GC separation of volatiles generated during lipid oxidation. Solid-phase microextraction sampling is especially preferred due to relatively simple sample preparation, sensitivity, and rapidity (Singh and Cadwallader, 2004). GC-mass spectrometry (GC-MS), and GC-flame ionization detector (GC-FID), and GC-olfactometry are widely used to analyze the composition of volatiles and to estimate the sensory contribution of a single aroma compound to food flavors (Limpawattana et al., 2008; van Ruth, 2001). Good correlations between sensory assessment and chemical measurements are reported. For example, rancid odor and flavor detected by sensory testing have been correlated with aldehydes, and particularly hexanal, which is therefore called a marker molecule (Fritsch and Gale, 1977; Morales et al., 1997). However, most often sensory descriptions are not related directly to individual compounds (Limpawattana et al., 2008). Consequently, more information on compounds that lead to the prediction of the sensory properties of foods needs to be elucidated. A recent development in detecting odors and aromas is the electronic nose, based on the GC volatile methods. It is able to determine the odor intensity of mixtures of a variety of volatile oil degradation compounds, due to its special detection system consisting of an array of gas sensors (mainly semiconductors). It may function as a rapid and non-destructive tool for on-line flavor characterization, especially for rancidity analysis for foods during storage. The electronic nose has been commercialized, and its use is widely reported for detecting lipid oxidation of foods and change in aroma, such as wine (GarcõÂa et al., 2006), meat (Vestergaard et al., 2007), and peach (Infante et al., 2008). A recent review on this subject was written by Peris and Escuder-Gilabert (2009). An `electronic tongue' has also been developed that may be used to detect taste and olfaction in foods. An electronic tongue consists of an array of crosssensitive (or partially selective) sensors. Good correlation was found between the instrument output and sensory descriptors pertaining to the global quality of a product (body, overall quality, and astringency) (Rudnitskaya et al., 2009). Recent published reviews on this subject include those by Li et al. (2006) and Ampuero and Bosset (2003).

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2.5 Predicting and monitoring chemical deterioration and physical instability of foods and beverages The shelf life of many foods is limited by the chemical and physical changes that lead to deterioration in appearance, texture, and odor/flavors. The rate of deteriorative reactions depends on product composition as well as environmental factors, i.e., temperature, water activity, and ambient atmosphere. Quantitative prediction of chemical deterioration and physical instability is critical for estimating the shelf life of food products and designing new processes and packaging. This can be done by the use of mathematical modeling. Mathematical modeling of quality deterioration is commonly conducted to describe the fate of quality indicators as a function of intrinsic and extrinsic factors in the food chain. There are a number of modeling methods, of which kinetic modeling is the most commonly used. Kinetic modeling implies that characteristic kinetic parameters are contained in the mathematical models, such as rate constants and activation energies. Kinetic modeling has been used to characterize microbiological growth, changes in texture and color, as well as chemical/ biochemical reactions in foods during processing and storage. The derived models are either empirical or semi-empirical (van Boekel, 2008). To develop these models, experiments are needed to collect data relating the change in food quality with given storage conditions. The model can be developed by analyzing the experimental data statistically to determine kinetic parameters and seek mathematical relationships. Validation of the model is needed to determine how well it describes the original data. It is important to note that these empirical models may not be valid when used outside the region of influencing parameter on which the models are based. Other types of mathematical modeling are available, such as multivariate statistical tools. They are not covered in this chapter and readers are referred to books or papers in literature such as van Boekel (2000) and Martins and van Boekel (2005).

2.5.1 Kinetic modeling of food quality attributes Modeling chemical reactions The rate of chemical reactions is an important determinant of food quality changes and shelf life. Chemical kinetics involves the study of the rates and mechanisms by which a chemical species converts to another. It is characterized by the rate constant and the order of the reaction. The rate of a chemical reaction (or deterioration of a quality indicator) is defined as the change of concentration of a reactant (or quality factor) (C) at a given time (t): ÿ

dC ˆ kC n dt

2:1

where k is the rate constant in appropriate units, and n is the order of the

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chemical reaction of the quality factor. Solutions of Eq. 2.1 for zero-, first-, or second-order reactions are, respectively: C ˆ C0 ÿ kt

2:2

C ˆ C0 eÿkt

2:3

1 1 ‡ kt ˆ C C0

2:4

where C0 is the initial concentration. In zero-order reactions, the rate of loss of the quality factor is constant. An example of a zero-order reaction is the formation of brown color in foods as a result of the Maillard reaction (van Boekel, 2008; Kong and Chang, 2009). First-order reactions are frequently reported for reactions in foods, including lipid oxidation and development of rancidity, microbial growth, vitamin losses in dried foods, and loss of protein quality (Sewald and DeVries, 2003). Second-order reactions are relatively less common. Examples include changes of amino acids involved in the Maillard reaction (van Boekel, 2008) and decay of thiamin during heating (Kong et al., 2007a). Modeling temperature dependence of chemical reactions Increase in storage temperature will accelerate many quality deteriorative reactions in stored food. The relationship between reaction rate constant k and temperature can be described by the Arrhenius equation: k ˆ AeÿEa =RT

2:5

where A is a so-called `pre-exponential factor', Ea the activation energy, and R and T the gas constant and absolute temperature, respectively. The Arrhenius equation is derived from thermodynamic laws and statistical mechanics principles, and it is the most prevalent and widely used model describing the temperature dependence of chemical reactions that occur in foods during processing and storage. High activation energy implies that the reaction is strongly temperature dependent, i.e., accelerates greatly with increase in temperature. It should be noted that there are situations where the temperature effect on food quality loss does not follow Arrhenius behavior (Labuza and Riboh, 1982). These situations often involve phase change such as the melting of fats, crystallization of amorphous carbohydrates, and denaturation of proteins as well as increased water activity. These changes may increase or decrease the mobilization of reactants, thus complicating the effect of temperature. For example, temperature decrease may cause crystallization of carbohydrates that will reduce the amount of available sugars for reaction but create more free water for other reactions. It is therefore important to test the validity of the Arrhenius equation whenever it is used for modeling the temperature effect. This is particularly important when the result of accelerated testing is used to estimate the deterioration characteristics under ambient storage conditions (Mizrahi, 2000).

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An alternative way of expressing temperature dependence of a reaction is to use the concept of `Q10 '. `Q10 ' is defined as the ratio of the reaction rate constants at temperatures differing by 10 ëC (18 ëF). It indicates how faster a reaction will occur if the temperature is raised by 10 ëC, and thus can be used to predict expected product shelf life. For example, if a food attribute is stable for 10 weeks at 30 ëC, and has a Q10 of 2, then its stability at 20 ëC will be 2  10 weeks = 20 weeks. The Q10 and Arrhenius equation together are the principles behind accelerated shelf life testing, a method commonly used for rapid estimation of the shelf life. Determination of kinetic parameters Kinetic parameters of food quality loss are determined through experimental and statistical means, including reaction constant k, reaction order n, activation energy Ea , initial quality C0 , and Q10 . When conducting shelf life experiments, stress variables are defined depending upon the factors that affect the concerned reactions. For example, to study lipid oxidation, influencing factors that should be considered include temperature, water activity, antioxidants, oxygen, pH, and light or even the presence of catalysts. Accelerated testing is often needed when the product shelf life is relatively long (e.g., canned foods). Packaging materials and geometrical shapes significantly affect the rate of quality loss reactions by allowing different levels of heat/mass transfer and light exposure. These factors need to be carefully selected simulating industrial practice. During storage experiment, the quality attributes of food samples are measured at different temperatures and time periods. For each testing temperature, at least five to six data points should be taken over time to make the study results statistically reliable. The higher the storage temperature, the more frequent should be the testing. Determination of the model parameters is usually carried out by statistical regression calculations based on the principles of temperaturedependent chemical reaction kinetics. For details, readers are referred to numerous papers and books in this regard (Sewald and DeVries, 2003; Kong et al., 2007a). Other kinetic models In addition to reaction order and the Arrhenius equation, other models are also available for kinetic modeling of reactions. One of them is Michaelis±Menten equation, which is mostly applied to model enzymatic reactions. As mentioned previously, enzymatic catalyzed degradations cause hydrolytic rancidity, and discoloration and texture degradation in fruits and vegetables. These reactions can be described by Michaelis±Menten kinetics (van Boekel, 2008): v0 ˆ

vmax ‰SŠ ‰SŠ ‡ KM

2:6

where v0 is the initial rate of the reaction, vmax the maximum rate under the conditions studied, [S] is the substrate concentration, and KM the Michaelis constant. vmax and KM are the parameters of the equation. The Michaelis±

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Menten equation relates the initial reaction rate v0 to the substrate concentration [S]. The rate of the enzymatic reaction can be predicted by nonlinear regression estimation. Glass transition significantly affects food stability through changes between glassy and rubbery state. For foods that undergo glass transitions, the Williams± Landel±Ferry (WLF) model is mostly used to describe the temperature dependence of mechanical properties. Specifically, the WLF equation describes the relationship between viscosity and temperature T and the glass transition temperature Tg0 :   C1 …T ÿ Tg †  ˆ 2:7 ln C2 ‡ …T ÿ Tg † g where  is the viscosity, g, is the viscosity at Tg, and the parameters C1 and C2 are empirical constants. By calculating the viscosity in the glass transition range, the WLF equation relates the molecular mobility of food to the temperature range where glass transition occurs. Molecular mobility is closely related to rate of reactions causing food deterioration. Therefore, the WLF model can be used to obtain valuable information about physical processes such as recrystallization, loss of flavor and desired textural attributes caused by such structural changes (Mizrahi, 2000; van Boekel, 2008).

2.5.2 Time±temperature history The food distribution chain includes several stages involving storage, transport, and handling, where food is often exposed to varying temperatures. Since temperature is one of the most important environmental factors that influence a number of quality attributes in foods, it is critical to know the temperature exposure of a food consignment during storage and distribution. The time± temperature indicator (TTI) is a device that can be attached to foods to indicate the time±temperature history of the food. It is a reliable tool for continuous temperature monitoring and shelf life prediction, and has been selectively used as a food quality monitor for various perishable and semi-perishable foods, particularly chilled and frozen foods which are sensitive to temperature, such as fresh milk, frozen fish, meat, and seafood (Wells and Singh, 1998; Taoukis and Giannakourou, 2004). The principle of TTI operation involves irreversible biological, chemical, or physical reactions that are accelerated at elevated temperature, resembling the temperature dependence of most quality loss reactions of foods (Yan et al., 2008). TTI reflects the cumulative time±temperature history of foods by different means, including development of a specific color or movement of a dye (of known color) along a scale. TTI can indicate full history, partial history, or critical temperature. It is important to know that TTI can reflect the quality status of the food only if the activation energy of quality loss reaction is close to that of the TTI response; therefore successful simulation of the food quality loss kinetics determines the effectiveness of TTI in monitoring

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quality deterioration (Taoukis and Labuza, 1989; Taoukis and Giannakourou, 2004). More details on TTI devices can be obtained from many books and papers (Taoukis and Labuza, 1989; Yan et al., 2008). With TTI, the time±temperature history of the product can be monitored continuously. This information, plus modeling, primarily kinetic modeling of different deteriorative reactions that occur in food systems, allows us to assess the extent of quality loss of a product, and estimate the remaining shelf life at any point along the distribution chain of products (Taoukis and Giannakourou, 2004). An approach presented by Wells and Singh (1992) involves using the response of a TTI at a constant reference temperature. This information is used along with the activation energy of the indicator to calculate a constant temperature equivalent of the change in the indicator response during the inspection interval. The amount of food quality attribute remaining at the end of the interval is then predicted using the calculated temperature equivalent. Wells and Singh (1992, 1998) conducted detailed research in this area and explored the mathematical derivations that describe this approach for zero-order and firstorder reactions.

2.6 Preventing chemical deterioration and physical instability of foods and beverages As described earlier, chemical and physical reactions occur that lead to food spoilage. Whereas the key factors controlling food stability are temperature, time, and water content, other extrinsic and intrinsic factors, such as pH, light, ingredients, product formulation, oxygen, and packaging, also significantly impact quality changes of food during processing and storage. Deteriorative reactions can be retarded by controlling these factors through the food chain from product manufacturing, processing, to packaging and storage. Strategies that are often employed include control of temperature and water activity; addition of chemicals such as salt, sugar, carbon dioxide, or antioxidants; removal of oxygen; modification of initial headspace gas composition and its retention during distribution and storage; or a combination of these with effective packaging (Brody et al., 2008; Singh and Cadwallader, 2004). The design of product formulation is fundamental to the safety and quality of the food. Specifically, ingredients should be selected or tailored to meet clearly defined quality characteristics. Antioxidants can be used to control oxidation reactions and minimize rancidity. Water activity in foods is critical for food stability, especially for low-moisture foods. Additives (salts, sugars, and glycerol) can be added to lower aw, thus increasing the stability of foods. A variety of processing methods are available for food preservation. Traditional approaches include thermal processing (pasteurization, blanching, cooking, and sterilization), drying, refrigeration (chilling and freezing), extrusion, and separation (filtration, centrifugation, and membranes). New processing technologies are being researched including high hydrostatic pressure, pulsed electric

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fields, microwave heating, and ohmic heating (Kong and Singh, 2009; Sun, 2005). These technologies provide various options for food preservation and extended shelf life. For example, heat treatments such as blanching effectively inhibit enzymatic activity and preserve color and texture of fruits and vegetables; high hydrostatic pressure can significantly improve the shelf life of minced pressurized albacore muscle (Ramirez-Suarez and Morrissey, 2006); plums treated with putrescine are likely to be more resistant to mechanical damage during handling and packaging (PeÂrez-Vicente et al., 2002). Packaging is an essential element of the food preservation chain. The technique of modified atmospheric packaging (MAP) extends vacuum packaging to more sophisticated gas flush packaging. Roasted coffee can be stored for as long as 18 months after being flushed with CO2 and N2 then vacuum packaged, up from 3 days without packaging (Winger, 2000). As shown earlier in this chapter, light can trigger and accelerate oxidation of unsaturated fatty acids. Therefore, suitable packaging for fatty foods should be designed to reduce the intensity of the incident light, thus retarding or eliminating lightinduced reactions. Beers packed in amber glass bottles have a longer shelf life than those packed in clear glass. When designing modified atmosphere packaging, a number of variables need to be taken into account: the characteristics of the product, the optimum atmosphere composition, the permeability of the packaging materials to gases, sensitivity to temperature, and the respiration rate of the product as affected by different gas composition and temperature (Fonseca et al., 2002). It should be recognized that MAP is a dynamic process, and the gas composition will alter to a certain level after storage is initiated. It is also important to impose tight quality control through package testing to avoid any potential problems that may cause product spoilage. Routine package testing should be conducted to analyze headspace gas composition, oxygen levels, and examine package seals that assure package quality (Fonseca et al., 2002). Active packaging with special gas and moisture absorbers to maintain proper gas composition provide more options (Emblem, 2000). Many of the physical, chemical, or biochemical changes that occur in foods are difficult to control using only one control measure. Hurdle technology, although defined for microbial aspects of the shelf life extension, is also applicable for preservation of food quality. Hurdle technology employs a number of individual hurdles in such a way as to minimize the deterioration reactions. Low temperatures and modified atmosphere packaging together are applied to decrease the rate of quality degradation in minimally processed vegetables during storage. It is also found that the effectiveness of the modified atmosphere on fruits and vegetables may be enhanced by the appropriate use of anti-browning agents (Ragaert et al., 2007). The use of PPP (product, process, and packaging) concepts has been suggested to be the most important overall consideration for frozen product quality, in which precise integration of the product formulation, processing, package, and distribution is required to alleviate food quality loss (Jul, 1984). For example, in manufacturing potato

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chips, different approaches are combined to minimize deterioration during storage, including use of high solid potato varieties, proper selection of frying oil and the use of antioxidants (Winger, 2000).

2.7

Future trends

One of the aims of current food research is to develop new technologies for high quality shelf-stable food products. An example is microwave sterilization technology. The US Food and Drug Administration (FDA) has recently approved the use of microwave energy for producing pre-packaged, low-acid foods (Harrington, 2010). Other technologies that are being vigorously researched include high-pressure processing, pulsed electric fields, ohmic heating, and ultrasound. These technologies aim to inactivate microorganisms in foods with improved quality attributes, by either reducing heating time (e.g. microwave processing), or non-thermal processing (e.g., high-pressure processing). The reduced heat load will benefit the preservation of nutrients, and reduce the rates of deteriorative reactions such as lipid oxidation, thus extending the shelf life. These technologies also offer the potential for improving existing processes. Packaging is essential for food stability. Synthetic polymers are the most common packaging materials due to their flexibility, light weight and transparency. However, they are non-biodegradable and impose serious ecological problems (Siracusa et al., 2008). With heightened social and environmental consciousness, and strict regulations on pollutants and disposal of municipal solid waste, active research is being conducted to develop innovative packaging approaches. Natural polymers, such as films made of polysaccharides and proteins, are used in packaging to replace petroleum-based polymers. So far, the application of biodegradable films for food packaging is limited because of their poor barrier and weak mechanical properties (Brody et al., 2008; Marsh and Bugusu, 2007). The use of nanomaterials in packaging is being actively studied. Nano-particles such as titanium dioxide and silver when combined into natural packaging materials have shown to be effective in both antibacterial activity and preservation of quality for fresh fruits, thus extending the shelf life of packaged products (Yang et al., 2010). Ongoing research in this area is expected to provide new opportunities to food manufacturers to extend the shelf life of foods with minimal quality loss.

2.8

Sources of further information and advice

Several recently published reference books and review articles that are focused on the area of shelf life of foods (in addition to the chapter's references) are as follows:

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and LASEKAN, O. (2009). The relationship between water activity and fish spoilage during cold storage: a review. Journal of Food, Agriculture and Environment, 7(3±4): 86±90. AMPUERO, S. and BOSSET, J.O. (2003). The electronic nose applied to dairy products: a review. Sensors and Actuators B, 94: 1±12. ESKIN, M. and ROBINSON, D. (2001). Shelf-life Stability: Chemical, Biochemical and Microbiological Changes. Boca Raton, FL: CRC Press. È TKE ENTRUP, M. (2005). Advanced Planning in Fresh Food Industries. Heidelberg: LU Physica-Verlag. MARTINS, R., V. LOPES, V., VICENTE, A. and TEIXEIRA, J.A. (2008). Computational shelf-life dating: complex systems approaches to food quality and safety. Food and Bioprocess Technology, 1(3): 207±222. MESTDAGH F., DE MEULENAER, B., DE CLIPPELEER, J., DEVLIEGHERE, F. and HUYGHEBAERT, A. (2005). Protective influence of several packaging materials on light oxidation of milk. J. Dairy Sci., 88: 499±510. OHLSSON, T. and BENGTSSON, N. (2003). Minimal Processing Technologies in the Food Industry. Weimar, TX: C.H.I.P.S. ROBERTSON, G.L. (2006). Food Packaging: Principles and Practice, 2nd edn. New York: Marcel Dekker. ROBERTSON, G.L. (2009). Food Packaging and Shelf Life: A Practical Guide. Boca Raton, FL: CRC Press. SKIBSTED, L., RISBO, J. and ANDERSEN, M. (2010). Chemical Deterioration and Physical Instability of Food and Beverages. Cambridge: Woodhead Publishing. ABBAS, K.A., SALEH, A.M., MOHAMED, A.

2.9

References

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 ., SERRANO, M., RIQUELME, F., PEÂREZ-VICENTE, A., MARTIÂNEZ-ROMERO, D., CARBONELL, A  GUILLEN, F. and VALERO, D. (2002). Role of polyamines in extending shelf life and

the reduction of mechanical damage during plum (Prunus salicina Lindl.) storage. Postharvest Biology and Technology, 25(1): 25±32. PERIS, M. and ESCUDER-GILABERT, L. (2009). A 21st century technique for food control: electronic noses. Analytica Chimica Acta, 638(1): 1±15. RAGAERT, P., DEVLIEGHERE, F. and DEBEVERE, J. (2007). Role of microbiological and physiological spoilage mechanisms during storage of minimally processed vegetables. Postharvest Biology and Technology, 44(3): 185±194. RAHMAN, M.S. (2006). State diagram of foods: its potential use in food processing and product stability. Trends in Food Science & Technology, 17(3): 129±141. RAHMAN, M.S. (2009). Food stability beyond water activity and glass transtion: macromicro region concept in the state diagram. International Journal of Food Properties, 12(4): 726±740. RAHMAN, M.S., AL-WAILI, H., GUIZANI, N. and KASAPIS, S. (2007). Instrumental-sensory

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evaluation of texture for fish sausage and its storage stability. Fisheries Science, 73: 1166±1176. RAHMAN, M.S., AL-BELUSHI, R.M., GUIZANI, N., AL-SAIDI, G.S. and SOUSSI, B. (2009). Fat oxidation in freeze-dried grouper during storage at different temperatures and moisture contents. Food Chemistry, 114(4): 1257±1264. RAMIREZ-SUAREZ, J.C. and MORRISSEY, M.T. (2006). Effect of high pressure processing (HPP) on shelf life of albacore tuna (Thunnus alalunga) minced muscle. Innovative Food Science & Emerging Technologies, 7(1±2): 19±27. REFSGAARD, H.H.F., BROCKHOFF, P.M., POLL, L., OLSEN, C.E., RASMUSSEN, M. and SKIBSTED, L.H. (1995). Light-induced sensory and chemical changes in aquavit. LebensmittelWissenschaft und -Technologie, 28(4): 425±435. RICO, D., MARTIÂN-DIANA, A.B., BARAT, J.M. and BARRY-RYAN, C. (2007). Extending and measuring the quality of fresh-cut fruit and vegetables: a review. Trends in Food Science & Technology, 18(7): 373±386. RODRIÂGUEZ, A., LOSADA, V., LARRAIÂN, M., QUITRAL, V., VINAGRE, J. and AUBOURG, S. (2007). Development of lipid changes related to quality loss during the frozen storage of farmed coho salmon (Oncorhynchus kisutch). Journal of the American Oil Chemists' Society, 84(8): 727±734. ROOS, Y.H. (2001). Water activity and plasticization. In Eskin, N.A.M. and Robinson, D.S. (eds), Food Shelf Life Stability. New York: CRC Press, pp. 3±36. ROOS, Y.H. (2010). Glass transition temperature and its relevance in food processing. Ann. Rev. Food Sci. Technol., 1: 469±496. ROUSSEAU, D. (2000). Fat crystals and emulsion stability ± a review. Food Research International, 33(1): 3±14. RUDNITSKAYA, A., POLSHIN, E., KIRSANOV, D., LAMMERTYN, J., NICOLAI, B., SAISON, D.,

DELVAUX, F.R., DELVAUX, F. and LEGIN, A. (2009). Instrumental measurement of beer taste attributes using an electronic tongue. Analytica Chimica Acta, 646(1±2): 111± 118. SEWALD, M. and DEVRIES, J. (2003). Shelf life testing. In Medallion Laboratories Analytical Progress. Available at http://www.medallionlabs.com/Downloads/ shelf_life_testing_web.pdf (accessed 4/10/10). SINGH, R.P. and ANDERSON, B.A. (2004). The major types of food spoilage: an overview. In Steele, R. (ed.), Understanding and Measuring the Shelf-life of Food. Cambridge: Woodhead Publishing. SINGH, T.K. and CADWALLADER, K.R. (2004). Ways of measuring shelf-life and spoilage. In Steele, R. (ed.), Understanding and Measuring the Shelf-life of Food. Cambridge: Woodhead Publishing. SIRACUSA, V., ROCCULI, P., ROMANI, S. and ROSA, M.D. (2008). Biodegradable polymers for food packaging: a review. Trends in Food Science & Technology, 19(12): 634±643. STONE, H. and SIDEL, J. (2004). Sensory Evaluation Practices, 3rd edn. Orlando, FL: Academic Press. STUDMAN, C.J. (1997). Factors affecting the bruise susceptibility of fruit. In Jeronimidis, O. and Vincent, J.F.V. (eds), Proceedings of Conference on Plant, University of Reading, Reading, pp. 273±281. SUBRAMANIAM, P. (2000). Confectionery products. In Kilcast, D. and Subramaniam, P. (eds), The Stability and Shelf-life of Food. Cambridge: Woodhead Publishing. SUN, D.-W. (ED.) (2005). Emerging Technologies for Food Processing. London: Elsevier. SZCZESNIAK, A.S. (1998). Effect of storage on texture. In Taub, I.A. and Singh, R.P. (eds), Food Storage Stability. Boca Raton, FL: CRC Press, pp. 191±244.

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and GIANNAKOUROU, M.C. (2004). Temperature and food stability: analysis and contol. In Steele, R. (ed.), Understanding and Measuring the Shelf-life of Food. Boca Raton, FL: CRC Press. TAOUKIS, P.S. and LABUZA, T.P. (1989). Applicability of time±temperature indicators as shelf life monitors of food products. Journal of Food Science, 54: 783±788. TAOUKIS, P., LABUZA, T.P. and SAGUY, I. (1997). Kinetics of food deterioration and shelf-life prediction. In Valentas, K.J., Rotstein, E. and Singh, R.P. (eds), The Handbook of Food Engineering Practice, Boca Raton, FL: CRC Press, pp. 361±403. VAN BOEKEL, M.A.J.S. (2000). Kinetic modelling in food science: a case study on chlorophyll degradation in olives. J. Sci. Food Agric., 80: 3±9. VAN BOEKEL, M.A.J.S. (2008). Kinetic modeling of food quality: a critical review. Comprehensive Reviews in Food Science and Food Safety, 7(1): 144±158. VAN RUTH, S.M. (2001). Methods for gas chromatography-olfactometry: a review. Biomolecular Engineering, 17(4±5): 121±128. VAN ZEEBROECK, M., VAN LINDEN, V., RAMON, H., DE BAERDEMAEKER, J., NICOLAIÈ, B. M. and TIJSKENS, E. (2007). Impact damage of apples during transport and handling. Postharvest Biology and Technology, 45(2): 157±167. Â NOVAS, G.V. (1998). Rheological properties of VEÂLEZ-RUIZ, J.F. and BARBOSA-CA concentrated milk as a function of concentration, temperature and storage time. Journal of Food Engineering, 35(2): 177±190. VESTERGAARD, J.S., MARTENS, M. and TURKKI, P. (2007). Analysis of sensory quality changes during storage of a modified atmosphere packaged meat product (pizza topping) by an electronic nose system. LWT ± Food Science and Technology, 40(6): 1083±1094. VISIOLI, F., BELLOMO, G., MONTEDORO, G. and GALLI, C. (1995). Low density lipoprotein oxidation is inhibited in vitro by olive oil constituents. Atherosclerosis, 117(1): 25± 32. WANG, C.Y. (1989). Chilling injury of fruits and vegetables. Food Reviews International, 5(2): 209±236. WELLS, J.H. and SINGH, R.P. (1992). The application of time±temperature indicator technology to food quality monitoring and perishable inventory management. In Thorne, S. (ed.), Mathematical Modelling of Food Processing Operations, Amsterdam: Elsevier Applied Science. WELLS, J.H. and SINGH, R.P. (1998). Quality management during storage and distribution. In Taub, I.A. and Singh, R.P. (eds), Food Storage Stability, Boca Raton, FL: CRC Press, pp. 369±386. WINGER, R.J. (2000). Preservation technology and shelf life. In Man, D. and Jones, A. (eds), Shelf Life Evaluation of Foods, 2nd edn. Gaithersburg, MD: Aspen Publishers, pp. 73±86. WUTTKE, W., JARRY, H. and SEIDLOVAÂ-WUTTKE, D. (2007). Isoflavones ± safe food additives or dangerous drugs? Ageing Research Reviews, 6(2): 150±188. XIONG, Y. (2000). Protein oxidation and implications for muscle food quality. In Decker, E., Faustman, C. and Lopez-Bote, C.J. (eds), Antioxidants in Muscle Foods: Nutritional Strategies to Improve Quality. New York: John Wiley & Sons. YAM, K.L., TAKHISTOV, P.T. and MILTZ, J. (2005). Intelligent packaging: concepts and applications. Journal of Food Science, 70(1): R1±10. YAN, S., HUAWEI, C., LIMIN, Z., FAZHENG, R., LUDA, Z. and HENGTAO, Z. (2008). Development and characterization of a new amylase type time±temperature indicator. Food Control, 19(3): 315±319. TAOUKIS, P.S.

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and HU, Q.H. (2010). Effect of nano-packing on preservation quality of fresh strawberry (Fragaria ananassa Duch. cv Fengxiang) during storage at 4 ëC. Journal of Food Science, 75(3): C236±C240. YANG, T.C.S. (1998). Ambient storage. In Taub, I.A. and Singh, R.P. (eds), Food Storage Stability. Boca Raton, FL: CRC Press, pp. 435±458. YUAN, S. and CHANG, S.K.C. (2007). Texture profile of tofu as affected by instron parameters and sample preparation, and correlations of instron hardness and springiness with sensory scores. Journal of Food Science, 72(2): S136±S145. YANG, F.M., LI, H.M., LI, F., XIN, Z.H., ZHAO, L.Y., ZHENG, Y.H.

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3 Moisture loss, gain and migration in foods G. Roudaut, University of Burgundy, France and F. Debeaufort, University of Burgundy, France and IUT-Dijon, France

Abstract: The loss, gain and transfer of moisture often affect food materials. Whether arising from interaction with the atmosphere or with another component of the food, such changes always cause deterioration of the overall quality of the food through softening, toughening, breakdown, swelling or shrinkage due to phase transitions or dissolution. In most cases, water migration leads to organoleptic or microbiological changes in the food. With a view to better understanding the physical deterioration of food and to providing a tool for better control of food quality (and therefore of longer shelf life), this chapter reviews the water relationships in foods with particular attention to, and illustration of, glass transition-related phenomena. It also considers examples of foods affected by moisture exchanges with the atmosphere or within the product itself. The mechanisms controlling these migrations are presented together with some experimental approaches (measurements of moisture content, water activity and migration and modelling). Key words: moisture migration, texture, stability, model.

3.1 Introduction: moisture loss, gain and migration in foods and quality deterioration Who has never experienced a shrivelled piece of fruit or a soggy pastry base while eating a cream cake? Whether dry or moist, all foods may be affected by moisture loss or gain during handling or storage. Moisture transfer, which increases or decreases the water content of a food material may affect the food

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through softening, toughening, emulsion breakdown and swelling or shrinkage due to phase transitions such as glass transition, crystallisation or dissolution (Petersen et al., 1999). In most cases, water migration leads to a deterioration of the overall organoleptic or hygienic quality of the food. Moisture transfers compromise the quality, stability and safety of the product and limit its shelf life. Chemical deterioration (e.g. oxidative reactions, hydrolyses) is caused mainly by moisture gain which leads to greater reaction rates due to increased water activity. These aspects are reviewed elsewhere in this book. With a view to better understanding the physical deterioration of food and for the provision of a tool for better control of food quality (and longer shelf life), this chapter will review the water relationships in foods with particular attention to, and illustration of, glass transition-related phenomena. It also considers examples of foods affected by moisture exchange with the atmosphere or within the product itself. The mechanisms controlling these migrations will be presented together with some experimental approaches (measurements of moisture content, water activity and migration and modelling).

3.2

Mechanism of the moisture transfers in food products

3.2.1 General considerations on moisture transfers in foods In all heterogeneous products, water transfer occurs from `wet' to `dry' areas. The water may be in the form of either liquid or vapour, or may form a `reservoir' when in the solid state, as in frozen products. For example, in an ice cream cone, moisture migrates in the liquid and vapour states. To control such transfers, a coating, usually chocolate or fat similar to cocoa, is applied. This controls both the migration of liquid water from the cryo-concentrated solution of the ice cream in contact with the wafer, and the exchange of water vapour inside and outside the cone. It also ensures an airtight seal with the packaging paper or aluminium-paper-based complex. Whatever the physical state of the migrating water, the temperature or the nature of the products, the humidity of the two areas tends to reach an equilibrium. However, it should be noted that the balance is established between the water chemical potentials, often expressed by their water activity, and not between the water contents. Indeed, as shown by Karathanos et al. (1995) when considering the interface between raisins and a brioche dough, the two areas do not balance at the same moisture content and the initially dry area reaches a water content higher than that of the initially wet area (Fig. 3.1). However, when at equilibrium, both sides of a heterogeneous product stabilise at the same water activity of 0.82 when the two areas were initially at 0.95 and 0.4 respectively for dough cereal and raisins. This can be described and predicted from the sorption isotherms and diffusion coefficients of the two areas. By using the sorption isotherms of the two products and knowing their relative proportions in the mixture and the initial water activity, it may be foreseen that the raisins will rehydrate when the dough dehydrates. The adverse effects on the product are numerous: development of mould spores which are naturally present

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Fig. 3.1 Moisture transfer from dough to dry raisins after 3 days contact. Initial water contents and water activities were 0.96 and 55% for the dough, and 0.40 and 20% for the raisins, respectively (adapted from Karathanos et al., 1995).

on raisins, the swelling and bursting of the raisins, drying of the dough and problems with rising during the baking process. This example highlights the fact that the driving force for water transfer is not the differential in concentration or volume, but the differential of the chemical potential of water, generally expressed as the water activity, the mole fraction, or the partial pressure for the gaseous phases. This mechanism of water transfer is described by laws which differ according to the structure of the environment. When considering water migration in a porous open system, i.e. when channels or pores connect both sides of the product, the flow of water is described by Knudsen diffusion, Hage-Poiseuille's law and by Darcy's law as the hydration level increases as shown in Fig. 3.2. Darcy's law equation directly links the water flow rate (F) to the pressure on both sides of the porous film (
p), while taking into account the viscosity (), the density () and the specific environment resistance (R) which depends on the diameter of pores and their tortuosity: 
p Fˆ 
R However, Darcy's law only applies to fluid flowing through the pores of the film, i.e. for very high relative humidity. Indeed, several mechanisms are involved as the moisture level of the medium increases. Thus, as shown in Fig. 3.2, with increasing relative humidity we successively observe: first, a gaseous diffusion of water molecules associated with monomolecular adsorption on the surface of the pores; secondly, moisture disseminated to both the gas in the pores and the surface of the water film adsorbed on the surface of the pores and, finally, a flow as a condensed phase occurs (QueÂnard and SalleÂe, 1991). Although many food products are considered to be porous (cereal products, extruded material or foams such as ice cream or mousse and some vegetables like zucchini or leeks), it appears that this very simple model does not apply

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Fig. 3.2 Moisture transfer mechanism in porous media as a function of the relative humidity or water activity level (adapted from QueÂnard and SalleÂe, 1991).

because the pores never cross the structure of the product throughout its thickness. Most food products have an alveolar or cellular structure instead of truly porous systems. The model which better fits these products is the `simple' diffusion model which usually applies for dense, homogeneous and isotropic products described by Fick's laws (Crank, 1975) and shown in Fig. 3.3. There are two basic types of diffusion. The first is random and uncoordinated molecular motion, often referred to as Brownian motion or self-diffusion. The self-diffusion coefficient of water at the molecular level is commonly measured using pulsed field gradient nuclear magnetic resonance (NMR) spectroscopy and

Fig. 3.3 Diffusion through homogeneous medium: concentration profiles in transient and steady flow rates from Fick's laws, with x ˆ distance and C ˆ concentration.

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magnetic resonance imaging (MRI). The second type of diffusion, which is the focus of this chapter, is directional and reveals a concerted molecular motion which is attributed to the presence of a driving force (e.g., differences in chemical potential), often referred to as flow or bulk diffusion. Determination of the bulk moisture diffusion coefficient (D) of water in food materials is commonly obtained from Fick's laws applied to kinetic data from the three processes of drying, sorption and permeation. Fick's first law applies to a permanent flow rate or steady state (no accumulation, i.e., no change of concentration with time) with unidirectional diffusion and the absence of any chemical reaction.   @C @C @C ‡ ‡ J ˆ ÿD
grad C ˆ ÿD @x @y @z Fick's first law is often simplified as unidirectional to describe the moisture flow (J) or transfer rate (TR) in food or through packaging films as follow: dm dC ˆ ÿD ˆ k
dC J ˆ TR ˆ A
dt dx where J is the moisture diffusion flow or current (kg sÿ1 mÿ2); m is the water mass (kg); t is the time (s); A is the surface (m2); D is the water diffusion coefficient (m2 sÿ1); C is the moisture concentration (kg mÿ3); x is the distance (m) and k is the moisture transfer coefficient (m sÿ1) with k ˆ D=dx. For transient flow rates (variation of mass flux with time), a generalisation of Fick's second law, which is a derivative of the first law, applies:  2  @J @C @ C @2C @2C ˆ ˆD ‡ ‡ ÿ @…x; y; z† @t @x2 @y2 @z2 where D is the moisture diffusion coefficient or diffusivity (m2 sÿ1); C is the moisture concentration (kg mÿ3) as a function of x, y, z and t; x, y and z are the spatial coordinates (m). Solutions to this differential equation can be found for various boundary conditions (Crank, 1975). In all techniques for determining diffusion and mass transfer, water content, water activity and sorption, isotherm measurements are required.

3.2.2 Sorption isotherm characterisation of foods A moisture sorption isotherm maps the complex, product-specific relationship between water content and water activity. Considered as the `fingerprint' of a food product, this isotherm curve (usually S-shaped), shows how water content changes as water activity increases or decreases. The sorption isotherm is the key to understanding and controlling product formulation, product stability, moisture sensitivity, temperature effects and drying characteristics (Simatos, 2002). The relationship between total moisture content and the water activity of a food, considered over a range of values and at a constant temperature, yields a

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Fig. 3.4

Typical food adsorption and desorption isotherms.

moisture sorption isotherm when expressed graphically. This isotherm curve may be obtained in one of two ways (Fig. 3.4): 1. An adsorption isotherm is obtained by placing a completely dry material into differing atmospheres of increasing relative humidity and measuring the weight gain due to water uptake. 2. A desorption isotherm is found by placing initially wet material under the same relative humidity and measuring the weight loss. The adsorption and desorption processes are not fully reversible; therefore, a distinction can be made between the adsorption and desorption isotherms by determining whether the moisture levels within the product are increasing, thus indicating wetting, or whether the moisture is gradually lowering to reach equilibrium with its surroundings, implying that the product is being dried (Simatos, 2002). Sorption isotherms are usually divided into three zones corresponding to different ways in which moisture fixation takes place on the solid substrate as shown in Fig. 3.4: · Zone 1: monomolecular monolayer of adsorbed water on the product surface. This corresponds to the van der Waals interactions between the hydrophilic parts of the product and the water molecules. Water adsorption occurs progressively until it creates a continuous monolayer of water molecules on both the external surface of the product and on the surface of its infractuosities. Water is considered as strongly fixed and in a `semi-rigid' state because of the interactions between water molecules and the surface. The second zone starts when the whole surface is saturated (Van den Berg, 1991). · Zone 2: pluri-adsorption on the initial monolayer. This represents water molecules which are less firmly bound, initially as multi-layers above the

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monolayer. In this zone, water is held in the solid matrix by capillary condensation. This water may act as a solvent for low molecular weight solutes and for some biochemical reactions. The quantity of water that does not freeze at normal freezing temperatures is often associated with this zone. · Zone 3: water in liquid state. Excess water is present in macro-capillaries or as part of the liquid phase in high moisture materials. This exhibits nearly all the properties of bulk water, and thus is able to act as a solvent (Al Muhtaseb et al., 2002). On the basis of the van der Waals adsorption of gases and vapours on various solid substrates, Brunauer et al. (1940), the International Union of Pure and Applied Chemistry (www.iupac.org) classified adsorption isotherms into five general types (Fig. 3.5). The classification of isotherms corresponds to different types of interactions between adsorbed substances and the adsorbent or its porosity. Type I is the Langmuir, and Type II the sigmoid shaped adsorption isotherm. However, no specific names have been attached to the other three types. Types II and III are closely related to types IV and V, with the exception of the maximum adsorption occurring at a pressure lower than the vapour pressure of the gas. However, if the solid is porous and has a significant internal surface, then the thickness of the adsorbed layer on the walls of the pores is limited by the width (diameter and length) of the pores. The form of the isotherm is modified correspondingly and instead of type II and III, is classified as types IV and V. The moisture sorption isotherms of most foods are non-linear, generally sigmoidal in shape, and are classified as type II isotherms. Some mathematical models have been developed for sorption isotherm description as given in Table 3.1. These are often used in models developed for the prediction of mass transfer or diffusion equations.

Fig. 3.5

The IUPAC classification of isotherms.

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Table 3.1

Mathematical expression for sorption isotherm description

Model

Mathematical expression

Langmuir

X ˆ X0

BET Halsey

C
aw 1 ‡ C
aw

X0
C
aw …1 ÿ aw †
…1 ÿ C
ln…1 ÿ aw ††  1=B ÿA X ˆ T
ln…aw † X ˆ

X ˆ A ‡ ‰ B
log10 …1 ÿ aw †Š   ÿln…1 ÿ aw † 1=B Henderson X ˆ A   aw B Oswin X ˆA
1 ÿ aw  1=

Ferro-Fontan X ˆ ln…=aw † Smith

GAB

X ˆ

Reference Brunauer et al. (1940) Aguerre et al. (1989) Halsey (1948) Smith (1947) Henderson (1952) Oswin (1946) Ferro-Fontan et al. (1982)

X0
C
K
aw Guggenheim (1966) ‰…1 ÿ K
aw †
…1 ÿ K
aw ‡ C
K
aw †Š

with C ˆ c0
e
He =R
T and C ˆ k0
e
Hk =R
T Peleg

X ˆ K1
anw1 ‡ K2
anw2

Peleg (1993)

A is a constant (dimensionless), aw, the water activity, B, a constant (dimensionless), C, the GAB model parameter (dimensionless), c0, the constant adjusted to the temperature effect (dimensionless),
Hc, the difference in enthalpy between mono-layer and multi-layer sorption (J molÿ1),
Hk, difference between the heat of condensation of water and the heat of sorption of the multi-layer (J molÿ1), K, GAB model parameter (dimensionless), k0, the constant adjusted to the temperature effect) (dimensionless), n1 and n2, the equation parameters (dimensionless), R, the universal gas constant (8.314 J molÿ1 Kÿ1), r, the equation parameter (dimensionless), T, the temperature (K), X, the equilibrium moisture content (kg kgÿ1 dry solid), X0, the mono-layer moisture content (kg kgÿ1 dry solid), , the equation parameter (dimensionless), , the equation parameter (dimensionless).

3.3 Measuring, monitoring and predicting moisture loss, gain and migrations 3.3.1 Water content measurement The water content of foodstuffs may be determined using either direct or indirect methods. Direct determinations may be based on some physical separation techniques such as distillation, drying or chemical reactions (Mathlouthi, 2001). Indirect determinations rely on the spectroscopic properties of water molecules. This is the case for NMR, infrared and Raman spectroscopy, which are nondestructive techniques, as well as microwave spectroscopy or microwave resonator methods.

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Physical techniques for water content measurement Oven drying over a fixed period (from 1 to 18 h) at a standard temperature (from 102 to 105 ëC) is very often the legal-standard method for the determination of water content. The period of drying is specified for each type of product. The main sources of error or inaccuracy are usually the incomplete removal of water, the loss of volatiles other than water during the drying period, the formation of a crust at the surface of the product which slows down the evaporation of water, the decomposition of the product and the Maillard reaction, which also produces water. Vacuum-oven drying takes place at lower temperatures (70 ëC) for longer periods. This technique is particularly useful in preventing the destruction of heat-sensitive samples. However, the duration of the drying period may not be sufficient to allow the food to reach a steady state as this is strongly dependent on the size of particles. Solvent extraction may be used to extract water from food using an organic solvent having a strong affinity for water prior to its analysis by chemical titration. Chemical analysis of water content Karl Fischer titration is a classical titration method in analytical chemistry which uses coulometric or volumetric titration to determine trace amounts of water in a sample. It was invented in 1935 by the German chemist Karl Fischer. The main compartment of the titration cell contains the anode solution plus the analyte. The anode solution consists of an alcohol (ROH), a base (B), SO2 and I2. Typical alcohols for this purpose are methanol or diethylene glycol monomethyl ether, and a common base is imidazole. The titration cell also consists of a smaller compartment with an anode immersed in the anode solution of the main compartment. The two compartments are separated by an ionpermeable membrane. The Pt anode generates I2 when current is provided through the electric circuit. The net reaction as shown below, is the oxidation of SO2 by I2. One mole of I2 is consumed for each mole of H2O. In other words, two moles of electrons are consumed per mole of water as described in the following equations: BI2 + BSO2 +B + H2O ÿ! 2BH+Iÿ + B+SOÿ3 B+SOÿ3 + ROH ÿ! BH+ROSOÿ3 The end point is detected most commonly by a bipotentiometric method. A second pair of Pt electrodes is immersed in the anode solution. The detector circuit maintains a constant current between the two detector electrodes during titration. Before the equivalence point, the solution contains Iÿ but little I2. At the equivalence point, excess I2 appears and an abrupt voltage drop marks the end point. The amount of current needed to generate I2 in order to reach the end point can then be used to calculate the amount of water in the original sample.

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Volumetric titration is based on the same principles as coulometric titration, except for the anode solution being used as the titrant solution. The titrant consists of an alcohol (R-OH), base (B), SO2 and a known concentration of I2. One mole of I2 is consumed for each mole of H2O. The titration reaction proceeds as above. The end point may be detected by a bipotentiometric method as described above. Quantitative chemical reactions which produce gas may be used to quantify water content, provided that the released gas is accurately analysed. Among these reactions, we find: H2O + CaH2 ÿ! CaO + 2H2 H2O + CaC2 ÿ! CaO + C2H2 The volume of C2H2, which is directly linked to water content, may change as a function of temperature in the analysed medium and is easily determined (Mathlouthi, 2001). Thermal analysis Thermal analysis using either differential thermal analysis (DTA) or differential scanning calorimetry (DSC) may be used in the heating of a frozen sample to determine its freezable water content, which is approximately that fraction of water considered as being mobile or `free'. These techniques also provide information on the physical state of water in foodstuffs, which may be helpful in interpreting the behaviour of the product, for instance, during drying (Mathlouthi, 2001). Gas chromatography Gas chromatography has been applied to the determination of water content in freeze-dried or dried products. However, water has to be extracted by organic solvents before analysis and the sample must be homogeneous. The extraction solvent should have a high affinity for water and be protected from the surrounding atmospheric humidity. Using methanol or dimethylformamide together has proved to be an efficient method of extraction. Generally, Porapaq-Q or Carbowax is used as a stationary phase in the column and a thermal conductivity detector (TCD) or a mass spectrometer is required. This method is relatively quick, but limited to a sensitivity of approximately 10 ppm and inaccuracies are usually due to poor peak separation or water traces in the solvent when the TCD is used. GC-MS now permits a far greater sensitivity, but it remains a technically complex and expensive method. Spectroscopic techniques For all spectroscopic techniques, calibration to standards or products of known water content is required. NMR spectroscopy is informative on hydrogen atoms which are more easily detected in a liquid environment. This technique is better adapted to distin-

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guishing water of different mobilities than to the accurate determination of water content. Moreover, it is necessary to obtain a precise calibration which is specific to the analysed product and based on a good reference method. Timedomain nuclear magnetic resonance (TD-NMR) has proved a quick, reproducible, accurate and non-invasive technique which is particularly well suited to measuring moisture content. Nuclear spin±spin relaxation times (T2) are an excellent probe of molecular mobility, which in turn can be directly correlated to moisture content (Hickey et al., 2006). Near infrared (NIR) absorption of water occurs at different wavelengths (1950, 1450 and 977 nm). The ratios of the intensities of the bands at 1950 and 1450 nm are used to measure water content (Vornhof and Thomas, 1970). Automatic or on-line NIR spectrometers are used in different food industries for the determination of water content as well as for other food constituents such as proteins, fats, minerals, caffeine and sugars. This method requires a specific calibration for the analysed food. Several parameters affect the outcome of the results (colour, particle size, thickness and texture). The reflectance technique allows for the detection of surface water and may not be representative of the whole if the product is not homogeneous. Microwave spectroscopy uses the dipolar character of water molecules. Water content is measured by the shift in wavelength and the attenuation of the amplitude of the waves when a sample is placed between the microwave emitter and receiver. Parameters such as water concentration, density and thickness of the analysed sample, may have an effect on the result. Only mobile water can be measured. The method may be used for on-line measurements when the thickness and permittivity of the sample are known (Isengard, 1995). 3.3.2 Water activity determination Water activity or aw is a measurement of the energy status of water in a system. It is defined as the vapour pressure of water above a sample divided by that of pure water at the same temperature. Therefore, pure distilled water has a water activity of exactly one. Water activity is defined as:     p RH ˆ aw ˆ p0 T 100 T where p is the vapour pressure of water in the food product, and p0 is the vapour pressure of pure water at the same temperature, and RH is the relative humidity above the food sample when equilibrium between product and atmosphere is reached. If there is no difference in the interaction between water and water, and between water and solute, the determination of water activity is easy and its expression becomes: nw ˆ Xw aw ˆ ntotal

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which is directly obtained from the mole fraction Xw of water molecules (nw) to total molecules in the solutions (ntotal). For real solutions, aw ˆ
Xw , where is an activity coefficient. The higher the modification of water binding by the solute, the greater the difference between the coefficient and 1. There are several factors which control water activity in a system: · The colligative effects of dissolved substances (e.g. salt or sugar), which interact with water through dipole-dipole, ionic, and hydrogen bonds. · The capillary effect, where the vapour pressure of water above a curved liquid meniscus is less than that of pure water because of changes in the hydrogen bonding between water molecules. · Surface interactions, in which water interacts directly with chemical groups in undissolved ingredients (e.g. starches and proteins) through dipole-dipole forces, ionic bonds (H3O+ or OHÿ), van der Waals forces (hydrophobic bonds), and hydrogen bonds. It is the combination of these three factors in a food product which reduces the energy of the water and thus reduces the relative humidity when compared to pure water. These factors may be grouped under two broad categories with osmotic and matrix effects. Due to varying degrees of osmotic and matrix interactions, water activity is the term which describes the continuum of energy states of the water in a system. The water appears `bound' by forces in varying degrees. This is a continuum of energy states rather than a static `boundness'. Water activity in a system is sometimes defined as `free', `bound', or `available water'. Although these terms are easier to conceptualise, they fail to adequately define all aspects of the concept of water activity (Van den Berg and Bruin, 1981). Water activity is temperature dependent. Temperature changes the partial water vapour pressure, and then the water activity because of modifications in water binding, the dissociation of water, the solubility of solutes in water, or the state of the matrix. Although the solubility of solutes can be a controlling factor, the state of the matrix is usually more significant. As the state of the matrix (glassy vs. rubbery state) depends on temperature, the temperature affects the water activity of the food. The effect of temperature on the water activity of a food is product specific. While most high moisture foods exhibit negligible aw change with temperature, for some products, water activity increases with increasing temperature and in others, it will decrease with increasing temperature. Therefore the direction of the change in water activity with temperature cannot be predicted, since it depends upon the way in which temperature affects the factors controlling water activity in the food under consideration. As a potential energy measurement, water activity is a driving force for water movement from regions of high to low water activity. For example, if honey (aw  0:6) is exposed to humid air (aw  0:7) it will absorb water from the air. Other examples of this dynamic property of water activity are, as previously described, moisture migration in multi-domain foods (e.g. cracker-cheese sandwiches), the movement of water from soil to the leaves of plants, and cell

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turgor pressure. Since microbial cells have a high concentration of solute surrounded by semi-permeable membranes, the osmotic effect on the free energy of the water is important in determining microbial water relations and therefore growth rates (Fennema, 1985). Most of the methods used for determining the water activity or equilibrium relative humidity (ERH) of foods were originally devised by meteorologists for the measurement of relative humidity in atmospheric air. When water activity (aw) is measured, it is generally necessary to know whether or not the product has reached the critical zone where spoilage reactions may occur. For this reason, accuracy within 0.01 aw is sufficient for most food-related applications (Mathlouthi, 2001). Water activity values are obtained by a capacitance hygrometer, a dew point hygrometer or a mano-vacuometer. Capacitance or resistive hygrometer Capacitance hygrometers consist of two charged plates separated by a dielectric polymer membrane. As the membrane adsorbs water, its ability to hold a charge increases and the capacitance is measured. This value is roughly proportional to the water activity as determined by a sensor-specific calibration. Most volatile chemicals do not affect capacitance hygrometers which can be much smaller than other sensors. They do not require cleaning, but are less accurate ( 0.015 aw) than dew point hygrometers (< 0.01 aw). They require regular calibration and can be affected by residual water in the polymer membrane. Their accuracy is often limited to the range of 0.15±0.97. Novasina has specialised in the accurate measuring of air and material humidity. Their LabMaster AW is very accurate (Fig. 3.6). Due to the newly developed electrolytic measurement cell with saved calibration data as well as a temperature controlled measuring chamber, the instrument determines high precision and repeatable aw values. The integrated pre-conditioning chamber improves the measurement speed and increases the efficiency of the measurement process (www.novasina.com). Dew point hygrometer The temperature at which dew forms on a clean surface is directly related to the vapour pressure of the air. Dew point hygrometers work by placing a mirror over

Fig. 3.6

Principle of capacitive sensor for relative humidity measurement used in the LabMaster AW meter from Novasina (www.novasina.com).

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Fig. 3.7 Chilled mirror dew point principle used in the Aqualab (Decagon, www.decagon.com) and in the FA-st lab (GBX, www.GBXinstru.com) aw meters.

a closed sample chamber. The mirror is cooled until the dew point temperature is measured by means of an optical sensor. This temperature is then used to find the relative humidity of the chamber, using psychrometric charts. This method is the most accurate ( 0.003 aw) and often the fastest. The sensor will require cleaning if debris accumulates on the mirror. The AquaLab Series from Decagon is a lab-grade water activity meter (www.decagon.com). The chilled-mirror dewpoint sensor offers unparalleled accuracy ( 0.003 aw) and an extremely rapid reading time (less than five minutes, including equilibration time). Equivalent apparatus (Fast-Lab) were also developed by GBX, offering similar performance (www.gbxinstru.com) as displayed in Fig. 3.7. Manometric hygrometer As water vapour pressure is given in tables for different temperatures, a direct measurement of water vapour pressure in the food should give the best direct tool for the determination of aw. To achieve this measurement, it is necessary to establish a vacuum and to work at very low temperatures. Working at zero pressure on one side with the moisture freeze trap, and leaving the sample on the other side to release its vapour, permits an accurate measurement of aw. This method requires accurate temperature measurement and the device is extremely fragile (Troller and Christian, 1978).

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Spectroscopy determination of relative humidity The determination of relative humidity in equilibrium above a food product directly gives its water activity. Absorption spectroscopy is a relatively simple method of passing light through a gas sample and measuring the amount of light absorbed at the specific wavelength. Traditional spectroscopic techniques have not been successful at doing this in natural gas because methane absorbs light in the same wavelength regions as water. But by using a very high resolution spectrometer, it is possible to find water peaks that are not overlapped by gas peaks. The Tunable Diode Laser Absorption Spectroscopy (TDLAS) analyser is the only instrument that can meet all the following: the necessity for an analyser that will not suffer from interference or damage from corrosive gases, liquids or solids, that will react very quickly to drastic moisture changes and will remain calibrated for very long periods of time. SpectraSensors, Inc., is a manufacturer of optical-based gas sensors for the industrial processing, environmental monitoring and clean technology markets. The company's sensors measure the absorption of laser light at specific wavelengths to detect carbon dioxide and water vapour (RH or aw) in industrial process control and environmental monitoring applications (www.spectrasensors.com). 3.3.3 Isotherm determination Sorption isotherm determination requires either the water content or the water activity of the product to be measured. Discontinuous methods are most often used in factories and research laboratories. However, automatic systems have been developed and commercialised since the end of the 1990s. Conventional methods Micro-climates gravimetric method The gravimetric method involves the measurement of weight changes. Weight changes can be determined both continuously and discontinuously in dynamic or static systems (i.e., air may be circulated or stagnant). In the discontinuous systems, salt or sulphuric acid solutions are placed in vacuum or atmospheric systems with the food material, to give a measure of the equilibrium relative humidity. A static gravimetric technique was developed and standardised in the Water Activity Group of the European COST 90 project, using saturated salt solutions to control the relative humidity of the atmospheres in contact with the food samples (Jowitt and Wagstaffe, 1989). Continuous methods use electrobalances or quartz spring balances and are the basic principles behind commercial automatic devices. Manometric method The manometric method measures the vapour pressure of water in the vapour space surrounding the food. To improve accuracy, the fluid used in the Umanometer is often oil instead of mercury. The whole system is maintained at a constant temperature and the food sample will lose water to equilibrate with the

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vapour space. This will be indicated by the difference in height on the manometer. Hygrometric method The hygrometric method measures the equilibrium (balanced) relative humidity of air in contact with a food material at a given moisture content, in contrast to the previous methods which measure the water content of sampled equilibrated to fixed RH atmospheres. Dew-point hygrometers or capacitance (or resistive) hygrometers are often used. Diaphragm pressure drop method set up for very high relative humidity range isotherms A fast and accurate method has been set up to measure sorption isotherms of solid foods in the water activity range 0.9±1 by Beaucour and Daudin (2000). This method avoids the main problem generated by the micro-climate technique which is that it is unsuited to high humidity ranges owing to (i) the lack of ventilation which results in excessive equilibration times, and (ii) its inability to produce and control high relative humidities. In a purpose-built device, thin slices of solid material are subjected to a high velocity air flow (more than 10 m sÿ1), at temperatures ranging between 4 and 40 ëC. The relative humidity of the air is controlled by a reduction in total pressure of the saturated air by use of diaphragms. The humid air is obtained from saturated air which is expanded at a constant temperature. The relative humidity of the air may thus be controlled by precisely measuring the total pressure. For constant temperature and water molar fraction, RH1 Ptot1 ˆ , the relative humidity and total pressure vary in the same way: RH2 Ptot2 where Ptot is the total pressure and RH the relative humidity. Air relative humidity is very sensitive to pressure change, whereas the water activity of a food product does not vary significantly and this can be assessed as follows:   aw2 Mw …Ptot2 ÿ Ptot1 † ˆ ln aw1 w
R
T with Mw is the molecular weight of water (kg kmolÿ1), w is the density of water (kg mÿ3), T is the temperature (K) and R is the gas constant (8.134 J Kÿ1 molÿ1). The apparatus has two parts (Fig. 3.8): (i) a saturation column, which produces saturated air, and (ii) a sequence of 10 cells where the samples are placed. By making successive pressure drops from cell to cell, a specific range of air relative humidity can be covered from 0.9 to 1. Automatic commercialised apparatus The Autosorp from Biosystemes is an automatic device for the determination of water sorption isotherms of chemicals, food or biological products based on the gravimetric and micro-climate technique as standardised by the COST-90, which has been on the market since 1985 (www.biosystemes.com). The relative

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Fig. 3.8 General diagram of the experimental device and design of the 10 cells, sample holder and a cross-view of a calibrated diaphragm (from Beaucour and Daudin, 2000).

humidity in the cabinet where the samples are stored is fixed by mixing a wet saturated stream and a dry stream of air, in a range from 2 to 98%. The RH is controlled using a capacitance hygrometer. The temperature ranged from 10 to 45 ëC. Up to 34 samples can be defined simultaneously, with weights ranging

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from 1 to 220 g with a sensitivity of 0.1 mg. Samples are automatically and periodically weighed up to a constant mass which corresponds to the sorption equilibrium. The software can determine the equilibrium time, then automatically changes the RH for the next measurement, either in sorption or desorption determination for a period ranging from a few hours up to ten weeks. An example of results is given in Fig. 3.9. The introduction of the Dynamic Vapour Sorption (DVS) apparatus by Surface Measurement Systems (www.thesorptionsolution.com or www.smsuk.co.uk) in 1994, revolutionised the field of gravimetric moisture sorption measurement, replacing outdated time and labour intensive desiccators with cutting-edge instrumentation and overnight vapour sorption isotherms (Fig. 3.10). It is the main commercialised apparatus, cited and compared to the standardised methods in the scientific literature. Indeed, Yu et al. (2008) compared the performance of the DVS with the saturated salt solution method and concluded that the DVS provides accurate results and allows good estimations of diffusivity (Table 3.2).

Fig. 3.9 Example of sorption and desorption kinetics measured simultaneously on a model food sample (polysaccharide based) and the resulting sorption isotherm.

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Fig. 3.10

81

Schematic design of the DVS apparatus (from www.thesorptionsolution.com).

Table 3.2 Comparison between the saturated salt solution method and the DVS instrument for collecting data for determining the bulk moisture diffusion coefficient (from Yu et al., 2008) Experimental feature Saturated salt solution method DVS instrument Average sample size 1±2 g Experiment time Weeks to months Experiment design Less flexible; discrete relative humidity values dependent on salts selected and experimental temperature Air flow Data collection

Labor Cost

Static to slow movement with use of a fan or stir bar inside the chamber Wt measurements disturb the environmental relative humidity; fewer, discrete data points

5±100 mg Days More flexible relative humidity and temperature control; can obtain absorption and desorption data on the same sample in a short time Dynamic; air continuously flows past the sample

Wt measurements do not disturb environmental relative humidity; numerous, nearly continuous data points (e.g., 30±60 s intervals) More labor intensive (periodic Less labor intensive (instrument weighing of samples for weights sample) weeks to months) Low High

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DVS combines high quality micro-balance, gas flow and vapour measurement technologies to deliver excellent performance in terms of experimental design as well as instrument accuracy and repeatability. The Advantage set up uses a dry carrier gas, usually nitrogen, and the user can select one of any two vapour sources. Precise control of the ratio of saturated and dry carrier gas flow is enabled by mass flow control, combined with the use of unique real-time vapour concentration monitoring for both water and organics. A known concentration of the selected vapour then flows over a sample suspended from a recording ultramicro-balance, which measures the weight change caused by sorption or desorption of the vapour molecule. It is these dynamic flow conditions that enable the sorption/desorption process to be so rapidly studied. DVS allows sample weights from 1 to 150 mg, the weight variation sensitivity is 0.1 g, temperatures range from 5 to 50 ëC, RH can vary from 0 up to 98% with an accuracy of 0.5% and for the organic vapour from 0 to 96% of the saturation with an accuracy of 0.7%. The IGA series from Hidden Isochema is a fully automated benchtop gravimetric analysis system designed to quickly and accurately measure the magnitude and kinetics of moisture sorption by materials (www.hidenisochema.com). The IGA200 Multicomponent Gas/Vapour Analyser is a fully integrated gravimetric sorption analyser designed for dynamic multi-component gas and vapour sorption analysis. In addition to the multiple inlet mass flow controller system for multicomponent gas sorption experiments, the IGA-200 also features a unique multistream vapour generation module, allowing the integration of both gas and vapour inlet streams in pressure control and flow control modes. Anti-condensation protection up to 50 ëC is incorporated in the IGA-200, which allows operation with water and an extensive range of hydrocarbon vapours. The IGA-200 comes complete with a degas heater reactor with an integral refrigerated recirculating water bath for fully automated sample temperature control from ÿ15 to 500 ëC. The combination of the multi-component gas and vapour sorption capability with closecoupled quadruple mass spectrometry makes the IGA-200 the most complete and sensitive sorption analysis system. Using the Dynamic Dewpoint Isotherm method (DDI), AquaSorp from Decagon (www.decagon.com) produces highly accurate adsorption and desorption isotherm curves in 24 hours or less and is affordable for researchers and formulators. In contrast, an isotherm generator will cost around $100,000 and take between two and five weeks to create a single isotherm by hand. The relative humidity ranges from 10% to 90% with an accuracy of 0.5%, and the temperature can vary from 15 to 40 ëC. Very little information is available on this new apparatus which was presented in late 2007. 3.3.4 Measurement of water migration Concentration profile The concentration profile method uses a tube in a standardised design where two cylinders of solid or semi-solid products are brought into contact. These may

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have a different initial water content or activity and may, or may not, be separated by a barrier layer. The compartments can then be thinly sliced at timed intervals and either or both the water content and water activity of these slices be measured (Voilley and Bettenfeld, 1985) by the methods previously described. The concentration profiles are measured over time and distance from the interface in the multi-compartment system and the water transfer is defined through a concentration±distance curve. Nuclear magnetic resonance (NMR) imaging In contrast to the gravimetric methods previously described, NMR allows nondestructive measurements of water migration to be performed. The principle of NMR imaging is to offer spatial information on spins (Ruan and Chen, 1998), thus providing a spatial measurement of NMR parameters (such as T2, for example). When these parameters are sensitive to the moisture content of the sample, the spatial distribution of water in a sample can be defined. The recording of NMR imaging signals at timed intervals enables measurement of changes in moisture distribution within a sample (Ruan and Chen, 1998, Lodi et al., 2007), especially in intermediate and high moisture systems. Stray field nuclear magnetic resonance imaging (STRAFI-NMRI) The application of NMR imaging is generally limited to intermediate and high moisture systems by technical constraints (the necessity of rapidly switching high field gradients) in low moisture systems. However, the technique has been modified to expand its field of application to systems having a high solute concentration (and thus very short T2) (Hopkinson et al., 2001). As explained in detail in Hopkinson et al. (2001), the water profile of the sample can then be obtained either by moving the sample in the field gradient to excite successive slices, or by changing the frequency of the excitation pulse. The water content of the sample is measured as a function of position, by probing the sample with a pulse sequence of varying frequency. This displays the spatial sensitivity of the signal and thus the spatial distribution of the water. 3.3.5 Predicting moisture transport phenomena in food products From foodstuff to surrounding atmosphere and within foodstuff (from a moist area towards an area of lower hydration) Studies have recently been published describing the modelling of moisture transfers by sorption (wetting) and desorption (drying) behaviours, inside compartmented hetereogeneous food products (Guillard et al., 2003; Roca et al., 2008; Bourlieu et al., 2008). These models were established from either sorption experiments and/or the concentration profile methods, assuming the food products to be layers or sheets. Depending on the assumptions made for the description of product deformation and external mass transfer phenomena, four alternative models were developed in order to predict moisture migration inside products, and between

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products and environment, thus determining the effective moisture diffusivity (Roca et al., 2008; Karbowiak et al., 2006a, 2008). Considering the description of the influence of water uptake on the state of the product deformation, the product volume was assumed to remain constant during water sorption (no deformation hypothesis). Secondly, it was assumed that the solid structure of the product would swell according to the local value of moisture content: in this case, the volume occupied by both liquid and solid phases was assumed to be equal to the sum of partial volume occupied by each phase. Equations describing mass transport phenomena were therefore written in a referential (; t) moving at the velocity of the solid phase. The Lagrangian coordinate  is related to the dry matter in the main direction of mass transport (Boudhrioua et al., 2003). Dealing with the description of external moisture transfer (between the product surface and the surrounding environment), the external resistance to mass transfer was assumed to be negligible. The product surface moisture content was then assumed to be constant and equal to the equilibrium moisture content for the relative humidity of the air (no external resistance hypothesis). The external resistance to mass transfer was taken into account using an external mass transfer coefficient (kmass, in m/s), expressing the resistance to diffusion through the mass transfer boundary layer for the vapour emitted by the product surface (external resistance hypothesis). Combining these different assumptions, four models (Table 3.3) were developed for describing mass transport during moisture sorption or desorption experiments in a sample assumed to consist of sheets or thick layers: · · · ·

Model Model Model Model

1: 2: 3: 4:

no deformation and no external resistance to mass transfer. deformation but no external resistance to mass transfer. external resistance to mass transfer but no deformation. deformation and external resistance to mass transfer.

For all models, the system is assumed to be composed of a continuous aqueous phase moving through a solid phase (so-called dry matter). A Fickian theory with a constant moisture apparent diffusivity is used. Whatever the hypotheses chosen to describe product deformation and external mass transfer, the mass conservation equation in the system may be written as the generalised Fick equation. Whatever the time t,     @X @ @X ˆ Deff for 0  x  xmax @t @x @x and Deff

@X ˆ0 @x

for x ˆ 0

at the interface between the food and its surrounding atmosphere (or between two phases of the composite food), where x and Deff are respectively the modified space coordinate (m), and the modified apparent diffusivity (m2/s),

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Table 3.3 Assumptions and boundary conditions of models for effective moisture diffusivity prediction (from Roca et al. 2008) Model 1

Model 2

Model 3

Model 4

Assumptions No deformation No external resistance Eulerian coordinate x Deff ˆ Deff

Simple deformation No external resistance Lagrangian coordinate 

No deformation External resistance

Simple deformation External resistance

Eulerian coordinate X

Lagrangian coordinate 

Deff  Deff ˆ Deff Deff ˆ  0dm 1‡ 0 X x

Deff Deff ˆ  2 0 1 ‡ dm X 0x

Boundary conditions at x ˆ xmax whatever the time t

  @X @X @ ÿdm
Deff ˆ  2 ˆ 0 @x dm 1‡ 0 X x hm M hm M ... ... …aw pvsat † …aw pvsat † RT RT 

X ˆ X1

X ˆ X1



ÿ0dm
Deff

whose expressions depend on the hypothesis chosen to describe the product deformation. This hypothesis influences the nature of the boundary condition at x ˆ xmax . For the four mass transport models developed, the expressions for  and for the boundary condition at the surface of the product may be found in Table 3.2 where Deff stands for the effective diffusivity (m2/s) and dm, 0dm and 0x stand, respectively, for dry matter concentration in the binary mixture (kg mÿ3), pure dry matter and pure water intrinsic densities (kg mÿ3). When the hypothesis of simplified deformation is retained, the Eulerian coordinates xi corresponding to Lagrangian coordinate i are recalculated as follows:  Z i  0dm 1 ‡ 0 X d xi ˆ x 0 Concerning model 1, with the assumption of no deformation and no external resistance to mass transfer, the generalised Fick equation may be solved analytically in the case of an infinite slab; the evolution of moisture content with time is given by Crank (1975):   1 2 X ÿ X1 8X 1 2 
Deff ˆ 2 exp ÿ…2n ‡ 1†

t X0 ÿ X1  nˆ0 …2n ‡ 1†2 L2 where X is moisture content (g/g), X1 equilibrium moisture content (g/g), X0 initial moisture content (g/g), Deff effective moisture diffusivity (m2/s), t time

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Fig. 3.11 Moisture uptake of dry biscuit when put in direct contact with 0.75 aw agar (
), corresponding model fitting (± - ± -); moisture uptake of dry component when put in indirect contact with 0.75 aw agar with hydrophobic barrier at the interface (n), corresponding model fitting (ÐÐ) (from Bourlieu et al., 2008).

(s), and L thickness of the slab (m). When moisture transport occurs only from one surface of the slab, the thickness must be substituted by 2L. Concerning models 2, 3 and 4, with the assumption of a deformation and/or an external resistance, the generalised Fick equation can be solved numerically. The domain 0  x  xmax is divided into N sub-regions of equal thickness
x ˆ xmax =N . The first- and second-order spatial derivatives of the previous system of equations are then discretised. For example, the second-order derivation in the generalised Fick equation once discretised may be expressed as: Deff ;i ‡ Deff ;i‡1 dXi Deff ;iÿ1 ‡ Deff ;i ˆ
…X ÿ X † ‡
…Xi‡1 ÿ Xi † iÿ1 i dt 2
x2 2
x2 These models were solved and usually applied to experimental data through MatlabÕ algorithms. Figure 3.11 shows how the moisture migration model is effective in describing the moisture uptake of dry biscuits in direct contact with a wet agar gel phase. Through barrier packaging and/or edible coatings In dense materials, small molecules will permeate thin layers (such as packaging films or edible films and coatings), implying a molecular diffusion due to the chemical potential differential between the two sides of the layer (Chao and Rizvi, 1988). The moisture transfer mechanism follows a three step-process: 1. sorption, whether coupled or not to condensation, 2. diffusion of the solute in a liquid state, and 3. desorption whether coupled or not to evaporation (Fig. 3.12). Sorption and desorption are considered as instantaneous, whereas condensation and/or evaporation require energy for the diffusion process. The whole phenomenon of mass transfer through barrier layers is usually described by simplified first Fick's laws:

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Fig. 3.12 The three-steps mechanism of moisture transfer through barrier layers.

TR ˆ ÿD

@C
m ˆ @x A

t

where TR is the transfer rate (g mÿ2 sÿ1), D the diffusivity (m sÿ1), C the concentration (g mÿ3), x the distance (m),
m the weight variation (g), A the surface exposed to the transfer (m), and t the time (s). In the case of gases and vapours, Henry's law gives the relationship between the concentration in the solid or liquid phase and the vapour pressure. It represents the partition coefficient between the condensed and vapour phases. The Henry coefficient S is also called the solubility coefficient. The value of concentration can be related to the vapour pressure, giving a transfer rate equation which can be expressed as: TR ˆ ÿD

@C @p ˆ ÿD
S
@x @x

and the permeability coefficient is defined as P ˆ D
S, where S is the solubility coefficient (g mÿ3 Paÿ1), and p the partial vapour pressure (Pa). It therefore appears that permeability depends on both a kinetic parameter (diffusivity which represents the migration speed of the migrant molecule within the barrier layer), and a thermodynamic parameter (the solubility (sorption) coefficient which represents the affinity of the migrant molecule for the barrier layer). The water vapour permeability (WVP) is often expressed as a function of the water vapour transfer rate (WVTR) related to the thickness (L) and the vapour pressure differential at both faces of the barrier layer: L WVP ˆ WVTR

p Elsewhere, the water activity is defined as the ratio of vapour pressure:   p RH aw ˆ ˆ p0 T 100 The water transfer rate can be expressed as: WaterTR ˆ ÿD
S

@p @aw
aw ˆ P
p0 ˆ k
A

aw ˆ ÿD
S
p0 @x L @x

where k is the overall mass transfer coefficient. However, knowledge of the sorption isotherm (solubility coefficient) and of the moisture diffusivity in packaging films is necessary to predict permeability.

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Sorption may be measured using the previously described methods. The diffusivity coefficients of moisture in films may be measured according to several techniques. Moisture diffusivity in packaging films may be measured from the permeation kinetics according to Felder's solutions of Crank's equations (Felder, 1978). In the case of integral permeation which plots the cumulative amount of water vapour transferred through the film as a function of time, the diffusivity of moisture is equal to D ˆ L2 =…6
† where  is the time lag before the constant transfer rate (stationary flow) is reached. When the transfer rate is directly measured through continuous techniques (differential permeation), the moisture diffusivity is determined from D ˆ L2 =…7:199
t1=2 †, where t1/2 is half the time taken to reach the stationary phase of the permeation process. When no apparatus for permeability measurement is available, the diffusivity can be determined from the sorption or desorption kinetics from the following solution of the second Fick's law solved by Crank (1975): " # 1 M1 ÿ Mt 8X 1 …2n ÿ 1†2 2 DA t ˆ exp ÿ M1 ÿ M0 2 nˆ1 …2n ÿ 1†2 4L20 These methods for the diffusivity of moisture in packaging only apply for water vapour transfer. However, most foods contain liquid water and are in direct contact with the barrier films. The permeability of films by water sometimes depends on the physical state of water in contact with the packaging as shown by Morillon et al. (1998, 2000). Indeed, the liquid transfer rate through most packaging films is often much greater than that of water vapour permeability, and permeability is always measured for water vapour (Fig. 3.13). This discrepancy between liquid and vapour permeability for the same activity differential is called Schroeder's paradox. Karbowiak et al. (2008) proposed techniques ranging from the macroscopic to the molecular scale for the measurement of moisture diffusivity in films. The concentration±distance curves (or concentration profiles) method consists of bringing two cylinders of solid or semi-solid products into contact, either of which may contain a different initial water content or activity, and which are separated by the barrier layer. The concentration profiles are measured from their distance to the interface, as a function of time, along a onedimensional axis. From experimental kinetics obtained along the x-axis, and assuming D to be constant and independent of the concentration, the simplest analytical solution to Fick's second law can be applied (Crank, 1975) in order to estimate D app for the different times from a simple measurement of concentration at different points of the system: C ÿ C1 x ˆ erf p C0 ÿ C1 2 Dapp
t where erf …x† is the integral error function (Karbowiak et al., 2008). The possibility of studying mass transfers in edible films is considered at a mesoscopic scale using goniometry (Karbowiak et al., 2006b), which entails

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Fig. 3.13 Schroeder paradox: discrepancies of moisture transfers through cellulosebased and polyethylene films as a function of the state of water in contact with the films while the water activity gradients are the same (from Morillon et al., 2000).

investigation on a square-millimeter scale. The wetting phenomenon of a solid surface by a liquid was initially described by Young 200 years ago as the thermodynamic equilibrium measurement of the contact angle (Young, 1805). Although the value of the contact angle gives information on the surface hydrophobicity, it is not directly informative on transfers. However, the use of this technique in a dynamical way enables one to define mass transfers occurring on the surface of the studied material (Muszynski et al., 2003; Karbowiak et al., 2006b). In this case, it is important to take into account the evaporation flux involved at the liquid/air interface in order to correctly determine the absorption flux occurring at the solid/liquid interface. The investigation achieved by goniometry permits a rapid determination of the absorption flux of liquids within the tested materials and identification of the role of various constituents on the surface properties of the films. This approach is more relevant to food products in which more water is in a liquid state, as compared to vapour permeability. Fourier transform infrared (FTIR) spectroscopy is a very useful analytical technique, particularly for the identification of chemical groups within a molecule. Using the attenuated total reflectance (ATR) mode enables one to detect the chemical composition of a film surface. The infrared radiation penetrates the surface of the film in contact with the crystal. By putting liquid water on the other side of the film, the detection of a characteristic absorption band of water molecules enables the monitoring of water absorption over time. It then becomes possible to determine the apparent diffusion coefficient of water in the film, assuming a Fickian mechanism. This original approach has been developed by Fieldson and Barbari (1993), studying water diffusion in polyacrylonitrile. Diffusivity values obtained by this method are in accordance with those obtained

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from gravimetric measurements and have been recently applied by Karbowiak et al. (2009) for moisture diffusivity measurement through thin biopolymer films. The increasing absorption of the hydroxyl band is thus characteristic of the water transfer occurring through the film. The observed phenomenon can be described by the classical Fickian diffusion equation through a membrane of L thickness, with a uniform initial distribution, and different surface concentrations. It may be solved using an analytic solution to Fick's law as applied to the transient state (Crank, 1975): " # 1 X Mt 8 ÿD…2n ‡ 1†2 2 t ˆ1ÿ exp 2 2 M1 4L2 nˆ0 …2n ‡ 1†  In this case, the absorbance ratio At =A1 , obtained from the integration of the corresponding infrared absorption spectra, can be used in place of the mass ratio. However, such a classical Fickian model does not fit the data, because of structural changes or penetration depth of the detection IR beam. In this case, other factors need to be integrated to the model. 1. The penetration depth of the infrared radiation, dP:  s dp ˆ  2 n2 2
n1
sin2  ÿ n1 with n1 ˆ refractive index of the crystal (ZnSe), n2 ˆ refractive index of the packaging film,  ˆ angle of the incident radiation, and  ˆ wavelength of the radiation. 2. The field evanescence, E:   x E…x† ˆ E0 exp ÿ dp E decreases exponentially as a function of the distance to the surface of the crystal. The integration of these parameters into Fick's diffusion equation leads to the following model: At 8     ˆ1ÿ L A1 dp 1 ÿ exp ÿ2 dp !    3 ÿD…2n ‡ 1†2 2 t …2n ‡ 1† L n 2 ‡ …ÿ1† exp exp ÿ2 6 1 4L2 2L dp dp 7 X 6 7 6 7 ! exp6  2 7 4 5 4 …2n ‡ 1† nˆ0 …2n ‡ 1† 2 ‡ dp 2L 2

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Fig. 3.14 Diffusion coefficient calculated from moisture absorption in edible carrageenan-based films determined from ATR-FTIR:  experimental values, ÐÐ calculated values (from Karbowiak et al., 2009).

When these factors are taken into account, the model makes a good fit with the experimental values and allows an accurate prediction of moisture diffusivity in thin barrier layers as shown in Fig. 3.14. Knowledge of the solubility and diffusivity or permeability of moisture in film makes it possible to predict the shelf life of moisture-sensitive food products. Initially developed for the prediction of the shelf life of products packaged in plastic flexible or semi-rigid packaging, there are several simple models which also fit well with coated foods. These consider edible films and coatings as conventional packaging and take into account the characteristics of the food product, the surrounding medium, and the barrier layer (Labuza, 1982; Cardoso and Labuza, 1983; Hong et al., 1991). For instance, for water it is necessary to know: 1. the film permeability (WVP), or the water vapour transfer rate (WVTR) of the coatings, as well as the coating thickness; 2. the dry matter of the product to be coated, its initial and critical water contents, its sorption isotherm, and possibly its density and moisture diffusivity; 3. the water activity of the wet area and its possible diffusivity. These methods consist of evaluating the amount of transferred water necessary to induce product degradation, such as, e.g., the loss of crispness in a dry biscuit, and determining the time necessary for that amount of water to go through the coating (Debeaufort et al., 2002). The simplest model uses the water transfer rate and the critical water content of the dry part of the product according to the following equation: time ˆ

…Mc ÿ Mi †
m …Mc ÿ Mi †
m ˆ
L WVTR
A WVP
A

p

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Fig. 3.15 Schematic representation of shelf life prediction for a model of a wrapped food (dry biscuit) in a plastic film or of a composite food (stuffed biscuit) whose dry and wet compartments are separated by a barrier coating.

In this equation, WVTR is the water transfer rate (g mÿ2 sÿ1), A is the surface exposed to the transfer; L is the coating thickness (m); m is the dry matter of the product (g); Mi and Mc are respectively the initial and critical water contents; and
p is the water vapour partial pressure differential across the barrier. However, this model supposes that the water activity differential between the two faces of the coating remains constant over storage, which in reality never occurs. The progressive change in the water activity in the dry area (e.g., a cereal-based biscuit) has to be taken into account from the sorption isotherm modelled as linear between the initial and critical water contents if the predictions are to accord with reality (Labuza and Contreras-Medellin, 1981). Parameters used in this model are illustrated in Fig. 3.15, where Mi, Mc and Me are the initial, critical and equilibrium water contents, respectively; awi, awc, awe are the water activities; and bs is the slope of the linear-considered sorption isotherm between the initial and critical moisture content points. In an attempt to consider the water activity variation in the dry area, Labuza and Contreras-Medellin (1981) and Labuza and Altunakar (2007) suggested the following equation:   Mi ÿ Me ln Mi ÿ Me P
A
p0 Mc ÿ Me
time then time ˆ ˆ
L
m
b ln P
A
p0 Mc ÿ Me L
m
b In this equation, P is the coating permeability (g mÿ1 sÿ1 Paÿ1), A is the exposed surface (m2), p0 is the saturated vapour pressure at the experiment temperature, L is the coating thickness (m), m is the dry matter of the product (g), and b is the average slope of the sorption isotherm of the dry area (gwater/gproduct). This model was used by Biquet and Labuza (1988) for chocolate coatings applied between agar-gel and microcrystalline cellulose. Morillon et al. (1998) also compared the estimated shelf life calculated from this latter model, with

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Fig. 3.16 Prediction of moisture transfers in composite foods: application of cocoabased coatings to sugar wafer in contact with ice-cream at ÿ10 ëC (bars are estimated values from Contreras-Medellin and Labuza model and triangles are experimental values obtained from sensory analysis).

experimental values determined from sensory experiments for a wafer coated with a cocoa-based coating, as shown in Fig. 3.16. Even though many models have been developed for predicting either moisture diffusivity, sorption, permeability or shelf life of food in relation to moisture transfers, most of the works dealing with the control of moisture transfer between foods and the surrounding atmospheres, or between different areas within a composite food (sandwiches, stuffed biscuits, meat pies, etc.) remain empirical.

3.4

Moisture loss, gain and migration related to the shelf life

Water controls many properties of food materials at both the molecular and macroscopic levels. Such a role in both thermodynamic and dynamic properties is due to the interaction of water with the other food components. Food materials usually exist either in a liquid state (in solution or above melting temperature) or in a solid form. In the latter state, products may be either in the thermodynamically stable crystalline state or in the amorphous state (which is not a true equilibrium). Water uptake affects the structure of solid food through its plasticising effect which consists of the replacement of solute±solute interactions by solute±water interaction. This results in a softening, or even the dissolution of the material of increased hydration. Water relationships are particularly important in amorphous food systems. Such products are numerous, as many processes (baking, dissolution/drying) lead to a loss of crystallinity, which causes many foods to become amorphous below or above their Tg under storage conditions. Due to the plasticising effect of water, the glass transition temperature decreases with increasing water activity or content. Thus a food area which was initially glassy (hard and brittle)

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will become rubbery (malleable) following a moisture-induced decrease of Tg below the ambient temperature. The physical properties of the foods will then be particularly affected by water migration. 3.4.1 Plasticisation A decrease of Tg below the ambient or working temperature results in a marked decrease in the rigidity of the hydrated product which is then plasticised. However, in certain cases, water may exhibit an anti-plasticising effect. Instrumental and sensory measurements have shown that for many products, rigidity increases with increasing water activity in a limited humidity range, generally below 11% of water (Kapsalis et al., 1970; Harris and Peleg, 1996; Roudaut et al., 1998; Suwonsichon and Peleg, 1998; Valles-Pamies et al., 2000; Waichungo et al., 2000). Indeed, water keeps its ability to decrease the glass transition temperature. This mechanism, described as anti-plasticising for its opposite effect to plasticisation, is of practical importance but its physical origin is as yet not fully understood. 3.4.2 Crispness Among the textural changes occurring due to water migration or water activity changes, crispness is a well-known critical property. By definition, this attribute of texture may be associated with a combination of the high-pitched sound and the crumbling of the product as it is crushed through. Such behaviour is generally encountered with puffed and brittle food products at low hydration (<10% of water or aw < 0.55). This texture is generally associated with a solid foam structure in which mechanical properties are determined by the foam characteristics and the viscoelastic properties of the cell walls. If the moisture content of the product increases, a loss of crispness will be observed (Nicholls et al., 1995). Since crispness is associated with freshness and quality, its loss is a major cause of rejection by consumers. Pioneering works on the effect of water on crispness were presented by Brennan et al. (1974), followed by Katz and Labuza (1981), and Sauvageot and Blond (1991), in studies presenting sensory crispness and mechanical data for snacks and breakfast cereals equilibrated at different water activities. A great number of studies have followed on this topic (Tesch et al., 1996; Peleg, 1998 and references therein; Roudaut et al., 1998) with a view to predicting the effect of water on crispness or suggesting the physical basis for such effects. As illustrated in Fig. 3.17 for maize extrudates characterised at first bite by a sensory panel, the effect of water (aw) on crispness is sigmoidal in shape and described by a Fermi equation (Peleg, 1994), expressed as: Y a0 ÿ a  Yˆ w wc 1 ‡ exp b

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Fig. 3.17 Sensory crispness of starch-based extrudates versus water activity (VallesPamies et al., 2000).

where Y is crispness, Y0 crispness in the dry state, awc the critical water activity or water content corresponding to Y ˆ Y0 =2, and b is a constant expressing the steepness of the transition. Several explanations have been suggested to explain such a change in texture: change in fracture mechanism (brittle to ductile behaviour) (Kirby et al., 1993), glass transition (Ablett et al., 1986; Slade and Levine, 1993; Roos et al., 1998; Nikolaidis and Labuza, 1996), and localised motions preceding the glass transition (Hutchinson et al., 1989; Attenburrow et al., 1992; Wu, 1992; Kaletunc and Breslauer, 1993; Nicholls et al., 1995; Le Meste et al., 1996; Li et al., 1998). The effect of hydration (through water activity or water content) on the crispness of cereal-based products varies with the formulation or recipe of the sample. As an example given in Fig. 3.17, extruded waxy maize exhibits a loss of crispness centred at aw of 0.40, whereas the critical water activity is 0.75 when the extruded waxy starch contains 20% sucrose (Valles-Pamies et al., 2000). Such behaviour cannot be explained by glass transition, since the sugar-rich sample has a lower Tg than the pure starch sample, but a greater crispness at the highest aw. 3.4.3 Softness The influence of water on the mechanical properties described for low moisture cereal products under increasing hydration can also be considered for high or intermediate moisture (above 25% water) cereal products which are exposed to lower humidity atmospheres (below aw of 0.6). Bread-like or sponge cake-like products exhibit visco-elastic behaviour similar to that of synthetic polymers (Levine and Slade, 1990; Slade and Levine, 1993; Le Meste et al., 1992). At their original moisture content (>25%), in the rubbery plateau region, they are soft at room temperature and not very sensitive to changes in moisture content (Roudaut, 2007). They become progressively

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more leathery as moisture content decreases. Finally, below 20% moisture (this critical value depends, of course, on their composition), as their Tg becomes greater than ambient temperature, their Young's modulus increases sharply and they become brittle. 3.4.4 Stickiness, caking and collapse Generally used to describe powder behaviour at a macroscopic scale, caking (formation of hard masses of greater size) might be observed as being a result of stickiness, when individual solids of a free flowing powder stick to one another and ultimately form a mass of solids. The two main conditions under which caking is known to occur are drying and storage. However, the key parameter of the phenomenon is the same: a critical hydration level. When powder hydration increases, the surface viscosity of particles falls below 108 Pa s (Downton et al., 1982) which tends to cause a merging with neighbouring particles through interparticle liquid bridging. The latter will take place if sufficient flow occurs during contact and the bridge resists subsequent deformation. Caking can be evaluated by a caking index which corresponds to the amount of a sample (expressed as a percentage) retained by a given mesh. Figure 3.18 shows the effects of humidity on the caking kinetics of fish hydrolysates: the higher the humidity (or temperature) the higher the caking index (Aguilera et al., 1993). These structural changes will also be accompanied by changes in physical properties, such as an alteration of the visual aspect, flowability and water dispersibility. Caking and structure collapse processes generally occur in products with high levels of soluble sugars, minerals or protein hydrolysates (such as milk powders, instant coffee, and dehydrated fruit juices). Structural collapse is driven by the same mechanisms as caking and should be seen as an advanced stage of caking. As a result of the lower viscosity, the walls

Fig. 3.18 Caking index versus time for fish protein hydrolysates stored at various aw at 30 ëC (adapted from Aguilera et al., 1993).

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of the porous material become closer and the inter-pore space which controls the porosity of the material is progressively lost, leading to a more compact, collapsed material. 3.4.5 Crystallisation Given the threshold molecular mobility (both rotational and translational) required for crystallisation to take place, it is generally accepted that mobility below Tg is not sufficient to allow crystallisation. When water activity increases, the solute molecules become increasingly mobile and collide in the correct orientation for the formation of a nucleus. This is the starting point for crystallisation which eventually spreads to the entire matrix. Anhydrous crystal formation would expel water from the matrix, and depending on the close environment of the sample, the water molecules will diffuse towards the neighbouring phase or to the atmosphere when exposed to the open air. Among the products other than spray-dried milk powders (which are the subject of most publications on crystallisation in foods) for which crystallisation is particularly critical, ice cream, hard candies, soft cookies and baked products can be mentioned. The crystallisation rate compared with the temperature is known to exhibit a maximum between Tg and the melting temperature Tm: at low temperatures, the high viscosity hinders the diffusion required for crystal growth, whereas nucleation is limited at a temperature approaching Tm. A similar bell-shape behaviour has been described for isothermal crystallisation rate as a function of water content (Roos, 1995).

3.5 Conditions for moisture migration and foods affected by moisture transfer As soon as a relative humidity (RH) gradient (or water activity gradient) exists between a food and its environment, or between two food areas, there will be water migration: water will diffuse from the high to the low RH phase until equilibrium is reached between the two phases. Two situations exist for the occurrence of moisture migration: moisture transfer with the atmosphere and moisture transfer within the product. 3.5.1 Moisture transfer with atmosphere Water transfer may take place between the food and the surrounding atmosphere. Packaging has been developed to prevent various exchanges with the atmosphere and the permeability of the packaging material will control the dynamics of these transfers. The best candidates with regard to moisture exchange with the atmosphere are the food products having an RH range very different from the ambient RH. Owing to their high optimal storage RHs (85±95% and 90±98% respectively for fruits and vegetables), these foods are prone to moisture loss when stored under

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normal conditions. Moisture loss or uptake causes wilting, shrinkage and loss of the firmness, crispness and succulence of the product. However, too high a moisture barrier will cause a high RH in the packaging, leading to microbial growth (Petersen et al., 1999). Owing to the changes in water chemical potential values with temperature, refrigerated or frozen products are likely to be subject to moisture migration. Dehydration of unwrapped butter (aw: 0.75 at 25 ëC, Shukla et al., 1994) is quite usual when stored in the fridge. As a result, the surface of the butter dries out and becomes more yellow, which is often seen by the consumer to be an indication of lower quality. In cheeses such as Brie or Camembert, water exchanges with the environment must be maintained if the surface flora is to be kept alive and avoid an alteration in the appearance and organoleptic properties (Mousavi et al., 1998). The optimisation of packaging for such products is therefore of primary importance. Similarly when frozen products are submitted to temperature variations during storage, they may suffer from moisture migration to or from the atmosphere within the pack. This results either in freezer burns (when the surrounding temperature is greater than that of the food) or in frost deposition at the surface of the products (when the temperature of the latter is lower than that of the atmosphere). Moisture loss through sublimation from the surface of the product leads to freezer burns and this is avoided by using packaging material which is highly impermeable to water vapour and sticks tightly to the surface of the frozen food. In general, moisture exchange will impair the visual appearance of the product and lead to unacceptable changes in the weight of the product. 3.5.2 Moisture transfer within the product Owing to the RH gradient existing between different areas, composite food materials are excellent candidates for moisture migration between the different parts of the food itself. Multi-domain systems may be encountered at different levels: molecular or macroscopic (Labuza and Hyman, 1998). Different examples of macroscopic or composite materials which are candidates for moisture transfer are: genuinely multiple layer foods, or multiple food components packed together in a single container (breakfast cereals, salad or soup mixes). The difference between the two categories may be defined by the extent of the contact between the components. Multi-component foods are generally designed to have attractive contrasts of texture. These are controlled primarily by the association of multiple components which differ in texture, such as in-filled products (breakfast cereals, biscuits, sandwiches, ice cream wafers), dairy products with fruits and/or cereal balls and soups with croutons. Textural contrasts are generally achieved by differences in structure and/or composition with water being a key ingredient. One of the simplest examples of such contrast is bread. The contrast between the soft crumb and the crisp crust results from the baking process, during which

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Fig. 3.19 Moisture transfer in bread from crust to centre as a function of time (adapted from Piazza and Masi, 1995).

the surface of the bread is exposed to a higher temperature than the crumb. This causes both a RH and water content gradient between the bread surface and its core which is responsible for a change in the moisture distribution in the bread over time (Fig. 3.19) (Piazza and Masi, 1995). This is the cause of the familiar result of a softened crust and a stiffened crumb. It should be mentioned that starch retrogradation (recrystallisation) also contributes significantly to textural changes in the crumb as it is likely that the lower water content will have an effect on the starch reorganisation (Baik and Chinachoti, 2000). The aforementioned molecular level at which moisture migration may occur has also been described as playing a part in the deterioration of bread during storage. It has been claimed that moisture migration from gluten to starch occurs in the early stage of crumb evolution (Chen et al., 1997). When considered separately, the different components of composite foods (for example, a biscuit and a strawberry jam filling) differ in their water content and thus often by their water activity (respectively 0.4 and 0.84). When in contact with a multilayer food, water will migrate from the jam to the cake, inducing a softening of the cake and a thickening of the jam as a result of increasing concentration and the consequent crystallisation of sugar. Moreover, the latter may exacerbate the loss of quality, since sugar crystallisation may cause syneresis from the filling. Similarly, composite foods such as dairy products or ice creams (both of which have high RH) with confectionery additions (lower RH) will also be affected by moisture migration between the components. As a result, the added sugary components will lose their edible quality, becoming soft or even disappearing through dissolution into the surrounding aqueous environment. In some cases, the migration may have a deleterious impact on the other component which originally had the greater RH. Indeed, its decreased hydration may promote solute crystallisation in the vicinity of the addition. Increased granularity in ice cream may result from lactose crystallisation caused by the partial `dehydration' of the ice cream, to the benefit of the added components.

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Avoiding or limiting the above mentioned physical and chemical changes resulting from water uptake or loss may be achieved by controlling moisture migration into foods, or between the different components of the food. As the water activity gradient is one of the driving forces for moisture migration, one of the main solutions for stability in composite foods consists of limiting the gradient which exists between the components, often by lowering the water activity of the moist phase. This is generally achieved by the use of solutes, such as sugars, salts or polyols, which interact strongly with water, thus depressing the water activity of the highest RH phase. The use of humectants is generally limited by their solubility (no effect above saturation concentration), their reactivity (e.g., reducing sugars will result in the Maillard reaction), their effect on texture and taste and by regulatory requirements. Further information on water activity is given in the course of this chapter. There are many textbooks on water activity itself, and on water activity in foods which may be referred to for further information (Barbosa-CaÂnova et al., 2007, and references therein) on ways of manipulating water activity gradients. In addition to the thermodynamic control of moisture migration, the dynamic properties of food may also provide a means of influencing the extent of water transfer (Labuza and Hyman, 1998). The kinetics of water changes may be affected by the matrix composition and structure (through an increased viscosity, and decreased diffusivity of water) or by the application of a water barrier between the phases of differing water activity.

3.6

References

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and PELEG M (1996), `Patterns of textural changes in brittle cellular foods caused by moisture sorption', Journal of Texture Studies 73: 225±231. HENDERSON SM (1952), `A basic concept of equilibrium moisture', Agricultural Engineering 33: 29±32. HICKEY H, MACMILLAN B, NEWLING B, RAMESH M, VAN EIJCK P and BALCOM B (2006), `Magnetic resonance relaxation measurements to determine oil and water content in fried foods', Food Research International 39: 612±618. HONG YC, KOELSCH CM and LABUZA TP (1991), `Using the L number to predict the efficacy of moisture barrier properties of edible coating materials', Journal of Food Processing and Preservation 15: 45±62. HOPKINSON I, JONES RAL, MCDONALD PJ, NEWLING BA, LECAT A and LIVINGS S (2001), `Water ingress into starch and sucrose:starch systems', Polymer 42: 4947±4956. HUTCHINSON RJ, MANTLE SA and SMITH AC (1989), `The effect of moisture content on the mechanical properties of extruded food foams', Journal of Material Science 24: 3249±3253. ISENGARD HD (1995), `Rapid water determination in foodstuffs', Trends in Food Science and Technology 6: 155±162 JOWITT P and WAGSTAFFE PJ (1989), The Certification of the Water Content of Microcrystalline Cellulose at 10 Water Activities. Commission of the European Communities, Community Bureau of Reference, CRM 302, EUR 12429 EN. KALETUNC G and BRESLAUER KJ (1993), `Glass transition of extrudates: relationship with processing-induced fragmentation and end-product attributes', Cereal Chemistry 70: 548±552. KAPSALIS JG, WALKER JE and WOLF JC (1970), `A physico-chemical study of the mechanical properties of low and intermediate moisture foods', Journal of Texture Studies 1: 464±483. KARATHANOS VT, KOSTAROPOULOS AE and SARAVACOS GD (1995), `Diffusion and equilibrium of water in dough/raisin mixtures', Journal of Food Engineering 25: 113± 121. KARBOWIAK T, DEBEAUFORT F, CHAMPION D and VOILLEY A (2006a), `Wetting properties at the surface of iota-carrageenan-based edible films', Journal of Colloid and Interface Science 294(2): 400±410. KARBOWIAK T, HERVET H, LEGER L, CHAMPION D, DEBEAUFORT F and VOILLEY A (2006b), `Effect of plasticizers (water and glycerol) on the diffusion of a small molecule in iota-carrageenan biopolymer films for edible coating application', Biomacromolecules 7(6): 2011±2019. KARBOWIAK T, GOUGEON R, RIGOLET S, DELMOTTE L, DEBEAUFORT F and VOILLEY A (2008), `Diffusion of small molecules in edible films: effect of water and interactions between diffusant and biopolymer', Food Chemistry 106(4): 1340±1349. KARBOWIAK T, DEBEAUFORT F, VOILLEY A and TRYSTRAM G (2009), `From macroscopic to molecular scale investigations of mass transfer of small molecules through edible packaging applied at interfaces of multiphase food products', Innovative Food Science and Emerging Technologies 10: 116±127. KATZ EE and LABUZA TP (1981), `Effect of water activity on the sensory crispness and mechanical deformation of snack food products', Journal of Food Science 46: 403±409. KIRBY AR, PARKER R and SMITH AC (1993), `Effects of plasticizers on the fracture behaviour of wheat starch', Special publication of the Royal Society of Chemistry 133: 250. HARRIS M

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and ALTUNAKAR B (2007), `Diffusion and sorption kinetics of water in foods'. In Barbosa-Canovas GV, Fontana AJ, Schmidt SJ and Labuza TP (eds), Water Activity in Foods: Fundamentals and Applications, Blackwell Publishing, Oxford, 215±237. LABUZA TP and CONTRERAS-MEDELLIN R (1981), `Prediction of moisture protection requirements for foods', Cereal Food World 26: 335±343. LABUZA T and HYMAN CR (1998), `Moisture migration and control in multi-domain foods', Trends in Food Science and Technology 9: 47±55. LE MESTE M, HUANG VT, PANAMA J, ANDERSON G and LENTZ R (1992), `Glass transition of bread', Cereal Food World 37: 264±267. LE MESTE M, ROUDAUT G and ROLEÂE A (1996), `Physical state and food quality ± an example: the texture of cereal-based-foods'. In Fito P, Ortega-Rodriguez E and Barbosa-CaÂnovas GV (eds), Food Engineering 2000, Chapman and Hall, New York, 97±113. LEVINE H and SLADE L (1990), `Influence of the glassy and rubbery states on the thermal, mechanical, and structural properties of doughs and baked products'. In Faridi H and Faubion JM (eds), Dough Rheology and Baked Product Texture, Van Nostrand Reinhold, New York, 157±330. LI Y, KLOEPPEL KM and HSIEH F (1998), `Texture of glassy corn cakes as function of moisture content', Journal of Food Science 63: 869±872. LODI A, ABDULJALIL A and VODOVOTZ Y (2007), `Characterization of water distribution in bread using magnetic resonance imaging', Magnetic Resonance Imaging 25: 1449±1458. MATHLOUTHI M (2001), `Water content, water activity, water structure and the stability of foodstuffs', Food Control 12: 409±417. MORILLON V, DEBEAUFORT F, CAPELLE M, BLOND G and VOILLEY A (1998), `Effect of the water properties on the moisture barrier efficiency of lipid-sugar based edible coatings'. ISOPOW VII ± Water Management in the Design and Distribution of Quality Foods. 30 May±4 June, Helsinki, Finland. MORILLON V, DEBEAUFORT F, CAPELLE M, BLOND G and VOILLEY A (2000), `Influence of the physical state of water on the barrier properties of hydrophilic and hydrophobic films', Journal of Agricultural and Food Chemistry 48(1): 11±16. MOUSAVI SM, DESOBRY S and HARDY J (1998), `Mathematical modelling of migration of volatile compounds into packaged food via package free space. Part I: Cylindrical shaped food', Journal of Food Engineering 36(4): 453±472. MUSZYNSKI L, WALINDER MEP, PIRVU C, GARNER DJ and SHALER SM (2003), `Application of droplet dynamics analysis for assessment of water penetration resistance of coatings'. In Mittal KL (ed.), Contact Angle, Wettability and Adhesion. VSP, Utrecht, 463±478. NICHOLLS RJ, APPELQVIST IAM, DAVIES AP, INGMAN SJ and LILLFORD PJ (1995), `Glass transitions and fracture behaviour of gluten and starches within the glassy state', Journal of Cereal Science 21: 25±36. NIKOLAIDIS A and LABUZA TP (1996), `Glass transition state diagram of a baked cracker and its relationships to gluten', Journal of Food Science 61(4): 803±806. OSWIN CR (1946), `The kinetics of package life III. The isotherm', Journal of Chemical Industry 65: 419±421. PELEG M (1993), `Assessment of a semi-empirical four parameter general model for LABUZA TP

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sigmoid moisture sorption isotherms', Journal of Food Process Engineering 16: 21±37. PELEG M (1994), `A mathematical model of crunchiness/crispness loss in breakfast cereals', Journal of Texture Studies 25: 403±410. PELEG M (1998), `Instrumental and sensory detection of simultaneous brittleness loss and moisture toughening in three puffed cereals', Journal of Texture Studies 29: 255±274. PETERSEN K, VáGGEMOSE NIELSEN P, BERTELSEN G, LAWTHER M, OLSEN MB, NILSSON NH and MORTENSEN G (1999), `Potential of biobased materials for food packaging', Trends in Food Science and Technology 10(2): 52±68. PIAZZA L and MASI P (1995), `Moisture redistribution throughout the bread loaf during staling and its effect on mechanical properties', Cereal Chemistry 72(3): 320±325. QUEÂNARD D and SALLEÂE H (1991), `Le transfert isotherme de la vapeur d'eau condensable dans les mateÂriaux microporeux du baÃtiment', Cahier CSTB 323: 1±53. ROCA E, BROYART B, GUILBERT S and GONTARD N (2008), `Effective moisture diffusivity modelling versus food structure and hygroscopicity', Food Chemistry 106: 1428± 1437. ROOS Y (1995), Phase Transitions in Foods, Academic Press, New York. ROOS Y, ROININEN K, JOUPPILA K and TUORILA H (1998), `Glass transition and water plasticization effects on crispness of a snack food extrudate', International Journal of Food Properties 1: 163±180. ROUDAUT G (2007), `Water activity and physical stability'. In Barbosa-CaÂnova GV, Fontana AJ, Schmidt SJ and Labuza TP (eds), Water Activity in Foods: Fundamentals and Applications, Blackwell, Oxford, 199±213. ROUDAUT G, DACREMONT C and LE MESTE M (1998), `Influence of water on the crispness of cereal based foods acoustic, mechanical, and sensory studies', Journal of Texture Studies 29: 199±213. RUAN RR and CHEN PL (1998), Water in Foods and Biological Materials: A Nuclear Magnetic Resonance Approach. Technomic Publishing, Lancaster, PA. SAUVAGEOT F and BLOND G (1991), `Effect of water activity on crispness of breakfast cereals', Journal of Texture Studies 22: 423±442. SHUKLA A, BHASKAR A, RIZVI S and MULVANEY S (1994), `Physicochemical and rheological properties of butter made from supercritically fractionated milk fat', Journal of Dairy Science 77(1): 47±54. SIMATOS D (2002), `ProprieÂteÂs de l'eau dans les produits alimentaires: activite de l'eau, diagrammes de phases et d'eÂtats', In Le Meste M, Simatos D and Lorient D (eds), L'eau dans les aliments, Tech and Doc Lavoisier, Paris, 49±79. SLADE L and LEVINE H (1993), `The glassy state phenomenon in food molecules'. In Blanshard JMV and Lillford PJ (eds), The Glassy State in Foods, Nottingham University Press, Nottingham, 35±102. SMITH SE (1947), `The sorption of water vapour by high polymers', Journal of the American Chemical Society 69: 646±651. SUWONSICHON T and PELEG M (1998), `Instrumental and sensory detection of simultaneous brittleness loss and moisture toughening in three puffed cereals', Journal of Texture Studies 29: 255±274. TESCH R, NORMAND MD and PELEG M (1996), `Comparison of the acoustic and mechanical signatures of two cellular crunchy cereal foods at various water activities levels', Journal of the Science of Food and Agriculture 70: 347±354. TROLLER JA and CHRISTIAN JHB (1978), Water Activity and Food, Academic Press, New York, 13±47.

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and MITCHELL JR (2000), `Understanding the texture of low moisture cereal products: mechanical and sensory measurements of crispness', Journal of the Science of Food and Agriculture 80: 1679±1685. VAN DEN BERG C (1991), `Food±water relations: progress and integration, comments and thoughts'. In Levine H and Slade L (eds), Water Relations in Foods, Plenum Press, New York, 21±28. VAN DEN BERG C and BRUIN S (1981), `Water activity and its estimation in food systems'. In Rockland LB and Stewart GF (eds), Water Activity: Influences on Food Quality, Academic Press, New York, 147±177. VOILLEY A and BETTENFELD ML (1985), `Diffusivities of volatiles in concentrated solutions', Journal of Food Engineering 4(4): 313±323. VORNHOF DW and THOMAS JH (1970), `Determination of moisture in starch hydrolysates by near-infrared and infrared spectrophotometry', Analytical Chemistry 42: 1230. WAICHUNGO WW, HEYMANN H and HELDMAN DR (2000), `Using descriptive analysis to characterize the effects of moisture sorption on the texture of low moisture foods', Journal of Texture Studies 15: 35±46. WU S (1992), `Secondary relaxation, brittle-ductile transition temperature, and chain structure', Journal of Applied Polymer Science 46: 619±624. YOUNG T (1805), `An essay on the cohesion of fluids', Philosophical Transactions of the Royal Society 95: 65±87. YU X, SCHMIDT AR, BELLO-PEREZ LA and SCHMIDT SJ (2008), `Determination of the bulk moisture diffusion coefficient for corn starch using an automated water sorption instrument', Journal of Agricultural and Food Chemistry 56: 50±58. VALLES-PAMIES B, ROUDAUT G, DACREMONT C, LE MESTE M

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4 Insect and mite penetration and contamination of packaged foods C. H. Bell, Food and Environment Research Agency, UK

Abstract: The importance of packaging as a protective measure for stored food products and the currently available packaging materials are described. The pest status and life histories of the principal insect and mite species attacking packaged foods at various points in the supply train are outlined. Some of the most frequently occurring circumstances affecting the vulnerability of packaged foods are discussed together with measures to combat pest problems. Complete sealing of the package is needed and means for the early detection of pest populations whenever products are held in storage along the path between manufacturer and consumer need to be in place. Materials acting as attractants or repellents have a useful part to play in the protection of the product. Key words: insects, mites, packaged foods, MAP, storage, penetration of plastics.

4.1

Introduction

Any consideration of how best to protect and preserve foodstuffs by packaging needs to take into account measures designed to avoid infestation by insects or mites. These pests can locate and enter any flaw in packaging and are able to reproduce at an alarming rate. A widely dispersed residual population in the fabric of the storage or holding premise is the source of attack. Though they may be widely separated, individuals of many insect pest species release chemicals known as pheromones which attract the opposite sex and, once breeding starts, a population increase rate of twenty to thirty-fold per month is not uncommon, and even higher rates of increase may be expected from mite species under

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favourable conditions. With the increased stringency for hygiene in food trading standards, the discovery of a single insect in an imported consignment can lead to rejection by the port health authority of the entire batch, with severe economic and legal consequences for all involved in the trade chain. The risk for packaged products is highest in warm climates encountering periods of high humidity and where the residence time for products is prolonged. Today most non-perishable foods are packaged prior to distribution to the consumer and with the exception of canned products, most are susceptible to attack by stored product insects (Highland, 1984). One of the first synthetic packaging materials was cellophane, produced as an extrusion from a solvent solution of the plant polymer cellulose, (C6H10O5)n. Today there are many other materials in use, all loosely termed as plastics and often utilising cellulose ethers in their manufacture. Many are laminated, some layers providing tensile strength and others impermeability to moisture or gases (Greengrass, 1993). The materials in most frequent use are listed in Table 4.1. The desire to achieve gas-tight as well as moisture-proof barriers led to the development of modified atmosphere packaging (MAP). First practised on fruit in the 1920s, followed by meat and fish in the 1930s, the technique remained as a specialist option until its combination with vacuum packaging in the 1970s (Parry, 1993). The sudden popularity of shrink wrapping under vacuum of products such as poultry prior to freezing paved the way for an exponential expansion of not only modified atmosphere packaging but a much wider consideration of packaging applications, until by the end of the 1990s nearly every food product and even newspapers and magazines found themselves in plastic wraps. The sealing of the packaged food must remain intact to be effective, but insects possess some formidable equipment to gain entry. Mites and the younger stages of insects are very small and can exploit the tiniest openings. Characterised as arthropods by having an exoskeleton, some insects are heavily sclerotised as adults. Many beetles possess powerful mandibles, both as adults and larvae, which can cut through edges and folds in the package. Moth larvae also have strong biting and chewing mouthparts. In cockroaches and some beetles, a secondary set of biting or chewing apparatus is provided by the galeae and laciniae, distal lobes of the maxillae head appendages, which have developed sclerotised hooks and cutting surfaces (Fig. 4.1). In beetles which attack whole grains the combination of mouthparts allows holes to be `drilled' through the testa of seeds, and, of concern here, through various packaging materials.

4.2

Insects and mites contaminating stored food products

4.2.1 Coleoptera Beetles comprise the largest group of stored product pest species with nearly 200 species from 14 families having been implicated in storage problems. Only some of these qualify as pests of major importance (Bell, 2003) and not all of this

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Table 4.1

Some properties of materials in common use for the packaging of food products (after White and Roberts, 1992; Greengrass, 1993)

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Material

Polyethylene LD Polyethylene HD Polypropylene Ethylene vinyl acetate (EVA) Polyvinyl chloride (PVC) (unplasticised) Polyvinylidene chloride (PVdC) Nylon 6 (polyamide) Polyethylene tetraphthalate (PET) Polystyrene-butadiene Ethylene vinyl alcohol (EVOH)

Tensile strength

Thermoformability

Permeability at 25 ëC (litres/m2.day.atm) for 25 micron film Oxygen

Nitrogen

Carbon dioxide

Moisture transfer at 38 ëC, 90% r.h. (g/m2.day)

Good Good Fair Poor Good

Good Poor Good Good Good

7.8 2.6 2.0±3.7 12.5 0.15±0.35

2.8 0.65 0.4±0.7 4.9 0.06±0.15

42.0 7.6 8.0±10.0 50.0 0.45±1.0

16±24 6±10 6±12 40±60 22±40

Fair Very good Very good Good Fair

Good Fair Poor Good Poor

0.002±0.01 0.04±0.08 50±130 5.0 0.001±0.005

0.001±0.002 0.014 0.015±0.018 0.8 na

0.01±0.03 0.15±0.19 0.18±0.39 18.0 na

0.8±3.2 80±300 20±50 100±125 16±80

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Fig. 4.1 Mouthparts of Blatta orientalis. 1. Mandibles: pr, prostheca; ab.m, abductor muscle; ad.m, adductor muscle. 2. Left maxilla: mx.p, maxillary palp; g, galea; l, lacinia; s, stipes; sg, subgalea; c, cardo. 3. Labium: gl, glossa; pg, paraglossa; l.p., labial palp; pm, prementum; pgr, palpiger; m, mentum; sm, submentum. After Imms (1951).

smaller group are a threat to packaged products. The principal pests are described below by family. Anobiidae Lasioderma serricorne (F.) The cigarette or tobacco beetle has long been associated with dried vegetable products, and is one of the most widespread of all stored product pests. Of tropical origin and a strong if slow flyer, it favours warm, moderately humid conditions, and in temperate zones readily colonises any heated building where food material is processed or stored. Damage is caused by the larvae which have powerful biting mouthparts. Adults, whilst able to perforate dry tobacco leaves, do not feed in store, but may feed on nectar in the open. The biology of L. serricorne was reviewed by Ashworth (1993). The short-lived adults are about 3 mm in length and reddish brown in colour with smooth elytra. Though notorious as a pest of tobacco, L. serricorne is also a pest of cocoa, soybeans, various cereals, spices, textiles and many other products. It breeds rapidly, multiplying 20-fold in a 4-week period at 32±35 ëC with up to six generations per year in the tropics. A minimum temperature of 22 ëC and, at optimal temperatures, a minimum relative humidity (r.h.) of 30% are needed for a population increase (Howe, 1965).

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Stegobium paniceum (L.) The drug store, biscuit beetle or bread beetle is one of the most long-standing pests of homes and stores in temperate zones with numerous records going back to the birth of applied entomology. Excavations of archaeological sites have found dead specimens in leather artefacts from Roman times and in the remains of food left in tombs in ancient Egypt. Similar in appearance to L. serricorne except for its striated elytra, the 2±3 mm beetle is found on a very wide range of stored products, favouring finely divided materials for oviposition. The larvae cause damage to leather, textiles, tobacco, papers, wood, rubber and cork as well as food materials. S. paniceum was a particular pest of biscuits stored on sailing ships in the days of long voyages, but today it is found in bakeries, commercial retail stores and domestic larders. Here, for development to lead to a population increase a minimum temperature of 17 ëC is needed and development proceeds fastest (7.5 times increase over 28 days) at 25±28 ëC (Howe, 1965). High humidity is favoured. Bostrichidae Rhyzopertha dominica (F.) The lesser grain borer (Fig. 4.2a) is a serious pest of cereal grains, adults and larvae both boring into grain in which development is completed. Damaged grains are preferentially selected for attack and, if unchecked, populations can cause total loss of product. R. dominica can also complete development on various flours, meals and macaroni, and is able to penetrate most packaging materials. Development is rapid (c. 25 days at 34 ëC) with a high temperature optimum of 32±35 ëC and temperature and r.h. minima of 19 ëC or 30% r.h. (Howe, 1965; Arbogast, 1991). A 20-fold population increase can occur every 4 weeks and, in spite of the high temperature developmental range, the adults are cold hardy. Eggs are laid in batches on the kernels of grain or singly in frass or meal. The larvae are unusual in that they start life as active, campodeiform types while later instars are scarabeiform and immobile. The shiny dark brown 2±3 mm adults fly readily in warm conditions and a single female can lay over 400 eggs over a 5-month period. Bruchidae There are a very large number of beetles from this family that infest leguminous crops in the field but only a few can continue breeding in store. Problems have occurred when infested beans have been packaged and the non-feeding adults may then appear within the pack or larvae may actually bore out (de Luca, 1977). Clearly this is not a problem of packaging per se, and to avoid such instances corrective measures should have been applied to the commodity prior to packaging. Three species commonly implicated in this way are Acanthoscelides obtectus (Say) a serious pest of bean seeds (Phaseolus vulgaris) in store, Callosobruchus maculatus (F.) the cowpea weevil, and C. chinensis (L.) the adzuki bean weevil. All are about 3±4 mm in size and can increase at a rate of 25 times a month under optimal conditions. The developmental range extends

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Fig. 4.2 Some beetle pests of stored food pictured on grains of wheat: (a) Lesser grain borer, Rhyzopertha dominica; (b) Saw-toothed grain beetle, Oryzaephilus surinamensis; (c) Rust-red flour beetle, Tribolium castaneum.

from about 15 to 33 ëC for A. obtectus, 20±37 ëC for C. maculatus and 17±37 ëC for C. chinensis (Arbogast, 1991). Cleridae Necrobia spp. Two species of this genus, Necrobia ruficollis (F.), the red shouldered ham beetle, and N. rufipes (Degeer) the copra beetle or red-legged ham beetle, occur as pests of animal products such as dried meat and fish products, milk powder, cheese, hides and bone meal. N. rufipes is also frequently encountered on poorly-stored vegetable products such as copra, dried fruit, cocoa, rice bran, palm nuts and cassava. For optimal development the beetles require high humidity and warm conditions and the best method to avoid their establishment is to keep vulnerable products below 20 ëC and 50% r.h. Temperatures between 30 and 34 ëC give the maximal rate of population increase of 25 times in a 4week period (Howe, 1965), but Necrobia spp. are highly predatory and cannibalism can slow population growth. Mature larvae move out of the food medium and produce a characteristic strong white protective sheath for pupation. It is often at this point that their presence is noted. Cucujidae Cryptolestes ferrugineus (Stephens) The rust-red grain beetle is a common pest of stored grain, but is seen less often than may be expected because, quite apart from its small size (2.5 mm including long antennae), it will move away from areas of disturbance and, as its generic Latin name suggests, hide. This refuge-seeking behaviour of adults is promoted by low temperature, food shortage, and high population density, and is strongest

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in females and younger individuals (Cox et al., 1990). A highly adaptable species, in addition to grain C. ferrugineus has been recorded on flour, meals, oilseeds, dried fruit, cassava root and other dried vegetable materials. It is tolerant of low humidity and is cold hardy in the long-lived adult stage. Both adults and larvae cause damage. Above 25 ëC flight is initiated, enabling the rapid dispersal of populations (Cox and Dolder, 1995). The eggs of Cryptolestes spp. are elongate (over three times as long as wide, length c. 0.6 mm) and up to 400 may be laid by one female. For optimal development, temperatures of 32± 35 ëC at moderate r.h. can permit population growths of up to 60-fold in a 4week period (Howe, 1965). Other Cryptolestes species responsible for disrupting the trading of food commodities are the flat grain beetles C. pusillus (Schoenherr) and C. capensis (Waltl), and C. turcicus (Grouvelle), the Turkish grain beetle. The latter two species are often found in flour mills, C. turcicus throughout temperate Eurasia and America and C. capensis, like C. ferrugineus tolerant of low humidity, from Europe and North Africa (Arbogast, 1991). Cathartus quadricollis (Guenin-Meneville) The square-necked grain beetle is another cosmopolitan cucujid species, common in the USA. It attacks maize in the field and in store, but also wheat, rice and dried fruits. The developmental period varies according to the food medium and high humidity is preferred, but a generation can be completed in about six weeks at 30 ëC, 70% r.h. (Yoshida, 1976). Curculionidae Sitophilus spp. (grain weevils) Three species, the granary weevil, Sitophilus granarius (L.), the rice weevil S. oryzae (L.) and the maize weevil, S. zeamais Motschulsky, rank among the most serious pests of cereal grains in the world. Weevils develop inside the grain, females digging a tunnel into the grain with the chewing mouthparts at the end of the elongated snout before laying an egg and cementing over the opening with a gelatinous plug that rapidly hardens. On completing development inside the grain, the mature beetle chews through the grain shell to mate and start the next generation, this often being the first sign of infestation. Fortunately the group are confined to the harvested crop before processing, and do not attack packaged products, although production line hygiene failures may occasionally result in their discovery in packaged products such as popcorn. Dermestidae Dermestes lardarius L., D. maculatus Degeer These moderate sized (8±10 mm) beetles infest dried meat, bacon, sausages, fish and other animal products such as sheepskins, hides, furs, feathers, bone meal or cheese. Both larvae and adults feed on the product. Dried plant materials may also be attacked but females require a high protein diet for optimal and continued egg production. Eggs of D. lardarius, up to 80 per female, are laid

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singly on food at the rate of one every one or two days, and larvae pass through a variable number of instars to reach maturity, within 7 weeks after oviposition at 25±30 ëC (Coombs, 1978). Development can be completed between 15 and 32.5 ëC and adults may live for six months. Females of D. maculatus tend to lay eggs in small clusters and can produce over 300 eggs during their lifetime when both food and water are available (Arbogast, 1991). The developmental range of D. maculatus is slightly higher than that of D. lardarius, egg production and development proceeding up to 35 ëC. If a suitable material is present, Dermestes larvae often bore tunnels in which to pupate, a habit which can cause a great deal of damage to materials on which they do not feed (Hinton, 1945). Four other species are widespread, D. ater De Geer, D. frischii Kugelann, D. haemorrhoidalis Kuster, and D. peruvianus Laporte de Castelnau. Trogoderma granarium (Everts) The khapra beetle is one of the most destructive pests of whole grain and cereal products in warmer areas of the world, particularly North Africa and the Indian subcontinent. Many ships harbour endemic populations, larvae remaining concealed behind paint or rust scale, and because of its notoriety the species is on the quarantine pest list of many nations. The adult stage, 2±3 mm in length, is relatively short-lived but larvae can survive periods of adversity for some years (Burges, 1962). Poor food, high population density or lowered temperature can trigger a developmental arrest during which larvae may feed intermittently and even undergo moults to reduce as well as increase size while remaining for the most part in cracks or crevices (Beck, 1971; Karnavar, 1984). The arrest, variously described as a diapause or quiescence, may be terminated by a substantial temperature rise or the renewal of food (Nair and Desai, 1973). Under high temperature conditions development can be very rapid on foodstuffs, less than 30 days from egg to adult at 35 ëC, and 50±70% r.h. Very low r.h. can be tolerated but for populations to increase a minimum temperature of 22.5 ëC is required at 70% r.h. (Burges, 2008). Many other species of Trogoderma have been recorded on stored products. The warehouse beetle T. variabile Ballion is an important pest in the USA and Australia while T. inclusum Le Conte, T. angustum (Solier), T. anthrenoides (Sharp) and T. glabrum Herbst have caused problems in Europe and elsewhere. Ptinidae Ptinids are collectively known as spider beetles because the narrow waist between the abdomen and thorax gives a spider-like appearance to the 3±4 mm adults. Spider beetles are scavengers associated with long-term infestations of granaries, flour mills, biscuit manufacturing plants and other related food processing premises. The golden spider beetle Niptus hololeucus (Faldermann) may often occur in undisturbed areas in domestic stores and larders. Other species commonly encountered are the white marked spider beetle Ptinus fur (L.), the Australian spider beetle (though actually more common in Europe) P.

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tectus Boieldieu, the black spider beetle Mezium affine Boieldieu, and the shiny spider beetle Gibbium aequinoctiale Boieldieu. Ptinids are characterised by a long life cycle and an ability to survive in cool as well as warm conditions. Male ptinids are strong flyers but sexual dimorphism occurs, some females being sedentary (Howe, 1991). Silvanidae Oryzaephilus mercator (Fauvel) and Oryzaephilus surinamensis (L.) These are small, slim beetles, about 3 mm in length, strongly striated and medium brown in colour. The merchant grain beetle O. mercator is more commonly found on products such as oilseeds, dried fruit, nuts and cocoa beans than on grain or cereal products. It can complete development between 17 and 38 ëC and is tolerant of low r.h., though at 20 ëC no larvae develop at 30% r.h. or below (Lale et al., 1996). Fecundity is increased at moderate to high r.h. (not above 90%), larvae utilising stored product fungi in their diet. Females lay eggs singly or in small clusters and each may produce up to 300 (Arbogast, 1991). The saw-toothed grain beetle O. surinamensis (Fig. 4.2b) is a serious pest of stored grain in Europe, infesting wheat, oats and barley. It is also one of the commonest pests of cereal products, dried fruits, nuts, and oilseeds such as sunflower. It can develop rapidly, achieving a population increase of 50-fold over a 4-week period at 31±34 ëC (Howe, 1965). The minimum temperature for a population increase is about 20 ëC at 70±80% r.h., lower humidities being tolerated at higher temperatures (Arbogast, 1991). The cold tolerant adults are able to overwinter in cracks and crevices in the fabric of buildings, leaving their refuges in milder conditions to search for food residues at the onset of darkness (Bell, 1991). Tenebrionidae Tribolium confusum J. du Val and Tribolium castaneum (Herbst) A common pest of flour mills, the confused flour beetle was thought to be conspecific with T. castaneum the rust-red flour beetle until 1868, being of similar size (c. 4 mm) and colour. In addition to cereals and cereal products, T. confusum is also known to infest copra, groundnuts, sesame and oilseeds. Fungi and other insect remains can be utilised in the diet. Adults are extremely longlived (1±3 years), and tolerant of cold and very low humidity. The developmental range is 20±38 ëC with an optimum of 30±32 ëC, at which a 60-fold increase in population is achievable on an optimal food in a 28-day period at 70% r.h. (Howe, 1965; Arbogast, 1991). Worldwide the rust-red or red flour beetle T. castaneum (Fig. 4.2c) is perhaps the most frequently intercepted pest of stored products. It is the primary pest of flour mills, maltings and food processing premises, adults and larvae feeding on all cereal products, groundnuts, cacao, spices, dried figs and dates, copra, dried yam, palm kernels, various nuts, oilseeds and cotton seed. Its rapid development and readiness to breed in the laboratory have made it a popular tool in physiological and genetic studies. Like many other tenebrionids, the free ranging

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larvae and adults are predatory on other species. The life cycle can be completed between 22 and 40 ëC with an optimum of 32±35 ëC at which, on an optimal food at 70% r.h., a population increase of up to 70 times can be achieved over 28 days (Howe, 1965; Arbogast, 1991), the highest rate of increase achieved by any stored product insect. Adults live for 1±2 years, are capable of flight in warmer conditions and are cold hardy. Adults of Tribolium spp. have long been known to produce quinones, which at high population densities tend to trigger dispersion. Trogossitidae Tenebroides mauritanicus (L.) The cadelle beetle is a major pest of grain and cereal products in the USA. It also infests nuts, seeds, and dried fruit and vegetables of various kinds. Both adult and larval stages are voracious feeders, the former being predatory on any other insect stage they encounter, including larvae of their own kind. The adult is a shiny black medium sized (8±10 mm) beetle with an obvious waist dividing the body in two. The life cycle is relatively long, the time for completion under optimal conditions being about 10 weeks, while individuals hatching in late summer generally do not complete development until the following summer. Larvae are notorious for burrowing into structural materials, plastics and fabrics and have caused extensive damage to equipment in flour mills (Mueller, 1998). Adults are long-lived and females may produce as many as 1000 eggs in their lifetime (Arbogast, 1991). 4.2.2 Lepidoptera Many moth species are associated with stored or finished vegetable and animal products, but those in the families Gelecheidae and Tinaeidae attack only cereal grains, decaying food residues, textiles, furs, fabrics or household furnishings and do not occur on packaging. Two families remain for consideration here. Oecophoridae Hofmannophila pseudospretella (Stainton) The brown house moth (length 9±15 mm) occurs widely in buildings in northern Europe and is a pest of premises such as flour mills where food is stored or processed. In domestic houses it infests food residues, textiles, wool, dried decaying organic matter and various seed products at high humidity. The larvae can chew through many fabrics and packaging materials, being equipped with powerful sclerotised mandibles. The life cycle is complex and involves a larval diapause and stages of quiescence rendering it univoltine in nature (Woodroffe, 1951). Development can proceed between 10 and 29 ëC, r.h. at 80% being preferred (Howe, 1965). The related white-shouldered house moth Endrosis sarcitrella (L.) which develops more rapidly also occurs widely in European mill basements and domestic premises.

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Pyralidae This family contains most of the moth pests of stored products. Damage is caused by the larval stage which features a heavily sclerotised head capsule with biting and chewing mouthparts while, as in other stored-product Lepidoptera, the rest of the elongated body is unsclerotised and of a whitish colour. Corcyra cephalonica (Stainton) The rice moth is a serious pest of mills in hot damp climates but occurs widely on imports of cereals, cereal products, dried fruit, seeds, cocoa and groundnuts and can become established in heated premises anywhere in the world. It is capable of a population increase between 18 and 35 ëC (Howe, 1965; Cox et al., 1981). Under optimum conditions (30 ëC, 80% r.h.) the life cycle can be completed in 4 weeks and a population increase of 50-fold in 28 days can be achieved. Oviposition occurs from dusk onwards, but is inhibited by daylight (Bell, 1981). Eggs are not cold tolerant and will not hatch at 15 ëC or below. On completing their development, larvae spin a tough double-layered cocoon in preparation for pupation. Ephestia cautella (Walker) The tropical warehouse or almond moth is the most frequently intercepted moth pest on imports into the developed world and occurs on a very wide range of products including dried fruit, nuts, cereals and cereal products, dried vegetables, cocoa beans, spices, copra, pulses and carobs. The life cycle can be rapid (<4 weeks at 30 ëC, 75% r.h.), permitting a population increase of 60fold in a 28-day period (Cox and Bell, 1991). Although eggs will hatch at 15 ëC, the minimum temperature for a population increase is 17 ëC, and the minimum r.h. 25% (Howe, 1965). Oviposition is controlled by a diurnal rhythm entrained by nightfall, at the onset of which most eggs are laid over the first three or four days after emergence and mating (Bell, 1981). Eggs require 7±8 days to hatch at 20 ëC and 4-5 days at 25 ëC. In common with other pyralid moths, there are five larval instars. Larvae produce silk from glands in the mouth, infested product soon becoming covered with webbing. Mature larvae may wander from the food, and even bore through packaging to find a secluded site to spin a cocoon for pupation (Fig. 4.3a). The emerging adults (7±12 mm long) are of a yellowish or light brown tinted grey in colour and fly readily. Ephestia elutella (Hubner) A pest of grain and cocoa, especially in situations of long-term storage, the warehouse moth is similar in appearance and size to E. cautella but has a lower developmental range and longer life cycle adapted to temperate climates. The autumn generation enters an overwintering diapause stage as a fully-grown larva in response to short days and lowering temperatures (Bell, 1976). The photoperiodic signal triggering diapause, daytime length of 14 h or less, is received shortly after the last larval moult. Mature larvae migrate leaving a silken trail to seek harbourages in the fabric of the building. In warmer conditions there may

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Fig. 4.3 Common moth pests of stored food: (a) Mature larva of the tropical warehouse or almond moth Ephestia cautella in silken cell spun ready for pupation. (b) Adults of the Mediterranean flour moth Ephestia kuehniella, female left, male right. (c) Adult Indian meal moth Plodia interpunctella emerging in cereal product.

be one or two generations in the spring and summer prior to the overwintering one. The developmental range is 10±30 ëC with an r.h. minimum of about 20% (Cox and Bell, 1991). Ephestia kuehniella Zeller The Mediterranean flour moth or mill moth is a common pest of flour mills and bakeries throughout the world and the webbing produced by larvae causes problems for milling machinery when infestation is severe. Adults (Fig. 4.3b) are 10±16 mm in length and are medium grey in colour with narrow black zigzag markings across the wings. The developmental range is between 10 and 30 ëC, though males reared at 30 ëC, or in continuous light, are infertile (Raichoudhury and Jacobs, 1937). At 70% r.h., the life cycle can be completed on wholemeal flour in about 6 weeks at 25 ëC. A population increase of 50-fold can occur within 4 weeks (Howe, 1965; Cox and Bell, 1991). Very low humidities can be tolerated but development is slowed. Eggs and particularly older larvae are cold tolerant, being able to survive exposures of several days at subzero temperatures if quickly restored to temperatures allowing active development. The pupal stage lasts 35±44 days at 15 ëC, 17±22 days at 20 ëC, and 10±14 days at 25 ëC, about 2±2.5 times the duration of the egg stage as in other pyralid species (Bell, 1975). Plodia interpunctella (Hubner) The Indian meal moth, so named because it was first recorded on Indian meal, is a pest of a very wide variety of bulk or packaged stored products, including dried fruit and nuts, cereals and cereal products, cocoa, oilseeds, confectionery, citrus pulp, dried vegetables, pulses, seeds and carobs. The adult moth, 7±12 mm long, has a distinctive wing pattern of light grey proximally with dark and reddish brown markings over the distal half of the wings (Fig. 4.3c). The life cycle can be completed in 3 to 4 weeks at 30±32 ëC, 75% r.h., and development can proceed down to 17 ëC or 20% r.h. (Cox and Bell, 1991; Na and Ryoo,

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2000). Younger eggs are cold susceptible, all dying after a 14-day exposure at 15 ëC (Bell, 1975). Older larvae, however, are more cold tolerant, being able to overwinter in a state of diapause. This is induced earlier in development either by a temperature fall or in response to experiencing nights longer than 11 h and days shorter than 13 h, as occurs in autumn (Prevett, 1971; Bell, 1976). Larvae entering diapause spin a dense silk hibernaculum, in contrast to the more flimsy structure spun for pupation. The pupal stage lasts 15±20 days at 20 ëC, but only 6±9 days at 30 ëC. 4.2.3 Psocoptera These tiny, primitive insects feed mainly on moulds and decaying vegetable material in damp situations but occasionally occur in huge numbers on stored grain or in packaged foodstuffs such as flour in commercial or domestic premises. The smallest opening in packaged foods can provide a point of entry for the minute nymphal stages. Psocids can also cause major problems in museums and libraries, infesting the bindings of books and chewing parchments and paper. The commonest species is Liposcelis bostrychophila Badonnel (Fig. 4.4a), a rapid-moving, wingless, pale-coloured insect about 1 mm long for which males are unknown, an attribute which is unusual in the Psocoptera. At high temperatures in the presence of a food source, parthenogenetic multiplication can be extremely rapid, but temperatures above 20 ëC are needed for egg production (Turner, 1994). In domestic pantries an opened bag of flour may soon become the source of a large population. Many other psocids associated with stored products such as Lepinotus patruelis Pearman and Trogium pulsatorium (L.) favour temperate climates and populations increase more slowly. Psocids are best controlled by application of heat to dry the infested area (Turner et al., 1991). 4.2.4 Other insects Dictyoptera The common cockroach pests tend to be named after regions of the world but all have now become cosmopolitan in distribution (Ebeling, 1991). Most belong to the genera Periplaneta, Blatta or Blattella (Brenner, 1991). Eggs are produced in capsules, those of the American cockroach Periplaneta americana (L.) containing 14±16 eggs. This 30±40 mm insect may produce a capsule each week. The smaller (12 mm) German cockroach Blatella germanica (L.) can have 40 eggs per egg case and progress from egg to adult in 12 weeks. Cockroaches, particularly B. germanica, can cause allergenic problems, posing an additional problem to food spoilage when it occurs. Most species are cryptic, hiding in refuges with access to food residues, but the Asian cockroach Blatella asahinai Mitsukubo is actually attracted to light. The high mobility and non-selective dietary habits of cockroaches, coupled with their versatile mouthparts (Fig. 4.1), place any packaged foods in their vicinity at risk.

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Fig. 4.4 Other insects and mites associated with stored food: (a) The psocid Liposcelis bostrichophila. (b) The parasitic wasp Anisopteromalus calandrae. (c) The mite Acarus siro.

Hymenoptera Parasitic wasps Many species of stored product insects are parasitised as eggs, larvae or pupae by chalcidoid, bethyloid or ichneumonidoid wasps. These highly specialised Hymenoptera are characteristically of very small size but being dark in colour and highly mobile on emerging from their hosts as adults, are often the first evidence of infestation within the transparent packaging of various products. While the Chalcidoidea has families of both ectoparasitic and endoparasitic wasps, bethyloid wasps are mostly external parasites of larvae, and the Ichneumonoidea are mostly endoparasites, females inserting eggs directly into the host via a sharp ovipositor rather than adhering them to the surface. Some species commonly encountered are the egg parasite Trichogramma cacoeciae Marschal, the larval parasites Pteromalus cerealellae (Ashmead), Lariophagus distinguendus (Foerster), Choetospila elegans Westwood and Anisopteromalus calandrae (Howard) (Fig. 4.4b) (Chalcidoidea), Cephalonomia gallicola Ashmead, C. tarsalis Ashmead and C. waterstoni Gahan (Bethylidae), and Venturia canescens (Gravenhorst), Habrobracon brevicornis (Wesmael) and H. hebetor (Say) (Ichneumonoidea) (Gordh and Hartman, 1991). Ants Nearly every domestic or food storage premise has encountered the problem of ants at some time. The species concerned varies in different parts of the world but the typical situation is the persistent appearance of ants in growing numbers over a period of time that proves difficult to control. Ants are colonial insects with a worker class that forages for food and carries it back to a central nest often at a considerable distance from the food source. Several species of ant leave a chemical trail from a food source back to the nest with the result that increasing numbers of workers appear, all following the same route or routes

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(Beatson Campbell, 1991). Ants are equipped with powerful mandibles capable of cutting through plastic films but nearly always their appearance results from their finding access into opened or non-secure packages of sugar or proteinbased food materials. Two species regularly causing problems in houses, hotels, restaurants, hospitals, warehouses and food processing facilities are the common black ant Lasius niger (L.) and the pharaoh's ant Monomorium pharaonis (L.). Monomorium spp. are susceptible to control by insecticide baits exploiting juvenile hormone activity because unlike Lasius spp. there is usually only a single queen ant producing eggs in the nest. 4.2.5 Mites Mites are very different from insects and are more closely related to spiders. The life cycle includes a brief larval stage typically followed by three nymphal stages prior to the reproductive adult stage. The most important families associated with food storage problems are Acaridae, Carpoglyphidae and Glycyphagidae. Mites are small, almost microscopic species that utilise microenvironments of moderate temperature and raised humidity. Typically eggs and some other life stages are cold tolerant and development can proceed at lower temperatures than required by insect stored product pests, but low humidities prevent development. Acaridae Acarus siro L. The flour mite (Fig. 4.4c) is able to infest any food used by man if the local environmental conditions are suitable. The tiniest opening in packaging permits entry and in addition to the taint produced in the substrate, by which its presence is often detected, the mite is strongly allergenic. Development can proceed at 5 ëC or below, can be completed within two weeks at 23 ëC, while adults survive between 30 and 50 days at 20±30 ëC (Cunnington, 1965; Boczek, 1991). Females can produce over 600 eggs during their life span. Tyrophagus putrescentiae (Schrank) The mold mite is perhaps the most cosmopolitan mite pest of stored products, occurring in any product with a high fat or protein content and in any part of the world and, as with other mite species, requiring only the tiniest opening to gain entry. Tolerant of somewhat higher temperatures than many other species, the egg stage is nevertheless able to survive temperatures well below freezing for several weeks. Females may lay up to 300 eggs and development may be completed at 9±35 ëC and within 20 days at 80% r.h. above 25 ëC (Cunnington, 1969; Boczek, 1991). Mites from other families Carpoglyphus lactis (L.) The dried fruit mite (Carpoglyphidae) is another species able to complete development within 10 days at 25±30 ëC, 80% r.h. (Chmielewski, 1971). It

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infests milk products and various sugar-based products in addition to dried fruit. A hypopal stage which can be transported by insects appears at the deutonymph stage under conditions of high population density and permits an extension of the developmental period by up to 3 months. Glycyphagus domesticus (Degeer) The house mite (Glycyphagidae) occurs in most domestic premises in Europe feeding on flour, wheat, cheese or ham, and is strongly allergenic in house dust (Maunsell et al., 1968). A life cycle can be completed within 25 days but hypopal deutonymph resting stages are common, which can last several years. Lepidoglyphus destructor (Schrank) The cosmopolitan food mite (Glycyphagidae), as its name suggests, is a widespread and versatile species occurring on many food substrates. Able to develop between 3 and 34 ëC its population can increase four-fold per week at 25 ëC, 90% r.h. (Cunnington, 1976). In common with the other species mentioned, most infestation problems can be avoided by storage of food materials under dry conditions, the exception being where the product itself has a naturally high equilibrium relative humidity.

4.3

Combating critical points in the food chain

4.3.1 Arrival at the food processing facility Many harvest and cropping products are delivered to the flour mill, chocolate factory or food processing facility, either in bulk or in container loads of bags stacked on pallets (Fig. 4.5). Some may have been stored on farm or in warehouses at the place of import for some time prior to delivery and may have been invaded by pests. The usual control measures against stored product pests to protect or disinfest raw commodities such as bulk grain and bagged products are cold air aeration, pesticide or inert dust admixture, fumigation with phosphine, heated air circulation or, occasionally, controlled atmosphere application. The build-up of resistance to insecticides is now widespread, most species showing resistance to malathion, and many to other organophosphorus compounds such as fenitrothion, pirimiphos-methyl and chlorpyrifos-methyl, to synthetic pyrethroids and even to hormone analogues such as methoprene (Nayak et al., 2005). The widely used fumigant phosphine is also prone to the development of resistance although well-controlled fumigation operations can still eliminate resistant populations. For bulk cereals, cold aeration from the outset of storage is an effective strategy against population increase of pest species as this cools and dries the grain (Flinn et al., 1997). Essential for the maintenance of store hygiene is a regular monitoring programme to detect the presence of pests at an early stage. Various bait traps exist for moth species and most beetles and, if these are deployed appropriately through the facility and monitored systematically, an early warning of infestation

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Fig. 4.5

Bag stacks on pallets in store awaiting distribution.

problems is obtained (Trematerra et al., 2007). Localised pest outbreaks can be dealt with by removal of the source, spot fumigant or pesticide application, by use of localised heat, or by rigorous cleanup operations. 4.3.2 Packaging Packaging is usually tailored to fit the product and designed to last throughout the storage life of the product. The integrity of the packaging and the materials used are important considerations in preventing infestation (Collins, 2003). Entry by pests is gained through existing structural weaknesses or openings caused by mechanical damage or imperfect sealing. The insects are able to locate an opening in packaging by several methods. The first method is by exploration, the fact that insects are continually on the move, investigating their environment. On encountering a package a searching pest will follow along the fold of an over-wrap, the corner of a carton or the folds of a neck tie, and will locate any small opening, pinhole or puncture in the material (Collins, 1963; Nguyen et al., 2008). Seams and seals provide the most common routes of entry for invaders. A direct correlation exists between package seal quality and the extent and swiftness of infestation (Yerington, 1978). Examples of invaders include the red flour beetle (Tribolium castaneum), saw-toothed grain beetle (Oryzaephilus surinamensis), psocids, newly-hatched moth larvae and mites. A second method by which stored product insects are able to locate food is in response to an aroma (Barrer and Jay, 1980; Phillips and Strand, 1994; Trematerra et al., 2000; Mowery et al., 2002). Any defect in the packaging will allow the release of such aromas and provide a point of attraction.

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The size of the opening through which an insect can enter is dependent on the width of its widest rigid part (Cline and Highland, 1981). For example, the prothorax of O. surinamensis measures around 0.7 mm and the head capsule of newly-hatched moth larvae (e.g. Plodia interpunctella) can measure as little as 0.18 mm (Cline and Highland, 1981; Khan, 1983). Immature mites can gain entry through an aperture of only 0.1 mm. When intact, some materials offer better resistance against insect penetration than others, paper and cellophane being the least resistant while polycarbonate, some polyesters, polyurethane and aluminium foil are highly resistant (Rao et al., 1972; Highland, 1984, Jha and Yadav, 1991; Locatelli and Gambaro, 1999). The lesser grain borer (Rhyzopertha dominica), biscuit beetle (Stegobium paniceum), cigarette beetle (Lasioderma serricorne), cadelle (Tenebroides mauretanicus), warehouse beetle larvae (Trogoderma variabile) and larger larvae of pyralid moth species are among those most able to penetrate films. Very few film materials give total protection against attack, though thickness and smoothness reduce the risk (Rao et al., 1972; Cline, 1978; Khare and Shukla, 1979; Collins, 2003; Begum et al., 2007). Standard carton designs generally offer very little protection from stored product insects. The spot weld glue pattern commonly used often leaves channels through which smaller insect stages can enter, and the glue application needs to achieve a complete seal to be effective (Mullen and Mowery, 2000). Over-wraps can also improve resistance, particularly if applied as shrink-wraps fitting tightly around the package. A tightly-sealed over-wrap is more important than the type of over-wrap used, insects or mites often gaining entry at the corners of imperfectly folded flaps (Yerington, 1983). A much higher standard of seal is provided by the `form-fill-seal' machines employed in modified atmosphere or vacuum packaging. A heat-moulded base tray is filled with product (Fig. 4.6) and a flat lid is heat-sealed across the top in the relevant atmosphere for the product. Alternatively a pillow-wrapped box machine is used where the product is filled into a laminate `pillow' which is then evacuated and recharged with gas (White and Roberts, 1992). It can be possible to determine whether a hole made in packaging was the result of an insect leaving or entering a commodity (Brickey et al., 1973), the hole on the exit side generally being smaller with a cleaner cut perimeter. The perimeter on the entrance side (Fig. 4.7a) may be scored, fragmented, tapered or terraced (Collins, 2003), and with plastics, have a pushed-down or rucked-up edge. Although the direction of penetration may be determined, however, the point of origin of the infestation may still remain unclear. Some insects, such as moth larvae (Figs 4.3a, 4.7b), may enter packages by invasion through structural weaknesses after hatching from eggs laid on the surface, and exit when fully grown by chewing through packaging further down the distribution chain (Collins, 2003). The use of barrier materials such as acrylic, or polyvinylidene chloride coatings onto the outside of packages can prevent food aromas escaping from packages and attracting insects (Mullen and Mowery, 2000). However, any damage or defect in the package will negate the effect of the odour barrier.

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Fig. 4.6

A mechanised `form-fill-seal' production line for packaging ham.

Another established way of combating pest attack is the incorporation of insecticides and repellents into packaging (Newton, 1988). However, it is important that there is no migration of pesticide residues from the packaging into the commodity and that the compounds used do not pose any hazard. Methyl salicylate, a synthetic version of wintergreen oil, is an environmentally friendly product used for packaged products such as rice, flour, pasta, dry cereal, bake mixes, dry pet foods, instant soup, flowers and vegetables (Collins, 2003). It can be press-applied as a coating for folding cartons, corrugated boxes, or the inner plies of multi-wall bags.

Fig. 4.7

(a) Hole made by moth larvae to enter a package. (b) Mature larvae of Plodia interpunctella, one in a silken cocoon spun prior to pupation.

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4.3.3 Storage and distribution Most packaged food and beverage products, with the exception of those that are canned, bottled or frozen, are at risk of insect contamination which can be introduced at any stage during the product's life after manufacture through the whole distribution and storage process. Infestation frequently occurs after a product has left the site of manufacture, and is transported to another site for storage and further distribution (Bowditch, 1998). Complaints of infestations are, however, often directed back to the manufacturer. Identifying the point at which an infestation initiated is a difficult task, but knowledge of the biology of the pest can help identify the cause of infestation, its source and how to avoid future problems (Collins, 2003). The more suitable the conditions for insect development, the greater is the risk that the product will pick up an infestation. Insects generally multiply faster at higher temperatures with raised humidity. The less time the product is in storage, the lower the risk of invasion by insect pests. Insect infestation can usually be traced to transportation or prolonged storage under poor warehousing conditions (Mullen and Mowery, 2000). Rodents can often damage packaging and lead to further problems. Another area of concern is the loading and unloading operations for palletised goods. Fork-lift trucks can inadvertently damage the underside of packaging by trapping folds of plastic between the forks and the pallet. Care needs to be taken to avoid any projecting of packaging through the pallet, a situation that often occurs with heavier loads. Any puncture provides an obvious source for pests to enter. 4.3.4 At the retailer Most modern larger retail outlets have cold storage facilities for stock and this greatly reduces the incidence of infestation. However, not all products enter the cold store and store-rooms are vulnerable to the build-up of pest problems. Thind and Clarke (2001) found mites in 21% of a sample of 567 cereal-based food products examined soon after purchase. Store rooms benefit from having self-closing doors, louvered extractor fans, smooth, cleanable floors free from damp and no dead storage areas near to walls (Hohman, 1991). With some overlap, a different group of pests predominates in retailer premises and some species occur that are absent at the manufacturing site. Conditions tend to be more variable than in food processing facilities and pests that are more adapted to such environments predominate. For example, in north and western Europe the brown house moth H. pseudospretella and the warehouse moth E. elutella tend to replace the almond and Indian-meal moths E. cautella and P. interpunctella. Correct species identification can be important in tracing the source of an infestation. 4.3.5 In the larder As food is transferred on purchase to the domestic household, again a shift in the pests can be discerned. Most problems in domestic premises are caused by

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cockroaches, psocids or ants, the latter mostly invading houses from the outside in the summer in response to the establishment of a food trail to a sugar-rich food source. In north and Western Europe since the 1960s psocids, notably Liposcelis bostrichophila, have increasingly been the cause of pest complaints in bakery products, particularly those of higher moisture content (Turner and Ali, 1996). The availability of such products and the increased adoption of central heating could be contributory causes. Food products remaining on shelves for long periods or left partially unpacked are obvious sources for the transfer of infestation. Cockroach populations require high temperatures to expand to noticeable levels and a study in multi-occupancy buildings in London linked the persistence of infestation partly with poor hygiene, including clutter as well as food residues, and, in larger blocks, with communal heating systems where the ducting provided warmed communication between dwellings (Shah et al., 1996).

4.4

Future trends

4.4.1 Pest detection and control Perhaps the major emphasis for future development in the field of protecting packaged food from pest problems is the improvement of integrated pest management systems by researching means to facilitate the early detection of pest species. Early detection permits a wider range of options for dealing with, or circumventing, pest problems, and reduces the reliance on chemical control measures. In the past emphasis has been placed on the development of speciesspecific traps, facilitated by parallel studies identifying insect sex pheromones. Whereas traps baited with synthetic pheromones were highly successful for a variety of moth pests and some beetles, they were less effective for longer-lived beetle species where sex pheromones are of less importance than chemicals facilitating aggregation or the volatiles emanating from food sources (Chambers, 2002). Many other methods for insect and mite detection have been researched such as those based on acoustic detection, oil flotation, electronic odour detection, x-ray analysis, immunoassays, machine vision and spectral analysis. Each has proved of application to only a restricted set of circumstances, illustrating the complexity of this field. Increasingly we see the emergence of site-specific strategies with pest management systems being constructed to respond to the critical risk points identified in practice. In the field of pest detection, the trend is towards the development of multi-species lures rather than those of a more specific nature. Further development of chemical attractants for insect detection is in progress (Collins et al., 2007, 2008). 4.4.2 Food protection Most dried food materials are attractive to pest attack, especially those with an equilibrium relative humidity above 65%, and the increasing movement of

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commodities in international trade maintains the constant threat of transporting pest problems. Legislation demanding the highest standards in any food product destined for human consumption is a powerful driver for the elimination of insect contamination of food. Packaging is undoubtedly an effective measure for reducing access of pests to food materials awaiting use by the consumer but, as we have seen, is not invulnerable to pest attack. Any measures to improve packaging design by reducing the chance of incomplete seal and removing joins, folds and corners that are susceptible to mechanical damage or provide leverage for insect mouthparts are an obvious priority. Effective control measures at the importation stage of raw ingredients provide a vital start to the chain that leads to the final product. Streamlining product distribution to reduce residence time in store, and avoidance of storage alongside other less secure products are other goals to avoid infestation problems. All the above measures have economic implications and are only achievable in situations where there is a viable profit margin for the product. Furthermore, although the presence of pests can be minimised, total elimination of pest incidence can never be guaranteed. There is therefore the need for some additional measures to deter pests from remaining on or near the package. Insecticides were an obvious early choice but their application or impregnation leads to the problem of chemical transfer to the food (Highland et al., 1984). The field of insect repellency is one worthy of continued investigation, a non-toxic, non-specific insect and mite repellent being the goal. The industry continues to explore the application of techniques such as modified atmosphere packing to a wider range of products. The atmospheres used to preserve food quality, notably those based on removal of oxygen, are also suitable to prevent survival of insects and mites and so can reduce contamination problems from this source. Research continues to establish the requirements for control and exclusion of pests (Ruidavets et al., 2007, 2009). However, problems can only be avoided if vigilance is maintained and management procedures are optimised and rigorously applied.

4.5

Sources of further information and advice

The field of the protection of stored products from harvest to retail is diverse, encompassing many disciplines of research. In addition to the reference citation list below, much information can be gleaned by sight of the conference proceedings of the four-yearly International Working Conferences on Stored Product Protection (1994, Canberra; 1998, Beijing; 2002, York, UK; 2006, Campinas, Brazil), the most recent one of which was held in Estoril, Portugal, in 2010. Further information is available through the many relevant papers published in specialist journals such as the Journal of Stored Products Research (Elsevier).

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References

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1991. Beetles: Coleoptera. In: Gorham, J.R. (ed.), Ecology and Management of Food-Industry Pests. AOAC, Arlington, VA, pp. 131±176. ASHWORTH, J.R., 1993. The biology of Lasioderma serricorne. J. Stored Prod. Res. 29, 291±303. BARRER, P.M., JAY, E.G., 1980. Laboratory observations on the ability of Ephestia cautella (Walker) (Lepidoptera: Phycitidae) to locate, and to oviposit in response to a source of grain odor. J. Stored Prod. Res. 16, 1±7. BEATSON CAMPBELL, S.H., 1991. Ants: Formicidae, Hymenoptera. In: Gorham, J.R. (ed.), Ecology and Management of Food Industry Pests. US Food and Drug Administration Technical Bulletin No. 4, pp. 207±215. BECK, S.D., 1971. Growth and retrogression in larvae of Trogoderma glabrum (Coleoptera: Dermestidae). 1. Characteristics under feeding and starvation conditions. Ann. Entomol. Soc. Am. 64, 149±155. BEGUM, K., VANITHA REDDY, P., LEELAJA, B.C., RAJASHEKAR, Y., RAJENDRAN, S., 2007. Studies on insect infestation in chocolates. J. Stored Prod. Res. 43, 118±122. BELL, C.H., 1975. Effects of temperature and humidity on development of four pyralid moth pests of stored products. J. Stored Prod. Res. 11, 167±175. BELL, C.H., 1976. Factors governing the induction of diapause in Ephestia elutella and Plodia interpunctella (Lepidoptera). Physiol. Ent. 1, 83±91. BELL, C.H., 1981. The influence of light cycle and circadian rhythm on oviposition in five pyralid moth pests of stored products. Physiol. Ent. 6, 231±239. BELL, C.H., 1991. Activity rhythms linked with foraging behaviour in insecticide resistant and susceptible strains of the saw-toothed grain beetle Oryzaephilus surinamensis. J. Stored Prod. Res. 27, 171±177. BELL, C. H., 2003. Insect pests of stored products in Europe. In: Prakash, A., Rao, J., Jayas, D.S., Allotey, J. (eds), Insect Pests of Stored Products: A Global Scenario. AZRA, Cuttack, India, pp. 56±88. BOCZEK, J., 1991. Mite pests in stored food. In: Gorham, J.R. (ed.), Ecology and Management of Food Industry Pests. US Food and Drug Administration Technical Bulletin No. 4, pp. 57±79. BOWDITCH, T.G., 1998. Insect infestation of packaged foods ± investigation and prevention. Food Australia 50, 230±231. BRENNER, R.J., 1991. The Asian cockroach: Implications for the food industry and complexities of management strategies. In: Gorham, J.R. (ed.), Ecology and Management of Food Industry Pests. US Food and Drug Administration Technical Bulletin No. 4, pp. 121±130. BRICKEY, P.M., GECAN, J.S., ROTHSCHILD, A., 1973. Method for determining direction of insect boring through food packaging materials. J. AOAC 56, 640±642. BURGES, H.D., 1962. Studies on the dermestid beetle Trogoderma granarium Everts V ± Reactions of diapause larvae to temperature. Bull. Ent. Res. 53, 193±213. BURGES, H.D., 2008. Development of the khapra beetle Trogoderma granarium in the lower part of its temperature range. J. Stored Prod. Res. 44, 32±35. CHAMBERS, J., 2002. Where does pest detection research go next? In: Credland, P.F., Armitage, D.M., Bell, C.H., Cogan, P.M., Highley, E. (eds), Advances in Stored Product Protection, Proc. 8th Int. Working Conf. Stored Prod. Prot., York, UK, July 2002, CAB International, pp. 103±109. CHMIELEWSKI, W., 1971. Morphology, biology and ecology of Carpoglyphus lactis (L.,

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1758) (Glycyphagidae, Acarina). Prace Naukowe Instytutu Ochrony Roslin 13, 63± 166 (in Polish with English summary). CLINE, L.D., 1978. Penetration of seven common flexible packaging materials by larvae and adults of eleven species of stored-product insects. J. Econ. Ent. 71, 726±729. CLINE, L.D., HIGHLAND, H.A., 1981. Minimum size of holes allowing passage of adults of stored-product Coleoptera. J. Ga Entomol. Soc. 16, 525±531. COLLINS, D., 2003. Insect infestations in packaged commodities. Int. Pest Control 45, 142± 144. COLLINS, H.E., 1963. How food packaging affects insect invasion. Pest Control 31, 26±29. COLLINS, L.E., BRYNING, G.P., WAKEFIELD, M.E., CHAMBERS, J., COX, P.D., 2007. Progress towards a multi-species lure: identification of components of food volatiles as attractants for three storage beetles. J. Stored Prod. Res. 43, 53±63. COLLINS, L.E., BRYNING, G.P., WAKEFIELD, M.E., CHAMBERS, J., FENNAH, K., COX, P.D., 2008. Effectiveness of a multi-species attractant in two different trap types under practical grain storage conditions. J. Stored Prod. Res. 44, 247±257. COOMBS, C.W., 1978. The effect of temperature and relative humidity on the development and fecundity of Dermestes lardarius L. J. Stored Prod. Res. 14, 111±119. COX, P.D., BELL, C.H., 1991. Biology and ecology of moth pests of stored products. In: Gorham, J.R. (ed.), Ecology and Management of Food Industry Pests. US Food and Drug Administration Technical Bulletin No. 4, pp. 181±194. COX, P.D., DOLDER, H.S., 1995. A simple flight chamber to determine flight activity in small insects. J. Stored Prod. Res. 31, 311±316. COX, P.D., CRAWFORD, L.A., GJESTRUD, G., BELL, C.H., BOWLEY, C.R., 1981. The influence of temperature and humidity on the life cycle of Corcyra cephalonica (Stainton) (Lepidoptera: Pyralidae). Bull. Ent. Res. 71, 171±181. COX, P.D., PARISH, W.E., LEDSON, M., 1990. Factors affecting the refuge-seeking behaviour of Cryptolestes ferrugineus. J. Stored Prod. Res. 26, 169±174. CUNNINGTON, A.M., 1965. Physical limits for complete development of the grain mite, Acarus siro L. (Acarina, Acaridae) in relation to its world distribution. J. Appl. Ecol. 2, 295±306. CUNNINGTON, A.M., 1969. Physical limits for complete development of the copra mite Tyrophagus putrescentiae (Schrank) (Acarina, Acaridae). Proc. 2nd Int. Cong. Acarol. (Sutton Bonington, 1967), pp. 241±248. CUNNINGTON, A.M., 1976. The effect of physical conditions on the development and increase of some important storage mites. Ann. Appl. Biol. 82, 175±178. DE LUCA, Y., 1977. Resistance of plastic packaging to attack by bruchids (Coleoptera). Bollettino di Zoologia Agraria e di Bachicoltura 13, 173±177. EBELING, W., 1991. Ecological and behavioural aspects of cockroach management. In: Gorham, J.R. (ed.), Ecology and Management of Food Industry Pests. US Food and Drug Administration Technical Bulletin No. 4, pp. 85±119. FLINN, P.W., HAGSTRUM, D.W., MUIR, W.E., 1997. Effect of time of aeration, bin size and latitude on insect populations in stored wheat: a simulation study. J. Econ. Ent. 90, 646±651. GORDH, G., HARTMAN, H., 1991. Hymenopterous parasites of stored-food insect pests. In: Gorham, J.R. (ed.), Ecology and Management of Food Industry Pests. US Food and Drug Administration Technical Bulletin No. 4, pp. 217±227. GREENGRASS, J., 1993. Films for MAP of foods. In: Parry, R.T. (ed.), Principles and Applications of Modified Atmosphere Packaging of Food. Blackie Academic & Professional, Glasgow, pp. 1±18.

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1984. Insect infestation of packages. In: Baur, F.J. (ed.), Insect Management for Food Storage and Processing. The American Association of Cereal Chemists Inc., St. Paul, MN, pp. 311±320. HIGHLAND, H.A., SIMONAITIS, R.A., BOATRIGHT, R., 1984. Insecticide-treated film wrap to protect small packages from infestation. J. Econ. Ent. 77, 1269±1274. HINTON, H.E., 1945. A Monograph of the Beetles Associated with Stored Products, Vol. 1. British Museum (Natural History), London. HOHMAN, R.L., 1991. Food industry self-inspection. In: Gorham, J.R. (ed.), Ecology and Management of Food-Industry Pests. AOAC, Arlington, VA, pp. 519±527. HOWE, R.W., 1965. A summary of estimates of optimal and minimal conditions for population increase of some stored products insects. J. Stored Prod. Res. 1, 177±184. HOWE, R.W., 1991. Spider beetles: Ptinidae. In: Gorham, J.R. (ed.), Ecology and Management of Food-Industry Pests. AOAC, Arlington, VA, pp. 177±180. IMMS, A.D., 1951. A General Textbook of Entomology. 8th edn, Methuen, London. JHA, A.N., YADAV, T.D., 1991. Insect proof packaging against Lasioderma serricorne (F.) and Stegobium paniceum (Linn.), pests of spices. Indian J. Ent. 53, 401±403. KARNAVAR, G.K., 1984. Studies on the influence of larval treatment on the fecundity of the stored grain pest Trogoderma granarium Everts. J. Ent. Soc. SA 47, 67±73. KHAN, M.A., 1983. Investigation on the invasion of egg-larvae of stored product insects through different sizes of pores of the packaging material. Anz. SchaÈdlingsk. Pflanzenschutz Umweltschutz 56, 65±67. KHARE, B.P., SHUKLA, R.P., 1979. Penetration of different packaging materials by stored product insects. Indian J. Agric. Sci. 49, 116±117. LALE, N.E.S., DUDU, P., OKIWELU, S.N., 1996. The effects of temperature and humidity on oviposition and developmental period of Oryzaephilus mercator (Fauvel). Postharvest Biology and Technology 8, 75±79. LOCATELLI, D.P., GAMBARO, J., 1999. Susceptibility of pasta packaging to the attack of some infesting insects. Tecnica Molitoria 50, 525±530. MAUNSELL, K., WRAITH, D.G., CUNNINGTON, A.M., 1968. Mites and house dust allergy in bronchial asthma. The Lancet 7555, 1267±1270. MOWERY, S.V., MULLEN, M.A., CAMPBELL, J.F., BROCE, A.B., 2002. Mechanisms underlying sawtoothed grain beetle (Oryzaephilus surinamensis [L.]) (Coleoptera: Silvanidae) infestation of consumer food packaging materials. J. Econ. Ent. 95, 1333±1336. MUELLER, D.K., 1998. Stored Product Protection: A Period of Transition. Insects Limited Inc., Westfield, IN. MULLEN, M.A., MOWERY, S.V., 2000. Insect-resistant packaging, Int. Food Hygiene 11, 13±14. NA, J.H., RYOO, M.I., 2000. The influence of temperature on development of Plodia interpunctella (Lepidoptera: Pyralidae) on dried vegetable commodities. J. Stored Prod. Res. 36, 125±129. NAIR, K.S.S., DESAI, A.K., 1973. The termination of diapause in Trogoderma granarium Everts (Coleoptera: Dermestidae). J. Stored Prod. Res. 8, 275±290. NAYAK, M.K, DALGLISH, G.J., BYRNE, V.S., 2005. Effectiveness of Spinosad as a grain protectant against resistant beetle and psocid pests of stored grain in Australia. J. Stored Prod. Res. 41, 455±467. NEWTON, J., 1988. Insects and packaging ± a review. Int. Biodeterioration 24, 175±187. NGUYEN, D.T., HODGES, R.J., BELMAIN, S.R., 2008. Do walking Rhyzopertha dominica (F.) locate cereal hosts by chance? J. Stored Prod. Res. 44, 90±99. PARRY, R.T., 1993. Introduction. In: Parry, R.T. (ed.), Principles and Applications of Modified Atmosphere Packaging of Food. Blackie Academic & Professional,

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1994. Larval secretions and food odours affect orientation in female Indian meal moths, Plodia interpunctella. Ent. Exp. Appl., 71, 185±193. PREVETT, P.F., 1971. Some laboratory investigations on the development of two African strains of Plodia interpunctella (Hubner) (Lepidoptera: Pyralidae) with particular reference to the incidence of diapause. J. Stored Prod. Res. 7, 253±260. RAICHOUDHURY, D.P., JACOBS, S.E., 1937. Experiments on the sterility of Ephestia kuehniella in relation to high temperature (30 ëC). Proc. Zool. Soc. London A107, 283±288. RAO, K.M., JACOB, S.A., MOHAN, M.S., 1972. Resistance of flexible packaging materials to some important pests of stored products. Indian J. Ent. 34, 94±101. RUIDAVETS, J., PONS, S.J., SALAS, I., 2007. Evaluation and characterization of damage produced in packaging films by insect pests. IOBC/WPRS Bulletin 30, 127±132. RUIDAVETS, J., CASTANE, C., ALOMAR, O., PONS, S.J., GABARRA, R., 2009. Modified atmosphere packaging (MAP) as an alternative measure for controlling ten pests that attack processed food products. J. Stored Prod. Res. 45, 91±96. SHAH, V., LEARMOUNT, J., PINNIGER, D., 1996. Infestations of German cockroach Blattella germanica (L.) in multi-occupancy dwellings in a London borough a preliminary study into the relationship between environment, infestation and control success. In: Wildey, K.B. (ed.), Proc. 2nd Int. Conf. Insect Pests in the Urban Environment. Edinburgh, pp. 203±209. THIND, B.B., CLARKE, P.G., 2001. The occurrence of mites in cereal-based foods destined for human consumption and possible consequences of infestation. Exp. Appl. Acarol., 25, 203±215. TREMATERRA, P., SCIARRETA, A., TAMASI, E., 2000. Behavioural responses of Oryzaephilus surinamensis, Tribolium castaneum and Tribolium confusum to naturally and artificially damaged durum wheat kernels. Ent. Exp. Appl., 94, 195±200. TREMATERRA, P., GENTILE, P., BRUNETTI, A., COLLINS, L.E., CHAMBERS, J., 2007. Spatio-temporal analysis of trap catches of Tribolium confusum du Val in a semolina-mill, with a comparison of male and female distributions. J. Stored Prod. Res. 43, 315±322. TURNER, B.D., 1994. Liposcelis bostrichophila (Badonnel) (Psocoptera): a stored food pest in the UK. Int. J. Pest Manag. 40, 179±190. TURNER, B.D., ALI, N., 1996. The pest status of psocids in the UK. In: Wildey, K.B. (ed.), Proc. 2nd Int. Conf. Insect Pests in the Urban Environment. Edinburgh, pp. 515±523. TURNER, B.D., MAUDE-ROXBY, H., PIKE, V., 1991. Control of the domestic insect pest Liposcelis bostrichophila (Badonnel) (Psocoptera): an experimental evaluation of the efficiency of some insecticides. Int. Pest Control 33, 153±157. WHITE, R., ROBERTS, R., 1992. Developments in Modified Atmosphere and Chilled Foods Packaging. A Literature Review. Pira Reviews of Packaging, Pira International. WOODROFFE, G.E., 1951. A life-history study of the brown house moth. Bull. Ent. Res. 41, 529±533. YERINGTON, A.P., 1978. Insects and package seal quality. Modern Packaging 51, 41±42. YERINGTON, A.P., 1983. Efficiency of various overwraps and seal tightness in excluding insects from dried-fruit cartons. Environ. Ent. 12, 1310±1311. YOSHIDA, T., 1976. The effect of crowding on the rate of reproduction in the squarenecked grain beetle Cathartus quadricollis (Guer.) (Coleoptera: Silvanidae). Scientific Reports of the Faculty of Agriculture, Okayama University 45(8), 10±16.

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5 The influence of ingredients on product stability and shelf life N. W. G. Young, Danisco A/S, Multiple Food Applications, Denmark and University of Chester, UK and G. R. O'Sullivan, Danisco A/S, Multiple Food Applications, Denmark

Abstract: This chapter discusses the role and influence of ingredients on shelf life, and how they can be utilised in shelf life maintenance and extension. Discussing the role of moisture management, microbiological contaminants, and oxidative effects, ingredient-based solutions will be presented to effectively achieve shelf life extension. Future trends are speculated to focus on general reduction of food spoilage and wastage, with concomitant shelf life extension, which are likely to be achieved through multidisciplinary collaborations between biotechnology and nanotechnology. This is envisaged to lead to new bio-based, nano-scale ingredients with the power to extend shelf life and maintain food quality and value. Key words: shelf life, moisture control, oxidation, microbiological contamination, humectants, cryoprotectants, antimicrobials, antioxidants, protective cultures.

5.1

Introduction to shelf life

5.1.1 What is shelf life? Shelf life has a number of connotations and definitions; to the general consumer, shelf life is the time limit, given typically on the best-before label, of how long the particular food can be kept before it should be thrown away. Or put another way, shelf life represents the length of time before the food is considered to be unsuitable for human consumption. However, shelf life can equally be given as the length of time a food product can be stored and displayed whilst still

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maintaining an acceptable quality or specific functionality. Shelf life therefore typically says nothing about the safety of the given food product. A product that passes its shelf life date does not immediately become dangerous for human consumption, but rather no longer conforms to a set of given quality parameters. There are food products that can, if kept well, remain fresh for days after their shelf life date subject to no bacterial contamination ± pasteurised milk, for example. But for some products, particularly where development of bacteria can take place, leaving foods beyond their shelf life date can result in the food being dangerous to eat and give rise to food poisoning. These products typically have their shelf life and expiry dates to correspond. The aim of this chapter is to probe the areas affecting shelf life, how it can be influenced and what ingredients can be used to extend the shelf life of a food product.

5.2

Methods of shelf life extension

There are a range of conditions and factors which influence the shelf life of a food product: temperature changes, exposure to light, mechanical stress, transmission of gases, humidity changes, and contamination with microorganisms and spores. Controlling these factors to minimise their effect will therefore increase the shelf life of a product, and can be achieved by a number of approaches. Packaging technology can be used to provide physical barriers to prevent the onset of certain effects, e.g. light exposure or gaseous (including moisture) exchange. The most obvious example of minimising the exposure to light is the coloured bottles used in beer, wine, port, and champagne production. By being coloured, usually green or amber/brown, the bottles prevent certain wavelengths of light from passing into the product, thereby minimising the otherwise damaging exposure. Similarly, packaging materials can be made to place a physical barrier between the foodstuff and the outside world, which can then hinder gaseous transfer, or indeed be placed under specific controlled atmospheres, e.g. potato crisps being packed in CO2-rich environments to preserve crunchiness, meat being packed under O2-rich environments to preserve red colouring etc. Individual ingredients can be added to food products which are able to deal with the effects of microbiological, oxidative, moisture control and effects of temperature. 5.2.1 Microbiological Extending shelf life by means of ingredients that are antimicrobial in character is commonly referred to as addition of preservatives, where the preservative itself must delay or inhibit microbiological contamination and spoilage of food. These preservatives can be chemical or based on natural ingredients. This class of

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ingredients act against patently visible spoilage such as moulds, yeasts and bacteria, but they also prevent the formation of the toxins that otherwise would be formed by the bacteria and moulds. Thus, they regularly perform two functions: product safety, where they increase the shelf life; and food safety, where they guard against the dangers of the microbiological contamination. The recent consumer-based desire to move from chemical to natural solutions has resulted in a range of new antimicrobial ingredients such as fermentates and protective cultures. However, traditional natural antimicrobials such as nisin and natamycin are still very much to the fore. Fermentates, protective cultures, nisin, and natamax are briefly outlined below. 5.2.2 Oxidative Controlling oxidation of food materials is achieved through a group of ingredients termed antioxidants. These delay the oxidative spoilage of food, and as such tend to only protect food quality, and less so food safety. Unless the oxidative products are directly harmful then the worst aspect about a food which has undergone oxidation is that it will taste bad, as opposed to being outright harmful. In order for the antioxidant to work, they must react quickly with oxygen, thereby acting as a quencher, thus preventing the oxygen's chemical interaction with the food. Oxidation occurs during processing and storage, and is particularly prevalent in fats containing unsaturated fatty acids. It is oxidation of these unsaturated fatty acids that causes the fats to go rancid, smell bad and taste unpleasant. Control of this autoxidative process can be managed through chemical compounds and now increasingly natural extracts. Synergistic effects can be observed when two antioxidants are combined, such that the mixture shows a stronger degree of antioxidative properties than the two antioxidants alone. However, increasing the dosage does not necessarily translate to a greater degree of antioxidative effect. Antioxidants themselves are optimally active only within a relatively narrow concentration range. Increasing the concentration can actually tip their function to becoming prooxidative! The three traditional chemical-based antioxidants, which are very effective are: BHA (butylated hydroxy anisole), BHT (butylated hydroxy toluene), and TBHQ (tertiary butyl hyroquinone). These are examples of phenols. There are many natural extracts which can be utilised for the antioxidative property, but the two main commercial examples are rosemary extract and green tea extract. These specific ingredients will be explored in further detail in Section 5.9.2. 5.2.3 Humectants Humectants are ingredients for moisture management in foods. Water is the major ingredient contributing to the texture and shelf life properties of food. Controlling the way water behaves in foods is known as moisture management. Humectants are a class of food ingredients or additives that are one of the tools

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available to control the movement of moisture in food. There are three major elements to food or beverage shelf life in terms of the benefits of incorporating a humectant. The most critical is that the product must not be spoiled by bacteria, yeast or moulds that will cause off-flavours and more seriously contain pathogens or toxins that could cause illness and even death. The next factor is the texture and flavour of the food product should be maintained for the duration of the shelf life of the product. Control of moisture within a product can also reduce the negative effects caused by oxidation and hydrolysis of food components within the food matrix that cause loss of nutritional availability of macronutrients and the loss of highly sensitive micronutrient food components such as vitamins A, C, D and E along with polyphenolic compounds.

5.3

Movement of moisture in food systems

Moisture management, or the control of the behaviour of water in foods, is the most important property of a humectants, a food ingredient which specifically influences the movement of water in a food matrix. The traditional view of a humectant is a substance used primarily in foods and cosmetic products to help retain moisture. These substances are also called hygroscopic, which means that they are able to absorb moisture from the atmosphere. A good humectant has been described as an ingredient which resists changes in moisture content as the humidity of its surroundings changes and thereby limits the exchange of water to and from water-containing products. These descriptions of a humectant ingredient or system of ingredients are too limited in the design of today's products and manufacturing processes. A humectant ingredient or humectant system will have a number of functions in a food matrix. It will: · influence the water activity of the whole food system or components within it · bind water or influence transport of water within the food product or to the environment · keep the texture and taste of the product within acceptable parameters for consumer acceptability · contribute to food safety of the product · help to keep the nutritional value of the macro- and micronutrients. 5.3.1 Water activity (aw) To describe the behaviour of food matrices, food ingredients and environmental humidity properties, it is necessary to have a means of measurement. The earliest way of describing these properties was termed as relative humidity, which compared all food matrices, environments and ingredients to the humidity of air above a pure water solution at 1 bar pressure and 25 ëC. We still use the same information today but use it in terms of water activity (aw), where a value of 1.0 would be the aw of pure water. The food developer is trying to optimise

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the aw difference between the food product and the humidity of the environment and/or another component in the food matrix. The value aw is the amount of potential free energy the water has in a system, and so the difference between food matrix aw and environment aw or other food component aw is an accurate measure of the available energy to drive the movement of water in the direction of lowest aw. This value is a thermodynamic constant that informs the developer that water will move in a given direction, but does not give the velocity at which the water will move. This is the kinetic behaviour of the system, which is strongly related to the structure of the food matrix and temperature. In the traditional meaning of the term, a humectant ingredient is used to adjust the aw of the components in the food matrix or the complete food. Today we also consider that a humectant can be a food ingredient or ingredients that can alter the physical or chemical behaviour of components within the food matrix or the complete food. 5.3.2 Fick's Law The most commonly used model for the kinectic behaviour of moisture in foods is described by a process known as Fick's law of diffusion and refers to movement of water through a binary solid mixture under a constant vapour (aw) pressure gradient. Fick's first law of diffusion is given by: dC 5:1 J ˆ ÿD dx m2 g (H2 O) g (H2 O) sec ˆ Jˆ m3 m sec m2 where J is the flux defined as the amount of moisture exchanged per unit of time per unit area g (H2O)/sec m2, C is the concentration as mass per unit volume, x is the distance transversed by the concentration gradient, D is the diffusion coefficient (L2/time), and dC/dx is the concentration gradient. The diffusion coefficient D of water in solid materials is the effective moisture diffusivity, which is not an overall transport property including all mechanisms such as capillary action or changes in state such as Tg (glass transition temperature). 5.3.3 Raoult's Law When we are describing a system in terms of the aw, Raoult's law is used to predict how ingredients in a system behave in terms of solutes and it is reasonable to expect that the lower the average molecular weight of a solute, the larger is its effect on decreasing the activity of water in a solution (at equal concentration) since: aw ˆ Pw =Pw 0 ˆ

xw

5:2

where Pw is the water vapour pressure of the sample at a temperature T, Pw0 is the water vapour pressure of pure water at a temperature T,
is the activity

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coefficient (accounts for the deviation of solution properties from Raoult's law at high solute concentration), and x is the mole fraction of water. The lower the molecular mass of an added solute, the higher is the number of mole contribution and the lower is the water mole fraction in the solution (x) and subsequently the lower is the aw of the solution. This gives a simple explanation of the function of the commonly used humectant ingredients glycerol (92.10 Da), sorbitol (182.2 Da) and salt (58.44 Da), simply based on their molecular mass making them very effective at reducing aw compared to other ingredients of a food system sugar such as starch with a range of very high molecular mass typically 5±10  107 Da. Reducing aw alone can be enough to prolong the shelf life of the product but conveniently some of these commonly used humectant ingredients also behave as plasticisers. 5.3.4 Water and humectant ingredients as plasticisers In a number of food systems the aw model alone can be enough to choose suitable humectant ingredients and the required moisture content of a food. The aim of keeping moisture levels constant in food matrices is to avoid changes in molecular structure of ingredients such as proteins, starches and hydrocolloids as well as crystallisation that can occur when water content is reduced over time. These changes in molecular state cause the food product to have an unacceptable texture or taste to the consumer. Modern understanding of the behaviour of water in foods has progressed because of the development of very sensitive analytical techniques such as nuclear magnetic resonance (NMR), differential scanning calorimetry (DSC) and other types of spectroscopy and imaging techniques to determine how water is behaving in the food matrix at a molecular level. The movement of water from key regions or zones in the food matrix is the major factor in food shelf life and changes in vibrational states of the water molecule itself has been found to have a bigger influence on food taste and texture than water being lost to the external environment. Managing these subtle changes in the behaviour of water in food systems is a challenge for the development of the next generation of humectant ingredients. Presently other ingredient systems such as enzymes and emulsifiers are used to counteract the changes in the molecular structure of food components and antioxidants and antimicrobials to maintain the product in terms of taste and safety over the required shelf life. One major feature of the deterioration in texture in foods such as bread and cakes is losing softness, and this is linked to the mobility of the food structure that is mostly based on starches or proteins and sugars that are plasticised (softened) by water. 5.3.5 Glass transition (Tg) The glass transition Tg is a kinetic process that relates to the change in property observed when a supercooled, malleable liquid or rubbery material is changed into a disordered solid glass upon cooling. This is a reversible process and when

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the mass is heated the brittle glass with a viscosity of 1012 Pa s is changed into a supercooled liquid or a rubbery material. The glass transition occurs over a temperature range, the width of which is controlled by the heterogeneity of the system. The greater the heterogeneity of the system, the wider the glass transition temperature range, which is mainly affected by the water content and the average molecular weight of ingredients in the food system. The glass to rubber or liquid transition is accompanied by definite changes in the physical properties of the material with temperature such as increase in entropy, heat capacity and volume and a decrease in both rigidity and viscosity. These changes in physical properties can be used to determine the glass transition temperature (Tg) of the food system. The anhydrous Tg of an individual component can be a useful tool to predict if a humectant ingredient can act as a plasticiser. If an ingredient has a Tg that is below room temperature, such as ÿ3.00 ëC for sorbitol, it will be a liquid and capable of lubricating the food system. If it is higher than room temperature, it is a solid and therefore not capable of lubricating the food system. The other aspect of the ingredient is molecular mass, and low molecular mass ingredients have a large effect on Tg and therefore softness of food systems such as bread. The commonly used humectant ingredients glycerol and sorbitol are of small molecular mass and are capable of plasticising the large molecular mass components such as the starches and proteins in bread and cake, keeping them softer over their shelf life even when moisture has been lost to the environment or transferred within the food matrix. Texture is governed by the way the structure of water is manipulated by other ingredients and how water affects the structure of ingredients contained in the food matrix. In confectionery, for example, there are products known as jellies or gummies with a pleasant taste and texture made by forming a gel with water sugars as well as a suitable acid and flavour with only a small amount of carrageenan, pectin or gelatine. These hydrocolloids are able to order water into relatively firm and elastic structures. The same can be seen in meat products where proteins with water create the complex structure and texture of meat. These examples are of foods with high water content, but water plays just as important a role in controlling the texture of foods containing very little water such as the bakery products wafers and biscuits. The use of humectant ingredients that can control aw and have an effect on plasticising starches and proteins can only take the developer so far in extending the textural shelf life of a food product. If the market requires much longer shelf life for food products, then more complex humectant systems of ingredients are needed. 5.3.6 Humectant systems The function of ingredients as humectants on the shelf life and stability of food is different depending on the aw and shelf life expectancy the market has for the product. For example, bread has an aw of about 0.95. However, another factor about bread that determines how quickly it is subject to microbiological spoilage

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is its pH (or acidity). Bread has a pH of about 5.3±5.8 which means it is slightly acid. This also helps keep it safe to eat on the shelf. One way to estimate how quickly bread will be subject to microbiological spoilage would be to look at its water content. For example the percentage of water in several breads is: Navaho fry bread 26%, banana bread 29%, toasted white bread 30%, plain white bread 36%, oat bran bread 44% and canned Boston brown bread 47%. In bread the most common humectant is sucrose, which is used to reduce aw but has the consequence of making the bread taste sweet and having an effect on texture. In countries such as France consumers once accepted the short shelf life of bread and bread was bought fresh every day or more often as required, but now consumers purchase breads with shelf life up to seven days. In the United States consumers would be happier with much longer shelf life and commonly want to keep bread for two weeks. It is possible to have a humectant system that will give packaged bread an almost indefinite shelf life. Bread may have a shelf life of several months by proper control of aw, pH, packaging conditions, and by addition of antimicrobial compounds and dough conditioners. The aw of a white pan bread was effectively lowered from 0.97 to 0.92±0.93 by addition of 7% sorbitol, 1% propylene glycol and 2% glycerol (flour basis). Incorporation of 0.3% lactic acid powder to the bread reduced its pH to 5.0. Other formulation changes included 10% shortening and addition of emulsifiers such as mono- and diglycerides and enzymes such as xylanase, which help prolong the shelf life of bread by modifying the arabinoxylans in flour, thereby altering water distribution in the dough. This allows more free water to be absorbed by the starch and the gluten proteins during the baking process. Some of the gluten proteins and starch are then kept in the amorphous stage for a longer time, rendering them unable to contribute to bread firmness (anti-staling). The resulting humectant system bread was satisfactory for baking and sensory quality. To prevent dehydration and to exclude oxygen, the bread was packaged in a partial CO2 atmosphere in a retort pouch. The packaged humectant system bread was microbiologically stable up to about four months. The growth of Aspergillus flavus, Staphylococcus aureus and other aerobic organisms was inhibited. However, pH of the product should be lowered to 4.8 to guard against anaerobic organisms. Table 5.1 gives examples of wheat/bakery type products. In the case of bread the humectant system used was mostly compensating for water losses from a high aw system to the environment. At the other end of the aw scale, we have pastry products such as flans/quiches where we have a relatively dry crumbly pastry in contact with a high moisture filling. In the case of the flan/quiche the humectant system is trying to counteract the uptake of water into the system. For the manufacturer just a few more days on the shelf life in terms of texture of the product makes the logistics of the retailer much easier in managing demand and stock rotation in the retail outlet. For flans/quiches, an addition of just 2% of polydextrose to the dough before baking is enough to make the pastry keep its texture for 2 extra days compared to the control product. This is the consequence of polydextrose having a high enough Tg compared to ambient temperature whilst binding moisture in the

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Table 5.1

Bakery product, water activity and typical shelf life

Product

aw

Pizza base

0.918

Madeira cake

0.758

Flan/quiche

0.724

Wafer

0.428

Rich tea biscuit

0.094

Typical shelf life A toasted bread with shelf life of a number of days mostly used fresh Sugar/s content reduces water activity and increases shelf life to 2±4 weeks depending on addition of humectant systems Reduced water activity associated with reduced water content and addition of salt. Shelf life is 2 days to 1 week This is a very low water content product and this gives the low aw and, if in airtight packaging, has shelf life of 9 months Low water content and water binding properties of gluten give a very low aw and shelf life of 9 months with airtight packaging and storage

glassy starch polydextrose matrix. The water controlling behaviour of polydextrose is a good example here as it can be used as a model to compare other ingredients and food systems. 5.3.7 Kinetics of water adsorption and desorption Method A small amount of sample (between 2 and 5 mg) was loaded inside the glass crucible and then located in the sample chamber of the dynamic vapour sorption (DVS) analyser (Surface Measurement Systems). The temperature was controlled to 25 ëC  0.5. The sample was first exposed to a dry N2 flow (RH ˆ 0%), followed by hydrated N2 flow of varying relative humidities (0, 10, 20, 30, 40, 50, 60, 70, 80, 90 and 95%). Hydrating and dehydrating cycles were used to establish the sorption±desorption isotherms of the polydextrose material. The results from this evaluation can be seen in Fig. 5.1. It can be seen that polydextrose is able to gain water until a liquid solution is produced, but on drying the loss of water occurs very slowly and this behaviour can keep textures of food matrices softer or more pliable. However, in the case of the pastry system for the quiche/flan example, another important behaviour with water and Tg is given in the next section, showing not only that polydextrose can hold on to this water but also remain in the glassy state at ambient temperature and so the system remains brittle or, in terms of the quiche/flan, crispy or crumbly. 5.3.8 Effect of water on physical properties: glass transition (Tg) Method The glass transition temperature (Tg) of the four polydextrose materials was measured over a range of water contents using differential scanning calorimetry (DSC). Four water contents were achieved as follows:

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The bold line shows the change in relativity humidity (RH%) and the increase in mass of the test sample is given as percentage increase in weight by the thin line.

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· Samples were hydrated over two different RHs in sealed chambers over saturated salt solution RH ˆ 55% (Na2Cr2O7) and RH ˆ 75% (NaCl). These were selected based on the sorption/desorption isotherms established above using the DVS. · Dry samples: these were obtained by first drying the samples at room temperature over P2O5 followed by vacuum drying (70 ëC) overnight. This protocol was adopted in order to minimise chemical degradation of the material by heat/drying.

The DSC measurements were carried out using a Perkin Elmer DSC7. The instrument was calibrated for temperature and enthalpy with indium (To ˆ 156.6 ëC and
H ˆ 28.45 J gÿ1) and cyclohexane (To ˆ 6.7 ëC). The calorimeter was equipped with an intra-cooler allowing cooling down to temperatures of ÿ60 ëC. Approximately 50 mg of sample were sealed in high pressure stainless steel DSC pans prior to analysis. The reference was an empty pan of the same type as the one used for the sample. The samples were first heated to undergo the glass±rubber transition (first heating scan) in order to eliminate their thermal history (time, temperature, drying, etc.). The sample was then rapidly cooled (~ 50 ëC/min) before being reheated (second heating scan). The thermograms were acquired at a heating rate of 10 ëC/min. The temperatures at which the step change in heat capacity (cp) associated with the glass transition were defined as onset (onset of the cp change), mid-point (temperature for 50% change in cp occurred,
Cp1=2 ) and the end temperatures. The glass transition temperatures were determined on the second heating scan. The plasticisation of polydextrose by water was modelled by fitting a widely used equation proposed by Ten-Brinke et al. (1983), equation derived from the well-known Couchman±Karasz equation (1978) which, based on a thermodynamic understanding of the glass-rubber transition, describes the composition dependence of Tg (see Fig. 5.2). The equation describing very satisfactorily the experimental data for polydextrose is: Tg ˆ

Wp
Cpp Tgp ‡ Ww
Cpw Tgw Wp
Cpp ‡ Ww
Cpw

5:3

where Tg is the glass transition of the polydextrose±water mixture (K), WP is the weight fraction of polydextrose, Ww is the weight fraction of water, TgP is the glass transition of the polydextrose material of interest) (K), Tgw is the glass transition of water (134 K),
Cpp is the difference in specific heat capacity between the liquid and the glassy states at Tg for polydextrose (J gÿ1 Kÿ1), and
Cpw is the
Cp for water (1.94 J gÿ1 Kÿ1). It can be seen in Fig. 5.2 that, by drawing an imaginary line from the water at 8±9% w/w content to the result line of the plot of the modified Couchman± Karasz equation to the Tg value on the y axis, we have a Tg value above 30 ëC and for a product consumed cool ± this is well within the Tg zone that will make the product have a crispy or crumbly texture.

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Fig. 5.2

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Modified Couchman±Karasz equation fitted to Tg values for polydextrose of given water contents.

5.3.9 Humectants as anti-crystallisation agents Keeping food materials such as sugar as starches and proteins in the plastic/ rubbery state is one property of a humectant ingredient or system. Crystallisation of ingredients within the food matrix is also a major texture, taste and food safety deterioration mechanism. For example, if sugars crystallise in a food product, the water of hydration will be lost and this creates zones of high water activity that can form on the surface of a product making the growth of food spoilage organisms such as bacteria, yeasts and moulds possible. This spoils the product appearance, smell and taste but also there is the possibility of growth of pathogenic bacteria and formation of toxins on the surface. Potentially more dangerous is formation of high water activity zones within the food matrix that can provide conditions for trace amounts of microorganisms or their spores to grow unseen producing poor taste, but also the potential for harmful toxins or bacteria without the warning signs of poor appearance or smell. In some systems the addition of a humectant ingredient alone is not sufficient to protect a food product from the formation of these high water activity zones, and it is common to use a preservative such as potassium sorbate or natural vegetable extracts to prevent the growth of microorganisms. To prevent crystallisation it is common to include in the food matrix a complex mixture of sugars or low molecular mass polyols. This reduces the saturation level of individual components within the food system and increases the solubility of the individual components. This is an additional benefit of glycerine, sorbitol and sugar syrups such as glucose syrup and invert sugar syrups that not only reduce water activity but also reduce the potential for crystallisation of sugars and starches in food systems.

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5.3.10 Starch retrogradtion or crystallisation A special case for consideration is the crumb-softening/anti-staling effect in wheat bread caused by emulsifier±starch interactions. Starch-based foods in the form of bakery products, such as extruded cereals, processed potatoes and pasta, contain emulsifiers in order to facilitate industrial production or prolong shelf life and improve texture. Starch consists of two types of polysaccharide, amylose and amylopectin, the ratio in wheat starch being approximately 1:4. Amylose is the water-soluble part of starch and this may cause various undesirable effects, such as stickiness in dough or pasta. In bread, soluble amylose retrogrades 6±8 hours after baking. This is the reason for the wellknown increase in bread firmness and is part of the staling process. When monoacyl lipids are present the amylose and lipid react and form a waterinsoluble complex. This prevents any further physical changes in the dissolved amylase reducing stickiness and preventing further retrogradation/crystallisation of the starch. Wheat starch contains amylose complexes with native isolecithin. Added emulsifiers form similar helical inclusion compounds with amylose. The amylose complexing ability of emulsifiers is strongest with monoacyl lipids such as distilled, saturated monoglycerides with a C16±C18 chain length as shown in Table 5.2. The complexing effect of various emulsifier types varies according to the fatty acid chain length, degree of unsaturation, degree of esterification (content of diacyl and triacyl esters) and the dispersibility of the emulsifiers.

5.4

Food spoilage due to water activity

Fortunately the development of interesting and pleasant tastes and textures has gone hand in hand with cooking, salting, smoking, fermenting and drying of foods that mankind has developed by trial and error over the last 12,000 years or more, to preserve food as both the nomadic hunter gather and farmer. Reducing water content, lowering pH, adding salt and some components of smoke prevent the growth of spoilage bacteria. Food preservation was necessary for nomadic peoples to transport foods and also to make the most of seasonal availability of some types of food. Most of the world's population today does not live on farms near to the source of their food, where food can be cooked or Table 5.2

Emulsifier type and complexing strength with amylose

Type of emulsifier

Amylose complexing index

Distilled monoglycerides based on · hydrogenated palm oil · hydrogenated soya bean oil · palm oil · soya bean oil

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Table 5.3 Examples of foods and microorganisms that can cause food spoilage at the indicated aw range aw

Microorganisms growing in this aw range

Examples of foods

1.00±0.95

Pseudomonas, Escherichia, Proteus, Shigella, Klebsiella, Bacillus, Clostridium perfringens, C. botulinum E, G, some yeasts

Fresh foods, foods containing less than 40% sucrose or 7% salt, canned foods, processed cheese, types of sausages, bread.

0.95±0.91

Salmonella, Vibrio parahaemolyticus, Clostridium botulinum A, B, Listeria monocytogenes, Bacillus cereus

Foods containing 50% sucrose or 12% salt, for example: mayonnaise, bacon, some hard cheeses, raw ham.

0.94 0.91±0.87

0.86

Growth and toxin production by all types of Clostridium botulinum Staphylococcus aureus (aerobic), many yeasts (Candida, Torulopsis, Hansenula), Micrococcus)

Foods containing 65% sucrose or 15% salt such as dry ham, fruit jams, fruit juice concentrates, some hard cheeses

Aerobic growth of Staphylococcus aureus

0.87±0.80

Most moulds (mycotoxigenic penicillia), Staphylococcus aureus, most Saccharomyces (bailii) spp., Debaryomyces

Foods containing 15±20% water: fruit cake, high moisture prunes, sweetened condensed milk, pectin gummies

0.80±0.75

Most halophilic bacteria, mycotoxigenic aspergilli

Foods with 26% salt or very high sugar content: salted fish, molasses, prunes, fondants, sugar syrups

0.80

Production of mycotoxins

0.75±0.65

Xerophilic molds (Aspergillus chevalieri, A. candidus, Wallemia sebi), Saccharomyces bisporus

Foods containing less than 10% water: dried dates, figs, nuts, rolled oats

0.65±0.61

Osmophilic yeasts (Sacharomyces rouxii), a few moulds (Aspergillus echinulatus, Monascus bisporus)

Confectionery products, dried fruits containing 15±20% water, honey

Below 0.61 No proliferation

Dried milk, instant coffee, dried egg, spices, crackers, flour, cereals

eaten almost immediately. Now most people live in cities and so the necessity to transport food sometimes large distances and to store food is a necessity of modern day living. Table 5.3 shows water activity and microorganisms that grow at a given aw range. Clearly, reducing aw reduces the number of viable species of bacteria and therefore the chance of spoilage and the risk of the food product being dangerous to human health as well as poor texture and taste.

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5.4.1 Food spoilage due to chemical reactivity of water Foods are composed of the macronutrients protein, carbohydrates and fats, and micronutrients such as vitamins, flavanoids and polyphenolic compounds and minerals. Hydrolysis is the major reaction by which water can degrade food components and can reduce the nutritional benefit of food, particularly reactive components such as vitamins A, C, D and E along with polyphenols. The macronutrients are not affected quite so much in terms of nutritional value but are responsible for the deterioration in colour and taste of a food. The rancid taste of foods is due to hydrolysis of fat in the food matrix producing free fatty acids and their salts that are detected by the human palate at only parts per billion levels. Evolution created this response in humans as an early warning of food safety. Hydrolysis of proteins tends to cause discoloration of food products and the loss of availability of proteins. Carbohydrates when hydrolysed break down to simpler sugars such as sucrose, dextrose and fructose that will alter the sweetness profile and sweet taste, which is typical of ripened fruit we have come to enjoy. The disadvantage of this is that simple sugars are more reactive molecules and other reactions begin breaking down the food matrix. However, in the absence of other elements or high temperatures, hydrolysis occurs relatively slowly but is drastically increased by a number of factors. 5.4.2 Lipid oxidation (rancidity) and enzymatic browning The two major chemical changes which occur during the processing and storage of foods that lead to a deterioration in sensory quality are lipid oxidation (rancidity) and enzymatic browning. Enzymes that are naturally occurring in every living organism play a role in the spoilage of the food such as browning of apples, potatoes or tomatoes that are cut and exposed to air. The enzymes present catalyse oxidation reactions converting colourless compounds into brown coloured components. In processed food most enzymes are denatured during cooking and heating processes. Foods can become tainted by chemical compounds in the environment and also there are oxidation reactions that occur from oxygen free radicals in the air that permeate into foods and are stabilised by water forming hydrogen peroxide producing a very powerful oxidising agent. This mechanism of food spoilage can be controlled by the addition of chemically manufactured antioxidants or by adding natural extracts such as green tea polyphenols to the humectant system. Hydrolytic rancidity is caused by the presence of water, which causes triglycerides to split into glycerol and fatty acids. The rate of hydrolysis in the presence of water alone at ambient temperature is very slow but, if enzymes (lipases) and microorganisms (bacteria, moulds and yeasts) are present, hydrolysis can happen very quickly. This type of rancidity results in the formation of free fatty acids and their salts, but is quite common in emulsions such as butter, margarine and cream. High temperatures in the presence of moisture, oxygen, high pH and light are among the factors that speed up rancidity as well as oxidative deterioration of other sensitive ingredients. Reducing aw of a food system has been shown to reduce the rate

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of the hydrolysis. Water activity is a measure of free energy available for chemical and physical changes in food and other systems. For the hydrolysis of sucrose by invertase the rate has been shown to be dependant on temperature, concentration of water, enzyme and aw. When adjusting aw of a food matrix and humectant system of ingredients is not sufficient to manage the effect of water movement in a composite product or loss of water to the environment, it is possible to use a physical barrier.

5.5

Edible moisture barriers

It has been found that the movement of moisture can be significantly reduced in a product such as an ice-cream cone, where water moves from the high aw icecream to the low aw wafer, by applying a coating made up of a beeswax and esters of mono- and diglycerides to the wafer on the inside of the cone. This system combines the excellent moisture barrier properties of beeswax that is brittle in nature with the elastic properties of the esters of mono- and diglycerides to form a flexible layer that will not crack during application or over shelf life. The water uptake of ice-cream-type wafers that have been coated with various coating films in contact with a carrageenan gel containing only water and preservative is shown in Fig. 5.3. It can be seen that simply using beeswax

Fig. 5.3

Permeability of the moisture barrier as indicated by increase in weight of test material.

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Fig. 5.4

Moisture barrier effectiveness shown in terms of absolute value of permeability coefficient of barrier.

or an emulsifier alone does not reduce water pick very much compared to an uncoated wafer. When the emulsifier acetylated mono-diglycerides is added to the beeswax there is a drastic reduction in water uptake. The kinetics of this water uptake is shown in Fig. 5.4, where the permeability coefficient of the films is compared at 5 and 20 ëC. It can be seen that beeswax alone has a very low coefficient and the acetylated mono-digylceride coefficient is very high. The combination of the two materials gives a film with very low coefficient of water permeability. The film is very effective at preventing exchange of moisture between food systems of high aw and low aw, but the film must be continuous, any small holes in the film layer allows rapid moisture transfer between the two aw systems.

5.6

Molecular mobility

Molecular mobility generally is greatly affected by temperature and, at lower temperature within the glassy state with a viscosity of 1012 Pa s mobility is mainly locally limited to vibrations of atoms or bonds and conformational changes in small groups of atoms. These do not directly involve the surrounding atoms or molecules so chemical reactions or physical changes in a food matrix occur at a very slow rate. Molecular mobility above Tg increases dramatically and this increased mobility with temperature is clearly shown in Fig. 5.5. It can

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Fig. 5.5

149

Change in log viscosity with temperature expressed as ratio of melting temperature (Tm) to measured temperature (T).

be seen from the plot of logarithm of viscosity against the observation temperature T and the melting point of the material Tm, there is a change in viscosity of 12 orders of magnitude. As discussed earlier, the most effective plasticiser of the glassy state in food systems is water and in Fig. 5.5 the increase in mobility is shown in terms of increasing aw and water content. The corresponding increase in the rate of physical and chemical reactions is illustrated against a theoretical rate curve that shows how the rate of crystallisation decreases from years to days and hours at very high aw, and also how chemical reactions and physical changes almost cease at very low aw (Fig. 5.6). This is shown for a sucrose model system showing sugar crystallisation from an amorphous system to make a crystalline sugar system.

Fig. 5.6

Reaction rate superimposed on water activity and water content for sucrose crystallising in model food system as it goes through glass transition.

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Another approach to food preservation is to reduce mobility and availability of water in the food matrix by reducing temperature and is particularly applicable to a high moisture food matrix. The food matrix is forced into the glassy state by quickly lowering temperature, a process that has its own unique, and some similar, aspects to what has been considered with food preservation with humectant ingredients and systems.

5.7

Preservation of foods by freezing

During freezing food safety rarely becomes a problem, most defects being related to the quality, taste and appearance of the food that occur immediately during freezing or on storage. In the humectant ingredient discussion in this chapter the preservation of food for safety, nutritional and taste reasons was achieved using ingredients for shelf life stability at ambient temperature. It was a natural next step to control the mobility and activity of water not by the addition of ingredients but by decreasing temperature. Freezing is one of the most effective methods for food preservation, as low temperature not only protects the product from microbiological spoilage but also slows down the rates of other chemical reactions. The same principles that were used to control the movement of water and the physical properties of the food matrix at ambient temperatures also play a large role in the preservation of the quality of foods in the frozen state. Freezing does have many advantages but freezing can cause unfavourable changes to food quality such as the freezing of bread dough. Ingredients or ingredient systems that can be added to food products to delay or prevent the damaging effects of freezing and frozen storage are known as cryoprotectants. Freeze-thaw stability is the ability of a product to maintain its composition and integrity after repeated cycles between freezing and ambient temperature levels. Even minor temperature fluctuations can cause slight thawing of liquids within a product. Those ice crystals freeze at a larger size, causing the breakdown of a product's structure, which is the most damaging effect on a product's texture, followed by flavour and other deteriorative effects. Damaging effects include: · · · · ·

Breakdown in emulsions and disruption of starch and protein structures. Oxidation leading to rancidity and nutrient loss. Loss of moisture during storage spoils appearance of foods. Enzyme activity. Shelf life.

5.7.1 Frozen yeast dough Frozen yeast dough is a good system to illustrate the function of a humectant system for preserving the texture of a food. The frozen dough area has for many years experienced a growth rate more than twice that of the bakery market in general. The reasons for the success are demand for convenience and outlets of freshly baked products in supermarkets and petrol stations and not least the

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catering business has a growing demand for these kinds of product. Although the frozen dough process has several benefits in relation to traditional bread making, a certain reduction in the quality of the final bread has to be accepted. The challenge has been ± and still is ± to produce bread with a quality that is comparable to bread baked by traditional processes. That is accepted by the consumer and today most supermarkets and small bakeries use frozen doughs. The freezing process in a yeast-containing dough system causes the gassing power and gas retention of the dough to decrease. In the baked product this is recognised as reduced oven spring and specific volume compared to products made from dough that has not been frozen. For this reason the frozen dough area has been the subject of many investigations aimed at optimising procedures and improving the quality of the finished baked product. The product attributes that need to be preserved are: · · · · · ·

the strength of the gluten network freeze-thaw and storage stability fermentation conditions for yeast maintain volume of the final product crumb structure the crust texture.

5.7.2 Strengthening the gluten network The gluten network of dough is strengthened by several mechanisms. A humectant system for this application is based on three main components: emulsifier, enzyme and an antioxidant of which the most commonly used is ascorbic acid. In these humectant systems the emulsifier of choice is diacetyl tataric acid esters of monoglycerides, which is known to form a complex with the proteins in the gluten network which creates a stronger texture. Also using enzymes specifically selected for frozen dough systems, such as xylanase, strengthens the gluten network by solubilising water non-extractable arabinoxylan. Since, due to its rigid structure, non-extractable arabinoxylan is known to have a negative effect on the formation of the gluten network, solubilising it will have a positive effect on the strength of the gluten network. The solubilisation of water non-extractable arabinoxylan allows an interaction with the gluten giving colloidal structure with water and thereby stabilising the dough system. 5.7.3 Freeze-thaw stability Pectin is a main component in some commercial freeze-thaw products. The pectin used has been specially selected for its stabilising effect in yeast raised, frozen dough systems. Pectin's ability to reduce ice recrystallisation during frozen storage prevents damage to yeast cell membranes, maintaining a greater number of living cells. If insufficient yeast cells survive, the gassing power of the yeast will be lost. The dough's gas retention properties will also decrease as the cytoplasma contains glutathione that will leak from the yeast cell into the

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dough having a negative impact on the gluten network. The bread volume and crumb structure are significantly improved with the addition of pectin which is also seen to improve the shape and dimensions of the final product. 5.7.4 Storage stability Pectin is largely used in frozen dough to reduce ice recrystallisation known as Ostwald ripening ± where many small crystals will attain a lower energy state if transformed into large crystals. This is a major problem during transportation and storage at the final destination when the products may not be maintained at a constant low temperature. Another very important effect of the pectin is to bind water during frozen storage and at the same time secure enough water for gluten hydration and gluten network development. 5.7.5 Fermentation conditions for yeast Small quantities of a mixture of enzymes such as pullulanase,  and amylase and glucoamylase can be added to the dough to provide a source of sugars for the yeast to ferment once the dough has thawed and is at optimum temperature to raise the dough. 5.7.6 Crumb structure and volume As emulsifiers, enzymes and pectins all have a positive effect on volume and crumb structure, bread quality can be significantly improved. One single ingredient does not have the functionality to give a bread the required protection on freezing. This humectant ingredient system provides good protection but when a storage period over 3 months is required, a stronger flour than usual should be used. When adjusting a recipe to a frozen dough recipe, the optimal protein content is 12±14%, depending on the quality of the gluten in the flour. If weaker flour is used the performance can be improved by adding extra gluten to the recipe. When adapting a recipe to frozen dough procedures, the water content should generally be decreased in order to minimise recrystallisation. Standard frozen dough has a water content adjusted to a relative viscosity of 500±700 BU. In frozen dough procedures, where fermentation takes place after freezing, yeast levels should increase with the frozen storage time. For three months in frozen storage up to 50% extra yeast is recommended, and when frozen storage exceeds three months 100% extra yeast is required. The yeast level should not be increased in procedures where fermentation takes place before frozen storage. More ascorbic acid should be applied in frozen dough recipes as well, as oxidation can degrade the gluten network during storage. To prevent this, extra ascorbic acid up to 100 ppm above the normal flour optimisation level is necessary. 5.7.7 Surimi Today virtually all frozen foods are free from cryoprotectants except for frozen chicken or turkey where phosphates are used to add water and these also have

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cryoprotectant properties. The modern trend is to have food free from these types of ingredients as freezing technology has advanced greatly in recent years. Surimi, which in Japanese means `ground meat' or `fish pureÂe or slurry', is a food product intended to mimic the texture and colour of the meat of lobster, crab and other shellfish. It is typically made from white-fleshed fish that has been pulverised to a paste and attains a rubbery texture when cooked. The term is also commonly applied to food products made from lean meat prepared in a similar process. In surimi and in products including salmon mince, there are still some examples of cryoprotectants being used to help prevent the denaturation of the functional fish proteins. Cryoprotectants must be added to salmon mince prior to freezing if the proteins are to maintain their functionality after storage. Traditionally 4% sucrose and 4% sorbitol have been used as cryoprotectants in fish mince; however, these products give the mince a sweet taste, something which is totally unsuitable for a salmon product, for example. Years of research by the Norwegian Institute of Fisheries and Aquaculture have shown that polydextrose, lactose or combinations of these products could be relevant in salmon mince applications, as no/less sweet alternatives to sucrose and sorbitol. Unfortunately, the cryoprotectant effect of polydextrose and lactose is weaker than that of sucrose and sorbitol but the products may still be acceptable because of the lack of a sweet taste. The Norwegian Food Inspectorate allows the use of polydextrose at concentrations of up to 80 g/kg in undiluted fish mince. 5.7.8 Cryoprotectants The physical factors that lead to conditions that bring about the deteriorative changes in foods can be explained when considering what happens during the freezing process. In feeezing the major goal is the preservation of the food by preventing the growth of bacteria that grow below ÿ10 ëC. Cryoprotectant ingredients are selected to prevent the major cause of deterioration in food quality in terms of texture and taste in freezing that is caused by the damaging effect of ice crystals forming in the food matrix. Ice occupies a greater volume than water and the exclusion of solutes from ice crystals causes an increase in the ionic strength in the unfrozen water. Together these phenomena cause a loss in cell structure for meat or vegetable products or breakdown of the structure of the food matrix, especially in emulsions and protein systems. All food processes are both a function of process and ingredients and this is particularly true of freezing. In this chapter the focus is on ingredients added to food systems to improve quality during freezing and safety over shelf life. Conveniently we can illustrate this by considering a system using a very commonly used cryoprotectant, sugar (sucrose) that has been used for many years in ice-cream and frozen desserts, where control of the amount and size of ice crystals is the most important quality attribute.

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5.7.9 Sucrose In describing the behaviour of a humectant ingredient, molecular mass was shown to influence aw and Tg. Generally, these properties are grouped together under one heading called colligative properties. In the case of the preservation of foods by freezing we will still use Tg, but aw is replaced by the term depression of freezing point and in the same way defined by the Gibb's free energy and Raoult's law. In order to achieve the protective effect of low temperature without the damaging effects of ice crystal formation, our goal is to have the food preserved in a glassy state matrix. Traditionally, before the development of more advanced analytical tools such as DSC, food developers used to use depression of freezing point to model the freezing process, but today Tg and the state diagram are accepted as providing a better understanding of this dynamic system. 5.7.10 Formation of the glassy state During the freezing of foods, ice is formed as pure water through the processes of nucleation and propagation. As temperature decreases and water is removed from a food in the form of pure ice, the solutes present in the remaining unfrozen water are concentrated. An equilibrium point for the freezing temperature exists for each ice and liquid water phase ratio that is a function of the solute concentration. This behaviour can be shown in a state (phase) diagram (Fig. 5.7) as a curve that starts from the melting temperature of pure ice 0 ëC (Tm) to the saturation temperature of the sucrose at this temperature, also known as TE. As temperature is lowered, it is highly unlikely that solute will crystallise at TE, due to high viscosity from concentration of solute and low temperature, so that freeze-concentration proceeds beyond TE in a non-equilibrium state. The highly concentrated unfrozen water phase can then go through a viscous liquid/glass state transition driven by the reduction in molecular motion and diffusion kinetics as a result of both the very high concentration and low temperature. In Fig. 5.7, the glass transition curve extends from the glass transition temperature (Tg) of pure water (ÿ134 ëC) to the Tg of pure solute (52 ëC). Below and to the right of the glass transition line, the solution is in the amorphous glass state and may include ice. Depending on temperature to the left of the glass transition line, this solution is in the liquid state and may also include ice. Ideally a system would be in the glassy state at the temperature used for storage with some allowance made for changes in temperature due to transport and domestic freezers.

5.8

Sweetener ingredients as humectants or cryoprotectants

Ingredients that are used as humectants such as sugar, trehalose, fructose and dextrose are simply classed by regulatory authorities as food ingredients and no restrictions other than those relating to basic food law and good manufacturing practice are placed on their use. Ingredients such as sorbitol that is commonly

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Fig. 5.7 The sucrose state diagram, describing the composition of a pure sucrose and water system during equilibrium and non-equilibrium freezing.

used as a humectant ingredient is classed as a sugar alcohol or polyol and is subject to the following legislation. Sweeteners are approved in the EU via the following pieces of legislation. 5.8.1 Directive 94/35/EC (Sweeteners Directive) Permitted for use as sweeteners in energy reduced, no added sugar or sugar free food products. This would limit the use of these materials but, for their use as functional ingredients, they are permitted under the following Directive. 5.8.2 Directive 95/2/EC (Miscellaneous Additives Directive) As an additive for purposes other than sweetening, the use of sugar alcohols, including sorbitol, is permitted in all food categories with the exception of drinks, baby food and certain specified foodstuffs, e.g. honey, butter, etc. The technical and functional purposes for which sweeteners are permitted are as a humectant, preservative, antioxidant, bulking agent, emulsifier and flavour enhancer. Within the EU and Switzerland (and some other countries outside the EU), foods containing more than 10% sugar alcohols (irrespective of polyol type) must carry the following warning on the package: `Excessive consumption

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can cause laxative effects'. To avoid this requirement, not more than 10% sweeteners should be used to achieve the functionality that is required. Other ingredients such as polydextrose and emulsifiers are also subject to restrictions and Directive 95/2/EC for food additives other than colours and sweeteners applies to emulsifiers and polydextrose which is classed as a bulking agent. To illustrate the principles we have discussed about humectant ingredients and systems we can take a look at commonplace ingredients that are used in food matrices. We will start with a brief description of sorbitol, xylitol, maltitol and polydextrose along with other commonly used sugars and polyols and will compare physical properties and function as humectant ingredients. The key properties of sugars and polyols for humectant and cyroprotection applications are summarised in the appendix to the chapter. 5.8.3 Sweetener ingredients as humectants It has been possible to define a humectant or humectant system as having six main properties that we can use to gauge the effectiveness of an ingredient or ingredient system. · Movement of moisture controlled by the aw of the humectant ingredient/s and its environment. · The effect of the humectant ingredient on the food matrix it is combined with is controlled by the Tg of the humectant ingredient/s and the resulting average Tg of the food matrix. · Controlling crystallisation is a function of an ingredient making a more complex ingredient solution that reduces crystallisation and also steric effects of a humectant ingredient that can prevent a molecule forming a crystal nuclei, such as the monoglyceride and starch interaction. · Solubility is another key factor for the humectant ingredient/s and so they must have a high solubility in water or the food matrix. · Chemical reactivity is very important and the humectant ingredient must be inert so that it will not be degraded by processing temperatures or oxidised during storage or react with other ingredients in the food matrix. · The humectant ingredient/s must have a very neutral taste including factors such as sweetness or other off-flavours at the effective usage level. Using these factors as a reference we can illustrate the effectiveness of a number of sweetener ingredients as humectants. 5.8.4 Sorbitol Sorbitol is commercially the largest produced polyol with an approximate volume of 800 000 MT and, because of this and the low cost of the starting materials, is also the least expensive. A survey of products shows that sorbitol is used in toothpastes, shampoo, soap as a humtectant and softening ingredient. In food it is mostly used in sweet food categories such as cakes, pastries, con-

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fectionery, chewing gum and snack bars. Sorbitol, a polyol that occurs naturally as the sweet constituent of many berries and fruits, such as Sorbus aucuparia (Rowan or European Rowan), is industrially manufactured from starch by enzymatic hydrolysis of starch to dextrose and catalytic hydrogenation of dextrose to sorbitol. Sorbitol has four crystal structures, four anhydrous crystalline phases plus a hydrate form. It is crystallised from an aqueous solution or spray crystallised. The gamma polymorph is the most stable of the anhydrous crystalline forms confirmed by its high melting point and low hygroscopicity and is the only form of significance for the confectionery and pharmaceutical industries. When sorbitol is compared to other commonly used polyols, such as xylitol as shown in Fig. 5.8, sorbitol is seen to be the most hygroscopic. Another commercially available type of sorbitol is a non-crystallising syrup that contains 50±70% of sorbitol together with the hydrogenated forms of higher sugars. Sorbitol does not promote tooth decay because it is resistant to metabolism by oral bacteria which break down sugars and starches to release acids that may lead to dental caries. Typical usage levels are around 5% w/w and because of its low molecular weight are able to significantly reduce aw and Tg. Possibly its most important property is its softening effect on starch, sugar and protein matrices in food products because of its low Tg that helps preserve the eating qualities of products such as cakes and cereal bars even when moisture has been lost over shelf life. It is highly soluble and will also reduce the crystallisation of sugars in confectionery and bakery products. It does not have reducing properties and is not chemically reactive with other ingredients in the food matrix. Like most polyols it is very stable to heat, acid and alkaline environments. It has a neutral taste and at the typical 5% usage level has no effect on the taste of the food. These factors when added together account for sorbitol being the most widely used humectant ingredient. 5.8.5 Xylitol Xylitol is commercially one of the largest produced polyols with an approximate volume of 200 000 MT. It is more expensive than sorbitol because it is derived from hard wood sources and is highly refined. Xylitol is used mostly in toothpaste and chewing gum because of its proven non-cariogenic nature and because it does not contribute to carie formation and is cariostatic because it prevents or reduces the incidence of new caries. Xylitol actually reduces the amount of plaque and the number of mutans streptococci in plaque. No other polyol has been shown to function in this way. It is also used as a tabletop sweetener as an alternative to sugar and it was this that led the way for developing the commercial process. Xylitol was first derived from birch trees in Finland in the 1970s but today xylitol is produced commercially by hydrogenation of xylose derived mostly from hard wood sources. Xylitol occurs in fruits and vegetable such as strawberries, raspberries and cauliflower as well as the human body in the mitochondria in the production of energy. It is not generally recognised as a humectant ingredient but in terms of its physical properties it

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Fig. 5.8 Increase in weight of test material versus relative humidity.

will have greater functionality compared to sorbitol. Xylitol has a lower molecular weight than sorbitol and will lower aw more effectively in terms of softening starch, sugar and protein matrices. It is highly effective with a Tg 20 ëC lower than sorbitol. It has a high solubility and chemically, like sorbitol, xylitol is very unreactive and has no reducing ability and so will not react with other ingredients in the food matrix. It is very stable to heat, acid as well as alkaline conditions and will reduce crystallisation of sugars in food matrices. In addition to these factors, xylitol has also shown some effect against food spoilage organisms. Xylitol has virtually no aftertaste and has the same sweetness as sugar and the required usage level has no impact on the taste of the food. In terms of hygroscopicity of the pure ingredient, it is shown in Fig. 5.8 that xylitol is much less hygroscopic than sorbitol. Xylitol technically has greater potential than sorbitol as a humectant ingredient or part of a humectant system because of its much lower Tg compared to sorbitol (Fig. 5.10), making it more effective at softening protein and starch matrices. 5.8.6 Maltitol Maltitol is commercially also one of the largest produced polyols with an approximate volume of 160 000 MT including hydrogenated starch hydrolysates. It is more expensive than sorbitol because it is more difficult to refine to make

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pure maltitol. A survey of products shows that maltitol is used in food mostly in the sweet food categories such cakes, pastries, sugar confectionery, chocolate, chewing gum and snack bars as well as a tabletop sweetener, as it has a similar sweetness to sugar (sucrose). Maltitol is made through the hydrogenation of maltose, which is obtained from enzyme conversion of starch to maltose. Maltitol is non-cariogenic and resistant to metabolism by oral bacteria which break down sugars and starches to release acids that may lead to cavities or erode tooth enamel. It is not so widely regarded as a humectant but will have almost identical properties to sugar as its molecular mass and Tg properties are similar. This means lowering of aw and softening of starch, sugars and protein matrices will be similar to sucrose. The potential advantage of maltitol in a food system is that it is chemically very inert and will not brown on heating. It has a neutral taste with a high sweetness level but it will be used in sweet products as a partial replacement for sugar and so will not have a detectable taste. In terms of hygroscopicity of the maltitol, it is shown in Fig. 5.8 that it is more hygroscopic than sucrose. Maltitol would seem to be limited in its scope as a humectant ingredient but there may be opportunities based on its very low chemical reactivity. 5.8.7 Polydextrose Polydextrose is commercially one of the largest types of soluble fibres with an approximate volume of 80 000 MT. It is more expensive than sorbitol because, although derived from starch, the manufacturing process is more difficult because of the refining stages needed to make an excellent product. Polydextrose is used in all types of food products such as cakes, pastries, sweet desserts, ice-cream, sugar confectionery and chocolate as well as meat products. Mostly it is used as a low calorie bulking agent with just 1 kcal per gram but is also a soluble fibre and sustained prebiotic and it has been shown that as little as 4 grams per day of polydextrose has a measurable prebiotic effect. Fermentation in the large intestine yields short-chain fatty acids (including butyrate) and the growth of intestinal Lactobacillus and Bifidus is enhanced, giving improved gastrointestinal function with no adverse effects. Polydextrose is a polysaccharide composed of randomly cross-linked glucose units with all types of glycosidic bonding (1±6 bonds predominate) containing minor amounts of sorbitol and citric acid. It has a molecular mass range of 182±5000 D with an average of 2160 D. Polydextrose is a high molecular weight molecule so is not as effective at reducing aw compared to sorbitol or xylitol. Its benefits have been found mostly in reduced sugar and calorie food where it replaces sugars with typical usage levels above 5%. There is also commercially available a hydrogenated form of polydextrose that has no reducing properties and is resistant to acid and alkaline conditions. Essentially refined polydextrose is nonsweet and has a neutral taste (but some types can be bitter and acidic in nature so care should be taken in the quality that is selected) and at effective usage levels has no effect on the taste of the food. Figure 5.9 shows the water activity of

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Fig. 5.9

Water activity of sucrose and polydextrose solutions.

polydextrose relative to sucrose. At low concentrations (below 60%), sucrose lowers aw slightly more than polydextrose. At higher concentrations polydextrose is more effective at reducing aw as it is highly soluble in water. This is because sucrose crystallises at high concentrations and these crystals do not interact with the water to lower aw. Polydextrose can function as a humectant in foods to slow down undesirable changes in moisture content as shown in the moisture sorption and desorption isotherm in Fig. 5.1. As discussed earlier in the chapter, it retains moisture because of its Tg properties that preserve texture even when moisture has been absorbed. A comparison of polydextrose and other carbohydrates can be seen in Fig. 5.10. Polydextrose helps to retain moisture, texture and shelf life in a range of product applications, from confectionery and baked goods to reformed meat products. Polydextrose technically has greater potential than sorbitol as a humectant ingredient or as part of a humectant system, but is required at quantities over 5% w/w.

Fig. 5.10 Glass transition temperatures of some common food carbohydrates.

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Ingredients for shelf life extension

5.9.1 Antimicrobials Nisin Nisin (Fig. 5.11), a bacteriocin of the lantibiotics group A, is a natural, toxicologically safe antibacterial food preservative. It is the only commercially accepted bacteriocin for food preservation, although most lactic acid bacteria will similarly produce bacteriocins and are accepted and used in commercial starter cultures. Nisin's mode of action is to target and disrupt the cytoplasmic membrane of sensitive Gram-positive bacteria. This disruption manifests itself as ion channels or formation of pores, which facilitate effusion of low molecular weight material through the membrane dissipating the membrane potential and the pH gradient, and thus inhibiting the cell's function. Gram-negative cells are protected against nisin by a cell wall outside the cell membrane, but any weakening of the cell wall causes these cells to be susceptible to nisin. As regards spore contamination, nisin affects the post-germination of spores, i.e. inhibiting the growth and formation of vegetative cells. This sporostatic, as opposed to sporicidal effect, is maintained throughout the shelf life of the product. Nisin is a key element in multi-preservation systems, i.e. a system containing more than one antibacterial/antimicrobial agent, used where conditions are not optimal for one agent alone, and in such systems its bacteriostatic effects are often enhanced. Applications for nisin are diverse and include: natural and processed cheese, pasteurised dairy products, pasteurised liquid egg, high moisture bakery products, canned foods, meat and fish products, yoghurt, salad dressings and alcoholic beverages. In natural cheese, nisin is especially effective in preventing the phenomenon known as blowing, where contamination takes place from anaerobic sporeforming Clostridium butyricum/tyrobutyricum, which converts lactic acid to butyric acid, causing an off-flavour. This process also releases hydrogen and carbon dioxide which can lead to the development of large holes in the cheese. Growth of Listeria monocytogenes, prevalent in ricotta cheese, can be successfully hindered by use of nisin, and as such the shelf life of the product can be extended from 1±2 weeks to 8 weeks. For processed cheese nisin is the established favourite as the most effective preservative, where typically the heat treatment step of pasteurisation does not eliminate all the spores. Lack of nisin application would result in outgrowth of these spores and production of gas and off-flavours and possible liquefaction of the solid cheeses. The dosages required to protect these cheeses from non-botulinal bacteria is typically low: around 6.25±12.5 mg kgÿ1, while for botulinal protection, higher doses of 12.5 mg kgÿ1 are required. Pasteurisation of dairy desserts, e.g. chocolate mousse type products, can adversely affect the sensory and mouthfeel properties, but use of nisin will protect effectively and extend their shelf life. For these typical chocolate mousse type products, the shelf life extension was seen to be in the order of 20 days when nisin was added at the dosage of 3.75 mg kgÿ1 at a temperature of 7 ëC.

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ß Woodhead Publishing Limited, 2011 Fig. 5.11 Schematic structure of nisin, where Aba: amniobutyric acid; Dha: dehydroalanine; Dhb: dehydrobutyrin (bmethylhydroalanine); Ala-S-Ala: lanthionine; Aba-S-Ala: b-methyllanthionine.

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Addition of nisin can also be used in milk to double the shelf life where climatic issues such as temperature play a role, although it is advisable to check local legislation, as not all countries allow nisin addition to milk. Nisin successfully protects pasteurised liquid egg from the psychrotrophic bacteria which survive the pasteurisation process; and extends shelf life by up to 17±20 days. Despite their short shelf life, high moisture bakery products (e.g. crumpets) can contain Bacillus spores from the flour well within the accepted shelf life period of 3±5 days, but application of nisin at dosage concentrations of at least 3.75 mg kgÿ1 will successfully inhibit any outgrowth, and thus keep the crumpets safe. In canned food products, nisin's use is to control thermophilic spoilage from the surviving spores after heat treatment from Bacillus stearothermophilus and Clostridium thermosaccharolyticum, particularly prevalent at high pH. At low pH other species are present, which although non-pathogenic can still spoil the food quality. All these can successfully be dealt with by addition of nisin at dosages of between 2.5 and 5.0 mg kgÿ1. For meat and fish, nisin is regarded as an alternative to nitrite, but it has been found that it only really works at high dosages (above 12.5 mg kgÿ1), perhaps due to its poor solubility in meat systems or interference of nisin's modus operandi by the meat phospholipids. Application to fish and shellfish can delay the onset of toxin production from C. botulinum from half a day to five days at 26 ëC. Post-production addition of nisin to stirred yoghurt paradoxically affects the starter culture in an inhibitory manner, which at first seems counterproductive. However, this carefully timed addition results in protecting the yoghurt from potential over-acidification, and as such extends the shelf life by maintaining the desired flavour of the product. Salad dressings with higher pH than normal, i.e. from 3.8 to 4.2, can be more prone to lactic acid bacterial spoilage, especially when stored at ambient temperatures. This can be effectively controlled by nisin addition at 2.5±5.0 mg kgÿ1. Finally, nisin can also have potential use in alcoholic beverages, which can easily control spoilage caused by lactic acid bacteria. Yeasts are completely unaffected by nisin, but their efficacy can be improved by nisin controlling the competitive lactic acid bacteria. Here the result is either increased alcohol content of the beverage by up to 10% or a lower dosage of yeast required to achieve the desired alcohol content. Typical dosage levels for nisin are given for a range of applications in Table 5.4. A range of factors detrimental to nisin's effective action exist and should be considered, and include susceptibility to enzyme degradation, nisin's hydrophobicity, and interaction with other ingredients. If a food material has not been adequately heat treated, some proteolytic enzymes may survive which can degrade the nisin during the shelf life of the product. Experience dictates the level of nisin used, by considering the likely degree of nisin degradation and subsequently allowing for this. Nisin's own hydrophobicity can be a problem for its successful function, especially in meat applications, where nisin is thought to bind to the meat through the phospholipids and thereby making itself unavailable for an antibacterial role. Equally certainly, other food additives

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Table 5.4

Typical addition levels of nisin (and nisaplin) in different examples of foods

Type of food/ application

Nisin (g/g)

Nisaplin (mg/kg) or (mg/L)

Canned food

2.5±5

100±200

Processed cheese

5±15

200±600

Pasteurised chilled dairy desserts Ricotta cheese Dressings and sauces

1.25±3.75

50±150

2.5±5 1.25±5

100±200 50±200

Milk and milk products Liquid egg Beer: pitching yeast wash reduced pasteurisation during fermentation post fermentation Crumpets Fruit juice (pasteurised, stored at ambient)

0.25±1.25

10±50

1.25±5

50±200

25±37.5 0.25±1.25 0.63±2.5 0.25±1.25 3.75±6.25 0.13±0.25

1000±5000 10±50 25±100 10±50 150±250 5±10

Typical target organisms

Bacillus stearothermophilus Cl. thermosaccharolyticum Cl. botulinum Bacillus spp. Clostridium spp. Bacillus spp. Clostridium spp. Listeria monocytogenes LAB Bacillus spp. Clostridium spp. Bacillus spp. e.g. B. sporothermodurans Bacillus spp., e.g. B. cereus LAB, e.g. Lactobacillus, Pediococcus

Bacillus cereus Alicyclobacillus acidoterrestris

degrade nisin, and therefore should either be avoided in combination with nisin, or the nisin dosage should be increased. These include titanium dioxide and sodium metabisulphite, a whitener and antioxidant respectively. In conclusion on nisin, it is an effective antimicrobial, and generally works best in liquid and homogeneous foods, as opposed to solid and heterogeneous ones, likely as a result of easier distribution within the liquid homogeneous foods. At all times local legislation regarding the approval and use of nisin should be checked before proceeding. Guidelines can be found in Table 5.5. Natamycin Since its isolation in 1955, natamycin (Fig. 5.12) has developed into a commercially global food preservative, with specific application to the surface treatment of cheese and processed meat products. It is effective at low concentrations, has a broad activity range and is active over a wide pH range. Natamycin also has an extremely low solubility, thus it remains on the surface of the food and does not migrate into the food bulk. This means that it does not adversely affect the sensory properties of the food it is protecting. Natamycin has no effect on bacteria, and therefore does not negatively affect any starter cultures. The modus operandi of natamycin is to interact with ergosterol or other sterols present in the cell membranes of yeasts and moulds. This irreversible

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A list of products and countries in which nisin is approved for use

Product

Permitted level (g/g food)

Country

Milk, pasteurised, flavoured, long life Condensed milk products Clotted cream

No limit

Abu Dhabi, Bahrain, Dubai

12.5 No limit

Cheese

10 No limit

Slovak Republic Cyprus, Gibraltar, Guyana, Hong Kong, Malta, Mauritius, Trinidad & Tobago EU Abu Dhabi, Australia, Costa Rica, Cyprus, Dubai, Gibraltar, Hong Kong, Malaysia, Malta, Mauritius, Papua New Guinea, Singapore, Trinidad & Tobago Czech Republic Bulgaria Taiwan Chile, EU, Slovak Republic, South Africa, Vietnam India Israel

3 5 6.25 12.5 Cheese, excluding soft white cheese Cheese, soft Cheeses, very high, high, medium, and low moisture content Mascarpone Processed cheese

Processed (pasteurised) cheese spread (and with vegetables, fruit, meat) Cheese preparations (spreadable) Cheese preparations Cheese products

25 No limit 25 12.5 10 Under review No limit 2.5 12.5

India MERCOSURa EU Mexico

25 100 120 200 4000 250

Abu Dhabi, Bahrain Belgium Argentina, Brazil, Codex Alimentarius Commission, Colombia, Czech Republic, Egypt, EU, Kuwait, Montenegro, Macedonia, New Zealand, Saudi Arabia, Serbia, South Africa, Venezuela India Algeria, Thailand, Uruguay Polandb Russia Philippines USA

12.5

Codex Alimentarius Commission

No limit 12.5 No limit

Zimbabwe Indonesia Australia

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Table 5.5

Continued

Product

Permitted level (g/g food)

Dairy products Puddings (semolina, tapioca etc.) Meat products Vegetables: sterlised and pickled Branzeturi paste Nisin as permitted preservative Mayonnaise Hermetically sealed food given botulinum process Part prepared products Canned food given botulinum process Canned foods

Canned tomatoes, paste, pureÂe Canned soups Canned fruit, pH < 4.5 Tomato pureÂe, canned tomato pulp, canned tomato paste, canned tomato juice, pH <4.5 Coconut water Plant protein foods Breads Crumpets, flapjacks Beer Ice for storing fresh fish Vegetables (raw, peeled, semi-preserved, potatoes, cauliflower, green peas) Ready to eat meals Requeijao a

No limit 12.5 3 12.5 200d 12.5 50 Not known

Country

Abu Dhabi, Bahrain, Dubai China EU, Czech Republic China Brazil Slovak Republic

No limit 12.5 No limit

Romania Boliva, Ecuador, Qatar, Sri Lanka, Yugoslavia Peru Slovak Republic Malaysia

12.5 No limit

Slovak Republic Singapore, Trinidad & Tobago

No limit 5 12.5 No limit

Abu Dhabi, Bahrain, Cyprus, Dubai, Gibralter, Guyana, Hong Kong, Malta, Mauritius China Slovak Republic Australia

No limit No limit No limit

Australia Papua New Guinea Papua New Guinea

5000 5 12.5 250 No limit No limit 100

Indiac China Slovak Republic Australia Australia, New Zealand Bulgaria Russia

12.5 12.5

Argentina, Brazil, Paraguay, Uruguay;

b

Slovak Republic Brazil

melted; c proposal for use;

d

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Fig. 5.12 Structure of natamycin.

binding disrupts the membrane and increases the susceptibility of leakage of essential cellular constituents due to increased permeability. Such leakage then results ultimately in cell lysis. The range of yeasts and moulds which natamycin is effective against is broad, and the concentration required to inhibit them extends from < 5 ppm for yeasts to at least 10 ppm for moulds. The sensitivity of various yeasts and moulds to natamycin is given in Table 5.6. There is low resistance to natamycin, and indeed resistance does not seem to occur naturally. This phenomenon is explained by the existence of natamycin in solution as micelles, whereby any yeast or mould which comes into contact with the natamycin micelle is met with locally high and therefore lethal concentrations of natamycin. The effective use of natamycin can be negatively influenced by affecting its stability by conditions such as pH, temperature, light exposure, oxidants and heavy metals. A prominent effect can be seen through careless use of plant cleaning agents, typically peroxides or chlorine. Principally, natamycin is used to surface treat cheese and meat products such as dry sausage, where it remains on the surface due to low solubility. This Table 5.6

Examples of sensitivity of yeasts and molds to natamycin

Strain

Minimal inhibitory concentration (ppm)

Apergillus chevalieri 4928 Saccharomyces cerevisiae H Penecillium chrysogenum Aspergillus niger Saccharomyces bailii Candida albicans Mucor mucedo Penecillium notatum 4620 Saccharomyces rouxii 0562 Rhizopus oryzae 4758

0.1±2.5 0.15 0.6±1.0 1.0±1.8 1.0 1±1.25 1.2±5.0 5.0 5.0 10.0

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property to remain on the surface, with a penetration limit of between 1 and 4 mm can also prove beneficial to the application itself. In a blue cheese where other antimicrobials (e.g. sorbate) can migrate into the cheese and inhibit the desired blue mould development, natamycin remains on the surface and allows full and proper development of the blue mould. Applying natamycin to cheese or sausage is usually achieved by dipping the food for a few seconds into an aqueous solution containing the natamycin at a given concentration, typically 1250 ppm, or even as high as 2500 ppm for blue cheeses. Natamycin should be applied evenly since the binding is both rapid and strong upon contact with the surface. This means there is no real advantage in coating the food twice in terms of making the coating better. Mixing the natamycin with a thickener and salt then allows the foodstuff to be repeatedly dipped, which results in a multiple layer being built up on the surface. As with nisin, the local legislation of what is allowed and at what dosage should always be consulted before use. Guidelines can be found in Table 5.7. Protective cultures Protective cultures essentially consist of bacteria that have been specifically selected for their ability to inhibit the growth of pathogenic organisms or microbiological spoilage agents, and have GRAS (generally regarded as safe) status. Thus, these bacterial species are fully natural and therefore provide a useful `green' benefit to the labelling of food products, a demand that is on the increase. The protective cultures have in themselves antimicrobial effects through production of specific metabolites such as organic acids (lactic, acetic and propionic), and engage in competitive exclusion where they outcompete the spoilage agent for nutrients and oxygen, and furthermore can take part in the phenomenon known as quorum sensing ± where they `feel' their environment and adjust their performance to deal with these new challenges. A number of factors will influence the activity of the protective culture, and vary according to: the initial level of the contamination; the nature of the contaminant species; the fermentation time; storage conditions, i.e. temperature, of the final product. It should be pointed out that if the initial contamination level is high, then the use of a protective culture cannot make a bad food good again. Rather, the protective culture has the ability to delay the onset of further contamination, thus extending the shelf life of the product through protection as opposed to open attack on already high concentrations of microbial contaminants. Protective cultures based on selected bacteria from Propionibacterium freudenreichii subsp shermanii and Lactobacillus rhamnosus, and Propionibacterium freudenreichii subsp shermanii and Lactobacillus paracasei, have been shown to successfully extend the shelf life of yoghurts against yeasts and moulds by up to 14 and 28 days (Fig. 5.13). These protective cultures offer other benefits, including: control of growth of yeasts and moulds; control of growth of heterofermentative lactic bacteria; can be labelled as a starter culture as opposed to an additive; and possess minimal influence over the food product's sensory properties.

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Food legislation on the use of natamycin

Country

Food in which natamycin is permitted

Maximum permitted level

Algeria

Cheese rinds

Argentina

Surface treatment of hard and semi-hard paste cheeses Surface treatment of cheese rind Uncooked fermented manufactured meat products Permitted food preservative Surface treatment of cheese Cheese rind Surface treatment of 47 listed cheeses Grated/shredded cheese (0.5% sodium lauryl sulphate prohibited as dispersant) Surface treatment of hard cheese (prohibited in wine) Surface treatment of cheese, processed meat products, moon cakes, baked goods, fruit juices, and processing utensils for easily moldy foods Cheese Surface treatment of specified cheeses Dairy and meat products as EU regulations (contact authorities for further information)

Used in suspension at 2.5 g lÿ1 Limit of 1 mg dmÿ2. Penetration limit of 2 mm. Limit of 15 mg kgÿ1 Penetration to 3±5 mm

Australia Bahrain Brazil Bulgaria Canada

Chile China

Colombia Cyprus Czech Republic

Egypt EU Hungary Iceland India

Surface treatment of cooked cheese (dehydrated, semi dehydrated, and semi soft cheese) Surface treatment of specified cheese and sausage Surface treatment of hard and semi hard cheese, dried, cured sausage Surface treatment of ripened and whey cheese Surface treatment of hard cheese

Limit of 2 mg dmÿ2 500 mg kgÿ1 20 mg kgÿ1 based on total weight 10 mg kgÿ1

Application by spraying or dipping in 200±300 mg kgÿ1, to leave a residue of < 10 mg kgÿ1 12.5 mg kgÿ1

Limit of 1 mg dmÿ2. Penetration limit of 5 mm Limit of 2 mg 100 cmÿ2 (1 mg dmÿ2) Limit of 1 mg dmÿ2 Penetration limit of 5 mm Limit of 1 mg dmÿ2 Limit of 2 mg dmÿ2 Maximum application level: 2 mg dmÿ2. Maximum residual level in finished cheese: 1 mg dmÿ2. Penetration limit of 2 mm

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Table 5.7

Continued

Country

Food in which natamycin is permitted

Israel

Surface treatment of specified cheese Permitted food additive Surface treatment of hard, semi hard, and semi soft cheeses Surface treatment of hard, semi hard, semi soft cheese and dried cured sausage Surface treatment of cheese

Kuwait Lithuania Mauritius Mercosur

Mexico Norway

Cheese surfaces Surface treatment of hard, firm, and semi firm cheese, dried, cured sausage

Oman

Surface treatment of specified cheese Surface treatment of specified cheese Permitted in coloured and uncoloured soft wax and polyvinyl acetate for application to skin of hard cheese Surface treatment of smoked dried sausage Permitted as a mold inhibitor in foodstuffs but controlled by standards of composition Surface treatment of cheeses and dried cured sausage Wine, alcoholic beverages, and grape-based liquors Fresh fruit pulp Fresh fruit (blackcurrant, pineapple, etc.) Fish sausages (to be applied to the outer inedible casing only) Manufactured fish products, fish pastes, fish roe and spawn with the exception of frozen fish, salted snoek, and canned fish products Lobsters (quick frozen)

Philippines Poland

Saudi Arabia Slovakia South Africa

Maximum permitted level

Limit of 1 mg dmÿ2. Penetration limit of 5 mm Limit of 1 mg dmÿ2. Penetration limit of 5 mm Limit of 1 mg dmÿ1. Maximum application of 5 mg kgÿ1. Penetration limit of 2 mm. Limit of 0.002% Maximum level of suspension: 2 g kgÿ1 Limit of 1 mg dmÿ2. Penetration limit of 5 mm.

No limits

Limit of 1 mg dmÿ2

Limit of 1 mg dmÿ2 30 mg lÿ1 5 mg kgÿ1 5 mg kgÿ1 6 mg kgÿ1 6 mg kgÿ1

6 mg kgÿ1

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Continued

Country

Food in which natamycin is permitted

Maximum permitted level

South Africa (continued)

Edam, Gouda, Tilster, Limburger, Cheddar, Cheshire

2 mg kgÿ1 in rind without plastic coating 500 mg kgÿ1 in a plastic coating 10 mg kgÿ1 for application to the surface of the cheese only Limit of 10 mg kgÿ1 10 mg kgÿ1 for application to the surface of the cheese only 10 mg kg ÿ1 6 mg kgÿ1 Limit of 500 mg kgÿ1 on casing or 6 mg kgÿ1 in contents Limit of 6 mg kgÿ1

Cottage cheese, cream cheese Process of blended cheese, including cheese spread, process cheese preparations and soft cheese Yoghurt Canned foods Manufactured meat products

Tunisia Turkey

Ukraine United Arab Emirates USA

Venezuela

Canned chopped meat, canned corned beef, cooked cured luncheon meat, cooked cured pork shoulder, Biltong, frozen cookedmeat pie fillings Surface treatment of hard, semi hard, and semi soft cheese, dried, cured sausage Surface treatment of hard, semi hard, and semi soft cheese, dried, cured sausages, salami and hot dogs Surface treatment of cheese

Limit of 1 mg dmÿ2 Limit of 1 mg dmÿ2. Penetration limit of 5 mm Limit of 1 mg dmÿ2. Penetration limit of 5 mm

Permitted food additive Surface treatment of cuts and slices of cheese Nonstandard of identity yoghurt Nonstandard of identity cream cheese Cottage cheese Sour cream Soft tortillas Nonstandard of identity salad dressing Surface treatment of specified cheeses and sausages

Limit of 20 mg kgÿ1 Limit of 7 mg kgÿ1 Limit of 7 mg kgÿ1 Limit Limit Limit Limit

of of of of

7 mg kgÿ1 7 mg kgÿ1 20 mg kgÿ1 20 mg kgÿ1

Maximum 0.5% suspension

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Fig. 5.13 Activity of challenge test mould pool against a reference control, and HOLDBACTMYM-B and HOLDBACTMYM-C protective cultures.

Similar protection can also be offered by these protective cultures against Listeria as a further barrier in the hurdle technique of protection. A specific protective culture against Listeria made from Lactobacillus plantarum is effective in preventing Listeria from forming on the high-risk red smear surfaceripened cheeses. The culture is applied to the surface of the cheese, but should not be applied in a disinfectant type role to make a bad cheese good. The culture is an effective tool to prevent contamination of fresh samples. In order to protect the cheese adequately against Listeria, a dosage of around 0.6±1.2 IP (inhibiting activity) of the protective culture is required to be added over several steps. Cost cutting regarding the dosage applied can take place, but simply lowers the hurdle the bacteria have to surmount and therefore effectively reduces the food protection ability. The same principles are true for a range of cheeses, which may either be hard or soft in nature. Applications such as meat and fish products are also open to contamination by Listeria, where excellent conditions for survival of Listeria exist ± even at refrigerated temperatures. Heat treatment of hams does indeed kill Listeria, but the ham is then exposed to further contamination risks as additional processing takes place under non-optimal hygiene conditions. Similar to the meats, fish products are open to contamination, and may exhibit a higher risk to the consumer since many fish products are consumed without prior heat treatment, and cold smoking in itself is insufficient to kill the Listeria. Addition of the faster metabolising protective cultures, and of starter cultures if the product is fermented in nature, outcompetes the Listeria for the available nutrients, and can keep the products free of Listeria for up to 15 days for smoked salmon, 28 days for sausages, and 39 days for cooked hams. Fermentates Fermentates are natural metabolites produced from cultured skimmed milk, now taken from dairy cows which have not received the growth hormone, recombinant bovine somatotropin (rBST), and specifically selected dairy starter culture bacteria. This whole mixture is controlled under rigorous conditions

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before the material is pasteurised and spray dried together with maltodextrin as a carrier. The maltodextrin variety has a natural dairy flavour, whereas substituting dextrose for maltodextrin gives the product a savoury flavour. Both of these fermentate products contain natural bacterial metabolites which contribute to protection against pathogenic contamination of processed or acidic foodstuffs. When used in combination with other food protective hurdles, the fermentates bring a number of benefits into play: they protect against bacterial spoilage and enhance shelf life in processed and low pH foods; have clean, natural labelling status; increase product safety, i.e. they can control pathogens such as Listeria monocytogenes; maintain food's sensory properties; protect against temperature gradients during storage and distribution; provide opportunity to reduce processing temperature (subject to HACCP requirements); enable development of higher pH/reduced acidity products; enable development of higher water activity (aw) formulations with reduced salt or sugar levels; and add desirable flavour notes to many types of food. Fermentates can be used as part of the hurdle mechanism and thereby be applied to a range of food products, which include processed meats, ready-to-eat meals, dairy products, pasteurised products (soups, dips, tofu, soya drinks, liquid egg), and low pH dressings and sauces. The shelf life extension of cottage cheeses with fermentates can be up to 50% more than cheeses without. The dosage level of fermentates varies from 0.2 to 1.0% depending on the nature of the food product, processing conditions and the microbial load already in the food. The fermentates work against Gram-positive bacteria, as opposed to Gramnegative types. Gram-positive types should be the only microorganisms to survive in properly pasteurised food, as some species of Bacillus or Clostridium produce heat-resistant spores that can survive the heat treatment, and some of these bacteria are able to grow at refrigerator temperatures. The fermentates do not destroy these spores, but they prevent their growth in the foodstuff and therefore stop them from developing. Fermentates at the dosage of 0.5% have also shown efficacy against Listeria monocytogenes, where a meat sauce has seen its shelf life extend by a factor of four compared to the control. This adds another powerful weapon in the fight against Listeria monocytogenes in, especially, meat products. 5.9.2 Antioxidants Antioxidants, by dint of their early rapid ability to quench oxygen, delay the onset of oxidative food spoilage. This can be particularly the case with fat-based systems, especially if the fat contains large percentages of unsaturated fats. Oxidation causes these fats to become rancid, i.e. they smell and taste awful, although the food itself is not necessarily dangerous. The process of the oxidative cycle and the role of the antioxidant are represented schematically in Figs 5.14 and 5.15.

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Fig. 5.14 Schematic of the oxidative cycle.

Fig. 5.15 Schematic representation of the mode of action of antioxidant function against lipid radicals.

Butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT) and tertButylhydroquinone (TBHQ) Butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), and tertButylhydroquinone (TBHQ) (Fig. 5.16) represent the three classic chemicalbased antioxidants that have been the effective stalwarts of the industry for many years. BHA is an isomeric mixture, which has waxy solid-like characteristics and is classified as E320. BHA's mode of action is to sequester the free radicals by being able to stabilise them within its conjugated ring, effectively scavenging the free radicals from the system. Despite controversy with BHA's use in foods, no significant increase in cancer has been associated with the product, and similarly only a fraction of the population exceeds the accepted daily intake values. BHA is insoluble in water, but completely soluble in alcohol, oils and fats. BHT, with classification E321, has many antioxidative uses but is used mainly within foods. It converts peroxy radicals to hydroperoxides, thereby suppressing the autooxidative processes by functioning as a synthetic vitamin C

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Fig. 5.16

175

Chemical structures of BHT, BHA, and TBHQ.

analogue. BHT has been largely voluntarily phased out of food products, due to controversy over links with hyperactivity in children and doubts as to its potential to increase the risk of cancer, in favour of BHA. TBHQ, E319, is a highly effective antioxidant for unsaturated oils and animal fats, where it does not adversely affect the taste or discolour the food. Within its wide range of food applications, it is primarily used to enhance shelf life, and has an upper limit of use in fish of 1000 mg/kg. Tocopherol and ascorbyl palmitate These are sometimes referred to as vitamin-based antioxidants because of their source. Similarly, their vitamin base gives them essentially a restriction-free status in their use in many foods, where they are generally permitted at GRAS level or quantum satis. All tocopherols can also be termed vitamin E and are natural antioxidative substances, which can prevent oxidation of oils and other lipid based systems, where -tocopherol (E307) has the highest bioavailability. Cereals and cereal products provide rich sources of tocopherols, whereas in meat, sources are limited to trace quantities. The antioxidant activity of tocopherols is based on radical scavenging, where they quench lipid radicals, thereby halting the oxidation process. Unlike the antioxidants above, tocopherol with its vitamin E status has recommendations of daily intake, which currently lie at 25 mg/day for the average healthy 25-year-old male. Upper limits of 1000 mg/day have been set due to its anticoagulant properties. Tocopherol is commercially available in extract form, derived from soya oil, and is used specifically to extend the shelf life of oils and fats, and infant food. For applications that require non-GM certification, it is also available as an identity preserved status. Ascorbyl palmitate (E304) is an ester formed from the reaction between ascorbic acid and palmitic acid, creating a lipid soluble version of vitamin C. It is used throughout the food industry as an antioxidant where it performs as an excellent oxygen scavenger. Increasing the blood plasma concentration of ascorbate can lower the oxidative stress, and lead to potential health benefits. Rosemary and green tea extracts Natural extracts are the new trend in antioxidant materials because they are seen by consumers as being natural. This provides the manufacturer with the

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additional benefit of `clean labelling', and they are gradually taking over from the previously traditional chemical antioxidants such as BHA, BHT and TBHQ. Rosemary extract, which is rich in phenolic diterpenes such as carnosic acid, carnosol and 12-0 methylcarnosic acid, is widely recognised for its ability to not only delay lipid oxidation but also maintain sensory and nutritional qualities of numerous applications, including meat (raw and fermented), long-life bakery, dressings, soups, sauces, margarines and spreads, and ready meals. Among the benefits are its low flavour intensity; its ability to retard onset of rancidity and off-flavour; retard loss of colour and flavour; and extend shelf life. For meat applications effective reduction of oxidation can be achieved with dosages as low as 100±200 ppm, and thus play a significant role in hindering the development of warmed-over flavours, discoloration and protein degradation. In bakery applications, lipid oxidation is a main problem, with many of the shortenings being based on unsaturated fatty acids where C18:2 and C18:3 fatty acids contribute to less overall oxidative stability. Rosemary extract together with the vitamin-based antioxidants are gradually replacing the more traditional BHA, BHT, TBHQ solutions, and can result in shelf life extension of 130% when used in combination. Rosemary extract similarly has the ability to protect all types of animal-based oils; including omega-3 long chain polyunsaturated fatty acids, and can be used effectively at doses of 200±500 ppm in dressings and mayonnaise which is equivalent to 8±20 ppm diterpenes based on the oil phase. Green tea extract contains a potent mix of catechins: epicatechin (EC), epigallocatechin (EGC), epicatechin gallate (ECG), and epigallocatechin gallate (EGCG), which together give green tea extract an antioxidative potential 20 times stronger than vitamin-based antioxidants. The strongest antioxidative component is EGCG. Green tea extract is already popular in beverages and as a food supplement, whereas now it is being actively used as an antioxidant in its own right to extend shelf life, protect flavour and offer potential health benefits. Like the other phenolic antioxidants, green tea extract prevents fat rancidity by donating a hydrogen atom to the lipid free radicals, breaking the chain reactions and preserving the lipid. As long as there are green tea molecules present, lipid protection can be offered. Green tea extract can effectively retard the warmed-over flavour (WOF), typically described as a cardboard-like flavour and preserve colour stability within meat and poultry applications at dosages between 50 and 250 ppm.

5.10

Future trends

With the global population projected to reach 9 billion by 2050, one of the key issues facing the food industry will be to ensure the cultivation and production of sufficient raw materials to produce foodstuffs that will be able to last longer and provide humanity with safe, high-quality foods. This will demand increased focus on how to extend shelf life of individual products well beyond their current performances, creating the possibility to prevent up to 25% of all food

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material being discarded as waste due to microbiological spoilage. Reducing wastage and spoilage coupled with a concomitant extension of shelf life should lead to improved standards in terms of food production and achievable shelf life. To achieve this, new ingredients are likely to be developed which build on the foundations of the existing available ingredients, but also encompass new technologies in true multidisciplinary cooperation. These will doubtless include the advent of nanotechnology, whereby functional changes are engineered into a food ingredient by changing the particle size to the nano-scale. Obvious areas today are nano-encapsulation, which can be used as flavour enhancers, salt reducers and fat reducers. Other areas of exploitation lie within the biotechnology world, where new uses of microbiological engineering will likely lead to new and hitherto undreamt of advances. Indeed, merging the benefits of biotechnology with nanotechnology is likely to lead to food products being possible that are currently within the realms of science fiction. Technologically this is all possible, but a large question remains unanswered: Will the public embrace this development and accept its benefits? One has to be aware that applying such new technologies results in a highly emotive response from the public, given that they have to eat and consume these new food ingredients. `Is it safe?' is perhaps the most critical question to be answered. The facts must be conveyed in safe, sure, scientifically simple and familiar language such that the layperson feels comfortable, and not only the benefits but also the risks must be clearly outlined. It is envisaged therefore that the future holds in its cusp, the advent of new bio-based, nano-scale ingredients that are likely not only to offer better moisture control, oxidation control, reduction of microbiological spoilage and therefore extend shelf life but may also be in a position to reduce the demand for raw materials and increase sustainability. Due to their nano-scale size, smaller amounts will be required to give the same taste and functionality, and therefore overall less is required. In a world with a large population this is another benefit that should not be overlooked.

5.11

Sources of further information and advice

and MARTIN, D.R. (2002) `Relationship between ice recrystallisation rates and the glass transition in frozen sugar solutions' Journal of Science in Food Agriculture 82 1855±1859. AVALTRONI, F., BOUQUERAND, P.E., and NORMAND, V. (2004) `Maltodextrin molecular weight distribution influence on the glass transition temperature and viscosity in aqueous solutions' Carbohydrate Polymers 58 323±334. BARBOSA-CAÂNOVAS, G.V., FONTANA, A.J., SCHMIDT, S.J., and LABUZA, T.P. (2007) Water Activity in Foods ± Fundamentals and Applications, John Wiley & Sons, New York. BLOND, G., SIMATOS, D., CATTE, M., DUSSAP, C.G., and GROS, J.B. (1997) `Modeling of the water-sucrose state diagram below 0 ëC' Carbohydrate Research 298 139±145. BOOS, Y., and KAREL, M. (1991) `Applying state diagrams to food processing and development' Food Technology 107 66±72. ABLETT, S., CLARKE, C.J., IZZARD, M.J.,

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(1989) `Improving the control of staling in frozen bakery products' Trends in Food Science & Technology 9 56±61. CLAUDY, P., JABRANE, S., and LEÂTTOFFEÂ, J.M. (1997) `Annealing of a glycerol glass: enthalpy, fictive temperature and glass transition temperature change with annealing parameters' Thermochimica Acta 293 1±11. COUCHMAN, P.R., and KARASZ, F.E. (1978) `A classical thermodynamic discussion of the effect of composition on glass-transition temperatures' Macromolecules 11 (1), 117±119. DA SILVA MALHEIROS, P., DAROIT, D.J., DA SILVEIRA, N.P., and BRANDELLI, A. (2010) `Effect of nanovesicle-encapsulated nisin on growth of Listeria monocytogenes in milk' Food Microbiology 27(1) 175±178. DE ARAUZ, L.J., JOZALA, A.F., MAZZOLA, P.G., and CHRISTINA, T. (2009) `Nisin biotechnological production and application: a review' Trends in Food Science and Technology 20 146±154. DECGUN, L.H., COTTER, P.D., HILL, C., and ROSS, P. (2006) `Bacteriocins: biological tools for biopreservation and shelf-life extension' International Dairy Journal 16 1058±1071. DEMAN, J.M. (1999) Principles of Food Chemistry, 3rd edn, Springer-Verlag, Berlin. FELLOWS, P.J. (2009) Food Processing Technology ± Principles and Practice, 3rd edn, Woodhead Publishing, Cambridge. FENNEMA, O., POWRIE, W., and MARTH, E. (1973) Low Temperature Preservation of Foods and Living Matter, Marcel Dekker, New York. FUNG, D.Y.C. (2009) `Food spoilage, preservation and quality control' in Encyclopedia of Microbiology, 3rd edn. 54±79. HELDMAN, D.R. (1974) `Predicting the relationship between unfrozen water fraction and temperature during food freezing using freezing point depression' ASHRAE Transactions 91(2B), 371±384. HOLZAPFEL, W.H., GEISEN, R., and SCHILLINGER, U. (1995) `Biological preservation of foods with reference to protective cultures, bacteriocins, and food grade enzymes' International Journal of Food Microbiology 24 343±362. KADOYA, S., FUJII, K., IZUTSU, K., YONEMOCHI, E., TERADA, K., YOMOTA, C., and KAWANISHI, T. (2010) `Freeze-drying of proteins with glass-forming oligosaccharide-derived sugar alcohols' International Journal of Pharmaceutics 389 107±113. KAHN, H., FLINT, S., and YU, P-L. (2010) `Enterocins in food preservation' International Journal of Food Microbiology 141 1±10. KENNEDY, C.J. (2000) Managing Frozen Foods, Woodhead Publishing, Cambridge. KRISTO, E., and BILIADERIS, C.G. (2006) `Water sorption and thermo-mechanical properties of water/sorbitol-plasticized composite biopolymer films: Caseinate±pullulan bilayers and blends' Food Hydrocolloids 20 1057±1071. MIZUNO, A., MITSUIKI, M., and MOTOKI, M. (1998) `Effect of crystallinity on glass transition temperature of starch' Journal of Agricultural and Food Chemistry 46 98±103. CAUVAIN, S.P.

Ä EZ, M.J., ÂN MOURE, A., CRUZ, J.M., FRANCO, D., DOMIÂNGUEZ, J.M., SINEIRO, J., DOMIÂNGUEZ, H., NU and PARAJOÂ, J.C. (2001) `Natural antioxidants from residual sources' Food

Chemistry 72 145±171.

and RING, S.G. (2005) `Physical aging of starch, maltodextrin, and maltose' Journal of Agricultural and Food Chemistry 53 8580±8585. PERES, A.M., and MACEDO, E.A. (1996) `Thermodynamic properties of sugars in aqueous solutions: correlation and prediction using a modified UNIQUAC model' Fluid Phase Equilibria 123 71±95. NOEL, T.R., PARKER, R., BROWNSEY, G.J., FARHAT, I.A., MACNAUGHTAN, W.,

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(1983) `Fundamental physicochemical aspects of food freezing' Food Technology 37 110±115. RICE-EVANS, C.A., MILLER, J., and PAGANGA, G. (1996) `Structure ± antioxidant activity relationships of flavanoids and phenolic acids' Free Radical Biology and Medicine 20 933±956. RODGERS, S. (2003) `Potential applications of protective cultures in cook-chill catering' Food Control 14 35±42. ROUDAUT, G., SIMATOS, D., CHAMPION, D., CONTRERAS-LOPEZ, E., and LE MESTE, M. (2004) `Molecular mobility around the glass transition temperature: a mini review' Innovative Food Science and Emerging Technologies 5 127±134. SCHILLINGER, U., BECKER, B., VIGNOLO, G., and HOLZAPFEL, W.H. (2001) `Efficacy of nisin in combination with protective cultures against Listeria monocytogenes Scott A in tofu' International Journal of Food Microbiology 71 159±168. SHAHIDI, F., JANITHA, P.D., and WANASUNDARA, P.D. (1992) `Phenolic antioxidants' Critical Reviews in Food Science and Nutrition 31(1) 67±103. SLOAN, A.E., and LABUZA, T.P. (1975) `Prediction of water activity lowering ability of food humectants at high aw' Journal of Food Science 41(3) 532±535. SONG, H., and SCHWARZ, N. (2009) `If it's difficult to pronounce it must be risky: fluency, familiarity and risk perception' Psychological Science 20 135±138. SONG, H., and SCHWARZ, N. (2010) `If it's easy to read, it's easy to do, pretty, good and true' The Psychologist 23(2) 108±111. SUHAJ, M. (2006) `Spice antioxidants isolation and their antiradical activity: a review' Journal of Food Composition and Analysis 19 531±537. TEN-BRINKE, G., KARASZ, F.E., and ELLIS, T.S. (1983) `Depression of glass-transition temperatures of polymer networks by diluents' Macromolecules 16 (2), 244±249. THOMAS, L.V., and DELVES-BROUGHTON, J. (2003) `Natamycin' in Encyclopedia of Food Sciences and Nutrition, 4110±4115. TSIMIDOU, M. (1997) `Kinetic studies of saffron (Crocus sativus L.) quality deterioration', Journal of Agricultural and Food Chemistry 45 2890±2898. WILLIAMS, G.C., and DELVES-BROUGHTON, J. (2003) `Nisin' in Encyclopedia of Food Sciences and Nutrition, 4128±4135. YILMAZ, Y. (2006) `Novel uses of catechins in foods' Trends in Food Science and Technology 17 64±71. REID, D.S.

5.12

Appendix

Table 5.8 (pp. 180±183) shows some physical properties of common carbohydrates and polyols, which may be used both as humectant ingredients and cryoprotectants.

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Table 5.8

Physical properties of common carbohydrates and polyols

Compound

Physical properties

Glycerol

Properties Molecular formula Molar mass Melting point Boiling point Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness

Xylitol

Sorbitol

D-Glucose

Properties Molecular formula Molar mass Melting point Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness Properties Molecular formula Molar mass Melting point Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness Properties Molecular formula Molar mass Melting point -D-glucose -D-glucose: Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness

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C3H5(OH)3 92.09 g/mol 17.8 ëC 290 ëC 100 ÿ84 ëC (-) 103 60%

C5H12O5 152.15 g/mol 94 ëC 64 ÿ21.9 ëC (-) 159.00 100%

C6H14O6 182.17 g molÿ1 97 ëC 70 ÿ1.9 ëC (-) 111 60%

C6H12O6 180.16 g/mol 146 ëC 150 ëC 47 37.3 ëC ± 104.6 74%

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Sucrose

Properties Molecular formula Molar mass Melting point Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness Maltitol

Properties Molecular formula Molar mass Melting point Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness

Polydextrose See page 182 for chemical structure

Maltodextrin 10 DE

Properties Molecular formula Molar mass Melting point Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness Properties Molecular formula Molar mass Melting point Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness

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C12H22O11 342.30 g/mol 186 ëC 67 52 ëC ÿ18 100% C12H24O11 344.31 g/mol 145 ëC 60 47.3 ëC (-) 79.1 90%

(C6H12O6)x 182±5000 g/mol 108 ëC 80 99.3 ëC ‡ 21 Low (C6H10O5)n 15 000 ~160 ëC 80 138 ëC ‡ 26 Low

Polydextrose

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Properties

Molecular formula Molar mass Melting point Solubility % w/w @ 25 ëC Glass transition temperature Heat of solution KJ/Kg Sweetness

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(C6H10O5)n 1.100, 000 ~250 ëC None 200 ëC ‡ 200 None

6 Processing and food and beverage shelf life Martyn Brown, MHB Consulting, UK

Abstract: The sensory characteristics of many food products alter during storage and these changes are often recognized by consumers as quality loss. Such changes are caused by chemical, biochemical and physical processes which start at harvest and continue during processing and storage and may eventually limit shelf life. Food processing is used to transform ingredients into products and change the properties, distribution and structure of ingredients. It may also affect the mechanisms of quality change. Hence product shelf life is determined by a combination of the raw materials used, the product formulation, processing, packaging and storage conditions. Key words: food components, food quality and safety changes, food processing and unit operations, thermal processing, food packaging and storage.

6.1

Introduction

The flavour and texture characteristics of many foods and beverages are unstable, and desirable characteristics can decline over a product's shelf life, being replaced by undesirable ones. These changes are recognized by consumers as quality loss and are caused by chemical, biochemical and physical processes. Their type and rate depend on various factors: · intrinsic factors derived from the raw materials, ingredients and the physicochemical environment in the product and its packaging · extrinsic factors surrounding or outside the food, including packaging, gaseous atmosphere, light and temperature which are important during storage

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· implicit, or combination, factors resulting from interactions between the other factors, especially processing and with microbes during storage (e.g., shifts in pH and nutrient degradation). Processing is used to give mixtures of ingredients a unique character and quality, and to control the rate of quality change during storage. Processing may change the intrinsic or extrinsic properties of materials or inactivate (e.g., enzymes or microorganisms) or activate (e.g., cellular disruption or fermentation) mechanisms of quality change. The shelf life of ambient stable foods and beverages is mostly determined by formulation, processing and packaging; storage conditions usually playing a minor role. But the stability of perishable foods (such as chilled products) is not fixed finally during manufacture, but depends on the way that the food is handled and stored (especially storage temperature) in the later stages of the supply chain (e.g., during transport, at a retail or food service outlet and then with the consumer). Processing may create or destroy food structures (e.g., by heating, cutting, freezing or bruising). At the microstructure level it may cause changes in the structure of polymers (e.g., proteins and starch) and mass transfer (e.g., water movement or loss). Mixing and cutting can influence the rate of adverse chemical changes, dominated by rancidity and browning reactions. Endogenous enzymes in ingredients can cause hydrolysis (lipids and proteins) and liquefaction or cloudiness in juices (see http://www.foodnavigator.com/FinancialIndustry/DSM-launches-enzyme-for-cloudy-citrus-drinks) and may also alter flavours. Ripening can also occur before or during storage, improving quality (e.g., cheese, vegetables and fruits). Unless processing eliminates microorganisms, they can cause spoilage and a wide range of chemical changes, which may be noted as gas production, off-flavours and odours or discoloration, including the appearance of microorganisms on the surface or within products, but foods and beverages may also be improved by microbiological fermentation processes. Quality change during storage usually follows the time course and temperatures in the supply chain (e.g., manufacturing, packaging, distribution and preparation by the consumer), but its rate is additionally affected by formulation and any packaging barriers to water and oxygen or gas transfer or protection from physical damage provided by packaging. As elements of processing, unit operations will have largely foreseeable effects on ingredients (e.g., size reduction, cooking, freezing, drying), and a series of unit operations will have more extensive effects and their combination and sequence will lead to recognizable products (e.g., cooked meat or bread or juice; see Meyer et al., 2001). In order to make good quality, stable products, input materials of the right age or ripeness and quality are needed, these should be used with the right processing conditions and equipment acting at the right time, or following a particular event such as harvesting or slaughter. In mildly or unprocessed products (e.g., washed salads), quality change will be driven mainly by chemical composition, mass transfer, microbial activity and enzyme activity. In more heavily processed products, these intrinsic factors will be overshadowed

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by the effects of processing. These effects are altered by inactivation of microorganisms and enzymes, ingredient history and microbiology (both before and after processing), the packaged environment (e.g., dry/moist, high CO2 or O2 free) and any additives, packaging or logistics systems designed to slow, or prevent, changes. Processing can stop or minimize quality loss, but it cannot reverse quality changes that have already happened, although it may be used to mask the presence of low quality materials and some quality loss. Fatty or gristly meats can be `improved' by mincing, flaking or bowl-chopping to make sausages. Tomato paste or juice quality is determined by ripeness at harvesting, quality defects (e.g., insect or sun damage) and processing conditions (see http://www.fenco.it/eng/ tomato-paste-processing.asp) and can also change during storage (Apaiah and Barringer, 2007). But quality can be standardized by blending fruits of different ripeness (http://www.fda.gov/Food/GuidanceComplianceRegulatory Information/GuidanceDocuments/Sanitation/ucm056174.htm). Whilst there are accepted, objective methodologies to assess the physicochemical effects of processing (texture, colour, pH), the same is not true for assessing its overall effect on `quality' and `quality loss' in consumer terms, because quality is often a subjective view of a product, and opinions on good and poor quality may differ within groups of consumers. To help producers meet consumer needs, ingredient and process specifications and work instructions for equipment often contain targets and limits (e.g., temperatures and times, texture and colour descriptions) for controlling the attributes valued by consumers. Shelf life is the limited time between the manufacture of a food ingredient or product and the time when it no longer meets its design requirements for quality or safety because desirable characteristics have declined and unwanted ones built up to unacceptable levels. It can be assessed in a variety of ways, including chemical, physical and sensory analysis after processing, during realistic storage or accelerated trials, by challenge testing and modelling, and consumer feedback on product quality, including complaints. Knowledge of factors causing quality change and their mechanisms, including rates of change and interactions between specific ingredients or process conditions means that it may be possible to improve ingredient sourcing, formulation or processing to reduce rates of, or even prevent, deteriorative reactions. To supplement sensory measurements, instrumental techniques can also be used to analyse texture changes or the appearance of trace amounts of chemical components related to, or responsible for, sensory changes (e.g., pH shift, offflavours or rancidity). If sensory panels are used to validate conclusions drawn from instrumental tests, it is important that the results are scored against fixed sensory markers based on a hedonic scale, `just noticeable difference', or the intensity of relevant descriptors or attributes. Scoring a product as only acceptable or unacceptable usually provides insufficient information for guidance on the causes of quality change and any corrective measures needed. For example, rancidity in frozen meat and fish products is a quality change obvious to many consumers. It is caused by the oxidative breakdown of fats, and may be accele-

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rated by cell damage during processing and sublimation during frozen storage. Quality change can be tracked using aldehydes and hydroxy compounds that can be analysed chemically (e.g., TBA or peroxide value), but flavour changes are only evident at the later stages of the oxidation process. Without doubt in the market place, consumers indicate their view of quality by purchasing, or not purchasing, products. After an initial purchase, repeat purchase indicates that products have met consumer requirements including quality (and cost). Prior to launching a product, pilot plant trials may be carried out to explore the effects of different process conditions or ingredient combinations. Trained sensory panels can be used to indicate likely consumer views on each combination, using appearance, smell and taste to characterize the `quality' produced. The information generated can be used to scale up processes to commercial production and information may be used later, by producers and retailers, to track quality change, predict shelf life and likely consumer response to any changes.

6.2 Main quality change factors and their interaction with processing There are well-defined links between quality changes and processing. Processing will cause major texture and flavour changes in proteins and other polymers. Structural changes include coagulation caused by heat or chemical additions, which are affected by the rate of heating and the chemical environment (e.g., pH or ion (Na++ concentration) during heating). In juices, changes in particular proteins and polyphenols will alter particle size distribution in colloids and cause haze (Siebert, 2006). Fermentation processes may use intrinsic enzymes and those from microorganisms to cause other changes including pH shifts (e.g., pH change in cheese or yoghurt), flavour changes resulting from the breakdown of proteins to amines or peptides (e.g., ripening of cheese and salamis ± see Coppola et al., 2000). Changes in carbohydrates and starches can similarly be caused by heat, microbial or enzyme action. These can lead to gelling (e.g., by baking ± see Fessas and Schiraldi, 2000), liquefaction (by microbial action) or staling due to water movement and retrogradation of amylopectin during storage (Gray and Bemiller, 2003). Some chemical changes take place at rates governed by moisture content and temperature; changes in storage temperature can change the physical state of one or more of the components and alter the reactions occurring. A 10 Cë rise, at normal or hot ambient temperatures, causes about a twofold increase in reaction rates. Cool storage retards changes such as fat oxidation, vitamin loss and container corrosion. Keeping foods cool and dry will usually greatly reduce the rate of browning reactions and associated off-flavours (see http://foodquality.wfp.org/ Portals/0/Foodstoragemanual.pdf). During processing and storage, fats and oils with different melting points may be crystallized or melted by temperature changes. Oxidation and lipolytic

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changes may occur in response to levels of oxygen, temperature and the degree of unsaturation of the fat, leading to stale or rancid tastes that decrease palatability (see Evans and Ranken, 2007). The rate of oxidative reactions also depends on the presence of pro- or anti-oxidants, energy inputs (light or heat), and the level of moisture in the food. Colour change in beverages can be minimized by addition of ascorbate (Lea, 1994). Some fats such as coconut and palm oil are very resistant to oxidation, while others such as fish oil, soybean oil, lard and tallow containing double or triple unsaturated bonds are less so. Many metal compounds (especially iron, which may be released from muscle tissue by cutting or mixing) can catalyse oxidative or rancidity reactions (both the initiation and propagation stages) and degrade other nutritional and flavour components present. The rate of rancidity development in meat (e.g., pork, bacon and turkey) is increased during storage, if haem compounds have been released from meat and fat cells damaged by mixing or cutting (mincing) and freezing/thawing (see http://www.fao.org/DOCREP/004/T0279E/T0279E06.htm and Farag et al., 2009). Rancidity can limit the shelf life of fats and oils, and also the shelf life of many ambient stable and frozen foods that contain them. When fatty products (e.g., nuts and savoury snacks and frozen minced meat or fish products) are stored in air, oxidation may proceed at a rapid rate, limiting the high quality shelf life to weeks rather than months or years. These non-microbial changes can be controlled by careful choice of additives (e.g., antioxidants), packaging (especially oxygen barriers to limit rancid odours and flavours) or processing (e.g., to inactivate peroxidises or lipases). Some mild steel equipment can also release catalytic ions during processing. Effects may be further increased if catalysts and reactants are concentrated in the unfrozen water remaining in frozen stored product. Browning of frozen white fish is caused by endogenous reactions (see Pearson et al., 1977). Perceived product quality may be affected by storage temperature; at high ambient temperatures (>25 ëC), the fats in canned meat melt, but at chilled temperatures these fats, and any sugars in solution, crystallize giving a granular texture. The absorption of moisture by dried foods can also cause undesirable physical changes but can be prevented by packaging in suitable moisture barrier materials. For example, sugar will absorb water from the atmosphere when the relative humidity exceeds 86%; this causes a film of saturated sugar solution to form around each particle and if the relative humidity falls below 86%, water is lost from this saturated solution and crystals form on the surface of each particle binding them together, so that the sugar becomes caked into a hard mass. Salt behaves similarly, but forms saturated solutions at a lower relative humidity (75%). The absorption of moisture by dried fruits may also lead to sugar crystallization. After harvest, enzymes may also cause the oxidative breakdown of fatty acids in fruits. Bruising or damage during handling will give characteristic aromas and colours. Bruising and cutting during processing may also cause the browning of cut surfaces exposed to oxygen (browning caused by polyphenoloxidases). The main process routes to control endogenous enzyme activity (e.g., peroxidises,

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polyphenoloxidases and lipases) are blanching, drying, pH modification or chemical addition (such as sulphite) or combinations of these measures (e.g., citric acid or sulphite blanching). Exclusion of oxygen or gas blanketing during processing can reduce oxidative reactions significantly and also slow ascorbic acid breakdown (Kacem et al., 1987). Similarly oxidative reactions, especially in dry products, can be slowed by placing the materials in sealed packs providing an oxygen barrier; such packs may also be filled with an oxygen-free gas mixture to further increase their effectiveness. Oxygen barriers also control the oxidative loss of ascorbic acid from foods, such as aseptically packaged fruit juices (Soares and Hotchkiss, 1999). Almost any type of processing (especially heating or size reduction) and storage will cause changes to the colour of vegetable and fruit tissue, because bright pigments (chlorophyll, red anthocyanin or red/yellow carotenoids) are converted to dull ones (e.g., phenophytins) during heating. Loss of chlorophyll is accelerated by dehydration and catalysed by low pH and light. Modified or controlled atmosphere storage can be used to slow the rate of loss of colour. The rate of destruction of anthocyanins is also pH dependent, faster at high pH values, and purple pigments may be formed when these pigments are in contact with metals (e.g., in cans). This may be prevented if cans have inert coatings, such as epoxy. Carotenoids may auto-oxidize in the presence of oxygen at rates dependent on process temperature, light and the presence of catalysts or free radicals (Borowska et al., 2003).

6.3

Shelf life and stability

6.3.1 Process factors influencing shelf life No processing operation acts alone to determine the shelf life of a food, but they interact with the chemical, physical, biochemical and microbiological factors in foods to give food an initial quality followed by a sequence of quality changes during its shelf life. Many changes to the structure and chemistry of food are linked to changes in temperature during processing, and storage will accentuate these changes. Table 6.1 shows the three main groups of factors controlling the type and rates of food quality (and safety) changes. Unless a food has been freed of all living microorganisms and microbial or fungal spores by processing (e.g., a commercial sterilization process), and is packaged (e.g., cans, jars or aseptic packaging) to prevent re-contamination or has intrinsic properties (e.g., low aw) which prevent microbial growth, it will be perishable and will spoil due to the action of microorganisms and the accumulation of their metabolic products. Many heating processes (e.g., pasteurization or sterilization) are designed to eliminate or inhibit specific microorganisms and/or enzymes which cause spoilage (e.g., pseudomonads or lactic acid bacteria) or present a safety risk (e.g., salmonella, Listeria monocytogenes and Clostridium botulinum ± see Section 6.8). Water activity (aw) is one of the most critical intrinsic factors determining the shelf life, safety, texture, and the other sensory properties of foods. It can be controlled by ingredient (humectant)

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Table 6.1

The three main groups of factors controlling the rates of food quality (and safety) change

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Intrinsic

Extrinsic

Implicit

a. Cellular or larger structures b. Composition, different ingredients and their concentration, changes to the concentration or distribution of ingredients or addition of new ones (e.g. acidification or fermentation) c. Changes in ingredient concentration due to reactions during storage d. Functional attributes of ingredients (e.g., heat setting of proteins and polysaccharides and creation of flavours), e. Creation of new structures (e.g., mixing and emulsification) f. Diffusion and migration properties g. Enzymes (e.g., polyphenol oxidases and peroxidases) h. pH or acidity i. Water activity (aw), moisture content and solute concentrations j. Redox or dissolved oxygen or CO2 level k. Presence of preservatives (either natural or added)

a. Disruption (e.g., by mincing or dicing) or creation of structures by processing b. Process and storage temperatures (e.g., designed to kill or retard the growth of microorganisms or inactivate enzymes) and gradients involved heat or cold diffusion c. Presence of barrier materials (e.g., packaging) d. Gas transfer, removal or inclusion in the product or pack headspace (e.g., concentrations of oxygen and carbon dioxide) e. Visible and UV light.

a. Presence of microbial contaminants b. Specific microbial growth rates in the food or beverage c. Interactions between microorganisms and ingredients to produce changes d. Synergy between microorganisms e. Antagonism between microorganisms f. Commensalism between microorganisms (e.g., the relationship between organisms of two different species in which one derives benefits from the association while the other remains unaffected) (Encarta Dictionary).

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addition or by water removal during processing (e.g., air or osmotic drying). Water activity is an important intrinsic factor determining how fast microorganisms will grow and metabolize in a product, causing spoilage. Most spoilage bacteria, for example, do not grow at water activities below 0.91, and most moulds cease to grow at water activities below 0.80 (minimum aw for xerophytic moulds is 0.65). By measuring aw, it is possible to predict which microorganisms may cause spoilage. If the changes mediated by microorganisms are insignificant or non-existent, chemical, biochemical or physical reactions (e.g., rancidity, non-enzymatic browning or staling) will limit shelf life. Many vitamins are degraded by oxygen including vitamin C (ascorbic acid) and vitamin B (thiamine). If quality depends on packaging systems to control product attributes such as crispness, or shelf life relies on a modified atmosphere or aseptic packaging, then the correct barrier material, packaging and sealing system must be provided and the resulting pack must be capable of excluding microorganisms, preventing the transfer of moisture or gas from the outside to the product and resisting physical damage during distribution in the designated markets or logistics chains. While freezing stops microbial activity, other chemical reactions can still proceed. Reaction rates may be increased if reactants are concentrated in the unfrozen water, present even at storage temperatures below ÿ12 ëC. Slow freezing rates may cause greater concentration of reactive solutes than fast freezing, but the effects on quality are not always clear cut (see http:// www.unido.org/fileadmin/import/32111_18FreezingMethods.10.pdf and de Kock et al., 1995). 6.3.2 Quality and shelf life management Product safety covers microbiological, chemical and physical (e.g., bones and sharp items) safety factors, whereas product quality is defined by the product characteristics wanted by marketing and consumers and these should be specified in the design (see Fig. 6.1). Ensuring that food products retain their quality and stability over their shelf life and a product range retains them over its product life cycle (which may be months or years), requires reliable identification, control and monitoring of process conditions and quality hazards. Key controls should be derived from ingredients and the product and process designs (see Section 6.4). The indicators (e.g., temperature, particle size, salt level or pH) used to monitor them should show what has happened during processing and if possible in the supply and logistics chains under realistic conditions. Analytical or sensory measurements immediately after production show the initial quality; further testing may be used to show how quality changes over the shelf life. Data should be sufficient to show variability within a batch and between batches, it should be regularly reviewed to indicate effects that can be attributed to changes in origin or quality of raw materials or the operation of equipment and processes. The most effective means of controlling quality is to focus on critical raw materials, processing

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Fig. 6.1

Linking design to management of quality using a HACCP type approach.

operations, storage conditions or aspects of product usage or abuse (quality control points (QCPs) ± see below). If realistic hazards are not controlled, then the risks of making low or variable quality products and failure to meet shelf life targets are increased. If over-severe processes are used to compensate for unrealistic or lax controls (e.g., over-severe heat processes to compensate for variable product heating or insensitive control systems), initial product quality may be reduced and quality change accelerated. Today it is widely recognized that the most effective way to manage food safety is using the Hazard Analysis and Critical Control Point (HACCP) system. The principles of HACCP are equally applicable to quality management (Peters, 1998 ± see Table 6.2) where the critical control points (CCPs) relevant to safety are replaced by QCPs covering quality. Table 6.2 shows the stages linking design to quality management based on the stages used in the HACCP principles: hazard identification, flow diagram and CCPs (QCPs), targets and limits, monitoring, corrective actions and validation. Safety aspects of HACCP are defined by the Codex Alimentarius Commission and are written into the legislation of many countries and trading groups (e.g., EU). However, the HACCP system alone cannot ensure that the supply chain is effectively managed to make safe, high quality products. The HACCP programme for any process line or manufacturing area must be based on hygienic manufacture and sourcing (Recommended International Code of Practice General Principles of Food Hygiene, CAC/RCP 1-1969, rev. 4-2003). In addition, the prerequisites applicable to the process technology (e.g., thermal processing, ready meal manufacture

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The HACCP principles applied to quality

HACCP principles

Safety

Quality

Conduct a hazard analysis based on the intended product use

Biological, chemical and physical hazards

Taste, texture, colour, shelf life and product characteristics

Identify critical control points (CCPs) based on a flow diagram and its onsite validation

Identify process steps controlling the identified safety hazards (CCPs)

Identify process steps controlling the identified quality and shelf life hazards (QCPs ± quality control points)

Establish critical limits for each critical control point

Critical limits derived from legislation or process performance

Critical limits derived from sensory or consumer trials or process performance

Establish critical control point monitoring requirements

On line or by-line product or material testing with sampling plans or instrumental data from process equipment

Establish corrective actions

Actions to protect safety and minimize losses

Actions to protect quality and minimize losses

Establish record-keeping procedures

Records to show performance at CCPs and prerequisites

Records to show performance at supply chain and process stages affecting quality and shelf life

Establish procedures for ensuring the HACCP system is working as intended

Monitoring, verification or validation procedures for identified safety hazards

Monitoring consumer complaints and QA data

or salad preparation) need to be identified. These define the necessary operational conditions in areas used for manufacturing and storage, adequate equipment, control systems, facilities (e.g., transport and stock rotation) and utilities (e.g., steam, potable water and air supply). Prerequisites are the basic control measures that should be in place in any manufacturing facility, such as pest control, hygiene, waste management, training programmes and supplier assessment. It is often said that HACCP should be limited to safety-related issues, but because this technique identifies the requirements for ensuring that a process is under control (FAO, 1998), it will by default include conditions affecting quality. Although controls and monitoring procedures for prerequisites should extend throughout the entire supply chain, QCPs should focus on unit operations that impart quality, alter the risks of quality change or increase the presence or levels of precursors of quality change (e.g., under-processing or recontamination). Procedures or corrective actions must be in place to ensure quality defects and risks to the consumer are minimized if processes go wrong or defective material is processed.

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Based on quality requirements, the production planning system should provide cleaning at suitable intervals. Whilst this is important for quality, it is critical if allergenic materials are handled and products not labelled `at risk' or `may contain traces'. Good hygiene practices, which prevent the build-up of food debris in equipment or areas, and minimize cross-contamination or carryover of incipiently spoiled material that can prematurely initiate quality changes, are essential to ensure quality and shelf life remain consistent. Product contamination can lead to unnecessarily high costs arising from defective, prematurely spoiled or rejected products. The requirement for specific levels of hygiene for processing and handling perishable products has led to the designation of different types of manufacturing area based on their level of hygiene (e.g., good manufacturing practice (GMP), High Care or High Risk areas; CFA, 2006). Choice of manufacturing area based on hygiene is particularly important in chilled food manufacture, especially if ready-to-eat products are made, because microbiological contamination in conjunction with temperature or time abuse during storage can lead to premature spoilage, quality loss or a safety hazard (e.g., from Listeria monocytogenes). 6.3.3 Challenge studies Challenge tests can be used to find out what can happen to ingredients and products during storage or within equipment during processing (e.g., dairy protein coagulation and equipment fouling during UHT heating) or storage (e.g., elevated storage temperature trials) at or outside the limits. They can also be used to validate any proposed limits for ingredients or process conditions, by using materials or processes run at the limits. The effects of microbiological contamination or spoiled or defective material, including material held up in equipment, can be investigated using inoculation of ingredients or tracers into products. To simulate the effects of microorganisms, the actual hazards or more frequently indicator microorganisms (e.g., Listeria sp., lactic acid bacteria or harmless heat-resistant spores) can be used to mimic the response of the target microorganisms to processing, hygiene or storage. Taste panels should never be subjected to the hazard of food poisoning from trial samples. Challenge studies are also widely used to determine if processes can control different input levels or types of spoilage microorganisms (e.g., the effects on the effectiveness of pasteurization and hygienic assembly) or cope with quality variability or substitution of ingredients in a product (e.g., the impact of different thickening agents on heat exchanger performance or product viscosity). The impact of changes may be judged by examination of process data (e.g., steam consumption of a heat exchanger to maintain a fixed product flow temperature) or by sensory panels, microbial counts or chemical analysis (e.g., pH shift or viscosity). Where new ingredients affecting product structure or flow are being trialled, process analysis based on inspection of equipment or process records is always needed to provide a complete picture.

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6.3.4 Shelf life testing For most foods, the aim of shelf life testing is to find, or confirm, the acceptable life of product made under manufacturing (not pilot plant) conditions, with realistic distribution, retail storage and consumer handling. Unless there is very good evidence to the contrary, shelf life testing should only monitor factors likely to accelerate or contribute to quality change, for example, the effects of variable process temperatures (e.g., low pasteurization conditions or severe sterilization processes) and fluctuating (or higher) storage temperatures. Fluctuating temperatures during processing may have some unusual effects, and may cause condensation or moisture migration in some dry product/pack combinations leading to caking or spoilage by moulds. For chilled products shelf life estimates based on a steady 8±10 ëC or cycling between 5 and 10 ëC are likely to be significantly shorter than an estimate based on a steady 5 ëC (e.g., Riva et al., 2001) and judgement must be exercised when such data are used to set a shelf life. 6.3.5 Predictive modelling Mathematical modelling has been used extensively to predict the behaviour of pathogenic microorganisms (http://www.combase.cc/) during processing (e.g., during heating) and in foods (e.g., different storage temperatures, pH values and aW). It is well established as a means of designing safe processes and preservation systems or assessing the effects of process conditions and the safety of chilled products when storage temperatures have been within the growth range of pathogens (see http://www.fsai.ie/food_businesses/topics_of_interest/ predictive_micro.html). And it has to some extent replaced challenge tests as a means of helping manufacturers produce microbiologically safe and stable products. Modelling the behaviour of spoilage microorganisms or sensory changes in foods during storage is carried out less frequently, and is more difficult because many factors can alter the relative rates of quality changes, or the production of the end-products noted as spoilage or predict the behaviour of the few species from the whole microbial population that cause spoilage (Koutsoumanis, 2001; Koutsoumanis and Nychas, 2000). However, it is generally true that the higher microbial numbers at the start of storage, the shorter will be the shelf life of the product. To realistically predict the effects of processing on quality change, models have to take account of any variability arising from different ingredient, process and storage conditions (see Cerf et al., 1996; Mataragas et al., 2006). Mechanistic models can be used to interpret process data collected during trials (van Boekel, 2008) and models based on the underlying physiological and biochemical mechanisms for quality change have been used to predict quality change in mushrooms (Lukasse and Polderdijk, 2003). Modelling is often based on principal component analysis and detects differences using regression techniques (see Ross, 1998). Predictive models for the effects of processing equipment on foods (e.g., mincers and mixers) do not exist at the present time

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and for this reason, trials are done to find the optimum settings for the equipment used to make a product. An exception is models predicting heating by continuous heat exchangers (Cox and Fryer, 2002). Models for in-pack heat treatments Besides microbiological growth models, there are also models that predict the lethal effects of heat on vegetative microorganisms and their spores. Models range from simple `D' and `z' models, used to analyse the lethal effects of heat treatments, to more sophisticated models which use the physics of heat penetration into foods to predict the lethal effects of process conditions (see Peleg and Cole, 1998; Coroller et al., 2006; Pradhan et al., 2007). However, direct temperature measurements taken at the coldest points in packs are still used routinely with various calculation tools such as the General Method and the Ball formula method (see http://www.tcal.com/library/ProcessesCalculation Method.html) to evaluate sterilization and pasteurization processes (see Lanoiselle et al., 2006). And over the past 10±15 years, computer software (e.g., TechniCal software ± http://www.tcal.com/CALSoftSoftware.php) has been increasingly used for thermal process assessment and generation of records. Conventionally `D' represents the decimal reduction time (the time required for a one log cycle reduction in a specified microbial population) and `z' is the temperature coefficient of microbial destruction, linking temperature and lethal rate. Advanced computational fluid dynamic (CFD) calculations are beginning to allow improved understanding of the movement of heat and the formation of temperature gradients in packs with different heating characteristics (Hiddink et al., 1976 and http://www.biw.kuleuven.be/aee/vcbt/model-it/pdfs/24.pdf); and CFD has also been applied to studying flow and heat transfer in products with non-Newtonian flow characteristics (RodrõÂguez-Luna et al., 2006). Improved understanding of heat fluxes will allow more realistic models to be built and coupling these models to the kinetics of quality change, rather than microbial lethality, will allow the quality impact of different process conditions to be assessed and optimized, for example by the use of variable retort temperatures (Awuah et al., 2007). From very basic physics it can be understood that the material at the outer edge of a pack will receive a much higher heat process than material at the centre. And this is evident in solid or conduction heating products. There are models for convection heating products (thin soups or beverages) being sterilized in cylindrical cans (Abdul Ghani et al., 1999, 2001, 2003) and flat pouches (Datta and Teixeira, 1988) where natural convection is the main mechanism of heat transfer and product mixing during processing gives a more uniform quality. Tattiyakul et al. (2001, 2002) have modelled product flow and heat transfer in axially rotating cans (forced convection) and concluded that the slowest heating zone was not at the geometric centre of the can and its position was shifted by the speed of rotation. Natural and forced convection and agitation are used to speed up heating and also reduce the range of heat treatments within

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any pack. Hence commercial sterilization processes often use end-over-end rotation of cylindrical cans to accelerate heating rate and product flow (Hughes et al., 2003). Models for in-line heat treatments Many liquids and liquids containing particles are processed in continuous heat exchangers. Mathematical modelling is a critical technique for designing and setting process conditions for these heating and cooling systems (see Lewis and Heppell, 2001) and models may also be used as part of the control systems of heat exchangers (e.g., a first-order plus dead time (FOPDT) dynamic model ± see http://www.controlguru.com/wp/p57.html) or feed-forward or feed-back control (see http://www.mathworks.co.uk/products/control/demos.html?file=/ products/demos/shipping/control/heatexdemo.html). At present, temperature measuring equipment cannot be used to assess the thermal processing of particles in a liquid flow, because available sensors and logging equipment can affect the size and/or density of particles, and hence their flow characteristics, which can cause significant and unknown inaccuracies in the measured temperature history as they travel through the various heating, holding and cooling stages of the equipment (see Sastry, 2007; Meng and Ramaswamy, 2007). Hence the use of conservative models to predict changes in particle centre temperatures, based on low heat transfer rates from the carrier liquid to the particle surface, is essential for the safe processing of liquids containing particles. The current focus of modelling is to predict temperature history at the coldest point within the slowest heating, or fastest-moving, liquid (Pacheco and de Massaguer, 2005) or particles (Cacace et al., 1994; Chandarana et al., 1990; Mankad et al., 1997; Sastry, 1986) during sterilization. There have been attempts to provide realistic `sensor' particles that do not upset flow characteristics and some practical methods are based on inoculating mimic particles of the same size and specific gravity as `real' particles with known levels of heat-resistant marker spores (e.g., Bacillus subtilis) to show the extent of sterilization (see Dallyn et al., 1977; Richardson, 2004; Martinez et al., 2006). At the end of processing, surviving spores from the particle are counted to determine the effective heat treatment. Because spores are located around the cold-point of the particle, a `representative' integrated, not a minimum, heat process is measured, but the minimum transit time of particles cannot easily be found. The fastest moving particles receive the lowest thermal process and are used as a basis for setting safe processes. But it is the slowest moving particles and the bulk flow fraction that will determine quality. The variables and interactions affecting thermal processing of particles and residence time distribution among the fastest and slowest moving particles in the flow are not yet fully understood. In real food systems colliding particles, different viscosities, specific gravities and the nonlinear flow characteristics of many carrier liquids are likely to limit the applicability and reliability of modelling for process verification (Sastry and Cornelius, 2002). The lethal effects of heating irregular shaped large pieces have

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been modelled by integrating heat and mass transfer models with a kinetic model predicting microbial inactivation, to show the effects of temperature and water content on inactivation during air±steam impingement cooking (Pradhan et al., 2007).

6.4

Product and process design

Food products are usually composed of carbohydrates, fats, proteins sourced from plants, fruits, animals or fish and water. Stability is a product's ability to retain characteristics and functionality during processing and its anticipated shelf life. Hence a product design describes the character, quality characteristics, stability and shelf life intended for a product, and a process design describes the raw materials and sequence of processing steps proposed for making it, including the control parameters and necessary targets and limits at each stage. In many cases, packaging is part of the design as it plays an essential role in processing, presenting the product and preventing quality change during storage. Target physical and chemical properties and changes need to be included in the design and then controlled during processing. These changes may be measured or predicted using sensory, chemical or physical indicators. Key changes include: · changes to structure, texture and aw (e.g., progressive changes in the crosslinking of macromolecules ± proteins, pectins and starches, the coalescence of emulsions, chilling or freezing damage and mass transfer of water) · chemical changes influencing taste, smell and colour (e.g., the oxidation of fats and oils, denaturation or other reactions of proteins and peptides, changes in vitamin, porphyrin and chlorophyll pigment levels and changes in the state of haem and other pigments) · biochemical reactions (such as autolysis, enzymatic browning or oxidation) · physical (e.g., bruising or puncturing) or insect damage · microbial activity (e.g., spoilage, food poisoning toxins or infectious doses of pathogens) · ingredients causing or accelerating unwanted changes in other ingredients. Designs are often turned into specifications through development trials which provide an outline of the materials, processes and operational procedures to be used and an indication of quality when the product is made on a larger scale. Early in the development process, all the factors realistically affecting product quality, stability and safety need to be identified, so that suitable controls and monitoring techniques can be decided before trials are carried out (ICMSF, 1996). Trials represent the best way of selecting ingredients and processing conditions that will turn a marketing concept into a successful and stable product and trial results should show which ingredients and equipment require tight control to ensure high quality and identify the impact of variability on quality, for example the effects of poor equipment control or the variability of

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commercially sourced raw materials. Trials with different materials can be used to identify ingredient characteristics, and process or storage conditions, that can lead to formation of the precursors accelerating quality change in processed or part-processed materials (e.g., the use of over-ripe or wilted vegetables and fruit, the use of fats or oils with a high level of rancidity precursors. or equipment that retains aged material in tide marks). Identifying key materials and process conditions is often difficult, but should be tackled before a design is finally translated into manufacturing specifications and procedures. Trial results are an important contributor to any HACCP study because they indicate likely control points, limits, monitoring and corrective actions. Heat treatments, not process conditions are normally given in a process design; therefore heating trials are performed as part of product development to verify that any pilot-scale equipment used to prepare the concept samples makes products of similar quality to production scale equipment providing the same heat treatment. For example, heating in large vessels (e.g., jacketed kettles > 1 tonne volume) may be very slow compared with heating in a 10 l vessel, heating will be done for longer and product will be in contact with the heat exchange surfaces or vessel jacket and may be burnt. If heat treatments have been adapted from pilot plant trials by calculation, based on temperature measurements (e.g., using D and z), it is necessary to conduct sensory and storage trials during the initial commercial production runs to validate that the large-scale process conditions still provide the quality characteristics required by the original design. If the selected combination of processing and preservation measures gives a stable product with the required sensory characteristics, then it has a chance of being successful in the market place. If the demands of production impose oversevere conditions during processing or in the logistics chain, then product stability and quality may be reduced and this lowers the chances of product success. Any specifications and work instructions derived from trials should be reconciled to the original product design and at least specify the material flow, treatment of ingredients during processing and storage and take account of process and material variability. They should also specify the quality characteristics of the product immediately after manufacture (e.g., sensory quality and performance when used) and detail any preservation factors which determine the safety and shelf life. These key factors should be picked up as CCPs in the HACCP plan. Many safety and quality problems found during the life cycle of a product are traceable to mistakes made at the development and scale-up stages. However, in reality a product is often a compromise between demands for safety, quality and ingredient cost on one hand, and supply chain or equipment limitations on the other. With a potentially successful design, the task of the supply chain is then to consistently provide good quality products meeting consumer expectations on cost, availability, shelf life, quality and quality change, so the skill of process engineers lies in being able to deliver the original design with commercial scale equipment and take account of the variable materials inevitably sourced by the supply chain.

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To reduce variability, raw material buyers should minimize the intake of ingredients known to vary product quality or processability. Often these materials can be identified at the design stage because they have a history of causing variable processing or unwanted quality changes in other products. Successful product manufacture must take account of these risks, and the impact of the anticipated product distribution and storage conditions on quality change. For any product and consumer use, the microbiological safety rules are generally clear cut (see Lund et al., 2005) and usually based on product usage, but defining good quality is more difficult because requirements can vary depending upon the type of food and the consumer's preference, including the extent of changes acceptable in the product at consumption. Quality characteristics important to consumers include perceived freshness, flavour, texture, colour, aroma and nutrition.

6.5

Processing

Processing covers all the activities, techniques and equipment used in a coordinated way to transform raw materials, ingredients and packaging into food products. Commercial production may be done on a variety of scales, ranging from small scale, employing 1 or 2 people, to large scale automated lines producing 6±10 tonnes per hour. To ensure consistent quality and stability, process lines should be operated in a planned way, and have sufficient capacity to meet input and output demands. Fresh or perishable ingredients should be stored for the minimum time and handled to minimize damage; they should be cooled rapidly after harvesting to slow down ripening and spoilage processes. To ensure optimum processing, equipment for the primary processing of harvested materials (e.g., tomatoes or peas) usually has a very high capacity to match the peak harvest rate. To preserve quality, lines have to process ripe material within a very short time after harvest and if processing is delayed quality is lost (see Miers et al., 2006). Such equipment is usually specialized and is only used for the harvest season (e.g., 12 weeks/year). With the advent of mechanized harvesting, the range of qualities that processes have to handle has increased, because harvesting is often timed to achieve the best yield and the material harvested may be over- or under-ripe. After harvest, temperatures and the change of temperature (e.g., heating and cooling) should be controlled prior to further processing to ensure consistent quality. Preparation and preservation techniques for ingredients all provide distinctive sensory properties, even after further processing. A variety of physical technologies, especially heat, are available to kill, inactivate or remove microorganisms from ingredients. To ensure predictable quality and shelf life, all ingredients, in-process materials and products should be kept within their designed handling and storage conditions (see Singh and Heldman, 2008). The aim of processing is to develop or create desirable flavours, textures, colours, aromas and prevent or delay quality and microbiological changes.

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Different materials will need different process conditions and transfer techniques to move along a process line. They may be solid or liquid or change from one state to another during processing; liquids may change from liquid to a vapour, solid or gel. Packaging equipment and control systems and maintenance of equipment needs to cope with variable raw materials, materials of different hardness, abrasiveness and particle sizes and its design, maintenance and operation can alter the balance between desirable and undesirable effects. Often functionally similar process stages will produce very different effects when carried out by different equipment or under different operating conditions. Heating by different heat exchangers may give different flavours, because of different temperatures and residence times. And size reduction equipment may give different particle size distributions depending on the type of blades, their sharpness and feed pressures used (see http://www.nzifst.org.nz/unitoperations/ sizereduction1.htm). Processing and storage may also initiate or cause unwanted quality effects (e.g., cell damage, colour change, loss of volatiles, syneresis, oxidation and browning). If heat exchangers and the products are not compatible so that flow and heat transfer are not consistently controlled or there is heavy fouling, there may be over- or under-processing or burning of product. Often factory-based industrial or large-scale processes will use stored or possibly pre-prepared ingredients to ensure that lines run smoothly and give consistent quality by minimizing stops and starts. In some process equipment, the specified time/temperature conditions are met by the main flow of material, but small amounts of material may accumulate in dead ends or a boundary layer and then return to the product flow after an extended residence time. These materials may cause product quality loss because they have had a longer residence time or are more heavily processed than the main flow. 6.5.1 Process flow The layout of the plant will determine the flow of materials and the movement of personnel, both key contributors to product quality and stability. Hence layout, staff training and operating procedures should be matched as closely as possible to the needs of the product design. The layout of process lines and storage areas needs to ensure that ingredients are available when needed, process conditions can be controlled and there are appropriate levels of hygiene. As a general rule, product flow should be `onward', so that materials from earlier and later stages of the process do not cross. This is essential to prevent cross-contamination and ensure that materials do not miss critical stages, e.g. heat treatment or different stages of processing (e.g., sterilized and unsterilized cans are mixed up). Measures to minimize the risks of cross-contamination, such as segregation in stores, should receive special attention if cross-contamination will lead to quality, shelf life or allergy problems. If areas surrounding processing, assembly and storage are used for storage of in-process material, these will also play a part in determining the risks of product contamination with out-of-date or spoiled material and hence influence quality loss during the shelf life.

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To minimize hygiene risks, plant layout and operation should ensure effective cleaning and clean-as-you-go with minimum disruption to production. Equipment design should be considered early on, because process equipment will provide sequence of temperatures and a range of flows and residence times (e.g., the main flow and the material left behind at each stage), and it is important to consider the effect of this on quality and microbiological changes. Excessive residual material can shorten shelf life by providing low quality material (e.g., burnt or dried material) or the precursors of quality change. Retained material will be most evident as tide-marks or fouling in equipment or debris in processing areas during operation or after cleaning. Therefore processing equipment should be designed and maintained to minimize the amount of material `heldup' and provide a narrow and predictable range of residence times for in-process material. To support this, process flows and layouts should be designed for ease of operation and provide good access for cleaning and maintenance. As part of the development process, machines should be examined before and after cleaning to identify areas where product is retained. 6.5.2 Manufacturing areas Wherever possible the layout, operation and hygiene of each manufacturing and storage area should be suitable for the products made. Key quality and performance indicators derived from the product design should be identified before manufacturing is started and used to show the level of hygiene needed. Some of the necessary hygiene and control measures will be covered by prerequisites, whilst others specific to a particular product will be noted in the HACCP plan as CCPs or QCPs. Stock control should ensure batch integrity and traceability for ingredients and process sessions to minimize risks of harming consumers, or the business, in the event of a process or material problem. Raw materials differ in their storage requirements, but all should be stored so that cross-contamination (e.g., with allergens), physical damage, premature spoilage and loss of processability are prevented. Maximum storage times and temperatures should be specified and controlled. Clear pack, or container, coding or labelling and a FIFO (first-in-first-out) stock usage system should be used to ensure materials are used within their quality and shelf life limits. If materials are unstable (e.g., contain high levels of unsaturated fats or undergo colour or texture change during storage), protective packaging that provides effective gas and moisture transfer barriers for both open and unopened packs should be used to maximize shelf life. For unpacked or bulk raw materials (e.g., raw vegetables), clean containers or conveyors are required to minimize damage and unwanted mixing or contamination during handling, sorting and storage. Where the primary packaging forms a part of the preservation system of perishable materials (e.g., aseptic bag-in-box), shorter storage times or refrigeration may be needed once packs have been opened. A factory may have a number of different controlled temperature areas for storage and processing ± ambient, chilled, 0±5 ëC or frozen, below ÿ12 ëC and

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ideally ÿ18 ëC. Chilled and frozen storage areas should have effective temperature control and monitoring, with high temperature alarm systems and sufficient capacity to maintain product temperatures when there are high outside temperatures or there is a peak demand for cooling (e.g., new warmer materials are brought in or doors are opened and closed frequently). Processing areas may be operated at ambient or chilled temperatures (about 12 ëC) and to different levels of hygiene (GMP, High Care, etc., see CFA, 2006). There may be separated areas for storing or processing materials with a known high microbiological or allergen risk. Prevention of re-contamination after products or ingredients have been decontaminated (e.g., by cooking) is a key requirement for perishable and readyto-eat products. Chilling, assembly and primary packaging after cooking needs to be carried out in higher hygiene filling/packing areas separated from the areas handling non-decontaminated materials. These specialized areas are known as High Care Areas (HCAs) or High Risk Areas (HRAs) and are constructed, laid out and operated to minimize the risks of product re-contamination from raw materials, food contact surfaces, air or personnel originating from the low risk (or GMP) areas. Air flow between these areas should always be from `clean' to `dirty', and any steam extraction hoods in cooking areas, which may separate high and low risk areas, should be designed and operated to ensure that condensation does not drop onto cooked products. HCAs and HRAs have stringent cleaning, disinfection and personnel handling systems to minimize or eliminate the chances of causing contamination. These precautions can extend to systems for circulation or recirculation of services such as cooling water and chilled air and container or packaging material handling systems (see CFA, 2006). Production scheduling and the intervals between cleaning and disinfection should prevent risky materials remaining in equipment, production and storage areas for periods that allow them to deteriorate before finding their way into product. If physical separation of the areas cannot be achieved, then cooked products should not be handled by personnel or equipment that has previously been in contact with uncooked or non-decontaminated material. Where single-door ovens or autoclaves (for sterilization) are used, there is an increased risk of cross-contamination or mix-up of processed and unprocessed products, because it is difficult to segregate pre- and post-process materials effectively. Layout and labelling should be used to minimize these risks and process sessions for products with different hygiene levels may be sequenced (decontaminated then non-decontaminated) or separated in time by an intervening clean. Where dry products such as soups or ready-meals are made, process and storage areas and equipment should operate `dry' (e.g., low humidity) to ensure that the materials remain dry and their quality does not change as a result of water uptake (e.g., by clumping; see Clark, 2009). Many materials need to remain dry so that they can be processed, mixed and filled without caking or clumping. As many of these products use raw, dried herbs and spices, etc. and are not pasteurized as part of their manufacturing procedure, it is important that

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processing equipment is operated hygienically and prevents microbial growth. To ensure good quality, special consideration should be paid to the retention and removal of caked, fatty materials from processing (e.g., mixing) and packing equipment where oxidative and browning reactions may occur in retained material. If water remains in equipment after cleaning, there is a high risk that any wet or semi-dry environments accidentally created will cause quality change (colour loss, rancidity or microbial growth).

6.6

Unit operations

Although the unit operations making up a process line can be described individually (see below), normally they are used in a sequence to provide the character and attributes of foods. The effectiveness of processes relies on the choice of suitable equipment and its reliable operation and maintenance, including control systems and hygiene. A single piece of equipment may include several unit operations (e.g., cooker extruders ± see http://www.extrutechinc.com/Extruders.htm) and some can be operated using different conditions to give distinctly different technologies (e.g., retorts can be used to make pasteurized or sterilized products, depending on the operating temperature). 6.6.1 Transfer and weighing of food materials and products Transfers between pieces of equipment can influence quality if they damage structure or retain food debris for uncontrolled periods of time. In simple, low capacity process lines, ingredients and products are often placed in trays or bins for transport or further processing. In complex or long production lines, conveyor belts or other automated transfer equipment (e.g., vibratory, screw or auger conveyors or pneumatic powder handling systems) may be used. Transport belts may be flat and made from fabric (e.g., http://www.conveyorsystems.co.uk/), plastic links (e.g., http://www.digwood.com/) or stainless steel (http://www.contibelt.com/PDFs/delivery_intl.pdf). Transport systems should be designed to give predictable movement of product (including at stops and starts), minimize product damage or losses, whilst being hygienic and cleanable. Specialized soft solid handling or pumping equipment (see http:// www.wildenpump.com/flyers/Saniflo_VC.pdf) is often used with cutters and mixers that minimize cell or particle damage (see http://www.urschel.com/ Model_GA_5c888e6823d941ed61ab58f.html). If transfer equipment is incorrectly chosen, aligned or set up, this can increase the quantity of product waste generated, so that even properly designed and operated cleaning systems will not be able to keep the system hygienic and prevent product contamination or pack soiling with spoiled product. Product and ingredient characteristics, such as stickiness and crumbliness, should be considered when transfer systems are designed, so that the generation of debris is minimized.

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6.6.2 Pumping and homogenization Pumps move liquid and slurry products with or without particles along processing lines (e.g., through continuous heat exchangers), between different unit operations (e.g., mixers) or through fillers into packs. The product/process design, type of material and quality requirements (e.g., particle integrity) will dictate the type of pump needed (e.g., positive displacement, centrifugal, lobe or triplex piston; see Singh and Heldman, 2008). If not used and controlled correctly, pumps can reduce product quality, by breaking down cell structures, reducing particles to a mush or breaking emulsions. If particle integrity is important, additional criteria relating to particle damage (e.g., particle size or hardness) should influence the choice of pump. Peristaltic or high pressure piston pumps generally cause the least structural damage. In lines including a heat exchanger or filler, the capability of a pump to provide consistent flow rates is very important for ensuring consistent quality and safety. The main pump determining the flow rate through heat exchangers is known as the metering pump, because it determines the residence time in the heating, holding and cooling stages. Sometimes consistent flow rates may be difficult to achieve if the viscosity thickener system changes with temperature and time. Where there are variations in the flow rate, these should be taken account of in the scheduled heat process (see Department of Health, 1994), and residence times may need to be lengthened. Before the results of commercial-scale trials are converted to final manufacturing specifications, operating experience must be used to confirm that equipment, for example, a pump can run at the required flow rates and specification for the run time required. Back pressure may be increased and heat transfer reduced by fouling in heat exchangers and such changes eventually limit run times. Fouling may promote quality change as severely over-processed or burnt material can be released from surfaces of heat exchangers and returned to the main product flow. Homogenizers and colloid mills are specialized types of high shear pumps or mixers used to disperse ingredients and disrupt or create food structures. They reduce particle or droplet size, often to less than one micrometer diameter, and can suspend these particles in a carrier liquid to form stable suspensions and emulsions (e.g., homogenized milk, margarines and mayonnaise; see http:// people.umass.edu/mcclemen/FoodEmulsions2008/Presentations(PDF)/ (5)Emulsion_Formation.pdf and http://www.niroinc.com/gea_liquid_ processing/VHP_design.asp). High pressure rotor/stator homogenizers, known as colloid mills or piston homogenizers (working at up to 1500 bar) may create emulsions by forcing suspensions through a very narrow tube or orifice at high pressure. In a high pressure homogenizer the dimensions of the exit orifice cause a large pressure drop leading to turbulence and strong shearing forces which are responsible for mixing the oil and water phases to form the emulsion. In a colloid mill, high shear mixing occurs in the area of the rotor tips. Emulsions are dispersions of one liquid in a second immiscible liquid, such as oil-in-water, and they are stable if the droplets formed cannot coalesce or sediment. They may

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have oil as the continuous phase and water as the discontinuous or dispersed phase (e.g., margarines) or the other way round (e.g., mayonnaise and salad dressings), where water is the continuous phase and oil (fat) the discontinuous phase. Such products may also have inclusions such as garlic and various herbs or spices. Emulsions are used to compartmentalize ingredients and structure products, and can preserve products by depriving microorganisms of water and nutrients and limiting the space available for growth (e.g., in small water droplets). The formation of emulsions gives a distinctive quality to products (e.g., mayonnaise or margarine) and differences in stability may alter the mouthfeel and flavour released from products. Emulsion stabilization is achieved by a range of interfacial agents, e.g. proteins including casein and whey protein isolate, polysorbates, lecithins and xanthan. Quality is also determined by the type of homogenizer and the interaction of its operating conditions with the continuous and dispersed phases and the emulsifier. Beverage emulsions include dairy-based drinks and many soft drinks, which are diluted emulsions. Because of their very high surface area, emulsions containing unsaturated fats or oils are usually protected by antioxidants. 6.6.3 Size reduction Size reduction has a major effect on quality characteristics, ingredient processing and quality change during storage. The macrostructure of foods (e.g., whole fruits or vegetables and muscles) will be damaged or destroyed by the cutting process and cells will also be damaged so that their contents are released. As part of processing, solid and particulate foods may be converted to smaller particles or powders by processes such as slicing, milling or mincing, which may be done to improve functionality, portion control or cooking characteristics. Equipment used includes dicers (e.g., for fruit, vegetables and bacon), slicers (e.g., for cooked meat), mincers (e.g., for beef or pork), shredders (e.g., for lettuce and carrot), finishers (e.g., for tomato paste), mills (e.g., for grains) and colloid mills (e.g., for mayonnaise). Cutting may be carried out using conventional metal blades or cutter discs in various configurations (see www.urschel.com) or water jets may be used. Cutting heads are dimensioned to produce particles of different sizes (e.g., potato flakes, coleslaw, and minced beef) and in some cases pastes (e.g., ketchup, mustard and peanut butter). In plant materials, wound and a number of other biochemical responses will be initiated (Myung et al., 2006; Saltveit, 1997) when their cellular structure is disrupted (Van Linden et al., 2008). These responses are often evident as browning reactions. The contents of cells may be released and smeared within the resulting matrix by cutting processes and this will increase the surface area exposed to oxygen and the rate of oxidative reactions. If animal fat is minced, proteins and fat will be released and smeared as a thin film (Allen and Foegeding, 1981). If the fat is unsaturated and a haem catalyst from muscle tissue is present, then the rate of rancidity development will be increased (Hansen et al., 2004a,b; Cheah and Ledward, 1997). The meat proteins released

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by cutting and mincing include myofibrillar and sarcoplasmic proteins and collagen. Each has different properties and functionality in product and they differ in their nutritional value, ability to bind water and fat and give stability and texture to raw and heat set products (Briskey and Wismer-Pedersen, 1961; Byrne, 1999; Mielche, 1993; Satyanarayan and Honikel, 1992, Kumar et al., 2007). 6.6.4 Mixing Mixing aims to distribute ingredients and additives uniformly throughout a product matrix and minimize damage to the product and any particulates or structures it contains. It may be achieved by continuous or batch mixers with high (see http://www.silverson.com/UK/Default.cfm) or low (see http:// www.admix.com/admixer_general.htm) shear mixing blades. Depending on the properties of the materials being mixed, and the product properties, mixer configurations may be vertical or horizontal. Variable quality and shelf life is caused by the uneven distribution of ingredients within unit packs or between packs. Mixing during heating and cooling is also important to ensure maximum rates of heat transfer and heat penetration. 6.6.5 Filtration and reverse osmosis In-line filtration is used in soft drink and juice production to stabilize and sterilize products, as it eliminates the adverse effects of heating on colour, quality and stability. Filtration and centrifugation are used to remove fine (haze) and larger particles that may sediment during storage. Relatively coarse filters are used for clarification, pre-filtration and the removal of particles and crystals (e.g., undissolved sugar) from the product stream (see http://www.millipore.com/ techpublications/tech1/ds5623en00). After clarification, cold sterilization can then be carried out using membrane-based filters to remove microorganisms from the product. In-line sterilization is usually performed at the pre-bottling/ filling stages and uses absolute filters (0.2 m or 0.45 m). But, these low porosity filters can reduce colour and bind proteins, which may eventually block them unless adequate pre-filtration procedures or aseptic post-dosing are used (see http://www.millipore.com/beverage/bv3/softdrinkchart and http:// www.millipore.com/beverage/bv3/bottledwaterchart). Ultra filtration and reverse osmosis Ultra filtration removes particles down to 0.001 microns from liquids; reverse osmosis (RO) additionally removes metal ions and soluble salts. Both are high pressure systems, where a pump is used to force the liquid through a membrane or filter pad, retaining the solutes on one side and allowing the purified liquid to pass to the other side. Pressures of up to 70 bar are used to force a liquid from an area of high solute concentration through a membrane to a lower pressure region of low solute concentration by applying a pressure in excess of the osmotic

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pressure, which may be up to 50 bar in a juice. Typical processes use a pretreatment filter to remove suspended solids (1±5 micron particles) and chemical treatment and pH balancing of the feedstock is used to prevent precipitation of carbonates, phosphates and sulphates. High hygiene standards are important when working with RO, to prevent fouling of membranes by microbial slime and reduce the risk of damage to high pressure (> 20 bar) pump components or production of contaminated material. RO is used commercially for concentrating food liquids (such as fruit or tomato juice; Petrotos et al., 1999) as an alternative to conventional heat treatments which cause damage to heat-sensitive substances like proteins and pigments. RO can be used to concentrate and remove protein and enzymes from fruit and vegetable juices, including wine, without heating. It is used in the dairy industry for the production of whey protein and milk concentrates. In whey production, liquid whey can be concentrated from 6% to 20% total solids before ultra filtration is used to make products such as isolates and lactose (see http://www.lenntech.com/nanofiltration-and-rosmosis.htm and http://www.geafiltration.com/applications/food_beverage_applications.asp). RO membranes may be spiral wound or hollow fibre and are contained in pressure vessels or tubes and have to be strong enough to withstand the pump pressure (see http://www.gewater.com/products/equipment/mf_uf_mbr/uf.jsp and http:// www.dow.com/PublishedLiterature/dh_0274/0901b803802744c6.pdf?filepath= liquidseps/pdfs/noreg/795-00022.pdf&fromPage=GetDoc). 6.6.6 Preservation technology The most widely used method for preserving food products is `hurdle technology' which combines processing and packaging technologies, with chemical factors, to make a series of hurdles that the target microorganisms cannot overcome to grow or survive (Leistner, 2000; Leistner and Gould, 2003). Intrinsic factors (Table 6.1) can be used alone to prevent or delay the unwanted changes caused by microorganisms (e.g., souring or spoilage), but lead to obviously preserved products. Multiple, less obvious hurdles are necessary because no single factor has been shown to be completely effective from both a product preservation and consumer quality point of view. Typical combinations of factors are: · fruit juice which is acidified, pasteurized, aseptically packed and ambient or chill stored · meat may be mildly cured, pasteurized and vacuum or modified atmosphere packaged · pasteurized sauces (acidity, heating and hot or aseptic filling) · tomatoes are preserved by acidification and in-pack heating (canned tomatoes) and osmotic concentration (tomato paste) resulting from high temperature evaporation of water under vacuum and hot filling or aseptic packaging. Sometimes lower levels of concentration are combined with chill storage to give a milder and fresher product (a w about 0.70; Apaiah and Barringer, 2007)

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· cheeses (reduced water activity, natural acidification and chilled storage) · yoghurt (either natural starters and acidification with chill storage or acidification by lactic starters followed by pasteurization and chilled storage) · salamis (drying and acidification by fermentation) · heat-processed, cured meat products (heating, addition of nitrite, water activity modification and sometimes addition of lactate preservatives). Many of these hurdles exert significant effects on quality and impart unique flavours or textures (e.g., gelderse rookwurst; Zeuthen and Bùgh-Sùrensen, 2003). For some products, the timing and sequence of process steps is important for creating effective hurdles (e.g., SSPs; Leistner, 2000). The most commonly used chemicals in hurdle technology are the organic acids (e.g., acetic, sorbic, benzoic and propionic) and their salts such as sodium lactate (Devliegher et al., 2000). Sorbic acid is used to preserve syrups, salads and some cakes, benzoic acid is used for beverages and margarine, propionic acid is an ingredient of bread and bakery products. Sulphur dioxide is also used for dried fruits and juice concentrates. Non-thermal treatments (e.g. ultrahigh pressure (UHP); see Hendrickx and Knorr, 2002) are less commonly used as hurdles. Beverages may be carbonated with gaseous CO2 to give sparkling drinks or to give cans structural strength. High concentrations of CO2 and reduced pH inhibit the growth of aerobic microorganisms (Molin, 2000) in beverages. Carbonation can occur naturally during fermentation or carbon dioxide can be added under pressure to make carbonated beverages including soft drinks and beer. Quality and taste are affected by the amount of dissolved CO2 and the concentration of dissolved carbonic acid which depends on pH. Specialized carbonation equipment is used for dosing or injecting with CO2 and controls in soft drink and beer production are based on measuring CO2 and/or O2 levels (see http:// www.niroinc.com/gea_liquid_processing/carbonated_beverages_systems.asp).

6.7

Production of low and intermediate moisture foods

Typical dried foods are dry snacks, cereal and dairy products, vegetables, soups and instant drinks, pasta, powders and cubes, and semi-moist foods, such as cheese, pet food and salami. Water activity plays a major part in determining both quality change and microbial growth or survival. The water activity (aW) indicates the amount of free water available for microbial growth and quality change; it is not the water content. However, moisture content is often used as the routine control parameter for aW, based on the link between absorption or desorption isotherms linking aw and moisture content. Water activities below about 0.6 are needed to prevent microbial growth, at these aw levels the rate of quality change is slowed; but if aw is reduced further to below about 0.2 (e.g., whole milk powder containing 2±3% moisture or dried vegetables with approximately 5% moisture), reactions such as rancidity and browning may speed up. Drying is used to produce low aW levels below about 0.75 and the addition of agents such as salt (saturated salt solution aw = 0.75) and sugar

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(minimum about 0.8) can also be used. In addition to influencing microbial spoilage, modification of water activity can alter the rates and relative rates of texture, colour, taste, and aroma change. It plays a significant role in determining enzyme activity, loss of vitamins and non-enzymatic browning and rancidity/lipid oxidation reactions (Labuza et al., 1971). Therefore if a product design specifies a certain water activity, the aim of processing should be to provide it accurately and uniformly within the product, too rapid drying will cause case hardening and leave the centre too moist. Drying rate and the conditions used for drying and making products often reflect diffusion coefficients or ease with which water can reach and then leave surfaces. This in turn depends on how it is bound or held (e.g., cellular structure) within the product. Changes in moisture content during storage are often controlled by using packaging that provides an effective moisture barrier. Moisture uptake during storage causes quality change in dry foods with water activities below 0.7 (e.g., nuts or powders or dry compounded products such as soups) and some also lose functionality (crispness, cohesion or caking). Other foods are affected by moisture loss (e.g., meat, fish (surface desiccation) and vegetables (wilting or loss of turgor)). Drying processes range from freeze drying at low pressures (e.g., 0.06 bar) and temperatures ÿ30 to ÿ50 ëC (which are determined by the critical temperature of the material and the need to minimize quality defects) up to ambient or high temperature atmospheric, evaporative (>50 ëC) or vacuum drying, sometimes assisted by microwaves. When heating is used to assist drying, it may cause irreversible changes to vitamins and loss of volatile flavours and aromas. Many different types of continuous and batch equipment are used, spray dryers and heated drums or belts. Dryers are normally used at high or low temperatures that prevent the growth of, or to kill, microorganisms, and conditions are usually a compromise between preventing quality damage to the product from high temperature processing (e.g., burning or surface desiccation) and minimizing the time to reach the target aW (e.g., time available for chemical and microbiological reactions to occur). An exception to this is the production of potato and vegetable crisps by deep frying (see http://www.hyfoma.com/en/content/ food-branches-processing-manufacturing/fruit-vegetable-potato/potato/crisps/). The addition of glycerol, sorbitol, sugar and salt, is used to produce semimoist or intermediate moisture foods (IMF) which have a soft texture and 15± 30% moisture content with aw levels from 0.65 to 0.90. They are preserved because the humectants or water-binding substances, such as sugar and salt, restrict the amount of water available for microbial growth and during processing some water may also be removed by drying. Typical foods are dried beef, peaches and apricots. There are many IMF pet foods. To formulate IMF products, direct measurements of aw are needed because the effectiveness of combinations of humectants cannot be calculated reliably. The effectiveness of IMF preservation can be increased by the addition of organic acids. (See also http://www.fao.org/docrep/005/Y4358E/y4358e07.htm for information on the preparation of stable intermediate or high moisture fruits.) They receive a pasteurization treatment and have an aw of 0.94±0.98 and low pH 3.0±4.1. They

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contain preservatives (e.g., citric acid and potassium sorbate) and an antibrowning agent (sodium bisulphite) to provide colour stability. The stability of IMF foods relies on packaging providing effective oxygen and water barriers. Clear or opaque fruit syrups (e.g., cassis and peach) are low aw products made from concentrated fruit juice. They are often ambient stable because of a high concentration of sugar and solutes (50±70%) and a low pH (<4). Syrups with aw levels down to 0.85 may spoil by the growth of fungi, producing heatresistant spores, e.g. Byssochlamys fulva (ValõÂk and PieckovaÂ, 2001).

6.8

Thermal processing

All types of food material and filled packs may be heated during processing to cook and preserve them. This has led to the development of many different types of equipment (see Fig. 6.2), with common features designed to achieve · particular levels of heat transfer to the product either directly (contact with a heated surface or microwaves) or indirectly (using a heat transfer medium) · known temperatures in the product · a consistent, narrow range of residence times. Product heating is determined by the type of equipment and temperatures used and the material being heated. Unique combinations of process conditions and heating characteristics give products their distinctive quality or character and stability (e.g., chill or ambient stable). With all heating processes, the conditions needed for a specified heat treatment (see below) will involve higher temperatures and longer times than the intended heat treatment. These are the process conditions and depend on the equipment used; similar heat treatments may be achieved by different combinations of process times and heating temperatures. A temperature difference is needed to cause heat transfer from equipment or heating medium to the product. This is described by the `F value' (the time in minutes required for the difference between equipment temperature and food temperature to decrease or increase by a factor of ten) ± see also the associated definitions for F value http://www.iftps.org/pdf/nomenclature_6_04.pdf and http://www.iftps.org/protocols.html). Also when foods heat or cool in containers, there is often a time lag in the temperature change (j) which can be defined as the time taken from the assumed initial temperature of the container for the temperature change (heating) to become linear; and a similar lag also exists during the cooling phase. As a result, cooking continues within a pack after heating has stopped and cooling has started. The effect of this extra heating on quality should be taken into account when heating processes are designed, especially for large packs or large vessels (see Yang and Rao, 1998). In practice, many techniques are used to optimize heat processing or develop particular quality characteristics: these include designing containers with short thermal paths (rather than conventional circular cans) or developing heaters (grills, kettles, fryers) with particular characteristics, e.g. for searing or branding

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products or heat exchanger configurations that increase mixing or turbulence, minimize the thermal path and maximize heat transfer (e.g., shell and tube, scraped surface or annular). Defined minimum heat treatments are relatively easy to achieve in solids and liquids with uniform heating characteristics, but in composite products with several components (e.g., muscle and bone), or in liquids containing particulates, it is more difficult to ensure the minimum heat treatments without over-processing. For microbiological purposes the heat treatment is based on the coldest spot within the product, which may or may not be its geometric centre, but to optimize quality overall heating needs to be considered. For example thick burgers (5 cm) cannot be cooked to the centre on a barbeque before the outside is burnt. Process conditions must take account of heat transfer from the heat exchange surface to the material. If particles are heated in a carrier fluid, heat is transferred to the carrier liquid and then from it to the particles giving slower rates of heat transfer into the particles. Hence carrier fluids can be over-processed before particles are adequately heated, leading to loss of quality and especially colour and texture. Setting processes is complicated when there are different rates of heat transfer and heat penetration and this often leads to using severe process conditions, to ensure a minimum heat treatment at the slowest heating location. The microbiological effects of heat treatments are described in terms of lethality: `D' which represents the decimal reduction time (e.g., the time required for a one log cycle reduction in a specified microbial population) and `z' which represents the temperature coefficient of microbial destruction, linking time and temperature models describing microbial lethality. Different reference temperatures (Tref) and kinetics (z) are used to describe and compare pasteurization, sterilization and quality change processes (cook value C): · pasteurization: Pvalue ˆ t . 10(TÿTref)/z, when Tref ˆ 85 ëC and z ˆ 10 Cë or · sterilization: Fo value ˆ t . 10(TÿTref)/z, when Tref ˆ 121.1 ëC and z ˆ 10 Cë. · quality: Cvalue ˆ t . 10(TÿTref)/z, e.g. Tref ˆ 100 ëC and z ˆ 30±50 Cë. It is important to realize that quality changes in a product are often determined by more than one reaction and overall quality changes in response to a process (e.g., texture change, enzyme inactivation or vitamin degradation) will be determined by the integration of many reactions with different z values; in contrast microbial lethality is based on a single effect at the coldest point. Therefore to be meaningful cook values need to reflect what has happened to key quality reactions in the `whole' pack or product (see Awuah et al., 2007). The difference in z values between microorganisms (typically 10 ëC) and food quality change (typically 30±50 ëC) has allowed processors to increase microbial lethality by using higher temperatures (e.g., UHT c. 140 ëC) and reduce the effects on quality. This is possible because for a process temperature rise of 20 Cë, lethal rates for microorganisms are increased 100-fold, whereas quality change is only affected 10-fold or less. UHT processes are used to optimize the quality of dairy and other products, but have the disadvantage that some enzymes (e.g., lipases) are not inactivated by high temperature/short time

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processes because they have very large zC values (up to 50 Cë) and therefore the very short times possible to give microbial inactivation cause only small reductions in enzyme activity (see Lewis and Heppell, 2001; Tucker and Holdsworth, 1991a,b; Richardson, 2004). After any heating process, cooling should be rapid enough to stop both heatrelated quality changes and, if the product is to be chill stored, prevent the growth or outgrowth of any spores surviving processing or introduced as contaminants (see http://www.eastriding.gov.uk/corp docs/foodservices/ Food_Advice_Notes/food_services advice_28.pdf). For ambient stable products a `quality safe' (low) temperature is often considered to be below 50 ëC and this should be achieved before products are packed (e.g., aseptic packaging) or product units are palletized and put into store. 6.8.1 Other effects of heating Heating or cooling may cause phase transitions in response to temperature (e.g., temperature rise can cause water to change to steam and create pressure within a sealed pack and chilling can cause condensation on packaging; substantial temperature drops can cause solidification or freezing). Hence phase transitions may have major effects on the choice of equipment and packaging and also on quality (e.g., phase change in fats, expansion of foams or freeze damage to fruits and vegetables; Reid, 1997). Product volume may change during processing (e.g., water changing to steam or ice) or plastic packaging may become brittle. Phase changes may uncouple temperature changes from heat input, and the most important practical effect occurs when frozen ingredients are heated and additional heat is needed to overcome the latent heat of fusion before temperature can rise. If sealed packs are heated above about 60 ëC, then counterpressure around the pack, or venting systems in the pack are needed to prevent distortion and bursting. For sterilization at temperatures in the range 110±145 ëC pressure vessels (e.g., retorts) are used for processing sealed packs and for continuous heat exchangers back-pressure retaining devices are used to prevent boiling (e.g., valves) http://straval.com/catlist-back-pressure-regulators/bps-09?size_id=209. 6.8.2 Heating mechanisms Products can be heated by three mechanisms (and cooled by only conduction and convection). Different types of heating impart different quality characteristics. Heating from the outside by conduction is often used to give desirable surface characteristics (e.g., fried or grilled food), but it can also produce undesirable characteristics (e.g., over-processing of conduction heating packs during sterilization, if the thermal path is long e.g. large cans ± A10). Equipment for direct heating includes steam injection vessels, skillets and microwave ovens. Indirect heating equipment, where heat is transferred by an intermediate heating medium, includes retorts, heat exchangers, fryers and water baths.

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Conduction Solids are often heated and cooled by conduction and heat flows from hotter to cooler areas, progressively heating or cooling the product. This involves direct contact between the product and a surface (e.g., griddle) or indirect contact with heating media (e.g., hot oil in frying). During cooking, surfaces and corners will be hotter for longer than the inside, and the outside may be burnt. Product quality will vary from the centre to the outside and this may be part of the product character. Where the foods are thin or viscous liquids, heated by conduction, it is possible to reduce the range of qualities by mixing; but with solids the range of qualities can only be reduced by reducing the length of the thermal gradients (e.g., by making smaller particles or packs). For packaged products, the conduction properties of the packaging material itself may slow the rate of heating depending on its thermal conductivity. Some liquid products may have thermal conductivities like water, but stable porous, emulsified, foam or dry materials (e.g., powders) will have lower conductivities. Convection Materials heated by convection (e.g., thin liquids) will heat more quickly than conduction heating materials (solids or particles). Longer times will be needed if these materials are heated in large diameter packs or in heat exchangers with a long thermal path, than when there are small distances or diameters involved. In convection heated products (e.g., non-viscous liquids, soups and sauces or vegetables in brine), the heat transferred to the product or pack surface moves within it more rapidly than by conduction, because heated material moves away from the heat exchanger surface, mixes and carries energy into the product. In more viscous products this effect can be accentuated by mixing (e.g., forced or induced circulation). Hence heating equipment is often designed to accelerate heating by promoting mixing, for example retorts may rotate packs. Liquid products may be pumped through continuous heat exchangers at velocities that cause turbulence and minimize resistance to heat transfer. Static mixers are also used to do this (see http://www.koflo.com/). Convection heating can minimize the cook values given by a heat treatment, and also gives a narrower range of qualities because of mixing. During heating some materials, especially starchy ones may change their heating characteristics. In the initial phase of heating these materials follow the kinetics of convection heating, then gelling takes place and the later stages of heating and cooling follow the kinetics of conduction (see Berry and Bush, 1987). Such materials are said to have broken heating curves (see http://www.iftps.org/pdf/nomenclature_6_04.pdf). Radiation Radiation heating occurs when heat is transferred to the product by electromagnetic waves. For food products, infrared or microwave radiation frequencies of 900 or 2450 MHz are normally used. If heating is carried out using microwaves or ohmic heating, it is said to be volumetric, and heating throughout the product because it can be relatively uniform (see http://www.industrial

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microwave.com/foodprocessing.htm) as energy is absorbed by all the material (dielectric heating) and heat exchange is not limited to the surface. Therefore heating rate is not limited by pack or particle size and uniformity of quality can be greatly improved. However, this potential improvement may not be realized because hot and cold spots will still exist depending on the dielectric properties and geometry of the materials or packs being heated (Sarang et al., 2007). The depth of penetration of microwave heating is a function of frequency (higher frequency shallower penetration, so commercial ovens work at 900 MHz). After microwave heating and absorption, the flow of heat within the product continues by conduction or convection, driven by product temperature and internal temperature differences. 6.8.3 Pre-fill and post-fill heating Products may be heated prior to sealing in their primary packaging (pre-fill heating) or in-pack (post-fill heating). These two approaches require different technologies and facilities as shown in Fig. 6.2 and carry different risks of quality change and product contamination. Pre-fill heating Materials are heated before they are placed in their primary packaging and this may be for a number of reasons: · to give sensory characteristics, e.g. grilled surfaces, or reduced water content · to reduce viscosity and allow materials to flow for filling, portioning or placing into packs · to drive off unwanted volatiles (such as the smell of brassicas), re-hydrate dry ingredients or speed up acid or flavour penetration · to inactivate enzymes and microorganisms · to achieve a pre-determined temperature (e.g., Tih) for post-fill cooking, filling or sterilization · sterilization and cooling in continuous heat exchangers for downstream aseptic packaging. Rates of heating and the process temperatures used exert a critical effect on quality. Batch equipment for heating includes kettles, blanchers and fryers (see http://www.jbtfoodtech.com/Solutions/Processes/Frying-and-Filtration.aspx) and griddles. From a quality point of view, heating in tanks gives variable quality because the total heating or hot holding time varies between the first and last product out of the tank; hence the range of qualities depends on the capacity of the vessel and its discharge rate. However, batch heating can give good control of minimum holding times and provide traceability, but may lead to quality loss by over-cooking (e.g., softening of vegetables). Batch heating tanks or kettles require good mixing to aid the transfer of heat and keep particles in suspension, but vigorous mixing may entrain air in the product and promote oxidation, and batch equipment is labour intensive to run. Continuous blanchers,

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Different types of pre- and post-fill heating.

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ovens and fryers give good overall control of residence times, determined by the belt speed. Pre-fill heating is often carried out with the product in contact with air, which can promote quality change by oxidation or reduction in water content; but it may also be carried out under vacuum (see http://www.giusti.co.uk/) to limit contact with oxygen. Solids may be heated in batch or continuous ovens or frying equipment, or in brat pans and this type of heating also increases risks of oxidative change, as the product is not separated from air. Frying may be carried out under a gas blanket ± http://www.linde.com/international/web/lg/us/ likelgus30.nsf/repositorybyalias/us_food/$file/Linde%20Treating%20Food %20Better%20Brochure.pdf). Similarly, liquid and pumpable products heated in continuous heat exchangers (see http://www.alfalaval.com/about-us/our-company/key-technologies/heattransfer/pages/heat-transfer.aspx) are effectively isolated from air during heating and this is similar to post-fill heating, where the packaging provides a barrier (e.g., vacuumized packs) or reduces the availability of oxygen (e.g., packs with a small air headspace or a modified atmosphere of nitrogen or carbon dioxide). To reduce the risks of oxidation, products may also be deaerated before or during heating (see http://www.hrs-spiratube.com/en/products/processing-systemsdeaeration-system.aspx). During frying the product surface is cooked and dehydrated (see Boskou and Elmadfa, 1999). Fried product quality depends on ingredients and frying oil quality and temperature. Generally fryer oils are formulated to resist oxidation. This limits the levels of unsaturated fat in them and they are often predominantly palm oil, supplemented with antioxidants (e.g., tocopherols or ascorbyl palmitate) to increase stability during use and storage, but most will eventually degrade (Lalas, 2008). During frying, products are subject to both thermal and oxidative stress, because during cooking, water in the product is heated and expands as it is converted to steam, which is transferred to the heating oil and may be replaced in the product by oil (some products may pick up 25% of their weight). To maintain the quality of oil, and hence products, oil is generally filtered to remove particles of product storage (see http://www.allbusiness.com/ business-finance/leasing-equipment-leasing/615559-1.html) and losses replaced with fresh oil. Fryers may be heated by either electricity or gas or by other heating media (see http://www.jbtfoodtech.com/Solutions/Equipment/~/media/ JBT%20FoodTech/Files/Stein%20Brochures/TFF%20CoolHEAT.ashx). Continuous heating and cooling in plate or tubular heat exchangers is used because it can give more uniform heat treatments and faster heating than batch heating. From a quality perspective it can give lower cook values and better retention of volatiles. Continuous heat exchangers have many different configurations and capacities and can be used for liquids and liquids containing particles to give very consistent heat treatments (e.g., see http://www.gowcb.com/ products/heatex/ssheatx.asp; http://www.hrs-spiratube.com/en/default.aspx; http://www.apv.com/us/products/heatexchangers/Heat+exchangers.asp; http:// www.foodsci.uoguelph.ca/dairyedu/uht.html). They are designed and constructed according to the general scheme shown in Fig. 6.3.

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Fig. 6.3

Design and construction scheme for continuous heat exchangers.

The main stages all affect quality. Pre-heating provides a flow of material with known quality and flow characteristics and an assured minimum initial temperature (Tih). The heating-up stage raises the product to its sterilization temperature at the coldest point in the product flow (typically to > 130 ëC) from the minimum Tih. This product enters the holding section, where there is no further heating and the flow rate from the metering pump provides a specified minimum holding time at the sterilization temperature. For calculating process lethality, the sterilization temperature is defined as the temperature on exit from the holding section and therefore may be 1 or 2 Cë below the exit temperature from the heating section. Lastly the cooling section provides a defined exit temperature of <45 ëC. Continuous heat exchanger systems require a constant flow of product and flow stoppages lead to burning of product in the heating-up stage and other adverse effects on quality. There should be a means to `dump' or divert under-processed product before it enters the cooling stages and contaminates previously sterilized product (see Kuppan, 2000; http://www02.abb.com/ GLOBAL/SEITP/seitp161.nsf/viewunid/37F17470012AAB31C1256 BFE0032DF09/$file/Pasteurization+Control+Systems.pdf). Any variability in heat exchanger and pump performance and control responses must be specified in the scheduled process as they determine the effectiveness of sterilization, hence choice of pump, control and product divert system can have a major effect on quality. Usually for processing a similar volume of product, continuous systems have a lower energy demand and may provide opportunities for heat recovery (regenerative cooling). Cleaning is more difficult, usually based on CIP (clean-in-place) and creates more waste than with batch systems (see Georgiadis et al., 2000). Two methods of heating are used by continuous heat exchangers: · Indirect ± where the product flows over heated surfaces, often stainless steel, which separate the product from the heat transfer medium. See http:// www.alfalaval.com/solution-finder/products/Pages/default.aspx; http:// www.gea-phe.com/themes/products/product-lines/; http://www.gowcb.com/ products/heatex/ssheatx.asp). This type of heating can give gradual temperature rises and the volume of product is not increased by absorption of the heat transfer medium (condensing steam). · Direct ± where high pressure, culinary steam is pumped directly into the product flow. This steam condenses in the product, transferring its heat and

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also increasing product volume (see http://www.goldpeg.com/about_us/ profile.htm and http://www.pickheaters.com/). Indirect heat exchangers are generally designed with large surface areas for heat exchange and short thermal paths. To aid the diffusion of heat, the product flow can be mixed by using static mixers (e.g., www.chemineer.com) or rotating blades or scrapers (e.g., Contherm scraped surface heat exchangers ± see http:// www.alfalaval.com/solution-finder/products/contherm-scraped-surface-heatexchanger-sshe/Pages/Contherm-Scraped-Surface-Heat-Exchanger(SSHE).aspx). Stirred systems may cause particle damage, and changes in product texture, appearance and colour. Continuous heating processes can cause a number of quality defects, especially over-cooking. If pre-heating stages provide product at a low temperature, heating-up conditions will become more severe because a greater temperature rise is needed and hence product may burn on the heat exchanger surfaces. Fouling by burnt-on product will in turn reduce heat transfer and cause further product burning and fouling. Slow cooling or failure to cool sterilized product to below 45±50 ëC will allow cooking to continue, leading to over-cooking and quality loss after packaging. Steam injection processes can accelerate quality change and especially colour loss due to the very high local temperatures when uncondensed steam is in contact with product (up to 140+ ëC). In addition, the rapid temperature rise achievable by steam injection (seconds) can limit the extent of heat diffusion into particles during heating and the temperature rise at the particle centre usually continues after the heating section has been passed (see Zhang and Fryer, 1995). Hence there is continuing debate about the definition of the holding tube in equipment processing particles, because it is necessary that any particles are completely temperature equilibrated before the holding time and the calculation of the lethal effect begin. Aseptic packaging A wide range of equipment and layouts is used to aseptically pack products which have been sterilized in continuous heat exchangers (see http:// www.foodengineeringmag.com/Articles/Feature_Article/BNP_GUID_9-52006_A_10000000000000029252). The storage, handling/forming and decontamination of primary packaging material (card laminate reels for Tetra briks, card laminate sleeves for Combi machines and plastic cuplets for Gasti machines) is generally done by hydrogen peroxide or heated hydrogen peroxide vapour before material enters the sterile zone of the packaging machine (see http://www.solvaychemicals.us/static/wma/pdf/1/3/5/6/8/3424H2O2ASEPTIC_Pkg.pdf). The effectiveness of this sterilization (normally a 5log reduction) exerts a major effect on the risks of producing contaminated product and must ensure specified maximum rates of product failure (e.g., 1:10,000 packs) are not exceeded. All operations involving primary packaging prior to sterilization (including storage) must be carried out in clean (especially dust-free) environments to minimize challenges to the chemical systems (e.g.,

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hydrogen peroxide) used for pack decontamination. The presence of dust or grease on the surface of packaging material or loss of activity in the sterilant will reduce the decontamination effect. Similarly the hygiene and management of post-process stages must minimize the chances of pack damage and product contamination. Post-fill or in-pack heating Post-fill heating of sealed packs such as cans, pouches or jars can be performed in batch (batch retorts ± see http://www.allpax.com/products/water-immersionretorts/) or continuous heating equipment (see http://www.sepak.com.au/images/ Tunnal%20Pasteurizer%20brochure%202009.pdf and http://www.steritech. eu.com/fr/nos-produits/cop/). Heating processes may include an element of cooking for the development of flavours, colours and textures, for softening of vegetables or meat or gelling starches. But its main purpose is to preserve the product by killing vegetative microbial cells and spores within the pack. Hence the accuracy of filling or dosing and assurance that seals are bacteria-tight are critical (see Section 6.9) to ensure consistent thermal processing and preventing re-contamination of the sterilized product. When processes are chosen for inpack heating, attention has to be paid to the components of the heating and cooling times. Time is taken for the equipment (e.g., retort or pasteurizing vessel) and product or pack (e.g., can, jar or pouch) to achieve the target temperature (sometimes called the come-up time) and then after the holding, or cook time at this temperature, the time taken to cool to a temperature stopping quality change. For large packs, the come-up time contributes significantly to the overall heat process and its contribution will be larger for packs which change temperature slowly or are processed at low temperatures (see http:// www.nzifst.org.nz/unitoperations/httrtheory2.htm). For example: · To achieve a heat treatment of 70 ëC  2 minutes at the coldest point in a 250 g `flat' pack may involve heating for 30 minutes or more, leading to quality loss. · Products such as cooked meats and paÃteÂs are prepared and cooked as larger blocks (5 kg) in water baths or ovens at 70 ëC to a low centre temperatures (c. 66 ëC) to minimize losses and develop texture. This combination of temperatures may give cooking times of 5±6 hours. · To achieve FO of 5±8 at the centre of a 500 ml can, an overall retort process time of 40±60 minutes is required and this will include exposing the surface of the pack to >123±126 ëC for about 40 minutes. Batch equipment includes vertical or horizontal retorts and pasteurizers using steam, water spray or water immersion for heat transfer, and packs can be held static or rotated to improve heat transfer. There are also continuous retorts (e.g., reel and spiral) (http://files.asme.org/ASMEORG/Communities/History/ Landmarks/5491.pdf) or hydrostats (http://findarticles.com/p/articles/mi_m3289/ is_n11_v159/ai_9099480/) and continuous, over-pressured pasteurizers (see www.steritech.eu.com). Tunnel pasteurizers are used for packaged products

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(e.g., canned beverages or liquid sauces in jars) and have typical transit times of up to an hour through the heating, holding (about 20 minutes at 60±70 ëC) and cooling sections. Process temperatures may be monitored by transit monitors (e.g., Ecklund±Harrison; Redpost PU-Monitor) (http://www.haffmans.nl/ purification/redpost.php), which travel with the product through the tunnel. The sensors of these RTDs (remote temperature devices) are placed at the cold spot of product containers and heating and cooling are recorded. Product temperatures are used to calculate `pasteurization units' (PUs). These descriptions of the heat treatment use 60 ëC as a reference temperature and a z value of 6.9 Cë. Typical PU values are 15±50, depending on the microbial load of the product. Heating equipment is usually controlled automatically and detailed records need to be kept to verify the process conditions for each batch. The main characteristics of retorts are shown in Table 6.3. Control of over-pressure is needed in vessels heating sealed packs to temperatures above about 60 ëC, because this temperature rise causes significant overpressures leading to volume changes which stretch the packaging. Failure to control temperature-linked volume changes will have a major effect on quality if it alters pack geometry and increases headspace volume, reducing heat transfer and the effective heat treatment. Pack distortion may also damage seals and cause loss of seal integrity (see http://www.retorts.com/white-papers/pouch-processing/) and barrier properties. Monitors are available to measure pack over-pressures (see http://www.ellab.com/Products/Validation/TrackSense_Pro.aspx). Where a laminated structure, including an inflexible aluminium layer is used in flexible pouch construction, pack distortion during heating can split this oxygen barrier layer (stress cracking) and allow the ingress of oxygen during storage. 6.8.4 Blanching Blanching with hot (85±100 ëC) water, brine or steam is used to inactivate the enzymes (e.g., polyphenol oxidase, catalase and peroxidise; MuÈftuÈgil, 2006) in fruits and vegetables. Blanching times and temperatures affect quality (Bourne, 1987); if treatments are too severe, they may accelerate quality losses during storage (e.g., development of toughness and colour or flavour changes). If they are too mild enzyme activity may persist (see Wichers and Boeriu, 2004). When the more heat-resistant enzymes, such as peroxidise, are inactivated by blanching processes, it is likely that other enzymes causing quality change will also be inactivated. Under some circumstances enzymes may regenerate their activity, and this can occur when there has been marginal heating under conditions that maximize enzyme stability (e.g., neutral pH). Chemical tests for the effectiveness of blanching are based on the detection of residual levels of heat resistant enzymes such as peroxidase in blanched material (see http:// www.fao.org/docrep/V5030E/V5030E0q.htm). Blanching is generally performed on a large scale (tonnes/h) using batch (kettles) or continuous equipment soon after harvesting, washing and inspection and prior to deep freezing, or chilled product manufacture. Efficient energy use

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Table 6.3

The main characteristics of different types of retort

Retort type

Investment cost

Operating costs

Throughput

Control

Flexibility

Average FO for target FO5

Cook value

Particle damage

Batch static

Medium

Low

Low

Complex

Very

Very high

Very high

Low

Batch rotary

Medium

Medium

Medium

Complex

Pack size limited

Medium

High

Medium

Continuous

High

Low

High

Easy

Can size limited

High

Very high

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is a prime consideration in blancher design and operation. Although blanchers usually have automated systems to control water or steam temperature, product feed rate and residence time (e.g., belt or auger speed) and are run at pasteurizing temperatures, they are not usually used to produce microbiologically safe (pasteurized) products, because process conditions are not designed to ensure minimum heating in all parts of the product flow. During heating of fruit and vegetables, for example during the manufacture of tomato paste, water-insoluble pectins can be hydrolysed to water-soluble pectin (Krall and McFeeters, 1998). Tenderness or softness develops as the cells separate and soluble pectins form colloidal suspensions, which thicken the juice of tomato products during cooking. On the other hand, fruits and vegetables also contain pectin methyl esterase, which is released from damaged cells and hydrolyses pectin so that it does not form gels. Tomato products contain both pectin and pectin methyl esterase and, if freshly produced tomato juice and paste are stored, viscosity gradually decreases because of the action of this enzyme on gelled pectin. Thinning can be prevented if tomato products are quickly heated (blanched) to above 82 ëC (`hot-break process', Chong et al., 2009; see http:// www.jbtfoodtech.com/Solutions/Processes/~/media/JBT%20FoodTech/Images/ Modules/Tomato%20Processing/PDF/1401%20GB_LRRGB.ashx). Heating during the hot break process deactivates pectin methyl esterase before it has a chance to hydrolyse the pectin; therefore hot-break processes yield high viscosity tomato products (see http://www.cybosoft.com/pdf/ATS_1_Hotbreak.pdf). For low viscosity products, cold-break processes are used and the enzyme activity is allowed to continue. To firm fruits and vegetables, if they are softened by processing, the reaction between soluble pectins and calcium ions is used to form calcium pectates which increase structural rigidity. Thus, low levels of calcium salts may be added to tomatoes, apples and other vegetables and fruits prior to canning or freezing; to firm up texture (Mafuleka et al., 1991). Rapid cooling immediately after blanching is needed to prevent unwanted softening. Cooling sections must be hygienic to prevent recontamination of the flow of blanched material with microorganisms and over-heated material, which has been retained in the equipment for prolonged periods of time. The development of microbial biofilms in the cooling stages can re-contaminate product and may re-introduce enzymes of microbial origin. Therefore the cooling, handling or packaging equipment used after blanching should be hygienically designed and managed to cause minimum hold-up of material (http://www.fao.org/docrep/v5030e/ v5030e0q.htm). For good quality, vegetables for freezing can be air cooled on a fluidized bed, but normally cooling is carried out in water either in fumes fed with chilled water (4±15 ëC) or by sprays. Water cooling is normally followed by de-watering. To minimize quality change, vegetable core temperatures should reach 37±40 ëC as soon as possible after blanching. Natural cooling (e.g., in boxes stacked on pallets) is a slow process and causes significant losses of colour and vitamin C.

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6.8.5 Cooking Cooking describes all the heat-related activities used to give food ingredients the characteristics of a finished, cooked product. For many processed products, the cooking to give an optimum product will be less severe than the heating needed for · pasteurization (coldest point temperatures from 65 to about 100 ëC which are used to eliminate vegetative microorganisms) or · sterilization (temperatures 110 to about 140 ëC) to eliminate all microorganisms and spores). Cooking equipment may be batch or continuous and includes: · · · ·

surface cookers, such as griddles; immersion cookers such as fryers (see Gupta et al., 2004) kettles for liquids, sauces and stews (see http://www.giusti.co.uk/) containment cookers such as ovens for baking (www.sveba-dahlen.se) or roasting (www.formcook.com).

Cookers may also be very specialized, e.g. vacuum cookers running under vacuum (620 torr at 98 ëC) to dry or concentrate products or pasta cookers. In any process making products for storage, the amount of heat used will be determined predominantly by product storage temperature (e.g., ambient or chill), shelf life and any additional preservation system present, such as reduced pH or water activity. Minimum heat treatments must effectively prevent spoilage, provide safe products and in some cases, ensure compliance with local legislation (e.g., milk pasteurization or sterilization of low acid foods). If the amount of heating needed to do this is less than is needed for quality reasons, then good quality products can be made; if it is more, then quality is likely to be reduced. Product quality and stability will be determined by the performance of cookers, their design and operating capability (see http://www.jbtfoodtech.com/ Solutions/Processes/Cooking.aspx) and the materials being processed. The interaction of food and equipment is a key determinant of product quality and character. Cooking may cause quality changes in some meat products (see www.meatscience.org). Cooking temperatures range from about 60 ëC for sous vide cooking (see http://amath.colorado.edu/~baldwind/sous-vide.html; http:// www.unifiedbrands.net/) up to air temperatures of 280 ëC used in jet sweep ovens (http://www.middleby.com/pdf/mm/4106.pdf) and similar temperatures for the surfaces of griddles. 6.8.6 Pasteurization Pasteurization describes a range of relatively mild heat treatments (up to about 100 ëC), which are designed to eliminate vegetative microbial cells and in acidified products (e.g., tomato products with a pH < 4.1) to injure or inactivate bacterial spores so that they cannot outgrow at pH levels below about 4.2. These mild processes may not cook products. Pasteurization treatments may be

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classified on the basis of temperature and residence time which vary depending on the product and the target organism: · Low temperature pasteurization (long temperature, long time ± LTLT) ± 60±70 ëC for periods of 30±45 minutes (e.g., egg products 54 ëC for 45 minutes). Low temperature pasteurization also includes sous-vide processes (see http://www.edinformatics.com/math_science/science_of_cooking/ what_is_sous_vide_cooking.htm). · High temperature pasteurization (higher temperature shorter time ± HTST) >70±100 ëC (e.g., milk pasteurization at 72 ëC for 15 seconds). Some products such as apple juice with pH below 4.0 receive a thermal process (72 ëC for 6 seconds) to cause a 5-log reduction in oocysts of Cryptosporidium parvum, because this parasite is believed to be more heat resistant than E. coli O157:H7 (see http://foodsafety.cas.psu.edu/apples/haccp/Past_ Parameters.htm). · Ultra pasteurization (UP) temperatures around or >135 ëC for 3±5 seconds are used for acidic fruit juices. · Ultra-high-temperature pasteurization (UHTP) ± the heat treatment is 138± 150 ëC for 1 or 2 seconds, followed by aseptic packaging. The process is used for acidic (pH below 4.2) milk or cream to give long storage times (up to 90 days) without refrigeration. After heating, products may then be hot filled (temperatures generally about 80 ëC) directly into containers (e.g., glass jars or plastic pouches) or aseptically packed, after cooling (maximum temperature at packing 45 ëC) under aseptic conditions into clean or pre-sterilized containers (e.g., cardboard bricks or plastic cuplets). The precautions taken to prevent re-contamination will depend on the product pH (low acid pH above 4.6 ˆ aseptic packaging; acidified products below pH 4.6 ˆ high hygiene or aseptic packaging), the type of product and the subsequent storage conditions (chilled or ambient storage). 6.8.7 Sterilization Sterilization is achieved by using combinations of time and temperature (usually between 110 and 130 ëC in retorts and 130 and 145 ëC in UHT continuous flow heat exchangers) to eliminate a defined number of heat-resistant microbial spores. The minimum heat treatments used in canning are designed to reduce numbers of spores of Clostridium botulinum by 12 logs (12D process: 3 minutes at 121.1 ëC or FO = 3) and are used for foods with pH values above 4.6 (low acid foods). Generally to ensure microbiological stability of foods, more severe processes are used (FO ˆ 5±8) and with many foods these cause a loss of quality or the development of very distinctive colour and texture characteristics. Transfer of heat into the pack results in a very heavy over-processing of material at the outside for a target heat process of FO ˆ 8, material at the surface may experience FO values in excess of 100. This has a big impact on quality and leads to the formation of pronounced quality gradients within packs of solid

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products. These gradients are much less pronounced in liquid packs where there is circulation of the liquid. For sterilized products, maintenance of the `initial' or starting temperature for sterilization is a key consideration for kitchen and process design and vessel (batch) sizing, to prevent uncontrolled, excessive cooking before sterilization (e.g., temperatures about 70 ëC) or if it is set too low (e.g., room temperature), then sterilization conditions may have to be increased and this also causes quality loss. 6.8.8 Chilling and freezing Chillers and freezers are designed either to cool or freeze materials (blast, spiral or tunnel chillers) or to maintain pre-cooled material at chilled or frozen temperatures (e.g., between 1 and 5 ëC, or ÿ12 to ÿ20 ëC) see http:// www.food.gov.uk/multimedia/pdfs/tempcontrolguideuk.pdf. Chilled storage temperatures (0 ëC and 7 ëC) do not halt, but only slow, quality changes caused by microbial activity. Neither chilling nor freezing will completely stop chemical and biochemical reactions and these will ultimately limit product shelf life. Chillers may be an integral part of processing in high hygiene areas (HCA or HRA). They should be able to reduce product temperatures from the process temperature (70±>90 ëC) to about 3±5 ëC in 90 minutes or so, but cooling rates depend on interaction between the equipment and the product units or product flow being cooled. Minimum cooling rates should be at least fast enough to prevent the outgrowth of any spores present after heat processing. Blast chillers should be designed to cool without re-contaminating material; often they will receive `naked' product and so their design and hygiene measures should ensure that food contact surfaces (e.g., belts and racks) remain free of contaminants. Freezers reduce or maintain temperatures below the freezing point of food. Freezing rates are determined by the quantity and temperature of the heat transfer medium, its contact with the product and the thermal path within the product. Heat transfer characteristics and the rate of freezing of packaged products will be affected by the insulating effects of packaging. In addition blast freezers may produce low quality product due to slow freezing if they are overloaded or undersized and some product shapes may allow excessive air to by-pass the product surfaces, leading to slow freezing. Freezing reduces the level of free (unfrozen) water present (low aw) and so will slow (or stop) microbial metabolism, but freezing does not kill microorganisms. This reduction in the level of unfrozen water accelerates the rate of some quality change reactions by concentrating soluble components. The best quality is usually achieved by using the fastest possible freezing rates and steady storage temperatures (Redmond et al., 2004). At fast freezing rates freeze concentration and cell damage are minimized and solutes are trapped within the ice crystals. Freezing rate determines whether ice crystals form inside or outside cells, and this will determine the extent of cell damage to cell walls and the proportion of intact cells. Temperature fluctuations mechanically destroy the structure of

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cellular materials by causing cyclic growth and thawing of ice crystals. Cellular damage causes a loss of texture and the release of intracellular materials, including enzymes and fats, which promote quality loss. Where high air velocities are used for freezing naked product, such as fish fillets, there is a risk of surface dehydration and this may lead to colour loss (freezer burn) and other oxidative changes which, once initiated, continue during storage. Slow freezing and temperature fluctuations during storage will drive sublimation and concentrate reactants and catalysts in the remaining unfrozen water, which dehydrates intact cells and increases reaction rates (Rahman, 1999). It may also change the configuration of proteins and break emulsions. Primary packaging with a minimum headspace can be used to reduce these effects. Some products may be physically damaged by handling in belt freezers, leading to poor appearance. Heat may be removed from products either by convection (air and cryogen cooling) or by conduction (belt freezers or mixer freezers). Equipment for freezing product can use a variety of agents for either direct or indirect freezing. Blast freezers use very cold air as the freezing medium (mechanical refrigeration, air typically ÿ20 to ÿ40 ëC). This air is in direct contact with the product or pack, which is transported by belts in a spiral or straight configuration or as a fluidized bed for small particles (such as broccoli florets). IQF freezers (for freezing individual items like pepper slices or florets) may use liquid nitrogen (ÿ190 ëC) or CO2 as the freezing agent (cryogenic freezing); these systems can produce very rapid freezing and high quality, reducing losses by evaporation during the freezing process. Products may also be contact frozen (indirectly) by plates, belts or other heat exchange surfaces (e.g., scraped surface heat exchangers). Often the choice of freezer will be determined by production volume demands and the type of material to be frozen. Vegetables are often frozen using fluidized bed tunnel freezers; poultry, meat and prepared, packaged foods are frozen on trays or directly on belts using spiral freezers. Solid stainless steel belt and drum freezers can be used for moist, soft moulded or extruded products, such as fish fillets. 6.8.9 Thawing It is usually necessary to thaw frozen ingredients and products, with the exception of ice-cream and frozen confectionary before further processing or consumption. Frozen raw materials are usually thawed before heat processing to ensure consistent heating times and also ensure that unfrozen ingredients are not over-processed. To retain quality, thawing should be carried out as fast as possible, if material being thawed is packaged, for example in cartons, then thawing rates will be reduced. Thawing is most rapid when there is direct contact of the heat transfer medium (air or water) with the product surface, but when naked product is handled special attention should be paid to hygiene and the temperature of the heat transfer medium. Thawing temperatures should not exceed 20 ëC, higher temperature thawing in hot air ovens or water baths

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(40±60 ëC), may reduce the quality of some materials (e.g., bell peppers) and can lead to texture, loss and possible growth of spoilage microorganisms and pathogens. If materials are to be cut, minced or flaked then their temperature during processing exerts a major effect on the type of particle and the distribution of particle sizes produced; generally the lower the temperature, especially below freezing, the smaller the particle size produced. Thawing can be speeded up by minimizing the thermal path within the product (40 mm or so maximum). More recently commercial scale equipment using microwaves (915 or 2450 MHz) and radio frequency radiation in cabinets or tunnels has become available and this allows deep frozen foods to be tempered (to about ÿ10 ëC from ÿ20 ëC) or defrosted (ÿ2 to ÿ3 ëC) uniformly in a few minutes. If overhigh power levels are used then run-away heating can occur with some parts of the materials being cooked or burnt.

6.9

Filling and packaging

Many types of filler are available and they may often include pack sealing, capping or closing mechanisms. Choice will be determined by the line speed required and the type of fill (e.g., liquid, viscous and with or without particulates) and the type, shape and weight of the pack and its type of closure. Different products may present different problems to filling and closing equipment (e.g., weight or volume variation, the degree of splashing or dripping during filling, product viscosity and particles) and lead to differences in performance. Fillers may be single or multistage and use either vacuum, auger, piston or overflow filling heads in a rotary, multi-head or in-line (intermittent motion) configuration. Control of the quantity filled can be either volumetric or by weight. Some fillers may be linked to closing or sealing machines that close or complete the pack and may add a modified headspace atmosphere containing a mixture of gases such as CO2 or nitrogen to preserve the product. Metal tops or bases may be seamed onto cans or plastic packs and pouches may be induction or heat sealed. Where hot filling is the preferred option, control of minimum temperatures after filling and temperature drop during any stoppages are critical to safety and quality. If product is supplied to filling heads by pipe work, it is necessary to ensure that there are neither unacceptable temperatures, leading to temperatures within the growth range of microorganisms or hold-up of material. Recirculation loops returning product to heated tanks or vessels may be used to prevent this, but their hygiene must be carefully monitored. When packs are filled for in-pack pasteurization or sterilization, consistent dosing plays a major role in ensuring that heating characteristics, weight and headspace are uniform. If pack dimensions or fill quantity are variable, then quality loss may be caused by over- or under-processing.

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6.9.1 Primary packaging Most food products are sold packaged. Primary packaging is often in direct contact with the product and must ensure that it is protected from contamination with microorganisms. This depends on good sealing, mechanical integrity of the pack (e.g., the absence of breaks or holes in the packaging material and seal imperfections), and on resistance of packs to physical damage, which can lead to contamination with microorganisms. Packaging materials coming into direct contact with food must not contaminate it chemically and there is legislation governing the materials that may be used for food contact packaging (see http:// www.kunststoffverpackungen.de/08_pressemitteilung/news/040616_ReferatBruder.pdf). Key pack properties include: · · · · · · · · ·

shape stability in use consistent dimensions stability after manufacture or forming to allow clean filling chemical and UV resistance and exclusion barrier properties (e.g., oxygen, CO2 and water vapour) reliable interaction with filling and closing equipment (machinability) freedom from pin holes and other defects toughness and rigidity to protect the product food product resistance to prevent staining.

Many products rely on their particular packaging to achieve their expected shelf life and this may be a major factor in the selection of a packaging material, for example if moisture and oxygen barrier properties are required or if aseptic packaging is used with UHT processing (see www.tetrapak.com, http:// www.sig-group.com/site/en/kartonpackung/Kartonpackung.jsp; http:// www.oystar.gasti.de/dogaseptic.html). If foods are intended for a long storage life, then the properties of the packaging material, especially barrier properties, must be retained over the shelf life (e.g., to prevent oxidative changes or fat staining in long shelf life ambient packs). In some cases the type (and cost) of barrier materials can be adjusted depending on the shelf life required (e.g., 6 weeks or 6 months). Whatever packaging material is used, the expected shelf life will be dependent on the integrity of the package seal to maintain the atmosphere and moisture level within the package (beyond any expected gas transmission across the packaging film) for the designed shelf life. Packaging material may also determine the response of a pack to processing; if packs are made of an unsuitable material, have an incorrect headspace volume or weakened seals are processed in retorts or ovens, burst or weakened packs may result. Some products designed for extended chilled storage (e.g., chilled meats) rely on the modified atmosphere surrounding the product forming part of the preservation system (e.g., vacuum, low PO2, high PN2 and CO2; see http:// www.eufic.org/page/en/faqid/what-is-modified-atmosphere-packaging-map/). Packs for microwave or oven heating carry very different temperature and migration risks to packs used for the distribution of chilled products, as they will

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be subjected to different temperature conditions during use and must be tested for suitability. 6.9.2 Secondary packaging It is essential that the secondary packaging protects the primary pack from damage during palletization, transport and storage. Secondary packaging may also contribute to limiting quality change during storage, for example cardboard sleeves may limit light contact with products in transparent pouches or trays lidded with clear film. Rigid overwrapping may prevent texture change due to particle breakage.

6.10

Novel processes

6.10.1 Ohmic, impedence or inductive heating During ohmic heating, an electric current is passed either continuously, or intermittently, through the foodstuff. In principle, this gives rapid and uniform heating, because unlike conventional in-pack heating (where heat is transferred from the surface into the pack by conduction and/or convection), there is no thermal gradient across the pack (see http://ohioline.osu.edu/fse-fact/0004.html). Usually liquid foods (e.g., liquids including soups, stews, fish, vegetable and fruit particles, up to 2.5 cm across, in liquid and sauces) are pumped through a pipe system past electrodes and volumetric heating occurs because the food has an electrical resistance (Samaranayake et al., 2005). Ohmic heating causes a temperature rise in the product, cooking occurs and microorganisms are killed predictably by heat. In practice, there are difficulties in reliably identifying the coldest or slowest heating spot in the pack and hence the process conditions needed to give a minimum heat treatment can be severe and in multi-component foods, some components may heat faster than others. Because of this uncertainty, extended holding times are used to allow temperature equilibration within the product and therefore the quality benefits of milder processing may be lost (see Fryer and De Alwis, 1989). Additionally quality assurance procedures have been designed to ensure that electrical conductivity of all components is controlled reliably, specific control procedures may be needed (e.g., presoaking) and has to be monitored to measure the ionic content of ingredients. 6.10.2 Pressure-assisted thermal sterilization (PATS) of food This technology combines mild heat with high pressure (138±483 MPa for 5±20 min at 25±70 ëC) to produce commercially sterile low-acid food products. Product is preheated to a specified temperature (50+ ëC) and then is pressurized to raise its temperature to above 121 ëC which is maintained throughout the pressure stage. When pressure is released, the product returns to the preheat temperature. Because of the short cycle times, loss of quality attributable to

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heating and cooling times is reduced. Research from the US Army Natick Soldier Systems Centre (NSSC) (http://www.natick.army.mil/soldier/media/fact/ food/HPP.htm) has found that the quality of these foods was better than that of traditional retorted foods. The effectiveness of the technology has been validated by NCFST researchers (see http://www.ncfst.iit.edu/pdfdocs/PressRelease PATSLACF.pdf for details of a recent FDA LACF process filing). Very little other work has been done on quality benefits, although the milder process conditions used offer the potential for improved quality. The killing mechanism is thought to involve either pressure-induced germination of spores, which results in 2- to 5-log reductions of resistant bacilli, alternatively the thermal expansion of liquids may cause structural damage to spores (see http:// researchspace.auckland.ac.nz/handle/2292/5294). This mechanism may also damage cellular food materials, but some authors consider it may preserve quality (see http://fshn.illinois.edu/food_processing_forum/presentations/ c1_Bala_astract.pdf). 6.10.3 Pulsed electric fields Pulsed electric field (PEF) processing is another non-thermal method for decontaminating liquid (grape juice: MarselleÂs-Fontanet, 2009 and http:// www.foodscience.csiro.au/pef-technology.htm) and semi-liquid food products (see Altunakar et al., 2007). It uses short pulses of electricity (20±80 kV for >1 microsecond) to inactivate vegetative microorganisms (e.g., > 5-log reduction of Saccharomyces, Lactobacilli, etc.) by creating or enlarging pores in their cell membranes (see Barbosa-CaÂnovas et al., 1999). Because heat is not involved, it is said to cause minimal changes in food quality (see http://ohioline.osu.edu/fsefact/0002.html). It may be used in combination or sequence with mild heating and its effects are changed by the properties of the food (Kristina and RoÈnner, 2001). At present it is predominantly used for acidic liquids and fruit juices. Application is limited to liquids free of gas bubbles, because bubbles allow electric arcing between the electrodes, burning the material being processed and potentially generating unwanted materials. Sanchez-Vega et al. (2009) compared the effect of UHT and PEF treatments on enzyme inactivation and quality of apple juice. They found that UHT treatment was more effective at inactivating enzymes than PEF treatment, but that the sensory quality of PEF processed juice was higher after processing. In a simulated skim milk, very severe PEF treatments had to be used to inactivate a microbial lipase, and the maximum reduction in activity was 62% (Soliva-Fortuny et al., 2006). Results indicate that enzymes are more resistant to PEF than microorganisms and it is not clear whether levels of enzyme inactivation are high enough to ensure high quality during storage. 6.10.4 Microwave and radio frequency processing Microwave and radio frequency heating use electromagnetic radiation (900±2450 MHz; see http://www.worldscibooks.com/etextbook/4763/4763_chap01.pdf) to

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heat food and water (Ramaswamy and Tang, 2008). This type of heating can be used for thawing, cooking, re-heating and pasteurization. Because heating is volumetric, these processes can take less time to heat solid and semi-solid foods than conventional methods (Fu, 2004). The interaction of the equipment, magnetron, product composition and pack shape and size can dramatically influence the location and temperature of the coldest point and hence the process time needed for a heat treatment. This uncertainty coupled with the complexity of energy absorption and heat transfer makes it difficult to design and specify the process conditions needed for a product and the means of handling process deviations. Many techniques have been tried to improve the uniformity of heating. Microwave sterilization has to be carried out in water-filled retorts, where heating is indirect because most microwave energy is absorbed by the immersion water, but this indirect method of heating is claimed to have the advantage that the energy distribution in the vessel can be tailored to the product and pack distribution to achieve more uniform quality. Although industrial and pilot microwave pasteurization and sterilization systems have been available for many years, with claims for improved quality, commercial systems are not known to be in use. 6.10.5 Irradiation ± pasteurization and sterilization Much information is available about food irradiation by gamma rays, X-rays and high energy electron beams (http://www.iaea.org/programmes/nafa/d5/public/ foodirradiation.pdf), but there is considerable consumer opposition to its use (see http://www.irradiation.info/). UV and electron beams have been used to reduce surface contamination on meat products and ionizing radiation has been used to pasteurize or sterilize pork rolls and chops (Shults et al., 1998). During exposure to ionizing radiation, the food absorbs energy (absorbed dose) and this causes the formation of free (or hydroxyl) radicals, which kill microorganisms, but can also interact with other food molecules and accelerate quality change in fatty materials by initiating rancidity. Hence it is not suitable for use with products containing unsaturated fats, where quality change is also caused by free radical reactions. However, some foods (e.g., poultry, red meat, spices, and fruits and vegetables) have been pasteurized by gamma rays, X-rays and electron beams to increase their storage life (Lund et al., 2005). 6.10.6 Ultra high pressure (UHP) treatment High pressure (HP) or ultra high pressure (UHP) processing involves applying 5000±11 000 bar pressure to a food to decontaminate (pasteurize) it and can be used much like heat. It destroys only vegetative microorganisms including pathogens and spoilage bacteria (He et al., 2002) but it is not effective at killing microbial spores (Patterson, 2005; Margosch et al., 2006). UHP denatures proteins in a manner similarly to heat (Balny and Masson, 1993) and can damage cell membranes (Luscher et al., 2005). It can slow biochemical and

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enzymatic reactions, by inactivating enzymes (Hendrickx et al., 1998). It can also unfold protein chains, by disrupting hydrophobic and ion-pair bonds, whereas the off-flavours formed by denaturation of proteins by heat result from the formation or destruction of covalent bonds. Foods, such as juices, salsas and other moist foods, can be decontaminated without affecting heat labile vitamins and flavours. Commercial equipment operates at pressures up to about 600 bar and causes about 5-log reduction of vegetative cells: see Avure Technologies ± http://www.avure.com/food/default.asp. Foods are treated by placing them in a liquid medium (usually water) within a thick-walled pressure vessel and compressing the medium. Treatment may be performed either by · heating at constant volume (adiabatic) or · compression at constant temperature (isothermal) conditions. Batch equipment can process products in bulk bags or consumer packs (see http://www.avure.com/archive/documents/Food-products/qfp_215l-eu-may2007.pdf). Semi-continuous equipment can be used for pumpable products followed by aseptic packaging. If food is air-free and contains water, the hydrostatic pressure does not crush the texture, because the water in the food protects it from physical damage. In 2009 applications of UHP cover a range of foods ± ready-to-eat meats, oysters (He et al., 2002), juices (orange, apple, tomato; see Deliza et al., 2005), fruit (melon; Wolbang et al., 2008); and guava (Yen and Lin, 1996) and prepared salads and dips (see http://www.fst.ohio-state.edu/1108feat_preserving foods.pdf). Commercial processes exist for guacamole (see http:// www.avure.com/pdf/Guacamole.pdf). Pressure treatment of non-pasteurized citrus juice results in no loss of vitamin C and extends the shelf life. See http:// www.hpp.vt.edu/references%5CHPPReferencesA.pdf for a list of references on the use of UHP. UHP may also alter the texture of proteins, and milk proteins may be coagulated without acidification or the use of rennet and gels of varying strengths were formed depending on hold time and the rate of ramping up and down of pressure (Pereda et al., 2007). UHP treatments have been used to process fruit and vegetables (Butz et al., 2003), but they accelerate browning in some foods. UHP treatment gave microbiologically stable single-strength tomato juice with improved viscosity and colour properties in comparison with conventional heat-processed juice (Poretta et al., 1995), but there was less enzyme inactivation than with conventional hot-break treatment; and UHP processing gave higher n-hexanal and cis-3-hexenal levels (from FFA oxidation) than heat processing. Pulsed light Pulsed light is a surface irradiation technology which uses very intense and short flashes of light in the UV to NIR range from xenon discharge lamps. This light affects only the surface of the material being treated and so it is only useful for killing surface contaminants or for clear liquids processed as a very thin film.

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Experimental work has shown it can reduce numbers of vegetative microorganisms (9-log) and bacterial spores (7-log) on smooth, non-porous surfaces, such as packaging materials, but if the surfaces are rougher, as in the case of foods, effectiveness is reduced to 2- to 3-logs (see http://www.fda.gov/Food/ ScienceResearch/ResearchAreas/SafePracticesforFoodProcesses/ucm103058.htm). Pulsed light treatment can be effective in extending the shelf life of a variety of foods, but despite its approval for surface decontamination by the US FDA, pulsed light is not yet commercially used (see http://www.embeddedstar.com/ press/content/2002/9/embedded5062.html and http://www.steribeam.com/), mostly due to the lack of knowledge regarding the critical factors that influence effectiveness and lack of knowledge of the mechanism of inactivation.

6.11

Hygiene

To ensure food quality and stability during storage, the cleaning and hygienic design of equipment need to prevent re-contamination of the main product flow with food debris remaining from previous processing sessions, because these will initiate quality changes or cause quality loss, for example if there are strong flavourings or allergens in a previous batch (Hayes, 1995). Hygienic design should keep material in the main product flow and minimize the range of residence times. Food debris may deteriorate if it remains in equipment (e.g., spoil, oxidize, desiccate or burn) or is retained adjacent to areas of high temperature (e.g., motors, etc.) which will accelerate rates of deterioration. To prevent this, equipment should not have dead ends or low spots to trap food and should be self draining. Construction materials (see http://www.ehedg.org/ uploads/DOC_08_E_2004.pdf) and maintenance should ensure that the food materials are not retained in cracks or corroded areas or absorbed into plastics. Under their anticipated operating conditions, product contact materials must be inert and not absorb either product or any detergents or disinfectants used (see Council Directive 89/109/EEC of 21 December 1988 relating to materials and articles intended to come into contact with foodstuffs). Hence processing and hygiene form an interconnected system that must be managed to ensure quality and limit quality change. If equipment cleaning does not remove residual material there may also be an adverse effect on equipment performance (e.g., a reduction in heat transfer by heat exchangers caused by fouling or ineffective sealing by sealing heads: see http://www.food-info.net/uk/eng/docs/doc8.htm). Cleaning between batches and product sequencing should prevent intermixing of different products and allergen or flavour contamination which could result from a product change-over. Optimum sequences of production should ensure that down time and the chances of contamination are minimized and product wastage is minimized. If successive products are very similar, full cleaning may not be necessary, and rinsing or scraping down between batches may be effective. The effectiveness of cleaning will be reduced if operatives need to prevent the wetting of sensitive parts of machines (e.g., electronic

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controls), which may be rendered inoperative by water penetration, especially if high-pressure cleaning is used. Hence an integral part of the hygienic design of machines is good access for cleaning and inspection and effective waterproofing of controls and sensors.

6.12

Future trends

Future trends in processing will focus on preserving quality, reducing conversion costs and meeting consumer expectations for fresher, more natural foods. This could lead to the wider use of integrated systems for ingredient sourcing, processing, including non-thermal technologies, and packaging to ensure product quality and stability and meet consumer wishes that food should be fresh and not over-packaged. Extended shelf life will be an issue in the developed world, as there is still distrust by consumers of foods that remain stable for longer periods than expected. However, pressure to reduce travel for shop visits and ensure that logistic chains are fully utilized will counter this pressure, and technology and formulations providing increased stability will gradually become accepted. In the undeveloped world `appropriate' technology will be developed to reduce food wastage through inadequate storage, processing, preservation and packaging. New and existing process technologies will focus on ensuring better nutrient retention, stability with lower levels of preservatives (such as synthetic antioxidants) and the capability to process novel ingredients (see USDA; Center for Food Safety and Applied Nutrition, 2000). Currently, the most widely used technology, thermal processing, provides high levels of microbiological stability, but tends to reduce the quality of foods. Often this occurs because there is poor process control and insufficient understanding of the underlying mechanisms of heating by developers. Freezing and frozen food distribution will continue to be used to retain nutrient quality and overcome seasonality in supply. Wider use will come from preventing unwanted reactions and especially texture changes during storage. The freezing process itself consumes high amounts of energy and more energy efficient techniques will be sought. Chilled foods offer quality and convenience but require highly complex hygienic areas for manufacture and energy intensive logistics systems to cope with their short shelf life, but continue to find favour with consumers. Many of the non-thermal technologies will continue to have a limited scope of application because of their limitations (e.g., their ability to penetrate food materials) and poor knowledge of their mechanisms and possible interactions which may reduce their effectiveness. There is only limited availability of equipment for commercial-scale production and current equipment cannot yet produce commercial volumes and products that command a premium price that would justify investment. There is always a risk of adverse consumer risk± benefit perception of non-conventional processing (e.g., ionizing radiation) which increases commercial risk. UHP treatment is attractive from a product

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quality point of view, but its application is currently limited to pasteurization processes, limiting it to low pH and chilled products. Similarly PEF can be used for non-thermal inactivation, but in common with microwave and ohmic heating, it requires complex control and fluid handling systems with extensive routine ingredient characterization. More realistically, advances in quality are likely to come from the development of predictive models for the interactions between microorganisms, quality, materials and process conditions during conventional processing. This will lead to the better use of the synergies, including natural ingredients, in hurdle technology. The development of functional foods is a challenge to processing, because current processes and process management systems cannot ensure that any beneficial compounds found in raw materials remain active after processing, or at consumption, because the impact of commercial processing on these compounds is largely unknown. Consumer acceptance of any new process is likely to be increased if consumer benefits are accepted, but this is likely to be a difficult process as there is an information gap between food technologists, marketers and consumers and activists.

6.13

References and further reading

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enzymes in foods. In Preservation of Foods with Pulsed Electric Fields. Eds. Barbosa-CaÂnovas, G.V., GoÂngora-Nieto, M.M., Pothakamury, U.R. and Swanson, B.G. Elsevier, Amsterdam. BERRY, M.R. JR. and BUSH, R.C. (1987) Establishing thermal processes for products with broken-heating curves from data taken at other retort and initial temperatures. Journal of Food Science 52, 4, 958±961. BOROWSKA, J., KOWALSKA, M., CZAPLICKI, S. and ZADERNOWSKI, R. (2003) Effect of hydrothermal processing on carrot carotenoid changes and interactions with dietary fiber. Nahrung 47, 1, 46±48. BOSKOU, D. and ELMADFA, I. (1999) Frying of Food: Oxidation, Nutrient and Non-nutrient Antioxidants, Biologically Active Compounds and High Temperatures. CRC Press, Boca Raton, FL. BOURNE, M.C. (1987) Effect of blanch temperature on kinetics of thermal softening of carrots and green beans. Journal of Food Science 52, 3, 667±668. BRISKEY, E.J. and WISMER-PEDERSEN, J. (1961) Biochemistry of pork muscle structure. I. Rate of anaerobic glycolysis and temperature change versus the apparent structure of muscle tissue. Journal of Food Science 26, 297±305. Â NDEZ GARCIÂA, A., LINDAUER, R., DIETERICH, S., BOGNA Â R, A. and TAUSCHER, B.J. BUTZ, P., FERNA (2003) Influence of ultra high pressure processing on fruit and vegetable products. Journal of Food Engineering 56, 2±3, 233±236. BYRNE, D.V. (1999) Development of a sensory vocabulary for warmed-over flavour: Part ii. In chicken meat. Journal of Sensory Studies 14, 1, 67±78. CACACE, D., PALMIERI, L., PIRONE, G., MASI, G.D.P. and CAVELLA, S. (1994) Biological validation of mathematical modelling of the thermal processing of particulate foods: the influence of heat transfer coefficient determination. Journal of Food Engineering 23, 1, 51±68. CERF, O., DAVEY, K.R. and SADOUDI, A.K. (1996) Thermal inactivation of bacteria ± a new predictive model for the combined effect of three environmental factors: temperature, pH and water activity. Food Research International 29, 3±4, 219± 226. CFA (2006) Best Practice Guidelines for the Production of Chilled Foods, 4th edn. CHANDARANA, D.I., GAVIN A. (III) and WHEATON, F.W. (1990) Particle/fluid interface heat transfer under UHT conditions at low particle/fluid relative velocities. Journal of Food Process Engineering 13, 3, 191±206. CHEAH, P.B. and LEDWARD, D.A. (1997) Catalytic mechanism of lipid oxidation following high pressure treatment in pork fat and meat. Journal of Food Science 62, 6, 1135± 1139. CHONG H.H., SIMSEK, S. and REUHS, B.L. (2009) Analysis of cell-wall pectin from hot and cold break tomato preparations. Food Research International 42, 7, 770±772. CLARK, P.J. (2009) Dry mixing. In Case Studies in Food Engineering. Springer, New York. COPPOLA, S., MAURIELLO, G., APONTE, M., MOSCHETTI, G. and VILLANI, F. (2000) Microbial succession during ripening of Naples-type salami, a southern Italian fermented sausage. Meat Science 56, 4, 321±329. COROLLER, L., LEGUERINEL, I., METTLER, E., SAVY, N. and MAFART, P. (2006) General model based on two mixed Weibull distributions of bacterial resistance, for describing various shapes of inactivation aurves. Applied Environmental Microbiology 72, 10, 6493±6502. COX, P.W. and FRYER, P.J. (2002) Heat transfer to foods: modelling and validation. Journal of Thermal Science 11, 4, 320±330.

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and BEAN, P.G. (1977) Method for the immobilization of bacterial spores in alginate gel. Lab Pract. 26, 773±775. DATTA, A.K. and TEIXEIRA, A.A. (1988) Numerically predicted transient temperature and viscosity profiles during natural convection heating of canned liquid food. Journal of Food Science 53, 1, 191±195. DE KOCK, S., MINNAAR, A., BERRY, D. and TAYLOR, J.R.N. (1995) The effect of freezing rate on the quality of cellular and non-cellular par-cooked starchy convenience foods. Food Science and Technology 28, 1, 87±95. DELIZA, R., ROSENTHAL, R.A., ABADIO, F.B.D., SILVA, H.O.S. and CASTILLO, C. (2005) Application of high pressure technology in the fruit juice processing: benefits perceived by consumers. Journal of Food Engineering 67, 1±2, 241±246. DEPARTMENT OF HEALTH (1994) Guidelines for the Safe Production of Heat Preserved Foods. HMSO, London. DEVLIEGHER, F., GEERAERD, A.H, VERSYCK, K.J., BERNAERT, H, VAN IMPE, J.F. and DEBEVERE, J. (2000) Shelf life of modified atmosphere packed cooked meat products: addition of Na-lactate as a fourth shelf life determinative factor in a model and product validation. International Journal of Food Microbiology 58, 1±2, 93±106. EVANS, G.C. and RANKEN, M.D. (2007) Fat cooking losses from non-emulsified meat products. International Journal of Food Science and Technology 10, 1, 63±71. FAO (1998) Food Quality and Safety Systems ± A Training Manual on Food Hygiene and the Hazard Analysis and Critical Control Point (HACCP) System. FAO, Rome. FARAG, K.W., DUGGAN, E., MORGAN, D.J., CRONIN, D.A. and LYNG, J.G. (2009) A comparison of conventional and radio frequency defrosting of lean beef meats: effects on water binding characteristics. Meat Science 83, 2, 278±284. FESSAS, D. and SCHIRALDI, A. (2000) Starch gelatinization kinetics in bread dough. DSC investigations on `simulated' baking processes. Journal of Thermal Analysis and Calorimetry 61, 2, 411±423. FRYER, P. and DE ALWIS, A. (1989) Validation of the APV ohmic heating process (APV Baker). Chemistry and Industry 2 October. FU, Y-C. (2004) Fundamentals and industrial applications of microwave and radio frequency. In Food Processing: Principles and Applications. Eds Smith, J.S. and Hui, Y.H. Blackwell Publishing, Oxford, pp. 79±100. GEORGIADIS, M.C., PAPAGEORGIOU, L.G. and MACCHIETTO, S. (2000) Optimal cleaning policies in heat exchanger networks under rapid fouling. Industrial & Engineering Chemistry Research 39, 2, 441±454. GRAY, J.A. and BEMILLER, J.N. (2003) Bread staling: molecular basis and control. Comprehensive Reviews in Food Science and Food Safety 2, 1, 1±21. GUPTA, M.K., GRANT, R. and STEER, R.F. (2004) Critical factors in the selection of an industrial fryer. In Frying Technology and Practices. Eds Gupta, M.K., Warner, K. and White. P.J. AOCS, Urbana, IL. HANSEN, E., LAURIDSEN, L., SKIBSTED, L.H., MOAWAD, R.K. and ANDERSEN, M. L. (2004a) Oxidative stability of frozen pork patties: effect of fluctuating temperature on lipid oxidation. Meat Science 68, 2, 185±191. HANSEN, E., JUNCHER, D., HENCKEL, P., KARLSSON, A., BERTELSEN, G. and SKIBSTED, L.H. (2004b) Oxidative stability of chilled pork chops following long term freeze storage. Meat Science 68, 3, 479±484. HAYES, R. (1995) Design of food processing equipment. In Food Microbiology and Hygiene. Springer, Berlin. HE, H., ADAMS, R.M., FARKAS, D.F. and MORRISSEY, M.T. (2002) Use of high-pressure DALLYN, H., FALLOON, W.C.

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and ZHANG, H.Q. (2005) Pulsed ohmic heating: a novel technique for minimization of electrochemical reaction during processing. Journal of Food Science 70, 8, E460±E465. SANCHEZ-VEGA, R., MUJICA-PAZ, H., MARQUEZ-MELENDEZ, R., NGADI, M.O. and ORTEGA-RIVAS, E. (2009) Enzyme inactivation of apple juice treated by ultrapasteurization and pulsed electric fields technology. Journal of Food Processing & Preservation 33, 4, 486±499. SARANG, S., SASTRY, S.K., GAINES, J., YANG, T.C.S. and DUNNE, P. (2007) Product formulation for ohmic heating: blanching as a pre-treatment method to improve uniformity in heating of solid-liquid food mixtures. Journal of Food Science 72, 5, E227±E234. SASTRY, S.K. (1986) Mathematical evaluation of process schedules for asceptic processing of low-acid foods containing discrete particulates. Journal of Food Science 51, 5, 1323±1328. SASTRY, S.K. (2007) A model for heating of liquid-particle mixtures in a continuous flow ohmic heater. Journal of Food Process Engineering 15, 4, 263±278. SASTRY, S.K. and CORNELIUS, W.D. (2002) Aseptic Processing of Foods Containing Solid Particulates. Wiley Interscience, New York. SATYANARAYAN, V.T. and HONIKEL, K-O. (1992) Effect of different cooking methods on warmed-over flavour development in pork. Zeitschrift fuÈr Lebensmitteluntersuchung und -Forschung A 194, 5, 422±425. SHULTS, G.W., COHEN, J.S, HOWKER, J.J. and WIERBICKI, E. (1998) Development of Radappertized Pork Items. US Army Natick Research Development and Engineering Center, MA. Available at: http://handle.dtic.mil/100.2/ADA356509 SIEBERT, K.J. (2006) Haze formation in beverages. LWT ± Food Science and Technology 39, 9, 987±994. SINGH, R.P. and HELDMAN, D.R. (2008) Fluid flow in food processing. In Introduction to Food Engineering, 4th edn. Eds Singh, R.P. and Heldman, D.R. Academic Press, New York. SOARES, N.F.F. and HOTCHKISS, J.H. (1999) Comparative effects of de-aeration and package permeability on ascorbic acid loss in refrigerated orange juice. Packaging Technology and Science 12, 3, 111±118. SOLIVA-FORTUNY, R.S. BENDICHO-PORTA, S. and MARTIN-BELLOSO, O. (2006) Modelling high-intensity pulsed electric field inactivation of a lipase from Pseudomonas fluorescens. Journal of Dairy Science 89, 4096±4104. TATTIYAKUL, J., RAO, M.A. and DATTA, A.K. (2001) Simulation of heat transfer to a canned corn starch dispersion subjected to axial rotation. Chemical Engineering and Processing 40, 391±399. TATTIYAKUL, J., RAO, M.A. and DATTA, A.K. (2002) Heat transfer to a canned corn starch dispersion under intermittent agitation. Journal of Food Engineering 54, 4, 321± 329. TUCKER, G.S. and HOLDSWORTH, S.D. (1991a) Optimization of quality factors for foods thermally processed in rectangular containers. Technical Memorandum No. 627. Campden & Chorleywood Food Research Association, Chipping Norton, Glos., UK. TUCKER, G.S. and HOLDSWORTH, S.D. (1991b). Mathematical modelling of sterilization and cooking process for heat preserved foods ± application of a new heat transfer model. Food & Bioproducts Processing, Trans. IChemE 69, Cl, 5±12. SAMARANAYAKE, C.P., SASTRY, S.K.

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(2000) Kinetics of Microbial Inactivation for Alternative Food Processing Technologies. US FDA, Washington, DC.

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and PIECKOVAÂ, E. (2001) Growth modelling of heat-resistant fungi: the effect of water activity. International Journal of Food Microbiology 63, 1±2, 11±17. VAN BOEKEL, M.A.J.S. (2008) Modelling the food matrix. In Kinetic Modelling of Reactions in Foods. CRC Press, Boca Raton, FL. VAN LINDEN, V., SILA, D.N., DUVETTER, T., DE BAERDEMAEKER, J. and HENDRICKX, M. (2008) Effect of mechanical impact-bruising on polygalacturonase and pectin methylesterase activity and pectic cell wall components in tomato fruit. Postharvest Biology and Technology 47, 1, 98±106. WICHERS, H.J. and BOERIU, C. (2004) Controlling the texture of fruit and vegetables: the role of oxidizing enzymes. In Texture in Food: Solid Foods. Ed. Kilcast, D. Woodhead Publishing, Cambridge. WOLBANG, C.M., FITOSA, J.L. and TREEBY, M.T. (2008) The effect of high pressure processing on nutritional value and quality attributes of Cucumis melo. Innovative Food Science & Emerging Technologies 9, 2, 196±200. YANG, W.H. and RAO, M.A. (1998) Numerical study of parameters affecting broken heating curve. Journal of Food Engineering 37, 1, 43±61. YEN, G.C. and LIN, H-T. (1996) Comparison of high pressure treatment and thermal pasteurization effects on the quality and shelf life of guava pureÂe. International Journal of Food Science and Technology 31, 2, 205±213. ZEUTHEN, P. and BéGH-SéRENSEN, L. (2003) Food preservation techniques. p. 117 Woodhead Publishing, Cambridge. ZHANG, L. and FRYER, P.J. (1995) A model for conduction heat transfer to particles in a hold tube using a moving mesh finite element method. Journal of Food Engineering 26, 2, 193±208. VALIÂK, L.

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7 Packaging and food and beverage shelf life G. L. Robertson, University of Queensland and Food
Packaging
Environment, Australia

Abstract: The role of packaging in extending the shelf life of foods and beverages is outlined and the major food packaging materials (metals, glass, paper, plastics) described. The key package properties related to shelf life are discussed including barrier, surface area:volume ratio and closure integrity. Three examples illustrating how the shelf life of packaged foods and beverages can be predicted are given for situations where the end of shelf life is determined by moisture gain, oxygen gain and microbial growth. Finally, the way in which packaging migrants can lead to end of shelf life is illustrated using as examples epoxidised soy bean oil, antimony, tin and photoinitiators. Key words: food packaging, shelf life, metals, glass, paper, plastics, barrier, surface area:volume ratio, closure integrity, food contact materials.

7.1

Introduction

Packaging is a socio-scientific discipline which ensures delivery of goods to the ultimate consumer of those goods in the best condition appropriate for their use. In today's society, packaging is both pervasive and essential as it protects the foods we buy from the moment they are processed and manufactured through storage and retailing to the final consumer. The importance of packaging hardly needs stressing because in developed countries it is almost impossible to find more than a handful of foods that are sold in an unpackaged state. A primary package is one which is in direct contact with the contained product. It provides the initial and usually the major protective barrier.

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Examples of primary packages include metal cans, paperboard cartons, glass bottles and plastic pouches. Frequently it is only the primary package which the consumer purchases at retail outlets. A secondary package contains a number of primary packages, e.g. a corrugated case or box. It is the physical distribution carrier and is increasingly being designed so that it can be placed directly onto retail shelves for the display of primary packages (so-called shelf-ready packaging). A tertiary package is made up of a number of secondary packages, the most common example being a stretch-wrapped pallet of corrugated cases. This chapter will confine itself to a consideration of the primary package. Packaging has a major impact on food and beverage shelf life and a recent book was devoted solely to this topic (Robertson, 2010a). This chapter will briefly review the key aspects of packaging and its influence on food and beverage shelf life.

7.2 Role of packaging in extending food and beverage shelf life The package must protect its contents from outside environmental effects, be they water, water vapour, gases, odours, microorganisms, dust, shocks, vibrations, compressive forces, etc., and protect the environment from the product. For many food products, the protection afforded by the package is an essential part of the preservation process. In general, once the integrity of the package is breached, the product is no longer preserved. Knowledge of the kinds of deteriorative reactions that influence food quality is the first step in developing food packaging that will minimise undesirable changes in quality and maximise the development and maintenance of desirable properties. Once the nature of the reactions is understood, knowledge of the factors that control the rates of these reactions is necessary in order to minimise the changes occurring in foods during storage, that is, while packaged (Robertson, 2010b). Deteriorative reactions can be enzymic, chemical, physical (typically as a result of moisture gain or loss), and biological (both microbiological and macrobiological, that is, due to insect pests and rodents). Biochemical, chemical, physical and biological changes occur in foods during processing and storage, and these combine to affect food quality. The most important quality-related changes are as follows (van Boekel, 2008): · Chemical reactions: due mainly to either oxidation or non-enzymatic browning reactions. · Microbial reactions: microorganisms can grow in foods which is desirable in the manufacture of fermented foods such as cheese or beer; otherwise, microbial growth will lead to spoilage and, in the case of pathogens, to unsafe food. · Biochemical reactions: many foods contain endogenous enzymes that can potentially catalyse reactions leading to quality loss (enzymatic browning,

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lipolysis, proteolysis, etc.). In the case of fermentation, enzymes can be exploited to improve quality. · Physical reactions: many foods are heterogeneous and contain particles. These particles are unstable, and phenomena such as coalescence, aggregation and sedimentation usually lead to quality loss. Also, changes in texture can be considered physical reactions, although the underlying mechanism may be of a chemical nature. The deterioration of packaged foods depends largely on transfers that can occur between the external environment, which is exposed to the hazards of storage and distribution, and the internal environment of the package. For example, there may be transfer of moisture vapour from a humid atmosphere into a dried product, or transfer of an undesirable odour from the external atmosphere into a high-fat product, or development of oxidative rancidity if the package is not an effective oxygen (O2) barrier. Also, flavour compounds can be absorbed by some types of plastic packaging materials (a phenomenon referred to as scalping), and chemical contaminants can migrate from the packaging material into the food (e.g., plasticisers from plastic film). In addition to the ability of packaging materials to protect and preserve foods by minimising or preventing these transfers, packaging materials must also protect the product from mechanical damage and prevent or minimise misuse by consumers (including tampering). Although certain types of deterioration will occur even if there is no transfer of mass (or heat, as some packaging materials can act as efficient insulators against fluctuations in ambient temperatures) between the package and its environment, it is possible in many instances to prolong the shelf life of the food through the use of packaging. Preservation is a means of protecting a product, usually against microbiological deterioration. It is important to understand the differences between biotic deterioration which refers to changes in a food brought about by biological agents such as enzymes (e.g., ripening of fruit, respiration of vegetables) or microorganisms (e.g., moulds, bacteria, and yeasts), and abiotic deterioration which is brought about by physical or chemical agents (e.g., atmospheric O2, moisture, light, odours and temperature). Common insect pests are attracted by food odours and some insect species have the ability to bore through flexible packaging materials (Riudavets et al., 2007). Both biotic and abiotic deterioration can lead to food spoilage, albeit by different methods. Packaging can often (but not always) provide a barrier to, or inhibit the action of, those agents that lead to deterioration. Deteriorative reactions in foods are influenced by two factors: the nature of the food and its surroundings. These factors are referred to as intrinsic and extrinsic parameters. Intrinsic parameters are an inherent part of the food and include water activity (aw), pH, oxidation-reduction potential (Eh), O2 content and product formulation, including the presence of any preservatives or antioxidants. The parameter aw is defined as the ratio of the water vapour

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Fig. 7.1 Schematic of a typical moisture sorption isotherm showing effect of temperature on water activity and moisture content. ß 2006. From Robertson G. L. Food Packaging Principles and Practice, 2nd edn. Reproduced by permission of Routledge/ Taylor & Francis Group, LLC.

pressure of a food to the vapour pressure of pure water at the same temperature and is an intrinsic property of the food. A plot of the moisture content (expressed as mass of water per unit mass of dry matter) against the corresponding relative humidity (RH) or aw at constant temperature is known as a moisture sorption isotherm. Such plots are very useful in assessing the stability of foods and selecting effective packaging. As aw is temperature dependent, it follows that moisture sorption isotherms must also exhibit temperature dependence (see Fig. 7.1). Thus, at constant moisture content (which is the situation existing in a food packaged in an impermeable package), aw increases with increasing temperature. As rates of deteriorative reactions depend on both aw and temperature, the increase in rate in such situations will typically be greater than that due solely to an increase in temperature. This has important implications for shelf life. Extrinsic factors that control the rates of deteriorative reactions include temperature, RH, gas atmosphere and light; packaging can, to varying degrees, influence the impact of these factors on the rates of deteriorative reactions, depending on the specific packaging material. Temperature is a key factor in determining the rates of deteriorative reactions, and in certain situations the packaging material can affect the temperature of the food. The RH of the

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ambient environment is important and can influence the aw of the food unless the package provides an impermeable barrier to water vapour. Many flexible plastic packaging materials provide good moisture barriers, but none is completely impermeable, thus limiting the shelf life of low aw foods. The presence and concentration of gases in the environment surrounding the food have a considerable influence on the growth of microorganisms, and the atmosphere inside the package is often modified. Atmospheric O2 generally has a detrimental effect on the nutritive quality of foods, and it is therefore desirable to maintain many types of foods at a low O2 tension, or at least prevent a continuous supply of O2 into the package. With the exception of respiring fruits and vegetables and some flesh foods such as meat, changes in the gas atmosphere of packaged foods depend largely on the nature of the package. Adequately sealed metal and glass containers effectively prevent the interchange of gases between the food and the atmosphere. With flexible packaging, however, the diffusion of gases depends not only on the effectiveness of the closure but also on the permeability of the packaging material, which depends primarily on the physicochemical structure of the barrier. Many deteriorative changes in the nutritional quality of foods are initiated or accelerated by light. The intensity of light and the length of exposure are significant factors in the production of discoloration and flavour defects in packaged foods (Manzocco et al., 2008). Modification of plastic materials can be achieved by incorporation of dyes or application of coatings that absorb light at specific wavelengths. Glass is frequently modified by inclusion of colourproducing agents or by application of coatings. In this way a wide range of light transmission characteristics can be achieved in packages made of the same basic material. There have been many studies demonstrating the effect of packaging materials with different light-screening properties on the rates of deteriorative reactions in foods. Many of the chemical reactions that occur in foods can lead to deterioration in food quality (both nutritional and sensory) or the impairment of food safety. The rates of these chemical reactions are dependent on a variety of factors amenable to control by packaging, including light, O2 concentration, temperature and aw. Therefore, the package can, in certain circumstances, play a major role in controlling these factors, and thus indirectly the rate of the deteriorative chemical reactions. In designing suitable packaging for foods, it is important to first define the indices of failure (IoFs) of the food, that is, the quality attributes that will indicate that the food is no longer acceptable to the consumer (Robertson, 2010c). An IoF could be development of rancid flavours in cereals due to oxidation, loss of red colour (bloom) in chilled beef due to depletion of O2, reduction of carbonation in bottled soft drinks due to permeation of CO2 through the bottle wall, caking of instant coffee due to moisture ingress, development of microbial taint in chilled poultry, or moisture loss in green vegetables resulting in wilting. Once the IoFs for a particular food have been defined, the next step is to

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attempt to quantify the magnitude of the particular degradation, for example, how much moisture or O2 can react with the food before it becomes unacceptable. The final step is to ascertain which (if any) of the IoFs might be influenced by the packaging material, as packaging cannot prevent all undesirable changes in foods. If, for example, the IoF of a snack food was loss of crispness, then the packaging material could influence this by the extent to which it permitted the ingress of moisture. Different plastic films, for example, have different water vapour transmission rates (WVTRs), and thus the shelf life obtained varies depending on the particular polymer selected. Similar considerations apply to foods for which the IoF is oxidation, as different packaging materials have different O2 transmission rates (OTRs). However, if the IoF of a snack food was non-enzymatic browning, then it is unlikely that different packaging materials would influence the extent of this reaction.

7.3

Major packaging materials

The protection offered by a package is determined by the nature of the packaging material and the format or type of package construction. A wide variety of materials is used in packaging and primary packaging materials consist of one or more of the following materials: metals; glass; paper; and plastic polymers. These are briefly described below; more detailed information is available elsewhere (Robertson, 2006; Yam, 2009). 7.3.1 Metals Four metals are commonly used for the packaging of foods: steel, aluminium, tin and chromium. Tin and steel, and chromium and steel, are used as composite materials in the form of tinplate and electrolytically chromium-coated steel (ECCS), the latter sometimes being referred to as tin-free steel (TFS). Aluminium is used in the form of purified alloys containing small and carefully controlled amounts of various metals. The term tinplate refers to low carbon mild steel sheet varying in thickness from around 0.15±0.5 mm with a coating of tin between 2.8 and 17 gsm (g mÿ2) (0.4±2.5 m thick) applied electrolytically on each surface of the material. After plating, the coating is passivated by electrolytic treatment in sodium dichromate to render the surface more stable and resistant, and then lightly oiled. The combination of tin and steel produces a material which has good strength combined with excellent fabrication qualities as well as a corrosion-resistant surface of bright appearance due to the unique properties of tin. ECCS consists of a duplex coating of metallic chromium and chromium sesquioxide to give a total coating weight of approximately 0.15 gsm. Although the surface of ECCS is more acceptable for protective lacquer coatings, printing inks and varnishes than tinplate, it is less resistant to corrosion and therefore must be lacquered.

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Aluminium is used to manufacture both metal cans and thin foil, the latter ranging in thickness from 4 to 150 m. Foils thinner than 25 m contain minute pinholes that are permeable to gases and water vapour. In both applications alloying agents including silicon, iron, copper, manganese, magnesium, chromium, zinc and titanium are added to impart strength and improve formability and corrosion resistance. 7.3.2 Glass Glass is an amorphous, inorganic product of fusion that has been cooled to a rigid condition without crystallising. Although rigid, glass is a highly viscous liquid that exists in a vitreous or glassy state. A typical formula for soda-lime glass is silica, SiO2 68±73%; calcia, CaO 10±13%; soda, Na2O 12±15%; alumina, Al2O3 1.5±2%; and iron oxides, FeO 0.05±0.25%. The two main types of glass containers used in food packaging are bottles (which have narrow necks) and jars (which have wide openings); about 75% of all glass food containers are bottles. Today's glass containers are lighter but stronger than their predecessors, and through such developments the glass container has remained competitive and continues to play a significant role in the packaging of food products. The container finish is the glass surrounding the opening in the container that holds the cap or closure and can be broadly classified by size (i.e. diameter) and sealing method (e.g., twist cap, cork, etc.). The type of closure can have a significant impact on the shelf life of foods and beverages packaged in glass. 7.3.3 Paper Paper is the general term for a wide range of matted or felted webs of vegetable fibres (mostly wood) used for the production of paper, paperboard, corrugated board and similar products. When its grammage exceeds 224 gsm, paper is referred to as board. Since it is obtained from plant fibre it is therefore a renewable resource. The properties of an individual paper or paperboard are extremely dependent on the properties of the pulps used (e.g. whether from hardwood or softwood species). These pulps may be used unbleached or bleached to varying degrees by various techniques. Almost all paper is converted by undergoing further treatment after manufacture such as embossing, coating, laminating and forming into special shapes and sizes such as bags and boxes. While paper that has been laminated or coated with plastic polymers can provide a good barrier to gases and water vapour, other paper packaging provides little more than protection from light and minor mechanical damage. Multi-ply boards are produced by the consolidation of one or more web plies into a single sheet of paperboard which is then subsequently converted into rigid boxes, folding cartons, beverage cartons and similar products.

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7.3.4 Plastics Plastics are organic polymers with the unique characteristic that each molecule is either a long chain or a network of repeating units. The properties of plastics are determined by the chemical and physical nature of the polymers used in their manufacture; the properties of polymers are determined by their molecular structure, molecular weight, degree of crystallinity and chemical composition. These factors in turn affect the density of the polymers and the temperatures at which they undergo physical transitions. Polymer chains can and do align themselves in ordered structures, and the thermodynamics of this ordered state determine such properties as melting point, glass transition temperature, and mechanical and electrical properties. However, it is the chemical nature of the polymer which determines its stability to temperature, light, water and solvents, and hence the degree of protection it will provide to food when used as a packaging material. A wide range of polymers is used in food packaging and the major categories are briefly reviewed below. Polyolefins These form an important class of thermoplastics and include low, linear and high density polyethylenes (LDPE, LLDPE and HDPE) and polypropylene (PP). The polyethylenes have the nominal formula ±(CH2±CH2)n± and are produced with a variable amount of branching, each branch containing a terminal (±CH3) group that prevents close packing of the main polymer chains. LDPE is a tough, flexible, slightly translucent material that provides a good barrier to water vapour but a poor barrier to gases. It is widely used to package foods and is easily heat sealed to itself. LLDPE contains numerous short side chains and has improved chemical and puncture resistance and higher strength than LDPE. HDPE has a much more linear structure than LDPE, is stiffer and harder and provides superior oil and grease resistance. It is used in both film form where it has a white, translucent appearance, and as rigid packs such as bottles. PP is a linear polymer with lower density, higher softening point and better barrier properties than the polyethylenes. In film form it is commonly used in the biaxially-oriented state (BOPP) where it has sparkling clarity; it can also be blow and injection moulded to produce closures and thin-walled containers. Substituted olefins Monomers in which each ethylene group has a single substituent are called vinyl compounds; those with two substituents on the same carbon are called vinylidene compounds. The properties of the resultant polymers depend on the nature of the substituent, molecular weight, crystallinity and degree of orientation. The simplest is polyvinyl chloride (PVC) with a repeating unit of (±(CH2± CHCl)n±). A range of PVC films with widely varying properties can be obtained from the basic polymer. The two main variables are changes in formulation (principally plasticiser content) and orientation. Thin, plasticised PVC film is

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widely used for the stretch wrapping of trays containing fresh red meat and produce. The relatively high WVTR of PVC prevents condensation on the inside of the film. Oriented films are used for shrink wrapping of produce and fresh meat, but in recent years LLDPE films have increasingly replaced them in many applications. Unplasticised PVC rigid sheet is thermoformed into a wide range of inserts from chocolate boxes to biscuit trays but recently they have been substituted by PET or starch-based biopolymers. Unplasticised PVC bottles have better clarity, oil resistance and barrier properties than those made from HDPE, but in recent years they too have been increasingly replaced by PET for a wide range of foods including fruit juices and edible oils. Polyvinylidene chloride (PVdC) has a repeating unit of (±(CH2±CCl2)n±) and the homopolymer yields a rather stiff film which is unsuitable for packaging purposes. When PVdC is copolymerised with 5±50% (but typically 20%) of vinyl chloride (VC), a soft, tough and relatively impermeable film results. Although the films are copolymers of VdC and VC, they are usually referred to simply as PVdC copolymer and their specific properties vary according to the degree of polymerisation and the relative proportions of the copolymers present. Properties include a unique combination of low permeability to water vapour, gases and odours, as well as greases and alcohols. They also have the ability to withstand hot filling and retorting and so find use as a component in multilayer barrier containers. Ethylene vinyl alcohol (EVOH) copolymers are produced by a controlled hydrolysis of ethylene vinyl acetate (EVA) copolymer, the hydrolytic process transforming the VA group into VOH; there is no VOH involved in the copolymerisation. EVOH copolymers offer not only excellent processability, but also superior barriers to gases, odours, fragrances, solvents, etc., when dry. It is these characteristics that have allowed plastic containers incorporating EVOH barrier layers to replace many glass and metal containers for packaging food. Polystyrene (PS) has the general formula (±(CH2±CHC6H5)n±). Crystal grade PS can be made into film but it is brittle unless the film is biaxially oriented. While a reasonably good barrier to gases, it is a poor barrier to water vapour. The oriented film can be thermoformed into a variety of shapes. To overcome the brittleness of PS, synthetic rubbers (typically 1,3-butadiene isomer CH2=CH± CH=CH2) can be added during polymerisation at levels generally not exceeding 25% w/w for rigid plastics. The chemical properties of this toughened or high impact polystyrene (HIPS) are much the same as those for unmodified or general purpose polystyrene (GPPS); in addition, HIPS is an excellent material for thermoforming into tubs which find wide use in food packaging. Polyesters Poly(ethylene terephthalate) (PET) is a condensation product of typically ethylene glycol (EG) and terephthalic acid and has the general formula (±OOC± C6H5±COOCH2±CH2±)n. The outstanding properties of PET film as a food packaging material are its great tensile strength, excellent chemical resistance, light weight, elasticity and stability over a wide range of temperatures (ÿ60 to

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220 ëC). PET films are most widely used in the biaxially-oriented, heatstabilised form. To improve the barrier properties of PET, coatings of LDPE and PVdC copolymer have been used but today the use of MXD6 (see next section) and nanoclays are increasingly common for bottles. PET film extrusion-coated with LDPE is very easy to seal and very tough. PET is also used to make `ovenable' trays for frozen foods and prepared meals. PET bottles are stretch blow moulded, the stretching or biaxial orientation being necessary to get maximum tensile strength and gas barrier, which in turn enables bottle weights to be low enough to be economical. Polyamides Polyamides (PA) are condensation, generally linear thermoplastics made from monomers with amine and carboxylic acid functional groups resulting in amide (±CONH±) linkages in the main polymer chain that provide mechanical strength and barrier properties; they are commonly referred to as nylons. Nylon 6 films have higher temperature, grease and oil resistance than nylon 11 films. A relatively new polyamide is MXD6 made from m-xylylene diamine and adipic acid; it has better gas barrier properties than nylon 6 at all humidities, and is better than EVOH at 100% RH, due to the existence of the benzene ring in the MXD6 polymer chain. Biaxially-oriented film produced from MXD6 is used in several packaging applications as it has significantly higher gas and water vapour barrier properties, and greater strength and stiffness, than other PAs. MXD6 film is also suitable as a base substrate for laminated film structures for use in lidding and pouches, especially when the film is exposed to retort conditions. Recently MXD6 has found use as a barrier layer in PET bottles. Regenerated cellulose Regenerated cellulose film (RCF) is made from cellulose and is therefore a natural and renewable polymer. It is not a plastic because it does not soften when heated but undergoes thermal decomposition. However, since it competes with synthetic polymers in food packaging applications it is discussed here. It is commonly referred to by the generic term cellophane which is still a registered trade name in some countries. RCF can be regarded as transparent paper and for food packaging applications it is plasticised (typically with ethylene glycol) and coated on one or both sides, the type of coating largely determining the protective properties of the film. The most common coatings are LDPE, PVC and PVdC copolymer.

7.4

Key package properties related to shelf life

7.4.1 Barrier In the selection of suitable packaging materials for a particular food or beverage, the focus is typically on the barrier properties of the packaging material. In

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contrast to packaging materials made from glass or metal, packages made from thermoplastic polymers are permeable to varying degrees to small molecules such as gases, water vapour, organic vapours and other low molecular weight compounds. A plastic polymer that is a good barrier has a low permeability. The following expression can be derived from Fick's first law (Robertson, 2006): Qˆ

DS…p1 ÿ p2 †At X

7:1

Here Q is the quantity of gas or vapour permeating through a polymer of thickness X and surface area A in time t under a pressure gradient of p1 on one side and p2 on the other where p1 > p2 . D is the diffusion coefficient and S the solubility coefficient of the permeant; the product DS is referred to as the permeability coefficient and is represented by the symbol P. Thus: QX 7:2 Pˆ At…p1 ÿ p2 † or: Q P ˆ A…
p† t X

7:3

The term P=X is referred to as the permeance. P is a property of the polymer while P=X is a property of the packaging material. Typical values for the permeability coefficient of commercial food packaging polymers are presented in Table 7.1. The permeability coefficient defined above is independent of thickness, since the thickness is already accounted for in the calculation of P. However, the total amount of protection afforded by unit area of a barrier material approaches zero only asymptotically. Consequently, as polymer thickness X is increased beyond a certain value, it becomes uneconomical to increase it further to obtain lower permeability. For example, to equal the O2 barrier of a 25 m film of a high barrier material such as PVdC copolymer would require 62 500 m of PP or 1250 m of PET or 1250 m of PVC or 250 m of nylon 6. In recent years rigid and flexible polymers have been coated with a variety of compounds to improve their barrier properties including aluminium oxides (Hirvikorpi et al., 2010), oxides of silicon (SiOx) (Deilmann et al., 2008) and amorphous carbon (Boutroy et al., 2006). Nanoclays have also been added to polymers to produce polymer nanocomposites which have improved barrier and mechanical properties (Thellen et al., 2009). Literature data for gas transport coefficients (permeability, diffusion and solubility coefficients) vary generally with parameters that are intrinsic to the polymer such as degree of crystallinity, nature of the polymer, and the thermal and mechanical histories of samples such as orientation. Sorption and diffusion phenomena take place exclusively in the amorphous phase of a semicrystalline polymer and not in its crystalline zones.

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Table 7.1 Typical permeability coefficients of various food packaging polymers and permeants at 25 ëC P  1011 [mL(STP) cm cmÿ2 sÿ1 (cm Hg)ÿ1] Polymer

O2

Low density polyethylene 15±30 Linear low density 31±36 polyethylene High density polyethylene 6±12 Ethylene vinyl acetate 27±54 (12% VA) Polypropylene 9±16 Poly(vinyl chloride) 0.3±1.2 Polystyrene (high impact) 15±27 Nylon 6 (0% RH) 0.09±0.11 Nylon MXD6 0.01 Poly(ethylene terephthlate) 0.3±0.75 Polycarbonate 10±15 PVdC/PVC copolymer 0.005±0.07 EVOH copolymer (0% RH) 27 mol% ethylene 0.0018 44 mol% ethylene 0.0033

CO2

N2

SO2

H2O (90% RH)

60±160 54

4±12 0.6

200

800

45 170

3.3

57

180

92 1.2±3.0 60±150 0.2±0.3

4.4 0.0093 2.4±7.8 0.015±0.05

0.7±1.2 0.02±0.06 47±66 1.7 0.23±0.48 0.006±0.012 0.024 0.012

7 680 1.2 93 220 12±18,000 22* 7,000 1,300 14

0.0005

* Nylon 11

However, in the published literature it is rare to find many details about a particular plastic packaging material apart from its name, sometimes the resin supplier and maybe if it has been oriented. This makes it virtually impossible to replicate the experimental conditions described in the literature since the range of polymers available is vast. For example, the website www.ides.com contains data sheets on over 80,000 commercial polymers from 694 resin manufacturers. Of course, not all of these polymers are approved or suitable for use in food packaging. The temperature dependence of the permeability coefficient can be represented by an Arrhenius-type relationship: P ˆ P0 exp …ÿEp =RT†

7:4

where Ep is the apparent activation energy for permeation, R is the gas constant and T is the absolute temperature. The permeability coefficient of a specific polymer-permeant system may increase or decrease with increases in temperature depending on the relative effect of temperature on the solubility and diffusion coefficients. Generally, the solubility coefficient increases with increasing temperature for gases and decreases for vapours, and the diffusion coefficient increases with temperature for both gases and vapours. For these reasons, permeability coefficients of different polymers determined at one temperature may not be in the same relative order at other temperatures.

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The above treatment of steady state diffusion assumes that both D and S are independent of concentration but in practice deviations do occur when there is interaction such as occurs between hydrophilic materials (e.g., EVOH and some of the PAs) and water vapour, or for heterogeneous materials such as coated or laminated films. The property is then defined as the transmission rate (TR) of the material, where: Q 7:5 TR ˆ At where Q is the amount of permeant passing through the polymer, A is the area and t is the time. In the case of water and oxygen, the terms WVTR (water vapour transmission rate) and GTR (gas transmission rate) or more specifically OTR or O2TR (oxygen transmission rate) are in common usage. It is critical that the thickness of the film or laminate, the temperature and the partial pressure difference of the gas or water vapour are specified for a particular TR. To convert a measured WVTR or OTR to P, it is necessary to multiply by the thickness of the film and divide by the partial pressure difference used when making the measurements. Example: Calculate the permeability coefficient of an LDPE film to O2 at 25 ëC given that the OTR through a 2:54  10ÿ3 cm thick film with air on one side and inert gas on the other is 1:5  10ÿ6 mL cmÿ2 sÿ1 at 50% RH. O2 partial pressure difference across the film is 0.21 atm ˆ 16 cm Hg OTR  thickness
p 1:5  10ÿ6 mL cmÿ2 sÿ1  2:54  10ÿ3 cm ˆ 16 (cm Hg) ˆ 2:4  10ÿ10 [mL(STP) cm cmÿ2 sÿ1 cm Hg)ÿ1 ]

Pˆ

ˆ 24  10ÿ11 [mL(STP) cm cmÿ2 sÿ1 cm Hg)ÿ1 ] Therefore: P  1011 ˆ 24 [mL(STP) cm cmÿ2 sÿ1 cm Hg)ÿ1 ] which is within the range given in Table 7.1.

The OTRs of packaging materials used for modified atmosphere packaging (MAP) of chilled products vary extensively with temperature, RH and material thickness after the thermoforming of packages. Jakobsen et al. (2005) studied two different polymer combinations: APET/LDPE (tray) and PA/LDPE (lid). A temperature reduction of 8 ëC (in the interval 7±23 ëC) caused an OTR reduction of 26±48% depending on material type, degree of thermoforming and RH. An

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increased OTR was observed as a result of material thinning; however, the increase was not always directly proportional to the degree of material thinning. The changes in OTR observed emphasise the necessity of evaluating the performance of packaging materials under realistic storage conditions, in order to estimate the real O2 content of a chosen package solution. 7.4.2 Surface area:volume ratio The dimensions of the package for a given weight of food can have a large influence on shelf life. While a spherical shape will minimise the surface area of the package (and thus the quantity of moisture or O2 that will permeate through the package wall) it is not a practical shape for commercial use and in practice most packages tend to be rectangular or cylindrical. Table 7.2 gives the surface areas for a range of different shapes which all have the same volume (approximately 450 mL). Compared to the surface area of a sphere, the surface area of a cylinder is 16% greater; a cube 24% greater; a tetrahedron 49% greater; a rectangular shape 58% greater and a thin rectangular shape 246% greater. Extremely thin packages have a much greater surface area:volume ratio and thus require a plastic with better barrier properties to get the same shelf life than if the same quantity of product were packaged in a thicker format. For different quantities of the same product packaged in different sized packages using the same plastic material, the smallest package will have the shortest shelf life as it inevitably has a greater surface area per unit volume. Many food companies still seem unaware of this fact as they continue to launch smaller-sized packages without changing the packaging material and then wonder why the shelf life is shorter for the smaller-sized package.

Table 7.2 Surface areas of different package shapes all having a volume of 450 mL. ß 2010. From Food Packaging & Shelf Life edited by G.L. Robertson. Reproduced by permission of Routledge/Taylor & Francis Group, LLC Shape Sphere Cylinder

Dimensions (cm)

Diameter 9.52 Diameter 7.3 Height 10.8 Cube Sides 7.67 Tetrahedron Sides 15.65 Rectangular pack (1) Height 3 Length 15 Width 10 Thin rectangular Height 1 pack (2) Length 20 Width 22.5

Surface area (m2) (cm2)

Increase (%)

Surface area: volume ratio

285 331

0.0285 0.0331

0 16

0.63 0.73

353 424 450

0.0353 0.0424 0.0450

24 49 58

0.78 0.94 1.0

985

0.0985

246

2.18

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Example: A food powder having a density of 1 is to be packaged in a plastic film which has a WVTR of 3.1 g mÿ2 dayÿ1 at 25 ëC and 75% RH. The initial moisture content of the powder is 2% and the critical moisture content is 8%. Assuming that each pack will contain 450 g of powder and will be exposed to an external environment at 25 ëC and 75% RH, calculate the shelf life if the shapes of the packs are the same as those listed in Table 7.2. For simplicity, assume that the driving force for WVT remains constant and that there are no moisture gradients in the powder. Weight of dry solids ˆ 98% of 450 ˆ 441.0 g Initial weight of water in powder ˆ 2% of 450 ˆ 9.0 g Final weight of water in powder ˆ 441.0/0.92 ÿ 450 ˆ 479.3 ÿ 450 ˆ 29.35 g Therefore weight of water permeating into powder is: 29.35 ÿ 9.0 ˆ 20.35 g For a spherical-shaped package: Quantity of water permeating into package per day is: 0:0285  3:1 ˆ 0:08835 g dayÿ1 Therefore shelf life s ˆ

20:35 0:08835

ˆ 230 days For the other package shapes: Cylinder: Cube: Tetrahedron: Rectangle 1: Rectangle 2:

s s s s s

ˆ 198 days ˆ 186 days ˆ 155 days ˆ 146 days ˆ 67 days

Thus the shelf life for the same quantity of product packaged in the same film varies by a factor of 3.4 from 67 to 230 days depending on the shape of the package.

7.4.3 Package closures and integrity While the choice of suitable packaging material is critically important to achieve the desired product shelf life, adequate closure or sealing of the package after filling is crucial since the quality of the resultant seal is of paramount importance to the ultimate integrity of the package.

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For glass containers, a wide range of closures made from either metal or plastics is available. Metal closures are stamped out of sheets of tinplate, ECCS or aluminium and can take four forms: screw caps, crowns, lug caps and spin-on or roll-on closures. Plastic closures are generally compression or injection moulded, the former being based on urea-formaldehyde or phenolicformaldehyde resins, and the latter on a variety of thermoplastic polymers including PS, LDPE, HDPE, PP and PVC. The closure used to retain internal pressures of 200±800 kPa as found in carbonated drinks and beer has traditionally been the crown cork, a crimp-on/ pry-off friction-fitting closure made from tinplate with a fluted skirt and a cork or plastisol liner. A roll-on tamper-evident (ROTE) aluminium or plastic closure is used where critical sealing requirements such as carbonation retention, vacuum retention and hermetic sealing are to be met and is especially popular for soft drinks in large containers where reopening is common. The same closures are applied to glass and plastic bottles. The most common closure designed to contain and protect the contents with no internal pressure (e.g. wine in a bottle) has been the traditional bark cork obtained from the holm oak tree Quercus suber, but it can present problems such as cork dust, leakage and cork taint. In recent years increasing quantities of wine in glass bottles have been sealed using an aluminium roll-on pilfer-proof (ROPP) closure (Brajkovich et al., 2005). The main routes of O2 ingress through different closures into wine bottles is now well established (Lopes et al., 2007). Three types of closures made from metal (either tinplate or ECCS) are used to maintain a vacuum inside a glass container which typically contains heat processed food: a lug-type or twist cap; a press-on twist-off cap held on mainly by vacuum with some assistance from the thread impressions in the gasket wall; and a pry-off (side seal) cap widely used on retorted products and consisting of a cut rubber gasket held in place by being crimped under the curl. Vacuum closures often have a safety button or flip panel consisting of a raised, circular area in the centre of the panel that provides a visual indicator to the consumer that the package is properly sealed. For metal containers, the end is mechanically joined to the cylindrical can body by a double seaming operation. The final quality of the double seam is defined by its length, thickness and the extent of the overlap of the end hook with the body hook. Heat sealable films are considered to be those films which can be bonded together by the normal application of heat. Non-heat-sealable films obviously cannot be sealed this way, but they can often be made heat sealable by applying a heat-sealable coating. In this way the two facing coated surfaces become bonded to each other by application of heat and pressure for the required dwell time. Methods to heat seal plastic films include conduction, impulse, induction, ultrasonic, dielectric and hot-wire (Robertson, 2006). Paper packages are typically sealed by the use of adhesives which can be made from either natural (e.g., starch, protein or rubber latex) or synthetic materials (e.g., PVA). The latter category can be either water- or solvent-borne;

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hot-melt and cold-seal type adhesives are also widely available. To confer gas and/or water vapour barrier properties, paper is coated with a continuous film of typically LDPE which also makes it possible to heat seal the coated layers.

7.5

Predicting shelf life of packaged foods and beverages

As discussed earlier, the shelf life of a food is controlled by product characteristics including formulation and processing parameters (intrinsic factors); the environment to which the product is exposed during distribution and storage (extrinsic factors); and the properties of the package. Examples of extrinsic factors include temperature, RH, light, total pressure and partial pressure of different gases, and mechanical stresses including transportation and consumer handling. Many of these factors can affect the rates of deteriorative reactions which occur during the shelf life of a product. The properties of the package can have a significant effect on many of the extrinsic factors and thus indirectly on the rates of the deteriorative reactions. Thus the shelf life of a food can be altered by changing its composition and formulation, processing parameters, packaging system, or the environment to which it is exposed. Foods can be classified according to the degree of protection required which focuses attention on the key requirements of the package such as maximum moisture gain or O2 uptake. This enables calculations to be made to determine whether or not a particular packaging material would provide the necessary barrier required to give the desired product shelf life. Examples of such shelf life calculations for moisture and oxygen exchange and microbial growth are given in the following sections. The use of mathematical modelling to design modified atmosphere packaging (MAP) has recently been reviewed (Torrieri et al., 2009); the use of such an approach enables a systematic approach to the design of packaging systems which is still all too rare. 7.5.1 Moisture exchange and shelf life When a food is placed in an environment at a constant temperature and RH, it will eventually come to equilibrium with that environment. The corresponding moisture content at steady state is referred to as the equilibrium moisture content. A plot of the moisture content (expressed as mass of water per unit mass of dry matter) against the corresponding aw at constant temperature gives a moisture sorption isotherm which is very useful in assessing the stability of foods and selecting effective packaging. The expression for the steady state permeation of a gas or vapour through a thermoplastic material presented above (see Eq. 7.3) can be rewritten as: w P 7:6 ˆ
A
…p1 ÿ p2 † t X where w=t is the rate of gas or vapour transport across the film, the latter term corresponding to Q=t in the integrated form of the expression (Eq. 7.3).

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The prediction of moisture transfer either to or from a packaged food requires analysis of the above equation given certain boundary conditions. If it is assumed that P=X is constant, that the external environment is at constant temperature and humidity, and that p2, the vapour pressure of the water in the food, follows some simple function of the moisture content, then a simple analysis can be made. However, because external conditions will not remain constant during storage, distribution and retailing of a packaged food, P=X will not be constant. If the food is being sold in markets in temperate climates, then WVTRs determined at 25 ëC/75% RH or 23 ëC/50% RH can be used. In tropical countries analysis can be made using WVTRs determined at 38 ëC/90% RH. A further assumption is that the moisture gradient inside the package is negligible, i.e. the package should be the major resistance to water vapour transport. This is the case whenever P=X is less than about 10 g mÿ2 dayÿ1 (cm Hg)ÿ1, which is the case for most films under high humidity conditions. The internal vapour pressure is not constant but varies with the moisture content of the food at any time. Consequently the rate of gain or loss of moisture is not constant but falls as
p gets smaller. Thus to be able to make accurate predictions, some function of p2, the internal vapour pressure, as a function of the moisture content, must be inserted into the equation. Assuming a constant rate results in the product being overprotected. In low and intermediate moisture foods, the internal vapour pressure is determined solely by the moisture sorption isotherm of the food. In the simplest case the isotherm can be treated as a linear function as shown in Fig. 7.2: m ˆ b
aw ‡ c

7:7

where m is the moisture content in g H2O per g solids; aw is the water activity; b is the slope of curve; and c is a constant. The moisture content can be substituted for water gain and, after some mathematical manipulation, the following expression is obtained: m e ÿ m i P A p0 ˆ
7:8

t ln me ÿ m X Ws b where me is the equilibrium moisture content of the food if exposed to the external package RH; mi is the initial moisture content of the food; m is the moisture content of the food at time t; and p0 is the vapour pressure of pure water at the storage temperature (NOT the actual vapour pressure outside the package). The end of product shelf life is reached when m ˆ mc , the critical moisture content, at which time t ˆ s , the shelf life. Although this equation has been extensively tested for foods and found to give reasonable predictions of actual weight gain (Labuza and Altunakar, 2007), it is clear from Fig. 7.2 that linearising the isotherm results in the use of a pseudo-equilibrium moisture content m0e that is less than what would be experienced in practice. Therefore the calculated shelf life will be longer than what would be achieved in practice.

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Fig. 7.2 Schematic of a typical moisture sorption isotherm for breakfast cereal with a superimposed straight line of slope b. Initial (mi), critical (mc) and equilibrium (me) moisture contents are indicated together with the pseudo-quilibrium (m0e ) moisture content used for package shelf life calculations.

Equations such as Eq. 7.8 can be used to calculate the effect on shelf life of various packaging films, different external conditions such as temperature and humidity, changes in the surface area:volume ratio of the package, and variations in the initial moisture content of the product. The following example will illustrate this. Example: A breakfast cereal has an initial moisture content mi of 2.5% and a critical moisture content mc of 8% due to loss of crispness. The equilibrium moisture content me at 25 ëC is 14.8% and the pseudo-equilibrium moisture content m0e obtained by extension of the linear portion of the isotherm is 11%; the slope of the line (b) is 0.147 g H2O/g solids/unit aw (see Fig. 7.2). Calculate the shelf life of the cereal if it is packaged in a 50 m (micron) LDPE film or a 50 m OPP film. The weight of dry cereal in the package is 400 g and the dimensions of the package are 20 cm  30 cm. The packed product is to be stored at 25 ëC and 75% RH. Surface area of the packs are 20  30 ˆ 600 cm2 ˆ 0.06 m2 Vapour pressure of pure water at 25 ëC ˆ 2.3756 cm Hg Data from a plastic film supplier indicated that WVTRs determined at 25 ëC/75% RH are: 50 m LDPE ˆ 8.0 g mÿ2 dayÿ1 50 m OPP ˆ 1.35 g mÿ2 dayÿ1

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These WVTRs must be converted into water vapour permeances P=X by dividing by the driving force for water vapour transfer: Driving force at 25 ëC/75% RH ˆ 2:3756  0:75 ˆ 1:782 cm Hg For LDPE film: P 8:0 g 1  ˆ X m2 day 1:782 (cm Hg) ˆ 4.489 g H2O mÿ2 dayÿ1 (cm Hg)ÿ1 For OPP film: P 1:35 g 1  ˆ 2 X m day 1:782 (cm Hg) ˆ 0.758 g H2O mÿ2 dayÿ1 (cm Hg)ÿ1 Substituting into Eq. 7.8 for cereal packed in LDPE film: ln

11 ÿ 2:5 0:06 2:3756 ˆ 4:489


s 11 ÿ 8 400 0:147

7.9

Solving for shelf life s : s ˆ ln [2.833]/1.088  10ÿ2 ˆ 1:0413=1:088  10ÿ2 ˆ 96 days If the cereal were packed in OPP film instead: s ˆ ln [2.833]/1.837  10ÿ2 ˆ 567 days The shelf life is inversely related to the water vapour permeances of the film; since P=X for LDPE is 5.9 times that for OPP, the shelf life in the latter film is 5.9 times that in the former. If the required shelf life were, say, 300 days then Eq. 7.8 could be recalculated using s ˆ 300 and solved for P=X . From this the corresponding WVTR could be calculated and the film supplier requested to supply a film that met this specification at 25 ëC and 75% RH. As noted earlier, the shelf lives calculated above will be longer than what would be achieved in practice because the pseudo-equilibrium moisture content used in the calculations is less than the actual equilibrium moisture content which is the real driving force for water vapour transport. Because of the simplifying assumptions made in the above calculations, the calculated shelf lives should be verified by actual shelf life testing.

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7.5.2 Oxygen exchange and shelf life It is also possible to calculate the shelf life of a food where the major mode of deterioration is oxidation as demonstrated in the following example.

Example: The six-layer PP/EVOH squeezable GammaÕ bottle became the first barrier food bottle to replace glass when it debuted for Heinz ketchup in 1983. About seven years later, the ketchup bottle moved to coinjection blow moulding with PET instead of PP to enhance both clarity and recyclability. Burgess et al. (1990) determined the O2 permeability coefficient for the GammaÕ bottle, studied the change in the colour of ketchup after long-term exposure to an oxygen-rich environment and established a minimum acceptable redness level for ketchup. The combined results were then used to determine the reaction rate between O2 and ketchup and to predict the shelf life for colour stability of ketchup packaged in the GammaÕ bottle. The OTRs of 12 bottles ranged from 0.31 to 0.98 with an average of 0.56 mL dayÿ1 at 22.7 ëC. The corresponding permeability coefficient P ranged from 4:1  10ÿ11 to 13:9  10ÿ11 with an average of 8:3  10ÿ11 mL cm cmÿ2 secÿ1 (cm Hg)ÿ1. The rate of colour change from red to brown fitted a second-order equation with a rate constant k ˆ 2:1  10ÿ6 day cmÿ2. The colour was judged to be unacceptable once 7:1  10ÿ6 mol of O2 per cm2 of bottle surface was absorbed by the ketchup. The surface area of exposed ketchup inside the bottle was 671 cm2. The maximum number of moles of O2 that could be consumed through permeation in order to reach an unacceptable colour is: (671 cm2)  (7:1  10ÿ6 mol cmÿ2) ˆ 0.00476 mol The ideal gas law was used to convert 0.00476 mol into mL at standard conditions: v ˆ nRT=p ˆ …0:00476†  …82:06†  …298†=1 ˆ 116 mL where R ˆ 82:06 mL atm molÿ1 Kÿ1. A bottle of ketchup can therefore consume 116 mL of O2 before changing to an unacceptable colour. As O2 permeates into the bottle, it can both build up inside the bottle and be consumed in a reaction with the ketchup. In the worst case, the ketchup will instantaneously absorb all of the permeating O2, thereby maintaining an O2 partial pressure of zero inside the bottle. The maximum value for the OTR found in the permeation experiment was 0.98 mL dayÿ1. Therefore, the predicted shelf life is at least 116/0.98 ˆ 118 days at 22.7 ëC.

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7.5.3 Microbial shelf life The influence of packaging on the microbial shelf life of food has recently been reviewed (Lee, 2010). For packages in which the atmosphere has been modified to exclude O2 either by applying a vacuum or gas flushing to suppress the growth of aerobic microorganisms and minimise oxidative quality changes, packaging materials with a poor gas barrier act to promote microbial growth of aerobes and facultative anaerobes. Even microaerophiles such as Lactobacillus spp. which dominate in vacuum and CO2 packaging of meat products may have enhanced growth rates with higher OTR film or packaging (Tsigarida and Nychas, 2006). The effect of gas permeability on microbial spoilage is shown clearly in Fig. 7.3 in which sous vide packages with a high OTR favoured the growth of aerobic and anaerobic bacteria. The high microbial load consisted of thermoduric Bacillus spp. facultative anaerobes which survived the pasteurisation process and were presumed to have been responsible for the microbial spoilage (Kim et al., 2003). When the microbial lag time was used to estimate shelf life in Fig. 7.3, a package with an OTR three times less extended the shelf life to twice that of the more permeable one. Uncertainty in estimating the microbial shelf life of chilled foods exposed to changing temperature is due to the experimental variability of the model parameters (Almonacid and Torres, 2010).

Fig. 7.3 Effect of gas permeability on evolution of aerobic and anaerobic bacterial counts of sous vide packaged seasoned spinach soup (600 g pouch pack) at 10 ëC containing thermoduric organisms. s: aerobic bacteria with high OTR film package (6.3 mL mÿ2 hÿ1 at OTR partial pressure differential of 1 atm); D: anaerobic bacteria under high O2 permeability film package; l: aerobic bacteria under low OTR film package (OTR 2.3 mL mÿ2 hÿ1); : anaerobic bacteria under low OTR film package. Adapted from Kim et al. (2003).

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7.6

Packaging migrants and food and beverage shelf life

7.6.1 Introduction There has been a long history of so-called food contact substances migrating from packaging materials into foods (Grob et al., 2006). Not surprisingly, food packaging materials are highly regulated in many countries to ensure consumer safety. Risk assessment of food contact materials (FCMs) in the EU and USA has recently been discussed (Barlow, 2009). Migration is the transfer of molecules originally contained in the packaging material (e.g. plasticiser, residual monomer, antioxidant, catalyst) into the food and possibly to the external environment. Overall migration (OM) is the sum of all (usually unknown) mobile packaging components released per unit area of packaging material under defined test conditions, whereas specific migration (SM) relates to an individual and identifiable compound only. OM therefore is a measure of all compounds transferred into the food whether they are of toxicological interest or not, and will include substances that are physiologically harmless. One of the complications from a legislative viewpoint is that many of the substances that migrate (especially components migrating from can coatings) are neither the starting materials, nor obvious derivatives therefrom, and are, therefore, not covered by existing systems based on positive lists of substances which can be used in food contact materials. The migration of molecules from packaging material into food is a complex phenomenon, and most mathematical treatments of transport processes are derived initially from a consideration of gaseous diffusion as discussed in Section 7.4.1. It is worth noting that diffusion in liquids is approximately one million times slower than in gases, and in solids about one million times slower than in liquids. In the initial stages when up to 60% of the migrant is lost from a polymer to a food, the amount of substance migrating into the food is typically proportional to the square root of time. The extent of migration is strongly controlled by the diffusion and partition coefficients which are influenced by the identity of the packaging material and its chemical structure, molecular weight, polarity and concentration of the migrant in the packaging, the kind of food, any interaction between the food and the packaging, the volume of the packed food and the time and temperature of storage (Ossberger, 2009). Therefore it is possible in both theory and practice that migrants in packaged foods will increase during storage and when they exceed the legal limit, the food will have reached the end of its shelf life and can no longer be legally sold. Space does not permit a detailed discussion of all the possible situations where migration may lead to the premature end of shelf life of packaged foods. Therefore several examples will be presented to demonstrate the diversity of migration of FCMs. 7.6.2 Epoxidised soy bean oil (ESBO) Many types of foods are sold in glass jars with metal lids. To ensure tight closure and fairly easy opening, the lids contain a gasket of PVC with 40±45%

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plasticiser, usually epoxidised soy bean oil (ESBO). Migration from these lids has repeatedly been an issue of concern. A widely publicised incident in 1998 concerned the migration of ESBO and ESBO derivatives into baby foods packed in glass jars with metal closures, the amounts sometimes exceeding the tolerable daily intake (TDI). Fankhauser-Noti et al. (2005) reported that the migration of ESBO into food products with some free oil far exceeded the SM and OM limit. When the gasket is tightened against the rim of the jar, 60±250 mg (average 165 mg) is in contact with food and on average 70 mg ESBO was in food contact. After exposure to olive oil for four weeks at ambient temperature, all the ESBO was transferred; 70 mg ESBO in a 250 g jar resulted in a concentration of 280 mg kgÿ1; in a 100 g jar it was 700 mg kgÿ1. In oily foods such as garlic, chilli or olives in oil, these predicted concentrations are approached. The estimated exposure of infants aged 6±12 months to ESBO migrating into baby foods can sometimes exceed the TDI by up to 4±5-fold. A SM limit of 30 mg kgÿ1 for ESBO in baby foods has been in effect in the EU since November 2006; for other foods a SM limit of 60 mg kgÿ1 applies. ESBO migration into food containing free oil in contact with the gasket has been reported with a mean of 166 mg kgÿ1 in 86 samples and a maximum of 580 mg kgÿ1 (Fankhauser-Noti et al., 2005). Recently Graubardt et al. (2009) reported further insights into the mechanism of migration from the PVC gaskets of metal closures into oily foods in glass jars. 7.6.3 Antimony (Sb) Antimony trioxide (Sb2O3) is used as a catalyst in 90% of PET manufactured worldwide. As a result most commercial PET material typically contains 190± 300 mg Sb kgÿ1. Antimony trioxide is a suspected carcinogen and is listed as a priority pollutant by the US EPA and the EU. A background level of antimony in pristine ground water in Canada is around 2 ng Lÿ1, but once filled into PET bottles, these levels rise to around 50 ng Lÿ1 in 37 days and 566 ng Lÿ1 after 6 months storage at room temperature (Shotyk et al., 2006). Up to 626 ng Lÿ1 have been found in German brands of water in PET bottles. Antimony residues in ready-to-eat meals heated in PET trays of up to 38 g Lÿ1 have been reported which is the SM limit in the EU. However, the migrated amounts of Sb relative to the accepted TDI give no cause for toxicological concern. Shotyk and Krachler (2007) determined antimony concentrations in 132 brands of bottled water from 28 countries; two of the brands were at or above the maximum allowable Sb concentration for drinking water in Japan (2 g Lÿ1). All of the bottled waters were found to contain Sb in concentrations well below the guidelines recommended for drinking water by the WHO (20 g Lÿ1), US EPA (6 g Lÿ1), as well as the German Federal Ministry of Environment (5 g Lÿ1). Although the extent of contamination of bottled waters by leaching of Sb from PET increased with duration of storage, the reactivities of the bottles were variable for reasons which are not apparent.

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Keresztes et al. (2009) determined Sb in 10 brands of Hungarian still and sparkling mineral water stored in PET bottles under various conditions. Generally, the Sb concentration of still mineral water was lower than that of sparkling; under certain extreme light and temperature storage conditions, the Sb concentration of some samples exceeded 2 g Lÿ1. The extent of Sb leaching from the PET of different brands of mineral water differed by one order of magnitude in experiments conducted under the same conditions. However, it is not only Sb in bottled water that has received attention. Recently Krachler and Shotyk (2009) reported levels of 23 elements in 132 brands of bottled water from 28 countries; trace metal levels of most bottled waters were below guideline levels currently considered harmful for human health. 7.6.4 Tin The chemical structure which gives metals their valuable practical properties is also responsible for their main weakness: susceptibility to corrosion, the chemical reaction between a metal and its environment. All metals are affected to a greater or lesser extent. Foods and beverages are extremely complex chemical systems covering a wide range of pH and buffering properties, as well as a variable content of corrosion inhibitors or accelerators. The most important corrosion accelerators in foods include O2, anthocyanins, nitrates, sulfur compounds and trimethylamines. While high concentrations of tin in food may cause stomach upsets in some individuals, this is unlikely to be the case where tin concentrations remain below the legal limit of 200 mg kgÿ1 (100 mg kgÿ1 in canned beverages and 50 mg kgÿ1 in canned baby foods). Grassino et al. (2009) reported maximum values of tin in cans of tomato pureÂe up to 301 mg kgÿ1 after 180 days at so-called elevated storage temperatures (36 ëC) which in countries near the equator is the ambient temperature. Based on the legal limit for tin, the shelf life of these canned foods would be less than five months. 7.6.5 Photoinitators Printing inks are incredibly complex materials and their detailed composition a closely-guarded trade secret. Over the past 20 years there has been a move away from solvent-based inks towards those that are cured by UV radiation or (less commonly) electron beams (EB). Photoinitiators are components widely used in UV-cured inks for printing food packaging and a number of food contamination incidents resulting from migration of photoinitiators into food have occurred. Johns et al. (2000) studied the migration of ink components from cartonboard to food during frozen storage and observed that under low temperature conditions (ÿ20 ëC) the migration of benzophenone (a widely-used photoinitiator) occurred even when there was no direct contact between the packaging and the food. Isopropylthioxanthone (ITX) is another photoinitiator used in UV-cured

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offset printing inks; it is not prohibited for use in food packaging by the EU; it is also not listed on the WHO's prohibited list. In 2005 Nestle undertook a recall of over 30 million cartons in four European countries of UHT baby milk packaged in multilayer laminate Tetra Brik Aseptic cartons following the discovery by Italian food safety authorities of the presence of ITX at levels ranging from 120 to 305 mg Lÿ1 for baby milk and from 74± 445 mg Lÿ1 in milk for babies aged 12 months and over; ITX was found at 600 mg Lÿ1 in a single sample of flavoured milk tested. The European Food Safety Authority (EFSA) later said that the presence of the chemical in packaged foods does not pose a health risk. Rothenbacher et al. (2007) detected ITX in 36 of 137 packages (26%) not limited to multilayer laminate cartons (e.g. it was found in sausage skins and plastic cups), and significant migration occurred in 75% of the packaging materials that tested positive. The levels of ITX ranged up to 357 mg Lÿ1 in orange juice. The authors concluded that industry should utilise other, lessmigrating photoinitiators, and that the implementation of legislative standards for GMP with a positive list for printing inks and maximum migration limits, especially for substances with incomplete toxicological assessment, is essential.

7.7

Future trends

Numerous factors including political and legislative changes as well as global demand for foods and the likely move towards a low carbon economy will influence the development and success of new packaging materials. However, there is no doubt that the use of existing food packaging materials will increase, but as part of the drive towards more sustainable packaging, food manufacturers will reduce the amount of packaging per unit of food. This will have obvious implications for shelf life. Major supermarket chains are already leading the way by encouraging their suppliers to use less packaging material and this trend is likely to accelerate. The use of bio-based materials which generally have poorer barrier properties will create challenges for food manufacturers who need to meet target shelf lives for their products to ensure orderly distribution and marketing. Finally, there will be greater legislative knowledge and oversight about potential migrants from food contact materials that will lead inevitably to some chemicals being banned or restricted in the manufacture of packaging materials.

7.8

Sources of further information and advice

(2006). Food Packaging Principles & Practice, 2nd edn. Boca Raton, FL: CRC Press. ROBERTSON G.L. (ed.) (2010). Food Packaging and Shelf Life. Boca Raton, FL: CRC Press. YAM K.L. (ed). (2009). The Wiley Encyclopedia of Packaging Technology, 3rd edn. New York: John Wiley & Sons Inc. ROBERTSON G.L.

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7.9

References

(2010). Uncertainty of microbial shelf-life estimations for refrigerated foods due to the experimental variability of the model parameters. Journal of Food Process Engineering 33: 66±84. BARLOW S.M. (2009). Risk assessment of food-contact materials: past experience and future challenges. Food Additives and Contaminants Part A 26: 1526±1533. ALMONACID S.F., TORRES J.A.

BOUTROY N., PERNEL Y., RIUS J.M., AUGER F., VON BARDELEBEN H.J., CANTIN J.L., ABEL F.,

ZEINERT A., CASIRAGHI C., FERRARI A.C., ROBERTSON J. (2006). Hydrogenated amorphous carbon film coating of PET bottles for gas diffusion barriers. Diamond & Related Materials 15: 921±927.

BRAJKOVICH M., TIBBITS N., PERON G., LUND C.M., DYKES S.I., KILMARTIN P.A., NICOLAU L.

(2005). Effect of screwcap and cork closures on SO2 levels and aromas in a Sauvignon Blanc wine. Journal of Agricultural and Food Chemistry 53: 10006± 10011. BURGESS C., BURGESS G., OFOLI R. (1990). Oxygen diffusion rate through the Gamma bottle and associated kinetic effects on tomato ketchup. Packaging Technology & Science 3: 233±239. DEILMANN M., THEIû S., AWAKOWICZ P. (2008). Pulsed microwave plasma polymerization of silicon oxide films: application of efficient permeation barriers on polyethylene terephthalate. Surface & Coatings Technology 202: 1911±1917. FANKHAUSER-NOTI A., FISELIER K., BIEDERMANN S., BIEDERMANN M., GROB K., ARMELLINI F.

(2005). Epoxidized soy bean oil (ESBO) migrating from the gaskets of lids into food packed in glass jars. European Food Research & Technology 221: 416±422. GRASSINO A.N., GRABARIC Z., PEZZANI A., SQUITIERI G., FASANARO G., IMPEMBO M. (2009). Corrosion behaviour of tinplate cans in contact with tomato pureÂe and protective (inhibiting) substances. Food Additives and Contaminants 26: 1488±1494. GRAUBARDT N., BIEDERMANN M., FISELIER K., BOLZONI L., CAVALIERI C., GROB K. (2009). Further insights into the mechanism of migration from the PVC gaskets of metal closures into oily foods in glass jars. Food Additives and Contaminants Part A 26: 1217±1225. GROB K., BIEDERMANN M., SCHERBAUM E., ROTH M., RIEGER K. (2006). Food contamination with organic materials in perspective: packaging materials as the largest and least controlled source? A view focusing on the European situation. Critical Reviews in Food Science & Nutrition 46: 529±535. È HA È -NISSI M., MUSTONEN T., IISKOLA E., KARPPINEN M. (2010). Atomic layer HIRVIKORPI T., VA deposited aluminium oxide barrier coatings for packaging materials. Thin Solid Films 518: 2654±2658. JAKOBSEN M., JESPERSEN L., JUNCHER D., MIQUEL BECKER E., RISBO J. (2005). Oxygen and light barrier properties of packaging materials used for modified atmosphere packaging: evaluation of performance under realistic storage conditions. Packaging Technology & Science 18: 265±272. JOHNS S.M., JICKELLS S.M., READ W.A., CASTLE L. (2000). Studies on functional barriers to migration. 3. Migration of benzophenone and model ink components from cartonboard to food during frozen storage and microwave heating. Packaging Technology & Science 13: 99±104. Â R E., MIHUCZ V.G., VIRAÂG I., MAJDIK C., ZA Â RAY G. (2009). Leaching of KERESZTES S., TATA antimony from polyethylene terephthalate (PET) bottles into mineral water. Science of the Total Environment 407: 4731±4735.

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(2003). Effect of different oxygen permeability packaging films on the quality of sous-vide processed seasoned spinach soup. Food Science and Biotechnology 12: 312±315. KRACHLER M., SHOTYK W. (2009). Trace and ultratrace metals in bottled waters: survey of sources worldwide and comparison with refillable metal bottles. Science of the Total Environment 407: 1089±1096. LABUZA T.P., ALTUNAKAR B. (2007). Diffusion and sorption kinetics of water in foods. In: Water Activity in Foods: Fundamentals and Applications (Ed. by G.V. BarbosaCaÂnovas, A.J. Fontana, S.J. Schmidt and T.P. Labuza). Oxford: Blackwell Publishing, pp. 215±237. LEE D.S. (2010). Packaging and the microbial shelf life of food. In: Food Packaging and Shelf Life (Ed. by G.L. Robertson). Boca Raton, FL: CRC Press, pp. 55±79. LOPES P., SAUCHIER C.D., TEISSEDRE P.-L., GLORIES Y. (2007). Main routes of oxygen ingress through different closures into wine bottles. Journal of Agricultural and Food Chemistry 55: 5167±5170. MANZOCCO L., KRAVINA G., CALLIGARIS S., NICOLI M.C. (2008). Shelf life modelling of photosensitive food: the case of colored beverages. Journal of Agricultural and Food Chemistry 56: 5158±5164. OSSBERGER M. (2009). Migration from food contact materials. In: The Wiley Encyclopedia of Packaging Technology, 3rd edn (Ed. by K.L. Yam). New York: John Wiley & Sons, pp. 765±772. RIUDAVETS J., SALAS I., PONS M.J. (2007). Damage characteristics produced by insect pests in packaging film. Journal of Stored Products Research 43: 564±570. ROBERTSON G.L. (2006). Food Packaging Principles & Practice, 2nd edn. Boca Raton, FL: CRC Press. ROBERTSON G.L. (ed.) (2010a). Food Packaging and Shelf Life. Boca Raton, FL: CRC Press. ROBERTSON G.L. (2010b). Food packaging and shelf life. In: Food Packaging and Shelf Life, (Ed. by G.L. Robertson). Boca Raton, FL: CRC Press, pp. 1±16. ROBERTSON G.L. (2010c). Food quality and indices of failure. In: Food Packaging and Shelf Life, (Ed. by G.L. Robertson). Boca Raton, FL: CRC Press, pp. 17±30. ROTHENBACHER T., BAUMANN M., FUGEL D. (2007). 2-Isopropylthioxanthone (2-ITX) in food and food packaging materials on the German market. Food Additives and Contaminants Part A 24: 438±444. SHOTYK W., KRACHLER M. (2007). Contamination of bottled waters with antimony leaching from polyethylene terephthalate (PET) increases upon storage. Environmental Science & Technology 41: 1560±1563. SHOTYK W., KRACHLER M., CHEN B. (2006). Contamination of Canadian and European bottled waters with antimony from PET containers. Journal of Environmental Monitoring 8: 288±292. THELLEN C., SCHIRMER S., RATTO J.A., FINNIGAN B., SCHMIDT D. (2009). Co-extrusion of multilayer poly(m-xylylene adipimide) nanocomposite films for high oxygen barrier packaging applications. Journal of Membrane Science 340: 45±51. TORRIERI E., MAHAJAN P.V., CAVELLA S., GALLAGHER M.D.S., OLIVIERA F.A.R., MASI P. (2009). Mathematical modelling of modified atmosphere packaging: an engineering approach to design packaging systems for fresh-cut produce. In: Advances in Modeling Agricultural Systems (Ed. by P.J. Papajorgii & P.M. Pardalos). New York: Springer Science + Business Media, pp. 455±482. TSIGARIDA E., NYCHAS G.-J.E. (2006). Effect of high-barrier packaging films with different KIM G.T., PAIK H.D., LEE D.S.

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oxygen transmission rates on the growth of Lactobacillus sp. on meat fillets. Journal of Food Protection 69: 943±947. VAN BOEKEL M.A.J.S. (2008). Kinetic modeling of food quality: a critical review. Comprehensive Reviews in Food Science and Food Safety 7: 144±158. YAM K.L. (ed). (2009). The Wiley Encyclopedia of Packaging Technology, 3rd edn. New York: John Wiley & Sons.

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9 Smart packaging for monitoring and managing food and beverage shelf life P. S. Taoukis, National Technical University of Athens, Greece

Abstract: Cost effective monitoring of food and beverage products in the cold chain can be realized by time-temperature integrators (TTIs), inexpensive, active `smart labels' based on physicochemical, chemical or biological principles of operation and exhibiting an easily measurable response that integrates the temperature history of the product. Prerequisite for application of TTI is a correlation system to translate TTI response to the quality status of the food at any point of the chain. Basic structural elements of this system are validated kinetic models of TTI response and kinetics of the degradation indices of the food or beverage, such as predictive models of microbial growth. TTIs can serve as temperature monitors and tools for the optimization of stock rotation policies and cold chain management in general. As an example case study, a kinetic model for growth of spoilage bacteria in modified atmosphere packed (MAP) minced beef was used to select appropriate time-temperature integrators (TTIs) in order to monitor the meat product quality during refrigerated distribution. Key words: smart labels, time-temperature integrators, TTI, shelf life, kinetics, Arrhenius, cold chain, FIFO, SMAS.

9.1 Introduction: smart packaging ± time-temperature integrators (TTIs) In addition to the protection required for ensuring the safety and integrity of foods and beverages, current packaging technology aims to provide additional functionality. Smart packaging contributes to shelf life extension and provides valuable information about the quality and safety status of food products for better management of the food chain, reduction of food waste, and increased

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protection of the consumer. The `smartness' of packaging refers to its ability to communicate information about the requirements known to ensure product quality, such as package integrity (leak indicators) and time-temperature history of the product (time-temperature integrators, `TTIs'). Smart packaging can also give information on product quality directly. For example, freshness indicators provide a direct indication of the quality (Smolander, 2003) by providing a signal that is the result of a reaction between the indicator and specific chemical compounds or metabolites produced by the deteriorative mechanism (chemical or microbial) of the food or beverage. Such direct or indirect indicators of quality or safety of the products are based on the recognition and thorough study of the deteriorative phenomena that define spoilage processes of foods and beverages throughout their intended shelf life. For perishable food products and beverages, temperature is the main parameter that determines post-processing food quality. Shelf life can be shortened considerably if products are not stored and distributed appropriately at controlled temperatures throughout their entire life cycle, from production to consumption. Monitoring temperature is therefore an essential prerequisite for effective shelf life management. A cost-efficient way to monitor and continuously communicate the temperature conditions of individual food and beverage products throughout distribution is time-temperature integrators (TTIs). Based on having available reliable models of the product shelf life and information on the kinetics of a TTI's response, temperature can be monitored, recorded, and translated into its effect on quality, all the way from production to the consumer's table. Implementing a TTIbased system could lead to realistic control of the chill chain, optimization of stock rotation and reduction of waste, and efficient shelf life management. TTIs are inexpensive, active `smart labels' that can easily show measurable, time- and temperature-dependent changes that reflect the full or partial timetemperature history of a food product to which it is attached (Taoukis and Labuza, 1989). TTIs are based on mechanical, chemical, enzymatic or microbiological changes that are irreversible and expressed usually as a response in a visually quantifiable identifier in the form of mechanical deformation, color development, or color movement. The rate of change in the system underlying the TTI is temperature dependent, increasing with higher temperatures, in a manner similar to the deteriorative reactions responsible for food spoilage. Overall, the visible response of the TTIs reflect the cumulative time-temperature history of the food products they accompany. TTIs are an integral part of an interactive intelligent package and can serve as part of an active shelf life signal in conjunction with the `use-by date' on the label.

9.2 Principles of the application of time-temperature integrators (TTIs) for shelf life monitoring Since the potential for significantly improving quality and shelf life by monitoring and controlling temperature in the food cold chain was realized,

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reliable, cost-effective temperature history integrating systems have been sought. The first application of a `device' to indicate handling abuse dates from World War II, when the US Army Quartermaster Corps used an ice cube placed inside each case of frozen food. The deformation or disappearance of the cube indicated mishandling (Schoen and Byrne, 1972). The ideal TTI would have the following properties (Taoukis and Labuza, 2003): · It responds with a continuous time-temperature dependent change. · Its response is easily measurable and irreversible. · Its response mimics or can be correlated with the extent of quality deterioration and residual shelf life of the food or beverage. · It is reliable, giving consistent responses when exposed to the same temperature conditions. · It has low cost. · It is flexible, so that different configurations can be adopted for various temperature ranges (e.g., frozen, refrigerated, room temperature) with useful response periods of a few days as well as up to more than a year. · It is small, easily integrated as part of the food or beverage package and compatible with a high speed packaging process. · It has a long shelf life before activation and can be easily activated. · It is unaffected by ambient conditions other than temperature, such as light, RH and air pollutants. · It is resistant to normal mechanical abuses and its response cannot be altered. · It is nontoxic, posing no safety threat in the unlikely situation of product contact. · It is able to convey in a simple and clear way the intended message to its target, be that distribution handlers or inspectors, retail store personnel or consumers. · Its response is both visually understandable and adaptable to measurement by electronic equipment for easier and faster information, storage and subsequent use. For more than three decades, numerous TTI systems have been proposed, of which only a few reached the industrial prototype and even fewer the commercial application stage. The history of TTI development is outlined by Taoukis (2010). Systems that are currently available commercially are the following: · The CheckPointÕ TTI (VITSAB AB, MalmoÈ, Sweden) is an enzymatic system. This TTI is based on a color change caused by a pH decrease which is the result of a controlled enzymatic hydrolysis of a lipid substrate. Different combinations of enzyme-substrate and concentrations can be used to give a variety of response lives and temperature dependencies. Upon activation, the enzyme and substrate are mixed by mechanically breaking a separating barrier inside the TTI. Hydrolysis of the substrate (e.g., tricaproin) causes

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acid release (e.g., caproic acid), and the corresponding pH drop induces a color change in a pH indicator from deep green to bright yellow to orange-red (Fig. 9.1). A visual scale of the color change facilitates visual recognition and evaluation of the magnitude and significance of the color change. The continuous color change can also be measured with instrumentation and the results can be used in a shelf life management scheme. The Fresh-CheckÕ TTI (Temptime Corp, NJ, USA) (successor to FreshCheck of Lifelines) is based on a solid state polymerization reaction. The TTI function is based on the property of disubstituted diacetylene crystals (R± C=C±C=C±R) to polymerize through a lattice-controlled solid-state reaction, resulting in a highly colored polymer. The response of the TTI is the color change as measured in terms of a decrease in reflectance. The color of the `active' centre of the TTI is compared with the reference color of a surrounding ring (Fig. 9.2). Before using the indicators, which are active from the time of their production, the TTIs have to be stored at deep frozen temperatures, where change is very slow. The OnVuTM TTI (Ciba Specialty Chemicals & Freshpoint, SW) is a newly introduced solid state reaction-based TTI. It is based on the inherent reproducibility of reactions in crystal phase. Photosensitive compounds such as benzylpyridines are excited and colored by exposure to low wavelength light. This colored state reverses to its initial colorless state at a temperaturedependant rate (Fig. 9.3). By controlling the type of photochromic compound and the time of light exposure during activation, the length and the temperature sensitivity of the TTI can be set. This TTI can take the form of a photosensitive ink and be very flexible in its application. The (eO)Õ TTI (CRYOLOG, Gentilly, France) is based on a time-temperature dependent pH change that is expressed as color changes using suitable pH indicators. The pH change is caused by controlled microbial growth occurring in the gel of the TTI (Louvet et al., 2005; Ellouze et al., 2008). The parameters of the TTI are adjusted for select microorganisms by appropriate variations in the composition of the gel. The response of the TTI is claimed to mimic microbiological spoilage of the monitored food products, as its response is based on the growth characteristics of similar microorganisms, such as select patented strains of the micoorganisms Carbonbacterium piscicola, Lactobacillus fuchuensis, and Leuconostoc mesenteroides. The pH drop occurs with a color change of the pH indicator from green to red (Fig. 9.4). A visual scale of the color change can facilitate visual recognition and evaluation of the significance of the color change. The continuous color change can also be measured instrumentally and be used in a shelf life management scheme. The TT SensorTM TTI (Avery Dennison Corp., USA) is based on a diffusionreaction concept. A polar compound diffuses between two polymer layers and the change in its concentration causes the color change of a fluorescent indicator from yellow to bright pink (Fig. 9.5). The 3M Monitor MarkÕ (3M Co., St. Paul, MN, USA) is based on diffusion of proprietary polymer materials. A viscoelastic material migrates into a

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Fig. 9.1 Response scale of enzymatic CheckPointÕ TTI from green at time of application (left) to orange-red (right) indicating end of shelf life.

Fig. 9.2

Fig. 9.3

Polymer-based Fresh-CheckÕ TTI.

Solid state photochromic OnVuTM TTI.

Fig. 9.4 Response scale of Microbial TTI (eO)Õ.

Fig. 9.5

TT SensorTM TTI.

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Fig. 9.6

Diffusion-based 3M Monitor MarkÕ TTI.

light-reflective porous matrix at a temperature dependent rate. This causes a progressive change in the light transmissivity of the porous matrix and provides a visual response (Fig. 9.6). The TTI is activated by adhesion of the two materials that, before use, can be stored separately for a long period at ambient temperature. TTIs can be used to monitor the temperature exposure of food and beverage products during distribution, from production up to the time they are displayed at the retail level. Attached to product cases or bulk units, they give a measure of the preceding temperature conditions at selected control points. Information from TTIs can be used for continuous, overall monitoring of the distribution system, leading to identification and correction of weak links in the chain. Additionally, it serves as a confirmation of compliance with contractual requirements by the producer and distributor. It can guarantee that a properly handled product was delivered to the retailer, thus disallowing unsubstantiated rejection claims by the latter. The presence of the TTI itself would probably improve handling, serving as an incentive and reminder to the distribution personnel throughout the distribution chain of the importance of proper temperature storage. The same TTIs can be used as shelf life end-point indicators readable by the consumer and attached to individual products. Tests using continuous instrumental readings to define the end-point under constant and variable temperatures showed that such end-points could be reliably and accurately recognized by panellists (Sherlock et al., 1991). However, for a successful application of this kind there is a much stricter requirement that the TTI response matches the behavior of the food. In this way the TTI attached to individually packaged products can serve as active shelf life labeling in conjunction with, open date labeling. The TTI assures the consumer that the product was properly handled and indicates the remaining shelf life. Consumer surveys have shown that consumers can be very receptive to the idea of using TTIs on dairy products along with the date code (Sherlock and Labuza, 1992). Use of TTI can thus also be an effective marketing tool.

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9.3 Requirements and selection of time-temperature integrators (TTIs) for food and beverage products A number of experimental studies have sought to establish correlations between the response of specific TTIs and quality characteristics of specific products. They tested foods at different temperatures, plotting the response of the TTI vs time and the values of selected quality parameters of the foods before testing the statistical significance of the TTI response correlation to the quality parameters (Taoukis and Labuza, 2003). Such studies offer useful information but do not involve any modeling of the TTI response as a function of time and temperature. They are thus applicable only for the specific foods and the conditions that were used. Extrapolation to other similar foods or quality loss reactions, or even use of the correlation equations for the same foods at other temperatures or for fluctuating conditions, is not accurate. A kinetic modeling approach allows the potential user to develop an application scheme specific to a product and to select the most appropriate TTI without the need for extensive testing of the product and the indicator. This approach emphasizes the importance of reliable shelf life modeling of the food to be monitored. Shelf life models must be obtained with an appropriate selection and measurement of effective quality indices and based on efficient experimental design at isothermal conditions covering the range of interest. The applicability of these models should be further validated at fluctuating, nonisothermal conditions representative of the real conditions in the distribution chain. Similar kinetic models must be developed and validated for the response of the suitable TTI. Such a TTI should have a response rate with a temperature dependence, i.e. activation energy EA1, in the range of the EA of the quality deterioration rate of the food. The total response time of the TTI should be at least as long as the shelf life of the food at a chosen reference temperature. TTI response kinetics should be provided and guaranteed by the TTI manufacturer as specifications of each TTI model they supply. The basic principles of TTI modeling and application for quality monitoring are detailed by Taoukis and Labuza (1989) and Taoukis (2001). The shelf life of a food or beverage product evaluated by the measurement of a characteristic quality index, A, can be expressed as:    ÿEA 1 1 t 9:1 ÿ f …A† ˆ kt ˆ kref exp R T Tref where f …A† is the quality function of the food or beverage and k the reaction rate constant; t is an exponential function of inverse absolute temperature, T, given by the Arrhenius expression shown, where kref is the reaction rate constant at a reference temperature Tref, EA is the activation energy of the reaction that controls quality loss and R the universal gas constant. The activation energy of food-related chemical reactions and spoilage or microbial growth usually falls within 30± 120 kJ/mol. The reference temperature used is characteristic of the storage range of the food or beverage, e.g. for chilled products Tref ˆ 273 K can be used.

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Similarly to food or beverage quality, a response function F…X † can be defined for TTI such that F…X † ˆ kI t, with kI an Arrhenius function of T. The value of the functions, f …A†t at time t, after exposure at a known variable temperature exposure, T…t†, can be found by integrating Eq. 9.1. Introducing the term of the effective temperature Teff, which is defined as the constant temperature that results in the same quality value f …A†t , as the variable temperature distribution over the same time period, Eq. 9.1 gives:    Z t EA 1 1 t 9:2 k…T†dt ˆ kref exp ÿ ÿ f …A† ˆ R Teff Tref 0 For an indicator exposed to the same temperature distribution, T…t†, as the food/beverage product, and corresponding to an effective temperature Teff, the response function F…X † can be expressed as:    Z t EA 1 1 dt exp ÿ I ÿ F…X …t†† ˆ kIref R T Tref 0    EAI 1 1 t 9:3 ÿ ˆ kIref exp ÿ R Teff Tref where X is the measured response of the TTI and kIref and EAI are the TTI Arrhenius parameters. A generalized scheme, illustrated in Fig. 9.7, was used (Taoukis and Labuza, 1989; Giannakourou and Taoukis, 2003) translating TTI response to food shelf life status. Based on the developed algorithm, from the measured response X of the TTI at time t, the value of the response function is calculated, from which by solving Eq. 9.3, the Teff of the exposure is derived. The underlying requirement for the reliable prediction of the effective temperature of the food is that the

Fig. 9.7 Schematic representation of the systematic approach for applying TTI as quality monitors.

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activation energy of the food and the TTI, EA(food) and EA(TTI) should be similar (EA(food) ÿ EA(TTI) < 25 kJ/mol) (Taoukis, 2001).

9.4 Use of time-temperature integrators (TTIs) for shelf life management and optimization in the cold chain ± case study The information provided by the TTI smart labels, translated to remaining shelf life at any point of the cold chain can be used to manage shelf life by improving distribution control and a stock rotation practices. The approach currently used is the first in first out (FIFO) system according to which products received first and/or with the closest expiration date on the label are shipped, displayed and sold first. This approach aims to establish a `steady state' with all products being sold at the same quality level. The assumption is that all products have gone through uniform handling, thus quality is basically a function of time. The use of the indicators can help establish a system that does not depend on this unrealistic assumption. The objective is again a `steady state' situation with the least remaining shelf life products being sold first. This approach was coded LSFO (least shelf life first out). The LSFO reduces the number of rejected products and largely eliminates consumer dissatisfaction since the fraction of product with unacceptable quality at the time of use or consumption is minimized. LSFO aims to reduce the rejected products at the consumer end, by promoting, at selected decision making points of the product life cycle, those product units with the shorter shelf life, according to the response of the attached TTI (Taoukis et al., 1998; Giannakourou and Taoukis, 2003). LSFO allows the calculation of the actual remaining shelf life of individual product units at strategic control points of the chill chain. Based on the distribution of the remaining shelf life, decisions can be made for improved handling, shipping destination and stock rotation. A further improvement of the LSFO approach is a chill chain management system coded SLDS (shelf life decision system) (Giannakourou et al., 2001). Compared to LSFO, SLDS policy takes additionally into account the realistic variability of the initial quality state Ao of the product. The state of the TTI technology and of the scientific approach with regard to the quantitative safety risk assessment in foods allows the undertaking of the next important step: the study and development of a TTI-based management system that will assure both safety and quality in the food chill chain (Koutsoumanis et al., 2005; Tsironi et al., 2008). The development and application of such a system coded with the acronym SMAS, was the target of the multinational European research project `Development and Modeling of a TTI based Safety Monitoring and Assurance System (SMAS) for Chilled Meat Products' (project QLK1CT2002-02545, 2003-2006; http://smas.chemeng.ntua.gr). SMAS uses the information from the TTI response at designated points in the chill chain, ensuring that the temperature-burdened products reach consumption at acceptable quality level. Although SMAS is developed for meat products, the

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same principles can be effectively applied to the management of the chill chain of all chilled food or non-food perishable products. The effectiveness of the TTI-based SMAS system was evaluated by running a large number of chill chain scenarios using a Monte Carlo simulation approach. Field test experiments to demonstrate and quantify the improvement at the time of consumption in comparison to the conventional FIFO rule, were also conducted. The SMAS decision-making routine at a specified control point of the chill chain is based on the microbial growth that has potentially occurred within the period between production and arrival of the product at the control point. The growth is estimated based on the product's characteristics and the timetemperature history of the product using the appropriate predictive model. The above elements form the core program of integrated software that allows the calculation of growth in individual product units (e.g. small pallets, 5±10 kg boxes or single packs) at strategic control points in the chill chain. Based on the relative growth, it is possible to make decisions for optimal handling, shipping destination and stock rotation, aiming to obtain a narrow distribution of quality at the point of consumption. At a certain point in the chill chain, e.g. at a distribution center, product from the same initial shipment is split in half and is forwarded to two different retail markets, a close and a distant one that requires long transportation. The split could be random according to conventional, currently used FIFO practice or it can be based on the actual microbial growth of the product units and the developed decision system. For all units, the time-temperature history of the product monitored by TTI is input. This information fed directly into a portable unit with the SMAS software, is translated to microbial status, Nt, based on the growth models of the pathogen of concern. Having calculated Nt for all the n product units, a microbial load distribution for the products at the decision point is constructed. Based on the load of each product unit relative to this distribution, decisions about its further handling are made (Fig. 9.8). In order to simulate the results of the application of the developed SMAS system and quantitatively prove its effectiveness, the Monte Carlo method can be applied (Koutsoumanis et al., 2005). By taking into account the status of the product after production and various temperature distributions at different steps and alternative storage conditions, the distribution of the quality of the studied set of products at the final stage of consumption can be estimated. To confirm the effectiveness of SMAS appropriate experiments were also designed and conducted. One such experiment is described below to demonstrate the SMAS approach and the kind of information required for its application. A kinetic model for growth of spoilage bacteria in modified atmosphere packed (MAP) minced beef was developed and appropriate enzymic and photochromic TTI were studied and selected in order to monitor the meat product quality during distribution. The applicability of the SMAS system for chill chain management and optimization of the studied products was demonstrated (Taoukis et al., 2010).

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Fig. 9.8 Classification of products based on their microbial load and rationale of SMAS-based split at the decision point (where A and B are the two possible destinations, the distant and the local market).

In order to present the applicability of the selected TTIs as shelf life monitors for MAP minced beef, a realistic distribution scenario in the chill chain was simulated. The simulated chill chain conditions consisted of five different timetemperature scenarios with effective temperatures, Teff, between 2 and 15 ëC, conducted in programmable temperature cabinets. Products were split at a designated point in the simulated chill chain, 24 hours from packing (corresponding to the distribution center) and followed a simulated path to a `local' and a `distant' market. Products with TTIs were split based on TTI response translated into temperature history based on TTI kinetics. According to the TTI-based system, the more temperature burdened products were diverted to the `local' market, shortening their shelf life cycle in order to be consumed first (Giannakourou et al., 2001). Sixty packages without TTI were split randomly, according to conventional, currently used FIFO practice. Half of the samples were subsequently stored at 4 ëC and half at 8 ëC for different times simulating the different final consumption times of products sold at the local and the distant market (Fig. 9.9). Lactic acid bacteria (LAB) level at these times, assumed as the end of storage period and time of consumption, was calculated using the kinetic models from the study on MAP minced beef. LAB level for packs simulating transport to a local market was calculated at 12, 24 and 36 hours and for packs simulating transport to the distant market was calculated at 48, 72 and 96 hours after split. The LAB loads of the overall 60 SMAS managed packs with TTI were compared to the LAB loads of the 60 FIFO managed packs without TTI. The response of the enzymic CheckPointÕ TTI, type M was described by the normalized …a ‡ b† value of the CIELAB scale (Eq. 9.4): X1 ˆ

…a ‡ b† ÿ …a ‡ b†min …a ‡ b†max ÿ …a ‡ b†min

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9:4

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Field test simulated chill chain conditions.

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Equation 9.4 represents the M-type TTI response, X1 , which, when plotted as a function of time, has a sigmoidal shape, of specific pattern, that was described by the following logistic type equation: 1   9:5 X1 ˆ k1I ÿ t 1 ‡ exp k2I where k1I and k2I are functions of storage temperature and enzyme concentration. Note that 1/k2I is the exponential rate constant, i.e. the slope of the phase in which the response of the TTI changes exponentially with time (Fig. 9.10). Values of k1I and k2I at each temperature were determined, by non-linear regression analysis (Sigma Plot 8.0). The response rate constants k1I and k2I showed the same temperature dependence expressed by the same value of

Fig. 9.10 (a) Response of Check Points TTIs at different enzyme concentrations and isothermal storage at 5 ëC (experimental points and potential fit) · M-50U,  M-100U and t M-200U, (b) total response time of Check Point TTIs as a function of temperature at different enzyme concentrations (ÐÐ 50U, ± ± ± 100U,


200U) calculated by the composite model.

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activation energy of the Arhenius equation (Ea ˆ 96±107 kJ/mol). The value of k1 was expressed as a function of enzyme concentration and a composite model was developed that can determine the TTI response at a selected timetemperature scenario and known enzyme concentration: 1    X ˆ F…XC † ˆ 9:6 0 1 Ea 1 1 ÿB1 ÿt k C  exp ÿ B 1;ref C R T Tref     C 1 ‡ expB @ A E 1 1 a k2;ref  C ÿB2  exp ÿ R T Tref where T is the absolute temperature (K), Ea is the activation energy (kJ/mol), R is the universal gas constant, Tref is a reference temperature (4 ëC), C is the enzyme concentration (50±200 U) and B1,2 are constants. The value of Ea for all different enzyme concentrations of the TTI was defined at 105:5  15:8 kJ/mol. The visual color change of the photochromic OnVu TTIs was adequately described by the
E value (Eq. 9.7).
E was modelled by an exponential decay function with time (Eq. 9.8) as representatively shown in Fig. 9.3. q 9:7
E ˆ …L ÿ Lmax †2 ‡ …a ÿ a2min † ‡ …b ÿ bmax †2
E ˆ
Eo exp…ÿk
t†

9:8

where k is a function of initial charging time, tc, and storage temperature T (K). The Lmax, amin and bmax values are the values of the `white' colored, uncharged TTI (Lmax ˆ 80, amin ˆ ÿ3.5 and bmax ˆ 1.2). The end-point of the OnVu TTI was determined at
E ˆ 11:9 (Lf ˆ 69, af ˆ ÿ5 and bf ˆ ÿ6), corresponding to the visual end-point. The response rate constants were plotted as a function of temperature in Arrhenius plots. The total response time (time from activation to end-point) of the TTIs is shown in Fig. 9.11. Based on the results of the testing of the TTI, a composite model that allows the calculation of the response rate, k, at any selected charging time was developed. The model was based on the observation that the response rate k at any temperature is a power function of the charging time, tc. It was also observed that the effect of charging time on the Ea values of the TTIs is within the statistical variation. Thus the Ea value can be assumed not to change with charging time. The form of the composite model is expressed as:    ÿEa 1 1 9:9
ÿ k ˆ kref ;Tref ;1s
tcÿA
exp R T Tref where T is the absolute temperature (K), Ea is the activation energy (kJ/mol), R is the universal gas constant, Tref is a reference temperature (4 ëC), kref,Tref,1s is the TTI response rate constant at Tref (with charging time tc ˆ 1 s). The composite model allows the calculation of the charging time needed in order to achieve the required color change rate and response time for the TTI in order to

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Fig. 9.11 Response of OnVu TTI at different charging times, tc (n 1 s, s 2 s, l 3 s) and isothermal storage at 5 ëC (experimental points and potential fit), (b) total response time of OnVu TTI as a function of temperature at different charging times, tc (ÐÐ 0.5 s,


1 s, ±
±
2 s, ± ± 3 s and === 4 s) calculated by the composite model.

better match the respective kinetics of the product. The activation energy value, Ea, for all different charging levels of the TTI was defined at 122  16:6 kJ/mol. Lactic acid bacteria were used as the spoilage index for MAP minced beef. Starting from an initial level of 103 CFU/g in raw fresh meat, LAB reached high populations of 107±108 CFU/g at the end of the storage period. The dominance of LAB in the CO2-rich atmosphere has been repeatedly reported in the literature for meat and meat products (Borch et al., 1996; Devlieghere et al., 1998; Mataragas et al., 2006; Nychas et al., 2008; Vaikousi et al., 2009). The experimental data for LAB of the MAP minced beef are shown in Fig. 9.12(a) with the fitted growth curves. The end of shelf life, i.e. the limit of sensory acceptability, was correlated to a 7 logCFU/g level, in agreement with published data (Borch et al., 1996; Devlieghere et al., 1998; Mataragas et al., 2006; Nychas et al., 2008; Vaikousi et al., 2009). The specific growth rates (k) of LAB

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Fig. 9.12 (a) Growth of lactic acid bacteria on MAP minced beef packed at ± ± 0 ëC, ÐÐ 2.5 ëC,


5 ëC and ±
±
10 ëC, (b) shelf life (h) is MAP minced beef at different storage temperatures, calculated using the Arrhenius model, together with the matching TTI response curves (dotted lines:


OnVu TTI, tc ˆ 2 s and dashed lines: ± ± ± Check Point TTI M-50U).

were modeled as a function of temperature using the Arrhenius equation. The activation energy value was defined at 122:5  14:0 kJ/mol and the growth rate of LAB at the reference temperature (4 ëC), kref, was 0:0171  0:0014 hÿ1. The applicability of the developed kinetic equations was validated at variable time-temperature profiles. The growth rate of the LAB predicted by the Arrhenius model, for the Teff of the profile, was compared with the rate obtained by the non-isothermal experiment. The relative error value was below the limit of 20% that is used in the literature as the criterion of applicability (Dalgaard et al., 1997; Gougouli et al., 2008), indicating that the Arrhenius model can describe satisfactorily the growth of LAB in MAP minced meat during refrigerated storage in the range of 0±10 ëC. To select the appropriate charging time, based on the kinetic studies of MAP minced beef and the response profiles of the TTIs, the composite models (Eq. 9.9) can be solved. To obtain an exact match between the product shelf life and response time of the TTI at a reference temperature in the chilled range (e.g. 4 ëC), it was calculated that charging time of 2 s for the OnVu TTI and 50 U for

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the M-type CheckPoint TTI could lead to suitable TTIs for monitoring the quality of MAP minced beef during refrigerated storage. In Fig. 9.12(b) the shelf life of MAP minced beef is shown together with the matching TTI total response time curves. If the products are stored at very low temperatures of 0±2 ëC the end of shelf life will be determined and limited by the expiration date on the food package. On the other hand, if abuse temperatures of 6±10 ëC prevail, then the TTI will conservatively signal poor quality products slightly before the end of shelf life. The SMAS system and FIFO approach were applied to MAP minced beef. The effectiveness of the SMAS system was evaluated based on the level of lactic acid bacteria at the end of storage. Samples with LAB levels above 7 logCFU/g were characterized as spoiled. The initial level of LAB was 3.1 logCFU/g. Using the FIFO approach, 12% of 60 samples ± `local' and `distant' promoted ± reached the spoilage level at the end of the storage period. When SMAS-based sorting is applied, only 3% of the 60 samples reached the spoilage level, significantly reducing the number of rejected products before the `time of consumption'. In Fig. 9.13 the observed LAB log counts of MAP minced beef samples at the `time of consumption' are depicted. In total (for both `local' and `distant' markets), the SMAS system resulted in a reduction in the number of spoiled products. SMAS uses the information from the TTI, at appropriate points in the chill chain (e.g., at a central distribution center), to make decisions for the further management of products based on their temperature history and hence microbial status and remaining shelf life of the products (Fig. 9.5b). The conducted simulated field test demonstrates the applicability of the TTI-based SMAS approach to improve the meat chill chain. The overall field test result showed that SMAS-based sorting at a decision point resulted in more uniform acceptable quality at the time of consumption in comparison to the conventional FIFO approach. In a previous study, growth of LAB and Listeria monocytogenes in fresh ground lamb (MAP) was modeled (Taoukis et al., 2006). Growth was measured on naturally contaminated products inoculated with the pathogen, at isothermal and dynamic conditions from 0 to 15 ëC. Enzymatic TTI with suitable response was also modeled. Some 120 products of MA packed ground lamb (20% CO2) were then tested, on half of which TTIs were attached at packing. All products were stored, in programmed cabinets simulating the conditions of the real chill chain to the consumption point. At the decision point, at 64 h from packing, the products were split in half and were stored for three different short times and three longer times (local and distant market scenarios). The products without TTI were split randomly. Split and further handling of products with TTI was based on their integrated temperature history and the SMAS scheme. According to the final microbiological measurements of all products at `consumption time', the spoilage profile of the products with TTI was significantly improved. A total of 22% of randomly handled samples were spoiled at consumption time (LAB > log8) compared to less than 6% handled with the SMAS approach. Respectively, 28% exceeded a set limit for Listeria compared to less than 3% handled with

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Fig. 9.13 (a) Distribution of the lactic acid bacteria log counts and (b) distribution of the remaining enzyme activity based on FIFO and PMAS approach.

SMAS. These experimental results demonstrate the applicability of the TTIbased system to optimize quality and reduce risk.

9.5

Future trends

TTI-based syatems could replace the current FIFO practice and lead to risk minimization and quality optimization by improving distribution logistics and management of the food chill chain. It improves stock rotation in selected points of the chill chain. It ensures that the temperature abused products are consumed before they reach unacceptable risk. When recommended chill chain conditions are maintained, TTI-based practices do not differ from the FIFO practice. However, in case of incidental temperature abuse, TTI-based systems can manage the chain by diverting abused products so that final rejection and risk are minimized. Cold chain optimization and effective management will be a central issue in research, industrial practices, and regulatory efforts, as industry continuously

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strives to deliver high quality foods and other perishable items to consumers. Integrated systems, like the proposed SMAS based on the availability of quality data and temperature history of individual product units, will be applied and validated in practice, and TTIs can be combined with RFID technology to supplement the current traceability requirements mandated by regulation or developed by industry initiatives.

9.6

Acknowledgements

This chapter includes results partly carried out with the financial support of the Commission of the European Communities, specific RTD program `Quality of Life and Management of Living Resources', Key Action 1 ± Health Food and Environment, Project No. QLK1-CT2002-02545 (http://smas.chemeng.ntua.gr), FP6 Collective Research Project COLL-CT-2005-012371 (http:// www.freshlabel.net) and FP7 Capacities Project IQ-Freshlabel (G.A. no: 243423).

9.7

References

(1996), Bacterial spoilage of meat and cured meat products. International Journal of Food Microbiology 33: 103±120. DALGAARD P, MEJLHOLM O, HUSS HH (1997), Application of an iterative approach for development of a microbial model predicting the shelf-life of packed fish. International Journal of Food Microbiology 38: 169±179. DEVLIEGHERE F, DEBEVERE J, VANIMPE J (1998), Effect of dissolved carbon dioxide and temperature on the growth of Lactobacillus sake in modified atmospheres. International Journal of Food Microbiology 41: 231±238. BORCH E, KANT-MUERMANS ML, BLIXT Y

ELLOUZE M, PICHAUD M, BONAITI C, COROLLER L, COUVERT O, THUAULT D, VAILLANT R

(2008), Modelling pH evolution and lactic acid production in the growth medium of a lactic acid bacterium: application to set a biological TTI. International Journal of Food Microbiology 128: 101±107. GIANNAKOUROU MC, TAOUKIS PS (2003), Application of a TTI-based distribution management system for quality optimisation of frozen vegetables at the consumer end. Journal of Food Science 68(1): 201±209. GIANNAKOUROU MC, KOUTSOUMANIS K, NYCHAS GJE, TAOUKIS PS (2001), Development and assessment of an intelligent shelf life decision system for quality optimization of the food chill chain. Journal of Food Protection 64(7): 1051±1057. GOUGOULI M, ANGELIDIS AS, KOUTSOUMANIS K (2008), A study on the kinetic behavior of Listeria monocytogenes in ice cream stored under static and dynamic chilling and freezing conditions. Journal of Dairy Science 97: 523±530. KOUTSOUMANIS K, TAOUKIS PS, NYCHAS GJE (2005), Development of a Safety Monitoring and Assurance System (SMAS) for chilled food products. International Journal of Food Microbiology 100: 253±260. LOUVET O, THUAULT D, VAILLANT R (2005), Method and device for determining whether or not a product is in condition to be used or consumed. Patent. International Publication Number WO 2005/026383 A1. MATARAGAS M, DROSINOS EH, VAIDANIS A, METAXOPOULOS I (2006), Development of a

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predictive model for spoilage of cooked cured meat products and its validation under constant and dynamic temperature storage conditions. Journal of Food Science 71: M157±M167. NYCHAS GE, SKANDAMIS PN, TASSOU CC, KOUTSOUMANIS KP (2008), Meat spoilage during distribution. Meat Science 78: 77±89. SCHOEN HM, BYRNE CH (1972), Defrost indicators: many designs have been patented yet there is no ideal indicator. Food Technology 26(10): 46±50. SHERLOCK M, LABUZA TP (1992), Consumer perceptions of consumer time-temperature indicators for use on refrigerated dairy foods. Journal of Dairy Science 75: 3167± 3176. SHERLOCK M, FU B, TAOUKIS PS, LABUZA TP (1991), Systematic evaluation of time temperature indicators for use as consumer tags. Journal of Food Protection 54 (11): 885±889. SMOLANDER M (2003), The use of freshness indicators in packaging. In Ahvenainen R (ed.), Novel Food Packaging Techniques. Woodhead Publishing Ltd, Cambridge, 127±143. TAOUKIS PS (2001), Modelling the use of time temperature indicators in distribution and stock rotation. In Tijskens L, Hertog M, Nicolai B (eds), Food Process Modelling, Woodhead Publishing Ltd, Cambridge. TAOUKIS PS (2010), Commercialization of active food packaging (Time-Temperature Integrators, `TTIs'). In Doona C, Kustin K, Feeherry F (eds), Case Studies in Novel Food Processing Techniques. Woodhead Publishing Ltd, Cambridge. TAOUKIS PS, LABUZA TP (1989), Applicability of time temperature indicators as shelf life monitors of food products. Journal of Food Science 54: 783±788. TAOUKIS PS, LABUZA TP (2003), Time-temperature indicators (TTI). In Ahvenainen R (ed.), Novel Food Packaging Techniques. Woodhead Publishing Ltd, Cambridge, 103±126. TAOUKIS PS, BILI M, GIANNAKOUROU M (1998), Application of shelf life modeling of chilled salad products to a TTI based distribution and stock rotation system. In Tijskens LMM, Hertog MLATM (eds), Proceedings of the International Symposium on Applications of modeling as an innovative technology in the Agri-food chain. Acta Horticulturae, 476: 131±140. TAOUKIS PS, KATSAROS G, GOGOU E, TSIRONI T, TSEVDOU M (2006), Application and Experimental Validation of the TTI Based Chill Chain Management System SMAS for MAP Lamb Products. Food Micro 2006: The 20th International ICFMH Symposium Food safety and food biotechnology: diversity and global impact International Committee on Food Microbiology and Hygiene (ICFMH), 29 August±2 September 2006, Bologna, Italy, Book of Abstracts, p. 529. TAOUKIS PS, TSIRONI TH, GIANNOGLOU M, METAXA I, GOGOU E (2010), Historical review and state of the art in time temperature integrator (TTI) technology for the management of the cold chain of refrigerated and frozen foods. In Proceedings of Cold Chain Management, 4th International Workshop, Bonn, 27±28 September. TSIRONI T, GOGOU E, VELLIOU E, TAOUKIS PS (2008), Application and validation of the TTI based chill chain management system SMAS (Safety Monitoring and Assurance System) on shelf life optimization of vacuum packed chilled tuna. International Journal of Food Microbiology 128: 108±115. VAIKOUSI H, BILIADERIS CG, KOUTSOUMANIS KP (2009), Applicability of a microbial time temperature indicator (TTI) for monitoring spoilage of modified atmosphere packed minced meat. International Journal of Food Microbiology 133: 272±278.

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10 Food storage trials: an introduction C. M. D. Man, London South Bank University, UK

Abstract: This chapter reviews definitions of shelf life and key concepts such as `best before' and `use by' dates. It reviews key factors affecting food spoilage and deterioration. It then goes on to discuss the principles and practices of shelf life testing and storage trials to establish accurate shelf life dates which manufacturers can use in food labelling. Key words: shelf life, stability, food spoilage, best before dates, use by dates, storage trials.

10.1

Introduction

Because of their perishable nature, all foods (taken to mean food and beverages) deteriorate throughout storage, albeit at different rates. For this and other related reasons, the behaviour of foods during storage is of immense interest to the consuming public as well as to all those who make, prepare, handle, buy, sell and distribute foods. The period during which a food remains safe and enjoyable to eat has been called its shelf life, which is now a legal term within the EU. Regulation (EC) No. 852/2004 of the European Parliament and of the Council on the hygiene of foodstuffs, implemented in England along with other associated regulations as the Food Hygiene (England) Regulations 2006, requires food business operators to adopt as appropriate a number of specific hygiene measures (Article 4(3(a))), which include `compliance with microbiological criteria for foodstuffs' as laid down in Commission Regulation (EC) No. 2073/ 2005 on microbiological criteria for foodstuffs. The latter regulation defines `shelf life' as `either the period corresponding to the period preceding the `use

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by' or the minimum durability date, as defined respectively in Articles 9 and 10 of Directive 2000/13/EC, the most recent European labelling Directive. A much more useful and informative definition of shelf life of food has been available for some time (IFST, 1993): it is the period of time during which the food will · remain safe; · be certain to retain its desired sensory, chemical, physical, microbiological and functional characteristics; · where appropriate, comply with any label declaration of nutrition data, when stored under the recommended conditions. Clearly, safety and quality are the two main aspects of shelf life of food, and food safety must always take priority over quality as it is both a fundamental and a legal requirement. According to Article 14 of the General Food Law Regulation (EC) 178/2002, food must not be placed on the market if it is unsafe. Food is deemed to be `unsafe' if it is considered: · injurious to health; · unfit for human consumption. Food can be injurious to health by virtue of the presence of a hazard, which may be microbiological, chemical or physical in nature. Article 14(4) of the Regulation goes on to say: in determining whether any food is injurious to health, regard shall be had: (a) not only to the probable immediate and/or short-term and/or longterm effects of that food on the health of a person consuming it, but also on subsequent generations; (b) to the probable cumulative toxic effects; (c) to the particular health sensitivities of a specific category of consumers where the food is intended for that category of consumers. In terms of `unfitness' for human consumption the central concept is unacceptability. Food can become unfit for human consumption because of contamination, whether by foreign objects (e.g., glass, plastics), by chemicals (e.g., cleaning chemicals, agrichemical residues) or by microbes causing putrefaction, decomposition or decay. Consequently, there should be little doubt in the mind of a food business operator as to what safe food means. Quality, on the other hand, is not usually regulated by law unless it has to do with compositional/marketing standards. British Standard BS EN ISO 9000:2005 (Quality management systems ± Fundamentals and vocabulary) defines quality as `degree to which a set of inherent characteristics fulfils requirements'. In practice, therefore, it is the job of every food business operator to establish as fully as possible the requirements of its target consumer and to ensure that the characteristics of its food product in question reflect and fulfil those require-

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ments consistently. The need to provide an acceptable, reliable and consistent product shelf life represents an obligation as well as a challenge to every food business operator. In the UK the legal responsibility to assign an acceptable shelf life is contained in the Food Labelling Regulations 1996 as amended, such that pre-packed foods that are required to carry a durability indication (i.e., most foods) must indicate either: · `Best before' followed by the date up to and including which the food can reasonably be expected to retain its specific properties if properly stored, or · `Use by', for foods which are, from the microbiological point of view, highly perishable and in consequence are likely after a short period to constitute an immediate danger to health, followed by the date up to and including which the food, if properly stored, is recommended for use. All such declarations must by followed by an indication of any storage conditions that need to be observed if the unopened food is to retain its specific properties up to the date indicated. This is understandable as all foods are perishable, they will naturally deteriorate in an unexpected manner, or faster or both, if they are stored under harsher conditions (usually warmer and more humid) for which they are not intended. The decision as to whether a food requires a `use by' date is one for those who manufacture, pack and therefore mark it in the first place. Useful guidance, however, is available and it has been suggested that the following food groups, essentially all chilled foods, are likely to require a `use by' date (Crawford, 1998): · · · ·

dairy products, e.g. fresh cream-filled desserts cooked products, e.g. ready-to-heat meat dishes smoked or cured ready-to-eat meat or fish, e.g. hams, smoked salmon fillets prepared ready-to-eat foods, e.g. sandwiches, vegetable salads such as coleslaw · uncooked or partly cooked savoury pastry and dough products, e.g. pizzas, sausage rolls · raw ready-to-cook products, e.g. uncooked products comprising or containing either meat, poultry or fish, with or without raw prepared vegetables · vacuum or modified atmosphere packs, e.g. raw ready-to-cook duck breast packed in modified atmosphere In order to arrive at an acceptable, reliable and reproducible shelf life, a food business operator will need to have answers for the following questions: 1. Is my product safe to eat throughout its intended shelf life? (Essentially, an unsafe food product has no useful/meaningful shelf life.) 2. How long will my product last for before it becomes unacceptable to the target consumer? In order to answer these separate and yet related questions satisfactorily, a food business operator needs to have sufficient knowledge about its product, in

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particular, a thorough understanding of the shelf life limiting mechanism of deterioration and factors that influence it. Typically, shelf life is determined by conducting shelf life studies commonly but not exclusively by experimentation using storage trials under defined conditions. The final shelf life that is ultimately assigned may be decided dependent upon commercial considerations such as product category and associated image perceptions, and the margin of safety required. This shelf life is then expressed legally either as a `use by' or `best before' date. Such is the importance of the legal requirement to set appropriate and accurate date marks that the UK Food Standards Agency launched a consultation on 25 March 2010 on the latest revision of its existing guidance on the application of date marks to food (FSA, 2010).

10.2

Food deterioration and spoilage

Changes in the characteristics of food inevitably occur during its storage. With very few exceptions such as cheeses and wines, these changes result in deterioration and spoilage of the food to the point when it is no longer acceptable to the target consumer and are usually classified as: · microbiological · non-microbiological ± biochemical ± chemical ± physical ± temperature-related. When they happen these changes effectively constitute the underlying mechanism(s) of deterioration and spoilage of the food in question, which if allowed to continue, will either singly or in combination cause the food to be rejected by the consumer. Figure 10.1 provides a picture of the progression of these changes, which cause the food to deteriorate and spoil during storage. In practice, a number of such changes can take place simultaneously or in sequence; in many cases, though, a particular type of change is likely to be the predominant one, which turns out to be the shelf life limiting change. The primary aim of a shelf life experiment, therefore, is to learn about these changes as they impact on the behaviour of the food during storage. As time goes on, a point is eventually reached when the food becomes unacceptable to the consumer, which marks the end of its shelf life and which has to be determined. A brief review of the different types of changes that can occur in food is given in the following sections. 10.2.1 Microbiological changes Besides the initial load or level of contamination, microbial growth depends on a number of well-known factors, which have been summarised by Mossel (1971):

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Fig. 10.1 A picture of changes in food during storage.

· intrinsic properties of the food (e.g., nutrients, pH, total acidity, water activity, structure, presence of preservatives and/or natural antimicrobials, redox potential) · extrinsic factors (e.g., environmental temperature, relative humidity, gaseous atmosphere) · processing factors (e.g., heat destruction, freezing, packaging) · implicit factors (e.g., physiological attributes such as specific growth rate of the micro-organisms and microbial interactions). Micro-organisms, be they pathogenic or spoilage, share the same factors for growth. However, the growth of pathogenic organisms in food such as Salmonella species and Listeria monocytogenes is not necessarily accompanied by changes in appearance, smell, and even taste or texture that human senses can detect, posing serious health concerns. On the other hand, growth of spoilage organisms in food is often associated with signs that can readily be recognised as changes in sensory properties, for example, visual mould growth and production of objectionable odours and flavours. Examples of some common food spoilage organisms and changes they cause in food are given in Table 10.1. 10.2.2 Biochemical and chemical changes Raw materials from which practically all food products are manufactured are biological in origin, and it may be unappreciated by the average consumer that food is composed of chemicals. Some biochemical and/or chemical changes in food are therefore inevitable. These changes can occur arising from reactions within the food or from reactions between food components and external species or factors such as oxygen or light respectively. In packaged food, interactions, many of which are chemical in nature, can occur between packaging and the food. With a few exceptions such as maturing of wines and cheeses, and post-harvest ripening of fruits, most biochemical and chemical changes in food are undesirable, deteriorative and effectively shelf life limiting.

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Table 10.1 Examples of food spoilage organisms and changes they cause in food (adapted from Huis in't Veld, 1996) Food spoilage organisms

Changes in food

Gram-negative rod-shaped bacteria, e.g. Pseudomonas spp.

Production of off-flavours, visible slime and pigmented growth in red meat, fish, poultry, milk and dairy products

Gram-positive spore-forming bacteria e.g. Bacillus and Clostridium spp.

`Sweet curdling' and `bitty cream' in milk (Bacillus cereus) Gas production ± `late blowing' of hard cheeses (Clostridium spp.)

Other Gram-positive bacteria, e.g. Brochothrix thermosphacta

Off-flavour development in MAP and VP meat products

Lactic acid bacteria, e.g. Lactobacillus, Streptococcus, Leuconostoc and Pediococcus spp.

Slime formation, generation of CO2, production of lactic acid, causing a drop in pH and off-flavour development in some dairy products

Yeasts and moulds

Production of soft rot in fruit, pigmented growth in baked goods, production of acid, gas or alcohol in some soft drinks and jams, development of off-odours in beer

Examples of some biochemical and chemical changes in food are given in Table 10.2. 10.2.3 Physical changes Significant transfer of moisture (or water vapour) and/or other substances in or out of food can often cause deteriorative changes in food. These changes are very common and can affect short-, medium- as well as long-life products. Most of these changes are important from a product quality point of view while a few can have food safety implications such as in the case of migration of chemical components from the packaging material into food, particularly when the latter has a long shelf life. In the EU, both overall and specific migrations of chemical components from packaging materials into food are controlled by Regulation (EC) No. 1935/2004 on Materials and Articles intended to come into contact with Food. Examples of some physical changes in food are given in Table 10.3. 10.2.4 Temperature-related changes Temperature, arguably the most important environmental factor, affects all of the above changes and not always in the same way. Micro-organisms, pathogens and spoilage organisms, exhibit a range of minimum growth temperatures below which they cannot grow. For instance, temperature selects for the types of organisms that can survive and grow at refrigerated temperatures. Table 10.4

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Table 10.2 Some biochemical and chemical changes in food (adapted from Man, 2002) Biochemical/chemical reactions

Changes in food

Oxidative rancidity, e.g. oxidation of fats and oils involving a catalyst such as copper ions; oxidation of fats and oils initiated by light in the presence of a photo-sensitizer such as myoglobin; oxidation of fats and oils catalysed by the enzyme lipoxygenase

Rancidity (off-flavour development) in fatty food and food products

Oxidation-reduction reactions with atmospheric oxygen

Degradation and loss of vitamins C, B1, A and E

Hydrolysis of aspartame (sweetener)

Reduction in sweetness of calorie-free/ low-calorie soft drinks

Non-enzymic browning (Maillard reaction)

Browning (discoloration) in dehydrated fruits and vegetables, instant potato powder, dried egg white and dried milk products

Enzymic browning

Browning in pre-cut vegetables and fresh fruit salads

Chemical breakdown caused by light

Colour fading

Electrochemical reactions between foods and tinplate cans

Gas production, discoloration of food, etc., depending on the food and type of metal can

Table 10.3

Examples of physical changes in food (adapted from Man, 2002)

Product

Quality change

Underlying mechanism

Fresh vegetables

Wilting

Moisture loss

Biscuits

Softening, loss of crunchiness

Moisture gain

Carbonated soft drinks

Loss of fizziness

Loss of carbonation (CO2) to the environment

Orange juice

Reduction in citrus flavour intensity

Sorption of limonene and other aroma compounds by the packaging material

Dressed salads, e.g. coleslaw

Changes in texture of vegetables, changes in consistency of dressing

Moisture migration from vegetables to dressing

Chilled composite desserts, Gradual loss of distinctive e.g. trifle layers

Bleeding of colours, migration of moisture/syrup

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Table 10.4 Some pathogenic micro-organisms known to be associated with chilled foods (Betts et al., 2004; Voysey, 2007) Micro-organism

Minimum growth temperature (ëC)

Salmonella Staphylococcus aureus Bacillus cereus (spores/heat resistant) Clostridium botulinum (non-proteolytic B, E, F) Listeria monocytogenes Escherichia coli Escherichia coli (O157:H7) Vibrio parahaemolyticus Yersinia enterocolitica Aeromonas hydrophila

4 5.2 (10 for toxin) 4 3 ÿ0.4 7±8 6.5 5 ÿ1.3 ÿ0.1

gives a list of pathogenic micro-organisms and their minimum growth temperatures that are known to be associated with chilled foods. In consequence, compliance with the relevant temperature control requirements, i.e., a maximum storage temperature of 8 ëC, of the current food hygiene regulations (TSO, 2006) is essential in assuring the microbiological safety and stability of chilled foods. The effect of elevating temperature on many chemical reactions, and hence potential adverse chemical changes in food during storage, is well known; increasing the temperature generally increases the rate of chemical reactions by a factor of 10. This empirical relation between the rate of reaction (k) and temperature was first proposed by Svante Arrhenius in 1889:   Ea k ˆ A exp ÿ RT where A ˆ the frequency factor (or pre-exponential factor), Ea ˆ the activation energy, R ˆ the universal gas constant (0.001987 kcal molÿ1 Kÿ1 or 8.31 J molÿ1 Kÿ1), and T ˆ the absolute temperature in K (kelvin). Converting this relationship to logarithmic form, the following is obtained: Ea log10 k ˆ log10 A ÿ 2:303RT or ln k ˆ ln A ÿ

Ea RT

In theory, a plot of lnk versus the reciprocal of absolute temperature should give a straight line, the slope of which is the activation energy divided by the gas constant (Ea/R). A graph of ln k against 1/T is called an Arrhenius plot; many chemical reactions have been found to show Arrhenius behaviour, i.e. their Arrhenius plots show a straight line. Thus, by studying a reaction and measuring k at two or three different temperatures, one could extrapolate with a straight line to a lower temperature and predict the rate at this temperature. This is the

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basis of accelerated storage trials for shelf life at an elevated temperature. Often though, reactions in real food systems are far more complex than can be easily modelled by the Arrhenius equation. For certain non-microbiological changes in food, lower temperatures do not automatically mean lower rates of change or insignificant changes. For instance, bread stales fastest at refrigerated temperatures; increased temperatures can slow the development of bread staling, which is thought to be due to re-distribution of moisture and retrogradation of starch molecules. Fluctuating temperatures can cause ice crystal formation in frozen foods such as ice cream, and changes in fat crystallinity are promoted by fluctuating storage temperature, which encourage bloom to develop in chocolate. 10.2.5 A summary The changes that bring about deterioration and spoilage in food as outlined in the previous sections can be summarised as in Fig. 10.2. Microbiological and non-microbiological changes can take place in parallel or in sequence. More than one type of change can take place at the same time, and changes in many foods can be complex. Nevertheless, a number of well-known mechanisms broadly classified as microbiological and non-microbiological changes can be used to explain deterioration, spoilage and subsequent loss of shelf life in many food products (Man, 2004): · microbiological changes · non-microbiological changes ± biochemical and chemical changes including light-induced changes ± moisture and/or water vapour transfer leading to gain or loss ± physical transfer of substances such as oxygen, odours or flavours other than moisture and/or water vapour ± other mechanisms or changes such as loss of pack integrity. The question as to which of the above changes and indeed what predominant change will take place in a food, will depend on many shelf life influencing

Fig. 10.2

A basic model for food deterioration and spoilage (Ellis and Man, 2000).

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factors, which can be categorised into product and external factors (IFST, 1993). Product factors are related to the composition, make-up and properties of the final product. They include the following: · · · · · · · ·

raw materials (their microbiology and biochemistry) product composition and formulation (e.g., use of preservatives) food structure (i.e., homogeneous versus heterogeneous) product assembly (i.e., composite, multi-component product) pH value, and total acidity including type of acid water activity (aw) redox potential (Eh) oxygen availability.

External factors are those that the final product is subject to or comes into contact with as it moves through the food chain up to the point of consumption. They include the following: · hygienic conditions during preparing, processing, storage and distribution · type and extent of processing (e.g., time-temperature combination of heat treatment) · conditions within packaging (i.e., composition and pressure of atmosphere) · packaging materials and system · exposure to light (UV and IR) during processing, storage and distribution · temperature control throughout the food chain · relative humidity during processing, storage and distribution · consumer handling, preparation and use.

10.3

Storage trials

The most common and direct way of determining shelf life is to carry out experimentally storage trials of the product in question under conditions that simulate those it is likely to encounter during storage, distribution, retail display and consumer use. The aims of all storage trials of food are the same, which are, as indicated earlier in this chapter: · to establish the safety of the food throughout its intended shelf life, whatever its length, and · to arrive at a period of time during which the food will be certain to retain its sensory, chemical, physical, microbiological and functional characteristics that meet the target consumer requirements, and where appropriate, comply with any label declaration of nutrition data, when stored under the recommended conditions. 10.3.1 Safe shelf life In order to establish food safety, the most effective way, which is also a legal requirement within the EU/UK, is to use the internationally recognised system

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based on the Hazard Analysis and Critical Control Points (HACCP) principles as detailed in Article 5 of the EU Regulation (EC) No. 852/2004 on the hygiene of foodstuffs. The principles consist of the following (European Commission, 2004): (i) identifying any hazards that must be prevented, eliminated or reduced to acceptable levels; (ii) identifying the critical control points (CCPs) at the step or steps at which control is essential to prevent or eliminate a hazard or to reduce it to acceptable levels; (iii) establishing critical limits at CCPs which separate acceptability from unacceptability for the prevention, elimination or reduction of identified hazards; (iv) establishing and implementing effective monitoring procedures at CCPs; (v) establishing corrective actions when monitoring indicates that a critical control point is not under control; (vi) establishing procedures, which shall be carried out regularly, to verify that the measures outlined in (i) to (v) above are working effectively; and (vii) establishing documents and records commensurate with the nature and size of the food business to demonstrate the effective application of the measures in (i) to (vi) above. Earlier, Article 4 of the same Regulation requires food business operators to adopt as appropriate a number of specific hygiene measures, which include among others compliance with microbiological criteria for foodstuffs as set out in Commission Regulation (EC) No. 2073/2005 on microbiological criteria for foodstuffs. This Regulation establishes two types of microbiological criteria: food safety criteria, and process hygiene criteria (FSA, 2005). A food safety criterion is one that defines the acceptability of a product or a batch of foodstuff, applicable to products placed on the market. Applicable food safety criteria in Regulation No. 2073/2005 should therefore be used to establish safe microbiological shelf life during product development and to assess the microbiological safety of a food product or batch of products within the framework of an effective HACCP-based food safety management system. Examples of the microbiological (food safety) criteria set out in Annex I of Regulation No. 2073/ 2005 are given in Table 10.5. In an effort to assist food businesses of all levels of expertise to assign appropriate and correct date marks, the Chilled Food Association in the UK recently published a good practice guide on `Shelf life of ready to eat food in relation to L. monocytogenes', which was produced by a stakeholder drafting group chaired by the British Retail Consortium and which has been endorsed by the FSA (CFA, 2010). Benefiting from a wide knowledge and experience base, and taking advantage of collective wisdom, this guide effectively develops and expands the requirement in Regulation No. 2073/2005 for food business

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Table 10.5 Examples of food safety criteria applicable to products placed on the market during their shelf life (taken from FSA, 2005 ± Annex 1, Chapter 1) Criterion

1.2

Micro-organism and food category

Examples of foods

Sampling plan

Limits m

Analytical reference method

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n

c

M

5

0

100 cfu/g

EN/ISO 11290-2

5

0

*Absence in 25 g

EN/ISO 11290-1

5

0

100 cfu/g

EN/ISO 11290-2

Listeria monocytogenes Ready-to-eat foods able to support the growth of L. monocytogenes, other than those intended for infants and for special medical purposes

Chilled ready-to-eat products with more than 5 days' life Pre-packed delicatessen products Pre-packed sliced cooked meat Smoked salmon PaÃte Soft cheese

1.3

Listeria monocytogenes Ready-to-eat foods unable to support the growth of L. monocytogenes, other than those intended for infants and for special medical purposes

Yoghurt Hard cheese Products with a pH less than 4.4, e.g. coleslaw Products with shelf life less than 5 days, e.g. sandwiches

1.4

Salmonella Minced meat and meat preparations intended to be eaten raw

Steak tartare

5

0

Absence in 25 g

EN/ISO 6579

1.8

Salmonella Meat products intended to be eaten raw, excluding products where the manufacturing process or the composition of the product will eliminate the salmonella risk

Salami Parma ham Cold smoked duck

5

0

Absence in 25 g

EN/ISO 6579

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1.20

Salmonella Unpasteurised fruit and vegetable juices (ready-to-eat)

Freshly squeezed unpasteurised fruit juices, mixed fruit juices; smoothies; vegetable juices

5

0

Absence in 25 g

1.21

Staphylococcal enterotoxins Cheeses, milk powder and whey powder, as referred to in the coagulase-positive staphylococci criteria in Chapter 2.2 of Annex 1 of Regulation No. 2073/2005

Cheeses, excluding processed cheese and non-fermented cheese

5

0

Not detected in 25 g

1.23

Enterobacter sakazakii Infant milk and dairy products, as referred to in the Enterobacteriaceae criterion in Chapter 2.2 of Annex 1 of Regulation No. 2073/2005

Dried infant formulae and dried dietary foods for special medical purposes intended for infants below six months of age

30

0

Absence in 10 g

ISO/DTS 22964

1.24

E. coli Live bivalve molluscs and live echinoderms, tunicates and gastropods

Oysters, clams, sea urchins, winkles and welks

1

0

230 MPN/100 g of flesh and intra-valvular liquid

ISO TS 16649-3

1.25

Histamine Fishery products from fish species associated with a high amount of histidine

Tuna, mackerel, sardines, mahi

9

2

100 mg/kg

100 mg/kg

EN/ISO 6579

European screening method of the CRL for milk

HPLC

* This criterion applies to products before they have left the immediate control of the producing food business operator, when he is not able to demonstrate, to the satisfaction of the competent authority, that the product will not exceed the limit of 100 cfu/g throughout the shelf life.

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operators to `conduct studies' (Article 3(2)) as necessary to ensure `that the food safety criteria applicable throughout the shelf life of the products can be met under reasonably foreseeable conditions of distribution, storage and use' (Article 3 1(b)). Annex II of the same Regulation says The studies referred to in Article 3(2) shall include: · specifications for physico-chemical characteristics of the product, such as pH, aw, salt content, concentration of preservatives and the type of packaging system, taking into account the storage and processing conditions, the possibilities for contamination and the foreseen shelf life, and · consultation of available scientific literature and research data regarding the growth and survival characteristics of the micro-organisms of concern. When necessary on the basis of the above-mentioned studies, the food business operator shall conduct additional studies, which may include: · Predictive mathematical modelling established for the food in question, using critical growth or survival factors for the microorganisms of concern in the product, · Tests to investigate the ability of the appropriately inoculated microorganism of concern to grow or survive in the product under different reasonably foreseeable storage conditions. · Studies to evaluate the growth or survival of the micro-organisms of concern that may be present in the product during the shelf life under reasonably foreseeable conditions of distribution, storage and use. The above-mentioned studies shall take into account the inherent variability linked to the product, the micro-organisms in question and the processing and storage conditions. In practice, therefore, in order to establish safe shelf life of ready-to-eat food in relation to L. monocytogenes and indeed other pathogens, a food business operator should use all or any suitable combination of the following: · product characteristics and relevant scientific literature and research data · historical data pertinent to the control of the pathogen of concern (i.e., in this case L. monocytogenes) · predictive microbiology, i.e. internet-based predictive microbiological models e.g. ComBase (http://www.combase.cc) · specific laboratory shelf life studies ± challenge testing ± storage trials under controlled conditions · Collaboration between food businesses in conducting shelf life studies. In view of the primary importance to assure microbiological safety of food, further guides in relation to other pathogens are likely to be produced in future, in particular, for ready-to-eat foods.

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10.3.2 Challenge testing In general, a challenge test is a laboratory investigation of the behaviour of a product when subjected to a set of controlled experimental conditions. Challenge testing, in the context of shelf life studies, almost always refers to microbiological challenge testing, the aim of which is to simulate what can happen to a food product during processing, distribution and subsequent handling, following inoculation with one or more micro-organisms of concern. As such, it is a very useful tool for determining the ability of a food to support the growth of pathogens or spoilage organisms. The main areas of application of microbiological challenge testing include: · determining microbiological safety and assessing the risk of food poisoning after HACCP has identified the organisms likely to be the microbial hazards for the product at some stage during production and distribution; for example, this is useful in determining the safe shelf life of chilled foods (Uyttendaele et al., 2004) · establishing quality shelf life by inoculating the product with food spoilage organisms known or likely to contaminate it; for example, this is useful in evaluating the microbiological stability of emulsified and non-emulsified condiment sauces intended for ambient distribution (Jones, 2000) · studying the effects of different formulations of the food on a target organism, i.e. either a pathogen or a spoilage organism, during product development with a view to achieving an acceptable shelf life · validating processes such as aseptic processing and packaging that are intended to deliver some degree of lethality against a target organism or group of target organisms. In all situations, relevant expertise and skills together with the necessary laboratory facility must be available to produce meaningful results from challenge testing. When conducting a microbiological challenge test, a number of factors need to be carefully considered: · · · · · · ·

the selection of appropriate pathogens/spoilage organisms the level of challenge inoculum the inoculum preparation and method of inoculation duration of the study formulation factors and storage conditions sample examination data analysis and interpretation, and pass/fail criteria.

Useful and detailed guidelines for the design and planning of microbiological challenge testing are available (Anon., 2003; 2010; Notermans et al., 1993). 10.3.3 Quality shelf life and storage trials Ideally, storage trials aimed at establishing the quality shelf life of a food product can begin once its safety has been established. In practice, and more

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often than not, storage trials will be run in parallel to food safety evaluation based on HACCP principles as required by law. While in principle shelf life storage trials should employ conditions that mimic those the product in question is expected to encounter during storage, distribution, retail display and consumer use, in practice, and in many small and medium-sized companies, a fully comprehensive storage trial is rarely possible as conditions during distribution and retail display, for instance, are difficult and expensive to reproduce. Consumer storage, handling and use, too, are often highly variable and unpredictable, and over which the manufacturer has little control. What the manufacturer must be certain about is the objective of the storage trial, which, after all, is a controlled experiment, and the manufacturer must be clear about what variables he can control and what he cannot. Storage conditions Storage conditions can be fixed or cyclical, or a combination of both. For a given set of storage conditions, the following variations should ideally be available (Man, 2002): · Optimum conditions: These are the most desirable conditions of temperature, humidity, light and so on under which the most optimistic shelf life data should be obtained. · Typical or average conditions: These are the conditions that are expected to be most commonly experienced by the product and under which shelf life data that apply to the bulk of future production should be generated. · Worst case conditions: These are the most extreme but not abuse conditions that the product is expected to encounter and under which the most conservative shelf life data should be obtained. The latter, if used to assign a shelf life, should give it a margin of safety ensuring that product failures due to insufficient shelf life are highly unlikely in practice. For cost reasons, storage trials tend to employ fixed conditions, which, in the absence of universal standards, commonly include: · Frozen: ÿ18 ëC or lower (relative humidity is usually near 100%). · Chilled: 0 to ‡5 ëC, with a maximum of ‡8 ëC (relative humidity is usually very high: ~90%+). · Temperate: 25 ëC, 75% relative humidity. · Tropical: 38 ëC, 90% relative humidity. · Control: control conditions (for storage of control samples) are usually the optimum conditions, be they ambient, chilled or frozen. Samples for storage trials As outlined in Section 10.2.5, there are product (e.g., raw materials, product composition) as well as external (e.g., packaging, processing) factors that can influence shelf life. As such, they need to be known, controlled and standardised across replicate storage trials or trials conducted during product development,

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otherwise results from these trials could be misleading or even meaningless. A corollary of this is that every time a significant change is made in any of these factors, for instance, in the microbiological quality of a major raw material or in the time-temperature combination of a thermal treatment, fresh storage trials will have to be conducted. The number and size of samples to be laid down for trials need to be carefully chosen. The type of product, its end-use application, the anticipated or required shelf life and the tests planned for assessing changes during storage are some of the factors that need to be taken into account. Should there be great uncertainty about the shelf life, it is better to be generous with the number of samples retained than to run out of samples before the storage trial ends. Frozen storage at ÿ18 ëC or lower is often used as a means of keeping control samples. However, if freezing and thawing are known to affect the product adversely, facilities must be available for the preparation of fresh reference/control samples that are identical to the test samples, at any time during a storage trial. Experimental design and sampling schedule At present, there are few universally accepted protocols for storage trials for shelf life testing, be it legal or industrial. A number of designs have been put forward (Kilcast and Subramaniam, 2000), including some based on a statistical approach (Gacula, 1975). All have advantages and disadvantages, as well as varying implications on resources that include number of samples, storage facilities, development and maintenance of a trained taste panel and the amount of testing required. When conventional profiling is used to study sensory changes during storage, difficulty can arise due to the taste panel generating inconsistent responses over time, particularly if the storage time is long and test frequency low. Difficulties such as this further underline the importance of assuring the quality of stored samples, both test and control, if storage trials were not to produce at best inconclusive and at worst incorrect shelf lives. Nevertheless, the following are some possible protocols (Man, 2002): · Short shelf life products: For chilled foods with shelf life of up to one week (e.g., ready meals), samples can be taken off daily for testing. · Medium shelf life products: For products with a shelf life of up to three weeks (e.g., some ambient cakes and pastry), samples can be taken off on days 0, 7, 14, 19, 21 and 25. · Long shelf life products: For products with a shelf life of up to one year (e.g., some breakfast cereals and heat-processed shelf-stable foods), samples can be taken off at monthly intervals or at months 0, 1, 2, 3, 6, 12 and (perhaps) 18. The exact frequency will depend on the product and on how much is already known about its storage behaviour. Accelerated storage trials Sometimes, accelerated storage trials, mostly based on the Arrhenius equation (see Section 10.2.4), may be used to shorten the time required to estimate a shelf

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life, which otherwise can take an unrealistically long time to determine. In principle, accelerated storage trials are applicable to any deterioration process, biochemical, chemical, microbiological or physical, that has a valid kinetic model. In practice, because of their obvious advantages over direct storage trials, validated accelerated storage trials may be viewed as commercially sensitive such that only a few are available in the literature. The latter include the following: · shelf life and safety of minimally processed CAP/MAP chilled foods over a limited temperature range (Labuza et al., 1992) · aspartame stability in commercially sterilised flavoured dairy beverages (Bell and Labuza, 1994) · accelerated storage of commercial orange juice in 1 litre TetraBrikTM (Petersen et al., 1998) · accelerated shelf life testing of whey-protein-coated peanuts (Lee et al., 2003). The limitations of accelerated storage tests are well known; they tend to be product-specific and their results have to be interpreted with care based on detailed product knowledge and sound scientific principles. Fuller accounts of the limitations are available (IFST, 1993; Mizrahi, 2000). Accelerated tests must not be mistaken for `abuse tests'. An accelerated test is only of value if the shelf life limiting mechanism of deterioration under accelerated conditions is the same as that under normal/ambient conditions, and the relationship between changes under accelerated conditions and those under normal storage needs to be confirmed and validated using food products of known quality. An accelerated storage model that has enjoyed notable commercial success and is widely used in the baking industry is called ERH CalcTM (Fig. 10.3). The model is part of a computer-based `Cake Expert System' for the baking industry originally developed by the UK Flour Milling and Baking Research Association (now part of Campden BRI). ERH Calc allows users to run simulations on flour confectionery formulations and rapidly calculate their theoretical equilibrium relative humidities (ERHs) and estimate their mould-free shelf lives. The latter, though, do not necessarily mean that the products themselves are organoleptically acceptable. Shelf life tests As pointed out earlier, besides food safety, an acceptable shelf life is expected to retain desired sensory, chemical, physical, functional or microbiological characteristics of the product and which, where appropriate, should comply with any label declaration of nutritional information throughout its shelf life. Thus, tests employed to measure shelf life tend to be product-specific, reflecting the quality characteristics of the product being studied. In a sense, the tests to be used are informed by the knowledge and understanding of the ways the food product deteriorates and spoils, including the mechanism of deterioration that is shelf life limiting. A systematic and structured approach based on the HACCP principles

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Fig. 10.3 Predicting mould-free shelf life of baked goods using ERH Calc (reproduced with kind permission of Campden BRI).

has been used to implement a control system designed to prevent rancidity in confectionery and biscuits (Frampton, 1994). Essentially, this approach follows the same principles of HACCP; here a hazard is taken to mean a microbiological, chemical or physical agent in, or condition of, the food with a potential to cause it to deteriorate and spoil, terminating its shelf life. Applying the principles systematically leads to the determination of the critical control points at which control can be exercised and which are necessary to eliminate or delay the shelf life limiting hazard, preventing it from ending the required shelf life prematurely. Given the nature of the potential and possible hazards, the following types of tests can be used individually or in combination to measure the progress of shelf life: · · · ·

microbiological examination, including challenge testing chemical analysis physical/instrumental testing, measurement and analysis sensory evaluation.

Many shelf life studies together with the tests employed have been published in both the primary and secondary literature. Table 10.6 gives some examples that illustrate the specific tests used to measure shelf lives in light of the underlying mechanisms of deterioration.

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Table 10.6 Examples of published shelf life studies and their tests Product

Storage conditions

Shelf life tests

Approximate shelf life

Reference

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Orange juice (11.2 ëBrix) reconstituted from concentrate, then exposed to thermosonication and pulse electric fields

25 ëC

Total bacterial counts Conductivity Soluble solids pH Colour attributes (tristimulus colorimeter) on day 0, 14, 28, 84 and 168

168 days

Walkling-Ribeiro et al. (2009)

Fresh Pacific salmon slices treated with salts of organic acids

1 ëC

pH ATP breakdown products Total volatile base nitrogen (TVB-N) and trimethylamine (TMA) Sensory analysis of cooked slices on day 0, 3, 6, 9, 12 and 15

15 days

Sallam (2007)

2  1 ëC

Composition of gas mixtures pH of meat Colour instrumental measurement and metmyoglobin percentage Lipid oxidation analysis Counts of aerobic psychrotrophic flora Sensory evaluation on day 0, 4, 8, 12, 16 and 20

20 days

Martinez et al. (2006)

Fresh pork sausages packaged in various modified atmospheres

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Assigning shelf life The main aim of a storage trial for shelf life is to find out as accurately as possible, under specified storage conditions, the point in time at which the product has become either unsafe or unacceptable to the target consumers, and if the product meets its shelf life objectives. In terms of microbiological safety and stability, the following should be useful in helping to fix an end-point for the shelf life of the food being studied: · Relevant food legislation, e.g. Commission Regulation (EC) 2073/2005 on microbiological criteria for foodstuffs. · Guidelines for the microbiological quality of some ready-to-eat foods (Gilbert et al., 2000) given by enforcement authorities or agencies in support of their work, e.g. those given by the UK Health Protection Agency (previously the UK Public Health Laboratory Service). · Guides on microbiological criteria for foods produced by independent food research associations such as Campden BRI (Voysey, 2007). · Current industrial best practice as published in the primary literature, which suggests probiotic functional foods and drinks should contain at least 107 live and active bacteria per g or ml for their functional claims to be maintained over the shelf life period (Birollo et al., 2000). · Predictive models, e.g. ComBase. Non-microbiological criteria that are used to set shelf life tend to be relatively more product-specific. In an ideal situation, these criteria are either contained in the original marketing brief or can be developed from it. Crucially, the criteria, be they physical, chemical or sensory, need to be correlated to the quality attributes that are critical to product acceptability/consumer requirements, and hence quality (as opposed to safe) shelf life and, where appropriate, they should be agreed between the manufacturer and its customer. Once product safety has been established, sensory evaluation is the most popular means by which the end of shelf life is determined. A detailed treatment of sensory evaluation to study shelf life, either using a trained panel, or a sample of consumers, is beyond the scope of this chapter. 10.3.4 A summary Success in determining the shelf life of a food product depends on the following factors: · confidence in assuring food safety · ability to define the critical quality characteristics that determine product acceptability and meet customer requirements · knowledge and understanding of the pertinent mechanisms of deterioration and spoilage including the shelf life limiting mechanism · adequate capability, either in-house or external, in terms of both technical know-how and appropriate resources (skilled staff, testing facility etc.), to measure shelf life either directly through storage trials or indirectly through prediction and estimation, or both.

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Storage trials for shelf life determination are controlled experiments, to which the basic principles of experimental design that include use of control, randomisation and replication apply. An estimate of shelf life without an indication of its variability is of little value. A safe food product of acceptable quality that consistently pleases its consumers has its origin in good product design that must include carefully planned and professionally executed shelf life testing. Replication of the storage trial experiment on sufficient food samples of agreed and consistent quality is essential for the setting of reliable and reproducible shelf life.

10.4

Future trends

In the past two decades, as a result of major research efforts in a number of countries, notably the US, UK and Australia, coupled with ever-increasing power of personal computers, the use of Internet-based predictive microbiological models as an aid to HACCP and microbiological risk assessment has had a significant and positive impact on the management of microbiological safety of foods. Food safety, which includes chemical and microbiological safety, is of fundamental importance and will always remain so. Recent research has focused on sensory shelf life in an effort to maximise consumer acceptance and minimise food waste due to inaccurate shelf life or shelf life that is too conservative. Apart from catastrophic circumstances, food products do not usually fail all at once such that for a given product there is a distribution of shelf lives over time, and concomitantly, an increasing proportion of the consumers are expected to reject the product over the same period. Realisation of this has led researchers to use survival analysis statistics to study sensory shelf life of foods (Hough et al., 2003). Since then, Bayesian methods and the Arrhenius equation have been used separately to study sensory shelf life of foods and to analyse data based on consumers' acceptance or rejection of samples stored at different times and different temperatures, respectively (Luz Calle et al., 2006; Hough et al., 2006). The number of consumers necessary for shelf life estimations based on survival analysis statistics has also been determined in a simulation study that assumes a Weibull distribution for the data model (Hough et al., 2007). Advantages of applying survival analysis statistics to sensory shelf life estimations include relatively simple sensory work with say 50±100 consumers and that the estimations are based directly on consumer data. The disadvantages are that the underlying mechanism of deterioration that limits shelf life will not be provided by the consumer data if it is unknown, and specialised statistical software and expertise are required for the calculations and interpretation of the results (Hough, 2006). Even more recent research has begun to look at the possibility of integrating the modelling of safety and quality of foods, taking a complex systems approach to estimating shelf life (Martins et al., 2008). In the meantime, storage trials for

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estimating shelf life remains a cornerstone of the shelf life determination of foods with which all responsible food businesses should be conversant.

10.5

References

(2003) Microbiological Challenge Testing. Comprehensive Reviews in Food Science and Food Safety, vol. 2 (Supplement), 46±49, IFT, Chicago, IL. ANON. (2010) Challenge testing protocols for assessing the safety and quality of food and drink. Guideline No. 63, Campden BRI, Chipping Campden, UK. BELL L N and LABUZA T P (1994) Aspartame stability in commercially sterilised flavoured dairy beverages. Journal of Dairy Science, 77, 34±38. BETTS G D, BROWN H M and EVERIS L K (EDS) (2004) Evaluation of Product Shelf-life for Chilled Foods. Guideline No. 46, Campden and Chorleywood Food Research Association, Chipping Campden, UK. BIROLLO G A, REINHEIMER J A and VINDEROLA C G (2000) Viability of lactic acid microflora in different types of yoghurt. Food Research International, 33, 799±805. CFA (2010) Shelf life of ready to eat food in relation to L. monocytogenes ± Guidance for food business operators, 1st edn. Chilled Food Association, Kettering, UK. CRAWFORD C (1998) The New QUID Regulations. Chandos Publishing, Oxford. ELLIS M J and MAN C M D (2000) The methodology of shelf-life determination. In: Shelf-life Evaluation of Foods, 2nd edn. Man D and Jones A (eds). Aspen Publishers, Gaithersburg, MD, pp. 23±49. EUROPEAN COMMISSION (2004) Regulation (EC) No. 852/2004 of the European Parliament and of the Council on the hygiene of foodstuffs. Official Journal of the European Union, 25 June 2004, L 226/3± L226/21. FRAMPTON A (1994) Prevention of rancidity in confectionery and biscuits ± a Hazard Analysis Critical Control Point (HACCP) approach. In: Rancidity in Foods, 3rd edn. Allen J C and Hamilton R J (eds). Blackie Academic & Professional, London, pp. 161±178. FSA (2005) General Guidance for Food Business Operators. EC Regulation No. 2073/ 2005 on Microbiological Criteria for Foodstuffs. Food Standards Agency, UK (www.food.gov.uk/). FSA (2010) Food Standards Agency guidance on the application of date marks in food. [Online]. Available from: http://www.food.gov.uk/consultations/consulteng/2010/ fsaguidanceappdatemarksfoodeng (accessed 1 April 2010). GACULA M C (1975) The design of experiments for shelf-life study. Journal of Food Science, 40, 399±403. ANON.

GILBERT R J, DE LOUVOIS J, DONOVAN T, LITTLE C, NYE K, BIBEIRO C D, RICHARDS J, ROBERTS D

and BOLTON F J (2000) Guidelines for the microbiological quality of some ready-toeat foods sampled at the point of sale. Communicable Disease and Public Health, 3(3), 163±167. HOUGH G (2006) How does survival analysis help us in estimating the probability of a consumer rejecting a stored product? In: Workshop summary: sensory shelf-life testing. Food Quality and Preference, 17, 644±645. Â MEZ G and CURIA A (2003) Survival analysis applied to sensory HOUGH G, LANGOHR K, GO shelf life of foods. Journal of Food Science, 68, 359±362. Â MEZ G (2006) Sensory shelf-life predictions by survival HOUGH G, GARITTA L and GO

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analysis accelerated storage models. Food Quality and Preference, 17, 468±473. and CURIA A (2007) Number of consumers necessary for shelf life estimations based on survival analysis statistics. Food Quality and Preference, 18, 771±775. HUIS IN'T VELD J H J (1996) Microbial and biochemical spoilage of foods: an overview. International Journal of Food Microbiology, 33, 1±18. IFST (1993) Shelf life of Foods ± Guidelines for its Determination and Prediction. Institute of Food Science & Technology, London. JONES A A (2000) Ambient-stable sauces and pickles. In: Shelf-life Evaluation of Foods, 2nd edn. Man D and Jones A (eds). Aspen Publishers, Gaithersburg, MD, pp. 211± 226. KILCAST D and SUBRAMANIAM P (2000) Introduction. In: The Stability and Shelf-life of Food, Kilcast D and Subramaniam P (eds). Woodhead Publishing, Cambridge, pp. 1±19. LABUZA T P, FU B and TAOUKIS P S (1992) Prediction for shelf-life and safety of minimally processed CAP/MAP chilled foods. Journal of Food Protection, 55, 741±750. LEE S-Y, GUINARD J-X and KROCHTA J M (2003) Relating sensory and instrumental data to conduct an accelerated shelf-life testing of whey-protein-coated peanuts. In: Freshness and Shelf-life of Foods. Cadwallader K and Weenen H (eds). American Chemical Society, Washington, DC, pp. 175±187. Â MEZ G (2006) Bayesian survival analysis LUZ CALLE M, HOUGH G, CURIA A and GO modelling applied to sensory shelf life of foods. Food Quality and Preference, 17, 307±312. MAN C M D (2002) Shelf Life. Food Industry Briefing Series, Blackwell Science, Oxford. MAN C M D (2004) Shelf-life testing. In: Understanding and Measuring the Shelf-life of Food. Steele, R (ed.). Woodhead Publishing, Cambridge, pp. 340±356. MARTINS R C, LOPES V V, VICENTE A A and TEIXEIRA J A (2008) Computational shelf-life dating: complex systems approaches to food quality and safety. Food Bioprocess Technol., 1, 207±222. Â N J A and RONCALEÂS P (2006) Effect of varying MARTINEZ L, DJENANE D, CILLA I, BELTRA oxygen concentrations on the shelf-life of fresh pork sausages packaged in modified atmosphere. Food Chemistry, 94, 219±225. MIZRAHI S (2000) Accelerated shelf-life tests. In: The Stability and Shelf-life of Food, Kilcast D and Subramaniam P (eds). Woodhead Publishing, Cambridge, pp. 107± 128. MOSSEL D A A (1971) Physiological and metabolic attributes of microbial groups associated with foods. Journal of Applied Bacteriology, 34, 95±118. NOTERMANS S, IN'T VELD P, WIJTZES T and MEAD G C (1993) A user's guide to microbial challenge testing for ensuring the safety and stability of food products. Food Microbiology, 10, 145±157. PETERSEN M A, TéNDER D and POLL L (1998) Comparison of normal and accelerated storage of commercial orange juice ± changes in flavour and content of volatile compounds. Food Quality and Preference, 9 (1/2), 43±51. SALLAM K I (2007) Chemical, sensory and shelf life evaluation of sliced salmon treated with salts of organic acids. Food Chemistry, 101, 592±600. TSO (2006) The Food Hygiene (England) Regulations (SI 2006/14), The Stationary Office, London. UYTTENDAELE M, RAJKOVIC A, BENOS G, FRANCËOIS K, DEVLIEGHERE F and DEBEVERE J (2004) Evaluation of a challenge testing protocol to assess the stability of ready-to-eat HOUGH G, LUZ CALLE M, SERRAT C

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cooked meat products against growth of Listeria monocytogenes. International Journal of Food Microbiology, 90, 219±236. VOYSEY P A (2007) Establishment and Use of Microbiological Criteria (Standards, Specifications and Guidelines) for Foods. Guideline No. 52, Campden and Chorleywood Food Research Association, Chipping Campden, UK. WALKLING-RIBEIRO M, NOCI F, CRONIN D A, LYNG J G and MORGAN D J (2009) Shelf life and sensory evaluation of orange juice after exposure to thermosonication and pulsed electric fields. Food and Bioproducts Processing, 87, 102±107.

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11 Sensory evaluation methods for food shelf life assessment D. Kilcast, Consultant in Food and Beverage Sensory Quality, UK

Abstract: The shelf life of foods that are microbiologically stable is limited by changes in perceived sensory characteristics (appearance, texture and flavour), which in turn result from physicochemical changes in the product in question. The main sensory methods used in shelf life testing are described, together with the design of shelf life testing programmes and the ways in which shelf life data can be analysed and interpreted. Published standards relevant to shelf life testing are outlined, together with associated instrumental test methods. Key words: sensory test methods, sensory standards, ethical procedures, end point, analysis and interpretation. Note: This chapter is a revised and updated version of Chapter 4 `Sensory evaluation methods for shelf-life assessment' by D. Kilcast in The Stability and Shelf-life of Food, ed. D. Kilcast and P. Subramaniam, Woodhead Publishing Limited, 2000, ISBN: 978-1-85573-500-2.

11.1

Introduction

The various available definitions of shelf life present some difficulties to the food industry when investigating the shelf life of microbiologically stable foods, in which the shelf life-limiting factors are usually changes in sensory characteristics. The definition of shelf life from the Institute of Food Science and Technology in the UK (IFST, 1993) specifies a single sensory criterion, that `be certain to retain desired sensory characteristics'. This requires identification and measurement of `desired' sensory characteristics, but does not expand on the meaning of `desired'. This definition also implies that sensory characteristics

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should not change over the shelf life of the product, but in practice most foods undergo deterioration following production, and this must be recognised by defining the ranges of required characteristics. Further, some notable foods, such as cheese and wine, undergo changes that generate desired product characteristics during storage. ASTM E 2454-05, which deals specifically with sensory shelf life, defines sensory shelf life as the `time period during which the products' sensory characteristics and performance are as intended by the manufacturer'. This definition itself adds little to the earlier IFST definition, but then the standard introduces more practical terminology, in which shelf life is described as the `time period that a product may be stored before reaching its end point', and then further defines the end point as the `point at which a product no longer meets predetermined criteria as defined by test data (for example, discrimination, descriptive, or affective, or a combination thereof)'. Three types of sensory shelf life end points are then described: `(1) the product's overall sensory profile has changed; (2) a product attribute(s) that is known or suspected to be key to the consumers' perception of the product has changed; and (3) the acceptability of the product is too low'. These concepts offer sensory analysts an improved springboard from which to design and operate sensory shelf life tests. When we eat food, we perceive a whole range of different characteristics relating to the appearance, flavour and texture of the food. Physiological differences between individuals result in a range of responses to these stimuli, and we must expect these different responses to be encountered within a given consumer population. Further, differences in ethnic and cultural backgrounds and in experiences of foods will broaden further the response of consumers to foods. In selecting and using sensory methods, we must be prepared not only to encounter and work within this wide response, but also to interpret data generated by sensory measurements in the context of the target consumer population. Changes in all the different sensory modalities can occur throughout the shelf life of foods. Appearance changes are commonly seen on storage of, for example, red meat (browning), fruit juices (darkening), dairy gels (syneresis) and emulsions (separation). Odour loss is a particular problem in products such as bread and coffee, whereas the development of off-odours is particularly important as an index of deterioration in many products. Odour changes are frequently accompanied by flavour changes, but flavour is a complex characteristic that is perceived in different ways and consequently flavour changes can occur independently of odour changes. Textural changes can be seen as positive (e.g., maturation and softening of fruit), but are more frequently deteriorative (e.g., staling of bread and loss of crispness in snack foods). A more complete set of examples of deteriorative changes in different product types is shown in Tables 11.1±11.5 in the Appendix. There is often a temptation to interpret measured sensory changes in terms of perceived quality, but this must be given careful consideration. In general, we dislike extremes, preferring intermediate levels of a sensory characteristic,

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leading to an inverted-U relationship between liking and attribute intensity; simple linear relationships are not often seen within a typical consumer population, although different relationships can be seen in segmented populations. Assessment of sensory shelf life can therefore be approached in one of two ways: from measurement of sensory characteristics, or from measurement of consumer liking. In this chapter, the principles underlying the measurement of sensory characteristics will be described, together with practical measurement systems and the interpretation of the measured data in terms of sensory shelf life.

11.2

Principles of sensory evaluation

Human beings employ a range of senses in perceiving food quality. A schematic diagram of the main senses, and how they can interact, is shown in Fig. 11.1. The discussion below summarises these senses briefly. Fuller descriptions can be found in the references in Section 11.13. 11.2.1 The human senses The visual senses are particularly important in generating an initial impression of food quality that often precedes the input from the remaining senses. If the appearance of the food creates a negative impact, then the food might be rejected without the other senses coming into play at all. The visual sense is often equated only with colour, but provides input on many more appearance attributes that can influence food choice, for example size, shape, surface gloss,

Fig. 11.1 The main human senses, and how they interact.

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and clarity. In particular, the visual senses can provide an early, and strong, expectation of the flavour and textural properties of foods. Taste (gustation) is strictly defined as the response by the tongue to soluble, involatile materials. These have classically been defined as four primary basic taste sensations: salt, sweet, sour and bitter, but these have now been joined by umami, the savoury sensation associated with monosodium glutamate. In some countries this list is extended to include sensations such as metallic and astringency. The taste receptors are organised groups of cells, known as taste buds, located within specialised structures called papillae. These are located mainly on the tip, sides and rear upper surface of the tongue. Sweetness is detected primarily on the tip of the tongue, salt and sour on the sides of the tongue and bitter on the rear of the tongue. Other oral surfaces have lower sensitivities. Taste stimuli are characterised by the relatively narrow range between the weakest and the strongest stimulants (ca 104), and are strongly influenced by factors such as temperature and pH. The odour response is much more complex, and odours are detected as volatiles entering the nasal cavity, either directly via the nose or indirectly through the retronasal path via the mouth. The odorants are sensed by the olfactory epithelium, which is located in the roof of the nasal cavity. Some 150± 200 odour qualities have been recognised, and there is a very wide range (ca 1012) between the weakest and the strongest stimulants. The odour receptors are easily saturated, and specific anosmia (blindness to specific odours) is common. It is thought that the wide range of possible odour responses contributes to variety in flavour perception. Both taste and odour stimuli can only be detected if they are released effectively from the food matrix during the course of mastication. The chemical sense corresponds to a pain response through stimulation of the trigeminal nerve. This is produced by chemical irritants such as ginger and capsaicin (from chilli), both of which give a heat response, and chemicals such as menthol and sorbitol, which give a cooling response. With the exception of capsaicin, these stimulants are characterised by high sensory thresholds. The combined effect of the taste, odour and chemical responses gives rise to the sensation generally perceived as flavour, although these terms are often used loosely. Texture is perceived by the sense of touch, and comprises two components: somesthesis, a tactile, surface response from skin, and kinesthesis (or proprioception), a deep response from muscles and tendons. For many foods, visual stimuli will generate an expectation of textural properties. The touch stimuli themselves can arise from tactile manipulation of the food with the hands and fingers, either directly or through the intermediary of utensils such as a knife or spoon. Oral contact with food can occur through the lips, tongue, palate and teeth, all of which provide textural information. The descriptions given above, whilst appropriate for the individual sensing modalities, fail to take into account their interactive nature. These interactions have been extensively reviewed by Cardello (1996). Colour, which is obviously an important appearance characteristic, can be shown to have an influence on

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flavour perception. For example, Dubose et al. (1980) found significant increases in perceived flavour intensity in beverages with increasing colour intensity. Textural properties of foods have substantial effects on the perception of flavour, and sound emission from crisp and crunchy foods has been shown to be of great importance in the perception of their texture (e.g., Vickers, 1991). The importance of the interaction between the texture of foods and their perceived flavour can be clearly seen if the time course of events during food consumption is considered. As already indicated, strong expectations of the flavour and texture characteristics can be generated before the food is introduced into the mouth. As food enters the mouth, and is either bitten or manipulated between tongue and palate, catastrophic changes occur to the structure of the food that strongly influence the way in which tastants and odorants are released from the food. These processes can result in important effects on perceived flavour, and can produce substantial changes in flavour and texture quality if changes to food structure occur on storage. 11.2.2 Factors influencing the quality of sensory data The complex nature of food quality perception creates many difficulties for the sensory analyst, whose primary task is to use human subjects as an instrument to measure the sensory quality of foods. The factors that should be considered in assessing the performance of human subjects in this way are accuracy, precision and validity (Piggott, 1995). Sensory measurements are a direct measure of human response, and have an inherently higher validity than instrumental measures, which are nonetheless of value as a complement to sensory data in shelf life assessment. In measuring human responses, low precision must be expected, but variation can be reduced by careful selection of a range of human subjects who can produce a response with lower variability, and by extensive training. Improving accuracy (giving the correct answer without systematic error or bias) can be achieved by recognising the various sources of physiological and psychological biases that can influence human subjects. The effect of physiological differences between individuals can be reduced, but not completely eliminated, by careful selection procedures. Psychological factors can introduce systematic biases that might not be recognised. These include those arising from unwanted interaction between panellists, and those from more subtle sources. These can be greatly reduced by choice of sensory test procedure and by careful experimental design and operation of sensory test procedure. Such factors play a major role in generating sensory data that can be interpreted reliably in terms of shelf life.

11.3

Basic requirements for sensory analysis

In developing and implementing a high-quality sensory evaluation system a number of inter-related requirements can be defined; these are discussed below,

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The components of a sensory evaluation system.

and more detailed discussions can be found in standard texts, examples of which are referenced in Section 11.13. The requirements are shown schematically in Fig. 11.2. 11.3.1 Clear definition of the objectives of the sensory evaluation system Clear objectives are central to the establishment of any system that will be sufficiently accurate to measure the required sensory characteristics with the required precision, but with the important proviso that it should be practical and cost-effective. This is particularly important in shelf life assessments, in which repeated measurements over a period of time demand substantial resources and commitment. Large amounts of sensory data can be generated over the test period, and careful planning must be given to how these data are produced and handled if a meaningful interpretation is to be achieved. Problems commonly seen in industry include: underestimation of panellist requirements, including enforced changes in personnel over the test period; ambiguity in the type of sensory information to be generated; and absence of guidelines on the interpretation of storage changes in terms of shelf life. 11.3.2 Provision of a dedicated sensory testing environment A suitable environment is essential for generating high-quality sensory data with minimal bias. The environment is important not only in providing standardised working conditions for the assessors, but also in providing a work area for

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sample preparation and for data analysis. The three main components of an ideal sensory evaluation environment are: · a preparation area of adequate size and appropriately equipped · a testing environment, adjacent to, but separated from, the preparation area · individual booths to eliminate panellist interaction. 11.3.3 Selection of suitable test procedures Many sensory test methodologies are available, but fall into two main classes, shown schematically in Fig. 11.3. · Analytical tests. These tests are used to measure sensory characteristics of products by providing answers to the questions: ± Is there a difference? ± What is the nature of the difference(s)? ± How big is(are) the difference(s)? · Hedonic/affective tests. These tests are used to measure consumer response to sensory characteristics of the products by providing answers to the questions: ± Which product is preferred? ± How much is it liked? The two classes comprise tests that satisfy completely different objectives, and which are subject to different operating principles. Analytical tests use human subjects as a form of instrument to measure properties of the food. Hedonic tests measure the response of consumer populations to the food in terms of likes or

Fig. 11.3 Main classes of sensory testing procedures.

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dislikes. Different psychological processes are used for each type of test, and in general there is no simple linear relationship between the two types of data, an inverted U-curve being typical. Of great practical importance, the type and numbers of subjects used for the analytical and hedonic tests are quite different. Use of each test type for shelf life determination is described in more detail in subsequent sections. 11.3.4 Selection and training of suitable test subjects The subjects to be used are defined by the objective of the test and by the consequential choice of test. The number of subjects to be used depends on the level of expertise and training of the panellists. General guidance on numbers is given in ISO 6658 (2005), which also discriminates between assessors, selected assessors and experts, but for guidance on specific tests, relevant individual standards should be referred to. (Note: the term assessor is used throughout the ISO standards, but for the remainder of this chapter, the more common term panellist will be used.) Analytical tests Both discriminative and descriptive tests use small panels of panellists chosen for their abilities to carry out the tests. Guidelines for establishing such assessors are given in ISO 8586-1 (1993). A general scheme for establishing a panel requires the following steps: · Recruitment. Panellists can be recruited from within the company, or dedicated part-time panellists can be recruited from the local population (company employees should not be compelled to participate). · Screening. These preliminary tests are used to establish that sensory impairment is absent, to establish sensitivity to appropriate stimuli and to evaluate the ability to verbalise and communicate responses. These tests will depend mainly on the defined objectives of the sensory testing, but will typically consist of the following: ± the ability to detect and describe the five basic tastes: sweet, sour, salt, bitter and umami; these may be extended to cover metallic and astringent ± the ability to detect and recognise common odorants, especially those characteristic of the product range of interest ± the ability to order correctly increasing intensities of a specific stimulus, for example increasing sweetness or increasing firmness ± the ability to describe textural terms characteristic of relevant food types ± absence of colour vision deficiencies. Approximately 8% men, but only 0.4% women, suffer colour vision deficiencies. Tests can be carried out using Ishihara charts (available from opticians or booksellers). Selection of suitable panellists is usually made on the basis of a good performance across the entire range of tests, rather than excellence in some and poor response to others. If the panel is to be used for a specific purpose, then the tests relevant to that purpose can be weighted appropriately.

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· Training. In the initial stages, training is limited to the basic principles and operations, following which further selection can be made. More closely targeted training can then be carried out using the products of interest and aimed towards the specific tests to be used in practice. · Monitoring. Close monitoring of panel performance is essential, and any drift that is identified must be corrected by retraining procedures. Hedonic tests Subjects (respondents) for hedonic tests are chosen to represent the target consumer population, and to reflect any inhomogeneity in that population. Consequently, they need to be used in sufficient numbers to give statistical confidence that they are representative, and they must be given the opportunity to behave as they would in a real consumption environment. In particular, they must not be selected on the basis of sensory ability and must not be given any training. Numbers in excess of 100 respondents are normally used. For the early stages of concept development, qualitative studies using focus groups with small numbers of respondents can be used, but the data generated should be treated carefully and conclusions must not be generalised. The same subjects must not be used for both types of test and, in particular, in-house staff must not be used to generate hedonic data that may be viewed as consumer-related. 11.3.5 Data handling, analysis and presentation Sensory experiments can generate large amounts of data, and reliable conclusions require validation using statistical techniques. Different types of sensory test procedures generally utilise specific analysis procedures, but, in the case of the more sophisticated profiling techniques, a wide range of options is available, ranging from basic univariate analysis to sophisticated multivariate analysis. Many statistical software packages are now available. The most sophisticated require a sound understanding of statistical principles, but more user-friendly packages are available that satisfy most requirements. In practice it is usual to find that no single package can cover the entire range of basic requirements. Clear and effective presentation of sensory data, including the results of statistical tests, is essential. Most standard spreadsheets are now able to offer a wide range of presentation possibilities for both univariate and multivariate data.

11.4

Discrimination tests

Discrimination tests are perceived as one of the easiest classes of sensory testing to apply in an industrial environment, and are consequently heavily used. The tests can be used in two ways: to determine whether there is an overall difference between two samples, or to determine whether one sample has more or less of a specific attribute than another. However, there are inherent limitations of such tests, and they are often overused in circumstances in which

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alternative methods such as profiling would be superior. In addition to testing for a difference, new versions of ISO standards also permit testing for similarity (contrary to common belief, absence of a difference does not imply similarity). In general, however, uses of similarity testing are more limited in practice as a consequence of the need for higher numbers of assessors and a lack of agreement in the choice of statistical test criteria. In this section, the main types of test with practical value for shelf life assessment will be described. 11.4.1 Paired comparison test In the most common form of the test (less commonly referred to as the 2-AFC, alternative forced choice, test), two coded samples are presented either sequentially or simultaneously in a balanced presentation order, AB and BA (ISO 5495, 2007). There are two variations on the test. In the directional difference variant, the panellists are asked to choose the sample with the greater or lesser amount of a specified characteristic. The panellists are usually instructed to make a choice (forced-choice procedure), even if they have to make a guess. In the directional form, it is important that the panellists clearly comprehend the nature of the attribute of interest. 11.4.2 Duo-trio test In the most common variant of the duo-trio test, the panellists are presented with a sample that is identified as a reference followed by two coded samples, one of which is the same as the reference and the other different (ISO 10399, 2004). These coded samples are presented in a balanced presentation order, i.e. A (reference) AB A (reference) BA The panellists are asked to identify which sample is the same as the reference. The duo-trio test is particularly useful when testing foods that are difficult to prepare in identical portions. Testing such heterogeneous foods using the triangle test, which relies on identical portions, can give rise to difficulties, but in the duo-trio test it is possible to ask the question: `Which sample is most similar to the reference?' 11.4.3 Triangle test The panellists are presented with three coded samples, two of which are identical, using all possible sample permutations (ISO 4120, 2007): ABB AAB BAB ABA BBA BAA The panellists are asked to select the odd sample, preferably using a fixed-choice procedure. The increased number of samples compared with a paired com-

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parison test can result in problems with flavour carry-over when using strongly flavoured samples, making identification of the odd sample more difficult. Difficulties can also be encountered in ensuring presentation of identical samples of some foods. 11.4.4 Difference from control test The panellists are presented with an identified control and a range of test samples. They are asked to rate the samples on suitable scales anchored by the points `not different from control' to `very different from control'. The test can be used to identify overall differences, or differences in specified attributes. The test results are usually analysed as scaled data. 11.4.5 Analysis of discrimination tests The basic principle underlying the analysis of difference is to test the actual response obtained against the response that would have occurred purely by chance: for the paired comparison and duo-trio tests this is 1 in 2, for the triangle test this is 1 in 3. One consequence of the different probabilities is that the statistical power of the tests differs, together with the numbers of responses that are needed in order to give a meaningful and reliable result. These numbers are related to the levels of risk that are deemed acceptable, and these are the Type 1 risk (incorrectly concluding that there is a difference that does not exist) and the Type 2 risk (not identifying a difference that is present). It is sometimes possible to generate the required number of judgements by replicated tests with a smaller number of panellists. Such a procedure should be used with care (e.g., generating 15 responses by using 3 panellists in 5 replicates is not recommended), and each replicate should be set up as an independent test. Individual ISO standards should be referred to for further details of minimum responses. The test results are usually analysed using tables of the binomial expansion, although other distributions have been used. The 5% level of significance is frequently used in sensory tests, but an increasingly common procedure is to calculate exact probability levels. If a strict statistical interpretation is required, a forced-choice response must be used. Similarly, if relatively inexperienced panellists, or consumers, are being used, then a forced-choice test must be used to prevent `fence-sitting'. However, if highly experienced panellists are used, a no difference response can be highly informative in specific circumstances. Extended variants of discrimination tests are often used, although some concerns have been raised in moving away from the simple test procedure. Descriptions of the nature of any difference can provide useful guidance for further testing. A simple scaled assessment of the degree of confidence in the decision (absolutely sure/fairly sure/not very sure/only guessed) is very useful, especially when using forced-choice procedures. Assessment of the degree of difference is only likely to be of value if panellists have been trained in scaling procedures. More controversially, panellists can be asked which samples they

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prefer, but this type of procedure is of value only for crude guidance; preference tests should be set up separately as consumer tests. There is potential value in acquiring this information in shelf life assessments, but the hedonic information should be used with great care. All such information must only be used in support of the main difference test data, and can only be used from panellists who have given the correct response.

11.5

Quantitative descriptive tests

The major advantages of discrimination tests are their relative simplicity to set up and operate, and their high sensitivity. However, they have two important limitations. Firstly, only two sample treatments are compared together. Secondly, the information content of discrimination tests is limited, even when operated in an extended format, incorporating a range of questions. More informative tests can produce more quantitative data that can be subjected to a wider range of statistical treatments. 11.5.1 Scaling procedures Quantification of sensory data is needed in many applications, and the recording of perceived intensity of attributes or liking requires some form of scaling procedure. These procedures should be distinguished from quality grading systems, which are used to sort products into classes defined by a combination of sensory characteristics. Such systems are not open to quantitative numerical analysis. Scaling procedures are mainly used to generate numeric data that can be manipulated and analysed statistically. Before this can be carried out, however, thought must be given to how the scales used are seen and interpreted by the assessors, and how this may influence the type of analysis that can be safely applied. The different types of scale used are described below. · Category scales use a defined number of boxes or categories (often 5, 7 or 9, although other numbers are often used). The scale ends are defined by verbal anchors, and intermediate scale points are often given verbal descriptions. · Graphic scales (line scales) consist of a horizontal or vertical line with a minimum number of verbal anchors, usually at the ends. Other anchors can be used, for example to define a central point, or to denote the position of a reference sample. · Unipolar scales have a zero at one end, and are most commonly used in profiling, especially for flavour attributes. · Bipolar scales have opposite attributes at either end. Definition of the central point can often give rise to logical difficulties, as can ensuring that the extreme anchors are true opposites. This can be a particular problem for textural attributes, for example when using soft . . . . . . hard type scales. Bipolar scales are frequently used for consumer acceptability testing, especially using the like extremely . . . . . . dislike extremely format.

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· Hedonic scales are use to measure consumer liking or acceptability. Category scales are usually used. · Relative to ideal scales are a type of hedonic scale which measures deviation from a personal ideal point. The type of scale used, and its construction, depends on a number of factors: · Purpose of test. Both category and graphic scales are commonly used with trained panels. In consumer testing, category scaling methods are usually used. · Expertise of assessors. Untrained assessors are generally poor discriminators, and can discriminate only over a small number of scale points. Trained panels can start with 5- or 7-point category scales, but, as their discrimination ability increases, they can use effectively more scale points or graphic scales. When using inexperienced assessors, scales incorporating a `neutral point', such as the central point in an odd-numbered category scale, are sometimes avoided in order to minimise the risk of `fence-sitting'. · Number of assessors. Using small assessor numbers with a low number of category scale points will limit statistical analysis options. · Data-handling facilities. Category scaling responses can be entered relatively quickly onto a spreadsheet, whereas data from line scales must be measured, and this can be a time-consuming procedure. Computerised data acquisition, either directly from a terminal or indirectly from optical readers, can avoid this problem. In practice, establishing a trained sensory panel can often proceed from a category scale with a small number of scale points (e.g. 5), through a category scale with more points (e.g. 9) to a line scale. Sensory analysts should be aware of difficulties that panellists have in using scales, and careful training is needed to ensure that scales are unambiguous and can measure the intended response. 11.5.2 Simple descriptive procedures Scaling may often be needed in order to quantify a single, well-defined attribute. However, it should be established that there is no ambiguity in the attribute of interest. This is particularly relevant during product development or modification, when the assumption that a process or ingredient modification will change only a single attribute is frequently violated. Such changes are especially common when textural changes are a consequence of process or ingredient modifications. If it is suspected that several attributes might be of interest, then the profiling procedures described in the subsequent sections should be considered. 11.5.3 Quantitative Descriptive Analysis (QDA) Variants of the original QDA procedures are probably used more than any other profiling procedure. The QDA technique uses small numbers of highly trained

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panellists. Typically, 6±12 people are screened for sensory acuity and trained to perform the descriptive task to evaluate the product. Three major steps are required: development of a standardised vocabulary, quantification of selected sensory characteristics and statistical analysis of the results. Vocabulary development Development of the vocabulary is a group process for creating a complete list of descriptors for the products under study. Panellists freely describe the flavour, appearance, odour, mouthfeel, texture and aftertaste characteristics of different samples. No hedonic (good or balanced), general (full or typical) or intensitybased (strong or weak) terms are permitted. Terminology should be consistent from product to product and tied to reference materials. The references decrease panellist variability, reduce the amount of time necessary to train sensory panellists, and allow calibration of the panel in the use of intensity scales. References should be simple, reproducible and clear to the assessors, and illustrate only a single sensory descriptor. They can be single chemical substances or finished products, and are made available during both the training and the testing phase, at various concentrations or intensity. One requirement for the use of QDA in shelf life testing is the use of training samples that illustrate quality changes that occur on storage. This is often difficult to achieve in practice, especially for long shelf life foods. The attributes are collected and compiled into a master list. This individual preliminary evaluation of the samples may be revised during an open discussion to eliminate any redundant or synonymous descriptors. New terms might be added and physical references proposed. The panel leader condenses and formats the information into a proposal for standardised vocabulary. This vocabulary is then modified and improved in several interactive sessions. Multivariate statistical methods (e.g., factor analysis) are sometimes used to reduce the number of descriptors. Finally, definitions for the attributes are agreed. Intensity measurement Once agreement is reached on the vocabulary, further training is performed. The number of training sessions is dependent on the subject's performance, product and attribute difficulties and the time allowed for QDA testing. Panel training increases panellist sensitivity and memory and helps panellists to make valid, reliable judgements independent of personal preferences. Once the training sessions have established satisfactory panel performance, and removal of ambiguities and misunderstandings, the test samples can be evaluated. This is usually carried out in replicated (commonly three) sessions, using experimental designs that minimise biases. 11.5.4 The SpectrumTM method The SpectrumTM method resembles QDA in many respects; for example, the panel must be trained to fully define all product sensory attributes, to rate the

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intensity of each and to include other relevant characterising aspects such as change over time, difference in the order of appearance of attributes, and integrated total aroma and/or flavour impact. However, the perceived intensities are recorded in relation to absolute or universal scales, which allow the comparison of relative intensities among attributes within a product and among products tested. Panellists develop their lists of descriptors by first evaluating a broad array of products that define the product category. The process includes using references to determine the best choice of term and to best define that term so that it is understood in the same way by all panellists. Words such as vanilla, chocolate or orange must describe an authentic vanilla, chocolate or orange character for which clear references are supplied. All terms from all panellists are then compiled into a list that is comprehensive yet not overlapping. The SpectrumTM method is based on an extensive use of reference points. The choice of scaling technique may depend on the available facilities for computer manipulation of data and on the need for sophisticated data analysis. Whatever the scale chosen, it must have at least two, or preferably three or five reference points distributed across the range. 11.5.5 Free choice profiling (FCP) Free choice profiling is a very different concept, which removes the need to generate a compromise consensus vocabulary (Williams and Langron, 1983), and which can also be used in consumer research (Jack and Piggott, 1992). Assessors are allowed to develop their own individual vocabularies to describe sensory perceptions of sample sets and to assign intensity scores to these attributes. As a consequence of removing the need to agree vocabularies, free choice profiling requires little training ± only instruction in the use of the chosen scale. Assessors merely have to be objective, capable of using line scales, and able to use their developed vocabulary consistently. Thus, assessors can be still regarded as representing naõÈve consumers. Characteristics being judged can be restricted by the panel leader, but the number of descriptors produced is limited only by the perceptual and descriptive skills of the assessors. A range of sensory characteristics such as appearance, flavour, aroma or texture can be examined. One particular advantage of the technique for shelf life assessment is that new attributes that develop on storage can readily be incorporated into the profile. Disadvantages include the need to use a complex statistical analysis technique (generalised Procrustes analysis) and the absence of any agreed terminology. 11.5.6 Time-related methods Time-intensity methods are used to measure intensity of a specific attribute as a function of time in the mouth, and have been used extensively to investigate the temporal behaviour of tastants, such as sweet and bitter molecules, and the release of volatile flavour materials from foods. Such studies are particularly

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important in the reformulation of foods that results in structural modifications, and in changes that can occur on storage. These structural modifications are often accompanied by textural changes, and these often result in complex perceptual phenomena that are direct consequences of the changes in texture with time producing different flavour release phenomena. Although the use of time-intensity for flavour measurement is relatively well established, textural changes can also be monitored using the method. A major limitation of the time-intensity method is that only a single attribute can be tracked with time, or, with some software packages, two attributes. If several important attributes are thought to be time-dependent, separate sessions are needed for each attribute. Difficulties encountered in time-intensity profiling prompted the development of a hybrid technique, progressive profiling (Jack et al., 1994). In this technique, assessors carried out a profile on a set of texture descriptors at each chew stroke over the mastication period. Such a method has a number of potential advantages: several attributes can be assessed in one session; scaling is reduced to a unidimensional process; and the most important aspects of the shape of a time-intensity curve are retained. 11.5.7 Statistical analysis of scaled data Univariate procedures are the starting point for the analysis of any sensory data. The procedures can be used at different stages of a sensory programme, but are particularly useful in assessing the performance of panellists undergoing training for profile panels, and for exploratory investigation of scaled data. An important consideration in selecting appropriate analysis techniques is the nature and distribution of the data. Prior to the use of any statistical procedure, the form of the data should be examined by visualisation techniques, such as the use of scatter plots. Data that are not normally distributed are analysed by nonparametric methods. It is frequently assumed that sensory data are normally distributed, and that parametric tests can be used. The distribution of all sensory data should be examined, however, especially when relatively small numbers of responses are being used. If in doubt, non-parametric tests can be employed. The most commonly used procedures used to examine sensory data are t-tests, analysis of variance (ANOVA) and multiple comparison tests. The t-test procedure can be used to compare the mean scores from two samples, usually used in the paired format if the same panellists have assessed both samples. If more than two samples are to be compared, two-way ANOVA is used with the panellists and samples as factors. Panellist  sample interactions are also usually examined. If significant differences for a given attribute are identified by ANOVA, multiple comparison tests can be used to identify which samples differ. In most applications of any form of sensory testing, the intensities of many attributes are being measured, leading to highly complex data sets. Multivariate analysis methods such as principal component analysis (PCA) are increasingly being seen as essential in interpreting such data sets, and several different uses are evident:

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· Assistance in panel training, including assessment of panellist performance and reduction of attribute lists in forming profile vocabularies. · Simplifying the complexity of data presentation. Visualisation of the relationships between two attributes is easily accomplished, and visualisation of three attributes presents few difficulties, but greater numbers of attributes present substantial problems. · Identification of redundancy in the use of descriptive attributes. · Investigation of the underlying structure between products and between the attributes characterising them. · Construction of `maps' visualising the similarities and dissimilarities between products. As sensory shelf life tests are usually carried out in conjunction with instrumental measures of product change, statistical methods can be used to explore data relationships. Methods include correlation analysis, regression analysis and multivariate analysis. Further details are given in Kilcast (2010).

11.6

Consumer acceptability testing

Consumer tests give a direct measure of liking that can be used more directly to estimate shelf life. The most common procedure is to ask consumers representative of the target population to scale acceptability on a 9-point category scale, anchored from like extremely to dislike extremely. A minimum of 50 consumers should be used, and preferably well over 100, although lower numbers (32±40) have been reported. Suitable experimental designs should be used, in conjunction with appropriate statistical analysis. Other information on individual modalities (appearance, odour, flavour and texture) can also be obtained, together with attribute intensity information, but it is preferable to keep such tests simple and to focus on overall acceptability. The most common procedure for operating the tests is to recruit consumers from a convenient high street or mall location and to carry out the tests in a convenient hall. Alternatively, a mobile test laboratory can be used to increase the degree of control.

11.7

Operation of sensory shelf life tests

11.7.1 Selection of tests for shelf life assessment The choice of tests for shelf life assessments depends on the purpose of the assessment, and on the way in which the sensory storage changes are to be interpreted in terms of shelf life. Quality grading schemes are available for some foods, for example fish (MartinsdoÂttir, 2010), but cannot be regarded as suitable systems for the shelf life assessments of most foods. Difference tests can be used if the shelf life criterion is defined in terms of the first detectable change, but in general difference tests will detect changes that are small and of little relevance to shelf life. Consequently, most sensory tests employ quantitative measures of

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change that are more open to interpretation in consumer terms. It is also possible to use hedonic tests to generate consumer acceptability directly. Such tests can be expensive, especially if used at repeated time points, and an alternative is to use quantitative sensory tests to measure change, and at critical change points to carry out consumer tests to evaluate the impact of the changes on consumer acceptability. 11.7.2 References for sensory shelf life assessment The variability of sensory data can be reduced substantially if a reference standard can be made available at each assessment session. Unless a very high level of panel training is feasible, memory of sensory quality is unreliable for most shelf life testing, especially over medium- to long-term storage periods, and reference samples should be provided for all tests. Ideally, a reference standard should be used from the same batch of product under test that can be stored under conditions in which changes do not occur. This is rarely achieved in practice, and more frequently it must be assumed that a stored reference undergoes quality change. Care must be taken to choose conditions that minimise the change. An alternative procedure is to manufacture a new reference for each test point. This is a valid procedure only in circumstances in which batch-to-batch variation is minimal; substantial variations will prejudice data interpretation. An increasingly common alternative to physical reference standard is a written specification (Beeren, 2010), generated by sensory techniques such as QDA. Whilst considerably superior to reliance on memory, successful use of such a standard requires extensive panel training and maintenance of a stable panel performance over the storage period. The problems described above are inevitably more serious in the case of shelf life tests carried out over long storage periods. 11.7.3 Ethical considerations Any sensory testing of foods must be carried out under a defined ethical policy for the use of human subjects, and general guidelines have been issued by the Institute of Food Science and Technology in the UK (IFST, 2005). This is particularly important in the case of storage testing, especially when the test protocol takes the products close to, or even past, the shelf life of the products. In particular, it is essential to assess any microbiological hazards that might be associated with testing, especially near the end of shelf life and under accelerated (especially elevated temperature) storage conditions. If necessary, microbiological testing should be carried out prior to sensory testing, preferably on the same samples to be used for sensory testing. Under no circumstances should samples of questionable microbiological quality be submitted for sensory testing. If there are any residual questions regarding microbiological quality, sensory testing should be limited to assessment of appearance and odour only.

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11.8

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Design of sensory shelf life tests

The experimental determination of shelf life can require a considerable amount of experimentation, with consequent costs and demands on time. Efficient design of such experiments is important if such tests are to be cost-effective. A statistical approach has been outlined by Gacula (1975), which describes a number of options for controlling the number of necessary measurements. In the most commonly operated type of test, a single batch of product (or replicate batches) is put on test at time zero, and samples are taken off for testing at intervals determined by the expectation of the likely shelf life (partially staggered design, Fig. 11.4a). If there is no prior knowledge of the shelf life, it may be necessary to take sufficient samples at each time point, therefore requiring extensive experimentation. In a variant of this procedure, the number of samples tested is increased up to the acceleration point, at which failure is expected, and after which a constant number of samples is tested. A further variant uses an expansion in sample numbers determined by the number of failed units. This basic type of design has the clear advantage that data related to shelf life are generated at intervals and build up to give a moving picture of deteriorative change. Whilst this carries few problems in circumstances in which instrumental measurements are the primary information source, problems are frequently encountered when sensory analysis techniques are being used to assess shelf life. This is related to the difficulties in generating consistent panel responses over time, these difficulties increasing over long storage times and if the test periods are infrequent. Several factors can contribute, mainly inconsistent use of scoring scales, changing panel composition and learning effects. If sensory profiling is the method of choice, the appearance of new attributes not present at the initial panel training stage (e.g., off-flavours) can give rise to difficulties. The ideal design for sensory testing would involve having all samples from all storage treatments and from all timepoints tested together in a balanced design. In principle, this can be achieved in three different ways: 1. Samples can be drawn from successive production batches and put into storage for an appropriate time. At the end of shelf life, all samples can be tested in an appropriate design. This design is of course susceptible to fluctuations in production quality, and can only be used in situations in which production consistency can be assured. 2. A more practical variant of this design is shown in Fig. 11.4b (drawn sample design), in which a single large batch is held under conditions under which quality changes are effectively zero, for example frozen storage. Samples are removed at appropriate intervals and stored under the desired conditions. 3. Another variant is shown in Fig. 11.4c (stored sample design). A large batch is put into storage, and samples are drawn at appropriate intervals and held under non-changing conditions (e.g. frozen) until the required storage time has been reached. The major difficulty in the last two designs is identifying appropriate non-changing storage conditions, as few foods can be stored in such a way without changes in some important quality attribute.

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Fig. 11.4 Shelf life test designs: (a) partially staggered design, (b) drawn sample design, (c) stored sample design.

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Whilst these last two designs all have the important advantage of delivering an internally consistent picture of changes in sensory characteristics, they suffer from a number of disadvantages. First, no information is generated on stability and shelf life until the very end of the storage trials, a situation which is unlikely to be tolerated in most industrial environments. Second, the setting up of the trials requires a prior knowledge of expected shelf life. Third, a large global test can impose severe logistical problems for both sensory and instrumental laboratory measurements.

11.9

Interpretation of sensory shelf life data

The various sensory test procedures generate information on whether changes are occurring, the nature of the changes that are occurring and the magnitude of the changes. Such information cannot be transformed into shelf life information unless two criteria are satisfied. First, the pattern of the changes must be understood, in terms of both the form and the direction of the change. Second, there must be a company policy on sensory quality that forms a framework within which the data can be interpreted. This is essential when interpreting analytical sensory data in terms of consumer response. These two issues are closely related, and are discussed subsequently. Important quality changes on storage are often assumed to be linear, but this is rarely the case in practice. It is also often erroneously assumed that any change represents quality deterioration, but this is clearly not the case with foods such as cheese, and beverages such as wines. Changes in product attributes with forms such as those shown in Fig. 11.5 are not uncommon, especially in the period immediately following manufacture. Clearly, the form of such changes must be known before any reliable interpretation can be made. The criteria that can be used for interpreting sensory shelf life data have been reviewed by Dethmers (1979), and fall into three categories: first detectable

Fig. 11.5

Illustrative changes in sensory attributes following manufacture.

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Fig. 11.6 Non-linear attribute change: similar differences are seen at three timepoints A, B, C.

change, measured attribute change and change in consumer acceptability. The first detectable change (or just noticeable difference) in product quality can be measured using difference tests, assuming that a suitable reference sample is available. However, difference tests can be over-sensitive to changes that have little relevance to sensory quality as perceived by consumers, and give limited information on the nature of the change. An additional problem can be encountered when non-linear changes occur, as shown in Fig. 11.6. In this case, spot difference tests carried out at timepoints A, B and C would all identify the same level of difference. This illustrates an underlying problem with the use of difference tests, which is that a quantitative picture of change is rarely attainable. If quantitative measures of relevant sensory attributes are made, a fixed level of change can be used as a criterion. This is illustrated in Fig. 11.7(a) for two products showing a decreasing attribute intensity. The decrease of this attribute is faster for product 1, reaching a critical limit at a shorter storage time. The critical limit needs to be agreed as representing the end of shelf life. Figure 11.7(b) shows an analogous situation in which an attribute that is absent at the start of storage increases in intensity. This typifies the situation in which an offflavour develops on storage. Growth of a non-characteristic attribute is often more easily detected than decrease of a characteristic attribute, and is likely to be of great importance to consumer acceptability. An alternative approach to shelf life assessment is to measure consumer acceptability directly. Figure 11.8(a) shows how direct measurement of consumer acceptability can be used to compare the shelf life of two products. Greater difficulty in interpretation is encountered, however, when the changes in acceptability of two products of different initial quality are measured. This is illustrated in Fig. 11.8(b), in which product 1 represents an economy product, and product 2 a premium product. The use of a single critical acceptability level fails to recognise the different quality levels, and in these circumstances it may be preferable to define critical levels for each product that reflect its market.

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Fig. 11.7 Level of change of a given attribute: (a) the attribute decrease is faster for product 1 than for product 2, and a critical intensity is reached more quickly, (b) the attribute increase is faster for product 1 than for product 2, and a critical intensity is reached more quickly. The curve form for product 2 is typical of off-flavour growth, for example rancidity.

11.10

Instrumental methods

Sensory measures of quality changes on storage are essential as the only valid reflection of perceived quality, but are expensive and time-consuming to operate. In addition, they suffer from high variability when carried out over long time periods, and need regular panel calibration, especially if the panel composition changes. If valid instrumental measurement methods are available, these can be of great value in augmenting the sensory data, although they are only rarely sufficiently reliable in replacing sensory data (e.g., Kilcast, 2010; Kress-Rogers, 1993). Their value can most clearly be found in long-term measurement of shelf life, which poses substantial challenges to the sensory analyst. 11.10.1 Appearance Overall appearance changes on storage can readily be tracked using either conventional or digital still photographs. This is a particularly powerful means of monitoring change in form of a product, and can be used to monitor visual

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Fig. 11.8 Changes in consumer acceptability: (a) for products starting with the same acceptability, product 1 has a shorter shelf life than product 2, (b) for products starting from different acceptabilities, different critical levels should be used.

colour changes. However, accurate rendition of colour changes requires careful standardisation of lighting conditions and photographic technique, and ideally should be carried out by a professional photographer. Successful imaging of appearance has the benefit of providing accurate visual standards that are of great value in shelf life measurement. For colour assessment alone, many instruments are available that can give relevant measurements of product colour characteristics. In addition, extensive use is made of standard colour atlases, although there are problems in applying these to wide ranges of foods. Consequently, many sectors of the food and drinks industry have devised colour matching charts specifically for their own products. Colour measurement and the use of colour atlases are discussed in detail in MacDougall (2002) and Hutchings (1999). 11.10.2 Aroma and flavour The complexity of the flavour response presents enormous difficulties for those needing a rapid and simple assessment. Measurement of the wide range of volatiles that contribute to food flavour is technically feasible, but even the most sophisticated techniques, such as gas chromatography-mass spectrometry, carry

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the risk of not identifying trace volatiles that have low detection thresholds. In principle, analysis of involatile tastants should pose a lesser problem, but, even though there are few basic tastes, the taste response can be stimulated by a wide range of food components. As a consequence, generalised analysis plays a limited role in shelf life assessment studies. If the deterioration mechanism is known, however, analysis for specific deterioration indicators, such as chemical compounds produced from rancidity development, can be highly effective. Contrary to popular expectations, the use of the so-called electronic noses and electronic tongues has been minimal in the food and beverage industries (Kilcast, 2010; RoÈck et al., 2008). 11.10.3 Texture Changes in physical properties that are perceived as textural changes can be measured using a range of techniques. Properties of fluid foods can be measured by a range of rheological techniques; properties of solid foods can be measured using mechanical techniques that typically measure force-deformation behaviour (Bourne, 2002; McKenna, 2003; Kilcast, 2004). Many of the techniques are capable of measuring change, but not necessarily change that is relevant to perceived texture. If a valid relationship can be established, such measurements can be a valuable adjunct to sensory testing.

11.11

Standardisation in sensory shelf life testing

The basic requirements for setting up and operating sensory testing procedures for foods and beverages are described in both standard texts (see Section 11.13) and in a series of Standards published by the International Standards Organisation (a full list of available standards can be found at http://www.iso.org/iso/ iso_catalogue/catalogue_tc/catalogue_tc_browse.htm?commid=47942, and some specific standards have been referred to earlier in this chapter). These provide general guidance on core sensory operations, but offer little practical advice on specific applications to activities such as shelf life testing. The American Standard (ASTM E 2454, 2005) is unique in its approach to sensory shelf life testing, in that in addition to describing appropriate sensory testing approaches, it also gives advice on possible decision criteria for establishing sensory shelf life of consumer products. The focus on the end point concept, as described in Section 11.1, forces the sensory analyst to give careful consideration to both the sensory changes that are likely to occur on storage, and to their importance to consumer perception of quality. Such focus is needed to avoid one of the most common problems in shelf life assessment, which is that studies are set up without any clear idea of the criteria that define end of shelf life, and of which measurements will be needed to generate data that relate to shelf life. Failure to define criteria and appropriate measurements very frequently leads to the generation over time of large numbers of measured parameters (both sensory

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and instrumental) that, even with the availability of multivariate statistical techniques, leads to intractable analysis problems. Use of the end point concept should circumvent many of these difficulties. This standard also gives advice on the types of test design shown in Fig. 11.4, although the notation of designs is changed to `multiple-point' and `single-point' designs.

11.12

Future trends

Progress in sensory shelf life measurement in recent years has focused on the increasing use of sensory quality specifications and on the use of consumer acceptability data. Considerable effort continues into developing simpler, costeffective test methods, and into researching accelerated test methods with the intention of developing predictive sensory shelf life models. However, the high resource levels required to design reliable methods introduce the temptation to cut too many corners, with the consequence that unstable and unreliable models are generated. In addition, warnings have been given on the validity of predictive models using sensory data (Guerra et al., 2008). Other shelf life modelling procedures have also been investigated, for example those based on artificial neural network (ANN) algorithms (Siripatrawan and Jantawat, 2009). 11.12.1 Sensory specifications In the years following the publication of the first edition of this text, the use of sensory specifications has become increasingly widespread (Beeren, 2010). Numerous different approaches have been used, although at present there has been no attempt to produce a uniform, standardised procedure, mainly as a result (at least in the UK) of conflicting requirements from the retail sector. However, a well-designed sensory specification provides the basis for not only sensory quality systems that are stable and continuous over long time periods, but also offers similar stability for shelf life testing over long time periods, with obvious benefits when dealing with long shelf life foods. 11.12.2 Survival analysis As consumer quality requirements form the basis of the most generally accepted definitions of sensory shelf life, it is of little surprise that there have been major efforts in employing consumer data in the measurement of shelf life. Particular progress has been made through the use of statistical procedures based on survival analysis (e.g., Hough et al., 2003, Hough, 2010), in which samples with different storage times are presented to consumers. Consumers are asked a question such as `Would you normally consume this product? Yes or no?' and a survival function is defined as the probability of consumers accepting a product beyond a certain storage time. The technique has been applied to a wide range of long shelf life foods, and has given superior results to other techniques in studies on bread (GimeÂnez et al., 2007).

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11.13

Sources of further information and advice

Literature on setting up and operating sensory evaluation systems is extensive. The following texts offer extensive information, but other literature is also available. Sensory evaluation

and HEYMANN H (1998). Sensory Evaluation of Food. Principles and Practices. Chapman & Hall. MEILGAARD M, CIVILLE C V and CARR B T (2006). Sensory Evaluation Techniques, 4th edn. CRC Press. Ä OZ A M, CIVILLE G V and CARR B T (1992). Sensory Evaluation in Quality Control. Van MUN Nostrand Reinhold. PIGGOTT J R (1988). Sensory Analysis of Foods, 2nd edn. Elsevier Applied Science. LAWLESS H T

Sensory perception BOURNE M C

Press.

(2002). Food Texture and Viscosity: Concept and Measurement. Academic

(1999). Food Colour and Appearance, 2nd edn. Springer. (1999). Food Texture: Measurement and Perception. Aspen. MACDOUGALL D B (2002). Colour in Food. Improving quality. Woodhead Publishing. MCKENNA B M (ed.) (2003). Texture in Food. Volume 1: Semi-solid foods. Woodhead Publishing. KILCAST D (ed.) (2004). Texture in Food. Volume 2: Solid foods. Woodhead Publishing. TAYLOR A J and ROBERTS D D (2004). Flavor Perception. Blackwell. HUTCHINGS J B

ROSENTHAL A J

Many contract laboratories offer sensory testing services that can be used for sensory shelf life assessment, but it is advisable to use those laboratories that also offer associated services relevant to shelf life measurement, in particular microbiological and physicochemical testing. In the UK, the main contract laboratories that can offer a full service package are, in alphabetical order: Campden BRI, Leatherhead Food Research, and Reading Scientific Services.

11.14

References

(2005). Sensory Evaluation Methods to Determine the Sensory Shelf Life of Consumer Products. ASTM E 2454-05. BEEREN C J M (2010). Establishing product sensory specifications. In Sensory analysis for food and beverage quality control, ed. D Kilcast, Woodhead Publishing, 75±96. BOURNE M C (2002). Food Texture and Viscosity: Concept and Measurement. Academic Press. CARDELLO A V (1996). The role of the human senses in food acceptance. In Food Choice, Acceptance and Consumption, ed. H L Meiselman and H J H MacFie, Blackie A&P. DETHMERS A E (1979). Utilizing sensory evaluation to determine product shelf life. Food Technology, September, 40±42. DUBOSE C N, CARDELLO A V and MALLER O (1980). Effects of colorants and flavorants on ASTM E 2454

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identification, perceived flavor intensity and hedonic quality of fruit flavored beverages and cake. Journal of Food Science, 45, 1393±1415. GACULA M C (1975). The design of experiments for shelf life study. Journal of Food Science, 40, 399±403. GIMEÂNEZ A, VARELA P, SALVADOR A, GASTOÂN A, FISZMAN S and GARITTA L (2007). Shelf life estimation of brown pan bread: a consumer approach. Food Quality and Preference, 18, 196±204. GUERRA S, LAGAZIO C, MANZOCCO L, BARNABAÁ M and CAPPUCCIO R (2008). Risks and pitfalls of sensory data analysis for shelf life prediction: Data simulation applied to the case of coffee. LWT - Food Science and Technology, 41(10), 2070±2078. HOUGH G (2010). Use of survival analysis statistics in analyzing the quality of foods from a consumer's perspective. In Processing Effects on Safety and Quality of Foods, ed. E Ortega-Rivas, CRC Press. Â MEZ G and CURIA A (2003). Survival analysis applied to sensory HOUGH G, LANGOHR K, GO shelf life of foods. Journal of Food Science, 68, 359±362. HUTCHINGS J B (1999). Food Colour and Appearance, 2nd edn. Springer. IFST (1993). Shelf Life of Foods ± Guidelines for its Determination and Prediction. IFST, London. IFST (2005). Ethical and Professional Practices for the Sensory Analysis of Foods (http:// www.ifst.org/documents/policy_statements/practicesforsensoryanalysis_ policystat.pdf). IFST, London. ISO 8586-1 (1993). Assessors for sensory analysis. Part 1. Guide to the selection, training and monitoring of selected assessors. ISO 10399 (2004). Sensory analysis. Methodology. Duo-trio test. ISO 6658 (2005). Sensory analysis. Methodology. General guidance. ISO 4120 (2007). Sensory analysis. Methodology. Triangle test. ISO 5495 (2007). Sensory analysis. Methodology. Paired comparison test. JACK F R and PIGGOTT J R (1992). Free choice profiling in consumer research. Food Quality and Preference, 3, 129±134. JACK F R, PIGGOTT J R and PATERSON A (1994). Analysis of textural changes in hard cheese during mastication by progressive profiling. Journal of Food Science, 59(3), 539± 543. KILCAST D (ed.) (2004). Texture in Food. Volume 2: Solid Foods. Woodhead Publishing. KILCAST D (2010). Combining instrumental and sensory methods in food quality control. In Sensory Analysis for Food and Beverage Quality Control, ed. D Kilcast, Woodhead Publishing, 97±117. KRESS-ROGERS E (1993). Instrumentation and Sensors for the Food Industry. Woodhead Publishing. MACDOUGALL D B (2002). Colour in food. Improving quality. Woodhead Publishing. MCKENNA B M (ed.) (2003). Texture in Food. Volume 1: Semi-solid Foods. Woodhead Publishing. Â TTIR E (2010). Sensory quality management of fish. In Sensory Analysis for MARTINSDO Food and Beverage Quality Control, ed. D Kilcast, Woodhead Publishing, 293315. PIGGOTT J R (1995). Design questions in sensory and consumer science. Food Quality and Preference, 6(4), 217±220. È CK F, BARSAN N and WEIMAR U (2008). Electronic nose: current status and future trends. RO Chem. Rev., 108, 705±725. SIRIPATRAWAN U and JANTAWAT P (2009). Artificial neural network approach to simul-

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taneously predict shelf life of two varieties of packaged rice snacks. International Journal of Food Science and Technology, 44, 42±49. VICKERS Z M (1991). Sound perceptions and food quality. Journal of Food Quality, 14(1), 87-96. WILLIAMS A A and LANGRON S P (1983). A new approach to sensory profile analysis. In Flavour of Distilled Beverages: Origin & Development, ed. J R Piggott. Ellis Horwood Ltd.

11.15

Appendix

Tables 11.1±11.5 show typical physicochemical and sensory factors that can change on storage and consequently limit the shelf life of different product types. Table 11.1 Fruit and vegetable products Product

Deterioration mechanisms

Limiting changes

Soft fruit

Enzymic breakdown Mould growth Moisture loss

Textural softening Visible mould Dry appearance

Hard fruit

Enzymic action Moisture loss

Textural softening, bruising Dry texture

Potatoes

Enzymic action Sprouting

Softening, poor cooking Sprouting, toxin production

Cucumber

Enzymic action

Loss of crispness, gross structure breakdown

Coleslaw

Moisture loss from vegetables Fat oxidation

Loss of viscosity in dressing, appearance changes, microbial growth Rancidity

Prepared salads

Moisture loss Oxidation

Loss of crispness, drying Browning

Fruit preserves

Syneresis Oxidation

Serum separation, mould growth Flavour loss

Dried fruit

Enzymic action Chemical reactions

Browning Flavour changes

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Meat and meat products

Product

Deterioration mechanisms

Limiting changes

Fresh red meat

Oxidation Microbial growth

Loss of red colour, rancidity Off-odours and off-flavours

Frozen meat

Oxidation Ice sublimation

Rancidity Freezer burn

Fresh fish

Microbial growth Chemical reactions

Microbial Off-odours Appearance changes

Fresh poultry

Microbial growth

Microbial Off-odours

Fresh sausages

Microbial growth Oxidation

Microbial Rancidity

Fresh bacon

Microbial growth Oxidation

Microbial Rancidity, colour change

Canned ham

Chemical reactions Can deterioration

Flavour loss Gas generation

Table 11.3

379

Beverages

Product

Deterioration mechanisms

Limiting changes

Carbonated beverages

Gas evolution Hydrolysis/oxidation

Carbonation loss Flavour loss, off-flavours, rancidity

Beer

Oxidation Microbial growth

Off-flavours Turbidity

Coffee

Volatile loss Oxidation

Flavour change Rancidity

Fruit juices

Oxidation Enzymic reactions

Flavour and nutrient loss Cloud instability

Tea

Volatile loss Volatile absorption

Flavour loss Off-flavours

Wine

Oxidation

Off-flavours Colour change

Low-calorie soft drinks

Hydrolysis

Sweetness loss

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Table 11.4 Cereal and other dry products Product

Deterioration mechanisms

Limiting changes

Bread

Starch retrogradation Moisture migration Moisture uptake Oxidation Moisture loss Starch changes Microbial growth Starch changes Protein changes Moisture migration Starch retrogradation Oxidation Moisture uptake

Stale texture and flavour Dry texture, mould growth Loss of crispness Rancidity Drying and hardening Stale flavour and texture Mould formation Texture changes, breakage Staling Softening (cereal), hardening (fruit) Stale flavour and texture Rancidity Caking Non-enzymic browning Mould, microbial growth Flavour changes Colour loss Fat crystallisation (bloom) Texture changes Staling, rancidity Texture changes Rancidity

Snack foods Cakes Dried pasta Breakfast cereals Dry mixes Spices Chocolate confectionery Sugar confectionery

Microbial growth Volatile loss Chemical reactions Fat migration Oxidation Moisture uptake Oxidation

Table 11.5 Dairy products Product Ice cream

Deterioration mechanisms

Moisture migration Oxidation Fluid milk Oxidation, hydrolytic reactions Microbial growth Dried milk powder Moisture uptake Oxidation Butter Oxidation Cheese Oxidation Lactose crystallisation Microbial growth Low-fat spreads Microbial growth Oxidation Yoghurt Syneresis Oxidation Fruit yoghurt Syneresis Oxidation Microbial

Limiting changes Ice crystal formation Rancidity Rancidity and other off-flavours Caking Flavour change, rancidity Rancidity Rancidity Gritty texture Mould Mould Rancidity Serum separation Rancidity Serum separation Rancidity Mould

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12 Advances in instrumental methods to determine food quality deterioration F. Kong and R. P. Singh, University of California, Davis, USA

Abstract: Instrumental techniques are widely used to assess the changes in quality attributes and evaluate remaining shelf life of the foods. This chapter presents some of the major instrumental techniques for evaluating shelf life of food, including determination of color, appearance, texture, rheological properties, lipid oxidation, and microbiological analysis. Recent developments in instruments and their applications such as electronic nose, electronic tongue, and Infrared (IR) Spectroscopy are discussed along with the limitations of selected instrumental techniques. Key words: instrumental determination, shelf life, electronic nose, electronic tongue, infrared (IR) spectroscopy.

12.1

Introduction

During food storage, chemical, biochemical and physical deteriorative reactions can occur that cause changes in food color, appearance, texture, and flavor, significantly impacting the overall quality attributes and consumer acceptability of foods. On the other hand, microbiological forms of deterioration can also occur that cause food spoilage and safety issues. Although sensory evaluation is routinely used in the industry to evaluate the quality of foods, it can be expensive and time consuming. Alternatively, instrumental techniques are widely used to assess quality attributes and determine changes in quality to evaluate the remaining shelf life of a food.

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Temperature and moisture are critical factors affecting the quality deteriorative reactions in foods. Food appearance, especially color, determines the first impression of consumers about food products. Texture and rheological properties such as viscosity significantly influence the taste of the food and handling characteristics of the product. All these factors may change during food storage and distribution. Lipid oxidation is one of the major spoilage reactions limiting the shelf life of foods. The unsaturated lipids in food can easily oxidize, resulting in alterations in smell, taste, texture, color and nutritional value. A number of chemical testing methods have been developed for determining the level of lipid oxidation by measuring primary and secondary lipid oxidation products. Volatile compounds are produced during lipid oxidation that are responsible for rancidity flavor. Gas chromatography (GC) is commonly used to differentiate and quantify volatile compounds. Rapid analytical techniques such as electronic nose and tongue, and infrared (IR) spectroscopy are becoming popular and attracting more attention of food processors. The advantages of these methods are their ability to provide rapid analysis and simultaneous evaluation of several parameters, and their potential for on-line or at-line use. Developments in computer science and chemometrics have enhanced the ability to analyse food quality. Instrumental methods usually have higher accuracy and reproducibility than sensory analysis. However, when instrumental techniques are used to measure sensory quality factors, they can be regarded as reliable only if the measured parameters can be correlated with the relevant sensory attributes (Kilcast, 2001). Although many instrumental methods are available to measure quality loss, some of the methods are more routinely applied in the food industry due to their simplicity, rapidity and convenience, such as color and texture determination. Other methods such as GC are used more often for research, because they are time-consuming and require expensive laboratory equipment and trained personnel. Different chemical reactions occur simultaneously during storage, but only the key reactions influencing major product quality attributes need to be measured during shelf life testing. These include crispness in biscuit, tenderness and drip loss in meat, and appearance (color, texture) in fruits and vegetables. Microbiological analysis is a primary indicator of safety in shelf life studies. The objective of this chapter is to provide a brief summary of the current status of a number of selected techniques that are often used to evaluate food quality with regard to shelf life. Key features of instrumental methods and their advantages and limitations are discussed.

12.2

Assessing food appearance

Color and other visual aspects of the appearance give consumers their first impression of the food significantly influencing their decision. The human eye perceives color as the reflected radiation in the visible region of the

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electromagnetic spectrum (400±700 nm). During storage, food color often degrades as a result of enzymatic and non-enzymatic reactions, oxidation, and other physical and chemical reactions. It is regularly used as a quality control measure of food during processing and storage. For fresh produce, color measurement is one of the few instrumental tests that gives results that correlate well with consumer assessment of quality (Aked, 2002). Kong and Chang (2009) and Kong et al. (2008) reported that soybean color can be used to predict the change of soybean quality during storage as well as tofu-making properties. Color can be assessed by using either a tristimulus colorimeter or a reflectance spectrophotometer to take color measurements of a single spot, and the data can be obtained in terms of tristimulus values, chromaticity coordinates, hue, and chroma (Clydesdale, 1998). A tristimulus colorimeter, such as the commonly used Minolta Chromameter, has three glass filters that correspond to the three primary colors in the spectrum (red, green and blue). The measured color data are expressed in a three-dimensional color space, L*, a* and b*, where the L* axis (luminance) indicates the brightness ranging from black to white, the a* axis ranging from green to red and the b* axis ranging from yellow to blue. Reflectance spectrophotometry determines the ratio of reflected light at specific wavelengths from a sample to that from a known reference standard. The spectrophotometer uses an integration sphere to collect light reflected from the sample, and normalizes the light to the source light of the reflectance. The light is calibrated with a pure white standard (100% reflection) and a black box (zero reflection) over the entire wavelength spectrum in the visible region. Results are expressed as a percentage, displayed as a graph showing reflectance versus wavelength. Different wavelength intervals may be used, typically 10 nm or 20 nm. Results from the spectral data can be converted to colorimetric values in the L*a*b* system. Spectrophotometry is more expensive than a simpler colorimetry, but it measures full reflectance curves, and is able to make colormatching and define tolerance volumes (Brimelow and Joshi, 2001). Machine vision system (MVS), also called computer vision system, is being increasingly used to assess food color and appearance. A MVS incorporates a camera to capture an image, and a computer to process and analyze the image, facilitating objective and nondestructive assessment of visual quality characteristics in food products (Brosnan and Sun, 2004). Using a camera, MVS can measure the color of the whole product surface, and is able to characterize food size, shape, roughness of surface, and defects (Chen et al., 2002; Kong et al., 2007). It has been successfully adopted to analyze the quality of various food products, including meat, fish, pizza, cheese, bread, and grain (Chen et al., 2002; Davies, 2009; Moreda et al., 2009). MVS-based online sorting systems have been developed to inspect, grade, and classify fruits, vegetables and fish (Brosnan and Sun, 2004). It is also used to locate bruising in fruits. In particular, spectroscopy and hyperspectral imaging have emerged as powerful techniques in that they can detect subtle and/or minor features and constituents in the products that are only sensitive at specific wavelengths (Van Zeebroeck et al.,

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2007; Chen et al., 2002). Moreover, when applying radiation of various wavelengths to food material, it will penetrate into the food, thus exposing the internal structure and fractures (Davies, 2009). Near infrared (NIR) and time resolved spectroscopy are used to detect internal defects such as cracks and hollow regions in melon, and brown heart in pears. Magnetic resonance imaging (MRI) and X-ray imaging techniques can also be used to evaluate global internal quality with better resolution, but are so far limited by the high equipment costs (Hertog et al., 2008).

12.3 Measurement of relative humidity (RH), moisture, and water activity (aw) The moisture content and water activity of stored food products are among the most important factors affecting food quality stability. The differences between food water activity (aw) and the relative humidity (RH) of the ambient environment will cause food to absorb or lose moisture to the ambient environment. The moisture change in the food will alter its texture. An increase in moisture content will increase molecular mobility in food and induce microbial growth. The methods for determining RH, moisture, and aw are closely related. A variety of methods have been explored over many years to obtain meaningful humidity measurements. These methods are employed either by probing the fundamental properties of water vapor or using various transduction methods which are capable of giving humidity-related measurements. Some of the available instruments include mechanical hygrometer, based on the use of materials which expand or contract in proportion to the humidity change, and chilled mirror hygrometer based on an optical technique for the determination of the dew point temperature. The chilled mirror hygrometer is known to provide the most accurate and reliable measurements, and is often used for measurements setting a calibration standard (Yeo et al., 2008). Wet and dry bulb psychrometry is also used as a simple and relativity low cost method. It consists of two thermometers, one of which measures the temperature of the sampled air (dry bulb temperature) and the other, covered with a damp wick, determines the wet bulb temperature. Absorption types of optical hygrometers, including infrared and ultraviolet hygrometers, are available based on water vapor absorption of radiation in certain optical wavelengths (Wiederhold, 1997). Electronic sensors are commonly used for RH and aw determination. Some of the most popular sensors for humidity measurements are capacitive- and resistive-based humidity sensors. Capacitive-based humidity sensors incorporate a polymer capacitor in a measuring chamber, and its capacitance can change as a function of humidity. Resistive-based sensors rely on hygroscopic materials such as conductive polymers whose conductivity changes with absorption of moisture. A conductivity hygrometer is also available, which measures electric impedance of a liquid hygroscopic substance (e.g., salt solutions) affected by the relative humidity or water activity (Chen and Lu, 2005). Recently, with the

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advent of optical fibre technology, a considerable level of research has focused on fibre-optic (FO)-based techniques for humidity sensing. FO humidity sensors employ materials whose optical property changes with humidity change (Yeo et al., 2008). As water activity of food is equal to equilibrium relative humidity divided by 100, the methods for RH measurement are also used for water activity determination, mostly involving the use of capacitance or dew point hygrometers (Mathlouthi, 2001). Moisture determination in food can use direct methods such as hot air oven drying, which is based on the weight loss of the sample when water is removed. Karl Fischer titration determines the water content in a sample based on an iodine/iodide redox reaction. It is not affected by volatile compounds, thus is advantageous compared with determination based on weight loss. Indirect measurement of moisture content includes measurement of the electrical resistance of a sample. In particular, infrared (IR) spectroscopy is increasingly used to quantify moisture of foods as a rapid and non-destructive approach. The principle of IR spectroscopy will be covered in Section 12.9.

12.4

Texture evaluation

Texture is one of the most commonly used physical indicators of food quality. Textural change may occur in stored food due to moisture migration, enzymatic hydrolysis, and other physical or chemical deteriorations that make food unacceptable for consumers. For example, fish muscle may become tough as a result of frozen storage, or soft and mushy as a result of autolytic degradation. Bread staling may occur due to moisture migration which causes a firming crumb and softer crust (Singh and Anderson, 2004). Szczesniak and her co-workers were the first to establish the relationship between the mechanical properties of a food and its texture profile (Friedman et al., 1963). They developed the method of texture profile analysis (TPA), in which a Texturometer was used to conduct a double-compression test to obtain a force±displacement curve (Fig. 12.1). A number of texture features can be obtained from the TPA profile, including hardness, cohesiveness, viscosity, elasticity, adhesiveness, brittleness, chewiness, and gumminess. TPA analysis is still frequently referred to in the literature as a standard method for texture characterization. Since Szczesniak's work, a variety of instrumental methods have been developed for texture measurements based on the mechanical parameters of food as determined by using the stress±strain or force±deformation relationship. A large number of texture measurement devices are available for different products for quality control purposes. The most popular ones include Texture Technologies' TA.XT2 Universal Texture Analyzer (Kong et al., 2007) and Instron universal testing machine (Yuan and Chang, 2007). Most measurements are based on empirical methods, in which the measured variables and procedures are from practical experience that are related to some aspect of textural quality for a

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Fig. 12.1

A typical force±displacement curve obtained from a TPA test.

certain range or specific products (Kilcast, 2001). Examples include using Magness±Taylor testers to assess fruits, Warner±Bratzler shear fixture to measure meat tenderness, and FMC Pea Tenderometer to grade pea quality. These devices measure the resistance of food during penetration, shearing, or compression by the machine. Extrusion devices are also used in which the food is forced through one or more orifices. Kong et al. (2007) developed a multipleblade texture probe to measure shear force of fish muscle as a representative indicator of tenderness. The results of empirical methods are ill-defined physical properties, i.e., the measured properties are dependent on the method of measurement. On the other hand, fundamental methods have been developed that measure well-defined physical properties of food. In these cases, the measured properties are independent of measurement method, thus they can be measured with general-purpose testing machines. The commonly measured fundamental parameters include Young's modulus, shear modulus, and bulk modulus (Kilcast, 2001). Physical measurement of textural characteristics can be of practical value only if it is shown to relate to some relevant sensory textural property. Statistical techniques are used to analyze and describe relationships between instrumental data and sensory texture profiling scores. Significant correlation has been reported between sensory and instrumental testing of texture for some foods and selected texture parameters (Adhikari et al., 2003; Rahman et al., 2007). However, the correlation is often dependent on the methods used in the measurements, such as type of probe, cross-head speed, sample position and alignment, and distance of penetration or strain. Therefore these methods must be chosen carefully to obtain the best possible correlation with sensory measurements. An extensive review of the principles and applications of texture measuring methods was published by Bourne (2002). Advances in food research and practice have resulted in new approaches for texture determination. Acoustic property of food during fracture corresponds closely to human perception of food crispness and crunchiness; therefore sound

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signal of foods during crushing can be used to evaluate crispness (Chen, 2009; Juodeikiene and Basinskiene, 2004; Liu and Tan, 1999). Sonic resonance testing is used as a non-destructive measurement to evaluate firmness, rigidity and the ripening for fruits and vegetables (GoÂmez et al., 2005). Spectroscopic and related methods are also developed for texture assessment. For example, nearinfrared (NIR) spectroscopy has been used to assess firmness of apples and other fresh fruits. The mechanism involves the backscattered radiation spectrum which is affected by both the scattering and absorption properties of the tissue, thus providing information about the physical structure (Hertog et al., 2008). Multivariate statistical techniques such as partial least squares regression are needed to analyze the relationship between the backscattered radiation spectrum and the texture. Mid-infrared (MIR) spectroscopy coupled with chemometrics has been successfully used to predict instrumental texture and meltability attributes of processed cheese samples (Fagan et al., 2007; Qing et al., 2007). A recent development in textural instruments is the application of the electromyography (EMG) technique. An acoustic-EMG system quantifies food texture by monitoring the mastication process through imaging techniques such as real-time magnetic resonance imaging (MRI), and acoustic sensors to record the auditory signals produced during mastication. This technique makes it possible to correlate food physics with the physiology of oral processing and food sensory perception, with the potential to become an alternative to texture profile analysis (TPA) and sensory texture measurements (Chen, 2009; Jessop et al., 2006).

12.5 Evaluation of rheological properties of liquid and semisolid foods Liquid and semi-solid food materials are generally non-Newtonian in nature, that is, the determined viscosity value is dependent on the shear rate. The majority of food materials display shear-thinning behavior. The Power Law model is commonly used to describe the relationship between viscosity and shear rate, from which the flow behavior index and consistency index can be derived. The rheological properties for liquid and semisolid foods are characterized in terms of viscosity, flow behavior index, consistency index and yield stress, which may experience significant change during storage. For example, the flow behavior index of concentrated milk changes significantly with storage time (VeÂlez-Ruiz and Barbosa-CaÂnovas, 1998). The complex viscosity of yogurts increases during storage due to the increase in lactic acid and production of exopolysaccharides (Saint-Eve et al., 2008). Fundamental methods determining food rheological properties are conducted by applying a well-defined stress on a food sample and measuring the shear rate or alternatively by measuring the developed shear stress on the food in a range of well-defined shear rates. The capillary viscometer is the simplest form of viscometer. The principle involves measuring the time taken for a fixed volume

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of the test fluid to pass through a length of capillary tubing. Rotary viscometry is the most commonly used instrument for testing food rheological properties, in which a sample is loaded between two surfaces, and one of which undergoes an applied rotary motion. The geometry of these surfaces can be a pair of parallel plates, cone and plate, or concentric cylinders. Based on how the rotating surface is controlled, these instruments may be rate- or stress-controlled (McKenna and Lyng, 2003; Steffe and Daubert, 2006). For more details, the reader is referred to the books by Bourne (2002) and Rao (2007). When taking measurements, it is important to select a range of shear rates covering the whole scope of interest, as power law fluids may not exhibit the same behavior over the entire range of shear rates. Empirical methods of measurement are also widely used for determination of rheological properties and quality control. Foods with non-homogeneous complex structures unsuitable for fundamental methods are commonly measured with empirical methods. They are used to obtain an index of product rheology, correlate with results from sensory analysis and sometimes even considered as official identification standards. For example, dough testing equipment is commonly used to determine flour specifications, such as the strength and mixing properties of dough, by using specialized testing including farinography, mixography, extensiography, and alveography. Other examples include rapid visco analysers, viscoamylographs, falling ball viscometers, Bostwick consistometers, Adams consistometers, Zhan viscometers, and Hoeppler viscometers. Description of these devices can be found in the books by Steffe (1996) and Rao (2007).

12.6

Assessing lipid oxidation

Lipid oxidation is one of the major forms of spoilage in foods resulting in development of objectionable flavors and odors known as `oxidative rancidity', thus leading to degraded quality and reduced shelf life of the product. Food lipids are composed mainly of triacylglycerols, which are esters of three fatty acids and a glycerol molecule. The fatty acids vary in chain length, degree of unsaturation and position on the glycerol molecule. When oxygen is present, lipid oxidation may occur consisting of a series of complicated autocatalytic processes, as shown by: Reactants (unsaturated lipids and O2) # Primary products (hydroperoxides and conjugated dienes) # Secondary products (ketones, aldehydes, alcohols, hydrocarbons) Peroxides (R±OOH) are primary reaction products formed during the initial stages of oxidation. They easily decompose into the secondary products, most of which, especially aldehydes, have strong off-flavors. In addition to rancid flavor, lipid oxidation also causes loss of vitamins, formation of potentially toxic

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compounds, and eventually unacceptability of the food. The oxidative stability of an oil or fat depends on the degree and nature of the unsaturation of its triglycerides, its antioxidants content, the presence of pro-oxidants such as trace metals (copper and iron), and storage conditions (such as temperature and light). A number of methods have been developed to characterize the extent of lipid oxidation in foods. The methods of peroxide value (PV) and thiobarbituric acid (TBA) are mostly used for general quality estimation. Other methods measure the content of conjugated dienes or use p-anisidine. Gas chromatography (GC) is commonly used for headspace analysis of the volatile oxidation products giving results that correlate well with sensory evaluation, but the method requires access to gas chromatographic equipment, and therefore it is more often used in research. 12.6.1 Peroxide value The peroxide value (PV) determines the concentration of hydroperoxide, the primary oxidation products. The principle involves peroxides liberating iodine from potassium iodide, i.e. ROOH ‡ KI ÿ! ROH ‡ KOH ‡ I2 The amount of ROOH is then determined by measuring the amount of iodine formed, which is done by titration with sodium thiosulfate and using a starch indicator: I2 ‡ starch ‡ 2Na2S2O3 (blue) ÿ! 2NaI ‡ starch ‡ Na2S4O6 (colorless) The amount of peroxides is calculated back by the amount of sodium thiosulfate (Na2S4O6) consumed. It is expressed as peroxide value (PV) in units of milliequivalents (meq) peroxide per 1 kg of fat extracted from the food. A general rule is that PV should not be above 10±20 meq/kg fat to avoid rancidity flavor (Connell, 1975). 12.6.2 Thiobarbituric acid (TBA) The peroxide value only indicates the amount of primary products. Because hydroperoxides are easily broken down into secondary products, the PV value may not reflect the whole extent of lipid oxidation. TBA is used to quantify the secondary oxidation products. Specifically, TBA measures the concentration of malonaldehyde, a secondary reaction product and a reactive aldehyde. During the TBA test, the thiobarbituric acid reacts with malonaldehyde resulting in the formation of a pink colored complex. The intensity of this pink color is determined by measuring its absorbance at 540 nm with UV-visible spectrophotometer, which is directly related to the concentration of malonaldehyde in the original sample. For this reason, this test is also referred to as the thiobarbituric acid reactive substances (TBARS) method. The results are expressed as micromoles malonaldehyde present in 1 g of fat. Foods with TBA above 1±2 mol MDA-equivalent per g fat will probably have rancid flavour (Connell, 1975).

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12.6.3 Conjugated dienes This method measures primary oxidation products; therefore it is only useful for monitoring the early stages of lipid oxidation. Along with the formation of peroxides, conjugated dienes containing conjugated double bonds (C=C±C=C) are formed based on the non-conjugated double bonds (C=C±C±C=C) that are present in the natural unsaturated state. The conjugated dienes strongly absorb ultraviolet radiation at 233 nm. Thus oxidation can be simply measured by dissolving the lipid in a suitable organic solvent and measuring the change in its absorbance with time using a UV-visible spectrophotometer. Conjugated dienes are broken down into secondary products in the later stages of lipid oxidation, leading to a decrease in absorbance. As some secondary products also have this conjugated structure and will contribute to the absorbance, the method is less specific than PV measurement. 12.6.4 p-anisidine Aldehydes deriving from the secondary oxidation of fats can react with panisidine to give products that absorb at 350 nm. By using a UV-visible spectrophotometer to measure the absorption, one can estimate the amount of secondary oxidation products of fat. The result is expressed as p-anisidine value or AnV. Measurements of p-anisidine value are commonly combined with peroxide value measurements to describe the total extent of lipid oxidation, as expressed by `Totox value'. Totox value is an empirical parameter equivalent to the sum of the p-anisidine value plus twice the peroxide value. 12.6.5 Analysis of volatiles with GC Gas chromatography (GC) is the most powerful method to identify and quantify individual aroma components, and monitor volatile lipid oxidation products of food. It is commonly used to quantify the secondary oxidation products including aldehydes, ketones, alcohols, short carboxylic acids and hydrocarbons. Some of these volatile compounds are highly specific to the oxidative degradation of a particular polyunsaturated fatty acid family. For example, hexanal, a main aldehyde formed during the oxidation of linoleic, gammalinolenic and arachidonic acids, is often measured as a good marker of oxidative rancidity (Pastorelli et al., 2006, 2007). The GC approach consists of three steps: recovery of volatile components, separation using GC column, and detection using mass spectrometry (MS), flame ionization detection (FID), or olfactory method. Volatile oxidization products can be recovered by means of extraction, for example, simultaneous steam distillation extraction (SDE) is one of the commonly used extraction methods. During SDE, a sample is distilled and the volatiles are collected in the extraction solvent. The solvent is then dried using a drying agent and the volatile components are concentrated by slow evaporation. The concentrated volatile analytes are then injected into the GC column. Compared to SDE, headspace

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analysis is more rapid and labor saving. Headspace analysis can be performed by static headspace (SH), dynamic purge-and-trap headspace (DH) or solid phase microextraction (SPME) techniques. SH involves collecting volatile compounds evaporated from a sample placed in an airtight vial. The headspace volatiles are harvested after equilibrium is reached, and are then injected into the GC column. This method can only quantify a fraction of the target compounds and the sensitivity is limited (Plutowska and Wardencki, 2008). DH involves using inert gas continually purging sample to extract volatile compounds, and the volatile analytes are then collected by passing the gas effluent through a porous polymer trap. This method can yield a high concentration of volatile compounds thus leading to high sensitivity (Plutowska and Wardencki, 2008). SPME utilizes adsorptive polymeric film to absorb volatile analytes, and the analytes are then released into the GC column. It is a simple, effective tool for detecting low levels of flavor compounds in foods and beverages, requiring less complex equipment than SH and DH (Laguerre et al., 2007a). In a gas chromatography column, the volatiles are separated, and the separated analytes are labeled and quantified by a detector. Flame ionization detector (FID) or mass spectrometry (MS) are the most often used detectors. GC-MS allows one to quantify aldehydes in g kg±1 concentrations (Varlet et al., 2007). GC-olfactometry is also used to determine the active odor compounds, in which sensory evaluation of the elute from the chromatographic column is conducted by a trained panel. This method involves installation of an olfactometric port that allows the sample to be split into two parts, for detector and for sensory evaluation, respectively (Fig. 12.2). GC-olfactometry allows qualitative and quantitative evaluation of the odor for each analyte leaving the chromatographic column, which helps to determine the intensity of the odor and understand the sensory properties of a certain compound at a given concentration (Plutowska and Wardencki, 2008). As MS is capable of interference-free detection and quantitation of each individual compound in a complex sample, a recent advance in the analysis of volatile fractions of foods is to directly couple MS with static headspace (SH),

Fig. 12.2

Scheme of the gas chromatograph equipped with the olfactometric detector.

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dynamic headspace (DH), or solid-phase microextraction (SPME). In this way, the GC separation step is omitted, leading to a fast characterization of food volatile fractions, and a rapid classification or prediction of quality factors. The mass spectrum obtained without prior chromatographic separation forms a `spectral fingerprint' from which qualitative or quantitative information can be extracted to predict food quality, using multivariate analysis, such as principal component analysis, linear discriminant analysis, partial least squares, and soft independent modeling of class analogy (Laguerre et al., 2007b). This method has been used to characterize cheeses (Peres et al., 2001) and study off-flavors in milk (Marsili, 1999).

12.7

Electronic nose

Electronic nose (EN) is an artificial olfactory system based on the GC volatile methods. It can detect and recognize a wide spectrum of odor patterns, and determine the odor intensity of mixtures of a variety of volatile oil degradation compounds. An EN can function as a rapid and non-destructive tool for on-line flavor characterization, especially, for rancidity analysis of foods during storage. The application of EN in the food industry has been increasing due to its rapidity, cost-effectiveness, objectivity and simplicity. An EN is composed of three elements: a sample handling system, a detection system, and a data processing system. The sample handling system introduces the volatile compounds present in the headspace of the sample into the detection system, by using the method of static headspace (SH) technique, dynamic headspace (DH) techniques, or solid-phase microextraction (SPME). The detection system consists of an array of gas sensors, which are electronic chemical sensors based on conducting polymers, metal oxides, surface acoustic wave devices, quartz crystal microbalances, or combinations of these devices. Of the various types of sensor, those based on metal oxides appear to be most suitable for the discrimination of different stages of lipid oxidation, and hence for shelf life prediction (MuÈller and Steinhart, 2007; Vinaixa et al., 2005). In the data processing system, responses generated by each sensor from the detection system are subject to analysis by pattern recognition (PR) techniques, in which principal component analysis or artificial neural network are commonly employed (Peris and Escuder-Gilabert, 2009). The partial specificity of gas sensors toward volatile components and the appropriate PR system make EN capable of recognizing simple or complex odors, and characterizing and discriminating products by their volatile components. Electronic noses have been commercialized. Some of the major manufacturers include Win Muster Airsense (WMA) Analytics Inc. (Schwerin, Germany), Alpha M.O.S. (Toulouse, France) and Cyrano Sciences Inc. (Danbury, CT, USA) (Tamaki et al., 2008). Figure 12.3 shows a portable electronic nose (PEN2) produced by WMA Analytics Inc. PEN2 consists of a sampling apparatus, a

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Schematic diagram of electronic nose measurement.

detector unit containing the array of sensors, and pattern recognition software (Win Muster v.3.0) for data recording. The sensor array system is composed of 10 metal oxide semiconductors (MOS) with different specificity for volatile compounds. EN systems are gaining applications in the food industry in process monitoring, shelf life investigation, freshness evaluation, authenticity assessment and other quality control studies. It is used to detect lipid oxidation of foods and change in aroma, in, for example, wine (GarcõÂa et al., 2006), meat (Tikk et al., 2008; Vestergaard et al., 2007) and fruits (Infante et al., 2008; Saevels et al., 2004). It is also used to monitor quality change and evaluate shelf life in nut (Pastorelli et al., 2007), olive oil (Mildner-Szkudlarz and Jelen, 2008), and cheese (Limbo et al., 2009). Other uses include characterization and classification of wines (Buratti et al., 2004; GoÂmez et al., 2006), and determination of fruit ripeness such as tomato (GoÂmez et al., 2008), mandarin (GoÂmez et al., 2007) and apple (Peris and Escuder-Gilabert, 2009). In addition to differentiating volatiles, EN can be used to assess other quality properties such as texture. This is done through multivariate statistical analysis to correlate electronic nose signals and quality indicators measured by other instruments. For example, good correlation was obtained between electronic nose signal and apple firmness (Brezmes et al., 2001; GoÂmez et al., 2008). Recently, a new type of EN system based on mass spectrometry has been investigated. As mentioned earlier, SPME-MS provides rapid classification or prediction of volatile components. This methodology is used in EN as an alternative design (Marsili, 1999). Similarly, multivariate statistic analyses (MVS) including principal component analysis are required to analyze signals from MS to differentiate between samples (Mildner-Szkudlarz and Jelen, 2008; Pastorelli et al., 2007). This new mode of EN composed of SPME-MS-MVS has been used to discriminate types of off-flavor problems in milk (Marsili, 1999) and apple (Saevels et al., 2004). The main problem with EN technology is `electronic drift' (Hertog et al., 2008), referring to the instability of signal over time. It is caused by physical

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changes in the sensors and the effects of the environment as well as the composition of the gaseous sample. One possible solution to this problem is to view sensor arrays as time-varying dynamic systems, and track the variation using adaptive estimation algorithms (Dutta et al., 2003).

12.8

Electronic tongue

Corresponding to electric nose, `electric tongue' (ET), also called artificial tongue, has been developed to detect taste and olfaction in foods. By mimicking the human tongue to differentiate tastes of sourness, saltiness, bitterness, sweetness and umami, ET is capable of both qualitative recognition and quantitative determination of taste. ET is based on an array of sensors displaying high cross-sensitivity to various substances in aqueous media (Li et al., 2006), which allows fast recognition and classification of multiple components, as well as quantitative determination of concentrations of these components. Compared with a sensory panel, the advantage of ET lies in its cost-effectiveness, rapidity, small sample volume requirement, objectivity, and ease of use. The basic structure of ET is shown in Fig. 12.4. The core part of the ET is the array of non-specific chemical sensors with a high cross-sensitivity. Crosssensitivity means that the sensor responds not to a single analyte but to several substances simultaneously present in the analyzed media. Two commonly used sensor types are potentiometry and voltametry. The potentiometric sensors are more selective than a voltametric sensor that makes data interpretation easier to operate; while the voltametric technique has higher sensitivity, versatility, and robustness. The digitized signals are recorded in the computer, and processed by statistical software to interpret the sensor data into taste patterns. ETs have been used in various areas in the food industry, and have proven to be successful in discrimination and classification, quality evaluation and control, process monitoring and quantitative analysis of foodstuffs and beverages. It has been applied to classify types of wines and discriminate varieties of apples (Buratti et al., 2004). Beullens et al. used an ET originally developed at Saint Petersburg University to classify tomato cultivars (Beullens et al., 2008; Vlasov et al., 1994). The system contained a sensor array of 18 potentiometric chemical

Fig. 12.4 Schematic diagram of electronic tongue.

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sensors. These sensors exhibit sensitivity to organic acids and minerals. A conventional Ag/AgCl electrode was used as a reference. When the sensors were exposed to tomato juice, equilibrium was obtained within 3 minutes and the chemical composition of the sample was determined. The 18 potential values were recorded in computer data files. Multivariate statistical data analysis techniques including principal components analysis, canonical discriminant analysis and partial least squares regression were used to quantitatively relate the taste compounds to the sensory panel scores and to classify tomato cultivars based on similarity in taste profile. The result showed that the electronic tongue was very well suited to classify tomato cultivars. Furthermore, the ET was suitable to quantify individual sugars, acids and minerals in a complex mixture (Beullens et al., 2008). Other researchers also found good correlation between instrument output and sensory descriptors pertaining to the global quality of a food sample (body, overall quality, and astringency) (Rudnitskaya et al., 2009). Recent reviews in this subject include Li et al. (2006) and Ampuero and Bosset (2003). EN and ET are sometimes combined as fusion sensors for food flavor detection, simulating the coexistence of the two sensory functions in humans (Li et al., 2006). Buratti et al. (2004) reported that combination of EN and ET in classification of Barbera wines gave 100% correct assignation. However, Cosio et al. (2007) reported that the ET did not seem to improve classification performance when electronic nose and electronic tongue are both used to evaluate olive oil samples stored under different conditions and periods (Cosio et al., 2007). Therefore, the success of combining electronic nose and tongue may be more dependent on the specific product concerned and storage conditions involved.

12.9

Infrared (IR) spectroscopy

Infra-red light is part of the broad spectrum of energy known as electromagnetic radiation. Within the infrared wavelengths of light, the waveband between 4 and 400 cm±1 is categorized as far infrared, between 400 and 4000 cm±1 is categorized as mid-infrared (MIR) and between 4000 and 14 000 cm±1 is categorized as near infrared (NIR). Identification of compounds in food by IR spectroscopy is based on the property of molecules to absorb the infrared light and experience a wide variety of vibrational motion characteristic of their composition. When coupled with chemometric data analysis techniques, NIR and MIR spectroscopy are rapid techniques that possess potential selectivity for screening products for qualitative attributes. IR spectroscopy in the mid- and near-infrared regions has become a powerful, fast, and non-destructive tool, and is widely used for quantitative analysis and quality evaluation of foods. The basis of spectroscopic techniques to study chemical composition of the food relies on wavelength-dependent interaction of light with the food material. In IR spectroscopy, a beam of infrared light passes through the sample.

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Radiation interacting with a sample may be absorbed, transmitted or reflected. The reflected or transmitted radiation can be measured, and the spectra contain information of molecular groups and chemical composition. Water, sugar, acids and a range of other organic substances absorb near infrared (NIR) light in proportion to their concentration. These absorption features make NIR spectroscopy able to discriminate the constituent parts of a foodstuff, and assess the concentration of each constituent. Absorption bands in the MIR region are generally due to intra-molecular phenomena and specific molecular composition and structure. Analysis of a food sample using the MIR spectrum (4000± 400 cmÿ1) reveals information about the molecular bonds present and can therefore give details of the types of molecules present in the food. Compared with MIR radiation, NIR can typically penetrate much further into a sample, which makes it suitable for probing bulk material with little or no sample preparation. The NIR spectrometer is generally composed of a light source, a monochromator, a sample holder or a sample presentation interface, and a detector, allowing for transmittance or reflectance measurements (Fig. 12.5). The light source is usually a tungsten halogen lamp or laser emission diode (Huang et al., 2008). The monochromator instrument may be a grating or a prism used to separate the individual frequencies of the radiation either entering or leaving the sample. The wavelength separator rotates so that the radiation of the individual wavelengths subsequently reaches the detector. Detector types include silicon, lead sulfide and indium gallium arsenide, with different size, speed, sensitivity and signal-to-noise properties (Reich, 2005). As radiation may be absorbed, transmitted or reflected, there are different measurement modes fitting different applications, and the two most frequently used are diffuse transmittance and diffuse reflectance (Huang et al., 2008). With the improvement of computer technology, Fourier transform infrared (FTIR) spectrometry has been developed and increasingly used in food

Fig. 12.5 Basic NIR spectrometer configurations.

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applications. Instead of a monochromator used for a NIR spectrometer, in FTIR, the IR light is guided through an interferometer to generate modulated light. By collecting interferograms of a sample, the FTIR spectrometer measures all infrared wavelengths simultaneously, rather than individual wavelengths of the radiation each time for NIR. The interferogram is then converted into a conventional spectrum using the Fourier transform algorithm. FTIR spectrometers are cheaper than conventional spectrometers but more rapid in response since information at all frequencies is collected simultaneously. A critical part in IR spectroscopy is to build a reliable and stable calibration model through using chemometrics (multivariate statistical techniques) to analyze a great deal of spectral data, i.e., to extract the information of quality attributes from the NIR spectrum (NicolaõÈ et al., 2007). To obtain accurate and reproducible calibration models, partial least squares regression and principal component regression are frequently used to estimate the component concentration and chemical and physical properties from the infrared spectra. Classification methods such as soft independent modeling by class analogy, K-nearest neighbors and artificial neural networks are powerful tools for the characterization, differentiation and classification of complex spectral data (Shiroma and Rodriguez-Saona, 2009). IR spectroscopy is a well-established technology and its use started 50 years ago. Now it is commonly used for rapid analysis of moisture, protein and fat content of a wide variety of agricultural and food products. It is a major method for determining authenticity of food products such as fats and oils, soluble coffee, green coffee and fruits. Rudnitskaya et al. (2006) reported that FTIR with attenuated total reflection (ATR-FTIR) can discriminate apples of varieties Jonagold and Golden Delicious despite the quite similar composition of these two apple varieties (Rudnitskaya et al., 2006). IR spectroscopy allows the measurement of many important parameters within a short period of time. For example, with NIR and MIR, moisture and fat content in potato chips can be determined within 5 min, compared to the 10±16 h required for conventional methods (Shiroma and Rodriguez-Saona, 2009). This feature, plus its noninvasive and non-destructive nature, makes the IR spectroscopic technique very suitable for online monitoring processes. The NIR technique is widely accepted as one of the most promising on/in-line process control techniques detecting fat, moisture, and protein content in meats, fruit and vegetables, grain and grain products, milk and dairy products, and beverages and other products (Huang et al., 2008). IR spectroscopy, coupled with the use of chemometric techniques, provides a reliable, accurate method for predicting the shelf life of foods under different storage conditions. The chemical and physical deteriorative reactions in foods during storage cause changes in a number of quality attributes that are reflected in IR spectra, thus IR spectrometry is suitable for evaluating food shelf life, including evaluation of loss of freshness, and onset of spoilage of various foods (Farkas and Dalmadi, 2009). IR spectroscopy was used to study shelf life of green asparagus (SaÂnchez et al., 2009), Crescenza cheese (Cattaneo et al., 2005),

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ricotta cheese (Sinelli et al., 2005), and fresh-cut pineapple (Di Egidio et al., 2009). New applications are being developed with IR spectroscopy. As the propagation of NIR radiation in food is affected by their microstructure, NIR spectroscopy is used to measure microstructure-related attributes, such as stiffness and internal damage, and even sensory attributes (NicolaõÈ et al., 2007). Other developments in NIR spectroscopy include multi- and hyperspectral imaging techniques to attain both spatial and spectral information from food material, thus obtaining a global measurement of quality attributes (Gowen et al., 2007). In addition, variations on spectroscopic techniques, such as time resolved spectroscopy and space resolved spectroscopy, have been developed to interpret the backscattered radiation spectrum differently, which may lead to novel and better calibration models for various fruit quality attributes including texturerelated attributes (NicolaõÈ et al., 2007).

12.10

Microbiological testing

Routine microbiological testing of food has traditionally involved enumeration of total numbers of organisms by direct microscopic methods or viable counts. These conventional methods are time consuming and labor intensive, and provide limited information about the behavior of microorganisms in food that may be important for assessing food quality and predicting shelf life. In recent years, much interest has been focused on development of rapid and automated methods in microbiology. These include automation and mechanization of traditional methods to facilitate easy handling of large numbers of samples and processing data using computational statistical techniques (White, 1993). A variety of rapid and sensitive methods have been developed. One of them is to use a special culture medium, which incorporates bio-chemical reaction substrate, antibody, fluorescence, reaction substrate, or enzyme substrate to the culture medium, enabling a better separation and identification of target microorganisms (Atlas, 1993). Another fast developing area is immunological techniques, which discriminate the bacteria by the differential combination reactions of antigen and anti-body involving immune magnification through immunofluorescence and irradiation immunity (Yali et al., 2009). Traditionally, the microorganisms in food have been studied by culture-based methods. The limitation of this method is its inability to detect non-culturable cells and failure to characterize minor populations of microorganisms. Cultureindependent techniques are thus developed, such as the polymerase chain reaction (PCR) technique based on the amplification of polymerase chain reaction and detection of nucleic acids. Compared with traditional culture-based methods, these new methods are generally faster, more specific, more sensitive and more accurate, and are now increasingly applied in food microbiology (Juste et al., 2008).

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Future trends

An important trend in shelf life evaluation is to develop rapid, simple, low-cost analytical tools that are suitable for on-line monitoring or quality control (Farkas and Dalmadi, 2009). Examples include machine vision system, electronic nose and tongue, and FTIR spectroscopic methods discussed in this chapter. Similar approaches include the use of chemical `markers', which employ biosensors and other types of sensors to track and analyze shelf life deterioration. Readers can obtain information on these topics from numerous literature resources, including Kress-Rogers (2001). These methods are rapid, non-destructive, non-invasive and cost-effective, representing the direction of instrumental development for assessing quality changes and enhancing control during processing and storage of foods. They are also suitable for on-line or rapid at-line measurement of quality attributes relevant to shelf life of foods which are of increasing importance to the food industry.

12.12

Sources of further information and advice

Additional references in the area of instrumentation for shelf-life evaluation are listed below: (2006). Rapid methods of assessing as a tool for quality improvement and standardization of food products. Electronic Journal of Polish Agricultural Universities 9(3), #07. MAN, C.M.D., JONES, A.A. (1999). Shelf Life Evaluation of Foods. Gaithersburg, MD: Aspen Publisher Inc. Â ZARO, D., LOMBARD, B. ET AL. (2007). Trends in analytical methodology in RODRIÂGUEZ-LA food safety and quality: monitoring microorganisms and genetically modified organisms. Trends in Food Science & Technology 18(6): 306±319. STEELE, M. (2004). Understanding and Measuring Shelf-life of Food. Boca Raton, FL: CRC Press. KONIECZNY, P., BILSKA, A., UCHMAN, W.

12.13

References

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13 Modelling microbiological shelf life of foods and beverages A. AmeÂzquita, D. Kan-King-Yu and Y. Le Marc, Unilever R&D Colworth, UK

Abstract: Predicting the fate of spoilage and pathogenic microorganisms can be very beneficial for food manufacturers if they are to market their products without harm to consumers and damage to the brand, through loss of quality. This chapter discusses the different biological `end-points' that are relevant to the application of predictive models in food manufacture, presents an overview of the mathematical modelling approaches available for microbial shelf life prediction of foods and beverages, and describes the key considerations for development of predictive microbiological models, as well as the main limitations and practical considerations for the sound application and usage of models. Key words: predictive microbiology, mathematical modelling, microbial growth, microbial spoilage, hurdle technology.

13.1

Introduction

Food is inherently perishable and, depending on its physical and chemical properties and the storage conditions, there will come a point when either its quality will be unacceptable or it will become harmful to the consumer. At this point it has reached the end of its shelf life and the ability to predict this is of great value to the food industry when defining storage and distribution conditions and limits, formulating products, assessing manufacturing processes and doing quantitative risk assessment. Furthermore, having the ability to predict accurately the shelf life of a product would reduce the risk of unnecessary disposal of wholesome food due to a conservative estimate of its shelf life. In

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designing a food product, it is important to identify which factors determine its shelf life: these may be microbiological, chemical or physical depending on the product, the process, the packaging and the storage conditions. This chapter focuses only on aspects related to the prediction of microbiological shelf life (safety and stability aspects), and it does not address chemical or physical factors affecting the shelf life of a food product. Depending on the product, process and storage conditions, the microbiological shelf life may be determined by either the growth of spoilage or pathogenic microorganisms. Traditional methods for determination of shelf life due to spoilage microorganisms include storage of the product at different temperatures and determining spoilage by sensory evaluation or microbial count. In the case of shelf life set by growth of pathogenic microorganisms, such methods may involve challenge testing the product with the organism prior to storage and microbiological analysis at intervals. These methods are labourintensive, time-consuming and expensive. Therefore, being able to predict the behaviour or fate of these various groups of microorganisms is very beneficial if manufacturers are to market their products without harm to consumers and damage to the brand, through loss of quality. Although challenge tests or product storage trials are often still used, the use of mathematical models to predict microbial behaviour or fate can help to reduce the need for them. Mathematical modelling in food microbiology is nowadays a well-established discipline, and has extended beyond academic research interests to real added-value industrial applications. There are several dedicated reference books (Brul et al., 2007; McKellar and Lu, 2004; McMeekin et al., 1993; Peleg, 2006), a number of electronic resources (which will be discussed later), and a plethora of peerreviewed publications, with some relevant recent review papers presented by Marks (2008), McMeekin (2007), McMeekin et al. (2002), and a complete special issue of the International Journal of Food Microbiology presenting selected papers from the Fifth International Conference on Predictive Modelling of Foods (PMF5), with the preface written by Koutsoumanis et al. (2008). In developing predictive models for spoilage microorganisms, the concept of specific spoilage organisms (SSOs) has proven to be very valuable in prediction of shelf life of certain types of foods such as seafood and meat products (Dalgaard, 1995; Koutsoumanis and Nychas, 2000; Kreyenschmidt et al., 2010; Nychas et al., 2008). An SSO can be defined as the fraction of the total microflora in a specific food product that is able to establish itself as the dominating population and is responsible for spoilage. The application of this concept assumes that the SSO produces the metabolites responsible for spoilage, that the rate of metabolite production is proportional to its growth rate, and that spoilage is noticeable when the SSO reaches a minimal spoilage level (MSL). As such, the end of shelf life can be defined on the basis of a spoilage criterion which could be either given by the time the SSO requires for multiplication from an initial population level to the MSL or by the time required for the production of a certain metabolite by the SSO to a level which results in sensory rejection (Dalgaard, 1995; Koutsoumanis and Nychas, 2000). Therefore, kinetic growth

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models as a function of the spoilage domain (i.e. the space of environmental conditions within which the SSO is responsible for spoilage) are relevant and often used. For products where the shelf life may be set by the growth of pathogenic microorganisms, the range of relevant organisms is wide and includes infectious pathogens (e.g., Listeria monocytogenes), toxin-producing organisms (e.g., Staphylococcus aureus) and toxico-infectious agents (e.g., Bacillus cereus). Depending on the pathogen of concern, growth/no-growth models are often more appropriate, since manufacturers need to design foods that do not support even small amounts of growth during shelf life (e.g., where L. monocytogenes is tolerated in foods, such as in Europe, this is generally up to a level of 100 cfu/g of food). For organisms that can be tolerated at higher levels, such as B. cereus, kinetic models are more relevant, to predict time to a given log increase in the population. Predictive models are often used at early stages in the design of a food, to identify means through which a product developer can control relevant target microorganisms and set a shelf life that delivers the required safety and quality characteristics. Validation of the predicted behaviour is a common subsequent step that is carried out, to provide additional evidence and confidence that the design is appropriate. When used as part of the product and process design, predictive models can greatly facilitate `in-silico' assessments of the effect that product reformulations and process modifications would have on the product shelf life, before planning laboratory or pilot-scale experiments. As such, predictive models offer a systematic, cost-effective approach for the development of microbiologically safe and stable food and beverage products. The main purpose of this chapter is to present an overview of the mathematical modelling approaches available for microbiological shelf life prediction of foods and beverages, and to describe the key considerations for development of predictive microbiological models, as well as the main limitations and practical considerations for the sound application and usage of models.

13.2 Classification of predictive models by microbial response Predictive models can be defined as a set of mathematical equations that describe the number of microorganisms present in laboratory media or in a food product, as a function of some environmental variables. Such variables (or controlling factors) as will be described later (on pp. 414±15) can be intrinsic to the food product or medium (e.g., pH or water activity of the food product formulation) or extrinsic (e.g., storage temperature of the food product). The vast majority of predictive models available in the literature quantify microbial populations or probabilities of presence of microorganisms. Little development has been made to model the behaviour of single organisms, partly due to the limited knowledge available at the cellular level.

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Predictive models are commonly classified as primary, secondary or tertiary models (Whiting, 1995). Primary models characterise the number of microorganisms in a population as a function of time under specific conditions. Secondary models establish a mathematical relationship between the primary model parameters and the environmental variables of interest (e.g., pH, product storage temperature, etc.). By successively applying primary and secondary modelling, it is possible to describe the complete evolution of a microbial population as a function of the environmental conditions. The implementation of both primary and secondary models in a user-friendly software application is referred to as `tertiary models'. Several notable tertiary models exist in the public domain (see Section 13.5). For the food industry, the availability of ready-to-use tools is particularly useful for assessing the potential risk associated with some identified microbiological hazards in food products and processes. For food developers, tertiary models are particularly attractive for optimising new products and processes. Predictive models can be developed in many ways, depending on the purpose serving the model development and the information available at the time of development. With regard to the latter point, another level of model classification is commonly described in the literature (Peleg, 2006). Depending on the current scientific knowledge about the system to be modelled and the quality and quantity of data available for that particular system, predictive models (primary, secondary and tertiary) are usually described as empirical or mechanistic. Empirical models describe the data in a purely statistical way, with no representation of the current scientific knowledge about the underlying biological phenomena occurring in the system. These models are intended to provide the most accurate fit to the data. They are therefore very good for predicting microbiological behaviour within the range of the observed data (i.e., interpolation region). Microbial mechanistic models, on the other hand, mathematically characterise some known microbiological phenomena. They theoretically provide an exact mathematical translation of a microbiological behaviour, as understood and described by the broader scientific community. In theory, mechanistic models have the major advantage of providing reliable predictions of microbiological behaviours under any environmental conditions within and outside the range of the observed data (i.e. extrapolation region). Currently, insufficient knowledge is available to implement purely mechanistic models for microbial growth or inactivation. Most models used are either purely empirical or semi-empirical, meaning that some microbiological knowledge is incorporated, to a certain extent, into the model. Another way of classifying predictive microbiological models is based on the nature of the different biological `end-points' (or microbial responses). Subjected to certain intrinsic and/or extrinsic conditions, observed microbial responses over time can be predicted and quantified by the use of growth models, inactivation or death models, survival models, growth/no-growth models or combined models. Growth models describe an increase in a population over time whereas inactivation models describe a decrease over time. Survival models also

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describe death over time, but in this case death occurs relatively slowly when no lethal treatment is applied deliberately to the product (e.g., ambient-stable acidpreserved products such as mayonnaise or salad dressings). Growth/no-growth interface models (also called growth boundary models) describe the probability of survival (or growth) of microorganisms in the situation when the environmental conditions can either way result in microbial growth or inactivation (Dang et al., 2010; McKellar and Delaquis, 2002; McMeekin et al., 2000; Ratkowsky and Ross, 1995). Combined models describe the changes of behaviour in a microbial population subjected to conditions that can vary from growth to inactivation (Ross et al., 2005; Whiting and Cygnarowic-Provost, 1992). These models require particular attention in order to avoid some discontinuities at the interface between growth, growth/no-growth and inactivation. If such models are attractive for describing the complete range of microbial responses, they represent, however, a major `investment' in terms of data requirements and modelling effort. Such investment may not be justifiable in practice for most food process models, which would usually focus on either microbial inactivation (for instance to ensure that pathogenic microorganisms are reduced by a certain amount (e.g. 6 logs) after a specific period of time) or growth (for instance to ensure that spoilage microorganisms are not able to grow to the extent of spoiling the food product before the end of shelf life). In the context of modelling the growth of spoilage microorganisms, if the population reaches the death phase (see Fig. 13.1), one might have no interest in quantifying the subsequent inactivation rate of the microbial population as the product would have already been spoiled.

Fig. 13.1 Schematic representation of a typical microbial growth curve.

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13.2.1 Growth models Growth models have been a major area of development in predictive microbiology over the past 25 years. Traditionally, these rely on generation of kinetic data that enable a description of the whole growth curve that includes lag time, exponential growth phase, stationary phase and death phase (see Fig. 13.1). In practice, most growth models are based on the assumption of a sigmoidal growth function; in other words, the death phase is ignored in practice. The simplest form of sigmoidal response has been described by Buchanan et al. (1997) with a three-phase linear model, representing the lag phase, the exponential growth phase and the stationary phase. Zwietering et al. (1990) reparameterised different forms of sigmoidal curves in order to relate the model parameters to biologically meaningful terms, namely the lag time, the maximum specific growth rate and the maximum cell density. In the context of predicting microbiological shelf life, kinetic growth models are the most relevant ones, and these will be described in more detail in Section 13.4.1. Some of the most commonly used primary growth models are the Baranyi model (Baranyi and Roberts, 1994), the logistic model (Dalgaard, 1995), the modified Gompertz model (Gibson et al., 1987) and the three-phase linear model (Buchanan et al., 1997). 13.2.2 Growth/no-growth or growth boundary models The use of kinetic growth models might be appropriate for spoilage microorganisms or pathogens for which some growth may be tolerated up to a certain level. The situation becomes different when dealing with foodborne pathogens with a very low infective dose (e.g., E. coli O157:H7), or with toxigenic organisms where even a small amount of growth is considered potentially hazardous (e.g., Clostridium botulinum). In that respect, the ability to predict whether a foodborne pathogen might grow or not becomes more relevant with regard to consumer safety. Similarly, the ability to determine the growth limits of spoilage microorganisms with a high spoilage potential under certain environmental conditions might be of relevance (e.g., Zygosaccharomyces bailii in fruit concentrates and juices). The latter is particularly useful when designing ambient-stable products with long shelf lives. Being able to predict the location of the boundary between growth and no growth means being able to determine, in a multi-factorial space, the combination of environmental conditions (such as temperature, water activity, pH, etc.) that will influence the probability of microbial growth. This underpins the concept of `hurdle technology' (Leistner, 2000) to design combinations of environmental factors that will inhibit growth, ensuring the stability and the safety of the foods without compromising their nutritional and sensorial qualities (see Section 13.4.2). Models that define the combinations of environmental factors that prevent growth are known as `growth/no-growth' or `growth boundary' models. To some extent, when designing food products, growth/no-growth models are

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preferred to kinetic growth models because any growth implies the possibility to cause food spoilage or illness. There is therefore an economical interest for food manufacturers to be able to design product recipes that would exclude the possibility of microbial growth without the need for challenge testing. Various authors have described and highlighted the importance of growth/no-growth models for designing safe and stable foods through `hurdle technology' (McMeekin et al., 2000; Ratkowsky and Ross, 1995). Ross and Dalgaard (2004) classify growth/no-growth models under three broad groups: deterministic approaches, logistic regression techniques and artificial neural network. Deterministic approaches to growth/no-growth interface modelling involve determining the set of environmental conditions that will predict a probability of growth of 50% as the boundary (Augustin and Carlier, 2000b; Le Marc et al., 2002; Membre et al., 2001). Another technique involves using combined models (describing growth and death) where both the growth rate and death rate are estimated at the same time. The set of conditions predicting a growth rate equal to the death rate constitute the growth/no-growth interface (Battey et al., 2001). Logistic regression is a common statistical technique (falling under the family of generalised linear models) that is used to model binary data. Data available under the form `growth' or `no-growth' are adequate for the use of logistic regression. By using the logistic link function, it is possible to estimate the probability of growth under specific environmental conditions and the growth/no-growth boundary can be specified at any level of confidence. For example, Dang et al. (2010) proposed the use of linear logistic regression to help develop guidelines for designing new shelf-stable foods without the need for chemical preservatives. The model used in the study describes the growth/nogrowth boundary of the food spoilage yeast Z. bailii at 30 ëC, given a range of pH, water activity and (total) acetic acid (Ac), based on the following model:   P ˆ b0 ‡ b1
aw ‡ b2
pH ‡ b3
Ac ‡ b4
a2w ‡ b5
pH2 ‡ logit…P† ˆ ln 1ÿP b6
Ac2 ‡ b7
aw
pH ‡ b8
aw
Ac ‡ b9
pH
Ac 13:1 where P is the probability of growth, and b1 ; . . . ; b9 represent the parameters to be fitted to the experimental data. As can be observed in Eq. 13.1, the logistic regression approach relates logit(P) to a polynomial expression of the explanatory variables. Artificial neural networks (ANNs) have been proposed as an alternative to logistic regression (see for instance FernaÂndez-Navarro et al., 2010). They are mainly algorithms that can be used to describe complex nonlinear relationships between a large set of covariates and responses variables. Despite the efforts of some authors to demonstrate the fitting performance of ANNs, they are still not as widely used as logistic regression models. Advantages and disadvantages of ANN are described in Ross and Dalgaard (2004).

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13.2.3 Inactivation and survival models Modelling inactivation is an important aspect of microbiological safety and stability by design, and it has received considerable attention in the field of food research. However, within the scope of this chapter, inactivation models are of little relevance with a view to modelling the microbiological shelf life of foods and beverages. A top level description is therefore given in this section, but no further details are covered throughout the chapter. Further information can be found in the literature (Peleg, 2006; Ross and Dalgaard, 2004). Kinetic inactivation models describe the decrease in microbial population over time, as is often observed after the application of a lethal process such as a heat treatment. When no lethal treatment is applied deliberately, but there is a death response under conditions where growth is prevented, the models describing this response are often called `survival' models. These are particularly useful when modelling the fate of microorganisms in products where the preservation system is based on non-thermal intervention processes, such as fermented meats, fermented dairy products (e.g., yoghurts and cheeses), dressings or mayonnaises and beverages (e.g., fruit juices). Likewise, survival models are useful when designing multiple-use food products where the shelf life can extend for many weeks after opening and it is critical that the same consideration for design is applied to `open' as well as `closed' shelf life. Unlike growth, where the shape of the microbial response is generally the same i.e. sigmoid, the kinetics of survival are not easily predicted. Different shapes of microbial inactivation/survival curves can be observed, and generally they can be described as having (a) a tailing pattern, (b) an increase in population followed by die-off (commonly observed when spore activation occurs), (c) a shoulder or lag prior to inactivation, or (d) a sigmoidal pattern with both a lag and a tail (see Fig. 13.2). Despite these observed shapes of inactivation/survival curves, most inactivation data available in the literature are assumed to be log-linear and are modelled as such. This assumption is likely to be dominated by mathematical considerations so that a simple log-linear form can be used for modelling purposes. At the moment, there is no clear consensus about a suitable choice of model for describing inactivation data. This may change with the proposal of new mechanistic models that would relate biological responses to inactivation patterns and incorporate the natural variability of the behaviour of microorganisms under lethal stress.

13.3 Development of predictive models for microbiological safety and stability Although there are different approaches to develop predictive models in food microbiology, this section discusses key aspects that should be considered when developing a model. As mentioned in the previous section, mechanistic models aim at describing the theoretical basis of the microbial response, but owing to the complexity of microbial physiology and our current level of

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Fig. 13.2 Common shapes of survivor curves: (a) initial rapid decrease with a subsequent tail, (b) initial increase in numbers followed by a phase of rapid decrease (observed typically during heat inactivation studies of spore-forming bacteria), (c) initial shoulder (or lag) followed by a phase of rapid decrease, (d) sigmoidal curve.

understanding, these types of models are rare. Consequently, most predictive microbiological models are, generally speaking, empirical. By `empirical' we mean that the way in which the microbial behaviour or fate is predicted is based on observing the effects of various factors on microorganisms in systems (either laboratory media or foods), usually under well-controlled conditions, and then fitting these data with mathematical functions (models). In most cases, these models have been formulated in such a way that the fitted parameters have biological relevance (e.g., specific growth rate or lag phase duration). In that context, although they are observational models, they are not, strictly speaking, `black box' models as is the case with purely statistical models (e.g., polynomial models). In some instances, though, statistical models offer the most suitable alternative to describe the dataset used for their generation, and therefore, are still often used; however, their parameters have no biological significance. One of the fundamental premises on which predictive modelling in food microbiology is based is that the microbial responses to environmental conditions are reproducible. Therefore, if those environmental conditions can be properly characterised in terms of the factors that control the main physiological events (i.e., growth, survival and inactivation), then it is possible to predict the microbial responses on the basis of past observations when similar environmental conditions can be properly monitored. To that end, having high-quality data describing the full range of responses to the

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environmental conditions of interest is a fundamental step when building a predictive model. In order to gather sufficient information to build a good database for development of a model, the main options are either to generate new data via experimentation or to use data reported in the literature or in public databases. The latter option has become in recent years more accessible to non-academic users with the creation of web-based databases such as ComBase (http:// www.combase.cc) (Baranyi and Tamplin, 2004) or Sym'Previus (http:// www.symprevius.net) (Leporq et al., 2005), which will be discussed later in the chapter (see Section 13.5). When using data from literature to develop a predictive model, the main disadvantage is that, in most cases, the experiments reported are not designed primarily to produce a predictive model or some details of the experiments are not always described adequately. Nonetheless, good examples where only data from literature and/or public databases were used for model development have been reported (Augustin et al., 2005; Le Marc et al., 2005; Ratkowsky and Ross, 1995), though due to the availability of data in the public domain, these are typically limited to pathogenic organisms. In spite of some of the possible limitations of such an approach, oftentimes a thorough investigation of the data available in the literature or in public databases can provide useful information about certain patterns of microbial behaviour under the environmental conditions of interest. That information may in turn indicate areas where gaps exist, thereby facilitating the design of experiments to generate the data required for model development. 13.3.1 Experimental considerations Experimental design Due to the empirical nature of predictive models in food microbiology, they cannot be used reliably to make predictions beyond the area defined by the conditions used to generate the model (see page 422 for a more in-depth discussion on this topic). Therefore, the intended range of model usage is a key consideration for the design of experiments to generate the data required for model development. When a model is developed without much prior thought to the scope of the subsequent applications, this may result in inappropriate choice of key controlling factors and limitation of its use. A better strategy is to decide on the food or range of foods to be targeted and ensure that the controlling factors are selected to reflect this. The many factors that can affect the fate of microorganisms in food can be grouped into three categories: · Intrinsic factors: characteristics of the food itself (e.g., pH, water activity (aw), concentration of preservatives). · Extrinsic factors: characteristics of the environment in which the food is stored (e.g., temperature, gaseous atmosphere, humidity). · Implicit factors: the characteristics of the microorganism itself and how it behaves in the presence of combinations of the intrinsic and extrinsic factors (e.g., specific growth rate of the microorganisms).

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In many cases, the fate of microorganisms in foods is determined by a small number of factors, such as pH, aw and temperature, and it has therefore been relatively straightforward to characterise responses in laboratory media and to develop models that predict their fate in foods, provided that the food environment can be adequately simulated. An experimental system is required in which these factors can be altered easily. In most cases microbiological media are used because they are of consistent composition and can be easily and reproducibly modified to the required conditions. In some cases there may be different methods of applying factors, e.g. the choice of acidulant and humectant for adjusting pH and aw, respectively. If the model is to be applied across a wide range of foods, then the use of less inhibitory chemicals, e.g. hydrochloric acid, are more likely to avoid fail-hazardous predictions (where slower microbial growth is predicted than actually happens). However, if the model is intended for specific foods then the choice of factors may need to be more focused, e.g. specific organic acid in order to include the effects related to the undissociated molecule. This approach allows inclusion of additional inhibitory factors that may be the difference between a safe or stable formulation and a potentially hazardous or unstable formulation. When considering aw as a controlling factor, it must be noted that different microbial responses, at a given aw, can be observed when different humectants are used to control the aw value (Mattick et al., 2001; Stewart et al., 2002). This specific solute effect not only can affect the minimum tolerated aw (i.e., the minimum aw level allowing growth), but also the growth rate. This may be particularly difficult to deal with when it comes to designing an experiment with a view to developing a predictive model, because for some organisms, a particular humectant may be more inhibitory than others on an aw basis but the opposite effect is observed for another organism. For example, glycerol is more inhibitory than NaCl for some Gram-positive cocci such as Staphylococcus aureus, with minimum aw for growth reported as 0.86 with NaCl as humectant and 0.89 with glycerol (Marshall et al., 1971), whereas for Listeria monocytogenes the opposite effect is observed, with minimum aw for growth given as 0.92 with NaCl as humectant and 0.90 with glycerol (Tapia de Daza et al., 1991). Simplifying the experiments by choosing only the most relevant three or four factors driving the microbial response in laboratory media is common practice, and this is typically done for cost reasons. However, growth models developed using those simplified systems tend to give conservative predictions (i.e., failsafe predictions), and this results inevitably in restrictive estimates of product shelf life. To that end, models that are developed in a matrix that closely simulates the food product of interest provide more accurate predictions, but these usually require more complex experimental conditions and have a restricted domain of validity for their application. The choice of strain(s), size of inoculum and culturing conditions of the microorganism used will all affect the responses measured and subsequent predictions. Different strains have different phenotypic responses and so the inclusion of mixtures of strains (i.e., cocktails) or some form of strain selection or screening needs to be carried out. Cocktails are more likely to contain a range

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of physiological responses that may not be fully characterised, but may be more representative the diversity found in naturally occurring microbial populations. The strains used in the cocktail should be, as much as reasonably possible, representative of the target group of organisms likely to be found in the product for which the model is intended to be used. For shelf life studies, a commonly used approach is to select the fastest growing strain in the spoilage domain, which will simulate a worst-case scenario. Likewise, strains that have been isolated from spoiled products representative of those under investigation are often used. For example, Neumeyer et al. (1997) screened nine strains of psychrotrophic pseudomonads of dairy origin, and selected the fastest growing strain (Pseudomonas putida 1442) as the main isolate for model development; however, the authors also modelled the slowest of the strains (P. fluorescens 1412) to provide an indication of strain-to-strain variability of growth rates. The size of the inoculum has to ensure that the expected microbial response can be measured rather than necessarily actually reflecting the numbers commonly present. For instance, in generating growth curves for developing a growth model, an initial inoculum of 2±3 log10 cfu/ml or g is appropriate because it allows enumeration during the lag phase whilst reducing the chance of increasing unrealistically the probability of growth which could occur at high initial levels. In contrast, if a survival model is of interest (i.e., a non-thermal inactivation model under mild conditions), for example in the case of a pathogen of concern in a product designed to be ambient-stable, then an appropriate inoculum can be around 4±6 log10 cfu/ml or g to allow either growth or death responses to occur (as the experimental conditions of interest may fall very near the growth/no-growth boundary). The pre-history (growth or storage conditions including temperature and growth medium) can affect the microorganism's response to the controlling factors and it should be carefully selected to reflect as far as possible the likely conditions of naturally contaminating microorganisms. The statistical design to be used is crucial for the subsequent stages in the process of developing a predictive microbiological model. In recent years, various sources of detailed information about statistical design of experiments for microbiological modelling have become available (Rasch, 2004; van Boekel and Zwietering, 2007). We limit our discussion to basic principles that may be important to be considered in the context of growth and growth boundary models, which are of special interest for microbiological shelf life prediction. In growth models, full factorial designs are often not necessary because the region of interest may be in the area where the response that is being measured is more variable (e.g., near a boundary of growth/no-growth), and some treatments in the design will involve combinations of factors that do not support growth. Therefore, fractional factorial designs are often used, particularly Box±Behnken designs as these not only allow a reduction in the number of experimental units (compared to a complete factorial design) but also the design points fall on the edges of the cuboidal region rather than on the corners (i.e., where combinations of conditions are likely to result in a no-growth response) (see Fig. 13.3). Battey and Schaffner (2001) reported the development of a growth model for the

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Fig. 13.3 Example of a Box±Behnken design for the case of three factors (e.g., temperature, pH and water activity). Several replications of the design centre are typically included.

spoilage bacteria Gluconobacter oxydans and Acinetobacter calcoaceticus in cold-filled ready-to-drink beverages, using a Box±Behnken design for the generation of growth curves. Their design consisted of 42 experimental conditions (in duplicate) to cover five factors and three levels (pH 2.8, 3.3, 3.8; titratable acidity 0.2%, 0.4%, 0.6%; sugar content 8, 12, 16 ëBrix; sodium benzoate 100, 225, 350 ppm; and, potassium sorbate 100, 225, 350 ppm), resulting in a more manageable study than a full factorial design (i.e. 53 experimental conditions), yet providing sufficient information for model development. In growth/no-growth models, the main interest when designing an experiment is the detection of growth, without the need to quantify it. For this type of model, it is crucial that the experimental design matrix includes many replicates with about half of the conditions resulting in observable growth on one side of the interface, and the other half resulting in non-detectable growth on the other side of the interface. Therefore, automated methods are often used primarily in screening experiments to elucidate the choice of experimental conditions that are `marginal' (i.e., very near the growth/no-growth interface), and ideally, these could have complete factorial designs which can be handled relatively easily in the automated system. For generating the dataset that will ultimately be used for model development, central composite designs may be more manageable, but ideally they should be centred on the `marginal' growth conditions where the greatest variability is expected. Data generation The most labour-intensive stage is the generation of data (e.g., growth or survival) of the organism in the model system. Quantification of microorganisms

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at selected time points is usually by standard colony count methods, but optical density and conductance measurement have also been used. When the target microorganism is in pure culture, methodology for enumeration is usually straightforward, but for survival models provision to enumerate sub-lethally injured cells may need to be made. Although total viable count (TVC) methods are expensive and labour intensive, they have the advantage of best describing growth kinetics of a bacterial population. The accuracy of the growth parameter estimates depends on the number of counts made per growth curve and also the quality (uncertainty on the experimental data points) of the measurement (Poschet et al., 2004). For instance, Walker and Jones (1993) suggested a minimum of 10 points per growth curve. This is not always achievable in practice due to time and/or budget constraints. It is important to note that having a large amount of observations can be of little use if these are wrongly positioned in time. For example, the accuracy of the lag time estimate will be optimal if one can sample sufficient data points during the transition zone between the lag phase and exponential phase. Automated optical density (OD) methods have the advantage of being rapid, inexpensive and, generally speaking, allow for quicker data generation with less need for human resources. However, they present the main disadvantage of having a limited range of validity. This is because the experimental detection limit usually corresponds to a bacterial concentration in the range of 106±107 bacteria/ml (Begot et al., 1996). The growth rate obtained using OD will typically represent the late-exponential growth phase which will be less than the maximum specific growth rate, leading to underestimation of the `true' value. For this reason, OD measurements are often used in combination with time-to-detection (TTD) measurements (Cuppers and Smelt, 1993). Using serial dilutions (i.e. changing the inoculum size), TTD measurements can be used to obtain values for both the growth rate and the lag time (Baranyi and Pin, 1999; Cuppers and Smelt, 1993; Wu et al., 2000). This technique has been applied by several researchers in recent years, and comparisons between TVC and automated OD methods have shown that both types of techniques can be used reliably depending on the objectives of the study (Augustin et al., 2005; Biesta-Peters et al., 2010; Metris et al., 2006). For instance, automated OD measurements can be used to determine growth parameters for certain factors such as pH or preservative concentration, where a large number of combinations can be assessed quickly. However, for some specific growth conditions, TVC methods will remain necessary, such in the case of modified atmospheres which cannot easily be achieved in OD measurements, or for certain temperatures where evaporation or condensation of liquid media may affect the reliability of the method. 13.3.2 Data analysis and modelling The next stage involves mathematical analysis of the data to produce a model and determine the quality of the data and the goodness of fit of the data to the model. There are a number of different modelling techniques for growth,

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probability of growth, survival and inactivation, and these are now well established and thoroughly described in dedicated books and review papers (Brul et al., 2007; McKellar and Lu, 2004; McMeekin et al., 1993; Whiting, 1995). These techniques essentially comprise the development of primary and secondary models (see Section 13.2) from a database (either built from experiments specifically designed to build the model or from literature or independent sources), and turning those data into knowledge by developing user-friendly software (or tertiary models) through which application is made possible (i.e. they enable users to `interrogate' primary and secondary level models in order to obtain predictions). ComBase (http://www.combase.cc) and Sym'Previus (http:// www.symprevius.net) are examples of current systems that combine that database-modelling-software functionality, and these will be described later (see Section 13.5). Initial inspection of the raw data using plots or tabulations is often used to check for quality and consistency. The fitting process typically involves linear or nonlinear regression techniques where the use of statistical software is required. For kinetic models (primary level), some tools are available free of charge in the public domain for both growth and inactivation models. For example, GInaFiT (Geeraerd et al., 2006) is a freeware tool to fit inactivation data to different mathematical models that describe all the known survivor curve shapes shown for vegetative bacterial cells. DMFit is another example of a freeware tool developed by the Institute of Food Research in the UK, and available as part of the ComBase Modelling Toolbox (http://www.combase.cc/toolbox.html). DMFit allows the user to fit bacterial (growth or survival) curves (i.e., logarithmic cell counts vs time) where a linear phase is preceded and followed by a stationary phase to different primary models. In growth models, traditionally the fitting process is done in two steps, i.e. fitting kinetic data to a primary model first, and then fitting the parameters of interest (e.g., growth rate) in terms of the independent variables (e.g., temperature, pH, etc.) via a secondary model. However, one-step global regression procedures are now used more frequently, where the response can be fitted directly as function of time and the independent variables in one step. This approach offers the flexibility of selecting parameters that can be fitted in common for all the data (according to the assumptions or constraints of each model), as well as selecting parameters that can be fitted individually for each curve. Although this approach is more demanding in terms of both software and expertise, it offers the advantage of preventing accumulation of fitting errors (Valdramidis et al., 2005), and it is particularly useful when the dataset contains incomplete growth or survival curves. Currently, there are freeware user-friendly tools that facilitate this onestep regression process, and one example of such a tool is OptiPa (Hertog et al., 2007, available at http://perswww.kuleuven.be/~u0040603/optipa). An important consideration when starting the development of a predictive model relates to the stochastic assumption used when fitting a mathematical equation to experimental data, i.e., to obtain the best fit of the model to the data, the error in the estimate of the selected response must be independent of the

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value of the measured response. In microbiology, due to the exponential nature of growth, the growth rates over the range of conditions tested may span several orders of magnitude (from the slowest to the fastest growth rate), and the measurement error tends to be a constant proportion of the magnitude of the growth rate (Ross, 1999). As such, data for longer generation times will tend to have a greater influence on the fitting process than data for shorter generation times, because the differences between measured and expected values are usually larger. Therefore, a suitable transformation should be used to normalise this variance. This is particularly relevant when comparing the performance of different models. Two transformations are commonly used: logarithmic and square root of rate. Whichever modelling technique is used, the model should describe the data as accurately as possible without being overly complicated. Models should use the minimum number of parameters which describe the response adequately (i.e., be parsimonious), where an adequate fit is defined by certain criteria. 13.3.3 Model validation Mathematical testing and examination for biological sense Mathematical testing is the process of quantifying how well the model describes the data and one approach has been described by McClure et al. (1994). There are a number of sources of variability that may be the inherent variability of the microorganism, systematic errors due to analytical laboratory methods or bias due to inappropriate modelling techniques not adequately describing the data. There is a degree of acceptance or rejection at this stage and any requirement for additional or repeated microbiological data, or the use of a more appropriate modelling technique, can be highlighted. Visual comparison of predicted values against observations under the same conditions is always a good starting point in assessing the performance of the model. However, more systematic measures of goodness of fit are necessary. A commonly used measure for both linear and nonlinear regression models is the root mean square error (RMSE, Eq. 13.2), which measures the `average' discrepancy between observed data (transformed if necessary) and their predicted values (Ratkowsky, 2004). The magnitude of the RMSE is useful in assessing whether the model fits the data well; the smaller its value, the better the fit of the model to the experimental data. s P …predicted ÿ observed†2 13:2 RMSE ˆ df where df is degrees of freedom (i.e., the number of observations minus the number of parameters estimated). In order to assess the performance of a model in a more systematic way, Ross (1996) introduced two dimensionless indices: the bias and the accuracy factors (Eqs 13.3 and 13.4, respectively), later modified and generalised by Baranyi et al. (1999) to quantify the confidence in the model predictions:

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Modelling microbiological shelf life of foods and beverages 421 P bias factor ˆ 10… log…GTpredicted =GTobserved †=n† 13:3 P accuracy factor ˆ 10… jlog…GTpredicted =GTobserved †j=n†

13:4

where GTpredicted is the predicted generation time and GTobserved is the observed generation time, and n is the number of observations. The bias factor indicates systematic over- or under-prediction. For example, a bias factor of 1.15 indicates that the predicted generation times, on average, were 15% longer than the observed values, indicating that the model is `faildangerous'. It also indicates that the predictions exceed the observations by 15% on average. Equation 13.3 can equally be used for the maximum specific growth rate, and in that case a bias factor greater than 1 indicates a `fail-safe' model. The accuracy factor provides a measure of the average difference between the observed and predicted values. The larger the value of the accuracy factor, the less accurate the prediction. An accuracy factor of 1.1 would indicate that the observed and predicted values differ by 10% on average, without indicating if the discrepancy was an over- or under-prediction. Ross (1999) proposed general criteria defining the acceptability of a validated model on the basis of the bias factor, as follows: · a bias factor of 0.9±1.05 can be considered good · a bias factor of 0.7±0.9 or 1.06±1.15 can be considered acceptable · a bias factor < 0.7 or > 1.15 can be considered unacceptable. The criteria above are consistent with recommendations given by Dalgaard (2000) for spoilage models in seafood, which considered that bias factor values between 0.75 and 1.25 can be used as a criterion for successful model validation. The criteria proposed by Ross (1999) have been used by various authors in validating their models (see, for instance, Mejlholm et al., 2010). It is also important that the model predictions make biological sense. This is often done by plotting predictions in three dimensions via surface plots or bar graphs of the response variable of interest (e.g., growth rate) as function of two of the independent variables included in the model. Several such plots can be created for different conditions, and it is simply recommended to examine if the predictions from the model behave as expected on the basis of microbiological experience. This may readily help in understanding unexpected model predictions in particular circumstances where the presence of a preservative at a certain level may hinder the expected effect of another one (i.e., opposite to the `hurdle' effect). One such effect, for example, has been reported for E. coli and Salmonella in acid-preserved foods containing a combination of NaCl and acetic acid (a commonly used hurdle strategy) (Chapman and Ross, 2009). In that study, the authors reported that NaCl at intermediate concentrations in an aqueous solution containing acetic acid at lethal acidity levels has a protective effect on both pathogens, delaying the `lag' time prior to inactivation.

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Domain of validity The domain of validity of a predictive model is defined by the minimum convex polyhedron (MCP) of the experimental design (Baranyi et al., 1996), which can be understood as the minimum space enclosed by the actual combinations of conditions used to generate the model. In other words, the MCP defines the interpolation region of the combinations tested. Predictions outside the MCP (i.e., extrapolation region) may not be reliable (see Fig. 13.4). When models are used outside the interpolation region, this should be made explicit and considered in the interpretation of the outcome. In the case of growth models, it is often the case that conditions resulting in no growth are omitted from the model fitting, but these may still be of interest to the food industry as they may be very close to the growth/no-growth interface. In that case, comparisons made with literature data outside the model interpolation region are useful to highlight areas where model data could be added to the original dataset in order to make the model more applicable to a wider range of products. Le Marc et al. (2005) proposed the utilisation of the MCP concept to define a `growth' region, which could contain data for which growth has been reported in the literature or recorded in a public database such as ComBase. This `growth' region may include conditions that could be used for fitting the predictive growth model, plus additional growth data (from independent sources) not used in the model development. The advantage of this approach is that this new `growth' MCP region may highlight new combinations of factors where new data could be generated for model refinement (i.e., a growth region where previously no data was available from the experimental design). The region outside the `growth' MCP can be considered a `no-growth' region. However,

Fig. 13.4 Schematic representation of the model interpolation region (minimum convex polyhedron ± MCP) for the simple case with two variables (temperature and pH).

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Fig. 13.5 Schematic representation in two dimensions of the space of the environmental variables as divided into the `Model' (M), `Growth' (G), `Uncertainty' (U) and `No Growth' (NG) regions (after Le Marc et al., 2005).

this region can be further divided into an `uncertainty' region and a `no-growth' region, where there is certainty that the conditions will result in no growth based on microbiological knowledge and experience (see Fig. 13.5). Product validation Product validation involves the comparison of predictions from a model with growth, survival or death data of the relevant organism in food. The most rapid and inexpensive way of acquiring these data is the use of scientific publications, although the amount of data can be limited and is often incomplete with no measurement of some of the necessary physicochemical factors such as pH, sodium chloride concentration or aw. However, for some pathogenic microorganisms such as L. monocytogenes, there is nowadays a considerable amount of data available in the public domain (from the literature or public databases) in different food matrices. This has recently allowed a joint international effort to validate various proposed growth models for this organism (Mejlholm et al., 2010). Figure 13.6 shows an example of model validation using literature data. The figure compares the predicted growth/no-growth interface from a model developed in the authors' laboratory for L. monocytogenes as a function of pH, aw and preservative concentration against data reported by Tienungoon et al. (2000). The problems of incomplete or lack of data from the literature to validate a predictive model can be overcome by the use of challenge tests specifically designed for the purpose of product validation. In this way, the data are often more accurate, reliable and complete. Specific challenge tests can be time consuming and are relatively expensive, so they are often used to supplement

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Fig. 13.6 Effects of pH, aW and lactic acid (50 mM) on the growth boundary of Listeria monocytogenes at 25 ëC. The solid line represents predicted values of a model developed in our laboratory; dark grey and light grey points are reported growth and no-growth values, respectively (data from Tienungoon et al., 2000).

published data. Obtaining quantitative microbial growth or survival data can be problematic if the target organism or group of organisms is outnumbered by the natural food microflora. This may require the use of selective agars, which in themselves may not completely prevent overgrowth by competitor organisms, but may lead to an underestimate of any injured cells that are present. One way of eliminating the problem of the natural flora in the food is simply by purchasing sterile or commercially sterile foods (Walls and Scott, 1997), or using a heat, filtration or irradiation process. While this approach enables nonselective agars to be used, it can be criticised for not reflecting the ecology of most foods. The use of antibiotic-resistant strains of the target organism and the incorporation of the antibiotics in non-selective or minimally selective agar has enabled specific enumeration in the presence of outnumbering background flora (Blackburn and Davies, 1994). Ideally, the validation should include the foods in which the organism is considered a hazard or the cause of spoilage and the physicochemical properties of the foods and storage/heating temperatures should, as far as possible, cover the range of the controlling factors of the model. Physicochemical analysis of the food and monitoring of the storage conditions are required and as a minimum, these must include the controlling factors of the model (e.g., temperature, pH, aqueous sodium chloride, aw). Measurement of other factors that are not in the model and that may affect growth/survival (e.g., preservatives) can be useful to help explain any deviations between predictions and challenge test data. There are a number of reasons why significant deviation between predictions and observed data may be seen. Published data are usually not designed for validation purposes and are, therefore, often incomplete. There can be considerable variation between species and strains. There may be growth-inhibitory factors in the food that are not accounted for in the model, e.g. the presence of an organic acid or different humectant. This tends to lead to fail-safe predictions for

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growth models. The history of the inoculum can affect the subsequent lag phase or survivability of the population. The natural food microflora can affect the physicochemical properties of the food when they reach spoilage levels. The inappropriate use of physicochemical data (e.g., the use of an aqueous salt measurement for a food in which aw is affected by other humectants) or the use of the model outside its domain of validity can account for some of the differences between predictions and experimental data. An understanding of all these factors greatly enhances the interpretation and application of predictions. In the past, there has been considerable scepticism towards the application of predictions from models developed in laboratory media to foods. Product validation has gone some way to redress the balance and demonstrate the value of predictive models. More specifically it determines the applicability of a model for use with different foods and can highlight foods or conditions where care is needed in applying predictions. In this way the data can be used as a means of accepting, rejecting or modifying the model. Ironically, it is often when conducting product validation that any limitations of a model, in terms of the choice of controlling factors and their ranges, are realised. In fact, an initial, limited product validation study is useful as an integral part of experimental design. 13.3.4 Limitations of using models Models can obviate the need to generate results in all conditions of interest, but should be interpreted with care and by those with a certain level of microbiological knowledge. Models are most often not identical to reality; they are a simplified representation of reality so that their outcomes have to be interpreted with a good understanding of the window of conditions they were generated for. Model predictions should only be used as a guide to the response of an organism under a particular set of conditions. One reason for this is that the strain of a contaminant and the conditions in the food are unlikely to be the same as those used to generate the model. Some models have been built using single strains, whereas others use cocktails containing several strains of an organism. When a cocktail has been used, the response will be determined by the fastest growing or the longest surviving strain under the particular conditions tested. The experimental methods and conditions used to generate the data will also affect the model (e.g., pre-treatment of strains, type of recovery media, plus numerous other experimental variables). Growth models, which have been generated from data in liquid microbiological media, oftentimes give predictions on the side of safety, as the media are normally designed to give optimum growth of the microorganisms, whilst growth may be slower in some foods. Therefore, the user may want to validate the model predictions in their specific food of interest (i.e., use the models to define parameters for a challenge test), as discussed on pages 420±5. Even if the models have been generated from experiments in a food, the user should still validate these, as it is unlikely that the food used in the model will be identical to

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the food of interest. Completeness errors are a common source of disagreement between model predictions and observed values in actual food matrices, i.e., there may be factors in some foods which could have a big effect on the fate of the microorganism of interest but which may not have been considered in the generation of the model. Other limitations are related to the design and structure of the model itself. For example, over-parameterised models, where the principle of parsimony has not been observed, provide good descriptions of the data in the interpolation region (i.e., acceptable fit), but can result in highly erratic predictions near the limits of the interpolation region or for conditions not originally tested. Finally, a model is only as good as the data used to build it, so the fit of the data to the model is important, and it may be better in one region of the model than another (or there may have been more data generated in one region, e.g. at a specific temperature). When using growth models, care should be taken when predicting at the boundaries of the model, as predictions are not always so good at the extremes of parameters. However, in these regions, the growth model predictions are generally fail-safe. Where there is more than one model for an organism, the user should choose the model and the parameters which most closely reflect the food of interest, but should be aware of the limitations described above. Despite the limitations described, several advantages can be gained from using model predictions. For example, to start a challenge test from scratch often involves setting up numerous conditions, which can be very lengthy and costly. Use of models can narrow down the range of conditions which need to be investigated in a challenge study.

13.4 Modelling approaches, applications and opportunities for shelf life prediction This section focuses on those predictive models and approaches that are of particular interest and applicability in the prediction of microbiological shelf life. It discusses growth models and how they can be used to predict shelf life of foods and beverages, growth boundary models for quantification of hurdle effects, and finally, relative rate of spoilage (RRS) models. 13.4.1 Modelling microbial growth The food industry is increasingly asked to provide fresher or more natural foods and beverages to the consumer. The general demand for authentic foods with less or no preservatives implies milder treatments without compromising the microbiological stability and safety of food products during their shelf life. The design of such foods requires a thorough characterisation of the growth kinetics of relevant microorganisms in order to establish a shelf life that is suitable for both the food company and the consumer. For example, toxigenic microorganisms such as S. aureus may be present as long as they are not able to grow

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to a level where they produce toxin. Spoilage microorganisms such as yeasts and lactic acid bacteria can be tolerated as long as no visible signs of spoilage are observed during the entire shelf life. Being able to model accurately the growth rate and the lag time of microorganisms present in the food is therefore fundamental in determining a shelf life. Primary growth models In 1825, a new mathematical function was proposed by Gompertz to describe the human mortality rate as a function of age. Known as the Gompertz function, this equation was used by insurance companies to calculate the cost of life. A modified version of this equation was first used in predictive microbiology by Gibson et al. (1987), and is given by: log10 N …t† ˆ A ‡ C
expfÿexp‰ÿB…t ÿ M†Šg

13:5

where N …t† is the number of bacteria at time t, A is the asymptotic log-count as t decreases to zero, C is the asymptotic amount of growth that occurs as t increases indefinitely, and B is the relative growth rate at M, where M is the time at which the absolute growth rate is a maximum. From the modified Gompertz model presented in Eq. 13.5, other quantities of interest are derived as follows: BC 13:6 growth rate (log10 count/h) ˆ exp…1† lag time (h) ˆ M ÿ

1 B

13:7

In the early years of predictive microbiology, some authors considered this model to be one of the best sigmoidal models for growth curves (McMeekin et al., 1993; Zwietering et al., 1991). However, it presents the main drawback of overestimating the specific growth rate and the lag time due to an inflection curve inherent to the Gompertz curve (Baranyi et al., 1993; McKellar and Knight, 2000; Membre et al., 1999; Whiting and Cygnarowic-Provost, 1992). Some attempts have been made to propose more biologically-based growth models. The Baranyi model (Baranyi and Roberts, 1994) is one of the most popular population growth models that was developed to describe the process of adjustment of microbial cells by hypothetical adjustment functions (Eqs 13.8 and 13.9).   dN Q…t† N …t†
N …t† 13:8 ˆ
max
1 ÿ dt 1 ‡ Q…t† Nmax dQ ˆ max Q…t† dt

13:9

where N …t† is the cell density at time t (cfu/ml), max the maximum specific growth rate (hÿ1), Nmax the maximum cell density (cfu/ml) and Q…t† is a dimensionless quantity related to the physiological state of the cells at time t (Q(0) is the initial physiological state of the cells at inoculation).

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Q…t† ) is a 1 ‡ Q…t† monotonic increasing function taking values from 0 to 1. This function enables the transition from lag phase to exponential phase by gradually diminishing the effect of the previous environment embedded in Q…t†. Similarly, the adjustment   N …t† enables the transition from the exponential to the function b…t† ˆ 1 ÿ Nmax stationary phase, inhibiting growth when N …t† approaches Nmax. According to the Baranyi model, the lag time can be calculated as follows:   1 1 ÿln…0 † ˆ
ln 1 ‡ 13:10 ˆ max Q…0† max The first term on right-hand side of Eq. 13.8 (i.e., a…t† ˆ

The definition of lag time presented in Eq. 13.10 is related to the concept of relative lag time (RLT), which assumes that the product of lag time () and the maximum specific growth rate (max) is constant. This product is a measure of the amount of work that a bacterial cell has to do before it can initiate growth. As such, the dependence of the lag time on the environmental conditions can be derived from the dependence of the maximum specific growth rate on the environmental conditions as long as the pre-culturing conditions remain unchanged. The parameter 0 has the role of an initial value, quantifying the history of the cells. Its value ranges from 0 to 1. When 0 ! 0, there is no growth and the lag time is infinite. Conversely, when 0 ! 1, there is no lag phase and growth will start immediately (see Fig 13.7). The assumption of the product of max
 ˆ constant, although practical, may not always be valid under all conditions and should therefore be used with care (Delignette-Muller, 1998). The popularity of the Baranyi model resides in its capacity to provide good fits. It is also applicable under dynamic environmental conditions and from a biological point of view, most of the model parameters are interpretable (Lopez et al., 2004; Pin et al., 2002; Van Impe et al., 2005).

Fig. 13.7 Effect of the `initial physiological state' parameter (0 ) on duration of lag phase according to the Baranyi model.

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Fig. 13.8

429

Graphical representation of the Buchanan three-phase linear model.

A simpler three-phase linear model was proposed by Buchanan et al. (1997), which can be expressed by the following system of equations: 8 t > < log10 N0 13:11 log10 N ˆ log10 N0 ‡ …t ÿ †  < t < tmax > : log10 Nmax t  tmax where N0 is the initial population density (cfu/ml), Nmax is the maximum population density supported by the environment (cfu/ml), t the elapsed time,  the time when the lag phase ends (h), tmax the time when the maximum population density is reached (h),  the specific growth rate (log10 cfu mlÿ1 hÿ1) (see Fig. 13.8). When fitting the three-phase linear model to experimental data, the parameters to estimate are , tmax, N0 and Nmax. The (maximum) specific growth rate is then calculated as: Nmax ÿ N0 13:12 ˆ tmax ÿ  This model embeds stochastic aspects with respect to the lag time, i.e. it assumes that each individual cell has a lag time i that depends on its adaptation time i and its generation time tmi , so that i ˆ i ‡ tmi . If the variances of i and tmi are large, the transition from lag phase to exponential phase for the whole population will be smooth, while for very small variances, the transition will be abrupt (Buchanan et al., 1997). Another type of primary growth model commonly used is the four-parameter Logistic model, which is given by Eq. 13.13:   Nmax ÿ Nmin 13:13 log10 N …t† ˆ log10 Nmin ‡ 1 ‡ exp…ÿmax …t ÿ ti ††

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where Nmin is the minimum asymptotic cell concentration (cfu/ml), ti is the time (h) when half the maximum cell concentration is reached, and the other parameters have been already explained. From the four-parameter Logistic model, the population lag time has been derived as follows (Dalgaard, 1995):   1 Nmax ‡ Nmax
exp…max
ti † ÿ1 13:14
ln  ˆ ti ÿ max Nmax ‡ Nmin
exp…max
ti † A three-parameter version of the Logistic model, which does not consider the lag phase (i.e., the parameter Nmin is not included), has been used by Dalgaard (1995) to calculate the end of shelf life in seafood products, as the time the specific spoilage organisms (SSO) requires for multiplication from N(0) to a minimal spoilage level (MSL), as given by Eq. 13.15: shelf life (days) ˆ

‰log10 (MSL) ÿ log10 …N …0††Š
ln…10† max
24

13:15

Obviously, application of Eq. 13.15 requires the determination of the MSL. This can be achieved by controlled storage trials, where the concentration of the SSO is monitored over time, and then correlated to the time where products are spoiled as determined by sensory rejection. For example, Dalgaard et al. (1997) determined that cod fillets stored in modified atmosphere conditions at 0 ëC, on average, spoiled four generation times (tg) after the SSO, Photobacterium phosphoreum, reached the inflection point (ti) of the three-parameter Logistic growth curve. A spoilage criterion was then defined as the storage time equal to ti ‡ 4tg as shown in Eq. 13.16:   Nmax ÿ1 ‰4
ln…2†Š ‡ ln N …0† spoilage criterion ˆ 13:16 max The correlation between a cell concentration and the point of sensory rejection is not always straightforward as variable levels of cells may be measured when spoilage occurs. This makes it difficult to predict the end of shelf life accurately. For particular product types, it makes more sense to predict the end of shelf life as the time required for the SSO to produce a certain level of a metabolite that will be responsible for sensory rejection. For example, Dalgaard (1995) reported that in packed cod, a concentration of approximately 30 mg of N-trymethylamine (N-TMA) per 100 g is typically found at the time of sensory rejection. Therefore, the end of shelf life was predicted as the time required for P. phosphoreum and Shewanella putrefaciens (the SSOs identified for spoilage) to produce 30 mg of N-TMA, as given by Eq. 13.17: shelf life (days) ˆ     30 mg N ÿ TMA/100 g ‡ N …0† ÿ log10 … N …0††
ln…10† log10 YTMA=cfu
100 13:17 max
24

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Equation 13.17 combines the exponential growth model (see Eq. 13.15) for the SSO with the yield factor for TMA production (YTMA/cfu) which needs to be measured experimentally with appropriate analytical techniques. Individual cell lag time While the growth rate has been extensively studied in the literature, the study of the lag time is rather recent in comparison. This observation seems quite surprising as the characterisation of the lag phase (in combination with the growth rate) will determine whether growth of spoilage or pathogenic microorganisms can occur before the end of a target shelf life. It is therefore necessary to better understand the lag phase and the factors most likely to affect it. The development of such knowledge is only recent, which is the reason why the study of the lag time has received relatively less attention than the study of the growth rate. There is a greater difficulty in estimating the lag time as this not only depends on the environmental conditions but also on the previous history of the cell, the composition of the medium in which the inoculum was cultivated or the stress conditions before inoculation into the new medium. These various factors make the lag time inevitably more prone to variability. In the previous subsection, we presented several population-based lag models, which are derived from deterministic primary growth models. However, it has been shown that the lag time depends on the inoculum level as the inoculum decreases to less than 100 cells per ml (Augustin et al., 2000; Robinson et al., 2001). This may be caused partly by the fact that not all the cells are able to divide, so what we observe is not a `true lag' phase but rather an `apparent' one (Pirt, 1975). The behaviour of an individual cell can be represented by using stochastic models. Such models have the major advantage of incorporating differences between individual cells so that a change in individual cell behaviours can be used to predict a change in population behaviour. Two stochastic growth models are mentioned in the following: the Baranyi lag phase model and the McKellar continuous discrete continuous (CDC) model. The Baranyi lag phase model (Baranyi, 2002) was developed to describe the transition between lag phase and exponential phase of the cell population by applying an integral formula for lag time distribution of the individual cells in a bacterial population. Assuming an exponential distribution for individual lag times, the model successfully predicted the growth curves of Brochothrix thermosphacta. However, Baranyi indicated that the assumption about exponential distribution of individual lag times had not been experimentally validated as it was not in practice feasible. Developed for individual cells, the McKellar continuous discrete continuous (CDC) model (McKellar et al., 2002a, 2002b; McKellar and Knight, 2000) combines a continuous adaptation phase with a discrete step making the transition to a continuous exponential growth phase. In this model, each individual cell follows a positively truncated normal distribution. At the end of their lag time, the discrete step shifts each cell into an exponential growth phase. The population growth curve is then derived from the pool of individual cell growth and the population lag time can be estimated. The

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advantage of the McKellar CDC model is that the model is dynamic in the population lag, and the specific growth rate max can change with the environmental conditions during the lag phase. This approach facilitates the study of single cell behaviour subjected to certain environmental factors such as pH and temperature (McKellar et al., 2002a). Secondary growth models Secondary models describe the effect of environmental factors on one or more parameters of the primary models (e.g., lag time, growth rate, death rate). Most of the studies have focused on the description of the bacterial growth rate as it is considered an implicit characteristic of an organism in a specific environment. To homogenise the variance of the parameters, square root and logarithmic transformations were usually applied on the growth rate before fitting. A number of models have been used for this purpose, including response surface models, square-roots and gamma-type models. Each type of model has its supporters, merits and disadvantages being often discussed in the literature. Equation 13.18 shows an example of a response surface model, proposed by Gibson et al. (1988) for the effects of temperature, pH and NaCl on the growth rate of Salmonella: ln y ˆ a ‡ b1 s ‡ b2 t ‡ b3 p ‡ b4 s2 ‡ b5 t2 ‡ b6 p2 ‡ b7 st ‡ b8 sp ‡ b9 tp ‡ e 13:18 where ln y denotes the natural logarithm of the modelled growth response variable (i.e., the modified Gompertz model parameters B or M); s, t, and p represent NaCl (% w/v), temperature (ëC) and pH, respectively; a, b1, b2, . . . b9 are the coefficients to be estimated; and e represents a random error, assumed to have a zero mean and constant variance. Figure 13.9 depicts generation time predictions for Salmonella at pH 6.1 as a function of temperature and NaCl concentration derived from the secondary model presented in Eq. 13.18 and including the observed values reported by Gibson et al. (1988). One advantage of the polynomial models, such as the one illustrated in Eq. 13.18, is that they allow in almost every case the development of a model for any environmental factor to be taken into account. However, the disadvantages of this approach lie in the relatively large number of parameters and their lack of biological significance. An example of a square root type model is that proposed by Ratkowsky et al. (1983), which relates the specific bacterial growth rate to temperature (in the entire temperature range allowing the growth of the considered microorganism), and is given by: p 13:19 max ˆ b
…T ÿ Tmin †
f1 ÿ exp‰c
…T ÿ Tmax †Šg where T is the temperature, b and c are model parameters without biological meaning, Tmin and Tmax are the theoretical minimum and maximum temperatures for growth, respectively. The inclusion of other factors such as pH

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Fig. 13.9 Salmonellae generation time model at pH 6.1 with temperature and NaCl concentration as controlling factors. Solid squares are observed values (secondary model and data from Gibson et al., 1988).

and water activity in square root and gamma models is discussed in Section 13.4.2. Secondary lag models Secondary lag time modelling is complicated, because the lag time is influenced not only by actual environmental factors, but also by the history or preincubation condition of the cells (i.e., their physiological state) and the inoculum size. Thus, during the secondary modelling, the lag phase can be taken into account in different ways: (i) models that assume that the product 
max is constant (as shown, for instance, in Eq. 13.10), and (ii) models where the lag time and growth rate are modelled independently. Assuming that the product of the lag time  and the maximum specific growth rate max is constant, the dependence of the lag time on the environmental conditions can be derived from the dependence of the maximum specific growth rate on the environmental conditions as long as the pre-culturing conditions remain unchanged. As such, the concept of relative lag time (RLT, Eq. 13.20) is useful when developing secondary lag models, but, as mentioned before, it should be used with caution, because distributions of RLT rather than

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single constant values have been reported for various organisms under a wide range of experimental conditions (Augustin and Carlier, 2000a; DelignetteMuller, 1998; Ross, 1999). In spite of that fact, the RLT concept simplifies the growth modelling process, because it enables the effects of  and max to be predicted by a single growth model. 
max 13:20 RLT ˆ ln …2† The cardinal parameter models (CPMs) (Le Marc et al., 2002; Rosso et al., 1995) can be used in such a way and have become an important group of empirical secondary models. The general principle of CPMs is to use model parameters that have a biological interpretation. CPMs rely on the assumption that the inhibitory effects of the environmental factors have a multiplicative effect on the maximum specific growth rate max (see Section 13.4.2 for further details). The inhibitory effect of each environmental factor is represented by a numerical function taking values between 0 (at inhibitory condition for that factor) and 1 (at optimal condition for that factor). Square-root type models have also been used to derive lag time from existing growth rate models based on the same assumption that the product 
max is constant (Devlieghere et al., 2000; Zwietering et al., 1991). Davey (1991) also applied this concept to change the linear Arrhenius model into a lag time model. Other authors developed secondary models independently for the generation time and the lag time. For example, Gibson et al. (1988), McClure et al. (1993), Zaika et al. (1998) followed such an approach using polynomial models, and Geeraerd et al. (1998) and GarcõÂa-Gimeno et al. (2002) followed this approach using artificial neural networks. It can be easily argued that pre-growth conditions are not taken into account in the estimation of the lag phase from these models. This will subsequently make the lag time estimate subject to greater variability. 13.4.2 Quantification of hurdle effects The concept of `hurdle technology' was developed by Professor Leistner and colleagues (Leistner, 1995; Leistner and Gorris, 1995). The basis of this approach is that the microbiological safety of food products can be achieved by applying a combination of different preservative factors (called hurdles). This hurdle concept is of particular interest for mildly preserved foods with minimal inactivation/intervention during processing (e.g., mild heat or fermentation process; Leistner, 2000). Predictive microbiology models should aim at quantifying the effects of the combined hurdles on the bacterial growth rate and the ability of the microorganisms to grow under specific environmental conditions. In this section, we will focus on gamma type models and growth/ no-growth (G/N-G) models which are commensurate with the assumptions underlying the `hurdle concept' (Bidlas and Lambert, 2008; McMeekin et al., 2000).

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McMeekin et al. (1987) observed that temperature and water activity had independent effects on the growth rate of Staphylococcus xylosus and that their overall effect could be obtained by multiplying separate temperature and aw terms: p max ˆ b
…T ÿ Tmin †
aw ÿ aw;min 13:21 where Tmin and aw,min are the theoretical minimum temperature and minimum water activity for growth, respectively and b is a model parameter without biological meaning. The independence of the effects of temperature and aw on the bacterial growth rate was also demonstrated for various microorganisms by Davey (1989). Adams et al. (1991) drew the same conclusions for the effects of temperature and pH on the growth rate of Yersinia enterocolitica. Zwietering et al. (1996) formalised this independent/multiplicative effect through the `Gamma concept'. The approach consists in multiplying the separate effects (normalised between 0 and 1) of the environmental factors on the bacterial growth rate. For temperature, pH and water activity, the model is written as follows: max ˆ opt
…T†
…pH†
…aw †

13:22

where opt is the growth rate at optimum conditions and (T), (pH) and (aw) are the relative effects of temperature, pH and water activity, respectively. The model is consistent with the hurdle concept: each environmental factor produces its own hurdle and the overall effect is obtained by multiplying the individual hurdles (Witjzes et al., 2001). If the assumption of multiplicative effects usually provides reasonable results for the growth rate (Zwietering, 2002), experimental observations suggest a synergistic rather than an independent effect at the growth/no-growth boundary (McMeekin et al., 2000). For example, it has been observed that the minimum pH and the water activity at which growth of L. monocytogenes and E. coli could be observed were increasing at low temperatures (Salter et al., 2000; Tienungoon et al., 2000). For this situation, quantification of the hurdles requires the modelling of the boundary between growth and no growth. As mentioned previously (see Section 13.2.2), logistic regression procedures have been commonly used to build probability of growth models for both pathogens and spoilage microorganisms. Available growth boundary models include equations for Shigella flexneri (Ratkowsky and Ross, 1995), E. coli (Presser et al., 1998; Salter et al., 2000), L. monocytogenes (Tienungoon et al., 2000), Salmonella (Koutsoumanis et al., 2004), and S. aureus (Valero et al., 2009). Deterministic approaches for which a binary response (either growth or nogrowth) rather than a probability were also proposed by Augustin and Carlier (2000b) and Le Marc et al. (2002). In these models, the equation for the G/N-G interface is defined on the cardinal parameters or the functions used in the growth rate modelling. Mejlholm and Dalgaard (2009) and Mejlholm et al. (2010) extended the approach developed by Le Marc et al. (2002) to model the effects of 12 environmental factors on the growth rate and the growth/no-growth boundary of L. monocytogenes in lightly preserved seafood and ready-to-eat

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meats. Most of the authors reported an abrupt transition between the growthpermitting conditions and the no-growth conditions. Therefore at the growth limits, small variations in the factors have a huge impact in terms of microbiological stability. G/N-G models can be used to identify which levels of factors will guarantee the microbiological stability and quantify the effects of variations in the formulations and storage of food products. 13.4.3 Relative rate of spoilage models The concept of relative rate of spoilage (RRS) is defined as the shelf life at a reference temperature divided by the shelf life at a temperature of interest T. As such, mathematical RRS models can be developed on the basis of shelf life data obtained during product storage trials at different temperatures using sensory evaluation as criterion for evaluating shelf life. Therefore, they are not really predictive microbiological models, as they do not consider the kinetics of growth of microorganisms, nor the types of reactions that cause spoilage. However, they are practical, easy to use, and have proven to be useful in predicting shelf life of fresh and preserved seafood at different storage temperatures (Dalgaard, 2002). When developing RRS models, the only information required is the product shelf life determined at one single known storage temperature (as determined by sensory evaluation), whose reciprocal value is the rate of spoilage (RS, expressed in daysÿ1). RS values are then fitted to different types of models (Eqs 13.23 to 13.25) to estimate temperature characteristic parameters, which will allow for the prediction of shelf life at different storage temperatures. The main types of RRS models used are: Square-root model shelf life at Tref ˆ RRS ˆ shelf life at T



T ÿ Tmin Tref ÿ Tmin

2

Exponential model shelf life at Tref ˆ exp‰a
…T ÿ Tref †Š RRS ˆ shelf life at T

13:23

13:24

Arrhenius model

   shelf life at Tref ÿEA 1 1 ˆ exp
RRS ˆ ÿ shelf life at T R TK Tref ;K

13:25

where Tmin (ëC), a (Cÿ1), and EA (kJ molÿ1) are the temperature characteristics for the square-root, the exponential and the Arrhenius models, respectively; Tref and Tref,K are the reference temperature (ëC and Kelvin, respectively), T and TK are the temperature (ëC and Kelvin, respectively); and, R is the universal gas constant (8.31 J molÿ1 Kÿ1).

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A few RRS models have been implemented in the Seafood Spoilage and Safety Predictor (Dalgaard et al., 2002), software made available free of charge by the National Institute of Aquatic Resources in Denmark (http:// sssp.dtuaqua.dk/), which will be discussed later (see Section 13.5.2).

13.5 Usage considerations and access to predictive microbiology electronic resources Several predictive microbiology electronic resources and software systems are nowadays available in the public domain around the globe. They fall mainly into three general categories: (i) searchable databases, (ii) fitting tools, and (iii) userfriendly applications of mathematical models (i.e., tertiary models) to predict the behaviour of microorganisms under different conditions in food and food environments. The various systems have been built in different ways and for different purposes. They also have quite different scopes and levels of quality control. Some of the systems have been developed with the support of government agencies in different countries, whereas others have been supported by academic institutions, independent research organisations or private companies. The various software systems cover a range of microorganisms and conditions, which sometimes overlap. However, as the systems have not been built in exactly the same way and the mathematical models for seemingly identical microorganisms or species are different, the predictions can be different. This highlights that predictions should be interpreted with care, recognising the limitations and assumptions behind each model and the conditions under which each model is valid, thereby avoiding misinterpretation of model predictions. Available predictive microbiology application software packages are described below. 13.5.1 ComBase and ComBase modelling toolbox ComBase (Baranyi and Tamplin, 2004) is a relational database of predictive microbiology information (http://www.combase.cc). ComBase contains a large volume of data on bacterial growth, survival and death under a range of conditions of temperature, pH, water activity and atmosphere as well as in a variety of different foods, including meat and fish, dairy products, fruit and vegetables. Using an Internet interface, users identify criteria that they are interested in for a food microbiology scenario(s). This includes identifying a type or species of organism, a type or class of food, pH, temperature, water activity (or NaCl concentration), and specific food conditions. Alternatively, ComBase customers may be interested in retrieving data donated by a specific source (publication, organisation or researcher). The data in ComBase can be used not only for model development but also to validate newly created models, to compare the predictions of established models developed in a specific medium (e.g., broth) against data recorded in other matrices, or to identify boundary growth values of specific organisms in a variety of foods.

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This initiative is a collaboration between the Food Standards Agency in the UK, the Institute of Food Research (IFR) in the UK, the USDA Agricultural Research Service, and the Australian Food Safety Centre of Excellence. The datasets have been donated by microbiology laboratories in academia, government and industry and have been derived from the published literature. The database is continuously updated. Through the ComBase website, users can find the ComBase Modelling Toolbox (http://www.combase.cc/toolbox.html) which includes three main components: (i) ComBase Predictor, (ii) Perfringens Predictor, and (iii) DMFit. ComBase Predictor ComBase Predictor is, in fact, a modified and expanded version of another stand-alone application previously developed by IFR, known as Growth Predictor, which in itself was the successor of the former Food MicroModel (McClure et al., 1994). It has a set of twenty growth models, seven thermal death models and two non-thermal survival models (see Table 13.1). ComBase Predictor allows for predictions under static and dynamic temperature conditions. In this case, the user simply enters a time±temperature profile (e.g., from a temperature data-logger) into the main interface of ComBase Predictor, and the predictions are presented both in graphic and tabulated form. The predictions can be easily copied into any spreadsheet software for further analyses. Another improvement over the Growth Predictor is the fact that ComBase Predictor can simultaneously produce predictions for up to four microorganisms, thereby facilitating comparisons amongst several scenarios. Perfringens Predictor Perfringens Predictor is specifically designed to predict the response of Clostridium perfringens during the cooling of cooked meats. Predictions from Perfringens Predictor are based on the heat treatment applied to the meat product being in the range of 70 ëC (for up to 6 hours) to 95 ëC (for up to 1.5 hours). The inputs to the model are temperature (dynamic profile to <15 ëC), pH of the meat (5.2±8.0), the concentration of salt (0±4%), and indicate whether or not the meat is cured. The cured meat option should only be used if the initial concentration of sodium nitrite is = 100 ppm and the residual concentration is 10 ppm. DMFit (web version) As mentioned in Section 13.3.2, DMFit is a fitting tool for bacterial growth or survival curves. The primary models included in DMFit are: (i) the Baranyi model (with three options: full model, model without lag, and model without asymptotic stationary phase), (ii) tri-linear model, (iii) bi-phasic models (with two options: no lag, and no asymptotic stationary phase), and (iv) linear model. The tool displays the fitted parameters for the selected model (maximum growth/death rate, lag time (or shoulder), initial cell count, final cell count, and estimate standard errors on these parameters) as well as the evaluation of fit (adjusted R2, and standard error of fit).

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Table 13.1 Summary of microorganisms and models included in the ComBase Predictor Microorganism

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Aeromonas hydrophila Bacillus cereus Bacillus cereus (spores) Bacillus licheniformis Bacillus subtilis Non-proteolytic Clostridium botulinum Non-proteolytic Clostridium botulinumb Proteolytic Clostridium botulinum Clostridium perfringens Escherichia coli Escherichia coli Listeria monocytogenes Listeria monocytogenes/ innocua Listeria monocytogenes Listeria monocytogenes

Physiological event

Response variablesa

Growth Growth Heat inactivation Growth Growth Growth

Independent variables and ranges Temperature

pH

NaCl (aw)

Other

, tD , tD k, D-value , tD , tD , tD

2±37 ëC 5±34 ëC 90±100 ëC 13±34 ëC 10±34 ëC 4±30 ëC

4.6±7.5 4.9±7.4 4.5±7.0 4.0±7.6 4.3±7.8 5.1±7.5

0.0±4.5% (0.974±1) 0.0±9.4% (0.94±1) 2.5±7.5% (0.954±0.986) 0.0±13.5% (0.907±1) 0.0±10.3% (0.933±1) 0.0±4.5% (0.974±1)

± CO2 (0±60%) ± ± ± ±

Heat inactivation

k, D-value

80±95 ëC

4.1±7.3

0.0±5.0% (0.971±1)

±

Growth

, tD

14±40 ëC

4.7±7.2

0.0±7.5% (0.954±1)

±

Growth Growth Heat inactivation Growth Growth

, tD , tD k, D-value , tD , tD

15±52 ëC 10±42 ëC 54.5±64.5 ëC 1±40 ëC 1±40 ëC

5.0±8.0 4.5±7.5 4.2±8.0 4.4±7.5 4.4±7.5

0.0±5.0% (0.971±1) 0.0±6.5% (0.961±1) 0.0±8.4% (0.986±1) 0.0±10.2% (0.934±1) 0.0±11.4% (0.924±1)

± CO2 (0±100%) ± CO2 (0±100%) NaNO2 (0±200 ppm)

Growth

, tD

1±40 ëC

4.4±7.5

0.0±11.4% (0.924±1)

Growth

, tD

1±40 ëC

4.4±7.5

0.0±11.4% (0.924±1)

Lactic acid (0±20 000 ppm) Acetic acid (0±10 000 ppm)

Table 13.1 Continued Microorganism ß Woodhead Publishing Limited, 2011

Physiological event

Response variablesa

Listeria monocytogenes Listeria monocytogenes Staphylococcus aureus Salmonella Salmonella Salmonella Salmonella Shigella flexneri Yersinia enterocolitica Yersinia enterocolitica

Heat inactivation Survival Growth Growth Growth Heat inactivation Survival Growth Growth Growth

Yersinia enterocolitica Brochothrix thermosphacta Brochothrix thermosphacta Pseudomonas spp.

Heat inactivation Growth Heat inactivation Growth

a

Independent variables and ranges Temperature

pH

NaCl (aw)

Other

k, D-value k, D-value , tD , tD , tD k, D-value k, D-value , tD , tD , tD

60±68 ëC 0±20 ëC 7.5±30 ëC 7±40 ëC 7±40 ëC 54.5±65 ëC 0±40 ëC 15±37 ëC ÿ1±37 ëC ÿ1±37 ëC

4.2±7.0 3.5±7.0 4.4±7.1 3.9±7.4 3.9±7.4 4.0±7.1 4.3±7.5 5.5±7.5 4.4±7.2 4.4±7.2

0.0±9.0% (0.943±1) 0.0±25.0% (0.793±1) 0.0±13.5% (0.907±1) 0.0±4.6% (0.973±1) 0.0±4.6% (0.973±1) 0.0±0.6% (0.997±1) 0.0±26.0% (0.781±1) 0.0±5.0% (0.971±1) 0.0±7.0% (0.957±1) 0.0±7.0% (0.957±1)

k, D-value , tD k, D-value , tD

52±60 ëC 0±30 ëC 40±55 ëC 0±20 ëC

4.2±7.0 5.5±7.0 5.0±7.0 5.0±7.4

0.0±6.5% (0.961±1) 0.0±8.0% (0.95±1) 0.0±2.0% (0.989±1) 0.0±6.5% (0.961±1)

± ± ± CO2 (0±100%) NaNO2 (0±200 ppm) ± ± NaNO2 (0±1000 ppm) CO2 (0±80%) Lactic acid (0±10 000 ppm) ± ± ± ±

 ˆ maximum growth rate (log10 concentration/h); tD ˆ doubling time (h); k ˆ maximum inactivation rate (log10 concentration/h); D-value ˆ decimal reduction time (h). b Spores, recovered in presence of lysozyme.

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13.5.2 Seafood Spoilage and Safety Predictor (SSSP) The Seafood Spoilage and Safety Predictor (SSSP) software (Dalgaard et al., 2002) predicts shelf life and growth of bacteria in different fresh and lightly preserved seafood. SSSP is a product of the Seafood and Predictive Microbiology research group of the National Institute of Aquatic Resources, Technical University of Denmark (available at: http://sssp.dtuaqua.dk/). The most current version of the software (SSSP v3.1) is available in various languages, and it is extremely well documented, with plenty of information about the development and validation of each of the models included, as well as other relevant information about predictive microbiology in general. Some of the key models included in SSSP v3.1 for prediction of shelf life in seafood are described below. Relative rate of spoilage models SSSP includes several RRS models, namely: · RRS models for fresh seafood (from tropical waters and from temperate waters). · RRS models for lightly preserved seafood (sliced and vacuum-packed coldsmoked salmon and cooked and brined shrimp stored in modified atmosphere packaging). · Models with user-defined parameter values that can be applied to any type of food. This module of SSSP also includes a facility that allows comparison of observed and predicted RRS data. Through this facility, shelf life data obtained at different temperatures can be quantitatively compared with the Arrhenius, exponential or square-root spoilage models (see Section 13.4.3) when used with known temperature characteristics. Thus, users can compare their own data with existing RRS models in SSSP or evaluate if the Arrhenius, exponential or square-root spoilage models will be appropriate for their shelf life data if these models are used with different temperature characteristics. The comparison between observed and predicted shelf life data relies on calculation of accuracy factor values as well as presentation of observed and predicted data in graphs. The accuracy factor in SSSP is calculated for RRS with the following equation: P 13:26 accuracy factor (RRS) ˆ 10 jlog…RRSpredicted =RRSobserved †j=n microbiological spoilage models SSSP includes various predictive models for different SSOs, namely: · Photobacterium phosphoreum: this microorganism is the SSO that limits the shelf life of fresh marine fish when stored in modified atmosphere packaging (MAP). Three models are available: fresh MAP cod fillets, fresh MAP plaice fillets, fresh MAP salmon steaks. The inputs to the model are: (i) initial concentration of bacteria in cfu/g, (ii) storage temperature, and (iii) percentage CO2. The outputs are remaining shelf life and microbial growth rate.

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· Shewanella putrefaciens: SSSP v3.1 includes a simple square-root model for the effect of temperature on max of Shewanella putrefaciens-like H2Sproducing spoilage bacteria in fresh fish stored aerobically. The range of applicability has been set to 0±10 ëC in SSSP although the more exact spoilage domain remains to be determined in storage trials. The maximum population density has been set to 109 cfu/g. · Microbiological spoilage model with user-defined parameters: this SSSP model with user-defined parameter values can compare growth and shelf life for: (i) two microorganisms with known and different cardinal parameter values when growing under a given set of storage conditions and product characteristics, or (ii) a single microorganism with known cardinal parameter values when growing under different storage conditions and/or different product characteristics (temperature, equilibrium CO2 concentration in MAP, aw and pH). In both cases, growth under constant or fluctuating temperature conditions can be compared. The square-root-type secondary growth model used by SSSP is given by Eq. 13.27: r (%CO2;max ÿ %CO2 † aw ÿ aw;min p

max ˆ b
…T ÿ Tmin †
%CO2;max …aw;ref ÿ aw;min † p 13:27 …pH ÿ pHmin †…pHref ÿ pHmin †

The model includes a constant (b) and the cardinal parameters Tmin, %CO2,max, aw,min and pHmin. The microbiological spoilage model with userdefined parameter values can be applied for all bacteria where an estimate of the constant b and the cardinal parameter Tmin can be obtained. Estimates of the other cardinal parameter values are not needed but clearly allow for a more flexible use of the model when available. · Comparison of observed and predicted data: this module allows data for growth of Photobacterium phosphoreum and Shewanella putrefaciens-like H2S-producing bacteria as determined in various experiments to be compared with predictions produced by SSSP. The module has been divided into three sub-modules to handle different types of data: (i) primary growth model at constant storage conditions, (ii) primary growth model at dynamic temperature conditions, and (iii) secondary model (for temperature and %CO2). Other relevant features of SSSP In addition to the RRS and spoilage models described above, SSSP v3.1 also includes models to predict growth and histamine formation by Morganella psychrotolerans and Morganella morganii (Emborg and Dalgaard, 2008a, 2008b), a model to predict the simultaneous growth of L. monocytogenes and lactic acid bacteria (LAB) in lightly preserved seafood (Mejlholm and Dalgaard, 2007), and a model to predict the growth boundary of L. monocytogenes in lightly preserved seafood depending on storage conditions and product characteristics (Mejlholm and Dalgaard, 2009). The L. monocytogenes-LAB

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growth model includes the effect of temperature, water phase salt/water activity, pH, lactate in the water phase, and smoke components/phenol on growth of L. monocytogenes in vacuum-packed cold-smoked salmon. SSSP recommends using the model for growth of L. monocytogenes without lag time. However, very little information is available about the lag time of L. monocytogenes in naturally contaminated cold-smoked salmon. Therefore, an optional lag phase corresponding to a RLT of 4.5 can be used. This option has not been included for LAB because numerous studies have shown these bacteria to grow without any lag time in chilled cold-smoked salmon. The growth boundary model for L. monocytogenes implemented in SSSP is based on the gamma model with interactions as originally proposed by Le Marc et al. (2002). 13.5.3 Sym'Previus Sym'Previus is a decision-making tool based on predictive microbiology. The software is organised as a collection of modules that are available on-line. An annual licence fee must be paid in order to access Sym'Previus. Instructions for subscribing to Sym'Previus are available on the website (http:// www.symprevius.org). Pathogens included in Sym'Previus are: Bacillus cereus, Clostridium botulinum type E, Clostridium perfringens, Escherichia coli, Listeria monocytogenes, Salmonella Typhimurium and Staphylococcus aureus. Spoilage organisms included in Sym'Previus are: Bacillus licheniformis, Citrobacter freundii, Enterococcus faecium, Lactobacillus casei, Lactobacillus sakei, Leuconostoc mesenteroides, Pseudomonas fluorescens, Pseudomonas putida and Serratia marcescens. The following are the main features and modules available in Sym'Previus. Database This database contains growth, survival and thermal destruction kinetics obtained in foodstuffs for the main pathogens. Data are mainly bibliographic and are progressively enriched by data from national and international research programmes. This database can be accessed using an interrogation module that is used to make structured requests related to foods and microorganisms. The results are shown as graphs or tables of values that can be saved directly as MicrosoftÕ Excel worksheets. The data collected are used to estimate parameters that reflect the characteristics of a microorganism in terms of growth potential or vulnerability to intrinsic or extrinsic factors. The different calculation modules can then be used to simulate the growth or inactivation of a given microorganism in a food. Growth simulation module Growth simulations take into account the food matrix effect and the main intrinsic/extrinsic environmental factors (temperature, pH and aw). Growth models are available for the following microorganisms: Bacillus cereus, Escherichia coli, Listeria monocytogenes and Salmonella. Up to 12 strains

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have been evaluated for each of these microorganisms in order to take biological variations into account. Simulations can be performed with any microorganism for which growth parameters are known. The primary growth model implemented in Sym'Previus is a Logistic model, which can be written as: 8 t  lag > < ln N0     ln N …t† ˆ Nmax > ÿ 1
exp…ÿmax …t ÿ lag†† t > lag : ln Nmax ÿ ln 1 ‡ N0 13:28 The parameters of Eq. 13.28 have already been explained in the context of other primary models described earlier in the chapter. The effect of the three main environmental factors (i.e., temperature, pH and aw) on growth of the microorganism is modelled using the Cardinal Model of Rosso et al. (1995). The input values for these three environmental factors can be entered as static (i.e., constant) or dynamic (e.g., a time±temperature profile) values. The output of this growth simulation module is presented as a list of growth parameters, a graphical display of the growth curve (including 80%, 90% and 95% confidence intervals), and a histogram of the growth rate distribution. Both the growth curve values (with confidence intervals) and the growth rate distribution can be easily exported to a MicrosoftÕ Excel file. Growth/no-growth interface simulation module This module calculates the combinations of environmental factors (temperature, pH, and aw) that represent the limits of growth/no-growth for a bacterial species. There are models available for the following microorganisms: Bacillus cereus, Clostridium botulinum (both proteolytic and non-proteolytic), Clostridium perfringens, Escherichia coli, Listeria monocytogenes, Salmonella, and Staphylococcus aureus. Additionally, the user can create a personalised model by manually entering the cardinal values for temperature (minimum, optimum, maximum), pH and aw (minimum, optimum). The personalised input screen also gives the option of defining the inhibitory effect of an organic acid, which the user can define by entering the following parameters: minimum inhibitory concentration (MIC, in mol/L), pKa and alpha (a shape parameter). The user enters a range of values for the two environmental factors for which a growth/no-growth interface prediction is desired (e.g., temperature and pH), and specifies a fixed value for the third factor (e.g., aw). The simulation result is provided as a graph showing three iso-probability growth curves (10%, 50%, and 90%). On this plot, the user can also add his/her own observations for comparison with the predicted probabilities of growth. A matrix containing the percentage probability of growth can be downloaded to MicrosoftÕ Excel. This module can be useful to evaluate whether a given pathogenic microorganism is capable of growing in a product (as defined by temperature, pH and/or aw), to evaluate the effect of changing a formulation, and to optimise the formulation (pH and/or aw) or the storage temperature.

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Other relevant features of Sym'Previus In addition to the three modules described above, Sym'Previus also includes the following facilities. Growth curve fitting tool This module allows the user to fit experimental growth data to the primary Logistic model shown in Eq. 13.28. The input (bacterial counts vs time) can be imported from a spreadsheet, or simply typed in directly on the input screen. The outputs are fitted parameters and standard deviations for growth rate, lag time, initial population and maximum population. The software displays the fitted curve and experimental inputs graphically. The fitted growth curve can be exported to MicrosoftÕ Excel. The second fitting facility in this module allows for secondary modelling of the growth rate as a function of environmental factors (temperature, pH or aw). Input values (growth rate vs one selected environmental factor) are fitted to the Cardinal Model of Rosso et al. (1995). The outputs are the fitted parameters for optimum growth rate (opt ), and the minimum, optimum and maximum values (temperature, pH or aw) for growth with corresponding standard deviation for each fitted parameter. A graphical depiction of the fitted model is also displayed on-screen. Probabilistic module This module simulates the evolution of a microbiological contaminant throughout the food product's shelf life and indicates the probability of exceeding a critical threshold at different stages of the shelf life. The inputs to this module are specific to the bacterial species, the characteristics of the food product and the environment it is in, as well as the processing conditions, so that the results can be tailored for each product and/or process relevant for a food company. The module is organised as a series of four sequential steps. Each step consists of a screen where specific questions need to be answered or for which information/data need to be entered. Outputs include the probability of growth in the food (per portion size), simulation of growth (with 90% confidence bands), evolution of contamination density (distribution) vs time, prevalence distribution of contaminated products at the end of shelf life, simulation of lag time and growth rate, factors affecting the growth simulation (i.e., evolution of gamma values and environmental factors), comments and remarks, and estimated contamination level at the end of shelf life. Thermal destruction simulation module This module simulates the destruction kinetics of a bacterial species during heat treatment, and calculates the reduction rate at the end of the treatment and the probability of a microorganism to survive. 13.5.4 Pathogen Modeling Program The Pathogen Modeling Program (available at: http://www.ars.usda.gov/naa/ errc/mfsru/pmp) is a stand-alone software package of microbial models and a

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research product of the Microbial Food Safety Research Unit (MFS) of the Agricultural Research Service (ARS) of the US Department of Agriculture. The model is available free of charge. The latest version (PMP 7.0) currently contains 38 models for 11 bacterial pathogens, including one model for spoilage flora in chicken (inactivation by irradiation). Table 13.2 presents a summary of the microorganisms and models included in PMP 7.0. Most models included in the PMP are isothermal; however, it contains four models that are able to predict the growth of C. botulinum and C. perfringens under time-varying temperature conditions (cooling models). Once downloaded, user-friendly features allow users to easily input food-relevant criteria and then to receive predictions about how pathogenic bacteria react to specific food environments. To further assist food processors in meeting regulatory requirements, references are provided for each model via direct Internet access to PDF files. A drawback of the PMP is the lack of information from validation studies showing the performance of models in specific foods as well as more general facilities to predict the effect of time-varying temperature conditions on growth and inactivation. Recently, an online version of PMP has been made available (http://pmp.arserrc.gov/PMPOnline.aspx), which does not include all the original models implemented in the stand-alone version; however, it includes new models that are not covered by the stand-alone version (e.g., a model for the transfer of Listeria monocytogenes during slicing of salmon).

13.6

Future trends

In spite of the scepticism that surrounded the field of predictive microbiology during the early years of research, predictive models are nowadays well established and widely accepted by the food industry, researchers in academia and government organisations. The international efforts to create databases such as ComBase have been fundamental to facilitate the development and validation of new models, but more importantly, to support the operation of quantitative microbiological risk assessments. However, there are still many models that could potentially be very useful to support product and process design in the food industry, but that have not been made available in a user-friendly software application. This is particularly true for models related to spoilage organisms. Other than a handful of applications (such as the Seafood Spoilage and Safety Predictor described in Section 13.5.2), most available systems and databases include models and data for pathogenic organisms only. Although many predictive spoilage models are available in the public domain, the majority of those are still only available via scientific publications. This poses a considerable barrier for wider application of models that are potentially very useful for the food industry. Although in some cases the implementation of published models in a spreadsheet format by potential users is possible, this can sometimes be limited by the lack of data (used for model development and/or validation) or other

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Table 13.2 Summary of microorganisms and models included in the stand-alone Pathogen Modeling Program (PMP 7.0) Microorganism

Physiological event

Response variablesa

Independent variables and ranges

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Temperature

pH

NaCl (% w/v)

Other

5±42 ëC

5.3±7.3

0.5±4.5

NaNO2 (0±150 ppm)

5±30 ëC

5.3±7.3

0.5±3.5

NaNO2 (0±150 ppm)

5±42 ëC

4.5±7.5

0.5±5.0

NaNO2 (0±150 ppm)

10±42 ëC

5.0±9.0

0.5±5.0

NaNO2 (0±150 ppm)

Time±temperature history (up to 50 data pairs) 15±34 ëC

±

±

±

5.0±7.2

0.0±4.0

±

Time to n-log reduction

70±90 ëC

5.0±7.0

0.0±3.0

Na-pyrophosphate (0.0±0.3%w/v)

Probability of growth (time to turbidity)

Pmax, , 

5±28 ëC

5.0±7.0

0.0±4.0

±

Length of lag phase

Lag (shelf life of fresh fish in modified atmospheres)

4±30 ëC

±

±

±

Growth (anaerobic)

GT, lag, time to n-log increase Net growth (in beef broth)

19±37 ëC

6.0±6.5

1.0±3.0

Time±temperature history (up to 50 data pairs)

±

±

Na-pyrophosphate (0.1±0.3%w/v) ±

Aeromonas hydrophila

Growth (aerobic)

Aeromonas hydrophila

Growth (anaerobic)

Bacillus cereus (vegetative cells) Bacillus cereus (vegetative cells) Proteolytic Clostridium botulinum (spores)

Growth (aerobic)

Proteolytic Clostridium botulinum Non-proteolytic Clostridium botulinum (spores) Non-proteolytic Clostridium botulinum (spores) Non-proteolytic Clostridium botulinum (spores ± types E & F) and aerobic competitive flora Clostridium perfringens (vegetative cells) Clostridium perfringens (spores)

Probability of growth (time to turbidity) Heat inactivation

Growth (anaerobic) Growth (during cooling)

Growth (during cooling)

GT, lag, time to n-log increase GT, lag, time to n-log increase GT, lag, time to n-log increase GT, lag, time to n-log increase Net growth Pmax, , 

Table 13.2 Continued Microorganism

Physiological event

Response variablesa

Independent variables and ranges Temperature

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Clostridium perfringens (spores)

Growth (during cooling)

Clostridium perfringens (spores)

Growth (during cooling)

Escherichia coli O157:H7 Escherichia coli O157:H7 Escherichia coli O157:H7 Escherichia coli O157:H7 Escherichia coli O157:H7 Listeria monocytogenes

Growth (aerobic) Growth (anaerobic) Heat inactivation Survival Inactivation by Gamma-irradiation Growth (aerobic)

Listeria monocytogenes

Growth (anaerobic)

Listeria monocytogenes

Heat inactivation

Listeria monocytogenes

Survival

Salmonella spp.

Growth (aerobic)

Salmonella spp.

Survival

Net growth (in cured beef)

Time±temperature history (up to 50 data pairs) Net growth Time±temperature (in cured chicken) history (up to 50 data pairs) GT, lag, time to 5±42 ëC n-log increase GT, lag, time to 5±42 ëC n-log increase Time to n-log 55±62.5 ëC reduction Time to n-log 4±37 ëC reduction Net reduction ÿ20±10 ëC (in beef tartar) GT, lag, time to 4±37 ëC n-log increase GT, lag, time to 4±37 ëC n-log increase Time to n-log 55±65 ëC reduction Time to n-log 4±42 ëC reduction GT, lag, time to 10±30 ëC n-log increase Time to n-log 5±42 ëC reduction

pH

NaCl (% w/v)

Other

±

±

±

±

±

±

4.5±8.5

0.5±5.0

NaNO2 (0±150 ppm)

4.5±8.5

0.5±5.0

NaNO2 (0±150 ppm)

4.0±8.0

0.0±6.0

3.5±7.0

0.5±15.0

±

±

Na-pyrophosphate (0.0±0.3%w/v) NaNO2 (0±75 ppm); lactic acid (0.0±2.0%w/w) Irradiation dose (0±2 kGy)

4.5±8.0

0.5±5.0

NaNO2 (0±150 ppm)

4.5±8.0

0.5±5.0

NaNO2 (0±150 ppm)

4.0±8.0

0.0±6.0

3.2±7.3

0.5±19.0

5.6±6.8

0.5±4.5

Na-pyrophosphate (0.0±0.3%w/v) NaNO2 (0±150 ppm); lactic acid (0.0±2.0%w/w) ±

3.5±7.2

0.5±16.0

NaNO2 (0±200 ppm)

Salmonella Typhimurium

Growth ± previous NaCl (aerobic)

Salmonella Typhimurium

Growth ± previous temperature (aerobic)

Salmonella Typhimurium

Growth ± previous pH (aerobic) Inactivation by Gamma-irradiation

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Salmonella Typhimurium

Inactivation by Gamma-irradiation

Salmonella Typhimurium

Inactivation by Gamma-irradiation

Shigella flexneri

Growth (aerobic)

Shigella flexneri

Growth (anaerobic)

Staphylococcus aureus

Growth (aerobic)

Staphylococcus aureus

Growth (anaerobic)

Staphylococcus aureus

Survival

Yersinia enterocolitica

Growth (aerobic)

Spoilage (normal flora)

Inactivation by Gamma-irradiation

a

GR, lag, time to 10±40 ëC n-log increase (in sterile chicken breast) GR, lag, time to 16±34 ëC n-log increase (in sterile chicken breast) GR, lag, time to 15±40 ëC n-log increase Net reduction (in ÿ20±10 ëC sterile chicken MDM) Net reduction (in non-sterile chicken MDM) Net reduction (in non-sterile chicken legs) GT, lag, time to n-log increase GT, lag, time to n-log increase GT, lag, time to n-log increase GT, lag, time to n-log increase Time to n-log reduction GT, lag, time to n-log increase Net reduction (in non-sterile chicken MDM)

±

±

Previous growth NaCl (0.5±4.5%w/v)

±

±

Previous growth temperature (16±34 ëC)

5.2±7.4

±

±

±

ÿ20±10 ëC

±

±

Previous growth pH (5.7±8.6) Irradiation dose (0±3.6 kGy); two models (air and vacuum atmospheres) Irradiation dose (0±3.6 kGy)

ÿ20±10 ëC

±

±

Irradiation dose (0±3.6 kGy)

10±37 ëC

5.0±7.5

0.5±5.0

NaNO2 (0±150 ppm)

12±37 ëC

5.5±7.5

0.5±4.0

NaNO2 (0±150 ppm)

10±42 ëC

4.5±9.0

0.5±12.5

NaNO2 (0±150 ppm)

12±42 ëC

5.3±9.0

0.5±16.5

NaNO2 (0±150 ppm)

4±37 ëC

3.0±7.0

0.5±20.0

5±42 ëC

4.5±8.5

0.5±5.0

NaNO2 (0±200 ppm); lactic acid (0.0±1.0%w/w) NaNO2 (0±150 ppm)

ÿ20±10 ëC

±

±

Irradiation dose (0±3.6 kGy)

GT ˆ generation time; GR ˆ growth rate; Pmax ˆ maximum probability of growth,  ˆ growth rate of individual samples showing growth;  ˆ time to ÝPmax (inflection point), MDM ˆ mechanically deboned meat; where there is no indication of a specific food matrix or medium in brackets it means the model was developed in laboratory media (broth).

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necessary modelling details, which are typically not included in the publication due to space limitations. Moreover, small processors may not have sufficient and/or qualified resources to use published models in an effective way. Also, in some cases, the model itself may indeed require software tools more sophisticated than a spreadsheet format in order to be implemented effectively. The submission of raw data to databases such as ComBase for newly developed and published models should be taken as `good modelling practice'. Moreover, details about conditions of the experiment, strains, growth or inactivation media, etc., used in the development of a model should also be reported clearly in order to prevent improper use of the data. Likewise, the presentation of experimental results used to develop a predictive model should, as much as possible, include information about sources of variability and the uncertainty of the results obtained. Of particular relevance to the prediction of shelf life, the effective integration of temperature data under real supply chain conditions with predictive models represents another important gap. Temperature conditions vary amongst different geographical regions and along different stages of the supply chain. However, it is still common practice to use single temperature values, simulating the worst-case temperature conditions along the supply chain, as inputs to deterministic predictive models for estimation of shelf life. This limits product design as the predictions obtained in this way are overly conservative. Instead, temperature distribution data collected during the different stages of the supply chain (e.g., storage, transport, distribution and retail) could be directly used as probabilistic inputs to predictive models to allow for a more realistic estimation of shelf life. To that extent, more studies dealing with stochastic models and associated implementation tools are necessary in order to account for the variation of supply chain data. Moreover, the ability to collect temperature data in real time for process control in situ remains an important challenge in the estimation of shelf life. In order to overcome this limitation, the use of radio frequency identification (RFID) tools (tags and readers) has gained considerable interest in recent years, not only for traceability of products through the supply chain, but also as a tool to collect product information (e.g., temperature) in real time. Other tools such as time±temperature integrators (TTIs) for monitoring temperature history and shelf life through the supply chain have been used in the food industry for several years, particularly in chilled foods. However, in recent years, excellent developments in the application of enzymatic TTIs (e.g., VITSAB Check PointÕ) and microbiological TTIs (e.g., Cryolog TRACEOÕ and (eO)Õ) to validate predictive spoilage models have been reported (see, for instance, Ellouze and Augustin, 2010; Nuin et al., 2008). This will allow food processors to bridge the gap between product traceability and management of food safety and stability. Development and validation of models in real food matrices continue to be another important gap that needs to be filled. Many of the models available in the public domain have been developed in liquid laboratory media (broth), which, oftentimes, supports the growth of microorganisms better than actual

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food matrices. Hence, many of these models are perceived by the food industry as very conservative, to the point that they have limited practical application. Although many efforts have been made in recent years to generate microbiological data in food matrices for model development and validation, there is still a need for more models developed in food materials for a wider range of applications. Likewise, understanding of microbial ecology in real food matrices, particularly as it relates to the interactions between populations of microorganisms under real manufacturing and shelf life conditions, remains a gap which needs to be filled. This knowledge would contribute to increasing the reliability of predictive models to support the design of microbiologically safe and stable food products. Undoubtedly, the development and application of predictive models in food microbiology have come a long way over the last 30 years. However, for real added value to food innovations at the stage of product/process design, predictive microbiological models need to be integrated with sensory response models, physical property models and process models with a view to providing the necessary tools for `in-silico' design of high-quality products. We are long way from achieving that. This is a need that is gaining increasing attention in the food industry as new preservation strategies need to be evaluated in a short amount of time in order to meet consumer demands for convenient, healthy, mildly preserved, and chemical-free labelled products. Computer-aided product/ process design, via an integrated user-friendly software application, could not only reduce considerably the time a new product takes to reach the market (from concept to delivery to consumer), but it could also allow for more realistic estimates of shelf life, reducing the potential for product wastage and for the occurrence of incidents in the market place. On a more futuristic note, it is worth highlighting that the evolution of science in the area of food microbiology has taken us to a point where there is a plethora of data and information on microbial physiology, genomics, microbial ecology and quantitative microbiology available in the scientific literature or other public sources. These areas will need to be linked in a systematic way for the development of models that can describe in a mechanistic way the behaviour of microorganisms in foods. This is by no means a small challenge, and it will require collaboration between food scientists, predictive modellers, network analysts and systems biologists to interpret and process the vast amount of bioinformatics information available in the context of realistic conditions found in food manufacturing.

13.7

Acknowledgements

The authors gratefully acknowledge Dr Clive de W. Blackburn, author of the first edition of this chapter and esteemed colleague at Unilever.

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13.8

Food and beverage stability and shelf life

References

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14 Modelling chemical and physical deterioration of foods and beverages M. J. Sousa Gallagher, P. V. Mahajan and Z. Yan, University College Cork, Ireland

Abstract: Foods are perishable and there are many factors that can deteriorate the quality and safety of food products during storage and distribution. These can be categorized into chemical and physical factors. To minimize the degradation of food during processing or storage, kinetic models which describe degradation rates and the dependence of intrinsic factors (i.e., critical factors) on extrinsic factors such as temperature and moisture content must be determined. The essential purpose of kinetic models is, first to describe sufficiently a set of experimental data obtained, and second to use the models for prediction, process control, optimization and simulation of food processing, packaging and storage operations. Key words: food degradation, shelf life, mathematical models, quality, temperature.

14.1

Introduction

The shelf life of food is the period during which the food retains an acceptable quality from a safety and organoleptic point of view, and depends on four main factors, namely formulation, processing, packaging and storage conditions. Foods are perishable and there are many factors that can deteriorate the quality and safety of food products during storage and distribution. These can be categorized into chemical and physical factors. To minimize the degradation of food during processing or storage, kinetic models which describe degradation rates and the dependence of intrinsic factors on extrinsic factors, such as temperature and moisture content, must be determined. The essential purpose of

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kinetic models is to describe sufficiently a set of experimentally obtained data. These kinetic models can then be used for prediction, process control, optimization and simulation of various food processing operations. It allows what-if scenarios and insights into the food systems to be explored and simplifies the process design for maximizing shelf life. Shelf life models are mathematical equations which describe the relationship between the food, the package and the environment. These models are based on different degradation factors (i.e., critical factors) and are essential in predicting the shelf life of food, in designing the packages, and providing useful insights about the foods under abnormal circumstances along the supply chain. Most of the efforts in terms of mathematical modelling have focused on microbiological safety and spoilage (Blackburn, 2000) and this chapter will be devoted to mathematical modelling of chemical and physical deterioration of foods.

14.2 Factors influencing shelf life 14.2.1 Factors responsible for degradation There are different types of product changes that can limit the shelf life of food and these can be classified into four main categories: formulation, processing, packaging and storage conditions. All four categories are critical, but their relative importance depends on the perishability of the food. Generally, a perishable food has less than 14 days of shelf life, but with aseptic technology and controlled atmosphere/modified atmosphere packaging (CA/MAP) such foods may last up to 90 days. A packaging system prevents the deterioration of packaged products to extend shelf life, to maintain quality and to increase the safety of the packaged foods. Some characteristics are considered important in assessing the quality of perishable food products, and knowledge of optimal environmental conditions and adequate packaging materials can be selected to guarantee high-quality product throughout the shelf life. The extent to which packaging can be successfully used to maintain quality and reduce spoilage and extend shelf life depends on: · an assessment of the product properties and identification of the critical quality parameters, i.e., how sensitive it is to changes in temperature, moisture, oxygen (air) and light; · an evaluation of the conditions to which the packed product is likely to be exposed in the supply chain, in order to design and develop packaging with an appropriate barrier and other relevant characteristics. Many factors can influence shelf life and these can be categorized into intrinsic and extrinsic (IFST, 1993). Intrinsic factors are the properties of the final product (e.g., water activity (aw), pH value and total acidity, available oxygen, redox potential (Eh), nutrients, natural microflora and surviving microbiological counts, natural biochemistry of the product formulation (enzymes,

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chemical reactants), use of preservatives in product formulation (e.g., salt)) (Kilcast and Subramaniam, 2000). Intrinsic factors are influenced by such variables as raw material type and quality, and product formulation and structure. Extrinsic factors are those factors that the final product encounters as it moves through the food chain (e.g., time±temperature profile during processing; relative humidity (RH), exposure to light and/or environmental microbial counts during processing/storage/distribution, temperature control during storage/distribution, composition of atmosphere within packaging, pressure in the headspace, subsequent heat treatment and consumer handling). The interaction of such intrinsic and extrinsic factors as these either inhibits or stimulates a number of processes which limit shelf life. These can be conveniently classified as: chemical, physical and microbiological. In modern processing, these factors are addressed in the HAACP (Hazard Analysis And Control Point) concept, a comprehensive quality control assurance methodology that aims to ensure both safety and high quality (Frampton, 1989; Stewart et al., 2003; Koutsoumanis et al., 2005). Therefore, the quality of products depends not only on its original state but also on the extent of changes during processing and storage. Environmental conditions like air humidity, air temperature, light, and oxygen affect the quality changes of foods during storage. Therefore, knowledge of optimal environmental conditions and selection of optimum packaging materials can be considered to prevent food degradation and ensure a high-quality product throughout the shelf life. 14.2.2 Identifying critical quality parameters Food is inherently perishable and, depending on its properties (e.g., physical and chemical) and the storage conditions, there will come a point when either its quality will become unacceptable or it will become harmful to the consumer. At this point it has reached the end of its shelf life and the ability to predict this is of great value to the food industry when defining storage and distribution conditions and limits, formulating products, assessing manufacturing processes and carrying out quantitative risk assessment. Therefore, it is important to identify which are the critical factors in order to determine the shelf life of the product. Depending on the nature of the product, various properties or quality indices must be experimentally followed as a function of time in order to evaluate the degradation of the product quality in terms of the physical-chemical properties. In order to fully account for all the degradation criteria, a well-planned experimental design must be adopted. Taking this into consideration, a standard and comprehensive protocol using the accelerated shelf life testing (ASLT) method has been outlined (Labuza and Schimdl, 1985; Corradini and Peleg, 2007). In general, the analysis is performed by following the variation of each quality index in time during storage and then comparing the measured value to a threshold, which is officially set by standards bodies or commonly accepted by a

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consumer panel as the limit of acceptance. As such the quality degradation of the product is judged by looking independently at the variations of the individual properties of the product during storage, with particular attention to the rapidly varying properties. The use of chemical kinetics, the study of the rates and mechanisms by which one chemical species converts to another and the Arrhenius relationship, which describes the influence of temperature on the reaction rate constants, have been used to model changes in food quality (Singh, 1994).

14.3 Development of mathematical models The essential purpose of mathematical models is to describe sufficiently a set of experimental data. Empirical models are useful in simulating food systems due to their complexity of reactions and non-homogeneous structure. Also from a pragmatic perspective, for practical purposes simple mathematical expressions can be easily used to control the process. The use of mathematical models can help to: · simplify design systems, e.g., product reformulations and process modifications, which are labour intensive, time consuming and expensive; · reduce number of experimental trials required to achieve optimal systems, e.g., packaging; · explore what-if scenarios and insights into the systems, e.g., possible packaging options worthy of testing; · develop a prototype, e.g., package and explore several choices of film types, package size, and product quantity, creating combinations that will result in beneficial atmospheres. 14.3.1 Basic reaction kinetics The loss of food quality for most foods can be represented by a mathematical equation: dC ˆ kC n 14:1 dt where C is the quality factor measured, t is time, k is a constant which depends on temperature and water activity, n is a power factor called the order of the reaction, and dC=dt is the rate of change of C with time. A negative sign is used if the deterioration is a loss of C and a positive sign if it is for production of an undesirable end-product. In zero-order reactions the rate is independent of the quality factor. For a degradation reaction: dC ˆk 14:2 ÿ dt

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which by integration results in: C ˆ C0 ÿ kt

14:3

where C0 is quality factor at time zero. In many cases C is not a very quantifiable or measurable value and is based solely on human panel evaluation. In this case Ci (initial value of C) is assumed to be 100% quality and Ce (value of C at end of shelf life) is just unacceptable quality. Thus, the rate of deterioration or the rate constant is given by: kˆ

100% ˆ constant % per day time

14:4

Some deterioration is applicable directly to zero-order kinetics, which include enzymatic degradation (fresh fruits and vegetables, some frozen foods, some refrigerated dough), non-enzymatic browning (e.g., dry cereals, dry dairy products, dry pet foods, loss of protein) and lipid oxidation (rancidity development in snacks, dry foods, pet foods, frozen foods). The mathematical expression for a first-order degradation reaction can be described by: ÿ

dC ˆ kC dt

14:5

which by integration becomes: C ˆ Ci  eÿkt

14:6

The types of deterioration that follow n ˆ 1 include rancidity (as in salad oil or dry vegetables), microbial growth and death, microbial production of offflavours and slime (meat, fish and poultry), vitamin loss (canned and dried foods) and loss of protein quality (dry foods). Very few data exist describing food degradation by orders other than zero or first. Lee et al. (1977) and Singh et al. (1976) have described the degradation of vitamin C in liquid foods such as tomato juice or canned infant formulas by a second-order reaction. Waloddi Weibull introduced the family of Weibull distributions in 1939. Determination of shelf life by hazard analysis has been extensively used in the mechanical and electrical industries. This approach has been adapted and developed for shelf life determination of foods. The procedure entails fitting failure time to a Weibull distribution and determining the time at which the product is expected to fail at different probability levels. This methodology has been utilized in the determination of the shelf life of foods (Thiemig et al., 1998; Hough et al., 1999; Cardelli and Labuza, 2001; Duyvesteyn et al., 2001). The Weibull model has been widely used in food research, e.g. describing water uptake and soluble solids losses during rehydration of dried apple pieces (Ilincanu et al., 1995), shrinkage of potato during frying (Costa et al., 2001), and enzyme inactivation under high pressure (Lemos et al., 1999).

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The probability product failure F…t† is related to storage time …t† according to:

F…t† ˆ 1 ÿ eÿ…t=†

14:7

where  is a scale constant and is the shape constant, or behaviour index. The Weibull model corresponds to the first-order degradation kinetics for specific case of ˆ 1 (Nelson, 1969). The is related to the kinetic mechanisms and may be expected to be temperature independent, at least within a limited range of temperatures, as found by Ilincanu et al. (1995) and Machado et al. (1999). This parameter gives the model a wide flexibility, making it a potentially good model to describe different reaction kinetics. Among empiric models, the Weibull model has been used to describe the behaviour of systems or events that have some degree of variability, such as quality parameters. The quality parameters can be described as:     C ÿ Ce t 14:8 ˆ exp ÿ C0 ÿ Ce  where C0, C and Ce are the initial, at time t, and at equilibrium quality parameter, respectively,  is the Weibull scale parameter, is the shape parameter (dimensionless), and t is the sampling time (Corzo et al., 2008). 14.3.2 Dependence of rate constant on temperature The above basic mathematical analysis of quality loss assumed a constant temperature. The rate constant k is dependent on temperature. Theoretically, k obeys the Arrhenius relationship, which states: k ˆ ko eÿEa =RT

14:9

where ko is a pre-exponent constant, Ea is the activation energy in cal/mol, R is the gas constant in cal/mol K and equals 1.986, and T is the temperature in K. Labuza (1982) enumerated potential causes for non-linear Arrhenius plots when the food product is held at high abuse temperature. Furthermore, when reaction or quality loss mechanisms change with temperature, the activation energy may be variable (Karel, 1983). The Arrhenius model does not use a finite reference temperature and the value of the rate constant (ko) at an infinite temperature is often very high. Van Boekel (1996) explained that to reduce correlation between ko and Ea, the temperature can be centred about the mean value of temperatures studied (Tref, reference temperature), and the Arrhenius equation can be reformulated as: ÿ
ÿERa T1 ÿT 1 ref 14:10 k ˆ kref  e where kref is the reparameterized pre-exponential factor: kref ˆ ko  e

ÿERa T 1

ref

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14.3.3 Q10 and accelerated shelf life tests Mathematical models have been used in the food and beverages industry to describe how much faster the product quality will proceed if this product is held at some high abuse temperature. If the temperature-accelerating factor is known, then extrapolation to lower temperatures could be used to predict true product shelf life in those conditions. This is the most often used methodology and yet it is commonly abused in design and interpretation of results, where the objectives are to store the finished product with certain packaging under some test abuse condition, examine the product periodically until the end of shelf life occurs, and then predict the product shelf life under true storage and distribution conditions. In the study of food shelf life, this accelerating factor is sometimes called the Q10 factor and is defined as: Q10 ˆ

s at T

14:12

s at T‡10

or Q10 ˆ

k…at T‡10† k…at T†

14:13

where T is the temperature (ëC), s is the shelf life at the indicated temperatures (Labuza, 1982), and k is rate constant of reaction. For any temperature difference
, different from 10 ëC, this becomes: Qs…T1 †
=10 14:14 Q10 ˆ Qs…T2 † If it is impossible to establish an Arrhenius plot, then, as shown by Labuza (1982), a simple plot of the log of the time to end of shelf life s (as established by some criteria) vs the temperature in ëC can be used, as long as the extrapolation does not go beyond the 30 ëC range. This plot also helps to establish the Q10. The value of either plot (log k vs Kÿ1) or (log s vs ëC) is that data can be collected at high temperature and used to extrapolate to shelf life at some lower temperature. However, when the product/package system is tested, the package also controls shelf life so that the true shelf life of the food itself is unknown; thus, if a new package with different permeability to oxygen, water, or carbon dioxide is chosen, Eq. 14.14 may not be applicable. If the accelerated shelf life test (ASLT) conditions are chosen properly, however, and the appropriate algorithms for extrapolation are used, then shelf life under any `unknown' distribution should be predictable. 14.3.4 Evaluation of the goodness of fit of the model to experimental data The criteria commonly followed to evaluate the goodness of fit of the model to the experimental data is the mean relative percentage deviation modulus (E), expressed as:

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N jmi ÿ mpi j 100 X mi N iˆ1

14:15

where mi is the experimental value, mpi is the predicted value, and N is the number of experimental data. The mean relative percentage deviation modulus (E) is widely adopted throughout the literature, with a modulus value below 10% indicative of a good fit for practical purposes. Boquet et al. (1978) suggested the use of the root mean square of deviations (Srm), expressed by Eq. 14.16 to compare the fitting abilities of the different equations when applied to the same experimental data: v u N u1 X …mi ÿ mpi †2 Srm ˆ t 14:16 N iˆ1 The relative percentage root mean square (r) has also been used (Bizot, 1983), expressed as: v u N  u 1 X mi ÿ mpi 2  100 14:17 rˆt mi N iˆ1 which combines both concepts described above.

14.4 Predictive mathematical models Kinetic studies dealing with the modelling of degradation of food components and nutrient losses during storage have received increasing attention in recent years. Labuza (1973), Saguy and Karel (1980) and Taoukis et al. (1997) have reviewed modelling of quality deterioration of foods during storage. 14.4.1 Colour Colour is one of the most important appearance attributes of food materials, since it influences the degree of consumer acceptability or it can even be harmful to health. Colour development is the result of various reactions such as non-enzymatic browning reactions and pigment destruction (Cornwell and Wrolstad, 1981; Wong and Stanton, 1992). In non-enzymatic browning reactions, the browning rates are closely related to temperature and relative humidity (Labuza and Saltmarch 1981; Rapusas and Driscoll, 1995; Soponronnarit et al., 1998). Prachayawarakorn et al. (2004) pointed out that the relative humidity at low levels played an important role in retarding browning reactions. Prachayawarakorn et al. (2004) and Kumar and Mishra (2004) found that the lightness and redness of dried garlic slices, and colour change of mango soy fortified yoghurt powder during storage followed a first-order and zero-order kinetic model, respectively. Dependence of the reaction rates on temperature

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could be described by the Arrhenius equation (Kaymak-Ertekin and Gedik, 2005). Krokida et al. (2001) found that the changes in redness (a) and yellowness (b) were found to follow a first-order kinetic model during drying of apple, banana, potato and carrot. Chen and Ramaswamy (2002) concluded that the changes of Hunter L and
E values of ripening banana followed a logistic model, while a and b values were well described by a simple zero-order and fraction conversion models. Yan et al. (2008b) showed that the colour (L and
E) degradation of intermediate moisture content (IMC) banana under different relative humidities at 20, 30 and 40 ëC showed a good fit to the zero-order reaction model and a secondary model (Eq. 14.18) was also developed to describe the changes of L values during storage, which could be used to predict the colour of IMC banana under a range of different relative humidities and temperatures during storage: h  i L ˆ Lo ‡ …a1 ln RH ‡ a2 †  t  e

…c1 ‡c2 RH‡c3 RH2 † R

1 1 Tref ÿT

14:18

14.4.2 Moisture content and water activity The moisture and/or water activity of dried or IMC product has a critical influence on its storage stability and moisture migration from the environment (Yan et al., 2008a). Textural quality, chemical and biochemical reactions, and microbial growth rates are greatly affected by moisture content of products. IMC banana is hygroscopic which absorbs or desorbs moisture under different environmental conditions. Therefore, control of moisture adsorption in the distribution chain is critical to control the quality of IMC banana. The effects of temperature (10, 15, 20, 30 and 40 ëC) and relative humidity (76% RH) on the kinetics of the changes of moisture content and water activity of IMC banana during storage were investigated (Yan et al., 2008b). It was found that moisture was absorbed faster when stored at high temperature and at high relative humidity due to higher driving force (awe ÿ aw ) at the beginning stage of storage (Fig. 14.1). However, when moisture content of IMC banana nearly reached equilibrium, the change in moisture content at different relative humidities all levelled off. To understand the physical-chemical relationship between water and the various components in foods, water activity is more revealing than moisture content. The equilibrium relationship between the water activity and moisture content of foods at constant temperature and pressures is shown by the sorption isotherms of foods. Thus, with the knowledge of the moisture content sorption isotherm, it is possible to predict the maximum moisture that the food can be allowed to gain during storage. Therefore, the moisture content of IMC banana was converted into water activity by sorption isotherms (Yan et al., 2008b). Various mathematical models have been proposed in the literature to describe sorption isotherms. Some were developed with a theoretical basis to describe adsorption mechanisms (e.g., GAB), whereas others are just empirical or a simplification of more elaborate models. In some ranges of water activity,

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Fig. 14.1 Influence of temperature on the moisture uptake by IMC banana under 75% RH (source: Yan et al., 2008b).

sorption isotherms can be approximated to linear equations. Sorption isotherms are usually classified according to their shape in five different types: I, II, III, IV and V (Brunauer et al., 1940). Dried food products usually show isotherms of Type II or III. A summary of the equations that have been reported in the literature to describe sorption isotherms of dried food products is shown in Table 14.1. It should be noted that in some cases these equations predict non-zero moisture content for zero water activity and some of the equations take into account the effect of temperature. The modified Chung±Pfost, modified Henderson, modified Halsey, modified Oswin and GAB equations have been adopted as standard equations by the American Society of Agricultural Engineers for describing sorption isotherms (ASAE, 1995). The equations of BET and GAB provide the monolayer moisture content, which can be considered to be the most useful for determining the optimum moisture conditions for good storage stability, especially for dehydrated foods (Arslan and TogÏrul, 2006). Yan et al. (2008b) found that water activity change of samples stored under different relative humidities and temperatures could be fitted by the lumped capacity model (i.e., first-order kinetics due to the predominance of the external resistance to mass transfer) (Eq. 14.19) in agreement with Costa and Oliveira (1999) and as shown in Fig. 14.2: daw ˆ K…awe ÿ aw † 14:19 dt where awe and aw are the water activity of sample at equilibrium and at time t, respectively; the rate constant, K (dayÿ1), changed with temperature according to an Arrhenius type equation:

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Table 14.1 Mathematical models used to describe sorption isotherms Model

Equation

Constants

Type

Halsey

  A 1=B MC ˆ ÿ ln aw

A ˆ RT=a B

II

Halsey (1948)

A B

II

Chung and Pfost (1967)

Mo Caw 1 ÿ aw ‡ aw …C ÿ 1†…1 ÿ aw †

C ± related to heat of sorption Mo ± monolayer moisture content

II

Brunauer et al. (1938)

A 1 ÿ Baw

A ˆ Mo BC B

III

Weisser (1986)

C ˆ C 0 e…H1 ÿHm †=RT K ˆ K 0 e…H1 ÿHq †=RT Mo ± monolayer moisture content

II or III

Van den Berg and Bruin (1981)

Mo ± monolayer moisture content Mo …C=T†Kaw K …1 ÿ Kaw †…1 ÿ Kaw ‡ …C=T†Kaw † C

II or III

Jayas and Mazza (1993)

Chung & Pfost* ß Woodhead Publishing Limited, 2011

BET

MC ˆ ÿ MC ˆ

BET (modified)

GAB

GAB (modified)

Oswin Henderson

ln …ÿA ln …aw †† B

MC ˆ

MC ˆ

MC ˆ

CKMo aw …1 ÿ Kaw †…1 ÿ Kaw ‡ CKaw †

 B aw MC ˆ A 1 ÿ aw   ln …1 ÿ aw † 1=B MC ˆ ÿ A

Reference

A B

B < 1 II B > 1 III

Oswin (1946)

A ˆ aT B

B > 1 II B < 1 III

Henderson (1952)

Table 14.1 Continued Model

Equation

Constants

Type

Smith*

MC ˆ A ÿ B ln …1 ÿ aw †

A B

II

Smith (1947)

A B

II

Iglesias and Chirife (1978)

A B

II

Iglesias and Chirife (1981)

A B C

II

Pfost et al. (1976)

  ÿexp…A ‡ Bt† 1=C ln aw

A B C

II

Iglesias and Chirife (1976)

 C aw MC ˆ …A ‡ Bt† 1 ÿ aw

A B C

C < 1 II C > 1 III

Oswin (1946)

A B C

C > 1 II C < 1 III

Thompson et al. (1968)

A B

II

Iglesias and Chirife 1*

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Iglesias and Chirife 2*

Chung±Pfost* (modified) Halsey (modified)

Oswin (modified)

Henderson (modified)

Freundlich

MC ˆ

e2…A‡Baw † ÿ M0:5 2e…A‡Baw †

MC ˆ A ‡ B

MC ˆ ÿln

MC ˆ

 MC ˆ

aw 1 ÿ aw

  ÿ…B ‡ t† ln aw =C A

ÿln …1 ÿ aw † A…B ‡ t†

MC ˆ A…aw †1=B

1=C

Reference

Freundlich (1926)

MC ± moisture content (g water/g dry solids); aw ± water activity; T ± temperature (K); t ± temperature (ëC); H1 ± heat of condensation of pure water vapour; Hm ± total heat of sorption of the first layer; Hq ± total heat of sorption of the multilayers; M0.5 ± moisture content at aw ˆ 0.5. * The moisture content for zero water activity is different from zero.

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Fig. 14.2 Variation of water activity with time predicted by sorption isotherm and by the approximation of the lumped capacity model at 10 ëC (a), 15 ëC (b), 20 ëC (c), 30 ëC (d) and 40 ëC (e) (source: Yan et al., 2008b).



aw ˆ awe ‡ …awo ÿ awe †exp…Kref

  Ea 1 1
t† ÿ
exp ÿ R T Tref

14:20

where T is temperature (K); t is time (day); Ea is activation energy in cal/mol, Tref and Kref are reference temperature (K) and K at reference temperature, respectively. The effect of temperature on the changes in water activity was also evaluated by using the secondary model (Eq. 14.20), which correlated the lumped capacity model (Eq. 14.19) with the Arrhenius equation. The comparison between water activity predicted by sorption isotherm and the secondary model, the plot of frequency distribution of residuals and normal probability plot of residuals are presented in Fig. 14.3. The secondary model was shown to fit very well (R2 ˆ 0:982 and E ˆ 1:642) all the data under different relative humidities at

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Fig. 14.3 Diagnosis plot between experimental data and the secondary model predictions of aw; small plots show the frequency distributions of the residuals (top left corner) and distribution of the residuals with the predicted values of water activity (bottom right corner) (source: Yan et al., 2008b).

different temperatures. Moreover, p-levels of all the constants estimated were less than 0.05 and the correlation matrix of the constant estimates (Kref and Ea) of the secondary model was low (ÿ0.275). Ea and Kref were determined as 26.71 kJ molÿ1 and 0.234 dayÿ1, respectively. Johnson and Brennan (2000) found that the changes in moisture content of plantain flour under certain relative humidities and temperatures could be represented by a quadratic polynomial model. Muthukumarappan and Gunasekaran (1996) and Sapru and Labuza (1996) used the finite difference method analysis to solve for moisture migration in corn kernel, cereals and raisins, respectively. 14.4.3 Respiration The processing of fresh-cut produce is different from intact produce, due to which interference occurs in tissue and cell integrity, with the associated increase in enzymatic, respiratory and microbiological activity, and therefore reduced shelf life. The respiration rates (RO2, RCO2) are measured by the difference in O2 and CO2 concentrations at different time intervals using the following equations:

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Modelling chemical and physical deterioration of foods and beverages yO2 ˆ yiO2 ÿ

RO2
W
…t ÿ ti † Vf

yCO2 ˆ yiCO2 ‡

RCO2
W
…t ÿ ti † Vf

473 14:21 14:22

where yiO2 , yiCO2 , yO2 and yCO2 are, respectively, the O2 and CO2 concentrations (volumetric fraction) in the gas mix at the initial time ti (h) (or time zero) and at time t (h). RO2 and RCO2 are the respiration rates and W is the weight of the product (kg) and Vf is the free volume inside the package (ml). The effect of temperature is described by an Arrhenius-type equation as shown by: ÿ
  ÿREac  T1 ÿT 1 ref 14:23 RR ˆ Rref  e where RR is respiration rate (ml/(kg.hr)), Rref is reference respiration rate (ml/ (kg.hr)), Ea is activation energy (kJ/mol), Rc is universal gas constant (0.008314 kJ/(mol.K)), T is temperature (K) and Tref is reference temperature (average temperature ˆ 283.15 K). By adjusting Eq. 14.23 in Eqs 14.21 and 14.22, the global mathematical model, as shown in Eqs 14.24 and 14.25, is then used to predict the respiration rate, for example, of mushrooms as a function of temperature and to estimate the Arrhenius equation parameter directly from the raw experimental data, thus minimizing errors in parameter estimates.
  EO ÿ W ÿ 2  1ÿ 1 14:24 yO2 ˆ yiO2 ÿ RO2;ref  e Rc T Tref   …t ÿ ti † Vf
  ECO ÿ W ÿ 2  1ÿ 1 14:25 yCO2 ˆ yiCO2 ‡ RCO2;ref  e Rc T Tref   …t ÿ ti † Vf The dependence of respiration rate on O2 concentration has been widely expressed by a Michaelis±Menten type equation, which is the simplest enzymatic kinetic mechanism. The role of CO2 in respiration was suggested to be mediated by an inhibition mechanism of the Michaelis±Menten equation, as shown in Table 14.2. The maximum rate () of O2 consumption or CO2 production and the dissociation constant () of the enzyme±substrate complex corresponding to the concentration of half the maximal respiration rate may be estimated by linearization of the equation. Competitive inhibition occurs when both the inhibitor (CO2) and the substrate (O2) compete for the same active site of the enzyme. Thus, the maximum respiration rate is lower in high CO2 concentrations. Uncompetitive inhibition occurs when the inhibitor reacts with the substrate±enzyme complex. In this case, the maximum respiration rate is not much influenced at high CO2 concentrations. Non-competitive inhibition occurs when the inhibitor reacts both with the enzyme and with the enzyme±substrate complex (Fonseca et al., 2002). 14.4.4 Water loss or transpiration Water loss or transpiration is an important physiological process that affects the main quality characteristics of fresh produce, such as saleable weight,

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Table 14.2 Enzyme kinetic equations for different types of inhibitory mechanisms to model the influence of O2 and CO2 on respiration rate (Fonseca et al., 2002), where  is the maximum rate of O2 consumption or CO2 production and  is the dissociation constant of the enzyme-substrate complex or the concentration corresponding to the half maximal respiration rate Equation Rˆ Rˆ

Rˆ

Rˆ

Rˆ

Type of inhibition

  yO2  ‡ yO2

No inhibition

  yO2   yCO2 ‡ yO2  1‡ yc   yO2   yCO2  ‡ yO2  1 ‡ yu   yO2   yCO2 … ‡ yO2 †  1 ‡ yn   yO 2     yCO2 yCO2 ‡ yO2  1 ‡  1‡ yc yu

Competitive

Uncompetitive

Non-competitive

Competitive + Uncompetitive

appearance and texture. Transpiration rate is influenced by factors such as temperature, humidity, surface area, respiration rate and air movement. The relative humidity of the ambient atmosphere has a considerable effect on water loss of fresh mushrooms during storage and the measurement and model development of mass loss rate (transpiration rate) was reported by Mahajan et al. (2008). Low RH was found to increase moisture loss in mushrooms causing shrinkage and quality deterioration, whereas high RH causes moisture to persist on caps supporting microbial growth and causing browning or yellowing of surface. The results stress the importance of maintaining proper in-pack humidity levels as well as storage temperature in order to extend the shelf life of mushrooms. Transpiration rate is expressed in terms of change in mass of mushrooms per unit time per unit surface area of mushroom as shown in Eq. 14.26: 1 dM 14:26 TR ˆ ÿ As dt where TR is the transpiration rate in mg/(cm2.h). Integrating Eq. 14.26 with the limits of initial mass Mi to mass M at time t and re-arranging, we have the mass at time t as:  1=…1ÿb† 14:27 M ˆ Mi1ÿb ‡ d  …b ÿ 1†  TR  t

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According to Ben-Yehoshua (1987) the flow of water vapour through a fruit surface was proportional to the difference between humidity of fruit internal atmosphere and humidity of the storage atmosphere and behaves according to Fick's law of gas diffusion. In this model the relative humidity of fruit internal atmosphere was considered as a first approximation to be 1.0 (or 100% RH). This parameter depends on solute content of the fruit and is slightly less than 1.0. dV 14:28 ˆ ÿKi  As  …awi ÿ aw † dt where V is the volume of water given off by the mushrooms; aw is water activity of the container, RH/100; awi is the water activity of mushrooms and Ki is mass transfer coefficient. The moisture content of fresh mushrooms was measured and found to be 92.4%; therefore the system developed for fruits could be applied to mushrooms. It showed that the aw of mushrooms remained constant throughout the storage period despite storing mushrooms at different combinations of temperature and humidity. This gives a constant humidity gradient across the mushroom yielding uniform mass loss during the storage period. Equation 14.27 was expressed in terms of change in mass of mushroom with respect to time as: dM ˆ ÿ  Ki  As  …awi ÿ aw † 14:29 dt where  is the density of water. Equation 14.29 was rearranged and combined with Eq. 14.26 yielding Eq. 14.30 where TR is the transpiration rate: dM ˆ TR ˆ   Ki  …awi ÿ aw † 14:30 dt  As Equation 14.30 was then integrated with the limits Mi to M for mushroom mass and 0 to t for storage time yielding:  1=…1ÿb† 14:31 M ˆ Mi1ÿb ‡ …b ÿ 1†    Ki  d  …awi ÿ aw †  t The mass transfer coefficient Ki of this model was estimated by fitting Eq. 14.31 to the experimental data by non-linear regression using Statistica software (Statsoft, Tulsa, USA). The values of mass of mushrooms predicted by Eq. 14.31 were in close agreement with those obtained experimentally (R2 > 99:8). A good agreement was found between observed and predicted transpiration rates as shown in Fig. 14.4. The distribution of residuals was normal (Fig. 14.4), indicating that the trend is not biased. The coefficient Ki, as determined for each set of experimental conditions, was found to increase with temperature. Hence, Eq. 14.31 was modified in order to incorporate the overall effect of temperature on Ki yielding:  1=…1ÿb† M ˆ Mi1ÿb ‡ …b ÿ 1†    Ki  d  …awi ÿ aw †  …1 ÿ eÿaT †  t 14:32

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Fig. 14.4 Relationship between experimental and predicted mass of mushrooms for all the experimental data. The upper left graph shows residual versus predicted values of mass of mushrooms and bottom right graph shows the distribution of residuals obtained from the secondary model (source: Mahajan et al., 2008).

14.5 Future trends It is widely accepted that consumer acceptance of foods is determined mainly by their sensory perception. Lots of researchers have been trying to explain the relationship between sensory characteristics and instrumental measurements. Auerswald et al. (1999), Bozkurt and Bayram (2006), Sousa et al. (2007) and Yan et al. (2008a) found a significant correlation between instrumental and sensory evaluation for blackberries, tomato and Sucuk, and banana, respectively. Repeated measurements are data where individuals have multiple measurements over time or space. Analysing these data requires recognizing and estimating variability both between and within individuals. Further, it is not uncommon for the relationship between an explanatory variable (e.g., time) and a response variable (e.g., colour or texture change) to be non-linear in the parameters. Non-linear mixed effects models provide a tool for analysing repeated measurement data by taking into consideration these two types of variability as well as the non-linear relationship between the explanatory variable and the response variable. Non-linear mixed-effects (NLME) models are hierarchical, involving both fixed effects associated to the population

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variability and random effects accounting for unexplained inter- and intraindividual variability, respectively. In a mixed-effect model, fixed effects are the parameters associated with an entire population or with certain repeatable experimental factors, and random effects are associated with individual experimental units (Lang, 2007; Mohapatra et al., 2008). Computational fluid dynamics (CFD) is a numerical solution of heat, mass and momentum (fluid flow) transfer equations simultaneously with the given boundary conditions. Use of CFD in food processing/preservation is currently limited to food processing operations. There is a need for application of CFD to food storage/packaging and shelf life studies (Erdogdu, 2009).

14.6

References

and TOGÏRUL H (2006). The fitting of various models to water sorption isotherms of tea stored in a chamber under controlled temperature and humidity. Journal of Stored Products Research, 42, 112±135. ASAE (1995). Moisture relationship of plant-based agricultural products. ASAE Standard D245.5. St. Joseph, MI. È CKNER B, KRUMBEIN A and KUCHENBUCH R (1999). Sensory AUERSWALD H, PETERS P, BRU analysis and instrumental measurements of short-term stored tomatoes (Lycopersicon esculentum Mill.). Postharvest Biology and Technology, 15, 323± 334. BEN-YEHOSHUA S (1987). Transpiration, water stress, and gas exchange. In: Postharvest Physiology of Vegetables, J Weichmann (ed.). Marcel Dekker, New York, pp. 113± 170. BIZOT H (1983). Using the GAB model to construct sorption isotherms. In: Physical Properties of Foods, R Jowitt, F E Escher, B Hallstrom, H F T Meffert, W E L Spiess and G Vos (eds). Applied Science Publishers, London. BLACKBURN W C (2000). Modelling shelf-life, In: The Stability and Shelf-Life of Food, D. Kilcast and P. Subramaniam (eds). Woodhead Publishing Limited, Cambridge, pp. 249±278. BOQUET R, CHIRIFE J and IGLESIAS H A (1978). Equations for fitting water sorption isotherms of foods. II. Evaluations of various two-parameter models. Journal of Food Technology, 14, 319±327. BOZKURT H and BAYRAM M (2006). Colour and textural attributes of Sucuk during ripening. Meat Science, 73, 344±350. BRUNAUER S, EMMETT P H and TELLER E (1938). Adsorption of gases in multimolecular layers. Journal of the American Chemical Society, 60, 309±319. BRUNAUER S, DEMING L S, DEMING W E and TELLER E (1940). On a theory of the van der Waals adsorption of gases. Journal of the American Chemical Society, 62, 1723± 1732. CARDELLI C and LABUZA T P (2001). Application of Weibull hazard analysis to the determination of shelf life of roasted and ground coffee. Lebensmittel-Wissenschaft und -Technologie, 34, 273±278. CHEN, C R and RAMASWAMY H S (2002). Colour and texture change kinetics in ripening bananas. Lebensmittel-Wissenschaft und -Technologie, 35, 415±419. ARSLAN N

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and PFOST H B (1967). Adsorption and desorption of water vapour by cereal grains and their products. Part II: development of the general isotherm equation. Transactions of the American Society of Agricultural Engineers, 10, 552±555. CORNWELL C J and WROLSTAD R E (1981). Causes of browning in pear juice concentrate during storage. Journal of Food Science, 46, 515±518. CORRADINI M G and PELEG M (2007). Shelf-life estimation from accelerated storage data. Trends Food Sci. Technol., 18, 37±47. Â SQUEZ A (2008). Weibull distribution for modeling CORZO O, BRACHO N, PEREIRA A and VA air drying of coroba slices. Food Science and Technology, 41, 2023±2028. COSTA R M and OLIVEIRA F A R (1999). Modelling the kinetics of water loss during potato frying with a compartmental dynamic model. Journal of Food Engineering, 41, 177±185. COSTA R M, OLIVEIRA F A R and BOUTHCHEVA G (2001). Structural changes and shrinkage of potato during frying. International Journal of Food Science and Technology, 36, 11±23. DUYVESTEYN W S, SHIMONI E and LABUZA T P (2001). Determination of the end of shelf life for milk using Weibull hazard method. Lebensmittel-Wissenschaft undTechnologie, 34, 143±148. ERDOGDU F (2009). Computational fluid dynamics for optimization in food processing. In: Optimisation in Food Engineering, F Erdogdu (ed.). CRC Press, Boca Raton, FL, pp. 219±227. FONSECA S C, OLIVEIRA F A and BRECHT J K (2002). Modelling respiration rate of fresh fruits and vegetables for modified atmosphere packages: a review. Journal of Food Engineering, 52, 99±119. FRAMPTON A (1989). Prevention of rancidity in confectionery and biscuits. The Manufacturing Confectioner, 129±136. FREUNDLICH H (1926). Colloid and Capillary Chemistry, Methuen, London. HALSEY G (1948). Physical adsorption on non-uniform surfaces. Journal of Chemical Physics, 16, 931±937. HENDERSON S M (1952). A basic concept of equilibrium moisture. Agricultural Engineering, 33, 9±32. HOUGH L, PUGLIESO M L, SANCHEZ R and DA SILVA O M (1999). Sensory and microbiological shelf life of commercial ricotta cheese. Journal of Dairy Science, 82, 454±459. IFST (1993). Shelf Life of Foods ± Guidelines for its Determination and Prediction. IFST, London. IGLESIAS H A and CHIRIFE J (1976). Prediction of the effect of temperature on water sorption isotherm of food materials. Journal of Food Technology, 11, 109±116. IGLESIAS H A and CHIRIFE J (1978). Delayed crystallization of amorphous sucrose in humidified freeze-dried model systems. Journal of Food Technology, 13, 137±144. IGLESIAS H A and CHIRIFE J (1981). An equation for fitting uncommon water sorption isotherms in foods. Lebensmittel-Wissenschaft und -Technologie, 14, 111±117. ILINCANU L A, OLIVEIRA F A R, DRUMOND M, MACHADO M F and GEKAS V (1995). Modelling moisture uptake and soluble solids losses during rehydration of dried apple pieces. In: Proceedings of the First Main Meeting of the Copernicus Programme Project `Process Optimisation and Minimal Processing of Foods. Vol. 3: Drying', J C Oliveira (ed.). Escola Superior de Biotechnologia-Universidade Catolica Portuguesa, Porto, Portugal, pp. 64±69. JAYAS D S and MAZZA G (1993). Comparison of five, three-parameter equations for description of dsorption data of oats, Transactions of the ASAE, 36, 119±125. CHUNG D S

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and BRENNAN J G (2000). Kinetics of moisture absorption by plantain flour. Journal of Food Engineering, 45, 33±36. KAREL M (1983). Quantitative analysis and simulation of food quality losses during processing and storage, In: Computer-aided Techniques in Food Technology, I Saguy (ed.). Marcel Dekker, New York, pp. 117±135. KAYMAK-ERTEKIN F and GEDIK A (2005). Kinetic modelling of quality deterioration in onions during drying and storage. Journal of Food Engineering, 68, 443±453. KILCAST D and SUBRAMANIAM P (2000). Introduction. In: The Stability and Shelf-Life of Food, D Kilcast and P Subramaniam (eds). Woodhead Publishing Limited, Cambridge, pp. 249±278. KOUTSOUMANIS K, TAOUKIS P S and NYCHAS G J E (2005). Development of a safety monitoring and assurance system for chilled food products, International Journal of Food Microbiology, 100, 253±260. KROKIDA M K, MAROULIS Z B and SARAVACOS G D (2001). The effect of the method of drying on the colour of dehydrated products. International Journal of Food Science and Technology, 36, 53±59. KUMAR P and MISHRA H N (2004). Storage stability of mango soy fortified yogurt powder in two different packaging materials, HDPP and ALP. Journal of Food Engineering, 65, 569±576. LABUZA T P (1973). Effects of dehydration and storage. Food Technology, 27, 20±26, 51. LABUZA T P (1982). Open Shelf Life Dating of Foods. Food and Nutrition Press Inc., Westport, CT. LABUZA T P and SALTMARCH M (1981). The nonenzymatic browning reaction as affected by water in foods. In: Water Activity: Influences on Food Quality, L B Rockland and G F Stewart (eds). Academic Press, New York, pp. 605±650. LABUZA T P and SCHMIDL M K (1985). Accelerated shelf life testing of foods. Food Technol. 39, 57±64. LANG W (2007). A computationally efficient method for nonlinear mixed-effects models with nonignorable missing data in time-varying covariates. Computational Statistics & Data Analysis, 51 (5), 2410±2419. LEE Y C, KIRK J R, BEDFORD C L and HELDMAN D R (1977). Kinetics and computer simulation of ascorbic acid stability of tomato juice as functions of temperature, pH and metal catalyst. Journal of Food Science, 42, 640±644, 648. LEMOS M A, OLIVEIRA J C, VAN LOEY A and HENDRICKX M E (1999). Influence of pH and high pressure on thermal inactivation kinetics of horseradish peroxidase. Food Biotechnology, 13, 13±32. MACHADO M F, OLIVEIRA F A R, GEKAS V and SINGH R P (1999). Kinetics of moisture uptake and soluble-solids loss by puffed breakfast cereals immersed in water. International Journal of Food Science and Technology, 33, 225±237. MAHAJAN P V, OLIVEIRA F A R and MACEDO I (2008). Effect of temperature and humidity on the transpiration rate of the whole mushrooms. Journal of Food Engineering, 84 (2), 281±288. MOHAPATRA D, FRIAS J M, OLIVEIRA F A R, BIRA Z M and KERRY J (2008). Development and validation of a model to predict enzymatic activity during storage of cultivated mushrooms (Agaricus bisporus spp.). Journal of Food Engineering, 86 (1), 39±48. MUTHUKUMARAPPAN K and GUNASEKARAN S (1996). Finite element simulation of corn moisture adsorption. Transactions of the ASAE, 39, 2217±2222. NELSON W (1969). Hazard plotting for incomplete failure data. Journal of Quality Technology, 1, 27±30. JOHNSON P N T

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(1946). The kinetics of package life. III. Isotherm. Journal of the Society of Chemical Industry, 65, 419±421. PFOST H B, MAURER S G, CHUNG D S and MILLIKEN G A (1976). Summarizing and reporting equilibrium moisture data for grains. Transactions of the American Society of Agricultural Engineers, 76, 3520±3532. OSWIN C R

PRACHAYAWARAKORN S, SAWANGDUANPEN S, SAYNAMPHEUNG S, POOLPATARACHEWIN T,

SOPONRONNARIT S and NATHAKARAKULE A (2004). Kinetics of colour change during storage of dried garlic slices as affected by relative humidity and temperature. Journal of Food Engineering, 62, 1±7. RAPUSAS R S and DRISCOLL R H (1995). Kinetics of non-enzymatic browning in onion slices during isothermal heating. Journal of Food Engineering, 24, 417±429. SAGUY I and KAREL M (1980). Modelling of quality deterioration during food processing and storage. Food Technology, 37, 78±85. SAPRU V and LABUZA T P (1996). Moisture transfer simulation in packaged cereal-fruit systems. Journal of Food Engineering, 27, 45±61. SINGH R P (1994). Scientific principles of shelf life evaluation, In: Shelf Life Evaluation of Foods, C M D Man and J A Jones (eds). Blackie Academic and Professional, London, pp. 3±36. SINGH R P, KIRK J and HELDMAN D R (1976). Kinetics of quality degradation: ascorbic acid oxidation in infant formula. Journal of Food Science, 41, 304±308. SMITH S E (1947). The sorption of water vapour by high polymers. Journal of the American Chemical Society, 69, 646±651. SOPONRONNARIT S, SRISUBATI N and YOOVIDHYA T (1998). Effect of temperature and relative humidity on yellowing rate of paddy. Journal of Stored Products Research, 34, 323±330. Â NDEZ C (2007). Effect of processing on the SOUSA M B, CANET W, ALVAREZ M D and FERNA texture and sensory attributes of raspberry (cv. Heritage) and blackberry (cv. Thornfree). Journal of Food Engineering, 78, 9±21. STEWART C M, COLE M B and SCHAFFNER D W (2003). Managing the risk of staphylococcal food poisoning from cream-filled baked goods to meet a food safety objective. Journal of Food Protection, 66, 1310±1325. TAOUKIS P S, LABUZA T P and SAGUY I S (1997). Kinetics of food deterioration and shelf life prediction. In: Handbook of Food Engineering Practice, K J Valentas, E Rotstein and R P Singh (eds). CRC Press, Boca Raton, FL, pp. 361±403. THIEMIG F, BUHR H and WOLF G (1998). Characterization of shelf life and spoilage of fresh foods. First results with the Weibull hazard analysis. Fleischwirtschaft, 78, 152± 155. THOMPSON T L, PEART R M and FOSTER G H (1968). Mathematical simulation of corn drying: a new model. Transactions of the American Society of Agricultural Engineers, 11, 582±586. VAN BOEKEL M A J S (1996). Statistical aspects of kinetic modelling for food science problems. Journal of Food Science, 61, 477±485. VAN DEN BERG C and BRUIN S (1981). Water activity and its estimation in food systems: theoretical aspects. In: Water Activity: Influences on Food Quality, L B Rockland and G F Stewart (eds). Academic Press, New York, pp. 1±61. WEISSER H (1986). Influence of temperature on sorption isotherms. In: Food Engineering and Process Applications, vol. 1, M Le Maguer and P Jelen (eds). Elsevier, New York, pp. 189±200. WONG M and STANTON D W (1992). Effect of removal of amino acids and phenolic

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compounds on non-enzymatic browning in stored kiwi fruit juice concentrates. Lebensmittel-Wissenschaft und -Technologie, 26, 138±144. YAN Z, SOUSA-GALLAGHER M J and OLIVEIRA F A R (2008a). Identification of critical quality parameters and optimal environment conditions of dried banana during storage. Journal of Food Engineering, 85, 168±172. YAN Z, SOUSA-GALLAGHER M J and OLIVEIRA F A R (2008b). Mathematical modelling of the kinetic of quality deterioration of intermediate moisture content banana during storage Journal of Food Engineering, 84, 359±367.

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15 Accelerated shelf life testing of foods S. Mizrahi, Technion-Israel Institute of Technology, Israel

Abstract: The food industry has a great need to obtain, in a relatively short time, the necessary information for determining the shelf life of its products. The chapter reviews the approaches available for running accelerated shelf life tests. The scientific basis behind each of these approaches is discussed as well as the problems and challenges that are involved. The chapter reviews methods that are based on the traditional linear kinetic models as well as on the recently emerging ones that are derived from non-linear ones. Key words: accelerated shelf life tests, non-linear kinetic models, kinetic model approach, dynamic shelf life testing. Note: This chapter is a revised and updated version of Chapter 5 `Accelerated shelf life tests' by S. Mizrahi in The Stability and Shelf-life of Food, ed. D. Kilcast and P. Subramaniam, Woodhead Publishing Limited, 2000, ISBN: 978-1-85573-500-2.

15.1 Introduction The food industry has a great need to obtain, in a relatively short time, the necessary information for determining the shelf life of its products. It has a very important impact on handling of the products' storage, distribution and shelf life dating.1 Moreover, it provides an essential tool to probe the possibilities of extending shelf life through proper product formulation and processing techniques. For practical reasons, especially when the actual storage time is long, the industry resorts to accelerated test techniques that considerably shorten the process of obtaining the necessary experimental data. In the context of this chapter, therefore, accelerated shelf life testing (ASLT) will refer to any method that is capable of evaluating product stability, based on data that are

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obtained in a significantly shorter period than the actual shelf life of the product. This chapter will discuss first the scientific basis of accelerated shelf life testing. It will indicate what tools are available for carrying out the tests and explain the problems encountered when using them. At the end, an attempt is made to suggest where this important area of accelerated shelf life testing is heading and what expectations one should have with regard to developing novel practical and reliable tools that the industry will find convenient to use.

15.2

Basic principles

ASLT is applicable to any deterioration process that can be quantitatively expressed by a valid model. This model may follow the changes in a shelf life expressing the value of a marker of deterioration or the extent of product failure under a given storage and handling history. The deterioration processes may be chemical, physical, biochemical or microbial. The principles of the ASLT will be the same in all cases. However, a larger range of different ASLT approaches are available for chemical deterioration of foods and therefore the examples in this chapter will be based on them. The following sections will discuss these approaches, all of which have a common goal of getting reliable deterioration data in a short period and selecting the proper model to use for predicting the shelf life of the product. In addition, cases of ASLT that have no need for a model will also be discussed.

15.3

Initial rate approach

Conceptually, one of the simplest techniques for obtaining useful data in a relatively short time for predicting shelf life is the `initial rate approach'.2 It may be applicable to cases where there is a shelf life determining deterioration marker that can be accurately monitored at levels well below failure. Such an approach may require an extremely accurate and sensitive analytical method. This method should be capable of measuring minute changes in the extent of deterioration after a relatively short storage time at actual conditions. The data of the initial rate of the deterioration process can serve to evaluate the parameters of a valid quantitative model. If a conventional kinetic model is used, the most important parameters to evaluate are the order of reaction (n) and the kinetic constant (K). In the case of monitoring the changes in the concentration (C) of a deterioration marker, the kinetic equation may be expressed as: dC 15:1 ˆ KC n dt where t is time. For sake of simplicity, let us define an index of deterioration (D) that has the form:

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dC ˆ K dt Cn

15:2

By doing that, the index of deterioration will be always linear with time and will have the following form: D ÿ D0 ˆ Kt

15:3

where D0 is the initial level of the index of deterioration. Equation 15.3, if valid, is the only kinetic model that is required to employ this approach to ASLT and the extrapolation process, after evaluating the value of K from the initial rate, is obviously very simple. The product shelf life (ts ) is therefore: D ÿ D0 15:4 ts ˆ K Fortunately, information about the order of reactions in many food systems is available in the literature. Many of the chemical deterioration reactions in foods follow either a zero- or a first-order kinetics. The value of the index of deterioration will be in these cases: · Zero order (n ˆ 0) D ˆ C · First order (n ˆ 1) D ˆ ln C

15.5 15.6

On a time scale it is translated to a linear or semi-logarithmic relationship, respectively (Fig. 15.1). When the order of reaction is unknown, a simple accelerated test procedure may be used to evaluate it empirically. In that case the simplest version of the kinetic model approach, which is discussed in the following sections, may be used. Such a method uses any convenient kinetically active factor to accelerate the deterioration process. The initial rate method, when applicable, can provide practically an ideal accelerated shelf life testing technique. It has the advantage of obtaining, in a relatively short time, the kinetic data at the actual storage conditions.

Fig. 15.1 Extent of deterioration as a function of time for zero- and first-order kinetics.

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An example of using a relatively sensitive analytical method was attempted by Teixeira Neto et al. to determine the rate of oxygen uptake during oxidation of dehydrated foods.3 The commonly used manometric techniques are notorious for being insensitive to minute changes in the relatively large mass of oxygen in the headspace.4 To overcome this problem, Teixera Neto et al.3 determined the rate of oxygen uptake by analyzing the changes in the mass of the oxygen, which was adsorbed or entrapped in the product.5 Since that mass is relatively much smaller than that of the headspace, the data of the rate of oxygen uptake by the product were obtained in only a few days. The discussion of the initial rate approach may serve also as an appropriate reminder as to why there is a need to have other accelerated shelf life testing methods for food systems having a shelf life determining marker. In the absence of a very sensitive and accurate analytical technique, the deterioration process should be allowed to progress for a longer time to enable the available method to detect the changes in a statistically significant way. The minimal time required to obtain significant data is therefore dependent on the accuracy and sensitivity of the analytical method; the worse they are the longer the time needed to obtain the data. In a way, accelerated shelf life testing is required to overcome the shortcomings of the analytical methods that are used by the industry. Therefore, the selection of the proper analytical techniques for monitoring the deterioration process is of great importance to shorten the period of the ASLT.

15.4

Kinetic model approach

The kinetic model approach is the most common method for accelerated shelf life testing. The basic process involves the following steps: · Selection of the desired kinetically active factors for acceleration of the deterioration process. · Running a kinetic study of the deterioration process at such levels of the accelerating factors that the rate of deterioration is fast enough. · By evaluating the parameters of the kinetic model, extrapolating the data to normal storage conditions (Fig. 15.2). · Use the extrapolated data or the kinetic model to predict shelf life at actual storage conditions. The absolute requirement for using this procedure is to have a valid kinetic model for the deterioration process. The general and most comprehensive kinetic model for chemical reactions in foods includes all the factors that may affect their rate. These factors may be divided into two main groups, namely compositional (CFi) and environmental factors (EFj).6 The model may be generally expressed as follows: dD 15:7 ˆ K…CFi ; EFj † dt

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Fig. 15.2

Schematic diagram of data extrapolation in accelerated shelf life testing.

This equation indicates that the kinetic constant K is a function of these factors. In practice, however, one does not need a comprehensive kinetic model. For prediction of shelf life at actual storage conditions, the model should include only those factors that change during storage (SFi). Therefore, the required model should only be as follows: dD 15:8 ˆ K…SFi † dt The list of SFi should include factors such as temperature, moisture content, light intensity, composition and others, but only if they change during storage. Obviously, when one is interested in predicting the shelf life of a product at a constant temperature, it is of no interest to have a kinetic model that includes this factor. Yet, temperature can be used very effectively to accelerate the rate of the deterioration process. Therefore, the demands from a kinetic model for ASLT may be different from one that is used only to predict shelf life. The model for accelerated shelf life testing should contain two groups of factors. The first comprises those that are changing during storage (SFi), as is in Eq. 15.8, and the second those that are used to accelerate the rate of reaction (AFj). The kinetic model for ASLT therefore has the form: dD ˆ K…SFi ; AFj † 15:9 dt The kinetic model for accelerated shelf life testing may therefore be different

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from the one usually used to predict product stability at normal storage conditions. Obviously, any of the factors that are changing during storage may be used to accelerate the rate of reaction. Equation 15.9 expresses a concept of great practical importance for ASLT. It indicates that it is possible to use any desired factor to accelerate the process of deterioration regardless of whether it is active during normal storage conditions. Weissman et al.7 have suggested that one might even use compositional factors to accelerate the rate of deterioration. Corradini and Peleg8 have suggested reducing the salt concentration in order to accelerate bacterial growth. This implies that the composition of a product may be altered just for the benefit of accelerating the deterioration rate. Clearly, the information obtained is useful only if a valid kinetic model is available for these compositional factors. Such a concept can open a large number of creative avenues for conducting accelerated shelf life testing.

15.5

Single accelerating factor

The simplest and most commonly used method of ASLT is based on employing only a single factor, mostly temperature, to expedite the deterioration process. The simplicity of such a method is related to both the experimental procedure and the availability of valid models. It should be emphasized that in ASLT, the validity of the kinetic model is crucial to obtaining accurate prediction of shelf life. Unfortunately, the validity of the model cannot be fully verified by the ASLT procedure, because the levels used for the accelerating factor do not include those of actual storage conditions. This is in contrast to the situation where the quantitative model is established and verified for actual storage conditions. Therefore, it is of great advantage if the selection of a model for ASLT is based on prior knowledge of its validity. The following sections will discuss the pros and cons of using temperature as a single accelerating factor and of the available models. 15.5.1 Arrhenius model The Arrhenius model that relates the rate of a chemical reaction to the changes in temperature is the best example of what is believed to be a generally accepted model with experimentally proven validity. It is a linear model expressing the effect of temperature on the rate constant (K) of different reactions in many food systems, represented by:   Ea 15:10 K ˆ K0 exp ÿ RT where K0 is a constant, Ea the energy of activation, R the gas constant and T the absolute temperature. The Arrhenius model requires the evaluation of two parameters only, K0 and Ea, that are supposed to be temperature independent.

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Therefore, it is very convenient that these parameters can be accurately evaluated by accelerated tests at high temperatures. Moreover, since this model has been applied to many cases, a large database is available, mainly of the energy of activation of different reactions. One may conveniently use this information to get a reasonable estimate of the extent a change in temperature may affect the rate of reaction. To simplify the process further, one may avoid the need to evaluate K0 by using a ratio between the rates of reaction when the temperature is changed by any arbitrary value. The most commonly used value is 10 ëC and therefore the ratio between the rate of reactions is known as Q10. The value of Q10 may be calculated by using Eq. 15.8 to express the rate of reaction first for a temperature of (T ‡ 10) and then for T and divide the two, namely:   Ea dD2 exp   10Ea R…T ‡ 10† dt   15:11 ˆ exp ˆ Q10 ˆ dD1 Ea RT…T ‡ 10† exp dt RT The simplicity of using Q10 has made it a very popular method for estimating shelf life. If prior knowledge or estimates of the value of the energy of activation are relied on, the accelerated tests may be run only at one elevated temperature. When choosing the maximal possible temperature, for which the Arrhenius model is still valid, the data are obtained in the shortest possible time by minimal experimental efforts. To improve the accuracy of this version of tests further, the energy of activation may also be evaluated. In that case, the rate of reaction must be obtained at a number of different temperatures below the maximal one in order to be within the range where the model is valid. Obviously, such a procedure takes a much longer time to run. The rule in accelerated stability tests is that to get more accurate data requires a longer experimental time. The use of the Arrhenius model, as will be discussed later, is questionable when changes in the mechanism of reaction take place due to phase transition and competitive reactions. However, even if it is valid, its use, or rather any approach that is based on a single accelerating factor, may be problematic with regard to the accuracy of the extrapolated data. To demonstrate that problem, let us consider first a simple case where the kinetic constant of the reaction is linearly related to the accelerating factor (Fig. 15.3). In this figure, the solid line represents the true relationship between the kinetic constant (y) and the accelerating factor (x). The point at the top end of the line represents the true kinetic constant (Ye) at the level (Xe), which may be estimated from the experimental data. To extrapolate the data, the slope (a) of the line must be evaluated by curve fitting of the accelerated test's kinetic data. That value of the slope is used to extrapolate the line to actual storage conditions (Xs) where the true rate of reaction is supposed to be (Ys). However, the error in the slope (
a) may cause the extrapolated line to produce a predicted kinetic constant (Yp

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Fig. 15.3 Analysis of extrapolation error in linear plot.

(high) or Yp (low)) which deviates from that true value (Ys) by
Y (Fig. 15.3). For the line that has a slope of …a ÿ
a†, which is symmetrical to the one with a slope of …a ÿ
a†, the following expression should hold: Ye ÿ Yp … high† Ye ÿ …Ys ‡
Y † ˆ ˆ a ÿ
a Xe ÿ X s X e ÿ Xs For the true line: Ye ÿ Ys ˆa Xe ÿ X s

15:12

15:13

Subtracting Eq. 15.13 from Eq. 15.12 one obtains:
Y ˆ
a X e ÿ Xs

15:14

To find how the error in evaluating slope (a) affects the accuracy of the extrapolated value, one should divide Eq. 15.14 by Eq. 15.13, resulting in the following expression:
a
Y
Y ˆ ˆ a Ye ÿ Ys Ys …YYe ÿ 1† s Therefore, the error in the extrapolated value is:  
Y
a Ye ˆ ÿ1 Ys a Ys

15:15

15:16

Let us define the acceleration ratio (AR) as the rate of the accelerated reaction in reference to that at normal storage conditions. In the case of the linear

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relationship between the kinetic constant and the accelerating factor, the value of that acceleration ratio is expressed as: Ye 15:17 AR ˆ Ys Therefore, the relative error of the predicted value of the kinetic constant is:
Y
a ˆ …AR ÿ 1† Ys a

15:18

The extrapolation process multiplies the experimental error of evaluating the slope of the line by the acceleration ratio minus one. The error of the predicted kinetic constant may be extremely high, especially when a very high acceleration ratio is used and if special care is not taken to reduce the experimental error to a very low value (Fig. 15.4). The magnitude of the error changes when the relationship between the kinetic constant and the accelerating factor is no longer linear. For example, when that relationship is exponential (Arrhenius model) or a power law, the extrapolation error may be different and it can be estimated by turning these models into their linear form and then using the above equations. The only necessary step is to assign the y-axis the value of lnK. In such a case, Eq. 15.18 will read:  
ln K ln Kp ÿ ln Ks ln …Kp =Ks †
a ln Ke ˆ ˆ ˆ ÿ1 15:19 ln Ks ln Ks ln Ks a ln Ks Therefore: ln

  Kp
a
a Ke
a ˆ ˆ …ln Ke ÿ ln Ks † ˆ ln ln AR Ks Ks a a a

Fig. 15.4 Error in linear extrapolation.

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Fig. 15.5 Error in exponential or power law extrapolation.

That results in: Kp ˆ …AR†
a=a Ks

15:21

The error in the extrapolated data is: Kp ÿ Ks Ks …AR
a=a ÿ 1† ˆ ˆ AR
a=a ÿ 1 Ks Ks

15:22

It appears, therefore, that using a model like the Arrhenius equation involves a lower error in extrapolating data (Fig. 15.5) than in the case of a simple linear model (Fig. 15.4). 15.5.2 Non-linear kinetic models The popularity of using the Arrhenius model, especially when the order of reaction is known, has made it synonymous with ASLT and therefore temperature has been the major accelerating factor. The practical aspects and data interpretation of such tests have been recently reveiwed by Saguy and Peleg.9 Most of the reported ASLTs are based on this model.10±15 However, as indicated above, this model may not be valid especially when changes in the mechanism of reaction take place due to phase transition, competitive reactions, glass transition, chemical changes in the food, etc.16 Therefore, large experimental efforts and lengthy procedures are required mainly to validate the linear Arrhenius model. In such cases a recently proposed approach of using non-linear kinetic versatile models may become attractive. This approach, developed mainly at the University of Massachusetts by Peleg and colleagues, is based on

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empirical models that are relatively simple to handle and are remarkably capable of quantitatively expressing the progress of a wide range of deterioration processes including very complex ones.8,17,18 Moreover, their usage does not require any assumption or knowledge about the order of reaction or the nature of the mechanisms that control food spoilage. There are a number of empirical models of that kind that fit the data of the deterioration processes and thus may be considered as a possible basis for ASLT. The one that got most of the attention is the Weibullian distribution that in our context has the following form in its decay mode: C ˆ exp…ÿZt † 15:23 Dˆ C0 where Z and  are constants known as the `rate' and the shape parameters, respectively. The kinetics of first-order decay is a special case of Eq. 15.23 where the shape parameter  ˆ 1. In this case the rate parameter Z ˆ K. For exponential growth, the sign of the exponent is reversed. Equation 15.23 has two temperature dependent coefficients, which must be determined experimentally instead of one as in the Arrhenius model. Fortunately, in many cases, the shape parameter () is much less sensitive to temperature changes and therefore can be considered constant. The determination of the temperature dependence of Z, and wherever needed of  as well, may not require any additional ASLT experiments but only different mathematical treatment. This issue was discussed by Corradini and Peleg,8 who suggested a number of simple versatile secondary models for this purpose. One model, for example, which they used to fit the rate parameter (Z) vs temperature data is the log logistic equation: Z ˆ loge f1 ‡ exp‰B…T ÿ Tc †Šg

15:24

where B and Tc are constants. Sometimes, evaluating these two constants by regression is all that is required when the shape parameter () can be considered constant. However, if the shape parameter is temperature sensitive, its temperature dependence too ought to be expressed by an empirical secondary model, a power law type, for example. In view of the available information for ASLT tests based on temperature, the non-linear kinetic approach has the potential of becoming generally accepted for many deterioration processes. Its use may become more common, especially when the deviations from constant order kinetics are large and the Arrhenius model's validity might come into question. In such a case, validation of the model also requires carrying out experiments at temperatures close to actual storage conditions, thus requiring a lengthy procedure. So far, the single accelerating factor that was discussed was temperature. As already indicated above, any factor that affects the deterioration process may be used in ASLT but only if it has a valid model for data extrapolation. The nonlinear kinetic models apply also for other accelerating factors but need more work to establish their validity.

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493

Glass transition models

One of the most interesting approaches to kinetic studies and their use for ASLT is based on glass transition models, which were borrowed from polymer science. Clearly, this approach may be applicable only to products that are in the physical state for which such models are valid. These models, such as the Williams, Landel and Ferry (WLF) model, relate changes in the system properties, which are connected with the polymer molecular mobility, to the temperature within the range of the transition of the product from its glassy to rubbery state.19 Based on the assumption that the rate of the deterioration reactions should relate to molecular mobility in much the same way, this approach yielded valuable information about processes of recrystallization, and losses of flavor and desired textural attributes caused by such structural changes.20 When applicable, glass transition models offer a number of very attractive features with regard to kinetic studies and ASLT. The first one is the fact that it combines both the effects of the temperature and the moisture content into one relatively simple equation.21 The second one, which is even more interesting, is that the rate of the deterioration is related only to the physical state of the system, which can be independently determined in a very short time by readily available physical techniques. That considerably simplifies the experimental work since one needs only the kinetic data, at one high level of temperature or moisture content, and the physical characterization of the system. Unfortunately, that kind of interesting approach to ASLT has, so far, found very limited use. In general, the glass transition model was found to correspond closely to a stability limit with respect to physical processes, such as the ones mentioned above.22 On the other hand, the glass transition model proved inadequate to account for different deterioration kinetics.20,23±27 In general, the glass transition model failed to account for diffusion of some small molecules, especially water. However, it has been proposed that the glass transition model may be applicable to predict changes in the rate of chemical reactions in food deterioration but only if proven to be diffusion limited.

15.7

Multiple accelerating factors

The use of multiple accelerating factors presents an effective approach to obtain a high acceleration ratio of the deterioration reaction at a minimal cost of prediction error. To demonstrate this fact, let us consider a simple theoretical case of a kinetic model that has the following form: K ˆ …c1 F1 †…c2 F2 † ˆ c1 c2 F1 F2

15:25

where c1 and c2 are the estimated parameters of the accelerating factors F1 and F2 , respectively. In order to evaluate the error in the kinetic constant due to that of the estimated parameters, Eq. 15.25 is differentiated with regard to these parameters, resulting in:

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Food and beverage stability and shelf life dK ˆ c2 F1 F2 dc1 ‡ c1 F1 F2 dc2

15:26

When dividing Eq. 15.26 by Eq. 15.25 and combining it with Eq. 15.18, the estimated error is found from the following expression:
K
c1
c2 ‡ ˆ …AR1 ÿ 1†RE1 ‡ …AR2 ÿ 1†RE2 ˆ c1 c2 K

15:27

where RE1 and RE2 are the experimental relative errors for the factors F1 and F2 , respectively. By using multiple factors, a 100-fold acceleration of the deterioration reaction, e.g. a single one may be replaced by two factors each having an acceleration ratio of only 10. This one order of magnitude reduction in the acceleration ratio decreases considerably the extrapolation error. If, for example, the error in estimating the model parameter for each of these factors is only 1%, the extrapolated data might deviate from the real value by 99% (Eq. 15.18) for a single as compared to 18% (Eq. 15.27) for two accelerating factors. While the total acceleration effect of using two or more factors is a multiplication of their effect, the error is only the summation. Moreover, the required relatively low acceleration ratio is achieved by a much smaller change in the level of the kinetic factors and thus the system stays much closer to the actual storage conditions. Furthermore, when a narrower range of the accelerating factor is used, not only is the validity of the kinetic model better maintained but also the kinetic model may have a simpler form. The advantages of the multiple factors approach are obtained at a cost of running a more complicated experimental procedure. That is the result of the need to evaluate not only the effect of each factor on the reaction kinetics but also a possible interaction between them. The procedure, therefore, lacks the simplicity that makes such a technique more practical for the food industry. A multiple factor acceleration of the deterioration reaction was carried out by Mizrahi et al. by combining the effect of temperature and moisture content (m).10 It enabled a shelf life that lasts for over one year to be predicted based on an experimental study that required only 10 days. The basic kinetic equation had the following general form: K…m; T† ˆ f …m†Tr exp ‰Ea =R…1=Tr ÿ 1=T†Š

15:28

where Tr is a reference temperature. Since moisture content in a food product is related to the water activity (aw) by the sorption isotherm, the kinetic function at the constant reference temperature ( f …m†Tr ) could be expressed also in terms of that water activity. One form of such a function for non-enzymatic browning of cabbage is:10 K ˆ K0 …aw †s

15:29

The kinetic model shown in Eq. 15.28 indicates that the evaluation of the kinetic effect of moisture content is performed for a constant reference temperature (Tr). Theoretically, therefore, the evaluation of the kinetic model may be as simple as first running an experiment at an elevated constant temperature and changing only

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the moisture content and then keeping the latter constant at any desired level and varying the temperature. In many cases, especially when the range of temperature and moisture content changes are kept within a relatively narrow range, that procedure may be adequate. However, when that range is relatively large, a possible interaction between the two factors might play an important role in determining the accuracy of the shelf life prediction. Such was the case in the study of the non-enzymatic browning of cabbage where the energy of activation happened to be affected by the moisture content.10 The empirical expression that was used to describe the effect of the moisture content on the energy of activation was: Ea ˆ c1 exp …ÿc2 m†

15:30

where c1 and c2 are constants. That interaction between the factors greatly complicates the experimental procedure since the effect of the moisture content on the energy of activation should be tested by changing both factors at the same time. That requires a much longer time and more experimental work, which may make this method very unattractive for practical use. However, as stated before, when a narrower range of accelerating factors is used, that elaborate and cumbersome procedure may not be necessary. Another example of using two factors for accelerating the deterioration process could have been based on the data of Dattatreya et al.28 that quantitatively evaluated how pH and temperature affect the rate of browning of sweet whey powder (SWP). Their data enabled an ASLT procedure to be devised where very high acceleration ratio could be obtained by acidifying this product and exposing it to elevetaed temperatures. In this case too, the Arrhenius model may be used for expressing the effect of temperature on the rate of reaction. Other empirical equations are used for the effect of pH. In a similar way to the former case where temperature and moisture content were combined to further accelerate the deterioration process, in this case too the Arrhenius model must be modified in order to account for the effect of the pH on the value of the energy of activation. But again, this multiple-factors ASLT method facilitates changing them only within a relatively narrow range in which the Arrhenius model is practically valid. The above discussion indicates that when using multiple accelerating factors, their interaction is complicating the deterioration models. In fact, one has to use mostly empirical models that are derived by curve fitting of data that are relevant to a specific case. Moreover, in order to establish their validity, the experimental conditions should include actual storage conditions. This requires a long experimental time that makes it impractical as an ASLT method. The same problem exists when using non-linear kinetic models.8 In this approach, too, the parameters of the empirical models should be expressed as a function of the accelerating factors. So far there are no such models that proved to be universal. Until this situation changes, the non-linear approach, therefore, does not look attractive when considering ASLT by multiple accelerating factors. So far, the practical use of multiple accelarating factors seems to be limited only to cases having well-established valid models.

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15.8

Food and beverage stability and shelf life

Dynamic methods

In many ways the simplest method of accelerating the rate of reaction is by placing the product at elevated constant temperatures. Data fitting establishes the parameters of the kinetic model which in turn helps in estimating the shelf life at storage conditions. More explicitly, the latter means storage at constant temperature. Based on the evaluated model, prediction of shelf life in a dynamic situation where the temperature is changing during handling and storage, may be inaccurate in cases where history effects exist. Quast and Karel29 found such an effect in oxidation of potato chips. Similarly, Labuza and Ragnarsson30 reported a significant history effect in lipid oxidation when transfering samples from one temperature to another. This, in turn, casts doubts about using Arrhenius or any other model for dynamically changing temperatures. Therefore, one must consider the possibility that the mode of changing the storage conditions might have an extra effect on the extent of deterioration. Regular kinetic models do not account for such extra effects. Therefore, for predicting shelf life under dynamic storage conditions one has not only to establish a kinetic model but also to determine if there might be a history effect and how it might be accounted for. In cases where the kinetic experiments are carried out at constant levels of the accelerating factor, for example temperature, one must include a step where samples are transferred from one temperature to another and monitoring whether their kinetics are the same as those of the samples that are kept all the time at that constant condition. Another way of establishing the existence of history effects may be by dynamic testing as will be discussed later in this section. For sake of convenience, the following discussion will use temperature as the main example of the kinetic factor in dynamic testing. The common term for such procedures is non-isothermal testing.8,31±40 Before getting into the discussion about dynamic testing, it may be helpful to consider first some of the pros and cons of such methods compared to the ones that are using constant conditions. When using constant temperature, for example, the effect of the come up and cooling time is assumed to be negligible due to slow kinetics. However, when the kinetics is very fast, one faces an experimental problem for which dynamic testing presents a good way to overcome such a problem. On the other hand, constant temperatures are much easier to maintain. One way, therefore, to improve the accuracy of the dynamic non-isothermal testing is to change the temperature in steps.39 Another advantage of dynamic testing is when it is possible to continously monitor the extent of deterioration. In such a case, one needs a much smaller number of samples as compared to isothermal tests where samples are withdrawn periodically for analysis. When dynamic testing is used as an ASLT procedure, shortening of the experimental time simply means that samples are not allowed to stay at the lower range of temperature for long enough to validate the model. Most of the significant kinetic data are obtained from the higher range of temperatures. In dynamic testing, the product is subjected to conditions where the kinetically active factor is programmed to change with time in any desired way.

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Fig. 15.6 Schematic diagram of dynamic testing of deterioration processes.

That creates a situation where both the extent of deterioration and the value of the kinetic factor are changing with time (Fig. 15.6). At any given time, namely at a given level of the kinetic factor, the rate of reaction can be obtained by a numerical or graphical derivative of the deterioration curve. When running a non-isothermal ASLT procedure and following the extent of deterioration, the rate of reaction is the slope of the curve of the extent of deterioration at a momentary value of temperature and time. The obtained data may be fitted with models that have been established or believed to be valid for the deterioration processes of the tested product. In order to test for history effect, one has to run another dynamic experiment having a different pattern of how the kinetically active factor is programmed and checking for a discrepancy between the calculated results and the actual ones. Another important way to establish the deterioration model and evaluate its parameters is to express the temperature history and the kinetics in a single rate equation. In cases where the Arrhenius model is valid, its coefficients K0 and Ea can be evaluated by one non-isothermal procedure. This is because the rate of reaction is dependent only on temperature. In case of the non-linear kinetic model, the rate of reaction is dependent also on time. That requires a different data analysis approach. In this case too the temperature history and the kinetics are expressed in a single rate equation. Solving this equation will result in an expression relating the extent of deterioration as a function of the model parameters that need evaluation. The technique was described by Corradini et al.41,42 In their case, the combined equation contained three adjustable parameters. Therefore, they had to have the results of four tests having four different dynamic temperature histories. They used the results of three experiments to create three equations with the three deterioration parameters (B, Tc and ) as the three unknown. By solving these three equations, the model parameters were determined. The model validity was thereafter tested by comparing the curve

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generated with these parameters inserted into the model equation with the actual data from the fourth experiment. Non-isothermal procedures, as well as dynamic moisture content tests have been reported in the food and in the pharmaceutical related literatures.1,8,31±41 A combination of non-isothermal tests and compressed oxygen has been reported for products that are susceptible to oxidation.39 A combination of dynamic tests involving temperature and moisture content have been succesfully used for accelerating the procedure for kinetic model evaluation.43±45

15.9

The `no model' approach

The `no model' approach is a term used for the accelerated shelf life testing method that assumes that a valid kinetic model exists but does not require experiments to evaluate it. This approach, which is a sort of dynamic test, may apply only to cases where the kinetically active factor (F) is changing during storage in a monotonically, continuous way. The ASLT technique is based on monitoring the extent of deterioration in the same product in which that factor is programmed to change in such a way that it goes through the `storage' cycle in a shorter period. The obtained data are then converted into real storage conditions by a calculation that is based only on knowing how the kinetically active factor (F) is changing with time (t), namely on having the following function (g): F ˆ g…t†

15:31

The inverse of that equation yields the function (f) of how time relates to the changing factor: t ˆ f …F†

15:32

It should be noted that this equation might have an analytical expression, but may as well represent a numerical or graphical datum. Assuming that a valid kinetic model exists for the deterioration reaction, it will have the following form: dD ˆ K…F†dt

15:33

The value of dt may be replaced in this equation by using the derivative of Eq. 15.32, namely: dt ˆ f 0 …F†dF

15:34

Thus Eq. 15.33 changes into: dD ˆ K…F† f 0 …K†dF

15:35

When we have two samples of the same product, one at actual storage conditions and the other at accelerated test conditions (denoted by subscript s and a, respectively), the ratio between their rate of deterioration is:

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Accelerated shelf life testing of foods …dD†s …K…F† f 0 …F†dF†s ˆ …dD†a …K…F† f 0 …F†dF†a

499 15:36

Thus, the rate of deterioration at actual storage conditions is related to that at accelerated ones by: …dD†s ˆ

…K…F† f 0 …F†dF†s …dD†a …K…F† f 0 …F†dF†a

15:37

Let us consider first a situation where the kinetic factor (F) is changing linearly with time both in storage and accelerated test conditions, thus having the following respective expressions: F ˆ F 0 ‡ bs t

15:38

F ˆ F0 ‡ ba t

15:39

where b is a constant. Using the inverse form of these equations, the ratio of their derivative is: fs0 …F† ba ˆ fa0 …F† bs

15:40

Therefore, the ratio between the extent of deterioration in this case is: R  F K…F†dF F0 ba b s …D ÿ D0 †a ˆ a …D ÿ D0 †a …D ÿ D0 †s ˆ  R F bs bs K…F†dF F0

15:41

a

Since both integrals in this equation are only functions of the factor F, they have the same value and therefore cancel out. The extent of deterioration at storage conditions is therefore obtained by accelerating the change in the kinetically active factor with time and multiplying the obtained data by the ratio of the rates of change. So far, this method is applicable only to cases where the kinetic factor is changing linearly with time. The application of this approach may be extended also to the general situation, which is expressed by Eq. 15.37. In that case, it is possible to divide the whole range of these equations into n sections, each of which may be approximated by a straight line with a slope, which can be calculated from the derivative of this equation. The basic equation in this case will be: …
Dj †s ˆ

fs0 …Fj †dF …bj †a …
Dj †a ˆ …
Dj †a 0 fa …Fj †dF …bj †s

The extent of deterioration is therefore: n n X X fs0 …Fj † …
Dj †a …
Dj †s ˆ …D ÿ D0 †s ˆ f 0 …Fj † jˆ1 jˆ1 a

15:42

15:43

This `no model' approach was developed and successfully tested for a moisture-sensitive dry product.46 The product was packaged in a water vapor

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permeable plastic film. Since the water activity in common storage conditions of such a product is higher than that of the packaged foods, the product will continuously absorb moisture through the film. The accelerated shelf life testing in this case was carried out by packing the same product in a film that has significantly higher water vapor permeability than the original one. In both the actual storage and the accelerated test conditions, the change in moisture content with time is not linear. In fact, the derivative of the relationship between time and moisture content for the samples that were kept at external constant water activity (ae) can be expressed:46 f 0 …m† ˆ ‰kP…ae ÿ h…m†Šÿ1

15:44

where h denotes a function of moisture content (m), k is a constant and P is the packaging film permeability to water vapor. If different films are used for storage and for accelerated tests having a permeability of Ps and Pa, respectively, then: fs0 …m† Pa ˆ fa0 …m† Ps

15:45

In that case the extent of deterioration is given by: Pa …D ÿ D0 †s ˆ …D ÿ D0 †a Ps

15:46

This is the same solution as the linear case owing to the fact that the external water activity is the same for storage and accelerated tests. Such an accelerated shelf life testing method is simple to perform, especially since it does not require the evaluation of the kinetic model. However, there is one important problem that should be considered. It has to do with the fact that the higher the rate that one programs the change of the kinetic factor, namely the moisture content in this example, the lower the extent of deterioration. That is simply the result of the fact that the deterioration reaction is given less time to develop. This approach is therefore more effective, the better the accuracy and sensitivity of the analytical method used to monitor the deterioration process. In any case, the acceleration ratio in this approach is very dependent on how small a fraction of the total acceptable extent of deterioration may be significantly determined.

15.10

Combination of approaches

The application of a combination of methods to accelerated shelf life testing has the same advantages as using multiple accelerating factors. Such a combination may provide an effective approach in obtaining a high acceleration ratio of the deterioration reaction at a minimal cost of prediction error by staying closer to actual storage conditions. Moreover, this approach provides potentially the largest number of avenues to ASLT. One may use a combination of multiple factors together with initial rate and `no model' approaches. Mizrahi and Karel

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have used a combination of the `no model' approach together with elevated temperature for accelerated stability tests of moisture-sensitive products.47 This combination presents an interesting case of how to link the effect of two methods where one requires evaluation of the kinetic model and the other one does not. The assumption was that the Arrhenius equation is a valid kinetic model for the rate of deterioration at different temperatures when the moisture content is kept constant. The procedure is based on packing the product in films of different permeability and placing them in an environment of the same, or different, water activity and elevated temperatures. The temperature changes not only the rate of reaction but also the moisture gain. Therefore, in order to evaluate the parameters of the Arrhenius equation one has to separate the two processes. The technique is based on the following steps:47 · Arbitrarily select a reference moisture gain curve. It may be, for example, the moisture gain of the product at actual storage conditions. For some cases, one may conveniently select a straight line. · At each temperature, transform the extent of deterioration to the reference moisture gain line by using the procedure outlined in the `no model' approach, namely by using Eq. 15.37 or 15.46 for the simple case where the ratio of the moisture gain is constant. · Use the transformed data, which are now normalized to the same reference line, to obtain the parameters of the Arrhenius equation. · Use the combination of the reference data and Arrhenius equation to extrapolate the data to actual storage conditions.

15.11

Problems in accelerated shelf life tests

The problems that are related to ASLT may be classified into three main groups. The first has to do with those cases where no valid kinetic model is believed to exist for any accelerating kinetic factor. No accelerated test procedure is available for such a case. The second kind of problem is encountered when a model does exist but it is very complicated and requires the evaluation of too large a number of parameters. The experimental procedure in such a case may prove very cumbersome to a point where the ASLT procedure may not be practical. The third group of problems relates to the application of valid ASLT methods. These problems are discussed in the following section. 15.11.1 Absence of a deterioration index Food products may be judged on the basis of sensory evaluation that is influenced by the combined effect of a multitude of different reactions. In many cases, a measurable deterioration index, which correlates well with the sensory evaluation, is unavailable. The product may therefore be judged only on the basis of being acceptable or unacceptable and not by a continuous measurable scale, thus eliminating the possibility of using the `initial rate', the `no model',

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or the `dynamic' approaches to accelerated stability tests. However, the kinetic model approach may be used in such cases simply by assigning the kinetic constant (K), at constant conditions, a value of: 15:47

K ˆ 1=tc

where tc is the critical time that marks the end of the shelf life of the product. This approach arbitrarily assigns the point of product failure a value of one. As in any other kinetic study, this kinetic constant is evaluated by an experimental procedure that is carried out at different constant storage conditions. The obtained data of the values of the kinetic constant as a function of these conditions provide the basis for evaluating the kinetic model and its parameters. That model can be used for predicting shelf life by integrating the kinetic equation and finding the time it takes to reach a degree of deterioration of one. This approach is exactly the same as the time±temperature tolerance (TTT) that has been extensively used to predict shelf life mainly in frozen products.48,49 15.11.2 Statistical problems Statistics is an essential part of designing the experimental procedures and analyzing the data both in common kinetic studies as well as in ASLT. Statistical methods have been critically evaluated, for example, for their use in data fitting of the Arhhenius model.50,51 In any case, it is essential that the proper statistical methods be used in ASLT. One particular subject in that respect, which relates to the validation of kinetic models, should be especially noted. The validity of the model is best established when kinetic data are available for both the actual storage and the accelerated test conditions. Obviously, the ASLT technique by itself lacks the capability of verifying the validity of the model, especially an empirical one, for actual storage. Moreover, when any model is used its parameters are evaluated only by using the data of the very high rate of reaction. That may produce a large deviation of the extrapolated data from normal conditions. One should therefore use statistical methods that test the sensitivity of the model by a cross-validation method. In principle, these methods use part of the data to verify the validity of the model. This requires a wider range of accelerated storage conditions. The closer they are to the actual storage conditions the better. Such an approach costs more both in time and in experimental effort.

15.12

Future trends

The subject of prime importance in ASLT and in the prediction of shelf life will continue to be the pursuit of simple-to-handle versatile kinetic models of product deterioration and establishing their validity. Such models are ideally expected to be a priori valid for any deterioration process, regardless of how complex it is, under any handling and storage conditions. In fact, this is what the non-linear

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kinetics approach claims to offer, as discussed earlier in this chapter. As already indicated, the non-linear kinetic models' approach is based on empirical equations that potentially cover a broad range of deterioration processes. The main difficulty with these models is that the resulting rate equation requires a numerical solution. This need not be a problem, though, because almost all modern mathematical software can handle such differential equations. Furthermore, there is a need now for secondary versatile models to correlate between the parameters of the nonlinear models and the accelerating factors. Therefore, it is reasonable to believe that the major thrust in the future will be in two areas. The first is to further establish the versatility of the non-linear kinetic models. The second area is to establish the validity and versatility of secondary equations preferably having a minimal number of constants. As already indicated, such work has been done with regard to temperature as the accelerating factor. In a similar way, it is expected that future research work will provide more information about the behavior of other accelerating factors that may be considered in ASLT. In future efforts to establish versatile secondary equations, one might expect also an attempt to reduce the number of parameters in the kinetic model. The best example so far is the shape parameter in the Weibullian model that shows little sensitivity to temperature changes. This greatly simplifies the deterioration rate model, which with a constant , has only two temperature-dependent terms that need to be expressed algebraically. A practical usage of non-linear models for ASLT and shelf life prediction must obviously be based first and foremost on the validity of the models. For cases where these models are proven valid, one should expect that future efforts will be dedicated also to making the non-linear kinetics much more popular. This may not be a simple task, especially when the curve fitting model combines both the primary and the secondary equations. It may be even more complex when using such models in dynamic ASLT procedures. The group of Peleg and his colleagues at the University of Massachusetts has been handling these problems using available mathematical software. It should be expected that their work and of other people will help in formulating experimental and data analysis ASLT procedures as well as in developing software that will make their use relatively simple.

15.13 1. 2.

References

Shelf-life Dating of Foods, Westport, CT, Food & Nutrition Press, 1982. Novel approaches to accelerated storage tests. In Engineering and Food, Vol 2: Preservation Processes and Related Techniques, Spiess W E L and Schubert H, eds, pp. 794±803, New York, Elsevier Applied Science, 1990. 3. TEIXEIRA NETO R O, KAREL M, SAGUY I and MIZRAHI S, `Oxygen uptake and 3-carotene decoloration in a dehydrated food model', J of Food Science, 1981 46 665±76. 4. QUAST D G and KAREL M, `Effects of environmental factors on the oxidation of potato chips', J of Food Science, 1972 37 584. LABUZA T P, MIZRAHI S,

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504 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.

19. 20. 21. 22. 23.

Food and beverage stability and shelf life SAGUY I, GOLDMAN M, HOREV B and KAREL M, `An improved method for the determination of adsorbed/entrapped gases in dehydrated foodstuffs', Z Lebensm Untess Forsch, 1983 177 359±63. SAGUY I and KAREL M, `Modeling of quality deterioration during food processing and storage', Food Technology, 1980 34 (2) 78±85. WEISSMAN I, RAMON O, KOPELMAN I J and MIZRAHI S, `A kinetic model for accelerated tests of Maillard browning in a liquid model system', J of Food Processing and Preservation, 1993 17 455±70. CORRADINI M G and PELEG M, `Shelf-life estimation from accelerated storage data', Trends in Food Science and Technology, 2007 18 37±47. SAGUY S and PELEG M, Accelerated and parallel storage in shelf life studies. In An Integrated Approach to New Food Product Development, Moskowitz H R, Saguy S and Straus T, eds, pp. 429±55, Boca Raton, FL, CRC Press/Taylor & Francis, 2009. MIZRAHI S, LABUZA T P and KAREL M, `Feasibility of accelerated tests for browning in dehydrated cabbage', J of Food Science, 1970 35 804±7. MIZRAHI S and KAREL M, `Accelerated stability tests of moisture sensitive products in permeable packages at high rates of moisture gain and elevated temperatures', J of Food Science, 1977 42 1575±9. LABUZA T P and RIBOH D, `Theory and application of Arrhenius kinetics to the prediction of nutrient losses in food', Food Technology, 1982 36 66±74. LABUZA T P and KAMMAN J, Reaction kinetics and accelerated tests simulation as a function of temperature. In Application of Computers in Food Research, Saguy I, ed., New York, Marcel Dekker, 1983. LABUZA T P and SCHMIDL M K, `Accelerated shelf-life testing of foods', Food Technology, 1988 39 (9) 57±62, 64. TSOUMBELI M N and LABUZA T P, `Accelerated kinetic study of aspartame degradation in the neutral pH range', J of Food Science, 1991 56 1671±5. NELSON K and LABUZA T P, `Water activity and food polymer science: implications of state on Arrhenius and WLF models in predicting shelf-life'. J of Food Engineering, 1994 22 271±90. PELEG M, ENGEL R, GONZALES-MARTINEZ C and CORRADINI M G, `Non-Arrhenius and non-WLF kinetics in food', J of the Science of Food and Agriculture, 2002 82 1346± 55. CORRADINI M G, NORMAND M D and PELEG M, Non linear growth and decay kinetics ± principles and potential food applications. In Food Engineering: Integrated Approaches, GutieÂrrez Lopez G F, Barbosa-CaÂnovas G V, Welti-Chanes J. and Parada Arias E, eds, pp. 47±71, New York, Springer, 2008. WILLIAMS M L, LANDEL R F and FERRY J D, `The temperature dependence of relaxation mechanisms in amorphous polymers and other glass-forming liquids', J of Chemical Engineering, 1955 77 3701±7. KAREL M, ANGLEA S, BUERA P, KARMAS R and LEVI G, `Stability related transitions of amorphous foods', Thermochimica ACTA, 1994 246 (2) 249±69. BUERA P and KAREL M, `Application of the WLF equation to describe the combined effect of moisture, temperature and physical changes on non-enzymatic browning rates in food systems', J of Food Processing and Preservation, 1993 17 31±47. KAREL M, Food research tasks at the beginning of the new millennium ± a personal vision. In Water Management in the Design and Distribution of Quality Foods, Roos Y H, Leslie R B and Lillford P J, eds, pp. 535±59, Lancaster, PA, Technomic, 1999. CHIRIFE J and BUERA P, `Water activity, glass transition and microbial stability in

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concentrated semimoist food systems', J of Food Science, 1994 59 921±7. BUERA M D P, CHIRIFE J and KAREL M, `A study of acid-catalyzed sucrose hydrolysis in an amorphous polymeric matrix at reduced moisture contents', Food Research International, 1995 28 (4) 359±65. KARMAS R and KAREL M, `Modeling Maillard browning in dehydrated food systems as a function of temperature, moisture content and glass transition temperature', ACS Symp Ser, 1995 610 64±73. CARDONA S, SCHEBOR C, BUERA M P, KAREL M and CHIRIFE J, `Thermal stability of invertase in reduced-moisture amorphous matrices in relation to glassy state and trehalose crystallization', J of Food Science, 1997 62 (1) 105±12. SCHEBOR C, BUERA M P, KAREL M and CHIRIFE J, `Color formation due to nonenzymatic browning in amorphous glassy anhydrous model systems', Food Chemistry, 1999 65 (4) 427±32. DATTATREYA A, ETZEL M R and RANKIN S A, `Kinetics of browning during accelerated storage of sweet whey powder and prediction of its shelf life', International Dairy Journal, 2007 17 177±82. QUAST D G and KAREL M, `Computer simulation of storage life of foods undergoing spoilage by two interacting mechanisms', J of Food Science, 1972 37 679±83. LABUZA T P and RAGNARSSON J O, `Kinetic history effect on lipid oxidation of methyl linoleate in model system', J of Food Science, 1985 50 (1) 145±7. LABUZA T P, `A theoretical comparison of losses in foods under fluctuating temperature sequences', J of Food Science, 1979 44 1162±8. LABUZA T P, BOHNSACK K and KIM M N, `Kinetic of protein quality loss stored under constant and square wave temperature distributions', Cereal Chemistry, 1982 59 142±8. RIBOH D K and LABUZA T P, `Kinetics of thiamine loss in pasta stored in a sine wave temperature condition', J of Food Processing and Preservation, 1982 6 (4) 253±64. TUCKER I G and OWEN W R, `High information kinetic studies: non-isothermal programmed acid concentration kinetics', International Journal of Pharmaceutics, 1982 10 323±37. ZHAN X, YIN G, WANG L and MA B, `Exponential heating in drug stability experiment and statistical evaluation of nonisothermal and isothermal prediction', J of Pharmaceutical Sciences, 1997 86 709±15. CORRADINI M G and PELEG M, `A model of non-isothermal degradation of nutrients, pigments and enzymes', J of the Science of Food and Agriculture, 2004 84 217±26. OLIVA A, LLABRES M and FARINA J B, `Data analysis of kinetic modeling used in drug stability studies: isothermal versus nonisothermal assays', Pharmaceutical Research, 2006 23 2595±602. ARANGUIZ M Y F, TORRE S and BERRAONDO M R, `A simulation study with statistical evaluation for the determination of non-isothermal kinetics conditions in drug stability', European Journal of Pharmaceutical Science, 2007 31 277±87. LIN B, ZHAN X C, LI L L, LI C R, QI H J and TAO J L, `Step nonisothermal method in kinetic studies of captopril oxidation under compressed oxygen', Yakugaku Zasshi, 2008 128 617±24. PELEG M, CORRADINI M G and NORMAND M D, `Isothermal and non-isothermal kinetic models of chemical processes in foods governed by compeing mechanisms', J Agricultural and Food Chemistry, 2009 57 7377±86. CORRADINI M G, NORMAND M D and PELEG M, `Prediction of an organism's inactivation pattern from three single survival ratios determined at the end of three non-isothemal

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Food and beverage stability and shelf life heat treatments', International Journal of Food Microbiology, 2008 126 98±111. CORRADINI M G, NORMAND M D, NEWCOMER C, SCHAFFNER D W and PELEG M, `Extracting survival parameters from isothermal, isobaric, and ``iso-concentration'' inactivation experiments by the ``3 end point method''', J of Food Science, 2009 74 R1±R11. SAGUY I, MIZRAHI S, VILLOTA R and KAREL M, `Accelerated method for determining the kinetic model of ascorbic acid loss during dehydration', J of Food Science, 1978 43 1861±4. HARALAMPU S G, SAGUY I and KAREL M, `Identification of moisture sensitivity models of packaged materials under simulated storage conditions', Mathematical Modelling, 1986 7 1±13. HARALAMPU S G, SAGUY I and KAREL M, `The performance of a dynamic stability test for moisture sensitivity', Mathematical Modelling, 1986 7 15±25. MIZRAHI S and KAREL M, `Accelerated stability tests of moisture-sensitive products in permeable packages by programming rate of moisture content increase', J of Food Science, 1977 42 958±63. MIZRAHI S and KAREL M, `Accelerated stability tests of moisture sensitive products in permeable packages at high rates of moisture gain and elevated temperatures', J of Food Science, 1977 42 1575±9. VAN ARSDEL W B, COPLEY M J and OLSON R L, Quality and Stability of Frozen Foods Time-Temperature Tolerance. New York, Wiley-Interscience, 1969. JUL M, The Quality of Frozen Foods, London, Academic Press, 1984. COHEN E and SAGUY I, `Statistical evaluation of Arrhenius model and its applicability in prediction of food quality losses', J of Food Processing and Preservation, 1985 9 273±90. HARALAMPU S G, SAGUY I and KAREL M, `Estimation of Arrhenius model parameters using three least squares method', J of Food Processing and Preservation, 1985 9 129±43.

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16 Microbiological challenge testing of foods E. Komitopoulou, Leatherhead Food Research, UK

Abstract: The chapter discusses the basic principles of microbiological challenge testing and provides some useful tips for the effective design and application of challenge testing protocols for the assessment of food safety, quality and stability. Differences between shelf life and challenge testing are highlighted. Specific advantages and limitations of challenge testing are discussed with emphasis on the use of the results in the production of microbiological predictive models. Key words: shelf life, challenge testing, predictive models, food safety, food quality.

16.1 Introduction: role of challenge testing in shelf life evaluation According to Notermans et al. (1993), microbiological challenge testing is an important tool used to: · determine the ability of the food matrix to support, or not, microbial growth or survival, i.e., to determine its safety and stability during storage until consumption, · establish the product's shelf life, · aid in product formulation in terms of intrinsic control factors (e.g. pH and water activity), and · establish critical points in a processing line. There is often confusion around the applicability of shelf life analysis versus that of microbiological challenge testing. In shelf life analysis, the product is

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stored under the normal conditions and analyzed over time to ensure that it is safe and stable. This approach assumes good manufacturing conditions under a HACCP plan which would limit the chances of micro-organisms, other than the normal background flora of the product (not pathogens), contaminating the product. Therefore, in shelf life trials, one assumes that analysis will target the naturally present spoilage micro-flora growing during storage under stipulated conditions. On the other hand, challenge testing is designed to answer the question of whether the product could be safe and stable if accidentally contaminated with pathogenic or spoilage micro-organisms, i.e., whether a specific product formulation would favor or inhibit their growth. The aim of challenge testing is to simulate what could happen to a product during production, processing, distribution or subsequent handling by consumers following inoculation with relevant micro-organism(s) and storage under the representative conditions, from production to consumption (Notermans and In't Veld, 1994).

16.2

Basic principles

The usefulness or appropriateness of challenge testing depends on factors such as the probability of the product supporting microbial growth (spoilage and pathogenic micro-organisms), and knowledge of its previous history, e.g., raw materials, processing, etc. This chapter discusses the major factors that need to be considered in the design of a microbiological challenge test, starting from the selection of the challenge micro-organisms, product inoculation methodology, sample analysis and results interpretation (Fig. 16.1). 16.2.1 Factors affecting microbial growth and survival The ability of a food matrix to support, or not, microbial growth and survival is a complex process that involves a combination of intrinsic and extrinsic factors. Water activity, pH, nutrient availability, oxidation-reduction (redox) potential, the presence of naturally occurring antimicrobial compounds and background micro-flora (competitive micro-flora) are all factors characteristic of the food itself (intrinsic). Changes in those factors as a result of the food's environment, e.g., packaging, processing, storage time and temperature (extrinsic factors), are those that finally determine its shelf life. Knowledge of the minimum, maximum and optimum microbial growth conditions is important in effective risk assessments, when decisions need to be made as to the possibility of specific micro-organisms growing in the product during its shelf life. Indicative water activity and ranges of pH values of specific foods are shown in Tables 16.1 and 16.2, respectively. Approximate water activity and pH values for the growth of major pathogenic and spoilage microorganisms are shown in Table 16.3 (IFT/FDA, 2003a). Dominant micro-organisms in food are those able to utilize available nutrients with carbohydrates and amino acids being utilized first, followed by more complex molecules. Gram-negative bacteria are generally able to derive

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Fig. 16.1 Steps in microbiological challenge testing.

their nutritional requirements from available nutrients, while on the other hand, Gram-positive bacteria are generally considered more fastidious in their requirements. Despite its importance in determining microbial growth rates, due to the complexity of its effects on micro-organisms, nutrient availability cannot be considered to be a strong predictive tool per se of microbial behavior in food. Practical difficulties in measuring redox potential in foods and in the interpretation of the redox potential values obtained have led to this factor being Table 16.1 Typical water activity (aw) values of selected food categories Food category

aw

Bread crust Bread white Cake icing Dried fruit Cereal Jam Fresh meat, poultry, fish Cured meat Fresh fruit and vegetables

0.30 0.94±0.97 0.76±0.84 0.55±0.80 0.10±0.20 0.75±0.80 0.99±1.00 0.87±0.95 0.97±1.00

Source: Adapted from IFT/FDA (2003a)

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Food and beverage stability and shelf life Table 16.2 Typical pH values of selected food categories Food category

pH

Milk Mayonnaise Fish (most species) Tuna fish Ham Beef Chicken Apples Bananas Parsley Tomatoes

6.3±7.0 3.0±4.1 6.6±6.8 5.2±6.1 5.9±6.1 5.1±6.2 6.2±6.4 2.9±3.3 4.5±4.7 5.7±6.0 4.2±4.3

Source: Adapted from IFT/FDA (2003a)

Table 16.3 Approximate pH and water activity (aw) values permitting growth of selected micro-organisms Micro-organism Campylobacter spp. Salmonella spp. Vibrio parahaemolyticus Bacillus cereus Clostridium perfringens Listeria monocytogenes Staphylococcus aureus (growth) Staphylococcus aureus (toxin)

pH

aw

4.9±9.0 3.8±9.5 4.8±11.0 4.3±9.3 5.5±9.0 4.39±9.4 4.0±10.0 4.5±9.3

0.98±0.99 0.94±0.99 0.94±0.99 0.91 (min.) 0.943±0.97 0.92 (min.) 0.83±>0.99 0.87±>0.99

Source: Adapted from IFT/FDA (2003a) and Micro-Facts (2007)

the least well-defined and most under-utilized parameter in microbial growth studies. Typical values of redox potential of some foods are shown in Table 16.4. However, these are highly dependent on changes in the food's pH, packaging, presence of background micro-flora, atmosphere and storage temperature and, therefore, presented values should only be taken as indicative. The ability of a dominant background micro-flora to inhibit the growth of the minority organisms in a food matrix was first described in the 1960s, when Jameson described the growth inhibition of salmonellae in the presence of a majority Gram-negative background population (Jameson, 1962). Later on, this inhibition was correlated to a rapid decrease in the redox potential caused as the dominant flora entered the stationary-phase in a mixed culture (Komitopoulou et al., 2004a, 2004b). In a food matrix, antimicrobial compounds can be part of the product's formulation (e.g., herbs and spices), can be added in the form of chemical preservatives, such as sorbate and benzoate, acetic acid, nitrite/nitrates, sulfur

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Table 16.4 Typical redox potential (Eh; mV) values of selected food categories Food category Milk Cheddar Raw minced meat Canned meat Whole grain cereals Grape juice Lemon juice

Eh (mV) ‡300 to ‡340 ‡300 to ÿ100 ‡225 ÿ20 to ÿ150 ÿ320 to ÿ360 ‡409 ‡383

Source: Adapted from IFT/FDA (2003a)

dioxide, etc., or can involve naturally occurring compounds, as a result of fermentation, produced by certain micro-organisms. Bacteriocins mainly produced by lactic acid bacteria (e.g., nisin) are the best-described naturally occurring compounds in foods, with proven antimicrobial activity against Gram-positive micro-organisms. Numerous studies on the antimicrobial activity of bacteriocins against Listeria monocytogenes have been published (e.g., ArqueÂs et al., 2005; Tahiri et al., 2009; Maks et al., 2010). However, their limited range of activity, restrictions in regulations covering their use in foods and their limited compatibility with most food matrices have restricted their application in food preservation. The effective use of antimicrobial compounds in food preservation and extension of a product's shelf life can only be a result of a combination of synergies occurring between the added compound(s) and a combination of other factors covering the food's intrinsic and extrinsic characteristics. The microbiological stability of certain shelf-stable processed cheese formulations, for example, can be taken as the best proof of Leistner's hurdle concept. This concept states that several inhibitory factors (hurdles), whilst individually unable to inhibit micro-organisms, will nevertheless be able to do so in combination (Leistner, 1995). The prolonged safe storage of processed cheese products in ambient conditions is a result of a combination of the appropriate heat process, water activity, salt and pH conditions. The application of the hurdle concept, with or without the use of preservatives, has been the basis for the development of predictive models as important tools in shelf life predictions. The effect of the external environment on the food's shelf life is determined mainly by microbiological challenge testing whereby products are intentionally contaminated with micro-organisms possessing implicit properties most closely related to the intrinsic and extrinsic properties of the food. The contaminated, spiked, product is then stored at the recommended storage temperature, and within the recommended packaging conditions (appropriate gas atmosphere), for a specific time period which would correspond to the current, or intended or desired shelf life of the product. Important parameters in the determination of the safe shelf life of foods using challenge testing involve the choice of

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challenge micro-organisms, the choice of inoculation methodology, including the inoculum levels and preparation conditions. 16.2.2 Selection of challenge organisms The choice of micro-organisms to be used in challenge testing should be a result of an assessment of the risk for food contamination and of the intrinsic and extrinsic characteristics of the food to support microbial growth. Knowledge of previous history of the food and any previous indications of pathogen growth, e.g. implication in episodes of food poisoning, is a very important determinant of the choice of microbial inocula to be used in any challenge testing. A list of indicative strains previously used in challenge testing of different foods is shown in Table 16.5. It is generally accepted that the ideal challenge micro-organisms are natural isolates having previously been isolated from similar type products. Use of strains from recognized culture collections (e.g., ATCC, NCTC) can be an alternative solution when natural isolates are not available. However, it is important that strain source and availability are clearly indicated within the challenge trial design. The latter may then need to be adjusted to accommodate a couple of extra steps in the preparation of the microbial inoculum to allow for a Table 16.5 foods

Typical pathogenic micro-organisms used in challenge testing of various

Food category

Challenge micro-organism(s)

Salad dressings

Salmonellae, S. aureus

Dairy products

Salmonellae, S. aureus, C. botulinum, enterohemorrhagic E. coli, L. monocytogenes

Confectionery products

Salmonellae

Sauces and salsas stored at ambient temperature

Salmonellae, S. aureus

Cooked or dried meat and poultry

C. botulinum, C. perfringens, L. monocytogenes, Salmonellae, S. aureus, enterohemorrhagic E. coli

Fish and seafood

B. cereus, C. botulinum, L. monocytogenes, Salmonellae, Shigella spp., S. aureus, Vibrio spp.

Fruits and vegetables

B. cereus, C. botulinum, enterohemorrhagic E. coli, L. monocytogenes, Salmonellae, Shigella spp., Y. enterocolitica

Cereal grains and related products (e.g., fresh pasta, cooked rice)

B. cereus, C. botulinum, Salmonellae, S. aureus

Source: Adapted from IFT/FDA (2003b) and NACMCF (2009)

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certain degree of adaptation of the strains to the product's intrinsic conditions (e.g., low pH, high sugar, etc.) prior to inoculation. Pre-adaptation, or microbial `conditioning' can be a lengthy, nevertheless essential, process in producing the worst-case inoculum scenario using otherwise `matrix-unfamiliar' strains. Use of conditioned strains can have its own benefits and drawbacks. In the absence of natural isolates, use of conditioned strains would represent the most valid alternative. However, such strains are generally characterized by faster growth rates and shorter lag-phases than their natural counterparts. This can seriously affect the results of challenge testing and although in reality this would represent a fail-safe result, it would not be particularly useful in trials designed to establish the time, within the storage period, required to achieve a specific log-increase in microbial numbers. When challenge trials are designed to assess the effect of another stress application (e.g., heating) on microbial loads, the use of artificially conditioned strains can result in false results and the indication of thermal death times significantly smaller than normal. In these types of challenge trials, it is advisable to allow conditioned isolates some adjustment time to survive, or even grow by one or two logs, in the food matrix prior to carrying out any thermal death trials. Use of combinations of challenge micro-organisms in microbial cocktails has generally been recommended, and has most often been included in the inoculation methodology part of challenge trial designs. Provided there is a lack of any mutual antagonism, which could affect the fate of the individual strains during storage, use of such a mixed inoculum represents the most realistic scenario that can also have its own limitations. In a mixed culture, individual strains may grow faster as a result of utilizing nutrients produced by the other strains in the cocktail. They may, however, grow more slowly as a result of a certain degree of competition, especially in cases where a cocktail of Gram-negative strains is used. To minimize the effect of strain competition, it is recommended that where possible, mixtures of Gram-negative strains are avoided. Use of a microbial cocktail can affect the recovery and enumeration of the individual strains during sampling, significantly compromising the results of the challenge testing. This can be the case when the work requires distinguishing between two or more different species used in a single cocktail, in which cases selective or indicator media need to be used. Media selectivity represents an additional hurdle to already stressed micro-organisms (e.g., those originally spiked in and recovered from a low pH, preservative-containing food matrix), significantly underestimating their ability to grow in the product. The choice of a mixed or single strain inoculum has generally been determined by available funds (mixed strain studies being the most cost-effective), rather than by any specific benefits overriding the limitations. In some cases, use of selective media to distinguish between strains in a cocktail can be avoided by using genetically modified strains and utilizing specific genetic markers, e.g., luminescence/fluorescence or antibiotic resistance. When this is the case, care should be taken to ensure that the genetically modified organisms used share the same growth/survival behavior as their parent strains under the same conditions.

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The use of surrogate strains, e.g. use of Clostridium sporogenes as a surrogate for Clostridium botulinum, or Listeria innocua as a surrogate for Listeria monocytogenes, is common when pathogenic strains cannot be used in processing plants. Care should be taken to choose the right surrogate strain(s) in the challenge trials so that meaningful results are obtained. The choice of surrogate strains should be based on the following key attributes of the successful surrogate (IFT/FDA, 2003b): · lack of pathogenicity · stable and consistent growth/survival characteristics, bearing strong similarity to those of the target pathogen when exposed to the same formulation or processing factors (e.g., pH and temperature sensitivity, oxygen tolerance, etc.) · inactivation characteristics and kinetics similar to those of the target pathogen · easy to produce, time-stable, high-density population that is easy to enumerate and distinguish in a mixed culture environment · genetically stable to ensure reproducibility of results independent of the laboratory or time of experiment · stress and injury susceptibility similar to that of the target pathogen. 16.2.3 Inoculum level and preparation The preparation and level of inoculum are both important parameters in the design of the challenge testing protocols. Inoculum levels per unit weight or volume of a product need to be realistic and in direct correlation to the purpose of the challenge testing. If the aim of the trials is to evaluate the safety and stability of a product during a specified period, then initial levels of inoculum should be between 100 and 1000 cells per gram or per ml of the product. Levels lower than 100 cells per gram or ml may be below the limits of detection in many sampling methodologies employed, thus making the incorrect assumption that the product is safe and stable, when it is not. On the other hand, levels any higher than 1000 cells per gram or ml may overcome the intrinsic preservation properties of the food matrix leading to the false assumption that the product is not safe and stable, when in reality it is. Use of inoculum levels higher than 1000 cells per gram or ml of a product applies to those trials aiming to determine microbial log-reductions following the application of a specific stress, such as heating, irradiation, etc. In these cases inoculum levels can reach 106±108 cells per gram or ml of a product, depending on the scale of the log-reduction the system tested needs to demonstrate. For example, if the aim of the trials is to confirm that a specific heating process can result in a five-log reduction in numbers of Listeria monocytogenes in cheese, then the product needs to be inoculated with a minimum of 106 cells per gram of the product and then be subjected to the specific heating process. Culture and inoculum preparation prior to inoculation is the second most important part of the challenge testing protocol following the choice of the challenge strains. There are no specific guidelines that govern inoculum

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preparation as generally this is affected by the type of inoculum and the nature of the food matrix to be challenged. A basic rule in all inoculation trials is standardization of the protocols used in culture preparation to involve clear instructions on culture maintenance (e.g., refrigerated cultures, slants, cultures frozen in glycerol, freeze-dried cultures etc.), isolate sub-culturing and recovery. Specific guidelines for culture maintenance exist (e.g., Kirsop and Doyle, 1991) and the choice of the best protocol to follow depends mainly on available facilities. The most important aspect in culture maintenance involves strains previously isolated from extreme environments (e.g., low pH, high sugar matrices). Storage of these strains should ensure that specific characteristics developed and expressed as a result of previous exposure to extreme environments are maintained and are adequately reproduced by the appropriate media throughout storage. For example, a yeast strain previously isolated from a low pH beverage (pH 3.5) needs to be stored and maintained in a medium of similar pH. Prolonged exposure of this strain to pH conditions higher than those previously encountered might render it unable to subsequently grow under low pH conditions. This is more so for isolates (not natural) previously conditioned to grow in extreme environments as one cannot assume that adaptation can be maintained in the absence of the appropriate trigger. Cell cultivation needs to take place under the optimum growth conditions for each strain. In most cases, resuscitation involves growth for 18 to 24 h under optimum temperature and atmospheric conditions; however, procedures that involve using 48 or 72 h cultures (e.g., certain yeasts) are often used. Culture enumeration at this stage is important to determine the scale of required dilutions to achieve the target inoculum in the challenge product. Spores washed and stored in distilled water to prevent germination may need to be heat shocked immediately prior to inoculation, if prompt germination and growth are to be achieved and represent what happens in food processing. Depending on the strain, spores may also need to be thoroughly washed to minimize the transfer of free toxin in the product during inoculation, as in the case of botulinal toxin produced by Cl. botulinum. In most protocols, cultures are centrifuged and the cell pellets are washed thoroughly to avoid the transfer of any compounds (e.g., nutrients) from the laboratory growth media to the food matrix during inoculation. For liquid products, washed pellets are then resuspended in a volume of the same food product, and any subsequent dilutions of the resuspended culture are also carried out using the appropriate volumes of the same product. Product inoculation can then be carried out without alteration of the intrinsic characteristics of the matrix. For solid products, cell pellets are resuspended in appropriate diluents, also used to carry out any necessary dilutions. Product inoculation is then carried out using the minimum possible volume of inoculum to ensure that its main characteristics, e.g., pH, water activity, remain unaffected. An alternative method of inoculum preparation involves microbial cell recovery from lawn plates prepared from 24±48 h cultures. Following this protocol, lawn plates are prepared using grown cultures and are incubated under

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optimum growth conditions. Cell recovery is then carried out using an appropriate carrier depending on the type of the challenge product, and the resuspended cells or spores are appropriately diluted and used in the challenge trials. Studies have shown that lawn-collected cells are characterized by an enhanced survival potential compared to broth-collected cells and can therefore represent a worst-case scenario in challenge experimentation (Komitopoulou and Penaloza, 2009). 16.2.4 Choosing the right method of inoculation The choice of the inoculation method is another crucial parameter in the design of challenge trials. A challenge test can be considered successful if inoculation does not affect any of the product's intrinsic or extrinsic properties. The methodology employed also needs to be reproducible and properly validated, one that also includes pre- and post-inoculation analysis of the critical characteristics of the product's formulation (e.g., moisture content, water activity and pH), to ensure that these have remained unaffected by the inoculation process. The choice and volume of the liquid inoculum carrier used in the inoculation methodology are crucial parameters affecting the success of the trials. Independent of the type of carrier used, the aim should always be to use the minimum possible volume of carrier to also ensure the least possible change in the product characteristics. In liquid products the inoculum can be suspended in a sample of the product matrix itself, creating a stock which is then used to inoculate different samples of the same product. In cases where maintaining the moisture level is important, the inoculum carrier can be the same diluent used to adjust the moisture content of the product formulation in the first case. The successful inoculation methodology needs to ensure even distribution of the inoculum within the product matrix to minimize errors in the subsequent sampling and enumeration of the challenge organism, whilst at the same time maximizing microbial exposure to the product's environment. This can prove particularly problematic when inoculation is carried out using a syringe through the packaging wall containing a rubber septum. When adequate mixing cannot be achieved, samples are first inoculated and then re-packed making sure that packaging after inoculation matches the normal packaging conditions of the product. Mixing of inoculum within the product matrix can easily be done in products with water activities higher than aw ˆ 0.96 (e.g., sauces) using the minimum volume of the inoculum carrier possible. Spraying has also been suggested and employed for inoculation of product surfaces, although care should be taken to ensure that this is carried out using the appropriate protective equipment to make sure that exposure to pathogenic aerosols is minimized. 16.2.5 Duration of trials and storage conditions The duration of the challenge trials will depend on the current, desired or intended shelf life of the product, needs to cover all of this period and also

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include a margin beyond this time to account for the possibility of consumers storing the product beyond its recommended life. Storage of the inoculated product during this time needs to replicate the conditions the product is likely to be exposed to under normal storage conditions. However, slight abuse storage conditions, as imposed by consumers, during transport and/or at retail, can often occur and, therefore, the challenge trials need to account for the possibility of the worst, within reason, scenario of slightly abused storage conditions. Storage conditions, and storage temperature in particular, can seriously affect the duration of the challenge trials; the duration of the challenge trials of chilled products should not be expected to be the same when the products are stored at normal (e.g. 4 ëC) and slightly abusive chilled conditions (e.g., 8 ëC). The extended lag-phase sometimes observed by micro-organisms, e.g. when they are exposed to extreme conditions within the food matrix when they are introduced, can also delay the duration of the challenge trial. This delay is deemed necessary to allow the micro-organisms time to overcome the preliminary shock, reflected by the lag-phase, recover and then grow depending on the ability of the food matrix to support or inhibit growth. Other storage conditions that need to be considered in a challenge trial involve the type of packaging and nature of the gas atmosphere within the packs. A number of challenge trials are carried out to determine the safety of a film type used in packaging or to determine the role of a gas mixture on the safety and stability of a product during storage under normal temperature conditions. When the inoculation methodology used in the challenge test involves interfering with the packaging characteristics of the product, these will then need to be replicated to mimic the exact conditions normally applied to the specific product, for the challenge trial to produce any meaningful results. 16.2.6 Sample analysis and data interpretation Duration of the challenge trial will affect the frequency of sampling during storage. In all cases, sampling needs to include time zero analysis, i.e., analysis immediately after product inoculation, to verify inoculum levels and allow calculation of log differences in the numbers of the challenge micro-organisms during storage. Depending on whether the duration of the challenge trial is measured in days, weeks or months, a sampling regime needs to cover representative time points during storage. When products have a short shelf life measured in days, sampling is required daily, while a more prolonged trial duration may require sampling once or twice a week. A minimum of five to seven points are required in a challenge trial to obtain an accurate indication of the behavior of the inoculum during storage. The results from sample analysis during storage can also be used as an indicator of duration of the challenge trial; there is no point to continue sampling a product when levels of inoculum have already reached 108 cells per gram or ml of the product. When levels below the limits of detection are obtained following the standard enumeration techniques, detection methodologies specific to the target micro-

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organism(s) need to be used instead. This is to confirm the absence of the organism and ensure that no subsequent recovery will occur that can compromise the shelf life of the product. When looking for toxin production during storage, this can be tested for at some but not necessarily all sampling points. Sample replication is an important factor contributing to the validity of the challenge trial. Duplicate or triplicate samples should ideally be analyzed at each sampling point, while it is recommended that the challenge trial is repeated twice or three times in independent trials (i.e., performed at different times, using fresh inocula and ideally carried out by different staff) in cases where a high degree of certainty is required. The selection of the media and reagents for sampling and enumeration of the challenge micro-organisms will depend mainly on the type of micro-organisms and also the nature of the challenge matrix itself. The use of selective media needs to be done with care to avoid imposing additional stresses on already stressed challenge micro-organisms in the food matrix. Absence of background flora in a product can allow the use of non-selective media. Monitoring of the background flora is carried out by setting up and analyzing un-inoculated, negative control, samples of the same product alongside the spiked samples. Positive controls, in which a portion of the same cell inoculum is used for the inoculation of laboratory media that can support maximum microbial growth, are also recommended. Both negative and positive controls can help interpret results. The presence or absence of background flora can be important in allowing or inhibiting/delaying the growth of major pathogens, respectively. Background flora can also have an indirect effect on the target micro-organisms by changing the product's critical parameters (e.g., lowering the pH). Monitoring of those parameters (mainly aw and pH, sugar and salt levels, preservatives, gas atmosphere) throughout the challenge trials can help validate the results of the challenge trials. If growth of a particular challenge micro-organism in the product is not observed, growth of the same cell inoculum in the positive control trials will indicate that absence of growth was related to the inhibitory/ preservative nature of the product and was not a result of a deficient inoculum. Interpretation of the results of a challenge trial should involve the use of all sets of data obtained during the trials; microbial growth, change in physicochemical and other intrinsic/extrinsic properties of the product, positive and negative controls, so that a comprehensive evaluation of the microbiological safety and stability of the product is achieved. Upon completion of the challenge trial, presentation of the results obtained can be in different forms depending on the individual writing up the report and any specific requirements, e.g. when the report is intended to reach a customer. Trend analysis and graphical plotting of mean log counts against time or mean survivor curves, depending on the experimental design, are undoubtedly the preferred way of presenting results. Prior to the start of the challenge trial, it is important to define the pass and fail criteria for the product and use those as the basis of any decision made around the duration of the trials and the need to reformulate. Pass/fail criteria

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and the significance of a population increase during storage depending on the hazard significance of that population. The outcome of the challenge trials can be very important in determining the shelf life of a product and indicating any potential changes in the product formulation that could affect product safety and stability. The use of challenge trials in the development of predictive models is a confirmation of the use and application of the challenge trials in the real-time determination of a current product formulation and prediction of the microbiological safety and stability of future formulations.

16.3

Challenge testing limitations

Challenge testing is a time-consuming process both in terms of required effort but also in terms of duration and elapsed time before any results are obtained. Use of accelerated storage conditions should not be considered an option in challenge testing. Designing a challenge testing protocol requires certain skills and knowledge, starting from the initial risk assessment, choice of challenge micro-organisms, protocols of product inoculation and result interpretation. Since most of the challenge trials involve use of pathogenic micro-organisms, it is important that these trials are conducted by experts, certainly qualified microbiologists, familiar with the necessary precautions that need to be taken for safe handling of pathogenic isolates and their potential toxins. Automatically, this makes challenge testing an expensive test to perform. The most important limitation of challenge testing is that its results are only valid for the specific product formulation challenged. Any changes in the product formulation, and/or handling of the product (e.g., processing, packaging), no matter how minor these may be, can render the results of the trial invalid. Inevitably this has made challenge testing an expensive test to perform in the development of a safe product formulation and has reinforced the need for the development of predictive models.

16.4

Challenge testing and the use of mathematical models

In the 1980s, predictive microbiology was made a priority as a result of major foodborne outbreaks caused by the so-called `traditional' pathogens (e.g., Salmonella in eggs) and other emerging pathogens with unusual characteristics (e.g., ability of Listeria monocytogenes to grow at chilled conditions). Since then, development of predictive microbiological models has found applications in a wide industrial context, making predictive microbiology an established scientific discipline. In product innovation, predictive mathematical models are used in the assessment of microbial growth characteristics or death kinetics (inactivation

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rates) associated with a particular food formulation or process condition, respectively. Their aim is to develop new products/processes, reformulate existing products and determine their shelf life and stability. In operational support, predictive models are used in support of food safety decisions around the implementation of specific food manufacturing operations. The latter may involve setting up critical control points (CCPs) in HACCP, designing heat processing protocols and assessing the impact of any deviation from the standard procedures on the microbiological safety and quality of the products. The impact of issues associated with products already in the market on consumer safety is often evaluated using predictive models, making incident support another distinct application of predictive modelling (Membre and Lambert, 2008). Available predictive models (e.g., Pathogen Modelling Programme (PMP), Growth Predictor, SymPrevius and ComBase) are user-friendly and easy-to-use software packages. The choice of the most appropriate software to use will need to be based on some comparison of preliminary predictions versus real-time experimentation (involving challenge testing), using the same input of information, to confirm findings and validate applicability of the system for the particular product. The majority of the existing predictive models describe population dynamics (continuous models) and serve as comprehensive analytical tools, requiring only basic expert mathematical skills and involving the application of mathematical equations. Classical mathematical models used in predictive microbiology usually describe the population through a `top-down approach'. They deal with equations that apply to the whole population and reflect essential microbial characteristics taking into account external variables such as water activity, pH and cell density (Li et al., 2007). Mathematical models that fit within the population top-down approach involve the mechanistic, empirical and probabilistic models. Mechanistic models are those that focus on studying microbial population dynamics and relate microbial lag-phase and growth rate with the state of the inoculum used and temperature (Baranyi and Roberts, 1994; Daughtry et al., 1997). Empirical models are those that predict the lag-phase and microbial growth rate incorporating data available from external databases (e.g., ComBase and PMP) and therefore focus on describing, reproducing and also predicting microbial behaviors (Buchanan, 1991; Baranyi and Tamplin, 2004). Finally, probabilistic models focus on the study of microbial communities in the growth/no-growth interface for risk assessment and spoilage (McKellar et al., 2002). It has been stated that a predictive model can provide results at least 1000 times faster and considerably cheaper than a traditional challenge test (Zwietering et al., 1996); however, use of predictive models cannot be considered as an alternative to challenge testing. Predictions can only provide indications of the likelihood for microbial growth and survival and should only be considered as such, unless these are tailor-made models produced using results obtained from real-time challenge tests of specific products. The source of information used in the construction of the predictive models is the most

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significant limitation to their application. The use of microbial growth and survival data from the literature and their incorporation into publicly available models have significantly restricted their industrial application. Nevertheless, they can be used to provide some preliminary indication of microbial behavior. Similarly, there are models that have been produced solely using data obtained under laboratory conditions, in broth systems, using combinations of parameters of no practical use and application to industry, using a limited number of microorganisms, mainly pathogenic, whilst no attempt has been made to validate those models in real-time food matrices. Production of tailor-made models is an expensive and lengthy process requiring the setting up of numerous challenge trials. However, it is thought to be the only precise way of producing models relevant to a specific product matrix. If a model is already in existence for a particular product design then it can be a very valuable tool for any subsequent reformulations of the same product.

16.5

Future trends

The demand for natural ingredients has been fuelled by a growing consumer preference for healthy foods. The loyal users of natural products are increasing and this trend is predicted to continue followed by an increased demand for new products to be of natural ingredients and old products to be reformulated. Replacement of chemical preservatives with natural alternatives is not the only need for product reformulation that industry is currently facing. Salt reduction in processed foods, including meats and baked products, has been on the agenda of the Food Standards Agency. Sugar (sucrose) is well known to increase the heat resistance of vegetative cells of microbes, and decrease microbial growth rates, by reducing water activity. Replacement of sucrose by an intense sweetener, or reduction by use of a sugar of higher sweetness intensity (e.g., fructose), will allow the growth of many microbes, including pathogens. As the demand for `clean labels' linked to significant product reformulation is on the rise, the requirements for verification of the safety and stability of the new formulations will increase dramatically.

16.6

Sources of further information and advice

Particularly useful sources of information on microbial characteristics (growth, survival, resistance) and their association with different foods are: · Wareing, P. and Fernandes, R. (eds) (2007). Micro-Facts. The Working Companion for Food Microbiologists. Leatherhead Food International, UK. RSC Publishing. · Leatherhead Food Research ± Microbiology Handbooks on: Meat Products (2009). Fernandes, R. (ed.), RSC Publishing.

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Fish and Seafood (2009). Fernandes, R. (ed.), RSC Publishing. Dairy Products (2009). Fernandes, R. (ed.), RSC Publishing.

16.7

References

and NUNÄEZ, M. (2005). Effect of combinations of high-pressure treatment and bacteriocin-producing lactic acid bacteria on the survival of Listeria monocytogenes in raw milk cheese. International Dairy Journal, 15, 893±900. BARANYI, J. and ROBERTS, T.A. (1994). A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology, 23, 277±294. BARANYI, J. and TAMPLIN, M.L. (2004). ComBase: a combined database on microbial responses to food environments. Journal of Food Protection, 67, 1967±1971. BUCHANAN, R.L. (1991). Using spreadsheet software for predictive microbiology applications. Journal of Food Safety, 11, 123±134. DAUGHTRY, B.J., DAVEY, K.R. and KING, K.D. (1997). Temperature dependence of growth kinetics of food bacteria. Food Microbiology, 14 (1), 21±30. IFT/FDA (2003a). Chapter III: Factors that influence microbial growth. Comprehensive Reviews in Food Science and Food Safety, 2, 21±32. IFT/FDA (2003b). Chapter VI: Microbiological challenge testing. Comprehensive Reviews in Food Science and Food Safety, 2, 46±50. JAMESON, J.E. (1962). A discussion of the dynamics of Salmonella enrichment. Journal of Hygiene, 60, 193±207. KIRSOP, B.E. and DOYLE, A. (1991). Maintenance of Microorganisms and Cultured Cells ± A Manual of Laboratory Methods, London: Academic Press. KOMITOPOULOU, E. and PENALOZA, W. (2009). Fate of Salmonella in dry confectionery raw materials. Journal of Applied Microbiology, 106 (6), 1892±1900. KOMITOPOULOU, E., BAINTON, N. and ADAMS, M.R. (2004a). Oxidation-reduction potential regulates RpoS levels in Salmonella Typhimurium. Journal of Applied Microbiology, 96(2), 271±278. KOMITOPOULOU, E., BAINTON, N. and ADAMS, M.R. (2004b). Premature Salmonella Typhimurium growth inhibition in competition with other Gram-negative organisms is redox potential regulated via RpoS induction. Journal of Applied Microbiology, 97 (5), 964±972. LEISTNER, L. (1995). Principles and applications of hurdle technology. In: Gould, G.W. (ed.), New Methods of Food Preservation. London: Blackie Academic & Professional, 1±21. LI, H., XIE, G. and EDMONDSON, A. (2007). Evolution and limitations of primary mathematical models in predictive microbiology. British Food Journal, 109 (8), 608± 626. MAKS, N., ZHU, L., JUNEJA, V.K. and RAVISHANKAR, S. (2010). Sodium lactate, sodium diacetate and pediocin: effects and interactions on the thermal inactivation of Listeria monocytogenes on bologna. Food Microbiology, 27(1), 64±69. MCKELLAR, R.C., LU, X. and DELAQUIS, P.J. (2002). A probability model describing the interface between survival and death of Escherichia coli O157:H7 in a mayonnaise model system. Food Microbiology, 19, 235±247. MEMBREÂ, J-M. and LAMBERT, R.J.W. (2008). Application of predictive modeling techniques ARQUEÂS, J.L., RODRIÂGUEZ, E., GAYA, P., MEDINA, M.

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in industry: from food design up to risk assessment. International Journal of Food Microbiology, 128(1), 10±15. NACMCF (2009). Parameters for Determining Inoculated Pack/Challenge Study Protocols, National Advisory Committee on Microbiological Criteria for Foods, Washington, DC. NOTERMANS, S. and IN'T VELD, P. (1994). Microbiological challenge testing for ensuring safety of food products. International Journal of Food Microbiology, 24, 33±39. NOTERMANS, S., IN'T VELD, P., WIJTZES, T. and MEAD, G.C. (1993). A user's guide to microbial challenge testing for ensuring the safety and stability of food products. Food Microbiology, 10, 145±157. TAHIRI, I., DESBIENS, M., KHEADR, E., LACROIX, C. and FLISS, I. (2009). Comparison of different application strategies of divergicin M35 for inactivation of Listeria monocytogenes in cold-smoked wild salmon. Food Microbiology, 26(8), 783±793. ZWIETERING, M.H., DEWIT, J.C. and NOTERMANS, S. (1996). Application of predictive microbiology to estimate the number of Bacillus cereus in pasteurised milk at the point of consumption. International Journal of Food Microbiology, 30, 55±70.

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17 Beer shelf life and stability G. G. Stewart and F. G. Priest, Heriot-Watt University, UK

Abstract: Brewing was one of the earliest processes to be undertaken on a commercial scale and consequently it became the first biological process to develop from a craft into a technology. Although the production of beer is a relatively simple process, the finished product is unstable when in its final package ± bottle, can or keg. As well as being susceptible to microbial infection, non-biological instability involves a number of complex reactions with proteins, carbohydrates, polyphenols, metal ions, thiols and carbonyls. Although our understanding of these reactions has progressed over the past 25 years, we are still far from a complete comprehension of beer instability/ stability reaction systems. Key words: beer, clarity, flavour, instability, infection.

17.1

Introduction

Brewing was one of the earliest processes to be undertaken on a commercial scale and, of necessity, it became one of the first processes to develop from a craft into a technology. Beer production is divided into five distinct processes: · malting is the germination of barley or other cereal and drying (or kilning) of the germinated cereal; · mashing is the extraction of the ground malted barley with water and separation from the insoluble material to produce wort; · wort boiling with the inclusion of hops or hop extracts; · fermentation, maturation and filtration; · packaging (used generally to mean kegging, bottling and canning). The production of beer is a relatively simple process. Yeast cells are added to the nutrient medium (the wort) and the cells take up the nutrients and utilise

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them to increase the yeast population. The cells excrete ethanol and carbon dioxide into the medium along with a host of minor metabolites, many of which contribute to beer flavour. The fermented medium, generally after the yeast has been removed for re-use, is often called `green' beer because it usually has the aroma of green apples (due to acetaldehyde and other carbonyl compounds). The beer is then aged (conditioned, matured or lagered), maybe diluted, clarified (filtered), carbonated and packaged.

17.2

Biological instability

Biological instability involves contamination by bacteria, yeast or mycelial fungi. There is always a risk during brewing that beer can become contaminated by microorganisms. However, beer is an inhospitable environment for microbial growth: it has a low pH (less than 4.4), ethanol is present in a range of concentrations (2.5±6.5 (v/v)), there are limited nutrients due to yeast growth, hop acids are present that are bacteriostatic, the environment is anaerobic, and the liquid is carbonated. The advent of low/no alcohol beers (LAB/NABs) and products with pHs above those of traditional beers has exposed them to a greater susceptibility of infection. Most potential contaminants originate from the raw materials or unclean brewing equipment. Barley can contain Fusarium fungi that can release mycotoxins or cause gushing (see Section 17.6). It can also carry bacteria that contribute nitrosamines (potentially carcinogenic agents) and cause filtration problems. Contaminants can cause flavour deterioration, turbidity and health problems. Of the microflora found in a brewery, the Gram-positive lactic acid bacteria are the most feared. In addition to being potential beer spoilers, the lactic acid bacteria have a reputation for being `difficult' in terms of detection, recovery from spoilt beer and identification. The concerns reflect the nutritional fastidiousness of these bacteria and their variable response to the anti-microbial effects of hop iso--acids. The major bittering (and antimicrobial) substances in beer include isohumulone, isocohumulone and isoadhumulone and their cis and trans isomers. Generally, Gram-positive bacteria are sensitive to these isomerised hop acids and accordingly cannot grow in hopped beers. However, strains of Lactobacillus and Pediococus able to spoil beer are significantly more resistant to these acids. Studies by Simpson (1993) showed great variation in the sensitivity of a selection of Gram-positive bacteria to one of the major hop acids, trans-isohumulose. Although many questions remain to be answered, typically lactic acid bacteria isolated from beer will not grow when the colony is transferred to beer. This is unsatisfactory, as the spoilage status of the isolate remains unclear. It is noteworthy that hop-sensitive and hop-resistant lactic acid bacteria are indistinguishable from each other in terms of morphology, physiology and metabolism. The molecular mechanisms of hop toxicity are becoming clear (Behr and Vogel, 2009) and the genetics of hop resistance in Gram-positive bacteria are being unravelled (Sakamoto et al., 2001; Iijima et al.,

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2006). Such studies will enable the rapid molecular detection of hop-resistant strains. The major contaminating Gram-negative bacteria are acetic acid bacteria (Acetobacter and Gluconobacter) and various genera in the Enterobacteriaceae (Obesumbacterium, Citrobacter, Klebsiella) as well as Zymomonas, Pectinatus and Megasphaera (Priest and Campbell, 2003). In comparison to the Grampositive bacteria, the threat of the various Gram-negative bacteria is under reasonable control. Day-to-day management of this microbiological threat is achieved through regular acid washing (Simpson and Hammond, 1989) of pitching yeast and scrupulous attention to process hygiene. A wild yeast is defined in the brewing industry as `any yeast not deliberately used and under full control' (Gilliland, 1971). This definition of wild yeast is divided into Saccharomyces and non-Saccharomyces groupings. Irrespective of classification, wild yeast contamination of process and product can be a major cause for concern. Generally, the Saccharomyces wild yeasts are regarded as more hazardous than the heterogeneous grouping of the non-Saccharomyces wild yeasts. It is important to exclude these contaminants from the brewing process. Modern plant and good hygiene will help. Many breweries pasteurise and others membrane filter their beer to ensure biological stability. With good hygiene, the use of expensive and potentially beer damaging processes can be reduced. However, inefficient operation of either pasteurisation or membrane filtration can negatively affect a beer's non-biological stability.

17.3

Physical instability

With a few notable exceptions, consumers prefer their beer to be bright and free of particles. When beer is stored it has the potential to produce haze and the brightness is compromised. Beer's physical stability, also called colloidal stability or simply haze formation, cannot be ensured by treating beer with one `super-product' that will solve everything. Stability will be affected by the whole brewing process; consequently, care must be taken at every stage. However, raw materials are typically the source of haze precursors. There are a number of types of beer haze including: -glucan, starch, pentosan, oxalate, microorganisms and can lid lubricants. However, the primary reaction is the polymerisation of polyphenols and their interaction with specific (sensitive) proteins. When beer is cooled below 0 ëC, chill haze will form that consists of a reversible association of small polymerised polyphenols and proteins. When the beer is restored to room temperature, this haze re-dissolves and the beer becomes bright again. If beer is chilled and warmed a number of times, or if beer is stored at room temperature for an extended time period (six months or longer), permanent haze will form. This haze does not re-dissolve even when the beer is warmed to 30 ëC or higher. The balance between flavenoid polyphenols (tannoids) (Fig. 17.1) and sensitive proteins largely dictates physical or colloidal stability. Beers can differ

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Fig. 17.1 A typical beer polyphenol.

widely in the content of these species, the relative levels of which depend upon raw materials and the process conditions employed. Haze formation is increased by a number of factors (Bamforth, 1985) but storage temperature has the greatest influence on haze formation because an increase in temperature raises the rate of the reaction. For example, pasteurisation accelerates colloidal haze formation. Oxidation (the presence of oxygen) has a great effect on beer haze formation. Extensive oxidation can increase the rate of haze appearance manyfold. Heavy metal ions (particularly iron) can promote the formation of colloidal haze. Movement of beer accelerates haze formation because of rapid interaction of colloids. Light encourages oxidation and consequently haze formation as well as other reactions that are dealt with later. Beer chill haze consists of a loose bonding of high molecular weight proteins with highly condensed polyphenols (predominantly anthocyanogens). In these loosely bound aggregates, small quantities of carbohydrates and inorganic materials are included. This loose binding is broken on warming. Haze formation occurs as a result of dissolved colloidal particles colliding and hydrogen bonds forming between them. In the course of time, increasingly large aggregates come together until they are visible as haze. Haze formation correlates with the presence of sensitive proteins (substances that precipitate with tannic acid) and tannoids (polyphenols adsorbed by polyvinyl-polypyrolidone or PVPP). The driving force for haze formation is the interaction of hydrophilic groups on these sensitive proteins with polyphenols. There are also hydrophobic proteins in beer. These surface-active species are important in foam formation (see Section 17.5). There are a number of procedures that can be employed to retard or prevent haze formation: · prevent the formation of large quantities of complex protein degradation products during beer production; · enzymatically hydrolyse the complex `sensitive' protein degradation products; · remove some of the polyphenols or sensitive proteins during brewing; · store packaged beer in cold temperatures to retard haze formation. Employing stabilisers can produce beers with a longer shelf life. The main stabilising agents, which can be used singly or together are: silica gel preparations, PVPP and proteolytic enzymes. Silica gel preparations are important

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stabilising agents that bind hydrophilic polypeptides. They are employed in quantities of 50 to 150 g/hL and are usually dosed into the beer before filtration. There are two types of silica gel preparations used in brewing: hydrogels that have a moisture content of more than 30% and xerogels (dry gels) with a 5% water content. PVPP selectively removes phenol-containing substances. PVPP binds to polyphenols as it has a similar structure to the amino acid proline (Siebert and Lynn, 1997). Both have five-membered saturated, nitrogencontaining rings with amide bonds and no other functional groups. It is not certain whether PVPP binds to the same part of the polyphenol molecule to which polypeptides bind. This selection depends on the pH-sensitive formation of hydrogen bonds that are broken again in alkaline solution with the release of the adsorbed phenol compounds. Regeneration of PVPP with hot caustic is very effective. PVPP and silica gel preparations have been used together with good results because both polyphenol and sensitive protein components are removed (McMurrough and O'Rourke, 1997). Proteolytic enzymes are also employed as stabilising agents, but because of the advent of silica gel preparations, their use today is not as common as it was a number of years ago. The enzymes employed include papain (from papaya), bromelain (from pineapple) and ficin (from figs). These enzyme preparations are not very specific and, as well as hydrolysing haze-specific proteins, they often hydrolyse the hydrophobic foamspecific polypeptides (see Section 17.5). Consequently, the use of these enzymes often requires the addition of a foam-enhancing agent such as propylene glycol alginate. The use of propylene glycol alginate has to be treated with care because hazy beer can result if pH control is not effective (Jackson et al., 1980).

17.4

Flavour stability

The flavour stability of a beer depends primarily on the oxygen content of packaged beer. However, it is now clear that flavour stability is influenced by all stages of the brewing process (Narziss et al., 1993): · preservation of reducing substances by minimising oxygen pickup during mashing, lautering or mash filtering (the separation of unboiled wort from solid grain material (spent grains)) and wort boiling; · elimination of substances that are prone to react with flavo-active compounds like carbonyls by good mashing and wort separation procedures; · prevention of ion accumulation, such as iron and copper (Irwin et al., 1991); · controlled exposure of the wort to heat to limit the formation of Maillard reaction products (produced as a result of heating sugars with amino acids) and related substances. The role of the above reaction products in beer flavour staling reactions is ambiguous and there are reports (Bright, 2001) of their positive and negative effects.

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In many foods, such as milk, butter, vegetables, vegetable oils, and beverages, staling is caused by the appearance of various unwanted unsaturated carbonyl compounds. It is now becoming increasingly clear that the same is true of beer staling. As already discussed, packaged beer has a limited shelf life. The phenomenon of beer aging or staling has been intensively investigated by the brewing industry with the objective to understand and control it (Bamforth, 2004) but the mechanism(s) of staling are still not fully understood. The actual compounds responsible for stale flavour vary during prolonged storage as evidenced by changes in the flavour profile of beer (Fig. 17.2) (Dalgleish, 1977). The compounds causing the sweetish, leathery character of very old beers have not been identified. However, there is evidence that the papery cardboard character of 2±4-month-old beer is due to unsaturated aldehydes. The most flavour-active aldehyde that has been conclusively proven to rise beyond flavour-threshold levels is trans-2-nonenal (Dalgleish, 1977). Other aldehydes such as nonadienal, decadienal, and undecadienal may also exceed threshold levels. Although there are many factors that will influence the flavour stability of beer, the oxygen level in the final package is of paramount importance. It is critical that this level in beer, immediately prior to packaging, is as low as possible (less than 100 mg/L) and that oxygen accumulation during filling is minimal. The adverse effects of oxidation on the flavour of finished beer have been known for a long time and some brewers add bisulfites or other antioxidants, such as ascorbic acid, to beer prior to packaging to provide protection against oxygen. This can improve flavour stability. The effectiveness of bisulfite, besides its antioxidant properties, is also its ability to bind carbonyl compounds into flavour-neutral compounds (Barker et al., 1983). The reaction is reversible and excess bisulfite will increase yields of the adduct (Fig. 17.3).

Fig. 17.2 Sensory changes in beer flavour during aging.

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Fig. 17.3 Binding of bisulfite to carbonyls.

Bisulfite addition to fresh beer minimises the increase of free aldehyde concentration during aging. In addition, when added to stale beer, bisulfite lowers the concentration of free aldehydes and affects the removal of the cardboard flavour. However, over time, the bisulfite will be oxidised to sulphate, thus increasing the concentration of free aldehydes again (Barker et al., 1983).

17.5

Foam stability

When beer is sold, the stability of the foam in a glass of beer is considered by many consumers to reflect the quality of the product. The increasing use of adjuncts (unmalted sources of carbohydrate) and the associated decrease in malt being used today, together with the employment of high gravity brewing techniques, have had a negative effect on foam values in many beers. There are many foam-promoting compounds in beer, such as iso--acids from hops, protein/polypeptides, metal ions, and polysaccharides, and all have an important role to play in foam formation and stability. However, the backbone of foam is protein. Many methods have been tried and extolled for their virtues in the isolation and characterisation of foam positive beer polypeptides, for example, separation of foaming proteins by hydrophobic interaction chromatography has long been a standard technique (Bamforth, 1999). Once separated, the proteins are investigated to discover whether they are related to beer foam potential or stability. On the basis of such experiments, it has been proposed that certain sizes of proteins are important in the formation and stabilisation of foam; for example, 40, 10 and 8 kD proteins have been postulated as major foam stabilising molecules (Lusk et al., 1995). However, it is now widely accepted that the polypeptides of greatest hydrophobic character produce the most stable foam and it is the hydrophobic property that is more important than size (Bamforth, 1985). The use of high gravity brewing techniques is essential for the present and future economic viability of the brewing industry internationally (Murray and Stewart, 1991). High gravity brewing is a procedure that employs wort at higher than normal concentration and therefore requires dilution with water later in the process. By reducing the water employed in the brewhouse, this process increases production capacity without adding to the existing brewing, fermenting and maturation plants. Therefore, most major brewing companies worldwide have revised their production processes to accommodate high gravity

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Fig. 17.4

Change in the levels of hydrophobic peptides during the brewing process (final high gravity beer diluted to 4.5% alcohol by volume).

brewing procedures as a means to reduce capital expenditure and increase process sustainability. Although this process has many advantages (Stewart, 1999), one of the problems that still exists is that beers brewed at higher gravities exhibit poor foam stability (d'Amore et al., 1991). The effect of high gravity brewing on head retention with respect to hydrophobic polypeptide levels has been examined using phenyl sepharose liquid chromatography (Bamforth, 1985) throughout the brewing, fermentation and finishing of high and low gravity worts (Fig. 17.4) (Cooper et al., 1998a). Three notable features of the data are highlighted. At the kettle full stage (when `run-off' from the lauter tun or mash filter is complete and wort boiling begins), the level of hydrophobic polypeptides was similar in the high gravity and low gravity worts despite the use of twice the quantity of malt grist to produce the high gravity wort. (In this case, the high gravity wort was measured at 20ë Plato and the low gravity wort employed was measured at 10ë Plato. 1ë Plato is equivalent to 1 g of glucose dissolved in 100 mL of distilled water at 20 ëC.) This implies there was a major failure to extract hydrophobic polypeptides during the high gravity mash. There was much greater loss of hydrophobic polypeptides during fermentation of the high gravity wort so that by the end of fermentation, the hydrophobic polypeptide content of the high gravity fermented wort was just over 50 mg/L, markedly lower than that of the low gravity fermented wort (90 mg/L). When the high gravity beer was diluted to 4.5% alcohol by volume, equivalent to the low gravity beer, it contained a level of hydrophobic polypeptide less than 50% of the low gravity brewed beer (Cooper et al., 1998b). The head retention of the diluted high gravity brewed beer was less than that of the low gravity brewed beer. This contrasts with the low gravity brewed beer where the hydrophobic polypeptide in this foam accounted for over 40% of the total polypeptide. Therefore, not only is the polypeptide of the high gravity brewed beer reduced, but so is the hydrophobic content of its foam that would adversely influence its stability (Bamforth, 1995; Cooper et al., 1998b). The

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amino acid profiles of hydrophobic polypeptides recovered from beer foam, unlike polypeptides involved in haze formation (where glutamic acid and proline account for 40±50% of the total amino acid composition) have no amino acids present in a distinctive quality (Leiper, 2002). It has already been discussed that the fermentation stage is a key stage where hydrophobic polypeptides are lost during the brewing process (Fig. 17.4). Two factors could account for the loss of hydrophobic polypeptides during fermentation. First, fermentation is known to be responsible for the loss of a large quantity of foam-active substances and this problem is exacerbated during the fermentation of high gravity worts. This loss is principally due to adsorption of foam onto the side of the fermenter. Second, yeast secretes proteolytic enzymes into the fermenting wort and these enzymes have a negative effect on foam stability of finished beer through protein degradation (hydrolysis) that occurs during fermentation and storage (Stewart, 2004). Analysis of proteinase A activity (using a fluorimetric method described by Kondo et al., 1998) in wort and beer during the brewing process (Fig. 17.5) showed, as would be expected, that freshly boiled wort did not contain enzyme activity. However, during fermentation proteinase A was secreted into wort by yeast cells. Proteinase A increased throughout fermentation with the highest enzyme activity occurring at the end. Considerably larger quantities of proteinase A were released during 20ë Plato fermentations compared to the 10ë Plato wort fermentations. During high gravity brewing, increased stress on the yeast, in the form of both elevated osmotic pressure and ethanol concentrations, stimulated the secretion of proteinase A into the wort during fermentation. In vitro studies in our laboratory have shown that both ethanol and increased osmotic pressure (simulated using sorbitol that is not metabolised by brewer's yeast) stimulated the secretion of proteinase by brewer's yeast strains (Brey et al., 2002).

Fig. 17.5

The effect of wort gravity on proteinase A release during fermentation of low (12ë Plato) and high (20ë Plato) gravity worts.

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17.6

Food and beverage stability and shelf life

Gushing

Excess foam in a beer is regarded as deleterious and is known as gushing or `wild beer'. Gushing is the violent, uncontrolled ejection of beer from the package at the time it is opened and involves the loss of a significant portion of the contents. There may be two classes of gushing namely, sporadic and epidemic. Sporadic gushing may occur as a result of minor production deviations that are generally difficult to pinpoint. Epidemic or long-term serious gushing may be caused by several factors. Perhaps the most widely discussed cause is the use of weathered (damp) barley. If barley is harvested when wet, Fusarium or other fungus infection can develop during the malting process, resulting in beer susceptible to serious gushing. The formation of mycotoxins such as deoxynivalent (DON) has been paralleled with the development of gushing potential. The screening of barley and malt for these metabolites may offer a means of reducing beer gushing problems (Heikara, 1980). Other factors, such as increased levels of carbonation or a carbonating system operating without proper controls, can produce beers that have the potential to gush. Calcium oxalate microcrystals in beer are another cause of gushing. These crystals are thought to form nuclei for carbon dioxide gas emissions, but excess treatment and filtration will overcome this cause of gushing. Excessive levels of iron and other nuclei forming particles such as sediments will contribute to gushing problems.

17.7

Light stability

Beer is sensitive to light, especially in the 350±500 nm range. Light at these wavelengths can penetrate clear and green glass containers and cause a nauseous off-flavour in beers bottled in such glass containers and drinking glasses. The beer is said to be `sunstruck' and the aroma and taste referred to as `skunky'. Light instability in beer results from hop components. As already discussed, hops in brewing have a number of roles: they impart bitterness to beer; provide characteristic hop aromas; suppress growth of certain microorganisms, particularly Gram-positive bacteria; assist in beer foam stability and contribute polyphenols to the protein-polyphenol complex during wort boiling. When beer is exposed to light, one of the side chains on the iso--acid (a component of hops) is cleaved and the highly reactive radical that is liberated combines with sulphur-containing compounds (Fig. 17.6) to produce 3-methyl2-butene-1-thiol (MBT). MBT has a skunky-like aroma. MBT has a flavour threshold in the order of parts per trillion, making it one of the most flavouractive substances in beer (Wilson et al., 2001). Specialised hop extracts (produced using liquid CO2 or ethanol as a solvent) have been developed to combat this sensitivity to light (Wilson et al., 2001). In essence, pairs of hydrogen atoms are catalytically added to the isomerised iso-acid, tetrahydro-iso--acid. There are three principal types of such extracts

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Fig. 17.6

537

Mercaptan formation in light-sensitive iso--acid.

(called reduced extracts) currently available on the market: RHO iso--acid, tetrahydro-iso--acid, and hexahydro-iso--acid. All of these materials are bitter to varying degrees, some improve beer-foam cling and stability and protect beer against light-struck-sun-induced skunky flavours. Normally all of these materials are used as a post-fermentation addition to achieve maximum benefit and optimum utilisation. To achieve complete light-strike protection, no iso--acid can be used in any other part of the process. Even repitched yeast (Lusk et al., 1995) with iso--acid absorbed onto its surface will provide sufficient material for photolytic cleavage to occur and the resultant production of MBT and skunky flavours.

17.8

Conclusions

Beer instability involves a number of complex reactions involving proteins, carbohydrates, polyhphenols, metal ions, thiols and carbonyls. There are many diverse types of beer instability involving a number of different microorganisms, chemical species and reactions. Our understanding of these reactions has progressed over the past 25 years, but we are far from a complete comprehension of beer instability reaction systems.

17.9

References

(1985), The foaming properties of beer, J. Inst Brew., 93, 216±219. (1995), Foam: method, myth or magic?, The Brewer, 81, 396±389. BAMFORTH, C.W. (1999), Beer haze, J. Amer. Soc. Brew. Chem., 57, 81±90. BAMFORTH, C.W. (2004), A critical control point analysis of flavour stability of beer, Tech. Quart. Master Brew. Assoc. Amer., 41, 97±103. BARKER, R.L., GRACEY, D.E.F., IRWIN, A.J., PIPASTS, P. and LEISKA, E. (1983), Liberation of staling aldehydes during storage of beer, J. Inst. Brew., 89, 411±415. BEHR, J. and VOGEL R.F. (2009), Mechanisms of hop inhibition: hop ionophores, J. Agric Food Chem., 57, 74±81. BAMFORTH, C.W. BAMFORTH, C.W.

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and STEWART, G.G. (2002), The loss of hydrophobic polypeptides during fermentation and conditioning of high gravity and low gravity brewed beer, J. Inst. Brew., 108, 424±433. BRIGHT, D. (2001), A study of the antioxidant potential of speciality malt. PhD Thesis, Heriot-Watt University, Edinburgh, Scotland. COOPER, D.J., STEWART, G.G. and BRYCE, J.H. (1998a), Hydrophobic polypeptide extraction during high gravity mashing ± experimental approaches for its improvement, J. Inst. Brew., 104, 283±287. COOPER, D.J., STEWART, G.G. and BRYCE, J.H. (1998b), Some reasons why high gravity brewing has a negative effect on head retention, J. Inst. Brew., 104, 221±228. D'AMORE, T., RUSSELL, I. and STEWART, G.G. (1991), Advances in the fermentation of high gravity wort. Proceedings of the European Brewing Convention Congress, Lisbon, pp. 337±344. DALGLEISH, C. (1997), Flavour stability. Proceedings of the European Convention Congress, Amsterdam, pp. 623±659. GILLILAND, B. (1971), Yeast classification, J. Inst. Brew, 77, 276±284. HEIKARA, A. (1980), Gushing induced by fungi. European Brewing Convention Monograph VI, pp. 251±258. IIJIMA, K., SUZUKI, K., OZAKI, K. and YAMASHITA, H. (2006), HorC confers beer-spoilage ability on hop-sensitive Lactobacillus brevis ABBC45cc, J. Appl. Microbiol., 100, 1282±1288. IRWIN, A.J., BARKER, R.L. and PIPASTS, P. (1991), The role of copper, oxygen and polyphenols in beer flavour instability, J. Amer. Soc. Brew. Chem., 49, 140± 149. JACKSON, G., ROBERTS, R.T. and WAINWRIGHT, T. (1980), Mechanism of beer foam stabilization by propylene glycol alginate, J. Inst. Brew., 86, 34±37. KONDO, H., YOMO, H., FURUKUBO, S., FUKUI, N., KAWASAKI, Y. and NAKATANI, K. (1998), Advanced method for measuring proteinase A in beer. Proceedings of the 25th Convention, The Inst. of Brewing, Asia Pacific Section, pp. 119±124. LEIPER, K. (2002), Beer polypeptides and their selective removal with silica gels. PhD Thesis, Heriot-Watt University, Edinburgh, Scotland. LUSK, L.T., GOLDSTEIN, H. and RYDER, D. (1995), Independent role of beer proteins, melanoidins and polysaccharides in foam formation, J. Amer. Soc. Brew. Chem., 53, 93±103. MCMURROUGH, I. and O'ROURKE, T. (1997), New insight into the mechanism of achieving colloidal stability, Tech, Quart. Master. Brew. Assoc. Amer., 34, 271±277. MURRAY, C.R. and STEWART, G.G. (1991), Experience with high gravity lager brewing, Birra et Malto, 44, 52±64. NARZISS, L., MIEDANER, H., GRAF, H., EICHFORN, P. and LUSTIG, G. (1993), Technological approach to improve flavour stability, Tech. Quart. Master Brew. Assoc. Amer., 30, 48±53. PRIEST, F.G. and CAMPBELL, I. (2003), Brewing Microbiology. Academic Press, New York. SAKAMOTO, K., MARGOLLES, A., VAN VEEN, H.W. and KONINGS, W.N. (2001), Hop resistance in the beer spoilage bacterium Lactobacillus brevis is mediated by the ATP-binding cassette multidrug transporter HorA, J. Bact., 183, 5371±5373. SIEBERT, K.J. and LYNN, P.Y. (1997), Mechanisms of beer colloidal stabilization, J. Amer. Soc. Brew. Chem., 55, 73±78. SIMPSON, W.J. (1993), Cambridge prize lecture. Studies on the sensitivity of lactic acid bacteria to hop bitter acids, J. Inst. Brew., 99, 405±411. BREY, S.E., BRYCE, J.H.

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and HAMMOND, J.R.M. (1989), The response of brewing yeast to acid washing, J. Inst. Brew., 95, 347±354. STEWART, G.G. (1999), High gravity brewing, Brew. Guard., 128, 31±37. STEWART, G.G. (2004), The chemistry of beer instability, J. Chem. Edu., 81, 963±968. WILSON, R.J.H., ROBERTS, I., SMITH, R.J. and BIENG, M. (2001), Improving hop utilization and flavour control through the use of pre-isomerized products in the brewery. Tech. Quart. Master Brew. Assoc. Amer., 38, 11±21. SIMPSON, W.J.

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18 Shelf life of wine R. S. Jackson, Brock University, Canada

Abstract: What constitutes shelf life in wine is difficult to define. It is often based on consumer or critic expectation, not objective criteria. Initially, changes are generally beneficial, resulting in a reduction in bitterness, astringency, and a loss of yeasty odors. Subsequent modification usually results in a diminution of fruity aromas. Wines with a longer shelf life typically possess a distinctive varietal aroma and develop an aged bouquet. However, in the absence of these features, or with the development of oxidized and other unpleasant odors, the shelf life of wine may be measured in terms of several months to a few years. The latter may develop as a consequence of failures in the bottle closure, exposure to sunlight, the presence of high temperatures, environmental contaminants, or microbial spoilage. Key words: cork closure, wine aging, wine shelf life, wine off-odors, wine oxidation.

18.1

Introduction

Wine differs from most foods and beverages in not possessing a `best before' date. This reflects ambiguity as to what distinguishes wine deterioration from the maintenance or improvement of its sensory attributes. Opinion varies markedly between wine authorities and consumers, usually based as much on experience as on preference. This situation indicates inconsistency in how wine quality is perceived and rated. It also mirrors the relative importance placed on wine retaining its initial, youthful attributes, versus attributes that develop upon extended aging. The relative weight given these factors can also vary depending on the type of wine. For example, most white wines and roseÂs are preferred with the presence of a fruity fermentation bouquet, combined with a mild varietal

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Shelf life of wine 541 fragrance. In contrast, most red and some white wines are often preferred when the varietal fragrance is more marked and supplemented with oak flavors. The eventual disappearance of varietal and fermentation fragrances in older wines can be accepted (even desired) if replaced by a refined aged bouquet. It is this complex, subtle flavor that provides much of the intrigue and exclusivity to mature, premium vintage wine. Although aging potential is highly regarded by afficionados, there are few objective criteria by which its development can be predicted. It is far easier to explain shelf life loss than its retention. What is considered an acceptable shelf life, and when the wine reaches its optimum, also depends on the production process. For example, beaujolais nouveau (made via carbonic maceration) is considered to be optimal just after production. It maintains its character for several months, but often deteriorates quickly thereafter. In contrast, premium barolos or bordeaux often require many years before developing their desired and traditional characteristics. However, this also depends on the expectations and preferences of the taster. British experts usually prefer well-aged, mellow versions, whereas French commentators often express a favor of the young, austere, astringent version. Similar differences often apply to other wines. Older champagnes are (or were) much appreciated in England, but depreciated in France. Fino sherries have short shelf lives upon bottling (if one prefers its initial attributes), whereas oloroso sherries can retain their character for decades, and for months after being opened. Thus, what is an appropriate or acceptable shelf life for one wine may be unacceptable for another. It is more typical to refer to the shelf life of wines designed to be consumed young than for those produced with long aging in mind. In the former, the desired properties are the retention of the sensory attributes expressed at bottling. These typically refer to a fresh fruity to floral fragrance, with a nonaggressive flavor. In contrast, premium wines often possess attributes unpleasant at bottling, at least to the novice drinker. Prolonged storage is expected to result in an enhancement of sensory quality, and the development of a complex, rich flavor and bouquet. In addition, flavors considered a fault in the majority of wines may be accepted, or even highly regarded in a premium wine. Thus, no precise set of chemical or sensory attributes consistently define wine shelf life. Wine is often considered a natural and artisanal creation of sun and soil, not a standardized commercial product. Another feature distinguishing wine from other beverages is the participation of consumers in its maturation. The shelf life of most products relates to their acceptability at the time of purchase or shortly thereafter. This applies equally to most wines, but to a select number of purchasers, shelf life reflects the wine's aging potential ± how long the wine can be stored before it passes its `peak' (in reality, an extended but changing plateau), before losing its desirable sensory attributes.

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18.2

Food and beverage stability and shelf life

Factors affecting wine stability and shelf life

18.2.1 Prior to bottling Viticultural conditions One of the current credos of modern wine making is that quality originates in the vineyard. It is the rationale given for emphasis on the wine's provenance (terroir). While partially true, the marketing advantage of the terroir concept is even more significant. That aside, the quality of grapes arriving at the winery door does set outer limits on the attributes the wine may possess, including its potential shelf life. However, this topic is too large for detailed discussion in this chapter. For details, the reader is directed to sources such as Jackson (2008) and White (2003). Some generalities are worth noting, however. Warm climatic regions have usually been considered to produce wines unsuitable for long shelf life, especially white versions. Warm climates tend to result in grapes being harvested with low acid levels. Low acidity not only favors the oxidation of wine phenolics (favoring the presence of the more readily oxidated phenolate state), but also promotes the breakdown of fruit esters. The latter donate most of the fruity fragrance of young white wines. pH values above 3.5 also favor the growth of spoilage lactic acid bacteria. Their action not only further reduces wine acidity (producing of a `flat' taste), but also results in the generation of off-flavors. Warm conditions may also promote the loss of desired and distinctive varietal fragrance compounds in grapes, and the development of high sugar contents. High sugar contents increase the likelihood of stuck fermentation (their premature termination) and the presence of high residual sugar contents. The latter give dry table wines an undesired sweet aspect. It also makes the wine much more liable to microbial spoilage. Wine produced in cool climate conditions seldom experience these problems, and historically have had longer shelf lives. Modern viticultural practices can help reduce these limitations, before and during harvest, and advanced wine-making procedures can further subdue the historic disadvantages of warm climate conditions. To offset the development of low acid/high pH juice, grapes can be picked earlier in the season, before grape metabolism consumes its malic acid content. Earlier harvesting also helps limit the development of undesirably elevated sugar contents, as well as the degradation of flavorants in the skins. Harvesting early in the morning can result in grapes being cooler when reaching the winery. Alternatively, the grapes may be cooled on reaching the winery. Fermenting the juice cool favors the production and retention of higher amounts of fruit (acetate) esters. In addition to macroclimatic factors, seasonal variations and microclimatic conditions can significantly modify the potential characteristics and shelf life of a wine. These are well recognized, and often used to advantage, when favorable, in marketing wine from a particular region. Some factors such as drainage conditions, susceptibility to frost, and slope of the land cannot be easily modified. However, some negative features can be modified without excessive difficulty. Disease control is a major example. Healthy grapes are far more

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Shelf life of wine 543 likely to produce wines with longer shelf lives than diseased grapes. The latter may be contaminated with laccase, a polyphenol oxidase with a much wider range of phenolic substrates than grape polyphenol oxidase. In addition, infected grapes are much more susceptible to the formation of light-diffracting, brownish tannin colloids. Infected grapes also tend to possess higher concentrations of soluble proteins (thaumatin-like and chitinases). These can generate a protein haze in bottled wines. More intractable are the disturbed sugar, acid and flavor constituents of diseased grapes. The major exception to the undesirability of infection involves `noble rotted' white grapes, given very slow pressing to avoid the release of fungal mucopolysaccharides. Such Botrytis-infected grapes, under special late-season conditions, can generate the most precious, and expensive, white wines, for example sauternes and trockenbeerenausleses. Training and pruning choices also affect optimal grape ripening, as do fertilization and irrigation decisions. An example of how shelf life can be adversely affected by growing conditions involves the development of an `untypical aged' (UTA) off-odor, about a year after bottling. It is variously considered to be reminiscent of naphthalene, furniture polish, or wet wool. It appears to be correlated with grapes having suffered stress during the growing season (Sponholz and HuÈhn, 1996). Minimizing undue (usually drought) stress is the principal means by which the development of this fault can be avoided. In addition, there is evidence that the incidence of UTA can be reduced by the addition of thiamine and diammonium phosphate at fermentation, as well as the addition of ascorbic acid (150 mg) (Rauhut et al., 2001). Modern technology, in combination with GPS, has led to a new term in viticulture: `precision viticulture'. It is beginning to permit the grape grower to understand and regulate one of the major limiting factors in grape quality ± vineyard variability, and thus wine shelf life. Variable conditions throughout the vineyard are reflected in non-uniform grape maturity ± inclusion of unripe and overripe grapes reduce overall wine quality. Understanding the origins of vineyard variability offers the opportunity for selective adjustment of viticultural practice for particular regions of a vineyard, or selective timing of harvest throughout the vineyard to provide fruit of more uniform quality. Vinification conditions As with viticultural conditions, fermentation procedures can significantly affect shelf life. For example, it has become standard practice for white wines to minimize oxygen exposure after crushing, during fermentation, and maturation. Red wines may be permitted limited air exposure during fermentation, usually associated with pumping over (mixing of the grape seeds and skins with the fermenting juice). Pumping over helps equilibrate temperature differences throughout the fermenting must and extract anthocyanins. The oxygen absorbed can assist fermentation. Pumping over is unnecessary for white wines due to the absence of seeds and skins during fermentation. The absence of oxygen tends to favor the production of acetate (fruity smelling) esters. These are especially important to the flavor and shelf life of

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white wines with limited or no distinctive varietal aroma. Cool fermentation temperatures also favor the formation of acetate esters and their retention. Correspondingly, most white wines are fermented at cool temperatures. In addition, oxygen favors the synthesis of C6 alcohols and aldehydes, which can donate herbaceous off-odors, as well as oxidize varietal aromatics. The production and retention of acetate esters, and reduced generation of C6 alcohols and aldehydes, can be further accentuated by the addition of antioxidants such as sulfur dioxide and ascorbic acid (Moio et al., 2004), the judicious selection of yeast strain (high ester producers) and maturation at cool temperatures. Nonetheless, with some cultivars, limited oxygen access during fermentation has been associated with the development of more complex flavors that develop in the bottle. Thus, the style and design of the wine can influence the procedures used during vinification. Wine intended for immediate enjoyment (but limited shelf life) accentuate development of a fruity flavor, whereas alternative procedures are used when a more mature bouquet is desired (providing and benefiting from prolonged storage). Where extended shelf life is desired for a white wine, the juice are often left in contact with the crushed grapes, rather than rapid separation from the seeds and skins upon crushing. This skin contact (maceration) period permits the increased extraction of distinctive (varietal) aromatics from the skins (their predominant location). Coincident with skin contact is also the increased uptake of phenolic compounds from the skins (those in the seeds are rarely extracted due to the maceration seldom lasting more than 24 hours). This practice must be used judiciously, however, to avoid the excessive uptake of flavonoid phenolics. These can result both in the wine taking on a bitterish aspect (undesired in most white wines), and enhancing the likelihood of early browning (Simpson, 1982). To minimize the latter possibility, juice exposed to skin contact is often given slight aeration. Early oxidation of flavonoids favors their precipitation during fermentation. Gentle pressing of the crushed grapes (as with pneumatic presses) further limits the uptake of flavonoid phenolics. A technique increasingly used in the production of premium white wines is sur lies maturation. This involves leaving wine in contact with the lees (dead and dying yeast cells) for several months at the end of fermentation. Typically sur lies maturation occurs in small cooperage (~250 l), to avoid the generation of hydrogen sulfide and reduced sulfur odors (notably mercaptans). These can easily form in the thick layer of yeast cells that develop in large-volume cooperage. The treatment has several benefits in terms of shelf life. Primarily, it reduces the wine's browning potential. This appears to involve the interaction between membrane sterols, released by autolysing yeast cells, and precursors of brown phenolics (notably catechins and their dimers) (MaÂrquez et al., 2009). The procedure can also add aromatic yeast metabolites, such as ethyl octanoate and ethyl decanoate. These ethyl esters could extend shelf life by augmenting the fruity aspect of the wine. Lees may also reduce the sensory defects generated by 4-ethylphenols (Chassagne et al., 2005), and the sensory impact of carbonyl compounds such as diacetyl. Exposure to yeast lees also diminishes the

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Shelf life of wine 545 production of sotolon (possessing a curry-like odor) during bottle aging (Lavigne et al., 2008). The benefit/detriment value of the latter depends on the type of wine and the expectations of the consumer. Most wines designed for early consumption (short shelf life) are matured in inert containers (often stainless steel) prior to bottling. Maturation in oak cooperage is normally reserved for wines designed for medium- to long-bottle aging. This is frequently viewed as contributing to the aromatic complexity of the wine. Although true, it can also extend shelf life by supplying small quantities of oxygen (stabilizing a red wine's color) and increasing the concentration of ethyl esters (Salinas et al., 1996). Red wines are considerably less susceptible to oxidation than white wines. This is partially accounted for by their higher phenolic concentration. oDiphenols are particularly active in consuming oxygen and protecting other wine aromatics from oxidation. In addition, the generation of acetaldehyde (a consequence of phenol oxidation) helps stabilize the wine's color, by forming oxidation resistant anthocyanin-tannin polymers. With most red wines, fermentation and maturation procedures are aimed at producing wine that possesses a shelf life of up to five years. This usually means that the wine will show a fresh berry to jammy fragrance, combined with any distinctive aroma the grape cultivar may possess. For wines designed for extended aging (shelf life greater than 5±10 years), production procedures are adjusted to give the wine an enhanced phenolic content. Although desirable in promoting long aging potential, it also demands patience on the part of the consumer. It takes many years for the wine to develop its optimal attributes. In contrast, when the intent is to generate a red wine that is drinkable almost immediately, carbonic maceration may be employed. One of the principal drawbacks of carbonic maceration is that it also results in a wine with a comparatively short shelf life (rarely more than a few years). To give most red wines their deep red color, the juice is fermented in contact with the seeds and skins. The anthocyanins that provide the red color are almost exclusively found in the grape skins. Coincident with the extraction of anthocyanins are other phenolic compounds. The latter donate red wine's typical bitter, astringent character. They are also crucial to giving the wine most of its antioxidant potential (and extended shelf life). These phenolics (mostly flavonoids) are also directly involved in stabilizing the wine's color, and in the gradual shift from the purplish cast of a young wine to the brickish shade of a mature red wine (Fig. 18.1). When these changes are gradual, they are an accepted and expected aspect of aging. If they occur early, and are associated with an oxidized flavor, they are a fault and severely shorten the wine's shelf life. The shelf life of all wines is enhanced by a desirable acid content (and low pH). Where juice acidity is undesirably low, it can be adjusted upwards by the addition of tartaric acid. Tartaric acid is preferred because it is a natural grape constituent, but primarily due to its being poorly metabolized by most bacteria (thereby reducing the likelihood of microbial spoilage).

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Fig. 18.1 The shift in color of red wines during aging as measured by a change in the absorption spectra: I, 1-year-old; II, 10-years-old; III, 50-years-old. (From RibeÂreauGayon `Shelf-life of wine', pp. 745±772, in Handbook of Food and Beverage Stability: Chemical, Biochemical, Microbiological and Nutritional Aspects (G. Charalambous, ed.). Copyright Elsevier (1986), reproduced by permission).

18.2.2 Storage conditions of bottled wine Oxygen exposure It is essential to minimize oxygen uptake to maximize shelf life. Despite all precautions, sufficient oxygen eventually enters to overpower the wine's antioxidant potential, inducing irreversible sensory degradation. Currently, it is impossible to predict how much, or when, oxidation will reach a level sufficient to negatively impact shelf life. It depends on the amounts of natural or added antioxidants, the rate and extent of oxygen ingress, the presence of spoilage microbes, the sensitivity of impact aromatics to oxidation, and the sensory threshold of oxidative deterioration. What is feasible is limiting the rate and degree of oxygen ingress, and adjusting wine conditions to either restrict the activation of oxygen or favor the consumption of oxygen in sensorially neutral or beneficial ways (for example, mollifying a red wine's astringency). Molecular oxygen is itself relatively stable under wine conditions. To be involved in oxidation, it usually must be converted to a more active form. These may include hydrogen peroxide, singlet oxygen, superoxide, or the hydroxyl radical. Their formation is facilitated primarily by trace amounts of iron and copper ions, and to a lesser extent, by light exposure. The latter is thought to involve the interaction of compounds such as riboflavin. The best understood oxidative reactions in wine involve phenolics, notably odiphenols. The oxidation of flavonoid phenolics, notably catechins (and their polymers) to quinones, changes their chromic properties, generating pigments with a yellowish to brownish color. These may also react with other wine constituents, such as acetaldehyde, that favor polymerization between flavonols, or between flavonols and anthocyanins. The latter tend both to stabilize the color of red wines and generate the brickish shift associated with bottle aging. The color shift may also involve the polymerization of oxidized tartaric acid

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Shelf life of wine 547 (glyoxylic acid) with flavonoid phenolics, to generate orangish to yellow byproducts, notably xanthylium derivatives (Oszmianski et al., 1996). In white wines, the oxidative generation of brownish pigments is largely thought to involve nonflavonoids, such as caftaric and fertaric acids, flavonoids such as quercetin and kaempherol, and small amounts of catechins. Some additional browning products may arise from the oxidation of galacturonic acid, and the formation of Maillard products from residual sugars. The presence of limited amounts of oxygen can also favor the degradation of the fragrance generated by fruit esters and various terpenes. In addition, less desirable fragrances, derived from aldehydes, diethylesters, heterocycles and thiols, may accumulate. Temperature Storage temperature is possibly second only to oxygen as a factor unfavorably affecting shelf life. Traditionally, wine has been stored under relatively constant, cool conditions. Temperatures above 25 ëC are generally viewed as not only speeding maturation, but also generating undesirable flavor changes (Singleton, 1962). Because aging is primarily physicochemical, heat can both activate and speed the reactions involved. However, different reactions possess distinct activation energies. Thus, a temperature change does not affect all reactions equivalently (Table 18.1). Cool storage tends to retain the fresh, fruity character of most young wines. For example, the concentrations of fragrant acetate esters, such as isoamyl and hexyl acetates are stable at 0 ëC, whereas they rapidly hydrolyze at 30 ëC (Fig. 18.2). In contrast, the formation of less aromatic ethyl esters is rapid at 30 ëC, but negligible at 0 ëC. Temperature also has marked influences on the liberation of norisoprenoid aromatics from their glycosidic precursors (Leino et al., 1993). This may account for some of the increased concentration of trimethyl-1,5dihydronaphthalene (TDN) in `Riesling' wine aged at 30 versus 15 ëC (Marais et al., 1992), as well as the content and types of monoterpene alcohols found in some wines (Rapp and GuÈntert, 1986). High temperatures also favor the degradation of sugars to furfurals and pyrroles. Whether similar activation affects the conversion of norisoprenoid precursors to spiroesters, such as vitispirane and theaspirane, or to hydrocarbons such as TDN and ionene, is unknown. For most wines, exposure to temperatures 40 ëC and above prompts rapid quality deterioration. Carbohydrates in the wine undergo Maillard and thermal degradation reactions, turning brown and producing a baked (maderized) flavor. The wine also tends to develop a sediment. Even temperatures about 30 ëC produce evident losses in fragrance within a few months. From the limited data available, it appears that traditional cellar temperatures (about 10 ëC) permit the prolonged retention of most fruit esters, while not excessively inhibiting other desired aging reactions. Nevertheless, temperatures up to 20 ëC do not appear inimical to the sensory modifications associated with aging, at least for red wines. Some of the changes that accrue under different storage temperatures are illustrated in Fig. 18.2.

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Table 18.1 Differences in aroma composition of several Riesling wines as affected by aging and storage temperature 1982

1978

1973

Acetate esters i-amyl acetate i-butyl acetate 2-phenylethyl acetate

107a 16.7 38.7

58.4 4.2 25.1

Ethyl esters butanoic acid ester hexanoic acid ester succinic mono-acid ester

15 47 128

Diethyl esters succinic acid ester malic acid ester

41 96

Carbohydrate degradation products 2-furfural 4.1 furan-2-carbonic acid ethyl 0.4 ester 2-formylpyrrole ± 5-hydroxymethylfurfural (HMF) ± Monoterpenes linalool -terpineol 3,7-dimethyl-1,5-octadien3,7-diol

16.8 8.4 33.3

Year

1964

1976 (frozen)

1976 (cellar storage)

5.9 2.8 1.9

10.9 3.1 5.7

243 32.1 27.2

27.1 6.0 3.2

19 72 338

16 47 438

30 77 415

40 48 152

41 63 339

384 640

656 1375

738 969

117 262

407 729

13.9 0.6

39.1 2.4

44.6 2.8

2.2 0.7

27.1 2.0

2.4 ±

7.5 1.0

5.2 2.2

0.4 ±

1.9 0.5

1.0 3.2 12.6

± 7.0 9.2

± 8.3 15.1

19.4 10.8 28.6

2.8 16.6 28.3

Data from Rapp and GuÈntert (1986). a Relative peak height on gas chromatogram (MM).

While cool temperatures are normally viewed as promoting the slow, favorable maturation of wine, storage under cold conditions can promote the precipitation of tartrate and other salt crystals. Occasionally, consumers may mistake potassium tartrate crystals as glass slivers. Because of this potential misinterpretation, wines are normally cold stabilized before bottling to minimize, though not entirely eliminate, their development. In addition to affecting the rate and direction of wine development, rapid and marked temperature fluctuations can sufficiently affect wine volume to loosen the cork seal. It can lead to wine seepage, oxygen ingress, and wine spoilage by permitting the reactivation of dormant microbes in the wine. If the wine freezes, the volume increase can be sufficient to force the cork out of the bottle.

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ß Woodhead Publishing Limited, 2011 Fig. 18.2 Effect of storage temperature and duration on the concentrations of (a) hexyl acetate, (b) i-amyl acetate, (c) diethyl succinate, and (d) dimethyl sulfide in a Colombard wine. (From Rapp and Marais `The shelf life of wine: changes in aroma substances during storage and ageing of white wines', pp. 891±921, in Shelf Life Studies of Foods and Beverages (G. Charalambous, ed.). Copyright Elsevier (1993), reproduced by permission).

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Food and beverage stability and shelf life

Light exposure Light exposure may have two, independent, detrimental effects on wine. Near ultra-violet and blue radiation can activate oxidative reactions, whereas direct exposure to sunlight may provoke heat-induced damage. Most light-activated reactions are thought to involve the production of potent oxidants, notably singlet oxygen. Its production appears to involve the activation of an electron on a pigment (presumably riboflavin) and its association with molecular oxygen. Examples of light-associated problems include the formation of a copper-induced haze and the shrimp to skunky thiol off-odor of `lightstruck' champagne (Carpentier and Maujean, 1981). Additional off-odors, unrelated to thiols, associated with champagne exposed to light have been noted by D'Auria et al., (2003). Light exposure, notably full sunlight, can cause rapid changes in wine temperature. The increased temperature can both promote undesirable reactions, generating off-odors, and produce pressure on the bottle closure. Repeated and rapid shifts in temperature (and wine volume) weaken the adherence of the closure to the bottle neck, leading to wine seepage and oxygen ingress. The best protection against light-induced spoilage is keeping the wine in lowlit conditions or in the dark. Alternately, bottling in UV and blue absorbing glass can limit photo-induced shortening of shelf life. pH and acidity Relatively low pH values are preferred for several reasons. They provide wines with a fresh taste, promote microbial stability, reduce browning potential, and diminish the need for SO2 addition. Regrettably, it also favors the breakdown of acetate (fruit) esters to their constituent moieties (an alcohol and acetic acid) (Marais, 1978). The monoterpene content may also be affected. For example, the concentration of geraniol, citronellol, and nerol may rise, whereas those of linalool, -terpineol, and hotrienol decline at low pH values. In red wines, color intensity and hue are enriched at lower pH values. Low pH also minimizes the concentration of the more readily oxidizable, phenolate form of phenolics. For example, there are nine times more phenolate ions at a pH of 4.0 than a pH of 3.0. This also helps to explain why white wines are less susceptible to browning at low pH values. Vibration It is commonly thought that vibration is detrimental to wine shelf life. Other than the resuspension of sediment in older wines, induced by agitation during serving, there is no evidence that vibration itself is detrimental. The one research paper on the issue notes some minor physicochemical changes that may occur with marked and prolonged vibration (Chung et al., 2008). However, even those noted seem unlikely to be of sensory significance.

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Shelf life of wine 551 Environmental contaminates Contaminants affecting wine shelf life can arise from a host of sources, but most can be grouped as originating from winery equipment or additives, bottle closures, or the storage environment. Probably the principal reason given for wine rejection results from the presence of corky odors. These may be generated by a range of compounds, but the most common appears to be 2,4,6-trichloroanisole (TCA) (Sefton and Simpson, 2005). It typically diffuses into wine from cork exposed to the pesticide pentachlorophenol at some stage during bark growth, stopper production, or storage. Several microbes metabolize the pesticide into TCA (a nontoxic but moldy-smelling compound at trace amounts). It may also be absorbed from winery cooperage or other wooden structures treated with the insecticide. Another source of corky odors, seemingly arising from winery cooperage, is 2,4,6tribromoanisole (Chatonnet et al., 2004). In this case it is the by-product of the microbial transformation of a fire-retardant and wood preservative, 2,4,6-tribromophenol. Another moldy odor noted as a frequent contaminant is 2-methoxy3,5-dimethylpyrazine (Simpson et al., 2004). Other moldy odors, potentially provoking consumer rejection, are 1-octen-3-one, 2-methylisoborneol, guaiacol, 1-octen-3-ol, and geosmin. These are all microbial by-products generated on cork or winery equipment. The shift to artificial corks and screw caps has markedly reduced, but not eliminated, their incidence in wine. Synthetic corks and screw caps stored in an environment contaminated by volatile microbial by-products may absorb these compounds and subsequently release them into wine. Winery equipment is also the predominant source of metallic contamination. Alternative origins include agents used in fining, notably bentonite. As noted later in the chapter, metal ions participate in the induction of several forms of casse (haze) in bottled wine.

18.3

Changes during the shelf life of wine

The chemical changes that commonly and negatively affect shelf life are those associated with oxidation and the hydrolysis of esters. Those involved with reduction, polymerization, structural rearrangement, and volatilization are more likely to be initially beneficial. Their relative importance depends on the type of wine, its production, its varietal origin, storage conditions, and the expectations of the consumer. Initially, most modifications enhance wine sensory characteristics. Subsequently, changes in the varietal aroma, fermentation bouquet, and color progressively modify the wine's original attributes. These alterations may or may not be viewed as desirable. Eventually, varietal aroma, fermentation bouquet and color begin to fade. If these sensory attributes are not replaced by nuances, termed the aged bouquet, the wine's shelf life will be comparatively short (1±5 years). However, if the aged bouquet develops and is appreciated, it supplies the wine with long-aging potential. Most premium wines possess this feature, supplying a shelf life that may extend beyond 20 years.

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Food and beverage stability and shelf life

18.3.1 Appearance All wines change color with age, becoming more brownish (white wine becoming darker, whereas red wines become lighter). The relative acceptability of these changes depends on how rapidly they develop and if they are normally expected. The most studied series of reactions involve select flavonoids. Their oxidation results in the formation of o-diquinones and hydrogen peroxide. The o-diquinones can polymerize with other phenolics, some of which can rearrange to form oligomeric o-diphenols. These, in turn, can oxidize and polymerize in a similar series of reactions forming larger polymers. Because quinones absorb light non-uniformly, tending to be brown colored, successive oxidations explain the expression `brown begets brown' (Singleton, 1987). The hydrogen peroxide generated during o-diphenol oxidation can activate the oxidation of other constituents, notably ethanol to acetaldehyde (Timberlake and Bridle, 1976), and presumably glycerol to glyceraldehyde and dihydroxyacetone (Laurie and Waterhouse, 2006). In addition, hydrogen peroxide may be consumed in Fentonlike reactions with phenolics (Walling and Johnson, 1975), involving the catalytic activity of iron and possibly copper, or reactions leading to phenolic degradation, such as the conversion of gallic acid to muconic acid derivatives (Singleton, 1987). It is in these secondary oxidation reactions that oxygen is incorporated into organic wine constituents. Color changes in white wines The most common and undesirable color change in white wines is termed premature browning. It is normally measured as a noticeable increase in absorption at 420 nm. The exact chemical nature of the, presumably multiple, chromophores involved still remains unclear. Most are thought to be derived from oxidation of the wine's limited phenolic content. The most prevalent of these is caftaric acid, a common constituent of grape juice. After hydrolysis, caffeic acid can significantly increase oxidative browning by polymerizing with flavonoids. Because the concentration and precise chemical nature of a wine's phenolic content vary from cultivar to cultivar, from year to year, vinification procedures, as well as storage conditions, predicting the occurrence of browning has proven intractable. Because molecular oxygen is thought to be essential for premature browning, its erratic appearance among samples of the same wine has often been ascribed to closure problems. Although white wines have a lower content of oxidizable phenolic compounds, they are more susceptible to oxidative browning than red wines. This apparent anomaly results from the ability of most flavonoid phenolics (more common in red wines) to consume large amounts of oxygen without noticeable browning, retarding the undesirable sensory consequences of oxidation. In addition, the paler color and milder flavor of most white wines make the consequences of oxidation evident sooner and of greater sensory significance. Besides oxidized phenolics, additional sources of colored material include phenolics that have a yellowish color in their natural (non-oxidized) state, notably kaempferol and quercetin. These are not considered a fault unless they

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Shelf life of wine 553 occur at abnormally high concentrations. For example, quercetin may occasionally induce a yellowish flavonol haze due to the precipitation of its fine crystals (Somers and Ziemelis, 1985). Another source of yellowish to golden coloration in white wines comes from the formation of Maillard products. In wine, this usually results from a reaction between residual sugars and organic bases, such as amines, amino acids, or free amino acid groups on proteins. The initial step involves the dehydration of sugars to deoxysones. These are more electrophilic than their parent sugars and react with nitrogen bases to generate various chromophores. In addition to generating a diverse range of pigmented compounds, some Maillard by-products are aromatic. Furaldehydes, with caramel-like flavors, are a classic example. At cellar and room temperatures, Maillard reactions occur slowly, but can eventually add to the admired golden coloration of aged, sweet, white wines. In baked fortified wines, notably madeiras, Maillard reaction products contribute significantly to the basic color and flavor of these wines. Another potential source of color change comes from metal-induced structural modifications of galacturonic acid (derived from pectin breakdown). These age-induced color changes are considered normal and often highly regarded by wine connoisseurs. The development of a slightly pink cast in white wines is an infrequent problem with wines produced from cultivars such as Sauvignon blanc, Pinot gris, and AlbaÄrino. It can usually be corrected, but at considerable expense, by opening the effected bottles, treating with polyvinylpolypyrrolidone (PVPP), and rebottling. It appears to be associated with exposure of the wine to oxygen. Its exact chemical nature is unknown but is suspected to be derived from flavan3,4-diols (leucoanthocyanins). These slowly dehydrate to flavenes under reducing conditions. Upon exposure to oxygen they can readily oxidize to their corresponding colored flavylium state. Color changes in red wines The color changes in red wines are much more chemically complex than those found in white wines (Fulcrand et al., 2006; Jackson, 2008). Nonetheless, the ultimate visual effect is relatively similar, the eventual shift toward the brown. Initially the changes are considered beneficial, with the depth of color generally increasing and possessing a purplish cast. Subsequently, color depth decreases as the cast becomes increasingly brickish. As long as the change is not associated with the development of an oxidized flavor, and does not occur atypically rapidly, the color change is not considered a fault. It is expected and appreciated as a sign of proper maturation. Rapid color shifts are, however, viewed as indicating a defect and can markedly influence consumer acceptance. The color of red wines comes primarily from anthocyanins. Five types occur in wine, of which the most prevalent and stable is malvin. In grapes, anthocyanins typically are bound with glucose, and are arranged in loose, stacked complexes. During and after fermentation, these complexes tend to break down, and the sugar moiety may be lost. This leaves the pigment more susceptible to oxidation and color degradation. This tends to be avoided by polymerization

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Food and beverage stability and shelf life

with the other principal group of flavonoids in wine, catechins and their polymers (procyanidins and condensed tannins). Polymerization may involve direct bonding between catechins with anthocyanins, or indirectly via the interaction of a by-product of phenol oxidation (the oxidation of ethanol to acetaldehyde). A host of other reactions products have recently been discovered that generate yellowish to brickish-colored pigments (Fulcrand et al., 2006; Jackson, 2008). The relative significance of these to the color shift of red wines is still being assessed. As noted, a color shift is considered normal and expected. They are not considered to contribute to a shortened shelf life. It is only when there may be insufficient flavonoids to stabilize the color (limit oxidative color loss), or there is excessive oxygen penetration, that an unacceptable premature browning and an oxidized flavor develop. Hazes and deposits Shelf life is negatively influenced by haze formation. To avoid its development, winemakers often go to great lengths. It is such a regular part of enologic practice that haze formation in bottled wine is now rare. Even the sediment (precipitated tannin/potassium tartrate complexes) that used to characterize most red wines is now relatively uncommon. If it occurs, it is not considered a fault. Deposition of sediment may even be considered a sign of quality. The only evidence that this view might possibly have some validity is the increased presence of several fruit esters in unfiltered wine (Moreno and Azpilicueta, 2006). Whether these esters would remain at levels sensorially significant by the time sediment might form is unestablished. Turbidity can be provoked by the presence of excessive amounts of iron or copper ions. Examples of colloidal hazes induced by the presence of metal ions are those produced by insoluble ferric phosphate in white wines (from the oxidization of ferrous phosphate); complexes formed between oxidized (ferric) ions and anthocyanins or tannins in red wines; and the development of a reddishbrown haze/deposit by the interaction of sulfides, copper ions and suspended proteins in white and occasionally rose wines. The development of any of these is likely to result in consumer rejection. Microbial growth may also generate a haze. Although extensive yeast growth is usually necessary to produce evident turbidity (~105 cells/ml), Brettanomyces has been reported to form a distinct haze at 102 cells/ml (EdeleÂnyi, 1966; Amerine et al., 1980). Bacterial growth may also provoke haze generation. A classic example is the problem called ropiness. It is produced by the profuse synthesis of mucilaginous polysaccharides by some strains of Oenococcus oeni and Pediococcus. When the bottle is undisturbed, the polysaccharides hold the bacteria together in long silky chains that appear like floating threads. When dispersed, the polysaccharides give the wine an oily look and possibly a viscous texture. Occasionally wine may form crystals of potassium tartrate on the underside of corks, or form slender crystals that may be resuspended if the bottle is

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Shelf life of wine 555 agitated. Tartrate crystal formation is more likely to form if the wine is stored at abnormally low temperatures. Additional sources of innocuous crystallization include a flavonol haze in white wines (fine yellow crystals of quercetin), a phenolic deposit generated by a fine precipitate of off-white to fawn-colored ellagic acid crystals (derived from extended exposure to oak chips), and crystals of the calcium salts of saccharic and mucic acids (in botrytized wines). Another precipitation problem occasionally observed in bottles of red wine is a lacquer-like finish on the inner surfaces of the bottle. The film apparently consists of a thin layer of tannins, anthocyanins and protein (Waters et al., 1996). Occasionally a film-like deposit, termed `masque', may also develop on the inner surfaces of champagne bottles. It appears to originate from the interaction of albumin (added as a fining agent) and fatty acids from yeasts (Maujean et al., 1978). Both may limit sales as they can give the false impression that the wine is turbid. 18.3.2 Gustatory changes One of the typical benefits derived from aging red wine is a reduction in bitterness and astringency. This benefit has usually been ascribed to the polymerization and precipitation of flavonoid phenolics. Conversely, if small phenolics remain in solution, or tannin polymers hydrolyze, perceived bitterness may increase. New evidence, however, suggests that bitterness arises more from nonflavonoids (ethyl esters of hydroxybenzoic and hydroxycinnamic acids) than flavonoids (Hufnagel and Hofmann, 2008). Other than the gustatory significance of phenolic polymerization, few other marked changes in taste occur during the shelf life of wine. Occasionally, a loss of sweetness in dry white wines may be noted. This probably arises from the hydrolysis of acetate esters. Their fruity fragrance in wine often induces the perception of sweetness, due to a learned association between fruity odors and sweetness (Prescott, 2004). Perceived sourness may also decrease slightly due to the slow esterification of tartaric acid (Edwards et al., 1985). Otherwise, noticeable gustatory changes usually accrue from microbial spoilage. 18.3.3 Olfactory changes The most significant modifications affecting shelf life involve aromatic deterioration. These have been most studied in white wines. The fresh, fruity fragrance of most young white wines, ascribed to the presence of acetate esters, is primarily the by-products of yeast metabolism. Because they often accumulate to concentrations significantly above their sensory threshold, and equilibrium with their acetic acid and alcohol constituents, they slowly hydrolyze back to their moieties after fermentation. This results in an eventual loss in their sensory impact. The rate at which these events affect the sensory attributes of wine depends on their importance to the fragrance (especially in white wines with

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Food and beverage stability and shelf life

little distinctive varietal aroma), the concentration of the individual esters, their specific sensory thresholds, the storage temperature, and the wine's pH. In Riesling wines, most esters fall to equilibrium levels within about six years at 14 ëC (Rapp et al., 1985). Similar findings have been found with other cultivars (Marais and Pool, 1980; Ferreira et al., 1997). Oxidation accentuates their decline (Ferreira et al., 1997). Other esters may hydrolyze even earlier. For example, the sulfur-containing (3-methylthio-propyl)-acetate was detected only during the first month after fermentation. The degree to which a wine experiences these changes may partially depend on its phenolic content. For example, caffeic acid can markedly retard the degradation of acetate esters, and especially ethyl esters of fatty acids (Roussis et al., 2005, 2007). The presence of caffeic acid also retards the oxidation of terpenes. The detection and olfactory significance of compounds depends not only on their sensory thresholds, and how other wine constituents affect their perception (synergistically or antagonistically), but also on the individual sensitivity of the taster and their interest in assessing such details. In contrast to the decline in acetate ester concentration, the content of diethylesters of some dicarboxylic acids tends to rise (Table 18.1). Some components of an aged bouquet appear to depend on the degradation of grape-derived carotenoids. A major example is 1,1,6-trimethy1-1,2-dihydronaphthalene, a sensorially important vitispirane. Other sources of aging-derived fragrances include carbohydrate dehydration products such as 2-furfural and 2hydroxymethy1-5-furfural. The latter are best known in relation to heat exposure (madeira maturation and oak barrel toasting), but can also form slowly at room and cellar temperatures. Although some aromatic changes are unaffected by the wine's redox potential, others definitely are. Generally low redox (reductive) potentials are considered beneficial, whereas high redox (oxidative) potentials are detrimental. For example, wines depending primarily on monoterpene alcohols for their varietal character are damaged by oxygen ingress. Frequently, oxygen converts monoterpene alcohols into their corresponding oxides. Not only are these less volatile, but they possess qualitatively different aromas. For example, linalool oxides have flavor thresholds in the 3000±5000 g/l range, versus 100 g/l for linalool (Rapp, 1988). -Terpineol, an oxide of linalool, possesses a musty, pine-like odor, in contrast to the floral aspect of linalool. The result is a loss in the desired varietal (floral) distinctiveness of wines produced from cultivars such as Riesling, GewuÈrztraminer, Viognier, and Muscat. Another example of fragrance loss involves the oxidation of thiol flavorants (conversion to disulfides or other constituents). In Sauternes, most polyfunctional thiols, typical of the young wine, are no longer detectable two years after bottling (Bailly et al., 2009). The principal exception is 3-sulfanyhexan-1-ol. It remains at concentrations above its threshold value for several years. Other varietally significant aromatics, such as -terpineol, sotolon, several fermentation esters, ethyl esters, and oak maturation volatiles tend to remain for at least five years. Occasionally, thiol compounds accumulate during aging, at least in wines aged

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Shelf life of wine 557 on lees. Examples are phenylmethanethiol and ethyl 3-sulfanylpropionate (Tominaga et al., 2003). Like most white wines, roseÂs have comparatively short shelf lives. RoseÂs often lose much of their fruity character within one to two years. This has been correlated with the degradation of 3-mercaptohexan-1-ol and 3-mercaptohenyl acetate (Murat et al., 2003; Murat, 2005). The limited presence of anthocyanins and tannins appears to be involved, their concentration being insufficient to provide adequate oxidative protection. This also probably explains another feature of the usual short shelf life of rose wines ± their tendency to rapidly take on an orangish coloration due to oxidation. That the fruity character of rose wines partially depends on acetate esters (notably phenethyl acetate) further clarifies the poor aging characteristics of roseÂs. Maintaining a low redox potential is generally considered essential for retaining the desirable attributes of a wine. Nonetheless, the adoption of screw cap closures may induce the development of a reduced sulfur odor, shortening shelf life. Its occurrence may partially depend on the oxygen impermeability of the foam liner used in the aluminum cap (Lopes et al., 2009). Alternatively, others consider the problem results from conditions associated with grape cultivation or fermentation. Although mercaptans are universally considered a fault, hydrogen sulfide can be considered acceptable, or even desirable, at just detectable values. In addition, the slow buildup of dimethyl sulfide (DMS) is often considered desirable, if not too obvious. In `late harvest' white wines, du Plessis and Loubser (1974) found DMS contributed to the full-bodied, bottle-aged characters of the wines. Segurel et al. (2004) found it contributed to the fruity, as well as the aged truffle and black olive attributes of Syrah and Grenache wines. Storage at cellar temperatures retards the formation of DMS. In addition to the loss or modification of grape- and yeast-derived fragrances, a wide range of new compounds develop during in-bottle aging. Some are beneficial, others undesirable, notably those resulting from oxidation. Although the origin of acetaldehyde is the best understood, its relevance to the `oxidized' odor of table wines remains doubtful (Escudero et al., 2002). Its distinctive odor is typically not detectable in table wines considered oxidized, nor does the free (volatile) concentration of acetaldehyde rise upon short-term, intentional oxidation (Singleton et al., 1979; Escudero et al., 2002). Although acetaldehyde is produced as an indirect by-product of phenol oxidation, free acetaldehyde is rapidly removed by its reaction with other wine constituents. It is only in some fortified wines, notably sherries, that an aldehydic odor is considered appropriate and expected. When wines are exposed to oxygen for several weeks, the treated wines develop characteristics described as `cooked vegetables,' and `pungent.' These attributes have been correlated with the presence of furfural and hexanal, respectively. Their pronounced odors may mask the wine's natural fragrance. Other aromatic constituents potentially involved in the development of an oxidized odor appear to be 2-nonenal, 2-octenal, and benzaldehyde (Ferreira et al.,

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Food and beverage stability and shelf life

1997). Escudero et al. (2000) also associated methional with a cooked cabbage odor in oxidized wine. Additional studies have correlated oxidative odors with the production of methional, phenylacetaldehyde, 4,5-dimethyl-3-hydroxy-2(5H)furanone (sotolon), and trimethyl-1,5-dihydronaphthalene (TDN), particularly at high (45 ëC) temperatures and/or low pH values (Silva Ferreira et al., 2003). Quinones generated during oxidation may react with amino acids. These reactions could potentially enhance flavor by generating aldehydes and ketones in Strecker-type degradations. It is a moot point whether some of the attributes associated with oxidation, such as honey (phenylacetaldehyde), hay and wood (eugenol), should be viewed as oxidation off-odors, or the benefits of aging. This situation is typical of issues relating to wine shelf life ± there is no clear definition of what constitutes an oxidized odor. In addition to the development of undesirable oxidized odors, and the loss of varietal and fermentation fragrances, associated with a shortened shelf life, there may be the formation of an attribute, termed the aged bouquet, that enhances shelf life. Examples of desirable compounds, formed during bottle-aging in red wines, matured in oak, include 4-ethylphenol, 2-methoxy-4-ethylphenol, 2furaldehyde, 5-butyl-4-methyldihydrofuran-2(3H)-one (whisky lactone) (PeÂrezPrieto et al., 2003; Fernandez de Simon et al., 2006). In Sauternes, desired, agerelated constituents include homofuraneol, theaspirane, -decalactone and abhexon (Bailly et al., 2009). The conditions that favor an aged bouquet development are far less understood than those that limit their formation. Examples of the latter are high pH, limited skin contact before or during fermentation, warm storage temperatures, exposure to sunlight, ingress of oxygen, and low alcohol content. Examples of terms used to describe an aged bouquet may include `leather,' `cigar box,' `truffle' for red wines, and `sun-dried linen' for white wines. These terms are used almost universally, regardless of the wine's varietal origin. Microbial spoilage is thankfully comparatively rare, but can rapidly shorten shelf life. Not only can it generate unsightly turbidity, noted above, but also can generate a variety of off-odors. The most common spoilage organisms are strains of acetic acid bacteria, some lactic acid bacteria, and yeasts such as Brettanomyces. At near threshold values, certain of their metabolic by-products, notably ethyl acetate, acetic acid, 4-ethyl phenol and related compounds, may be viewed as donating a desirable complexity to the flavor. Their presence has occasionally been mistaken as a component of the wine's geographic (terroir) attributes, presumably by those having high threshold values for these compounds. At recognition values they are highly undesirable.

18.4

Evaluating wine shelf life

Estimating the aging potential (shelf life) of a wine is one of the favorite pastimes of wine critics and connoisseurs. Regrettably, these predictions are

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Shelf life of wine 559 based on past recollections, not on objective or verifiable criteria. Thus, they are only a general guide, assuming ideal storage conditions. Examples are views that fino sherry and beaujolais nouveau wines possess short shelf lives (several months); that most white wine begins to show oxidative browning within two to three years, and experience a perceptible loss in fruity odors within a year; most regular red wines lose much of the fruity and varietal aromas within five years; sparkling wines begin to lose their characteristic effervescence with a few years; and most ports show little or no aromatic improvement subsequent to bottling ± with the exception of vintage ports (reaching `maturity' within 15 to 20 years). Despite being a useful guide, nothing at present can accurately predict how any particular wine will develop. Nonetheless, a few researchers are investigating nondestructive, in situ methods of assessing some aspects of shelf life. These include nuclear magnetic resonance (NMR) and spectroscopy. NMR has the potential to quantify certain wine constituents, indicating for example the presence of spoilage amounts of acetic acid (Weekley et al., 2003) and acetaldehyde (Sobieski et al., 2006). Because of its expense, its application may be appropriate only to verify the drinkability of rare vintage wine sold at auction. More affordable and readily available is spectroscopy. Regrettably, its analytic range is currently limited to assessing the degree of oxidative browning in white wines ± absorption at 420 nm (Skouroumounis et al., 2003), and total and free sulfur dioxide contents (Cozzolino et al., 2007). Spectroscopy is most readily applicable to wine in clear flint glass bottles. For amber and antique green glass, which absorbs intensely in the blue range, absorption at 540 nm and 540 nm or 600 nm, respectively, can be substituted (Skouroumounis et al., 2003). Nonetheless, with empty versions as a control, it can be applied to wine in colored glass bottles. Absorption at 420 nm is typically used as a rough indicator of oxidation, but Silva Ferreira et al. (2003) recommend forced oxidation as an indicator of the potential of a wine to undergo premature oxidation. It can be used to assess the need for additional antioxidants prior to bottling.

18.5

Preventing wine quality deterioration at or post-bottling

18.5.1 Fining, filtration and disinfection Wine is typically fined to remove soluble proteins, excess tannins, metal ions, or other constituents that could lead to haze formation or off-odor production. In addition, the wine is usually given a final polishing filtration prior to bottling, to remove particulate material that might subsequently precipitate in the bottle. Filtration is usually not designed to remove microorganisms. Such disinfection is typically unnecessary due to their relatively low numbers and the unfavorable conditions for growth in bottled wine. Correspondingly, other than regular cleaning after manufacture, bottles are typically not sterilized prior to filling. Only in sweet wines of low alcohol content may sterile (> 0.5 ) filtration into sterilized bottles be advisable to avoid microbial spoilage.

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Occasionally, some low priced, sweet wine may be pasteurized prior to bottling for the same reason. 18.5.2 Sulfur dioxide addition Once bottled, shelf life largely depends on the storage conditions and protective nature of the enclosure. Retarding oxygen ingress is one of the primary methods, as it favors optimal maturation and limits the development of undesirable flavors. Nonetheless, oxygen can gain access to bottled wine from air present in the headspace of the bottle, present in cellular voids in natural cork, seep in via faults or creases in the cork, or slowly diffuse through the cork. Although oxygen ingress may be minimized by a range of procedures, sulfur dioxide is typically added to limit the damage caused by what does enter. The amount added depends largely on the type of wine. White wines, having lower phenolic contents, need more protection than red wines. Also, red wines typically receive less sulfur dioxide to avoid partial bleaching of the wine's anthocyanin content. Sulfur dioxide owes much of its antioxidant activity to its reaction with peroxide, generated by the oxidation of phenols. This limits the oxidation of important fermentation odors, notably acetate esters, and varietally important aromatics, such as monoterpenes, and thiols (Blanchard et al., 2004). Sulfur dioxide also limits the oxidation of ethanol to acetaldehyde, binds acetaldehyde in a nonvolatile complex, and participates in the regeneration of phenols from quinones. Sulfur dioxide is also used in low alcohol, sweet table wines to reduce the incidence of microbial spoilage. It often remains at a level sufficient to be effective for periods of up to one to two years, usually sufficient to cover the normal shelf life of most white wines. Red wines, with long aging potentials, usually have sufficiently low pH values and high tannin contents to provide adequate microbial protection in the absence of oxygen. 18.5.3 Bottle closure and orientation Oxygen uptake is primarily restricted by the closure, but can also be reduced at filling by flushing air out of the bottle, usually with carbon dioxide. Subsequent upright positioning of the bottles for 24 h permits pressurized gas in the headspace, compressed on cork insertion, to escape between the neck and the stopper. Despite the elasticity of the cork, it takes about 24 h for a tight seal to fully develop. Any residual pressurized CO2 in the headspace is absorbed into the wine, equilibrating the pressure within the bottle and the atmosphere. Nitrogen gas is not recommended due to its poor solubility in wine. Pressurized nitrogen in the headspace would continue to exert its force against the cork. Alternatively, bottles may be put under a partial vacuum before filling. De Rosa and Moret (1983) showed that vacuum and flushing, and vacuum application, reduced average SO2 loss after 12 months from 28 to 16 mg/l and 5 mg/l, respectively. Reduction in sulfur dioxide content is often considered an

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Shelf life of wine 561 indication of the oxygen ingress. Application of a vacuum also avoids a pressure buildup in the headspace on closure insertion. With the introduction and market acceptance of a variety of bottle closures, there has been an upsurge in research on their effects on shelf life. Previously, the only variables were the quality of natural cork, its degree of compression in the bottle, and stopper length. Currently, the choice of closures has expanded to include agglomerate cork, synthetic corks, glass stoppers, and aluminum screw caps. Because of the importance of limiting oxygen access, most of the studies have concentrated on oxygen penetration and bottle-to-bottle variability. Natural cork appears to be associated with a short period of oxygen uptake, from the cellular voids in cork cells. Uptake subsequently declines to about 2± 6 l O2/day, finally stabilizing within a year at about 0.1±2 l O2/day (Lopes et al., 2007). In contrast, use of screw caps and agglomerate cork seems to be associated with less than 1 l O2 ingress per day, equivalent to that of the highest quality natural corks. Regrettably, the oxygen permeability of natural cork tends to exhibit variation (Caloghiris et al., 1997), occasionally by up to four orders of magnitude (Hart and Kleinig, 2005). In contrast, agglomerate cork and screw caps show high consistency in oxygen permeability. Synthetic corks tend to show undesirably high diffusion rates (Godden et al., 2001), often within the range of 6±12 l O2/day. Such high rates limit shelf life and restrict their use to wines intended for early consumption (less than two years). Nonetheless, where early maturity is desired, the increased oxygen permeability of synthetic corks might have some benefit. Although long, high quality, natural corks can provide good protection from oxygen uptake, corks are still potentially plagued by additional problems. The principal is their periodic association with a corked off-odor. This moldy odor is primarily, but not exclusively, caused by migration of 2,4,6-trichloroanisole (TCA) from the cork (Juanola et al., 2005). It is generally viewed as the most common fault in wine, and can severely shorten its shelf life. Various procedures have been developed to remove this contaminant from corks, as well as coatings developed to retard (if not prevent) its migration into wine. Contamination with other sources of moldy odors and extraneous off-odors is less common. This situation has led to a trend away from natural cork closures in many markets For white wines, there is general consensus as to the detrimental effect of oxygen ingress. There is more controversy concerning the effects of the slow, minimal, oxygen uptake from cork closures on red wine maturation, especially premium versions intended for extended bottle aging. Although opinions differ widely, recent evidence suggests that red wines do not need, at least at detectable levels, oxygen ingress for their maturation (Hart and Kleinig, 2005). Minimal oxygen contact retards the loss of the oxidative protection provided by both sulfur dioxide and tannins. Thus, color density is retained for a longer period and hue changes are slowed. Loss of the fruity fragrance of the wine is also delayed, further extending the wine's youthful characteristics. Bottle orientation is also important in minimizing oxygen ingress. For natural cork closures, horizontal positioning is essential for long-term storage. Contact

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between the stopper and the wine is required to maintain a stable moisture content. Otherwise, the cork will dry, losing its resilience and elasticity. Both are essential to retaining its protective sealing properties (Bartowsky et al., 2003). Nonetheless, serious consequences from upright storage may not appear for more than two years (Lopes et al., 2006). It may also take several years before upright storage results in distinct browning and the development of an oxidized odor (Skouroumounis et al., 2005). In contrast, hybrid cork stoppers, consisting of a combination of ground cork (often with its lignin content removed) and microspheres of a synthetic polymer, are comparatively moisture independent. Bottles so closed, like those with screw caps, can safely be stored upright. 18.5.4 Storage container The use of glass bottles has a long tradition dating back to the late 1500s. Its prime benefit, relative to shelf life, is its inertness and gas impermeability. Its transparency also facilitates direct observation of visual defects. Nonetheless, light transmittance permits some types of haze development, can induce lightstruck off-odors, and cause heat-induced problems. Surprisingly, white wines, those most susceptible to these disruptions, are typically the least protected, being bottled in clear or light-colored glass. Despite the predominant use of glass bottles, its position is being challenged by other containers. Improvements in the oxygen impermeability of lightweight, PET (polyethyleneterephtalate) bottles has led to their tentative adoption for wine storage (Giovanelli and Brenna, 2007). Currently, bag-in-box containers (Biuatti et al., 1997) are the principal alternative to glass. Here, the principal factor limiting shelf life is the attachment of the spigot that permits oxygen ingress (Armstrong, 1987). Other containers, such as aluminum cans and carton boxes are becoming popular in some markets for the casual wine consumer. Although the principal value of bag-in-box containers is their consumer friendliness, the plastic liner can have a little known, unexpected benefit. It effectively absorbs some wine off-odors. Examples are the absorption of 2,4,6trichloroanisole (TCA), napthalene, and 1,1,6-trimethyl-1,2-dihydronaphthanene (TDN) (Capone et al., 2002). Regrettably, pleasant smelling aromatics may also be `scalped.' This feature has also been detected with cork and artificial closures (Capone et al., 2003). 18.5.5 Temperature control As noted previously, the temperature of wine storage not only significantly affects the speed and characteristics of wine aging, but also can shorten its shelf life. Temperatures above 25 ëC, and especially above 30 ëC, modify the flavor characteristics of table wines in ways unacceptable to most consumers. Typically, wines for long storage are held at a relatively constant temperature of about 10 ëC. This retards most chemical reactions in the wine, providing

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Shelf life of wine 563 conditions optimal for what is considered favorable maturation. Colder temperatures may even further extend the shelf life, but at the expense of excessively slow maturation (Table 18.1).

18.6

Sensory significance of shelf life changes

A major concern for wine makers and wine merchants alike is consumer alienation. This not only results in direct financial loss, connected with bottle returns, but also indirect loss, associated with the forfeiture of repeat sales. Nonetheless, in most cases, the source(s) of customer dissatisfaction are unknown. There is no organized system in the wine industry for assessing why consumers have negative reactions to particular wines. When consumer surveys are conducted, it is critical that questions be worded to avoid biasing the response. In addition, the questions should be relevant to real-life situations (KoÈster, 2003). For example, questioning about faults can exaggerate their apparent presence, and preference choices in a laboratory or shopping mall will unlikely generate valid data relating to purchase activity. Of visual faults, oxidative browning is universally unacceptable among wine industry professionals. Despite this, there is little definitive evidence that consumers view this issue as equally important. The significance of wine color deviance appears to depend markedly on the experience or training of the assessor (Williams et al., 1984). Rejection appears most often to be associated with odor and taste faults. Commonly stated reasons are the presence of corked, oxidized, and vinegary attributes. Most corked odors probably arise from the presence of above threshold amounts of 2,4,6-trichloroanisole (though, as noted previously, corky/ moldy odors may be donated by other compounds). Oxidized odors are frequently mentioned, but exactly what consumers mean when they use this term is far from clear. In most instances, the mention of a vinegary odor is probably inappropriate. It probably refers to their perception that the wine is inappropriately or excessively sour. Nonetheless, it could legitimately arise from above threshold amounts of acetic acid (often associated with ethyl acetate). Other potential sources of shortened shelf life include a naphthalene-like odor found in some white wines (termed untypical aging flavor), a prune-like odor in red wines that age prematurely (possibly caused by 3-methyl-2,4-nonanedione) (Pons et al., 2008), baked odors (due to exposure to high temperatures), and the presence of a reduced sulfur (shrimp-like) odor (found in some white wines closed with screw caps). Although there is contention among wine industry professionals as to the latter's origin, it is also uncertain as to its importance to consumers. From my experience, the wine industry is lucky that consumers frequently do not recognize wine faults, and correspondingly do not consider them a shelf life issue. Even wine critics are often ambivalent on wine faults, accepting barnyardy (ethyl phenol) odors as a quality in some famous RhoÃne wines, and nail polish (ethyl acetate) odors in prestigious Sauternes. Thus, wine

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faults, and their shelf life significance, are often perceptions influenced by experience and exterior biases, not objective decisions.

18.7

Future trends

Because oxidation continues to be one of the principal causes of shortened shelf life, there is considerable interest in new means of addressing this issue. This is especially so, due to the increasing insistence of government and consumer advocacy groups on limiting the use of sulfur dioxide, despite it being the safest and most effective antioxidant currently available. Alternatives under investigation include compounds such as glutathione. Glutathione is a natural grape antioxidant, but is rapidly consumed in oxidative reactions during fermentation. Thus, for it to be of value in extending wine shelf life it must be added at bottling. Its addition, alone or in combination with caffeic acid (the principal hydroxycinnamic acid in wines) has been shown to delay the degradation of important flavorants in wines, notably acetate esters and terpenes (Roussis et al., 2005). Gallic acid is another natural phenolic that can limit oxidation (Lambropoulos and Roussis, 2007). N-acetyl-cysteine also can play an antioxidant role, in association with caffeic acid in wines (Sergianitis and Roussis, 2008). A very different approach, the immobilization of the yeast for fermentation in carragenate beads, has apparently been found successful in limiting browning (Merida et al., 2007). Other approaches are attempts to better predict wine shelf life. Examples are tests to assess a wine's susceptibility to browning (Palma and Barroso, 2002) or temperature damage (Sivertsen et al., 2001). As noted previously, techniques such as NMR and spectroscopy hold promise. They have the potential for assessing the presence of aroma compounds, off-odors, additives, and contaminants in unopened bottles. While still primarily in the research stage, improvements in their use and access may facilitate their transfer from the laboratory to the winery or wholesale merchant. In addition to issues about commercializing NMR and spectroscopic assessment, a precise correlation between wine chemistry and perceived quality is lacking. This requires further investigation to establish the compounds that are essential to a wine's distinctive sensory attributes. This will likely involve techniques such as gas chromatography-olfactometry (GC-O) (Plutowska and Wardencki, 2008), combined with data on odor activity value (OAV). The odor activity value is derived by dividing the concentration of a constituent by its detection threshold. Most significant aromatic constituents tend to possess OAVs above unity. Nonetheless, the sensory importance of a compound can only be confirmed by selectively adding them to a model wine, and assessing its impact on aroma detection (Grosch, 2001). Such a procedure has been successfully used in assessing the chemical nature of the varietal aroma of several wines (Hashizume and Samuta, 1997; Ferreira et al., 1998; Guth 1998; Kotseridis et al., 2000).

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18.8

Sources of further information and advice

Additional information on issues noted in this chapter may be found in books such as Jackson (2008), and reviews by Aldave et al. (1993), Marais (1986), RibeÂreau-Gayon (1986), Rapp and GuÈntert (1986), Rapp and Marais (1993) and Singleton (2000). Another informative review, but dealing with beer, is provided by Vanderhaegen et al. (2006).

18.9

References

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and DUBOURDIEU D (2009), `Impact of oxygen dissolved at bottling and transmitted through closures on the composition and sensory properties of a Sauvignon blanc wine during bottle storage' J Agric Food Chem, 57, 10261±10270. MARAIS J (1978), `The effect of pH on esters and quality of Colombar wine during maturation' Vitis, 17, 396±403. MARAIS J (1986), `Effect of storage time and temperature of the volatile composition and quality of South African Vitis vinifera L. cv. Colombar wines' in G Charalambous (ed.), The Shelf Life of Foods and Beverages, Amsterdam, Elsevier, pp. 169±185. MARAIS J and POOL HJ (1980), `Effect of storage time and temperature on the volatile composition and quality of dry white table wines' Vitis, 19, 151±164. MARAIS J, VAN WYK CJ and RAPP A (1992), `Effect of storage time, temperature and region on the levels of 1,1,6-trimethyl-1,2-dihydronaphthalene and other volatiles, and on quality of Weisser Riesling wines' S Afr J Enol Vitic, 13, 33±44.  RQUEZ T, MILLA  N C, SOUQUET J-M and SALMON J-M (2009), `Effect of different yeast MA strains and their culture conditions on the prevention of wine model solution browning by yeast lees' J Agric Food Chem, 57, 3771±3779.  tude sur un pheÂnomeÁne de masque observe MAUJEAN A, HAYE B and BUREAU G (1978), `E en Champagne' Vigneron Champenois 99, 308±313. MERIDA J, LOPEZ-TOLEDANO A and MEDINA M (2007), `Immobilized yeasts in -carragenate to prevent browning in white wines' Eur Food Res Technol 225, 279±286. MOIO L, UGLIANO M, GENOVESE A, GAMBUTI A, PESSINA R and PIOMBINO P (2004), `Effect of

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antioxidant production of must on volatile compounds and aroma shelf life of Falanghina (Vitis vinifera L.) wine' J Agric Food Chem, 52, 891±897. MORENO NJ and AZPILICUETA CA (2006), `The development of esters in filtered and unfiltered wines that have been aged in oak barrels' Int J Food Sci Technol, 41, 155±161. MURAT M-L (2005), `Recent findings on rose wine aromas. Part 1: identifying aromas studying the aromatic potential of grapes and juice' Aust NZ Grapegrower Winemaker, 497a, 64±65, 69, 71, 73±74, 76. MURAT M-L, TOMINAGA T, SAUCIER C, GLORIES Y and DUBOURDIEU D (2003), `Effect of anthocyanins on stability of a key-odorous compound, 3-mercaptohexan-1-ol, in Bordeaux rose wines' Am J Enol Vitic, 54, 135±138. OSZMIANSKI J, CHEYNIER V and MOUTOUNET M (1996), `Iron catalyzed oxidation of (+)catechin in model systems' J Agric Food Chem, 44, 1712±1715. PALMA M and BARROSO CG (2002), `Application of a new analytic method to determine the susceptibility of wine to browning' Eur Food Res Technol, 214, 441±443.  PEZ-ROCA JM, MARTIÂNEZ-CUTILLAS A, PARDO-MIÂNQUEZ F and GO  MEZPEÂREZ-PRIETO LJ, LO PLAZA E (2003), `Extraction and formation dynamics of oak-related volatile compounds from different volume barrels to wine and their behavior during bottle storage' J Agric Food Chem, 51, 5444±5449. PLUTOWSKA B and WARDENCKI W (2008), `Application of gas chromatography-olfactometry (GC±O) in analysis and quality assessment of alcoholic beverages ± a review' Food Chem, 107, 449±463. PONS A, LAVIGNE V, ERIC R, DARRIET P and DUBOURDIEU D (2008), `Identification of volatile compounds responsible for prune aroma in prematurely aged red wines' J Agric Food Chem, 56, 5285±5290. PRESCOTT J (2004), `Psychological processes in flavour perception' in AJ Taylor and D Roberts (eds), Flavour Perception. London, Blackwell Publishing, pp. 256±278. RAPP A (1988), Wine aroma substances from gas chromatographic analysis. In HF Linskens and JF Jackson (eds), Wine Analysis. Berlin, Springer-Verlag, pp. 29±66. È NTERT M (1986), `Changes in aroma substances during the storage of white RAPP A and GU wines in bottles' in G Charalambous (ed.), The Shelf Life of Foods and Beverages. Amsterdam, Elsevier, pp. 141±167. RAPP A and MARAIS J (1993), `The shelf life of wine: changes in aroma substances during storage and ageing of white wines' in G Charakanbous (ed.), Shelf Life Studies of Foods and Beverages. Amsterdam, Elsevier, pp. 891±921. È ber VeraÈnderungen der Aromastoffe È NTERT M and ULLEMEYER H (1985), `U RAPP A, GU waÈhrend der Flaschenlagerung von Weibweinen der rebsorte Riesling' Z Lebensm Forsch, 180, 109±116. È HNERTZ O È RBEL H, POUR NIKFARDJAM M, LOOS U and LO RAUHUT D, SHEFFORD PG, ROLL C, KU (2001), `Effect of pre- and/or postfermentation addition of antioxidants like ascorbic acid or glutathione on fermentation, formation of volatile sulfur compounds and other substances causing off-flavours in wine' in Proc 26th OIV Conf, Adelaide, pp. 76±82. RIBEÂREAU-GAYON P (1986), `Shelf-life of wine' in G Charalambous (ed.), Handbook of Food and Beverage Stability: Chemical, Biochemical, Microbiological and Nutritional Aspects, Orlando, FL, Academic Press, pp. 745±772. ROUSSIS IG, LAMBROPOULOS I and PAPADOPOULOU D (2005), `Inhibition of the decline of volatile esters and terpenols during oxidative storage of Muscat-white and Xinomavro-red wine by caffeic acid and N-acetyl-cysteine' Food Chem, 93, 485±492.

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Shelf life of wine 569 and TZIMAS P (2007), `Protection of volatiles in a wine with low sulfur dioxide by caffeic acid or glutathione' Am J Enol Vitic, 58, 274±278. SALINAS MR, ALONSO GL, NAVARRO G, PARDO F, JIMENO J and HUERTA MR (1996), `Evaluation of the aromatic composition of wines undergoing carbonic maceration under different aging conditions' Am J Enol Vitic, 47, 134±144. SEFTON MA and SIMPSON RF (2005), `Compounds causing cork taint and the factors affecting their transfer from natural cork closures to wine ± a review' Aust J Grape Wine Res, 11, 188±200. SEGUREL MA RAZUNGLES AJ RIOU C SALLES M and BAUMES RL (2004), `Contribution of dimethyl sulfide to the aroma of Syrah and Grenache noir wines and estimation of its potential in grapes of these varieties' J Agric Food Chem, 52, 7084±7093. SERGIANITIS S and ROUSSIS IG (2008), `Protection of volatile esters and terpenes during storage of a white wine and a model wine medium by a mixture of N-acetylcysteine and caffeic acid' Eur Food Res Technol, 227, 643±647. SILVA FERREIRA AC, HOGG T and GUEDES DE PINHO P (2003), `Identification of key odorants related to the typical aroma of oxidation-spoiled white wines' J Agric Food Chem, 51, 1377±1381. SIMPSON RF (1982), `Factors affecting oxidative browning of white wine' Vitis, 21, 233± 239. SIMPSON RF, CAPONE DL and SEFTON MA (2004), `Isolation and identification of 2-methoxy3,5-dimethylpyrazine, a potent musty compound from wine corks' J Agric Food Chem, 52, 5425±5430. SINGLETON VL (1962), `Aging of wines and other spiritous products, acceleration by physical treatments' Hilgardia 32, 319±373. SINGLETON VL (1987), `Oxygen with phenols and related reactions in musts, wines, and model systems: observation and practical implications' Am J Enol Vitic, 38, 69±77. SINGLETON VL (2000), `A survey of wine aging reactions, especially with oxygen' in Proc Am Soc Enol Vitic 50th Anniv Annu Meeting, Davis, CA, American Society for Enology and Viticulture, pp. 323±336. SINGLETON VL, TROUSDALE E and ZAYA J (1979), `Oxidation of wines. I. Young white wines periodically exposed to air' Am J Enol Vitic, 30, 49±54. SIVERTSEN HK, FIGENSCHOU E, NICOLAYSEN F and RISVIK E (2001), `Sensory and chemical changes in Chilean Cabernet Sauvignon wines during storage in bottles at different temperatures' J Sci Food Agric, 81, 1561±1572. SKOUROUMOUNIS GK, KWIATKOWSKI M, SEFTON MA, GAWEL R and WATERS EJ (2003), `In situ measurement of white wine absorbance in clear and in coloured bottles using a modified laboratory spectrophotometer' Aust J Grape Wine Res, 9, 138±148. ROUSSIS IG, LAMBROPOULOS I

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SEFTON MA and WATERS EJ (2005), `The impact of closure type and storage conditions on the composition, colour and flavour properties of a Riesling and a wooded Chardonnay wine during five years' storage' Aust J Grape Wine Res, 11, 369±384. SOBIESKI DN, MULVIHILL G, BROZ JS and AUGUSTINE MP (2006), `Towards rapid throughput NMR studies of full wine bottles' Solid State Nucl Magnet Reson, 29, 191±198. SOMERS TC and ZIEMELIS G (1985), `Flavonol haze in white wines' Vitis, 24, 43±50. È HN T (1996), `Aging of wine: 1,1,6-trimethyl-1,2-dihydroSPONHOLZ WR and HU naphthalene (TDN) and 2-aminoacetophenone' in Proceeding of the Fourth International Symposium on Cool Climate Viticulture and Enology, Geneva, New York, NY State Agricultural Experimental Station, pp. VI-37±57. TIMBERLAKE CF and BRIDLE P (1976), `Interactions between anthocyanins, phenolic

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compounds, and acetaldehyde and their significance in red wines' Am J Enol Vitic, 27, 97±105. TOMINAGA T, GUIMBERTAU G and DUBOURDIEU D (2003), `Role of certain volatile thiols in the bouquet of aged Champagne wines' J Agric Food Chem, 51, 1016±1020. VANDERHAEGEN B, NEVEN H, VERACHTERT H and DERDELINCKX G (2006), `The chemistry of beer aging ± a critical review' Food Chem, 95, 357±381. WALLING C and JOHNSON RA (1975), `Fenton's reagent. V. Hydroxylation and side-chain cleavage of aromatics' J Am Chem Soc, 9, 363±367. WATERS EJ, PENG Z, POCOCK KF and WILLIAMS PJ (1996), `Lacquer-like bottle deposits in red wine' in Proc 9th Aust Wine Ind Tech Conf, Adelaide, Australia, Winetitles, pp. 30±32. WEEKLEY AJ, BRUINS P, SISTO M and AUGUSTINE MP (2003), `Using NMR to study full intact wine bottles' J Mag Reson, 161, 91±98. WHITE RE (2003), Soils for Fine Wines. New York, Oxford University Press. WILLIAMS AA, LANGRON SP, TIMBERLAKE CF and BAKKER J (1984), `Effect of color on the assessment of ports' J Food Technol, 19, 659±671.

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19 The stability and shelf life of fruit juices and soft drinks P. Ashurst, Ashurst and Associates, UK

Abstract: This chapter considers the microbiological, physical and chemical factors that affect the stability of fruit juices and soft drinks, and the impact those factors have on the shelf life of the products. It looks at the impact that various processing techniques have in extending product shelf lives. Packaging plays a critical role in containing beverages and extending their shelf life and the use of various types of packaging is considered. Shelf life determination and accelerated testing are considered briefly as are possible alternatives to thermal pasteurization. Key words: fruit juices, soft drinks, processing techniques, pasteurization, packaging, shelf life, product stability.

19.1

Introduction

Unlike some food items, fruit juices and soft drinks cannot exist as articles of trade without the packaging that is needed to contain the product, protect it from deterioration, loss and damage and provide a vehicle to advise the consumer of the contents and other essential information. The interaction of product and packaging is thus key to ensuring that these products reach the consumer at the level of quality that the manufacturer intended. In addition to containing the product, the packaging has other important functions which include making the product look attractive to fulfil a marketing objective. In most countries it is now a statutory requirement for the consumer to be advised of the shelf life of the product and this is normally provided by printing the product's shelf life as a `best before' date. As an alternative, a `use by' date may be employed in products where there is a potential food safety issue. This

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latter term is only used (in the context of this chapter) for freshly squeezed juices that have a very short shelf life which is maintained by cold temperature distribution. The determination of the shelf life of a product is an essential part of its development phase and there are many considerations that must be taken into account when the shelf life is set. These include: · compliance with any statutory requirement for an indication of product durability · to ensure compliance with any nutritional claims made · to meet customer demands and minimize the risk of product failure and writeoff · to inform the distribution, marketing and retailer demands. Technically, the shelf life is established as the period of time in which the particular combination of product and packaging retains the quality and taste set by the manufacturer. Any processing that the product receives is an integral part of the shelf life determination. Any substitution of raw material, packaging or processing can then be evaluated to ensure maintenance of the desired shelf life. It is very important for manufacturers to understand any changes that occur within the predetermined shelf life under various conditions that should include all anticipated markets. Overall, the shelf life of a beverage is an important indicator of production consistency and the confirmation of quality systems. 19.1.1 Fruit juices At their simplest, fruit juices are obtained by pressing fruit of appropriate ripeness and collecting the expressed juice. Many consumers still carry out this operation in homes and other places where the juice will be consumed within a matter of hours. In such circumstances, the issue of the shelf life and stability of the juice is of little relevance. However, fruit juices are now sold across the globe and represent a multi-billion dollar industry that is dominated by orange juice. In order to transport, package and sell fruit juice to the consumer, its shelf life and stability are of major importance to both ensure that the consumer is provided with a product of acceptable quality and to avoid the loss of product of substantial commercial value. Fruit juices are generally available in various forms. There is a rapidly increasing market sector for fresh juice that is described as `not from concentrate' (NFC). This sector is divided into product that is unpasteurized and must be sold through a cold distribution chain and consumed within a few days of pressing, and product that is subjected to a `light pasteurization' (typically a few seconds at around 90±92 ëC) and packed into clean, but not aseptic, containers that are also distributed through a cold distribution system but with a shelf life of several weeks. The major market sector for fruit juices is based on product that is reconstituted from juice concentrated in the country of processing, shipped to the main market where water is added to reconstitute the typical composition of

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The stability and shelf life of fruit juices and soft drinks 573 fresh juice and packaged aseptically into containers that allow a shelf life of up to one year. In all these sectors, the related issues of the stability of the product and its shelf life are of the utmost importance to producer and consumer alike. This chapter will examine in more detail the outline processes that are involved in the production of fruit juices, the treatments needed to achieve the required stability and the factors that will impact on the resulting quality and shelf life of the product. 19.1.2 Soft drinks Traditionally, soft drinks were prepared by dissolving granulated sugar in specially treated water, or alternatively diluting liquid sugar with this water. A variety of ingredients including preservatives, flavouring and colouring agents, carbon dioxide and acidulants (invariably either citric or phosphoric acid) were then added. Other constituents such as fruit juice or comminuted fruit, artificial sweeteners, antioxidants, ingredients to deliver clouding and foam were added, depending on the particular product being made. More recently, `diet' soft drinks in which the sugar has been replaced with an artificial sweetener (typically aspartame or sucralose) have become very popular. Soft drinks are now prepared almost exclusively using the pre-mix system whereby the blended syrup, prepared using ingredients outlined above, after flash pasteurization if necessary (85 ëC for 15±30 seconds would be typical), is mixed in appropriate proportions with treated water prior to delivery to the filler. If the end product is to be carbonated, it has traditionally been cooled to 1±3 ëC before arrival at the filler in order to minimize loss of carbonation and facilitate filling. Fillers and ancillary equipment capable of handling the product at ambient temperatures have recently been introduced. Most food and drink products are supplied to consumers in some form of primary packaging and in many cases secondary packaging as well. Beverages, however, are totally dependent on primary packaging as a means of containing the product. This is true for all types of beverages but for carbonated drinks the packaging plays a greater role by retaining not only the liquid but also the CO2 that gives the product one of its principal characteristics. This chapter provides an insight into the processes used to manufacture and package soft drinks and the factors that affect their stability and shelf life. 19.1.3 Packaging Development of the beverage industry for fruit juices and soft drinks is paralled by the development of suitable packaging that provides physical support for the product in addition to providing a reasonable shelf life for the contents. All early long life fruit juices and carbonated products were packaged in glass which even today provides a performance benchmark for product protection despite its principal disadvantages of weight and brittleness. Today, a significant proportion of all beverages are packed in either some form of plastic container,

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plastic laminated paperboard or other flexible packing most of which have only made a significant contribution to the markets during the last 30 years. Metal cans still provide an important alternative to the other types of packaging. The packaging of carbonated products is, with few exceptions, limited to glass, metal cans and plastics. It is self-evident that the primary function of any beverage packaging, which must include the closure, is to provide the physical retention of the contents. The consumer expects to retain the amount of product that he or she purchased until the time for its consumption. Container leakage may also result in damage to other property. The primary evaluation of beverage packaging is thus concerned with the retention of liquid content. This performance characteristic is determined not only by the container itself but by the effectiveness of the seal between container and closure. It is rare for containers themselves to be produced with a defect in the body that permits leakage. For packages that are produced on line such as in `form-fill-seal' operations, there is a significantly increased risk of the failure of seals and quality checks need to be strengthened accordingly. Assuming the contents of a beverage container are retained satisfactorily, there are other quality attributes that determine the suitability or otherwise of the beverage/packaging combination. In most countries there is now a statutory requirement to state some form of product durability marking on the label and this is usually in the form of a `best before' date although with some very short shelf life products, such as freshly squeezed juices, a `use by' date is more appropriate. The performance of any package is thus measured by its ability to keep the contents in a condition that is as close to the taste, appearance and nutritional qualities or other standards as is required by the manufacturer (and expected by the consumer) within the period between the dates of manufacture and expiry. Although this chapter is not primarily concerned with packaging, its importance in ensuring the required product stability and shelf life cannot be ignored.

19.2 Factors influencing the stability of fruit juices and soft drinks 19.2.1 General The factors that affect the stability and shelf life of fruit juices and soft drinks may be conveniently divided into three main areas: microbiological, physical and chemical. Soft drinks and especially fruit juices are particularly susceptible to microbial spoilage and, in certain circumstances, may support the growth of pathogenic organisms. A rapid deterioration may occur if products are not pasteurized. Where microbial deterioration does occur physical and chemical changes are almost always evident. The physical and chemical changes that are discussed later refer to the changes that may be seen when no microbiological activity is present.

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The stability and shelf life of fruit juices and soft drinks 575 19.2.2 Fruit juices The processing details of fruit juices are well documented and it is not proposed to go into much detail in this chapter except insofar as process is likely to affect the stability of the end product. Details vary depending on the botanical structure of the fruit being handled and diagrams of typical processes for soft fruit such as apples and pears and citrus appear in Figs 19.1 and 19.2. The key stages in any fruit processing operation are: · Washing and inspecting to reduce microbial load and remove rotten fruit. · Pressing to obtain optimum juice yield that is compatible with the quality required. · Separating juice from pulp and debris. · Pasteurizing juice to deactivate enzymes and secure microbial stability. · Concentration (if required). · Packaging into appropriate containers and storage/distribution.

Fig. 19.1 Outline typical process for soft fruit processing.

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Fig. 19.2 Outline typical process for citrus fruit processing.

The relevance of these stages to the stability and shelf life of the end product is discussed below. Washing and inspection Most fruit processing operations incorporate some form of washing into the delivery and transport of fruit into the facility. Incoming fruit is often discharged into pits that use a water flume to provide a gentle means of transporting the fruit to the plant. The circulating water gives an initial washing stage that will usually remove gross soil and other debris. When fruit reaches the main facility it will typically be elevated into an inspection area. The elevators usually incorporate a

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The stability and shelf life of fruit juices and soft drinks 577 spray of clean water which may also incorporate a mild sterilant. Inspection in some countries is a manual operation where rotten fruit and other debris are removed. Automatic inspection facilities are often used in larger operations. The microbial load on most raw fruit is considerable and an effective washing operation will assist in reducing this load. Since in the pressing and separation stages, juice and pulp/peel are intimately mixed, high levels of initial contamination are likely to be found in the raw juice. Most subsequent pasteurization stages are likely to be based on typical microbial loads and excessive contamination may not be removed leading to later problems. Removal of damaged fruit also assists with the reduction of microbial load and, since damaged fruit may also be partly fermented, its presence, if not removed, may later affect the aroma of juice. Pressing to obtain optimum juice yield that is compatible with the quality required Many different types of fruit presses are used but all involve compressing the fruit to a greater or lesser degree. Soft fruit processes often involve a pretreatment with enzymes to break down the structure of fruit and release as much juice as possible. The development of off-flavours is rarely associated with such treatments but physical stability problems may arise. These include haze or sediments in clear juices or separation of cloudy products. Where clear juices are to be the end product, a later enzyme treatment is normal to assist with clarification. It is possible, by use of an appropriate cocktail of enzymes to procure an almost complete liquefaction of soft fruits such as apples and pears although the legal status of the juices so produced is unclear. Because of the botanical structure of citrus fruit, it is desirable to extract peel oils before juice pressing is undertaken although some extraction methods allow peel oil to be removed later. Peel oils have intense flavour and aroma characteristics which are not generally appropriate in citrus juices although they are likely to be added to citrus comminutes. Apart from the initial aroma and flavour impact of citrus oils, their terpene content renders them vulnerable to rapid oxidation and consequent flavour deterioration. The use of undue pressure in the pressing of oranges is likely to lead to a significant increase in the level of socalled peel extractives. All citrus juices are likely to have a low level of these but higher than normal levels may lead to later problems of chemical or physical stability that will affect shelf life and product authenticity. Citrus comminutes are manufactured by recombining the principal citrus fruit components (juice, peel and oil) in proportions that deliver the characteristics required by the purchaser. They are used as ingredients in citrus drinks, mainly dilute-to-taste products, with other ingredients such as antioxidants and preservatives which limit the rate of deterioration of citrus oils. Separating juice and pulp and debris In most processing operations of all types of fruit, it is necessary to separate juice from the matrix of vegetable matter that forms the structure of the fruit. A

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number of alternative methods are used to achieve this, including simple screening and the use of centrifuges or rotary separators. These are typically horizontally aligned rotating drums that have perforated walls. Juice is allowed to pass through the perforations whilst pulp and debris are retained. By inclining the drum at a slight angle, the residual material is made to fall from an aperture at the end of the drum onto a moving belt that removes it from the area. Some processors then incorporate the further use of a centrifuge to reduce the pulp content to a predetermined level. Excessive pulp levels in the finished product can have a significant effect on the appearance and mouthfeel of the product and in that way may render it unacceptable to consumers. Pasteurizing juice to deactivate enzymes and secure microbial stability Pasteurization is used for products that have a pH value of 4.5 or less, where the acidic conditions effectively reduce the risk of growth of pathogenic organisms. However, some care needs to be exercised with products that have pH values that are in the region of 3.9±4.5 as it has been demonstrated that some pathogens (e.g., E. coli O157) can survive for a limited period in such conditions. For bulk juice treatment, the normal process used is flash pasteurization, although for product directly packed into consumer units, either flash pasteurization (85±90 ëC for 15±20 seconds is a typical range) coupled with an aseptic packaging unit or in-pack pasteurization of filled products (20 minutes at 70 ëC) may be used. To determine the level of pasteurization needed (in-pack or flash treatment) it is normal to refer to the number of pasteurization units needed. No effective pasteurization occurs below 60 ëC and by holding a product at that temperature for 1 minute it is said to have received 1 pasteurization unit (PU). To calculate the number of pasteurization units for any given time temperature relationship, the following formula applies: Number of pasteurization units ˆ 1.389(t-60)  time in minutes As an example, a product is held for 20 minutes at 70 ëC (typical in-pack pasteurization conditions). Thus the number of PUs is: 1.389(70ÿ60)  20 (i.e. 1.389(10)  20) ˆ 26.73  20 ˆ 534.6 PUs A simplified approach is to accept that for every rise of 7 ëC over 60 ëC, there is an approximate 10-fold increase in the number of PUs, i.e. 60 ëC ˆ 1 PU/ minute; 67 ëC ˆ 10 PU/minute; 74 ëC ˆ 100 PU/minute, etc. It is, however, difficult to interpolate if the simplified approach is used. Unpasteurized fruit juices have a very limited shelf life of a few days and must be marketed through a cold chain distribution service. They are subject to problems of physical separation and will show rapid microbial spoilage if not

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The stability and shelf life of fruit juices and soft drinks 579 stored correctly or are held beyond their use by dates. Despite their relatively low pH, unpasteurized juices are now known to have the potential to support pathogenic microorganisms such as Salmonella, Shigella and Escherichia coli O157. Other than for this relatively small market sector, pasteurization is a critical step in the processing sequence of all fruit juices. Two objectives are secured by this process, an improvement in microbiological stability (and removal of any pathogens) and, provided a temperature of 90 ëC is reached, the destruction by heat of pectolytic enzymes that will otherwise promote physical separation into an upper clear layer and a lower layer of pulpy debris. The stabilization of enzyme activity may not be required if the juice is clarified as it will probably have been through a process that requires the addition of appropriate pectolytic and sometimes other enzymes. Fruit juices that are to be packed without concentration will often be suitably heat treated as part of the overall production and packaging process but juices that are to be concentrated may not necessarily receive the full pasteurization conditions if they are pre-heated as part of the evaporation and concentration stage. Concentrated juice produced in this way will normally be stored frozen, typically at around ÿ18 ëC. Any residual microbiological activity will not normally cause problems at such a temperature and since, when the juice is reconstituted, it will again be pasteurized, no further problems of microbiological activity will be expected. However, if during the concentration process, the juice temperature does not reach that required to deactivate enzymes (at least 90 ëC), they may remain active, albeit at a much reduced rate, during storage and may occasionally become the cause of impaired physical stability when the juice is reconstituted. It should also be noted that any significant delay in pasteurizing juice during the process will allow enzyme activity to proceed and may, even with later apparently adequate heat treatment, result in juice which shows problems of physical stability. Packaging into appropriate containers and storage/distribution The packaging of fruit juices into containers for direct use by the end consumer is the most critical stage in ensuring that the product has the intended shelf life and stability. The use of any containers that are intermediate between the juice producer and final packaging plant also represents a critical stage. Freshly squeezed juices There is a significant market for juices produced by pressing fruit, mostly citrus, placing it in small containers, and selling directly to the consumer without any further heat treatment other than refrigeration. The juice so produced has the freshest possible taste but carries significant risk of microbiological infection and lack of physical stability. The microbiological risk is principally that of spoilage by yeasts and moulds although, as indicated above, there is increasing concern about the ability of certain pathogens to survive in what has been traditionally regarded as a low pH

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(below 4.5) product. In consequence, this sector of the juice market relies on distribution in a cold chain, sales from refrigerated cabinets and has a very short shelf life of up to about 7 days. Generally, consumers appear willing to accept some physical separation and provided correct distribution and storage temperatures are maintained, microbiological problems are minimized. Direct or `not from concentrate' (NFC) juices NFC juices are products that are obtained by pressing fruit, separating from pulp and debris to the required level then pasteurizing and packaging into containers for consumer use. There may be an intermediate stage where juices are pasteurized and packed into bulk containers under aseptic conditions. Where this occurs the double pasteurization will lead to products that have a slightly less fresh taste. Where juices are packed directly into the consumer packs, they will be typically subjected to a `light' pasteurization, which may involve heating to around 90 ëC for a few seconds, before being packed under clean but not aseptic conditions. Like freshly pressed juice, these products are also stored, distributed and sold under refrigerated conditions and have a typical shelf life of up to 12± 13 weeks. The pasteurizing conditions will inactivate enzymes and thus maintain physical stability and provide a high degree of microbiological protection from spoilage. Pasteurization at the relatively low pH of juice also effectively removes any risk of pathogen survival. Concentrated juices The largest volume of fruit juices are manufactured by processing into concentrates at the fruit processing location, transporting the concentrate to the required packaging location where it will be reconstituted to a standard strength and repackaged as required. The concentration process usually involves heating the juice and evaporating most of its water content under vacuum, although other techniques such as freeze concentration are used on a small scale. In a standard concentration process, the juice may or may not be subjected to the necessary pasteurization temperature prior to the commencement of evaporation. It is therefore possible for concentrated juices to carry a residual active microbial load and, more particularly, to contain active pectolytic enzymes. Citrus juices such as orange and grapefruit are normally concentrated to around 65±66 ëBrix and frozen to around ÿ18 ëC for transportation. Any microbiological activity will be largely suppressed. When reconstituted, most juice is repackaged aseptically which will ensure microbial stability. A smaller proportion of reconstituted juice is marketed through cold chain distribution in similar packs to NFC products and only receives a `light' pasteurization. Pectolytic enzyme activity may continue in the concentrate at a low rate leading to the possibility of reconstituted juice which may not show the required level of physical stability. However, most aseptic packs, such as the 1 litre Tetrapak or Combibloc containers, do not allow the consumer to see the product before it is dispensed and in consequence any loss of physical stability is rarely noticed.

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The stability and shelf life of fruit juices and soft drinks 581 The issue of pectolytic enzyme activity and resulting latent physical stability is not normally an issue in pome and berry juices concentrated to around 70 ëBrix. These juices are invariably clarified before concentration and transported in cool but not frozen conditions. The reconstituted juices are also marketed as clear products and packed aseptically. 19.2.3 Physical and chemical changes Whilst microbiological stability is the most critical factor in determining the stability of fruit juices and soft drinks and must be effectively achieved in all products relative to their shelf life, the issues of physical and chemical stability then become significant. Physical stability normally refers to the appearance of a product and includes its propensity to separate into layers or the appearance of sediments, floc or particulates as well as any colour changes. Most of the physical changes that become apparent during the shelf life of a product are related to a chemical or biochemical reaction and it may be more appropriate to refer to this aspect of product stability as `physico-chemical' rather than to being either strictly physical or chemical. Key factors in such changes are the presence of any residual pectolytic or other enzymes, the presence of dissolved oxygen and the temperature at which products are stored. Changes in the appearance of a product relate particularly to its intended nature as being either cloudy or clear. These changes may be ameliorated to some extent by the use of packaging that prevents or limits the consumer from seeing all or part of the product until it is dispensed. Cloudy products Most fruit juices are of a cloudy nature when immediately pressed from the fruit and many consumers prefer cloudy to clear products for certain juice types. For example, there is little if any market for the sale of clear orange or grapefruit juice or related soft drink products whereas lemon and lime juice based products are frequently clarified. Apple and berry juices are also often clarified although `not from concentrate' apple juice is almost always cloudy. Whilst the factors that determine whether a product is to be marketed as either clear or cloudy are mainly subjective, the defects that may occur relating to the intended appearance are not. The main concern relating to the stability of cloudy products is the separation of the product into sediment, which may be pulpy or compacted, and a clear or almost clear supernatant layer. For pure juices and products with a significant juice content such separation is related mainly to the breakdown of natural pectin that is present in variable quantity and quality in juice expelled from fruit. Pectins vary in composition but are essentially methylated polygalacturonic acids. They play an important function in cell wall structures but once cells are ruptured as in the expression of juice, pectolytic enzymes start to break down the chain length as well as initiating the hydrolysis of the methyl esters. The ultimate result is to increase the amounts of galacturonic and polygalacturonic

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acids in the juice. In pure juices pectins are responsible for the cloud stability of the juice and any breakdown of pectins to galacturonic acids with various levels of demethylation and chain length will adversely affect cloud stability. This breakdown occurs quickly after juice expression as a result of pectolytic enzyme activity which is halted by rapid pasteurization of the juice to around 90 ëC. Thus loss of cloud stability in a pure juice or juice-based product usually relates to delay in pasteurization of the juice component. A clouding preparation may be used in products required to be cloudy but where there is no juice present. Such clouding preparations products are often oil-in-water emulsions produced using citrus oils emulsified with wood rosin ester or permitted synthetic emulsifying agents and an aqueous component incorporating, for example, gum Arabic. These preparations are mostly very stable provided the particle size is kept below about 10 microns, although their stability can be adversely affected by heat and the presence of solvents such as ethanol resulting from the addition of types of flavourings. Clarified products As indicated above, there are some products that consumers expect to purchase clear. In such products the level of clarity must be outstanding as the presence of haze, floc or precipitates will often result in rejection and may be regarded as an index of product failure. Clarification of the juice component is usually achieved by addition of pectolytic and amylolytic enzyme preparations to ensure removal of pectin and starch residues. These residues are frequently the source of haze or precipitates, although polyphenolic substances present may further polymerize on storage and produce sediment. Physical defects in clarified products are thus mainly those which produce haze or other sediments and may be caused by an inadequate treatment. After addition of enzymes, it is often necessary to carry out further treatment such as the addition of gelatin or bentonite to remove any residues of protein that may also be present. The use of a polishing filter is also often employed. Assuming that the product is free from any microbiological contamination that may produce a haze, the later appearance of any haze or other residue may be related to breakdown of other juice components. For example, in juices with a significant red colour, breakdown of anthocyanins may give rise to polyphenolic material that has a sufficiently large molecular weight to come out of solution and produce sediment. Floc can sometimes arise as a result of algal blooms contaminating the water source, although this phenomenon is very unusual and normally only seen during high temperatures and periods of extended sunshine. Other physical and chemical changes Oil rings Products that contain essential oils as part of a flavouring system sometimes suffer separation of some or all of the oily components which then form a socalled neck ring. This is evident as a ring of often coloured oily materials in the

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The stability and shelf life of fruit juices and soft drinks 583 neck of a bottle which may sometimes be redispersed by agitating the bottle contents. Essential oils, particularly those from citrus fruits may be added to beverages in the form of a cloudy emulsion where the oils are made to form an oil-in-water emulsion using appropriate permitted emulsifiers and then subjecting the mixture to high pressure emulsification. These cloud emulsions are normally very stable but can sometimes break down if subjected to high pasteurizing temperatures for extended periods (such as may occur when a flash pasteurizer is required to recycle product for 5±10 minutes) or if there is a significant level (over about 0.1% by volume) of alcohol in the product. Colour and flavour changes One of the more commonly observed defects in almost any soft drink or fruit juice is that of product discoloration. Products will be evaluated to establish a shelf life that enables the product to remain of an appearance and taste that the manufacturer decides will be acceptable to consumers. However, all soft drinks and fruit juices will show colour and flavour changes over a period of time which may be slowed or accelerated by the effect of storage conditions. Many manufacturers set the shelf life of their long life products based on the average conditions expected during warehousing and distribution. Typically, it will be assumed that in temperate climates this will be a year round average temperature of between 10 and 20 ëC and conditions of low or no light. Producers in or exporters to tropical or other extreme climates will need to evaluate the range of expected conditions and decide appropriate storage and distribution arrangements to ensure acceptable product quality during the stated shelf life. The most usual colour and flavour defects that are likely to arise in products that have been subjected to inappropriate storage temperatures or excessive pasteurization are the development of browning in the appearance coupled with a pronounced cooked flavour and aroma. In this respect the use of tunnel pasteurization or hot filling carries a greater risk of thermal damage to products than flash pasteurization. Although temperatures are greater in the latter case, it is exposure to longer time at increased temperature that is invariably more damaging. During the period of product development, storage for long periods and at excessive temperatures can be used to establish the likely deterioration of colour and flavour. Any unusual colour or flavour that arises, perhaps as a complaint, can then be readily distinguished from the norm. Light that is allowed to penetrate a product, for example in a clear glass container, is usually very damaging and a product left in direct sunshine will often develop unpleasant off-tastes and suffer colour changes, usually bleaching, in a very short time. This aspect of product deterioration should also be evaluated during the development period by exposing product to both south and north light. Unusual colour development or the presence of an uncharacteristic flavour taint will probably require the services of a specialist laboratory to establish the cause, although much can be done by a close evaluation of the individual ingredients, including water used.

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19.3

Food and beverage stability and shelf life

Ensuring product stability and extending shelf life

19.3.1 General principles The most important means of ensuring product stability and delivering a suitable shelf life is by the use of appropriate processing and packaging. Processing It will be evident from earlier sections in this chapter that the processing required for any given product will be determined by its ingredients, intended market, shelf life and packaging to be used. For example, at one end of the continuum will be freshly squeezed fruit juices where, apart from expelling the juice from the fruit and carrying out a simple separation to remove unwanted pulp and other parts of the structure of the fruit, there will be no other processing. Packaging in such instances will usually be a clear plastic (often PET) bottle to allow the consumer to see the product at the point of purchase. The typical shelf life of up to about 7 days will be achieved by storage, distribution and display in cold (2±5 ëC) conditions. At the other end of the continuum will be long life fruit juices which are flash pasteurized, probably at over 90 ëC, followed by immediate packaging into laminated cartons under aseptic conditions to give a shelf life in temperate conditions of at least 12 months. Leaving aside for the moment the issue of packaging, the processing required for any given product can be established by a risk assessment based on the ingredients to be incorporated (including the quality and quantity), the conditions under which it is to be packed, the use or not of permitted preservatives and the shelf life and market conditions for which it is intended. The highest risk ingredients are those which provide nutrients for the growth of microorganisms, although it must be remembered that because of the broad spectrum of conditions under which bacteria and to a lesser extent yeasts and moulds will grow, all soft drinks and fruit juices are at risk to some extent from microbial deterioration. On the assumption that all the products under consideration in this chapter are of a pH lower than 4.0, the greatest microbial risk is that from spoilage by yeasts and moulds. In practical terms, it will be the presence of fruit juices (especially pome and berry juices) at almost any level, but especially over 2% in single strength, that present the highest risk. This risk may be mitigated to a limited degree by the use of concentrated juices, particularly aseptically packed concentrates, but in all instances juice containing beverages require pasteurization. Carbohydrates provide a similar nutrient base for yeasts and moulds but provided that they are of high quality with a low residual count of organisms and there is no separate source of nitrogen, products can be successfully made without pasteurization but with permitted preservatives. The lowest risk products are those that contain synthetic flavours, artificial sweeteners and carbon dioxide as, provided water quality used is at least up to the standard of drinking water in the EU, there is minimal risk of microbial

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The stability and shelf life of fruit juices and soft drinks 585 deterioration and no processing is required. If packaging is sterile and equipment hygiene is outstanding, unpreserved products can be successfully made although the prudent manufacturer will always use a permitted preservative in even the lowest risk products. The use of carbon dioxide as an ingredient is worthy of particular mention as it performs a number of significant functions that could be described as `preservative'. Its presence in the headspace of a product container effectively excludes oxygen which substantially rules out mould growth in the product. It also reduces the pH of products in which it is used and as it is a normal byproduct of the metabolism of most yeasts, can be effective in suppressing yeast growth. When processing is deemed necessary for a fruit juice or soft drink, almost the only practically available solution for high volume production at the time of writing is the use of thermal pasteurization. The choice of flash or in-pack treatment or hot filling will largely depend on the packaging required coupled with the facilities available to a given manufacturer. In all instances, the level of pasteurization will be determined by the product risk factors. Typical pasteurizing conditions in use are flash pasteurization at around 85±90 ëC for a period of 3±30 seconds or in-pack treatment at 70 ëC for 20±25 minutes. Other potentially available treatments are discussed in Section 19.5. Packaging For all practical considerations, beverages cannot exist without packaging, except for products for almost immediate consumption; it is this factor more than any other that determines the shelf life of the product. Packaging must selfevidently be capable of physical containment of the product and, if carbonated, the carbon dioxide that gives the product its particular characteristic. It must then primarily protect the contents from microbial contamination and the effects of oxygen which will often produce rapid deterioration. Packaging must also be capable of ensuring adequate physical protection of the contents and is an essential means of communicating both statutory and marketing information to the consumer. Glass For many years glass has been the standard against which alternative packaging materials have been evaluated. Glass containers with an appropriate closure provide almost perfect protection to fruit juices and soft drinks within the agreed shelf life. The most likely cause of failure of glass containers is leakage at the interface between the cap and bottle body. Assuming a satisfactory sealing at the closure interface, there is no loss of contents by transmission of water vapour, carbon dioxide retention is excellent and there is virtually no transfer of oxygen into the product. The advantages of glass containers include its quality image, potential for brand differentiation because of relatively low tooling costs, tamper evidence, recyclability and reuse possibilities. Glass has the added benefit of being practically inert and apart from any risk of contamination of product by

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glass fragments or misuse of the container for storage of foreign substances, there is minimal risk of tainting. Glass can also be easily coloured or covered with a UV screen to minimize the effect of light on sensitive products. The disadvantages of glass are its weight and its brittleness that render glass containers liable to breakage with the risk of damage to people or property. Few manufacturers now collect, wash and reuse glass containers because of the associated cost and logistical problems, but glass can be easily recycled and most EU countries are now well advanced in schemes for collection of used glass containers for reprocessing as cullet. The effects on shelf life of products packed in glass are thus effectively confined to the physico-chemical changes that occur as a result of time and accelerated by storage at increased temperature, the transmission of light and the presence of dissolved oxygen. Intense light, such as direct sunlight, is extremely damaging to most products; indirect light is less so. The effects of light on most products are to cause breakdown of flavour components resulting in often very unpleasant off-flavours. Metal containers The market for soft drinks packed in cans has declined in recent years but despite that, they remain popular for single serve beverages because of their convenience, robustness and marketing image. Most beverages are now manufactured in aluminium as two piece cans (can body and one end) by the drawn and wall ironed (DWI) process. Such two-piece cans lack the body side seam of their three-piece predecessors and are inherently less prone to leakage of liquid and CO2. Provided the single can end is applied correctly, the risk of leakage of either liquid or gas is minimal. Probably the greatest risk of leakage is likely to arise from can corrosion and eventual pinholing and, if cans are subject to tunnel pasteurization, removal of surface moisture is vital to minimize corrosion. Like glass, cans offer almost perfect protection for soft drinks and, to a lesser extent, fruit juices. When correctly sealed, modern two-piece cans give outstanding retention of contents, prevent ingress of oxygen and are much lighter than glass and are not brittle. The contents are given total protection from the effects of light. Their use today is mostly limited to carbonated drinks because the presence of CO2 provides added physical stability to the can thus enabling a much thinner wall thickness to be used. Canned fruit juices and non-carbonated soft drinks, particularly those requiring tunnel pasteurization, must be injected with a small amount of liquid nitrogen to pressurize the contents and thus prevent can distortion. Like glass, cans may be readily recycled. The principal disadvantages of cans are that they are not easily used for carbonated drinks in volumes in excess of about 500 ml and for soft drinks they rarely exceed 330 ml. Because cans are usually decorated and printed at the time of manufacture and because modern filling lines often run at speeds in excess of 1000 cans per minute (which yields around 300 million units per annum), a substantial investment in stock with its corresponding logistical consequences is required.

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The stability and shelf life of fruit juices and soft drinks 587 The effects on shelf life of products packed in cans will, as with any other container, depend on time and temperature, but close attention must be paid to the detail of formulations for canned products and a correspondingly close liaison must be maintained between product formulation teams and the can maker. Any lacquer applied to the internal surface of cans must be compatible with the formulation. It is essential to ensure complete absence of sulphur dioxide from products as, if it is present, chemical reduction is likely to occur at the metal interface with the production of hydrogen sulphide. Perhaps the most significant risk to shelf life in the use of cans is that of metal uptake and the corresponding development of metallic off-tastes. In extreme circumstances, the level of metals could exceed statutory limits. Plastic containers A high proportion of soft drinks and, to a lesser extent, fruit juices are now packed in plastic containers. Whilst there are a number of plastics that have been used for this purpose, the predominant material now in use is polyethylene terephthalate (PET). An alternative, polyethylene naphthalate (PEN) is sometimes used for products requiring in-pack pasteurization as it is much less liable to distort at the temperatures used for pasteurization. Other plastics such as high density polyethylene (HDPE) and polystyrene (usually with co-polymers) find uses in very short shelf life products and form-fill-seal packs such as cup drinks. Since PET is predominant in beverage packaging, the comments in this section relating to shelf life issues will be made in respect of that material. The main advantages of using PET containers are its relative strength, particularly when carbonated, low weight and a clarity that compares favourably with that of glass. Bottles made of this material can also be recycled. The principal disadvantages of PET are its permeability to gases allowing the loss of CO2 and ingress of oxygen. Carbonated products packed in PET are normally given a significantly shorter shelf life than those packed in either glass or metal containers because, apart from the usual factors that determine shelf life, the loss of CO2 will render the product unacceptable to consumers in a shorter time. Manufacturers of carbonated drinks normally specify a maximum loss of 15% over 26 weeks for a 1.5 or 2.0 litre bottle. For smaller sizes, the 15% loss is likely to occur over 10±12 weeks because of the less favourable surface area to volume ratio. For this reason, the limiting shelf life factor for most carbonated drinks packed in PET is the loss of CO2 which is a determining characteristic of these products. Non-carbonated soft drinks packed in PET are susceptible to oxidative deterioration because of the ingress of oxygen through the packaging walls. It will thus be desirable to incorporate an oxygen scavenger such as ascorbic acid into the formulation of products packed in PET. Laminated board containers A significant proportion of fruit juices and non-carbonated soft drinks are now packed aseptically in laminated board packs as exemplified by the use of

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TetraPak, Combibloc and other similar packs. The material used in these packs is typically a laminate which, starting from the outside, is often made up as follows: Polyethylene Printed design Paper/board Polyethylene Aluminium foil Polyethylene Polyethylene The pre-printed laminate is reel fed through a sterilizing bath into the aseptic part of the machinery where it is formed into the required shape that can be in a limited number of shapes, filled, sealed and discharged ready for any secondary packaging required. These containers provide a very high level of product protection that, in most cases is at least as good as glass (and in some instances better as light is totally excluded) coupled with a large surface for decoration and labelling. Because of their low weight and regular size, they also offer excellent distribution characteristics. The principal disadvantages of these containers are that the maximum size is generally limited to about 1 litre and the enclosed formulation must be free from any substances, such as sulphur dioxide, that might react with the aluminium layer. Close attention must be paid to the box formation and sealing that takes place within the aseptic chamber as any leaking or pinholing will compromise microbiological integrity.

19.4

Shelf life determination

The determination of shelf life relies to a large extent on the use of organoleptic testing which is covered in detail elsewhere in this book. However, in parallel, it is important that other testing is used to confirm the microbiological, chemical and physical characteristics of the product. 19.4.1 Microbiological All fruit juices, which are not permitted to contain preservatives, and soft drinks that are packed without the use of any preservatives, must be free from any microbiological contamination. This will normally be achieved by the use of either aseptic packaging, hot filling or in-pack pasteurization. Samples from each batch of product manufactured by these methods should be taken on an agreed basis and subjected to appropriate testing. Many manufacturers still employ classical plating techniques although some excellent rapid microbiological testing methods are now available. Products without any preservatives

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The stability and shelf life of fruit juices and soft drinks 589 are often quarantined during the testing, and to ensure the required shelf life must be free from any microbiological contamination. Some manufacturers also subject products containing preservatives to a similar microbiological testing regime, although quarantining is not usually employed. Low counts, such as less than 10 colony forming units of yeasts and moulds per millilitre of product, may often be discounted particularly when products are carbonated, but the target must always be to obtain a zero count. Experienced technical staff will build up their own assessment of these products and when to release/quarantine or reject because in many cases very low counts will disappear within a short time because of the effects of preservatives. Yeasts and moulds are the organisms of greatest concern as they cause spoilage of the products that may include a build-up of CO2 that can, in extreme circumstances, cause bottle bursting and damage to people or property. Mould spores in a product are difficult to detect particularly by plating techniques and can develop after many weeks of storage. Most bacteria are of little concern provided that product pH values are less than 4 when most pathogens will cease to be viable. Spoilage from Lactobacillus species is not unknown and for non-carbonated ready to drink products Alicyclobacillus can be troublesome in warm conditions. Both these organisms are susceptible to the effects of flash pasteurization. 19.4.2 Physico-chemical testing Physical changes It is essential to ensure that products maintain their physical integrity during the storage period and, since some forms of plastic packaging allow water vapour to pass through the container walls, it will be desirable to ensure the quantity of product remaining in unopened containers at the end of shelf life is as stated on the label. Such losses may be accompanied by distortion of the container such as panelling. Products that are carbonated and packed in PET should also be checked for distortion of the container base particularly during storage in elevated temperatures. Base distortion will lead to the packages becoming unstable on shelves and cause rejection by retailers. Product colour changes during shelf life should also be noted and recorded. Although many coloured products lose `brightness' during storage, the effects of heat either from excessive pasteurization or during storage may cause browning to the extent that consumers may complain. Browning of products is often accompanied by the development of unwanted flavour defects. Colour changes can also arise as a result of interactions between ingredients although these are normally associated with products that contain added vitamins and especially minerals such as iron. Any appearance defects, such as physical separation or oil ring formation that occur during storage, must also be noted and assessed as being acceptable or leading to rejection of the product.

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Chemical changes The principal concern for chemical changes that occur during storage of soft drinks and fruit juices will relate to products where there are specific claims for ingredients of nutritional value. In most beverages, protein and fat are either absent or present in negligible amounts so the main energy source will be carbohydrates. There may be changes in the carbohydrate spectrum, such as the inversion of sucrose to dextrose and fructose or the partial breakdown of glucose syrup ingredients, but there will be no overall effect on nutritional value. Small changes in sweetness levels may occur but will probably be undetectable to most consumers. Where additions of other nutrients have been made, for example vitamins, and a claim made for their content, it is very important to carry out testing to ensure that the declared level is present at the end of the stated shelf life. In most cases this will mean the addition of an overage at the time of manufacture. Experienced formulators will be likely to know what level of overage addition will be necessary for individual ingredients in particular formulations. Other ingredients that should be checked during initial shelf life assessments include artificial sweeteners and preservatives as any reduction in the amounts of these may have a more significant impact on the product performance. Accelerated shelf life testing Accelerated shelf life testing is often employed to obtain advance indications of the performance of newly formulated products and products destined for tropical markets. Exposure to north light (in the northern hemisphere) or a light box with appropriate wavelength light of the required intensity may be used for coloursensitive products, but the majority of accelerated testing is carried out at increased temperature. If sensitivity testing for light is carried out in a light box the light source may also cause a temperature increase and care must be taken to differentiate between the effects of light and heat in such situations. Robertson (2009) has recently discussed several models that have been developed to demonstrate the effects of heat on the deterioration of products. The most commonly used and generally valid relationship between the effects of temperature and the rates of deterioration of products is that of Arrhenius. The relationship may be shown as: k ˆ k0 eÿEa =RT where k ˆ rate constant for the deteriorative reaction, k0 ˆ constant independent of temperature (the Arrhenius factor), Ea ˆ activation energy (J molÿ1), R ˆ gas constant, and T ˆ absolute temperature. The simplified form expressing the relationship between the rate of deteriorative reaction and temperature is also shown as: k ˆ k0 eb…TÿT0 † where k0 ˆ rate at temperature T0 (ëC), k ˆ rate at temperature T (ëC), e ˆ 2.7183, and b ˆ a constant of the reaction.

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The stability and shelf life of fruit juices and soft drinks 591 Another term used by Robertson to discuss the response of biological systems to the effects of heat is the temperature quotient. This indicates how much more rapidly a reaction proceeds at temperature T2 than it does at temperature T1. In practical terms, those concerned with the storage and deterioration of soft drinks and fruit juices will often use storage at ambient temperature (in the range of 15± 20 ëC) as typical of normal conditions and a warm room of 35±40 ëC to give an indication of the accelerated effects. At the elevated temperature, an approximate guide is that deterioration proceeds about 3±4 times faster than at ambient.

19.5

Future trends

19.5.1 Fruit juices and ready to drink uncarbonated soft drinks Recent years have seen a very rapid growth in the volume of fruit juices, and to a lesser extent soft drinks, sold through the cold chain distribution system. There is a limited market for so-called `freshly squeezed' juices where (mainly) citrus fruit is pressed, and with further processing limited to screening to remove seeds and some pulp packaged and sold within a few days. Despite their relatively low pH, such products do carry a risk of contamination by pathogenic organisms. The main growth area is for NFC juices and non-carbonated ready to drink soft drinks with a high percentage of fruit juice. The latter are unpreserved but, like the pure juices have been subjected to a `light' pasteurization. Otherwise the juices are almost indistinguishable from their freshly squeezed counterparts. These products will typically be allocated a shelf life of around 8±12 weeks and are typically packaged in laminated cartons. They carry a premium price and the development of their market may well be more limited during times of economic hardship, but otherwise seem set to be a growth feature of otherwise relatively static markets for fruit juices. Such products have a limited shelf life for mainly microbiological reasons, although the packaging employed does not give (and does not need to provide) the protection against oxidative deterioration that products with a longer shelf life need. At the other end of the storage spectrum are the long life fruit juices packed aseptically in laminated cartons. Such products are largely packed in 1 litre boxes, typically carry a shelf life of at least one year and account for a high proportion of all fruit juices sold. Juices packed in this way seem set to continue to dominate the market for many years to come. Despite the dominance of the aseptic pack, high quality adult soft drinks packed in glass continue to occupy a growing niche market where they attract premium prices coupled with long shelf lives. Products fortified with vitamins, minerals and phytochemical extracts (nutraceuticals) also occupy a small niche market and often show growth rates well in excess of mainstream products. Because of complex interactions of reactive ingredients in these products, colour and flavour changes often occur and shelf lives may be reduced accordingly. Non-carbonated RTD soft drinks in small aseptic packs (200±300 ml) are of increasing significance in the market as they offer the opportunity to produce

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drinks that are free from chemical preservatives. There is increasing resistance to some chemical preservatives, particularly sodium benzoate, in all soft drinks and the use of potassium sorbate is now widespread. In other RTD products that are non-carbonated, the use of dimethyl dicarbonate is now widespread. The use of PET, and other polymers such as PEN that are able to withstand tunnel pasteurization, is likely to increase, and this will facilitate packaging of juices and other microbiologically sensitive products in much cheaper alternatives to the aseptic packs. 19.5.2 Carbonated soft drinks Carbonated soft drinks that are sold in large volumes in PET packages that are mostly up to 2 litres in volume are likely to dominate the soft drinks market for the foreseeable future. However, for smaller PET bottles the development of pasteurizable material will be likely to facilitate the sale of carbonated products that are free from chemical preservatives. The extension of this property to larger PET containers is probably limited by the higher levels of carbonation needed. Additionally, larger containers are frequently left part used and the presence of a chemical preservative in such circumstances is desirable. The limiting shelf life factor for carbonated products packed in PET is likely to remain that of the loss of carbonation rather than other oxidative or deteriorative reactions and there is a significant development potential for PET or similar plastics with improved retention of CO2. As with other premium products, the use of glass is likely to dominate the market for high quality adult oriented products that benefit from the pack image coupled with a long shelf life. For smaller unit volumes, the beverage can is likely to retain an important segment of the market for carbonated drinks as its convenience, recyclability and suitability for pasteurization enable its use for a wide variety of soft drinks. 19.5.3 Dilute-to-taste products Traditionally these products have been packed in glass but the use of PET is now widespread. Glass containers remain the packaging of choice for premium priced products. Most dilute-to-taste products are packed in containers ranging from 75 cl to 2 l and invariably contain chemical preservatives as well as being pasteurized. The use of preservatives is of particular importance as these products are frequently left part used for periods of time. For unopened containers, products packed in PET are likely to suffer some effects of oxidative and other deteriorative reactions in a shorter time than those packed in glass, but once opened and oxygen is allowed to re-enter the headspace, the performance of glass and PET is likely to be similar. For dilute-to-taste products the use of both glass and PET seems set to continue.

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The stability and shelf life of fruit juices and soft drinks 593 19.5.4 Processing trends Various alternatives to thermal processing are available although it seems likely that for practical and economic reasons, thermal pasteurization is set to remain the preferred means of stabilizing fruit juice and soft drink products for the foreseeable future. High pressure processing This technique has been used successfully for the production of high value fruit juices where the retention of the characteristics of freshly pressed juice for longer shelf life is considered desirable. Batches of product, which must be packed in flexible containers, are placed in a pressure vessel and subjected to pressures of around 600 MPa. Current processes are both labour and capital intensive and are limited by the necessity of batch operation. Even then, the benefits that may be achieved for a freshly pressed juice only allow for an extension of shelf life by a factor of two or three times that of the unprocessed juice. The consumer benefit is thus limited with a significant increase in processing costs and thus selling price. Overall, this technology is still under development in both academia and the commercial world, but scope for its widespread adoption for relatively low value products such as fruit juices is probably limited. Irradiation Although the use of gamma ray irradiation from a source such as Cobalt 60 or Caesium 137 can be very effective in procuring microbiological stability in a variety of products, the technique is permitted by the US Food and Drug Administration (FDA) for only a limited range of foods which does not include fruit juices or soft drinks. Within the UK/EU, its use is even more limited. The use of high energy electron beams and X-rays is also very effective and may be more acceptable to consumers, although consumer acceptance of any irradiated foods remains a major obstacle. Developments of this technology are progressing widely but are likely, in the short to medium term, to be limited to foods where pathogens present a significant microbial hazard.

19.6

Sources of further information and advice

and ASHURST P R (eds) (1996) Fruit Processing, Blackie, Glasgow. (ed.) (2005) Chemistry and Technology of Soft Drinks and Fruit Juices, 2nd edn, Blackwell, Oxford. ASHURST P R and HARGITT R (2009) Soft Drink and Fruit Juice Problems Solved, Woodhead Publishing, Cambridge. GILES G A (ed.) (1999) Handbook of Beverage Packaging, Sheffield Academic Press, Sheffield. PAQUIN P (ed.) (2009) Functional and Speciality Beverage Technology, Woodhead Publishing, Cambridge. ROBERTSON G L (ed.) (2009) Food Packaging and Shelf Life, CRC Press, Boca Raton, FL. STEEN D and ASHURST P R (eds) (2006) Carbonated Soft Drinks, Blackwell, Oxford. ARTHEY D

ASHURST P R

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20 Practical uses of sensory evaluation for the assessment of soft drink shelf life L. L. Rogers, Consultant, UK

Abstract: This chapter is concerned with the practical use of sensory techniques for soft drink shelf life setting and confirmation. It introduces the use of a resource efficient risk-based method for shelf life determination and gives an overview of the different approaches to setting shelf life for soft drinks. A list of questions and answers are posed for the sensory scientist to consider prior to setting up their shelf life experiments, and soft drink-based case studies give details of two different experiments to help with the design of future shelf life experiments. Key words: sensory science, shelf life, soft drinks, practical examples, case studies.

20.1

Introduction

The sensory quality of soft drinks can perhaps be regarded as less critical than the microbiological and analytical specifications; however, the sensory aspects of shelf life are incredibly important for product success in the market place. Microbiological safety will always come first for shelf life determination and should always be considered when devising the sensory assessment plan to ensure the safety of the sensory panellists and any consumers taking part in tests. The legal requirements for nutritional labelling, such as vitamin content over shelf life, are also highly important for food companies as these also constitute a legal requirement. The Food Labelling Directive (2000/13/EEC) states that food businesses must guarantee the safety, legality and quality of the product through its shelf life and it is a legal requirement to assign a shelf life, either a `use by date' or a `best before date', to a food product. The `use by' requirement is for

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pre-packed foods `which, from the microbiological point of view, are highly perishable and are therefore likely after a short period to constitute an immediate danger to human health'. For soft drinks this could apply to freshly squeezed juices, smoothies and chilled juices. A best before date is the `date up to and including which the foodstuff will retain its optimum condition (e.g., it will not be stale)'. Soft drinks such as cordials, pasteurised ready-to-drink products and heat-treated juices would fall into this category. Sensory quality comes in a very close third place due to the fact that consumers will not repurchase a product that they deem low in quality and they will probably not even take the current shelf life of the product into consideration when making this judgement. The first time a consumer tries a low quality end-of-shelf life product, they will be unhappy with the product quality and may never purchase it again ± even if it was one week before the end of its nine-month shelf life. This is particularly true for ambient soft drinks but can also apply to fresh juices and smoothies. The ASTM state that sensory shelf life is `the time period during which the products' sensory characteristics and performance are as intended by the manufacturer' and they also refer to this as being set to `manage business risk and meet business needs' (ASTM, 2005). There will come a point, depending on the product's physical and chemical properties and its storage conditions, when either the product quality will become unacceptable or it will become harmful to the consumer. These two outcomes may happen in the opposite order or may well happen at the same time. A stronger definition is given by the IFST: `shelf life is defined as the time during which the food product will remain safe; be certain to retain desired sensory, chemical, physical and microbiological characteristics; and comply with any label declaration of nutritional data when stored under recommended conditions' (IFST, 1993). The IFST definition leaves one point for discussion, however: `desired sensory . . . characteristics'. This will depend upon the product, the product type or classification, the branding (premium or own label, for example), and the management decisions around the setting of shelf life in each individual company. The shelf life of products is affected by many different aspects of the product ingredients, processing, packaging and storage conditions (e.g., preservatives, water activity, heat treatments, temperature control, oxygen ingress, light, humidity and pack integrity). The IFST group these effects into intrinsic and extrinsic factors. Intrinsic factors are the properties of the final product (e.g., water activity, pH) whereas extrinsic factors are the external effects on the product such as the time±temperature profile of the product, exposure to light and handling through the supply chain. These factors can all interact ± often unpredictably ± and should be taken into account when planning a sensory shelf life study, particularly in respect of food safety. The microbiological safety and nutritional aspects are heavily regulated, whereas the sensory aspects are not, unless one includes groups such as the Trading Standards in the UK where, for example, calling a child's squash

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`peach' flavour where at the end of shelf life there is no peach flavour left, could mislead consumers. However, the sensory aspects of the food product: its flavour, texture and appearance, for example, will play a huge role in the consumer purchase behaviour ± both for first and repeat purchase decisions. The only way to measure this consumer `acceptability' is through sensory methods, be they analytical (triangle tests, profiling, difference from control) or consumer (hedonic, just about right scales, survival analysis) sensory methods (Stone and Sidel, 2004). Predictions of sensory shelf life may be possible through purely analytical methods, but this type of predictive method requires validation before use, using real-time storage conditions and sensory analysis to determine the level at which the marker compound results in an unacceptable product. This is generally conducted through the choice of `marker' chemicals, identified through gaschromatograph-mass-spectrometry (GCMS) methods, often linked to GColfactometry (Reineccius and Heath, 2005). This latter method allows the effluent from the GC column to be `sniffed' in an attempt to identify the key compounds responsible for the flavour of the product. Often the marker chosen is representative of the ageing process and gives a cut-off point for the end of shelf life when it reaches a certain level. Within different companies there will be additional considerations for shelf life setting. The supply chain network will probably play a role. For example, if a product has a shelf life of 7 days but it does not reach the supermarket until day 3, then the product quality for the 4 days the product is on sale will be critical. Supermarket requirements will also play a part: many will not accept a product with less than 70±80% of its shelf life remaining. This may result in a requirement to speed up time to market or extend shelf life by some means.

20.2

Using a risk-based approach to shelf life for soft drinks

The development of the shelf life plan for each experiment can be conducted using a risk-based approach. This is a simple way of making the best use of resources and facilities by only conducting comprehensive shelf life testing where required. All other plans will be based upon the amount of risk associated with each individual experiment. For example, for a new product in a new range, the risk assigned may be `high', as there is no existing data on which to base the shelf life determination. But for the change to a new powdered ingredient supplier from an existing supplier, the risk of the shelf life being affected is probably very low and therefore the minimum amount of testing could be conducted. For the confirmation of shelf life for ambient products the risk is generally low to medium, but within this range the sensory scientist may wish to assign further low to high categories, to further utilise resources effectively.

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597

Estimating shelf life

In order to assign shelf life to a new or adapted product, a review of data from previous experiments or new shelf life studies (see below) would be conducted to determine the stability profile of the product. Appropriate storage conditions and the estimated storage period can then be recommended. A review of similar products on the market and their packaging can also give guidance as to the potential shelf life of a brand new product.

20.4

Determining shelf life

It is well known in the sensory field that the use of quantitative descriptive profiling with a trained sensory panel, combined with consumer liking or acceptance methods, provides both research and marketing teams with valuable consumer insight into product behaviour over time. It is recommended that this approach is taken to set and in some cases monitor shelf life. For example, once the key drivers of consumer liking over shelf life are known, a descriptive trained panel can then be used to predict the end of shelf life for both new and any adapted products. See Section 20.5 for more information. Linking the quantitative profiling and the consumer liking data can be extremely helpful in trying to explain the reasons for any drop-off in consumer liking. The end of shelf life is often set at a certain number, for example a score of 6.0 on the nine-point hedonic scale, or a specific drop in consumer acceptability. This can be established dependent upon the product type: for example for a premium smoothie product the limit might be set at `less than a 0.5 drop' on the nine-point hedonic scale, whereas it might be set at `no greater than a 1.0 drop' on the same scale for a product such as UHT orange juice. In some rare cases an action standard of `no detectable change in the sensory characteristics over shelf life' might be used, but this is generally set as an action standard for premium products where the consumer will not accept any deterioration of the product over shelf life. Another action standard for shelf life testing can be to state that: `the product should fail when it no longer represents the product concept'. This can be very useful for long-life products such as cordials and Tetrapak drinks, which, when they change in flavour, and no longer match the concept, are outside a shelf life that is deemed acceptable by consumers. A similar action standard lies in the knowledge of the product's overall sensory profile especially when this is linked to sensory specifications. If the product's overall sensory profile changes then this is the end of shelf life (MunÄoz et al., 1992). For example, if a drink product has a certain intensity of ginger flavour and this drops by, say 10%, and the sweetness also drops by 10%, the point at which this change happens is the end of shelf life. In fact the developer may deem that this is actually beyond the end of shelf life and set the shelf life to be shorter.

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Food and beverage stability and shelf life

The overall product profile approach can also be adapted with consumer knowledge, in that only product attributes that are known or suspected to be key to the consumers' perception of the product are taken into account (ASTM, 2005). For example, in a fruit drink which develops a very slight `off-note', but this is not detectable by consumers, the change is not used to set the end of shelf life. But as soon as the appearance starts to change, which consumers will most likely notice, this analytical sensory measurement can be used to set the end of shelf life.

20.5

Monitoring shelf life

When monitoring or confirming shelf life, for example within a quality control environment, there are several methods available to the sensory scientist. These can include, for example, difference from control, rapid profiles, targeted attribute profiles and methods based on quality specifications (Carpenter et al., 2000). A control product of some description is generally required for comparison. When an ingredient change is being explored, for example, and no differences are required, this control would be the original product prior to any changes. Ideally this control should be made at the same time as the trial product and from the same batches of ingredients. This will help eliminate any additional changes to the product other than the change under consideration. The control product will be aged in the same way as the new product but generally a fresh control is included in the tests for production comparisons. For ambient products, storage under chilled conditions is generally suitable for the `fresh' control. Sometimes the control is simply data gathered for the existing product and used in the current experiment for comparison. There are a multitude of reasons for confirming shelf life during production. First, confirmation of shelf life is generally carried out on a regular basis on a certain number of batches a year for the simple reason of ensuring that the consumer is still receiving the high quality product they were expecting. Second, changes to ingredients and ingredient suppliers will result in the need to confirm these changes do not affect the product quality nor the product quality over shelf life. Other production changes such as temperature changes on processing, costsaving experiments, mixing times, equipment changes, will also result in the need to confirm that there has been no effect on shelf life. Packaging changes can also have a major effect on shelf life. Quite often packaging changes may be brought in to extend shelf life as advances in packaging technology become more cost effective. For quality teams heavily involved in new product development and the scale-up to factory production, there may well be involvement in the actual setting of shelf life for the product. This may require the setting up of several tests to determine when the end of shelf life has been reached using certain predetermined action standards linked to the risk level the company has agreed to take for that product. For other quality aspects, such as the change in an

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ingredient supplier, process changes or packaging changes, the involvement will be in confirming shelf life in comparison to the current standard product (Meilgaard et al., 1999). This can be a much simpler affair as previous work involving the consumer and the changes to key attributes that drive consumer liking, has already been determined and so more simple sensory difference tests might be used to confirm previous findings. However, if the changes under consideration shorten or lengthen the product's shelf life, consumer validation might be required, resulting in a complex experiment involving not only the product under consideration but also the control product or products.

20.6

Considerations before developing the shelf life plan

There are many aspects of the product's shelf life to consider before developing the plan of approach. These considerations are given in Table 20.1. Each of these are considered in turn below. Is the product stable or for how long is the product expected to be stable for? This is an important starting point, as the length of the expected shelf life will determine how many time points are considered, what sensory tests might be used and when decisions will be able to be made. For example, if the product is a powder, stable for one year under usual production conditions, and a change to the packaging is required which is expected to lengthen its shelf life, then conducting tests every month would seem to be rather excessive. If, however, the product has a shelf life of four months and a change to an ingredient is expected to shorten its shelf life, then early, and regular, testing would be recommended.

Table 20.1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Considerations before developing a sensory shelf life plan

Is the product stable or for how long is the product expected to be stable? When does the product start to change? What attributes change and how? What new attributes are introduced (if any)? What further changes happen after the initial change? Can the changing attributes be explained? How long are the products on the shelf? At what point in a product's life is it consumed? How many consumers have access to older products? When do consumers notice the product change? What effect do the changes have on consumer measures? When are the data required? At what project stage does the shelf life need to be set? How will the sampling plan accommodate these requirements? Are there any accelerated methods for storing the product?

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Food and beverage stability and shelf life

When does the product start to change? This knowledge is very useful as it can determine the start of the testing procedure, apart from, of course, the initial test on the fresh product to set the baseline data. If a product, with a shelf life of ten months starts to change at eight months generally, and the planned ingredient change is expected to shorten shelf life, the best plan may be to select two or three time points up to say, seven months and then test weekly or fortnightly around the expected change point. Then, if the data indicate the shelf life will be shorter, the time points will be readily available from which to select the new point at which the product has reached its end of shelf life. What attributes change and how? What new attributes are introduced (if any)? What further changes happen after the initial change? The main consideration here in the choice of sensory test, is whether or not quantitative data are required on the planned product change, as these data can be very useful in determining the reasons behind any problems and perhaps working towards eliminating these. If information is only needed about the fact a change has happened, then one of the simple difference tests may be the best choice. If the initial change is then followed quickly by a change that it is known to affect consumers' overall liking of the product, it is important to look for this initial change to help decide the end of shelf life: any later may be too late for the consumer. The answer to these questions will help determine the choice of sensory test. For example, if several attributes change over the product's shelf life, it might be worth considering a rapid profile at each time point, particularly if this method is also used for other quality measurements (Lawless and Heymann, 1999). This profile would be conducted using the attributes drawn up during product development phases or may be an existing `language' for a standard product. The addition of one or two `blank' attributes for each modality can be useful to monitor the introduction and level of new attributes over shelf life. A text box can be inserted into the protocol to enable the panellists to score and describe the new attribute simultaneously. If only one attribute is known to change over shelf life, then several methods are available. Ranking of the changing attribute may be useful, or a simple difference test to determine when the change is happening. Difference from control tests can also be very useful in confirming sensory shelf life, particularly as a direct comparison to the original control product is made within the test. Can the changing attributes be explained? This information can help eliminate changes that severely affect the product's shelf life and may well result in product reformulation in extreme cases. If the changes are due to, for example, flavour loss, tainting, colour changes or packaging effects, then further development work might be required to slow down or eliminate these changes ± particularly if the ingredient or packaging change under consideration itself is the main culprit.

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How long are the products on the shelf? At what point in a product's life is it consumed? How many consumers have access to older products? These questions are important when determining the time points to test. For example, if the majority of a product with nine months' shelf life is consumed within three months, then there is little requirement to test comprehensively after this point. But if a fair proportion of people may well purchase the same product when it is seven or eight months old, then testing should be extended over the complete shelf life. When do consumers notice the product change? What effect do the changes have on consumer measures? As soon as the product starts to change, as indicated by the sensory tests at each time point, the sensory scientist will need to determine whether this is noticed by the consumer. This might be carried out in any number of ways. First, data may already exist about the sensory attributes that are key drivers of consumer liking and if one of these key attributes is changing in a negative manner then perhaps the end of shelf life has already been reached. If these data exist but due to the experiment, for example a packaging change, additional attributes have been introduced for which no consumer data exist, it might be wise to conduct a small-scale consumer test to determine whether consumers notice the difference. If there are no data on whether the change will be detected by consumers or what effect it will have on their overall liking, again a small-scale consumer test, with around 60 consumers, can give valuable information. In this particular example it will be worthwhile planning for a consumer test at each time point when the sensory attribute data have been gathered and then deciding whether or not to conduct the test depending upon the result of the analytical sensory test. The action standards developed by the project team will be useful here in determining the end of shelf life. When are the data required? At what project stage does the shelf life need to be set? How will the sampling plan accommodate these requirements? It can be very cost and resource effective to conduct sensory shelf life tests by collecting samples throughout shelf life and conducting all the analysis at the hypothesised end of shelf life. This technique is often referred to as a singlepoint shelf life test. This can be conducted through the storage of one batch or through production of several batches. For short shelf life products it is generally fairly easy to set up and complete. The end of shelf life data will be available after a short time period and it is generally not worth considering any of the other approaches which are used for ambient products. For an ambient product, if it is known that the product stores well under chilled conditions with very little change to sensory characteristics, samples can be put on store in the conditions under study (for example, under supermarket type conditions) and then taken off store at the various time points in the sensory

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plan and put into chilled storage. This has the effect of `pausing' storage. For example, if an ambient product with an estimated shelf life of 26 weeks was stored in supermarket conditions for 13 weeks and chilled (paused) conditions for 13 weeks, although the sample will be 26 weeks old at the end of the shelf life, it is effectively 13 weeks old as it has been `in stasis' for 13 weeks. In this way all samples, for example 0, 3, 6, 9 weeks, can be saved up for a quantitative profile at the end of the 26-week period. This is obviously very cost effective but not particularly useful if the project manager needs to make decisions at 13 weeks of storage. In this case, especially if the project manager has to actually set the shelf life at, say 13 weeks, for a product that has a hypothesised shelf life of 26 weeks, predictive and accelerated methods might prove useful. If, however, chilled storage of the product is not feasible, another approach is to take production batches at certain time points and collect them for the final profile. In this example, production at week 0 would serve for the 26-week-old product, production at week 7 would serve for the 19-week-old product (26 ÿ 19 ˆ 7) and production at week 13 would serve for the 13-week-old product, and so on. In this case the production batches must be similar and this method will not work for products with large batch-to-batch variation, unless this can be taken into account during analysis. In cases where the project manager needs information throughout shelf life, the sensory test will need to be conducted at each time point. This method is generally referred to as multi-point shelf life testing, and is generally more resource intensive than the previous sampling methods. Any accelerated samples would also be included at each time point to allow information on the end of shelf life to be available as soon as possible (see Section 20.6.8 for more information). It is also very beneficial to have a sample, generally the fresh product, within the sample set to allow for changes in the panel scoring, particularly if the expected shelf life is over several months. To enable the attribute list to develop over time, the addition of line scales and text boxes to enable the panellists to score and describe the new attribute can be helpful. Are there any accelerated methods for storing the product? Accelerated shelf life testing (ASLT) (Kilcast and Subramaniam, 2000) can be incredibly useful when setting a shelf life for an ambient product, as the developer does not need to wait for the whole of the product's shelf life to determine the end of shelf life. For example, storage at a higher temperature can result in a prediction in, say, half the time of the real shelf life, although some methods claim to deliver the information in substantially less time. In some cases the developers may use the worse-case scenario risk assessment approach to help with the prediction of shelf life, e.g., heat cycling the pack that is most susceptible to change, or the injection of oxygen into the pack combined with heat treatment. However, there are many critics of accelerated shelf life testing. In a recent review (Hough, et al. 2006), Harry Lawless was quoted: `accelerated testing is

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mostly useless. If it worked, you could make fine aged Bordeaux in an oven. You can't!' The main issue with accelerated conditions is with the production of artefacts: chemical components that would not usually occur under normal storage conditions. Another problem is the amount of resource it takes to validate the accelerated method. The product must be kept at real-time storage conditions for the required length of time to compare to the accelerated test results, thus resulting in a long lead time before the accelerated test can be used with confidence. For confirmatory shelf life tests, this investment will be very worthwhile, but for new product development the resource is less warranted, until the product has been launched and becomes part of standard production. The quandary is that during the new product development phase, the accelerated test is at its most useful. In some cases companies have developed methods that are applicable to a certain group of products, and therefore predictions from accelerated tests are known to give a good enough approximation of the shelf life, until the confirmatory tests are finished.

20.7

Developing the sensory plan

A protocol should be prepared for each shelf life study and it can be very useful to discuss this with the project team prior to its commencement. This could include items from the list below. More details on each listed item are given later in the case studies. · · · · · · · · · · · · · ·

the purpose of the stability study business risk/product risk previous data about the product, similar products or competitor products packaging information and effect on shelf life project stage and when a shelf life decision is required expected shelf life accelerated tests availability storage conditions for each individual sample batches to be selected: number and type which pack type (where there are numerous sizes, for example) sampling plans and time points the testing to be performed at each time point testing specifications and action standards the number of packs required to conduct the specified testing (i.e., how many are required to be put on store and if there is sufficient quantity) · any special requirements (e.g., open shelf life tests, colour assessments).

20.8

Case studies

Using the protocol points above and the risk-based approach to shelf life testing, the sensory scientist can draw up a plan for the shelf life experiment. Two examples are given below and are compared directly in Table 20.2.

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Table 20.2 Case study comparison

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Point/Question

Case Study 1

Case Study 2

The purpose of the stability study Business risk/product risk

To set shelf life for a new product, a fresh juice product sold in one pack type and size. The business risk is high. The product risk is medium. There are no previous data for the final formulation but there are previous data collected during product development from pilot-plant manufacture but in a different pack size. These data are in the form of sensory profiling data, consumer acceptability tests and also analytical data. The product will be sold in a small PET, fully sleeved pack with a flat yellow-coloured cap. This pack and sleeving are ready and will be used for the trial. As the pack is slightly larger than the pack used in the pilot-plant trial, it is hoped this will help extend the shelf life, albeit only by a fraction. Information required throughout the experiment and a prediction required as early as possible. A final `go/no go' decision will need to be made on day 9 of the full-scale production trial. Initial studies suggest could be up to 10 days. The data from the pilot plant study indicate a shelf life of the experimental product of around 6 to 7 days. It is hoped that full production will give a shelf life of 9 days to help with supply-chain issues. Not necessary for the short shelf life. Multi-point shelf life plan. See Table 20.3 for details.

To confirm shelf life for an ambient juice product sold in three different pack sizes. The business risk is low. The product risk is low. Current product, complete data sets available for all three pack types. These data are in the form of sensory profiling data, consumer acceptability tests, difference from control production records and analytical data.

Previous data about product or similar products

Packaging information

Project stage, shelf life decision requirements Expected shelf life

Accelerated test availability Storage conditions for each individual sample

The current packs are for sale in three sizes: small, medium and large. Generally the smaller pack has more shelf life `issues' due mainly to the increased contact of the liquid with the pack. This experiment is simply a monitoring exercise as there have been several recent minor changes to ingredients and production and therefore confirmation of shelf life is required. This is fully documented: six months as per current smallest pack, nine for the medium pack and 12 months for largest pack. Available and validated. Single-point reversed shelf life plan. See Table 20.4 for details.

Batches to be selected, number and type Pack type

Three batches will be selected from the large-scale trial for sensory profiling and analytical tests; however, the consumer tests will be conducted on only one of the batches. This product will only be sold in one pack type and this pack will be studied in this experiment.

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Sampling plans and time points

As the shelf life is so short, and data are required as the experiment progresses, analysis of the samples will be conducted every day. See Table 20.3 for details.

The testing to be performed at each time point

Sensory profiling will be conducted using the existing attribute list. Small-scale consumer tests will also be carried out at day 1 and planned for day 5 and every day up to the end of shelf life. See Table 20.3 for overview of testing.

Testing specifications and action standards

The action standard for this experiment is: the shelf life for the new juice product will be longer than 7 days. If not the product will be reformulated. The end of shelf life will be set as when the consumer overall liking score drops by 0.5 or more on the 9-point hedonic scale. There will be sufficient quantity of product as the trial is full scale.

The number of packs required to conduct the specified testing (i.e., how many are required to be put on store and if there is sufficient quantity) Any special requirements (e.g., open shelf life tests, colour assessments)

Open shelf life tests will be required in the future. During this experiment the microbiological assessments on open shelf life will be conducted.

Three batches will be selected from the large-scale trial to be conducted. Each batch will be packed into the three different pack sizes. Only the smallest and largest pack sizes will be tested at the end of shelf life. The medium pack size will be kept on store in case the analysis highlights any issues. As the product has such a long shelf life, and data are not required immediately, analysis of the samples will be conducted at the end of shelf life. See Table 20.4 for details. All analysis will be conducted at the end of shelf life as this experiment is for confirmation only and data are not required earlier. A full quantitative profile will be conducted using the current attribute language. A small-scale consumer test is planned in case of any issues. All products should have the same shelf life as per current specifications. The action standard is: shelf life will be the same as per current production.

There will be sufficient quantity of product as the trial is full scale. There will be a requirement to put on store 100 spare units in case the sensory profiling tests indicate any concerns and consumer tests are required. No special requirements for shelf life testing.

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20.8.1 Case study 1 The purpose of the stability study To set shelf life for a new product, a fresh juice product sold in one pack type and size. Production will be at a new contract packer who currently packs other products for the business. Business risk/product risk The business risk is high as this is a new product with a large advertising campaign. The product risk is medium as the product appears to change very little over the first few days of shelf life, but more data are required for extending the shelf life, hence this full-scale experiment. Previous data about product or similar products There are no previous data for the final formulation but there are previous data collected during product development from an experimental pilot-plant manufacture in a different pack size. These data are in the form of sensory profiling data, consumer acceptability tests and also analytical data. The contract manufacturer is experienced in making similar products and produces for similar ownlabel products. Packaging information The product will be sold in a small PET, fully sleeved bottle with a flat yellowcoloured cap. This pack and sleeving are ready and will be used for the trial. As the pack is slightly larger than the pack used in the pilot-plant trial, it is hoped this will help extend the shelf life, albeit only by a fraction. Project stage, shelf life decision requirements The decision on the shelf life the product might reach is required throughout the experiment and a prediction required as early as possible. A final `go/no go' decision will need to be made on day 8 of the full-scale production trial. Expected shelf life In studies carried out before the pilot-plant shelf life experiment, similar competitor products indicated that the shelf life of this new product could be up to 10 days. The data from the pilot-plant study indicate a shelf life for the experimental product of around 6±7 days. The product developed a dried fruit note and lost the full intensity of its deep red colour. This affected the overall liking in the small-scale consumer tests which dropped from a score of 6.7 on the 9-point hedonic scale at day 0, to 6.0 at day 8. The sensory action standard has been set to indicate the end of shelf life when the consumer overall liking score drops by 0.5 or more on the 9-point hedonic scale. The sensory profiling data will give an early warning of this change when similar levels of dried fruit notes and a drop in red coloration are seen. It is hoped that full production, with its less harsh processing conditions, will give a shelf life of 10 days to help with supply-chain issues although this does

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not look likely from the previous data. A final `go/no go' decision will need to be made on day 8 of the full-scale production trial as this fits in with the panel working hours and is probably the longest shelf life possible based on the previous data. Accelerated tests availability Not necessary for the short shelf life as results will be ready in around two weeks. Storage conditions for each individual sample The experiment will be set up as a multi-point experiment conducted every day. See Table 20.3 for details. All product is stored chilled as per storage instructions developed during pilot-plant study. Samples from each batch will also be stored frozen for analysis on day 5 and day 9 and also in a later profile to determine whether the product can be frozen for future tests. Batches to be selected, number and type Three batches will be selected from the large-scale trial for sensory profiling and analytical tests; however, the consumer tests will be conducted on only one of the batches. The sensory profiling data will be used to determine the extent of the batch-to-batch variability. The production trial is required to be conducted on a Wednesday (or Thursday) to match with panel attendance days. Which pack type? This product will only be sold in one pack type and this pack will be studied in this experiment. Sampling plans and time points As the shelf life is so short, analysis of the samples will be conducted on day 0, day 1, day 2, day 5 (thus allowing for the weekend), day 6, day 7, day 8, day 9 and possibly day 12. Decision is needed if shelf life can be extended. Decision is also needed regarding panellists' attendance over second weekend if necessary. Further analysis days will be agreed as data are gathered through the joint analytical, micro and sensory meetings. Testing is also planned for day 12 in case the results from full-scale trial look better than the pilot-plant production. The testing to be performed at each time point Sensory profiling will be conducted using the existing attribute list. This attribute list was generated during the previous shelf life trials for the pilot-plant produced juice. Time will be set aside for additional training using the different batches on day 0 of the experiment to confirm the attribute list/vocabulary. Small-scale consumer tests will also be carried out at day 1 and planned for day 5 and every day up to the end of shelf life. See Table 20.3 for an overview of the testing. The tests will be conducted if the sensory profiling data indicate that consumer data will help in the shelf life determination.

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Table 20.3 Case study 1 experimental design ß Woodhead Publishing Limited, 2011

Day

Profile notes

Consumer test notes

Day 0 Wednesday

Day 1 Thursday

Full-scale trial: 3 batches of product produced

All product stored chilled Selection stored frozen

Sensory profile conducted after a panel session to confirm vocabulary

Sensory profile: day 1 (3 batches and 1 repeated to confirm panel performance) Small-scale consumer test (n ˆ 60) to assess any changes from pilot plant production

Day 2 Friday

Sensory profile: day 2 (3 batches and 1 repeated to confirm panel performance)

Day 3 Saturday

Day 4 Sunday

Weekend

Weekend

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Day

Day 5 Monday

Meetings

Joint analytical, micro and sensory meeting to discuss results so far

Profile notes

Sensory profile: day 5 (3 batches and 1 repeated to confirm panel performance)

Notes

Frozen product also assessed in sensory profile

Consumer test notes

Small-scale consumer test (n ˆ 60) to assess any effect on consumer liking of shelf life changes (if any)

Day 6 Tuesday

Sensory profile: day 6 (3 batches and 1 repeated to confirm panel performance)

Small-scale consumer test (n ˆ 60) to assess any effect on consumer liking of shelf life changes (if any)

Day 7 Wednesday

Day 8 Thursday

Day 9 Friday

Joint analytical, micro and sensory meeting to discuss results so far

Go/no-go decision ± meeting at 3pm

Final meeting

Sensory profile: day 7 (3 batches and 1 repeated to confirm panel performance)

Sensory profile: day 8 (3 batches and 1 repeated to confirm panel performance)

Sensory profile: day 9 (3 batches and 1 repeated to confirm panel performance)

Decide if panel working weekend

Agree future tests after day 9 (see note below)

Frozen product also assessed in sensory profile

Small-scale consumer test (n ˆ 60) to assess any effect on consumer liking of shelf life changes (if any)

Small-scale consumer test (n ˆ 60) to assess any effect on consumer liking of shelf life changes (if any)

Small-scale consumer test (n ˆ 60) to assess any effect on consumer liking of shelf life changes (if any)

Day 12: Sensory profile: day 12 (3 batches and 1 repeated to confirm panel performance) to assess if a longer shelf life may be possible. In-house consumer test (n ˆ 60) to assess any effect on consumers liking of shelf life changes also planned.

610

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Testing specifications and action standards The action standard for this experiment is: the shelf life for the new juice product will be longer than 7 days. Any issues in the sensory profiling results will be confirmed by consumer tests. If the shelf life is less than 7 days, the product will need to be reformulated. The later profiling tests may well be performed to help understand the changes happening in the product. These data will be used alongside the analytical testing data to help with the reformulation. The number of packs required to conduct the specified testing (i.e., how many are required to be put on store and is there sufficient quantity) The sensory tests planned will require ten product units at each time point and the consumer tests will require 60 of each at each time point. There will be sufficient quantity of product as the trial is full scale. A temporary refrigerated unit is in place at the contract manufacturer and has been used for other product trials. Any special requirements (e.g., open shelf life tests, colour assessments) Open shelf life tests will be required in the future. During this experiment the microbiological assessments on open shelf life will be conducted. A further open shelf life sensory experiment will be set up once the microbiological data have shown how long the product can be stored open safely. 20.8.2 Case study 2 The purpose of the stability study To confirm the shelf life for an ambient juice product, sold in three different pack sizes, due to recent production changes. The production will be at the current site where the recent production changes have happened. Confirmation of shelf life is required due to the numerous production changes. Business risk/product risk The business risk is low as it is simply a confirmation that the three packs still have the same shelf life. The product risk is also low as the product changes very little over shelf life but does change markedly as the end of its current shelf life is reached. Previous data about product or similar products This experiment concerns a current product and complete data sets are available for all three pack types. These data are in the form of sensory profiling data, consumer acceptability tests, difference from control production records and analytical data. The data span almost three years of production. The sensory vocabulary and consumer questionnaire exist and have been used during other experiments regarding this product. Packaging information The current product is for sale in three sizes: small, medium and large. Generally

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the smaller pack has more shelf life `issues' due mainly to the increased contact of the liquid with the pack. Project stage, shelf life decision requirements This experiment is simply a monitoring exercise as there have been several recent minor changes to ingredients and production, and therefore confirmation of shelf life is required as per production protocols. Expected shelf life This is fully documented: six months for the smallest pack, nine for the medium pack and 12 months for largest pack. Accelerated tests availability The accelerated test is available, in current use and has been validated. The acceleration involves storage of the products at an extended temperature only. The accelerated test predicts at double storage time (i.e., 6 months' storage under accelerated conditions is equivalent to 12 months' real-time storage). Generally tests are carried out on product stored chilled, at ambient (under supermarket conditions) and at the accelerated temperature. However, as this experiment does not require data upfront, and as the accelerated test is already validated, no storage at accelerated temperatures will be included in this study for confirmation. However, a simple difference from control test will be conducted with accelerated smaller packs compared to chilled stored controls, three months into the storage time to give an early warning of any issues. It would be a simple case to pick one, or even all, of the pack types to incorporate a validation exercise if needed. Storage conditions for each individual sample The experiment will be set up as a single-point reversed shelf life plan. Table 20.4 gives more details. All samples will be collected and placed on store at the start of shelf life. All samples will be stored chilled and under shelf conditions (i.e., supermarket conditions). They will be taken off store and placed into chilled storage at the required time points therefore `pausing' the storage time. The majority of analyses will be conducted at the end of shelf life. Spare product will be stored under shelf conditions for consumer tests if required. Batches to be selected, number and type Three batches will be selected from one production week. Each batch will be packed into the different pack sizes, labelled and stored accordingly. Which pack type? Only the smallest and largest pack sizes will be tested at the end of shelf life. The medium pack size will be kept on store in case the analysis highlights any issues.

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Table 20.4 Case study 2 profiling experimental design

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Week

Week 0

Week 1

Week 20

Week 22

Week 24

Storage conditions

Full-scale production. Tests conducted on all three pack sizes. Product stored chilled and under ambient supermarket conditions

Sensory profile conducted after a panel session to confirm vocabulary

Samples (small pack size stored at ambient temperatures) taken off ambient storage and stored chilled (or `paused')

Samples (small pack size stored at ambient temperatures) taken off ambient storage and stored chilled (or `paused')

Samples (small pack size stored at ambient temperatures) taken off ambient storage and stored chilled (or `paused')

Notes

Single-point reversed shelf life plan starts

All pack sizes included in the same profile

These samples will be equivalent to storage for 20 weeks

These samples will be equivalent to storage for 22 weeks

These samples will be equivalent to storage for 24 weeks

Week

Week 26

Week 35

Week 39

Week 48

Week 52

Storage conditions

Samples (all three pack sizes stored at ambient temperatures) taken off ambient storage and stored chilled (or `paused')

Samples (last two pack sizes stored at ambient temperatures) taken off ambient storage and stored chilled (or `paused')

Samples (last two pack sizes stored at ambient temperatures) taken off ambient storage and stored chilled (or `paused')

Samples (large pack size stored at ambient temperatures) taken off ambient storage and stored chilled (or `paused')

Samples (large pack size stored at ambient temperatures) taken off ambient storage and analysed.

These samples will be equivalent to storage for 26 weeks

These samples will be equivalent to storage for 35 weeks

These samples will be equivalent to storage for 39 weeks

These samples will be equivalent to storage for 48 weeks

Notes

All samples stored chilled/paused taken off store and analysed. Medium pack taken off store and analysed if required. These samples will be equivalent to storage for 52 weeks

Profile notes

Sensory profile conducted on all samples and batches for both smallest and largest pack size (after one panel session to check vocabulary)

Consumer test notes

Small-scale consumer test (n ˆ 60): chilled versus 26 (small pack), 39 (medium pack) and 52 week (large pack) ambient to assess any effect on consumers liking

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Sampling plans and time points The product has a shelf life of 52 weeks in the current pack and 26 weeks in the smallest pack. Shelf-stored samples will be taken at 0, 22, 24 and 26 weeks for the smallest pack and 0, 26, 35, 39, 48 and 52 weeks for the largest pack. Accelerated samples will be taken at 11 and 13 weeks for the smallest pack and 24 and 26 weeks for the largest pack. The testing to be performed at each time point All analysis will be conducted at the end of shelf life as this experiment is for confirmation only and data are not required earlier. A simple difference from control test will be conducted with accelerated smaller packs compared to chilled stored controls, three months into the storage time to give an early warning of any issues. A full quantitative profile will be conducted using the current attribute language; however, the panellists will be presented with all samples to update the language prior to conducting the three replicates on the stored samples. A small-scale consumer test is planned in case of any issues. Testing specifications and action standards All products should have the same shelf life as per current specifications. The action standard is: shelf life will be the same as per current production. Any issues in the sensory profiling results will be confirmed by consumer tests. The number of packs required to conduct the specified testing (i.e., how many are required to be put on store and is there sufficient quantity) The sensory tests planned will require five product units for the large pack and ten for the small pack at each time point. The time points have been kept to a minimum, so there are no store room issues. There will be sufficient quantity of product, as the trial is full scale. There will be a requirement to put on store 100 spare units in case the sensory profiling tests indicate any concerns and consumer tests are required. Any special requirements (e.g., open shelf life tests, colour assessments) No special requirements for shelf life testing.

20.9

Future trends

In the future, consumer expectations and consumer power can only be expected to increase. This may well result in a demand for products of a higher quality over the whole of their shelf life, as opposed to the trend in cheaper `close to the end of shelf life' sales seen recently. A similar trend has been seen in the increase of high quality products even for own label variants, as consumers' high quality demands are met. Therefore the combination of both analytical and consumer sensory methods can only be expected to increase, as companies realise the need for robust end-of-shelf life setting and confirmation.

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Improvements in the packaging field such as modified-atmosphere and advanced technology in the production of different types of packaging, will also benefit shelf life in the future. These include development of new coatings and barriers, the use of oxygen scavengers, particularly in caps, and the development of new techniques for packaging manufacture. Different production methods, such as microwave or high pressure processing may also help produce foods with a longer shelf life. Changes to the supply chain may also impact on shelf life. New methods of monitoring temperature in the supply chain and intelligent pack labels have the potential to both increase and decrease shelf life where required to help deliver higher quality products to the consumer. Predictive methods will also be more widely available, and using statistical modelling techniques will result in more accurate setting of shelf life, leading to higher quality foods at the end of shelf life. The use of more sensitive analytical techniques will allow shelf life data to be gathered more quickly and easily and will also help develop the understanding of the various mechanisms of the degradation of food and drink products over shelf life. The use of microbiological models and risk-based approaches will be an area of interest for food scientists in the future. New ingredients such as natural antimicrobials, new plant breeding techniques, and genetic engineering may also be areas to watch out for in future shelf life extensions.

20.10

References

(2005), Standard Guide for Sensory Evaluation Methods to Determine the Sensory Shelf Life of Consumer Products, E 2454-05. CARPENTER, R P, LYON D H and HASDELL, T A (2000), Guidelines for Sensory Analysis in Food Product Development and Quality Control, Aspen, Gaithersburg, MD. HOUGH, G, VAN HOUT, D and KILCAST, D (2006), `Workshop summary: sensory shelf-life testing'. Food Quality and Preference, 17, 640±645. IFST (1993), Shelf Life of Foods ± Guidelines for its Determination and Prediction, IFST, London. KILCAST, D and SUBRAMANIAM, P (2000), The Stability and Shelf-life of Food, CRC Press, Boca Raton, FL. LAWLESS, H T and HEYMANN, H (1999), Sensory Evaluation of Food: Principles and Practices, Aspen, Gaithersburg, MD. MEILGAARD, M, CIVILLE, G V and CARR, B T (1999), Sensory Evaluation Techniques, CRC Press, Boca Raton, FL. Ä OZ, M, CIVILLE, G V and CARR, B T (1992), Sensory Evaluation in Quality Control, Van MUN Nostrand Reinhold, New York. REINECCIUS, G and HEATH, H B (2005), Flavor Chemistry and Technology, CRC Press, Boca Raton, FL. STONE, H and SIDEL, J L (2004), Sensory Evaluation Practices, Academic Press, London. ASTM

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21 The stability and shelf life of coffee products L. Manzocco, S. Calligaris and M. C. Nicoli, University of Udine, Italy

Abstract: Shelf life assessment of coffee derivatives is a complex task due to the wide number and heterogeneity of products belonging to this food category. For this reason, shelf life assessment strategy must be carefully designed taking into account the peculiarity of the product. Shelf life testing of coffee derivatives will be discussed, focusing initially on the main critical events affecting the stability of coffee products and factors controlling the deterioration rate. Shelf life assessment strategies will then be illustrated by considering the identification of the acceptability limit described by the proper indicator and methodologies for shelf life testing under actual and accelerated storage conditions. Key words: coffee derivatives, acceptability limit, kinetic modelling, accelerated shelf life test.

21.1

Introduction

The shelf life of coffee products may range from a few minutes/hours for an espresso cup or a coffee brew, respectively, to several months for ground and roasted coffee beans, ending up with many years for instant coffee. In the first case, shelf life is too short to need an evaluation, in the last one it is so long that appropriate procedures for shelf life prediction should be developed. Such a variegated situation is the result of the fact that coffee products are wide and heterogeneous as well as their stability and lifespan. Coffee derivatives may exert strongly different shelf lives due to the combination of several variables including intrinsic aspects, such as product composition and characteristics, and

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Table 21.1 Key unit operations to obtain the main coffee products and relevant effects Unit operation Phenomena

Effect

Product

Roasting

Water removal Non-enzymatic browning Pyrolysis

Bean darkening Volatile and CO2 formation Bean expansion Volatile and CO2 release

Roast coffee

Grinding

Particle size reduction

Surface area increase Volatile and CO2 release

Roast and ground coffee

Brewing

Solid-liquid extraction

Extraction of soluble and Coffee cup emulsifiable substances from the coffee matrix to water

Dehydration

Water removal

Volume decrease Solid concentration

Coffee concentrate, instant coffee

Microbial inactivation

Ready-to-drink coffee drinks

Pasteurization Sanitization Sterilization

extrinsic ones, mainly relevant to packaging and storage conditions. In addition, marketing considerations are also expected to enter into the shelf life decision process since the extent of consumer satisfaction is fundamental for coffee producers. Therefore, shelf life testing of coffee derivatives should be carefully designed considering all these aspects. Green coffee beans from Coffea Arabica, Arabica coffee, and Coffea canephora, Robusta coffee, are the starting material for all coffee derivatives. The latter comprise roasted coffee ± decaffeined or not ± and a wide variety of convenience and semi-manufactured products such as coffee concentrates, instant coffee and ready-to-drink beverages. Table 21.1 shows the key technological steps applied to obtain the most important coffee products. The first operation needed to convert green beans into a beverage is roasting. This is the key technological operation allowing dark beans with the characteristic pleasant flavour and aroma to be obtained. During roasting, coffee beans are put in contact with a hot surface or gases to increase their temperature to 220 ëC. The main reactions occurring are water removal, carbohydrate fragmentation and polymerization, via non-enzymatic browning reactions, and pyrolysis. The chemical composition of the beans is drastically modified with release of large amounts of carbon dioxide (CO2) and the formation of hundreds of substances associated with coffee aroma and taste. Among reaction products, there is a wide number of volatiles and non-volatiles, such as melanoidins and their precursors. The formation of volatiles and CO2 during roasting in combination with the high temperatures of the environment causes the expansion of the beans and the formation of pores and pockets. The beans become very brittle and progressively lose their ability to entrap and retain volatiles. Thus, volatile

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and CO2 are easily released into the vapour phase due to diffusion mechanisms favoured by the pressure gradient between the internal bean pores and atmosphere. For this reason, a degassing step is carried out on roasted coffee before packaging in order to avoid the swelling of the packages during shelf storage. Alternatively, appropriate packaging solutions should be implemented to control these releases and to avoid over-pressure inside the package with possible bursting and loss of package integrity (Nicoli et al., 2010). The whole roasted beans should be ground into smaller fragments before extraction. The purpose of this operation is to increase the specific extraction surface and facilitate the transfer of soluble and emulsifiable substances from the coffee matrix into the brew (Petracco, 2005a). The roast and ground coffee is subjected to a solid-liquid extraction with hot water to obtain a beverage that may be consumed as is or constitute a semimanufactured product. The extraction methods adopted can vary greatly from country to country, strongly affecting the sensorial properties of the coffee (Pictet, 1987; Petracco, 2001, 2005b). Coffee brews prepared at domestic and catering level are generally consumed immediately after preparation. At industrial level, the dehydration of the coffee brews leads to the production of instant coffee or coffee concentrates depending on the degree of water removal. In the case of instant coffee, the dehydration is achieved by freeze drying or by spray-drying, whereas coffee concentrate is obtained through thermal or cryo-concentration (Clarke, 2001). While instant coffee is highly appreciated due to its convenient physical form and long shelf life, coffee concentrates are increasingly used as ingredients for the food industry or as semi-manufactured products for vending machines and catering. Finally, pasteurized or sterilized ready-to-drink coffee beverages have recently become very popular, especially in Asian countries, where the tradition of consuming freshly prepared coffee brews is not widespread. They could be variously formulated containing, besides coffee brews, sugar, dairy products, emulsifiers and other additional ingredients (Petracco, 2001). Although, in term of sold volumes, ready-to-drink coffee drinks are minor coffee products, they represent an interesting and dynamic area for both coffee roasters and soft drink producers.

21.2 Main critical events affecting the stability and shelf life of coffee products Table 21.2 summarizes the main critical events leading to quality depletion of coffee derivatives during their life on the shelf. While the instability of roasted and instant coffee is mainly due to the development of chemical and physical changes including oxidation, volatile loss and physical collapse, the stability of coffee derivatives with higher water content (i.e., coffee concentrates and brews) can also be potentially affected by microbial spoilage as well as by the development of chemical reactions requiring reactants' mobility.

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Table 21.2 Main critical event leading to quality depletion during shelf life Product

Critical event

Roast and ground coffee

Oxidative reactions Volatile loss Oxidative reactions Physical collapse Microbial spoilage Oxidative reactions Volatile loss Ester hydrolysis Non-enzymatic browning Microbial spoilage Oxidative reactions Volatile loss Ester hydrolysis Non-enzymatic browning

Instant coffee Coffee concentrate

Ready-to-drink coffee beverage

In general terms, all coffee products are known to lose their particular sensory properties due to the occurrence of a defect generally referred to as `staling'. Buffo and Cardelli-Freire (2004) defined coffee staleness as `a sweet but unpleasant flavour and aroma of roasted coffee which reflects the oxidation of many of the pleasant volatiles and the loss of others'. Both these phenomena contribute to coffee staling even if the relative weight of one mechanism in comparison with the other is not easy to highlight. The development of oxidative reactions causes not only the loss of pleasant aroma compounds but also the formations of off-flavours (Nicoli and Savonitto, 2005). The sensitivity of roasted coffee towards oxidation reactions is high due to the presence of a large number of strongly active volatile and non-volatile compounds that easily react with oxygen. Among these substances, aromaimpact components, such as aldehydes, ketones and thiols, are particularly prone to oxidation along with the lipid fraction of coffee (Nicoli and Savonitto, 2005; Ortola et al., 1998). The latter ranges from 10 to 14% and contains about 75% of triacylglycerols with a high percentage of unsaponificables, including diterpene alcohols, sterols and tocopherols (Speer and Kolling-Speer, 2001). It should be noted that the oil susceptibility is increased just after roasting due to its migration to the surface of the beans, where the risk of oxidation is maximal. Besides the presence of compounds clearly prone to oxidation, the role of other substances with strong antioxidant capacity should not be underestimated. Several authors (Nicoli et al., 1997; Daglia et al., 2000; Krings and Berger, 2001; Anese and Nicoli, 2003) have attributed the strong antioxidant properties of coffee to the presence of both naturally occurring phenolics, such as chlorogenic acids, caffeic, ferulic and cumaric acid, and heat-induced polyphenol-type structures, which are formed due to non-enzymatic browning reactions during roasting. Coffee was indeed demonstrated to act in vitro as pro-oxidant (Andueza et al., 2004, 2009). These apparent contradictory results can be

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explained considering that, depending on the extent of non-enzymatic browning, pro-oxidants and/or antioxidants can be formed. In the case of the Maillard reaction, the early stages of the reaction are responsible for the formation of prooxidant compounds while in the advanced stages antioxidant products seem to prevail (Manzocco et al., 2001; Calligaris et al., 2004a). These literature data highlight once again the compositional complexity of roasted coffee and explain why the oxidative reaction pathway in coffee product is not yet completely understood. The occurrence of oxidative reactions could also lead to the quality decay of instant coffee, coffee concentrates and drinks. The susceptibility depends greatly on the characteristics of the coffee derivatives and is due to the presence of sensitive compounds extracted from roasted coffee during brewing as well as of other ingredients added to the formula. Volatile concentration could also change due to their release from bean pores. In this way volatiles could be lost together with CO2 and the intensity of these changes is associated with the technological and packaging solutions adopted after roasting. As regards coffee brews, their aroma change during storage has been related to a supplementary mechanism. In particular, the loss of low-boiling potent aroma compounds, particularly sulfurcontaining key odorants responsible for fresh aroma, has been related to interactions with non-volatile components, such as melanoidins. For instance, odour-active thiols could be rapidly covalently bound by melanoidins just after coffee brew preparation causing a decrease in the overall sulphury-roasty odour (Hofmann et al., 2001; Hofmann and Schieberle, 2002; Mueller and Hofmann, 2007). The quality depletion of instant coffee is also due to its high hygroscopic properties. An increase in moisture content to 7±8% is responsible for caking and collapse of powder or granules which become a pasty or solid mass with reduced aroma compound retention (Clarke, 1987b). Additional detrimental events could take place during storage of coffee beverages. Depending on their water activity and composition, coffee concentrates and brews could present microbial risk. Coffee concentrates having 17% (w/w) water content demonstrated to be very stable from a microbiological point of view up to 1 year at temperatures between 4 and 35 ëC. This was attributed to their low pH and redox potential as well as to the presence of melanoidins with strong antimicrobial activity (Manzano et al., 2000). Coffee beverages also show a very low chemical stability, characterized not only by a change in the flavour profile but also an increase in general perceived sourness. These changes are accompanied by a pH decrease, corresponding to an increase in the titratable acidity (Manzocco and Nicoli, 2007; Perez-Martinez et al., 2008a). Quality depletion of coffee brews as well as of coffee concentrates starts immediately after brewing and proceeds at a significant rate, even at subzero temperatures. At present, very little is known about the mechanisms underlying liquid coffee instability. It has been suggested that the decrease in pH could be the consequence of complex reactions, probably related to nonenzymatic browning pathways involving carbohydrates and amino acids.

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Additional mechanisms involving lactone hydrolysis could also contribute to pH decrease (Balzer, 2001).

21.3

Ensuring stability and extending the shelf life of coffee

In general terms, the kinetics of deteriorative reaction of foods and thus their shelf life is a function not only of intrinsic factors (Ii) typical of the product but also of extrinsic ones (Ei) linked with environmental and packaging conditions: k ˆ f …Ii ; Ei †

21:1

Thus, in order to ensure or extend the product stability, both classes of factors should be considered. Table 21.3 summarizes the main intrinsic and extrinsic factors controlling the kinetics of the critical events which affect the shelf life of coffee derivatives. 21.3.1 Factors controlling the rate of volatile release in coffee derivatives As previously reported, volatile release could greatly affect the shelf life of coffee products. The pressure gradient between internal bean structure and package atmosphere can be regarded as the main driving force affecting the extent of volatile release. Volatile release is greatly affected by both technological procedures applied after roasting (e.g., processing conditions during Table 21.3 Intrinsic and extrinsic factors controlling the kinetics of the critical events which affect shelf life of coffee products Intrinsic factors

Extrinsic factors

Volatile release

Surface area Glass transition temperature (Tg) Other ingredients affecting Tg

Pressure Temperature Relative humidity

Oxidation

Surface area Redox potential Antioxidant and pro-oxidants Other oxidizable ingredients

Oxygen partial pressure Temperature Relative humidity Light

Physical collapse

Glass transition temperature Anticaking agents Other ingredients affecting Tg

Temperature Relative humidity

Ester hydrolysis and non-enzymatic browning

Water activity pH-regulator agents Formulation

Temperature Light

Microbial spoilage

Water activity Redox potential Antimicrobials

Temperature

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degassing or grinding) and packaging conditions. For instance, volatiles are easily lost together with CO2 through the one-way safety valve which is fitted on the package to avoid it bursting. Volatile release from roasted coffee can be further decreased by creating a pressure inside the package that is higher than the atmospheric one. Such high pressure can be established upon CO2 and volatile release from roasted coffee packed immediately after air-cooling or by sealing the filled containers in the presence of proper gasses at the desired overpressure (Nicoli and Savonitto, 2005). In addition, for non-hermetically sealed products, storage temperature is also expected to be critical for volatile release. In this case, the temperature dependence of volatile release can be well described by the Arrhenius equation from 4 to 40 ëC (Nicoli and Savonitto, 2005). In particular, the temperature sensitivity, expressed in term of Q10, was about 1.5. This means that for any increase of 10 ëC of temperature, the rate of volatile release increases 1.5-fold. One additional factor affecting volatile release is the physical structure of coffee, which is particularly important in the case of instant coffee. Volatile release is affected by coffee water activity (aw) and, consequently, by its glass transition temperature (Tg). The high volatile retention at low aw values, corresponding to a glassy system, was attributed to the entrapping capacity of the amorphous glass, where diffusion is very low. Plasticization by absorption of water may cause the depression of Tg below the room temperature, and hence the glass± rubber transition of the matrix. In these conditions the structural changes of the matrix may allow initial collapse to occur and volatile to be released (Anese et al., 2005). To control the physical state of coffee matrices, the choice of a proper packaging material with adequate water vapour transmission rate is crucial. For instance, the shelf life of instant coffee packed in flexible films seems to be well correlated to their water vapour transmission rate (Alves and Bordin, 1998). 21.3.2 Factors controlling the rate of oxidation in coffee derivatives The control of oxidative reactions still remains one of the major challenges for food scientists not only for coffee derivatives but also in other foods. The only way to design efficient constraints able to hinder lipid oxidation implies the deeper understanding of the factors affecting oxidative reaction. Unfortunately, the chemical structure of the huge number of compounds that could suffer oxidation in coffee derivatives, as well as the reaction pathways involved, is far from being elucidated. Both intrinsic and extrinsic factors play a critical role in determining the oxidation rate. For this reason, a number of different strategies may be simultaneously applied in order to hinder the development of oxidative reactions in coffee products. In other words, different hurdles should be designed to efficiently control the detrimental effects of oxidation. Since the intrinsic factors are hardly changeable, more possibilities come from the careful definition of the environmental factors. As is well known, oxygen partial pressure, temperature, relative humidity and light are critical in determining the oxidation rate and thus the product shelf life.

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Table 21.4 Shelf life data of roasted whole and ground coffee packed under different conditions (modified from Nicoli et al., 2010) Packaging technique Air Under vacuum Inert gas Pressurization Active packaging a b

Oxygen percentage

Shelf life (months)

21% 4±6% 1±2% < 1% < 1%

1±3a 4±6a/>12b 6±8a/>12b >18a,b >18b

Shelf life data from Nicoli and Savonitto (2005) Shelf life data claimed on product label

As shown in Table 21.4, decreasing the oxygen percentage inside the packaging, the shelf life of roasted whole and ground coffee could be greatly improved. According to Cardelli and Labuza (2001), the ground coffee shelf life was increased by about 20 times when O2 decreases from 21.3 to 0.5 kPa. For this reason, packing in air is nowadays an obsolete solution due to the very short shelf life of the product. The easiest way of modifying the atmosphere composition is based on the application of vacuum. The level of O2 could be reduced up to 4±6% prolonging the product shelf life. The latter could be further improved by reducing the oxygen level up to 1±2% by replacing the air inside the package with an inert gas, such as N2 or CO2. Active packaging has also been proposed to reach oxygen percentage residue in containers of less than 1%. To achieve this, sachets containing oxygen scavenger systems are included inside the package (Vermeiren et al., 1999). Similar oxygen concentration can also be achieved by high pressure packaging, thus hindering oxidative reactions. The extra pressure inside the package increases the retention of volatiles in the lipid phase leading to their protection. In addition, the quality improvement of coffee is achieved by an additional hurdle: the reduction of oil migration under pressurized conditions (Clarke, 1987a). The oil is thus less prone to oxidation because it tends to remain inside the cells. Besides the oxygen percentage inside the packaging, storage temperature can also affect the oxidation rate, following the well-known Arrhenius equation. The effect of temperature on ground and roasted coffee shelf life was studied by Cardelli and Labuza (2001) determining Q10 values and the energy of activation (Ea) for kinetics of sensory deterioration of roast and ground coffee. The results for Q10 indicated 15±23% acceleration per 10 ëC increase in temperature at an oxygen concentration of 10%. However, if coffee derivatives are packed under modified atmosphere conditions, allowing the decrease of oxygen below 0.5%, the rate of reaction change is almost negligible after up to 12 months of storage, independently of storage temperature in the range from 20 to 45 ëC (Nicoli et al., 2009). This means that oxygen concentration within the package seems to be much more critical than storage temperature.

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Table 21.5 Shelf life data of roast and ground coffee packed under 3.0 kPa oxygen partial pressure and stored at 22 ëC (elaborated from Cardelli and Labuza, 2001) aw 0.11 0.25 0.41

Shelf life (days) 19 9 5

Relative humidity could also affect the development of oxidative reactions. It is well known that lipid oxidation in dried foods is affected by moisture. In extremely dry and extremely moist environments, lipid oxidation develops rapidly, while at intermediate moisture levels, normally corresponding to the monomolecular water layer, the rate of lipid oxidation goes to a minimum (Labuza et al., 1971). In the case of coffee products, the literature reports that water activity plays an important role in determining the acceptability of ground and roasted coffee. Even if no specific evidence is available on the formation of oxidation products as a function of water activity, Cardelli and Labuza (2001) found a decrease in roasted ground coffee shelf life as the water activity increases from 0.10 to 0.41 (Table 21.5). Similar results were obtained by Anese et al. (2006). 21.3.3 Factors controlling the rate of physical collapse in coffee derivatives The occurrence of physical collapse of instant coffee and its derivatives is strictly related to its glass transition temperature, which is the result of its formulation. Coffee melanoidins are known to be relatively low molecular weight polymers thus showing a glass transition below room temperature (Anese et al., 2005). In order to increase glass transition, instant and soluble coffee is generally added with high molecular weight polysaccharides ensuring the free flowing of the powder. In addition, the presence of ingredients other than coffee, such as milk derivatives could greatly affect the caking rate. Anti-caking agents, such as carbonates, silicates and phosphates are extensively used in powdered drink due to their ability to rapidly absorb water excess or other plasticizers up to 2.5 times their weight yet remaining a free flowing powder (Jaya and Das, 2004). Since coffee collapse occurs when its glass transition temperature is exceeded during storage, temperature and relative humidity are critical. For instance, Anese et al. (2005) reported that soluble coffee stored at room temperature at ERH% lower than 35 is in a glassy state while over this critical value, the glass± rubber transition may allow matrix collapse to initiate. The latter is also favoured by the release of water upon crystallization during storage of sugar ingredients such as lactose and sucrose. 21.3.4 Factors controlling the rate of ester hydrolysis and non-enzymatic browning in coffee derivatives Ester hydrolysis and non-enzymatic browning development during storage tend to be particularly critical for coffee derivatives with high water content, such as

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coffee concentrates and drinks where they are responsible for the increase in acidity and the change in flavour profile. The rate of pH decrease is strongly affected by storage temperature. The temperature dependence is well described by the Arrhenius equation from ÿ30 to 60 ëC for coffee liquids with water activity within 0.85 and 0.99. The development of these chemical reactions is hardly controllable but can be masked by the addition of pH regulator agents such as sodium and potassium carbonate and bicarbonate (Perez-Martinez et al., 2008b). Similar to other foods presenting microbial risk, even in the case of coffee liquids, microbial spoilage is controlled by applying proper thermal or nonthermal pasteurization or sterilization treatments. The majority of the shelfstable brews present on the market are obtained by thermal sterilization or pasteurization. When pasteurization is not performed (e.g., coffee concentrates), antimicrobial substances and/or chilling are used to achieve adequate shelf life (Matsumiya et al., 2010).

21.4

Evaluating the shelf life of coffee

Despite the worldwide importance of coffee products, only limited and contradictory indications on their shelf life are available in the literature. There is even less information about the methodologies used for their shelf life assessment. Due to the poorness of literature data, the identification of a reliable shelf life for product belonging to the complex world of coffee must be performed by applying proper methodologies, specifically adapted to the product considered. However, a basic systematic approach for a cost-effective shelf life determination can be outlined. 21.4.1 Identification of the acceptability limit Before proceeding to the shelf life testing of coffee products, based on laboratory trials, it is necessary to clarify which is the acceptability limit to adopt in the shelf life study. The acceptability limit can be defined as the quality level discriminating products which are still acceptable for consumption from those no longer acceptable (Manzocco et al., 2010). The acceptability limit is often chosen by company management on the basis of available experience of the product performance on the market or on the emulation of competitors. Despite being simple and inexpensive, such procedure is obviously fraught with the risk of critical overestimations or disadvantageous underestimation of the shelf life. This hazard is much more probable in the case of new foods, for which no previous experience is available. In general terms, the acceptability limit may be the result of the application of different criteria depending on product criticism and on the likelihood that a certain default will cause product unacceptability first (Table 21.6). The acceptability limit may be decided by regulations produced by food/beverage

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Table 21.6 Main criteria for definition of shelf life acceptability limits for coffee products Product life end

Acceptability limit nature

Legal requirements Compulsory default Label claims default Compulsory Excessive consumer rejection

Volunteer

Subject deciding the acceptability limit

Acceptability limit

Authority

Limit value indicated by current regulation Concentration of molecule voluntarily claimed by the producer Maximum risk of consumer rejection considered tolerable by the producer

Producer Producer

authorities. In this case, the limit has to be compulsory respected by the producer in order to market the product. Due to the absence of specific legal requirements for coffee products, this kind of acceptability limit is rarely relevant to this sector. Indeed, it could find an application in the case of chilled liquid coffee suffering microbial growth during storage. Compulsory shelf life limits can also derive from volunteer label claims. In fact, according to the regulation, producers must guarantee the conformity of the product to any claim reported on the label. For instance, the amount of a bioactive compound, claimed on the label of a coffee beverage to increase its functionality, could be regarded as a shelf life acceptability limit. The latter is thus the result of marketing considerations achieved by merging actual product functionality, product positioning on the market and consumer perception of the claim. Since most coffee products do not present safety risks or special claims, in the majority of cases the producers are free to choose their own acceptability limit according to internal policy and quality targets. This is obviously a question of risk management which undergoes an unavoidable level of subjectivity. To this regard, it has been observed that the hazard should not be focused on the properties of the product, rather on the attitude of the consumers to accept or reject it (Hough et al., 2006). This is particularly true for coffee products because the end of their shelf life is strictly determined by the changes in their overall sensory impact and thus in the relevant level of consumer satisfaction/ dissatisfaction. The latter can be evaluated by studying the evolution of the percentage of consumers rejecting the product upon development of unacceptable quality during storage. For instance, at a given storage time, the product is certainly still acceptable to some consumers, despite being rejected by others. The coffee producer can choose to be exposed to more or less risk of product rejection by selecting, as the acceptability limit, the proper percentage of consumers rejecting the product. In other words, the acceptability limit becomes the maximum percentage of consumers that the company can tolerate to dissatisfy at the end of product shelf life.

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Table 21.7 Percentage of consumer rejection and relevant proposed risk of product rejection (Manzocco et al., 2010 with permission) Acceptability limit (% consumer rejection)

Risk

0 10 25 50 75

Negligible Very low Low Medium High

It must be pointed out that, since coffee quality perception is strictly related to a number of local traditions and drinking habits, studies dealing with consumer±food interaction, whose purpose is to identify product acceptability limits, should be carried out in the country/market in which the product has to be sold. In fact, depending on the different consumer sensitivities to coffee quality in different geographical areas, the same acceptability limit, expressed as consumer percentage rejection, could correspond to different product quality levels. This is the case for the acceptability limits identified for ready-to-drink coffees in eastern and western countries. Table 21.7 shows the relation between acceptability limit and the proposed rejection risk level. In most shelf life studies a medium risk level (50% consumer rejection) is chosen as a reasonable acceptability limit but it has been suggested that lower percentages of consumer rejection could be much more reliable. According to Guerra et al. (2008), the final shelf life value can be affected from 20 to 100% by selecting different risk levels. 21.4.2 Identification of proper shelf life indicators When the acceptability limits are derived from legal requirement or label claim defaults, the indicators to be monitored during storage in order to assess coffee product shelf life are easily defined. They are instrumental indicators describing the evolution of the property (e.g. microbial count, concentration of bioactive molecule) whose limit is set by the regulation or the label claim. By contrast, when the coffee life end is caused by an excessive quality loss, as indicated by too high a rejection percentage of consumers, the study of consumer±product interactions represents the most suitable indicator accounting for coffee product quality and thus acceptability. However, it should be noted that the evaluation of consumer rejection as a function of storage time is a time-consuming and expensive process. It requires a large sample size, a large number of consumers as well as the application of appropriate statistical techniques. These conditions make such kinds of studies, despite being powerful, hard to conduct by company operators to routinely assess shelf life. In order to meet industrial needs, instrumental or sensory attributes, whose evolution is correlated to the coffee product rejection expressed by consumers,

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could be identified and routinely assessed to detect the end of coffee product shelf life (Garitta et al., 2004; Calligaris et al., 2007). In other words, the coffee producers, after the identification of the acceptability limit expressed as the maximum tolerated consumer rejection percentage, can define the corresponding internal quality standards, described by instrumental or sensory shelf life indicators. Such instrumental or sensory acceptability limits can be simply used in routine shelf life tests. To do this it is necessary to identify the relationship between consumer rejection and quality indices, either instrumental or sensorial. This approach can be applied to coffee products, by addressing the following issues: · how consumer rejection and analytical indicators evolve during coffee product storage · which analytical indicators best correlate with consumer rejection during storage · what value for these analytical indices causes the maximum tolerable risk of consumer rejection to be reached. Figure 21.1 summarizes a possible methodology to answer these questions. The first critical step implies the identification of analytical quality indices which are easily assessable and potentially correlated to coffee sensory perception and thus to its rejection expressed by consumers. In the case of coffee products, different indicators can be identified depending on coffee products (Table 21.8). Peroxide value, which is a simple and widely used index of oxidation development in several foods, has also been used to follow coffee product

Fig. 21.1 Methodology for the definition of analytical indicators accounting for consumer rejection (modified from Manzocco and Lagazio, 2009).

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Table 21.8 Main indicators of coffee products quality depletion potentially accounting for consumer rejection during storage (modified from Nicoli et al., 2009) Coffee product

Indicator

Roast whole and ground coffee Instant coffee

Peroxide value (Chafer et al., 1998) Head space volatiles (Amstalden and Leite, 2001; Buffo and Cardelli-Freire, 2004; Holscher and Steinhart, 1992)

Coffee concentrates and drinks

Sensory flavour (Perez-Martinez et al., 2008a; Cappuccio et al., 2001; Manzocco and Lagazio, 2009)

Instant coffee

Water activity and glass transition temperature (Anese et al., 2005) Moisture uptake (Alves and Bordin, 1998; Alves et al., 2000) Particle changes (Saragoni et al., 2007)

Coffee concentrates and drinks

pH (Manzocco and Nicoli, 2007) Titrable acidity (Yamanashi et al., 1992) Sensory sourness (Manzocco and Lagazio, 2009; Perez-Martinez et al., 2008a)

stability. However, peroxides are not sensory perceivable compounds and, due to the bell-shape of their evolution during storage, they are likely to be difficult to relate to consumer rejection. In this regard, it is noteworthy that peroxide value of roast and ground coffee shows a dramatic increase after four months of storage in air (Nicoli et al., 1993) while, according to Table 21.4, its shelf life is expected to be lower than 3 months. By contrast, headspace volatiles could represent typical indicators potentially correlated to coffee product acceptability. Among the volatiles, some specific indicators of coffee aroma freshness have been selected: (a) M/B aroma index as the ratio between methylfuran and 2butanone (Reymond et al., 1962); (b) flavour quality index based on five key odorants (hexanal, vinylpyrazine, pyrrol, furfurylmethylketone and pyridine) which shows an inverse linear relationship with the M/B index (Spadone and Liardon, 1989); and (c) M/M aroma index as the ratio of methanol to 2methylfuran (Vitzthum and Werkhoff, 1978). Steinhart and Holscher (1991) suggested that the loss of coffee aroma freshness is due to the loss of certain aroma volatiles (mainly methyl mercaptan) which can be used as an indicator of freshness. Additional indicators can be derived by sensory evaluation of coffee flavour by a trained panel. Indicators of structure modifications leading to agglomeration and caking of the coffee powder could be water activity (aw), moisture content and the glass transition temperature. The indicators of ester hydrolysis and non-enzymatic browning in coffee liquids may be H3O+ concentration, as assessed by a pH meter or by titration, as well as assessment of sourness by a trained panel. An example demonstrating the possibility to `translate' the acceptability limit identified as a percentage of consumer rejection into an instrumental or sensory

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Table 21.9 pH limit of coffee brews in correspondence with increasing risk of consumer rejection risk (modified from Nicoli et al., 2009). Test performed in the Italian market Risk Very low Low Medium High Very high

pH  95% confidence interval 5.22 5.19 5.14 5.12 5.08

    

0.03 0.03 0.02 0.02 0.04

acceptability limit was recently reported by Manzocco and Lagazio (2009). In particular, coffee beverages were assessed during storage for consumer rejection as well as for hydrogen ion concentration and intensity of sensory properties measured by a trained sensory panel. Hydrogen ion concentration and sourness evolution during storage correlated best with the percentage of consumers rejecting the product. Mathematical functions predicting the limit value of hydrogen ion concentration and sourness as a function of the risk of consumer rejection were defined. For instance, Table 21.9 shows the estimated pH values of coffee brews in correspondence with increasing risk of consumer rejection. Similarly, in a study addressed to assess the secondary shelf life of roast and ground coffee at 30 ëC, the acceptability limit accounting for medium consumer rejection risk corresponds to a 60% reduction of initial headspace volatile area (Anese et al., 2006). The advantages of the exploitation of shelf life indicators simply assessable by instrumental or sensory analysis are undoubted. Once the analytical limits have been assessed by correlating with consumer rejection risk, further time-consuming consumer tests can be skipped and the analytical indicator can be routinely applied to evaluate the shelf life of the coffee product in the industry quality control programmes. Unfortunately, to our knowledge, very little information about the relationships between the evolution of simple quality indicators and consumer rejection risk during storage of coffee products is available. 21.4.3 Shelf life testing under actual storage conditions Shelf life testing is performed to estimate the length of time needed to reach the acceptability limit and implies the continuous monitoring of the changes of the shelf life indicator during storage of coffee products under controlled environmental conditions. When there is no necessity to speed up shelf life testing, the latter can be carried out under conditions simulating as much as possible those actually experienced by the coffee product on the shelves. The basic requirement is that storage conditions (e.g. temperature, relative humidity, light) during shelf life testing are kept constant and equal to those of real product storage. Data relevant to the evolution during storage of the shelf life indicator (i.e.,

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acceptability, instrumental or sensory data) are then modelled to obtain proper parameters describing/predicting the quality depletion kinetics. The latter are necessary to compute the shelf life value once the acceptability limit is known. Different approaches can be followed depending on the nature of the shelf life indicator. When the latter is product rejection expressed by consumers, data are analysed using the statistic methodology of survival analysis (Gacula and Kubala, 1975; Gacula and Singh, 1984; Hough et al., 2003). By contrast, if an instrumental or sensory indicator (derived by regulation, claim based or identified by the producer) is available, its changes over storage time are generally submitted to modelling according to the fundamental kinetic principles. An example of the application of consumer rejection modelling for different coffee products stored at 20 ëC is reported in Fig. 21.2. In particular, consumers were asked to give a response of acceptability/rejection of coffee brew, coffee concentrate and instant coffee stored for increasing times. Failure time, which is the length of time until the occurrence of product rejection, is then estimated considering that data are censored observations (Hough et al., 2003). In fact, the exact failure time cannot be systematically observed for all samples. If a consumer perceives the coffee sample as `acceptable' at a certain time t, that sample would be rejected beyond that time, thus the data are right censored. If the consumer response at time t is `rejection', the consumer started rejecting that coffee before time t and the data are left censored. When the same group of consumers is used to assess samples stored for increasing time, intervalcensoring is very common because the consumer can find the product still acceptable at time t but reject it at a following time. Thus, the data are intervalcensored between the two observation times. The censored nature of

Fig. 21.2 Probability of consumer rejection of coffee brew (1.8% w/w), coffee concentrate (93.7% w/w) and instant coffee (100% w/w) as a function of storage time at 20 ëC.

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acceptability/rejection data implies that they should not be statistically analysed as observations of exact failure time since they have a share of missing information. For this reason, regression analysis should not be performed and parametric distributions should be fitted to the data to estimate the most likely values of the parameters by appropriate statistical techniques (Hough et al., 2003). Shelf life is then estimated from the parametric survival curve (Fig. 21.2) by identifying the time needed to reach the maximum tolerable risk of consumers rejecting the coffee product. In the example, a low risk level (25% consumer rejection) was chosen, leading to shelf life values of about 3 days, 2.5 months and more than one year for coffee brew, coffee concentrate and instant coffee, respectively. In this regard, a number of different software packages can be used to perform survival analysis and obtain shelf life data. However, it is worth noting that reliable shelf life information with tight confidence intervals requires a large sample size (Hough et al., 2006; Guillet and Rodrigue, 2010). In the case of shelf life assessment using an instrumental or sensory indicator, data describing the changes of the coffee quality under conditions simulating actual storage are submitted to modelling according to the fundamental general rate law integrated to obtain the equations of the pseudo zero, first, second or n order. Z t Z I dI ˆ k dt 21:2 n I0 I 0 where k is the rate constant and n the reaction order. By solving the integrated forms of Eq. 21.2 as a function of time, shelf life at the actual storage conditions can be calculated: Z C dI In 0 T ˆ cost 21:3 SL ˆ C k where I0 is the value of food quality indicator just after production, I is the quality indicator value corresponding to the acceptability limit. Figure 21.3 shows an example of the application of the classic kinetic approach to evaluate the shelf life of a coffee concentrate having 15% soluble solids stored at different temperatures. In this case, consumer rejection risk correlated well with hydrogen ion concentration and hence pH (Manzocco and Lagazio, 2009). Based on this, the changes in this instrumental indicator were assessed during storage for each product. pH data were then transformed into hydrogen ion concentration values, which were plotted as a function of storage time. Data were analysed by linear regression according to the zero-order reaction kinetic equation: [H3 O‡ ]t ÿ [H3 O‡ ]0 ˆ kt

21:4

where [H3O+]t is the hydrogen ion concentration at time t, [H3O+]0 is the hydrogen ion concentration of the freshly prepared coffee product, k is the apparent reaction rate and t is the storage time.

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Fig. 21.3 Hydrogen ion concentration of a coffee brew having 15% (w/w) solid concentration as a function of storage time at 0 (n), 10 (l) and 20 (s) ëC. Figure also shows hydrogen ion concentration in correspondence of the lower confidence interval of 50% consumer rejection and relevant shelf life (elaborated from Manzocco and Nicoli, 2007).

Given an acceptability limit of pH equal to 5.16 (6:95  10ÿ6 M hydrogen ion), corresponding to a medium consumer rejection risk (Table 21.7), the shelf life value at each storage temperature can be calculated as follows: SL ˆ

[H3 O‡ ]lim ÿ [H3 O‡ ]0 k

21:5

where [H3O+]lim is the hydrogen ion concentration limit (6:95  10ÿ6 M). A similar approach was also used to evaluate secondary shelf life of ground roasted coffee (Anese et al., 2006). It should be noted that secondary shelf life represents the length of time after opening of the package during which coffee products maintain acceptable quality (Cappuccio et al., 2001). Figure 21.4 shows the evolution of total volatile peak area of coffee stored for increasing time after package opening. Data were analysed by linear regression according to the first-order reaction kinetic equation: ln Vt ˆ kt ‡ ln V0

21:6

where Vt is total peak area at time t, V0 is total peak area of the just opened coffee, k is the apparent reaction rate and t is the storage time. Considering an acceptability limit of total peak area (Vlim) equal to 866736 mV s, corresponding to a medium consumer rejection risk (Anese et al., 2006), the shelf life value can be calculated as follows: ln Vlim ÿ ln V0 21:7 SL ˆ k

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Fig. 21.4 Total volatile peak area of ground roasted coffee as a function of storage time. Figure also shows total volatile peak area in correspondence of 50% consumer rejection and relevant shelf life (elaborated from Anese et al., 2006).

21.4.4 Shelf life testing under accelerated storage conditions Shelf life testing under actual storage conditions is economically feasible only when coffee product quality decays in a reasonably short time. This generally occurs in the case of coffee derivatives with high water content such as coffee liquids or when assessing secondary shelf life of coffee products. Unfortunately, this methodology does not suit industrial needs when dealing with coffee products having a medium to long shelf life, such as roasted whole and ground coffee packed under modified atmosphere. For this reason, it is convenient to accelerate shelf life experiments by testing coffee products under environmental conditions that speed up food quality depletion and then extrapolating the results to milder conditions usually experienced by the product (Mizrahi, 2000). Accelerated shelf life tests (ASLT) have been proven to be effective when both consumer rejection and instrumental shelf life indicators are used. The basic premises for the application of ASLT are: · the quality decay rate varies only as a function of the accelerating factor, while other environmental and compositional variables are kept constant · an accurate kinetic/descriptive model of the quality decay rate is available · the relationship between the accelerating factor and the quality decay rate is known (Manzocco et al., 2010). In the case of coffee products, temperature seems to be the accelerating factor best meeting these requirements. This is due not only to the fact that temperature

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is one of the most critical extrinsic factors controlling the kinetics of coffee product quality depletion (Table 21.3), but also to the availability of a theoretical basis for the development of a mathematical description of the temperature sensitivity of chemical reaction rates. The Arrhenius equation can be exploited to estimate, by regression analysis, apparent activation energy and frequency factor of the changes in the quality indicator. These parameters are used to estimate the apparent reaction rate at any temperature in the experimental range tested. Such values can be finally integrated to predict the shelf life of the product under actual storage conditions, given the acceptability limit. Table 21.10 reports some examples from the literature relevant to the application of the Arrhenius equation to describe the temperature dependence of coffee product quality depletion. As can be observed, the Ea values reported in the literature for different combinations of shelf life indicators and coffee products vary greatly. This can be attributed to the differences in compositional and environmental factors taken into account in these studies. The temperature dependence of the chemical stability of instant coffee, coffee paste and coffee concentrate stored in conventional atmosphere was well described by the Arrhenius equation with Ea values higher than 50 kJ/mol (Manzocco and Nicoli, 2007). It is noteworthy that the Arrhenius model correctly predicts the rate of hydrogen ion concentration changes in different temperature ranges depending on the product considered. For example, in the case of instant coffee, the Arrhenius equation result is applicable only above 30 ëC. Between 20 and 0 ëC, a very low value was detected causing a deviation Table 21.10 Examples of the application of the Arrhenius equation to describe the temperature dependence of shelf life indicators of coffee products. Estimated values of Ea and relevant reference are also reported Shelf life indicator

Product

Temperature range (ëC)

Ea Reference (kJ/mol)

Hydrogen ion concentration

Instant coffee

30±60

89.5

Coffee paste (93.7% w/w) Coffee concentrate (78% w/w)

0±60

86.6

ÿ30±60

59.4

Manzocco and Nicoli (2007) Manzocco and Nicoli (2007) Manzocco and Nicoli (2007)

Head space volatiles

Roasted coffee packed in air

4±40

28.1

Nicoli et al. (1993)

Consumer rejection

Roast and ground coffee packed under modified atmosphere Roast and ground coffee packed under modified atmosphere in pods

4±35

13.0

Cardelli and Labuza (2001)

4±40

<1.0

Nicoli et al. (2009)

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from linearity in the Arrhenius plot. This means that the system was particularly stable from a chemical viewpoint in this temperature range. It is likely that, although the system is not vitreous at room temperature, it exerts a peculiar stability as a consequence of its low aw. In other words, water content would be enough to make the system rubber but not to allow solute reactivity (Manzocco and Nicoli, 2007). In these conditions the use of the Arrhenius equation to predict shelf life is precluded because it leads to a dramatic overestimation. In such cases, the Arrhenius model may still be useful, but requires some modification or rescaling of model variables (Calligaris et al., 2004b, 2007, 2008; Manzocco et al., 2006). It should be remembered that deviations from the Arrhenius equation are often detected when temperature change causes the occurrence of chemical and physico-chemical events modifying the characteristics of the system (Waterman and Adami, 2005; Manzocco et al., 2010). The major reasons for non-linearity in the Arrhenius plot are phase transitions, pH shifts, solubility changes, uncontrolled relative humidity, complex reaction mechanisms, and heat capacity changes of the activated complex. For these reasons, the choice of the working conditions to be adopted in the ASLT should be carefully defined taking into account the characteristics of the product. Moving to the temperature dependence of quality depletion of roasted coffee, it can be observed that the magnitude of Ea is generally quite low, independently of the nature of the shelf life indicator adopted in the study (Table 21.10). This result emphasizes that the shelf life of roast and ground coffee has little temperature sensitivity and thus, the basic working assumption of the ASLT that temperature affects the reaction rate in reasonable time falls down. Temperature could actually speed up quality depletion but not enough to allow the observation of quality decay in short times. In this regard, it has been reported that roast and ground coffee having less than 3% oxygen concentration in the head space presented shelf life values at 4, 22 and 35 ëC much higher than 30 weeks (Cardelli and Labuza, 2001). The situation becomes worse when considering coffee powder packed in pods under modified atmosphere. Table 21.11 shows the zero-order rate of decrease of acetylfuran, taken as a typical indicator of flavour changes, in coffee pods stored under different temperature and head space oxygen conditions. Table 21.11 Rate of acetylfuran decrease, taken as a typical indicator of flavour changes, in coffee pods stored for up to 2 months under different temperature and head space oxygen conditions (elaborated from Nicoli et al., 2009) Temperature (ëC) 20 45 20

Head space oxygen concentration (%)

k (% 2-acetylfuran/months)

0.5 0.5 21

n.d. n.d. 15.67 (R2 ˆ 0:95)

n.d. not detectable

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In a time span of 2 months, no changes in the head space presence of this volatile indicator were observed at both 20 and 45 ëC in samples packed under 0.5% oxygen concentration. By contrast, increasing oxygen concentration, the rate of acetylfuran loss significantly increases. Since the temperature increase does not allow reducing the shelf life testing times, oxygen concentration in the headspace could be a better accelerating factor for roast and ground coffee powders. However, the basic requirement for the successful exploitation of oxygen concentration as the accelerating factor is the availability of a mathematical model correctly predicting the oxygen sensitivity of the rate of the reactions leading to the end of shelf life.

21.5

Future trends

Shelf life assessment of coffee derivatives is a complex task due to the large number of deteriorative mechanisms that could affect their quality decay. For this reason, shelf life testing must be carefully designed depending on the product characteristics to obtain a cost-effective experimental design. When the quality decay occurs in rather short times, as in the case of chilled coffee liquids, the direct measure of their shelf life under actual storage conditions can be easily applied. In contrast, for shelf-stable products, which are the majority of coffee derivatives, there is the need of reliable shelf life tests to be carried out in times as short as possible. To achieve this goal, more research has to be done in order to: · develop criteria and protocols to support the choice of acceptability limits that account for consumer response; · improve the understanding of the relation between coffee quality decay and consumer rejection; · identify potential accelerating factors other than temperature and develop proper shelf life predictive models. The availability of this information will allow producers to integrate the shelf life decision process within the quality management system, thus handling shelf life labelling by a rigorous, systematic and well designed assessment methodology.

21.6

Sources of further information and advice

and VITZTHUM OG (2001), Coffee: Recent Developments, Oxford: Blackwell Science Ltd. VIANI R and ILLY A (2005), Espresso Coffee: the Science of Quality, 2nd edn, San Diego, CA: Elsevier Academic Press. CLARKE RJ

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Beverages and Antioxidant Applications, Cambridge: Woodhead Publishing Ltd, in press. MATSUMIYA K, TAKAHASHI W, INOUE T and MATSUMURA Y (2010), `Effects of bacteriostatic emulsifiers on stability of milk-based emulsions', J Food Eng, 96, 2, 185±191. MIZRAHI S (2000), `Accelerated shelf-life tests'. In Kilcast D and Subramaniam P, The Stability and Shelf-life of Foods, Cambridge: Woodhead Publishing Ltd, 107±208. MUELLER C and HOFMANN T (2007), `Quantitative studies on the formation of phenol/2furfurylthiol conjugates in coffee beverages: toward the understanding of the molecular mechanisms of coffee aroma staling', J Agric Food Chem, 55, 4095± 4102. NICOLI MC and SAVONITTO O (2005), `Physical and chemical changes of roasted coffee during storage'. In Viani R, Illy A, Espresso Coffee: the Science of Quality, 2nd edn, San Diego, CA: Elsevier Academic Press, 230±245. NICOLI MC, INNOCENTE N, PITTIA P and LERICI CR (1993), `Staling of roasted coffee: volatile release and oxidation reactions during storage'. Proceedings of the 15th International Scientific Colloquium on Coffee, Montpellier, France, 557±566. NICOLI MC, ANESE M, MANZOCCO L and LERICI CR (1997), `Antioxidant properties of coffee brews in relation to the roasting degree', LWT ± Food Sci Technol, 30, 292±297. NICOLI MC, CALLIGARIS S and MANZOCCO L (2009), `Shelf life testing of coffee and related products: uncertainties, pitfalls and perspectives', Food Eng Rev, 1, 2, 159±168. NICOLI MC, MANZOCCO L and CALLIGARIS S (2010), `Packaging and the shelf life of coffee'. In Robertson G, Food Packaging and Shelf-life: a Practical Guide, Boca Raton, FL: CRC Press/Taylor and Francis Group, 199±214. ORTOLA MD, GUTIERREZ CL, CHILART A and FITO P (1998), `Kinetic study of lipid oxidation in roasted coffee', Food Sci Technol Inter, 4, 67±73. PEREZ-MARTINEZ M, SOPELANA P, PAZ DE PENA M and CID C (2008a), `Application of multivariate analysis to the effects of additives on chemical and sensory quality of stored coffee brews', J Agric Food Chem, 56, 11845±11853. PEREZ-MARTINEZ M, SOPELANA P, PAZ DE PENA M and CID C (2008b), `Changes in volatile compounds and overall aroma profile during storage of coffee brews at 4 and 25 ëC', J Agric Food Chem, 56, 3145±3154. PETRACCO M (2001), `Technology IV: Beverage preparation: Brewing trends for the new millennium'. In Clarke RJ and Vitzthum OG, Coffee: Recent Developments, Oxford: Blackwell Science Ltd, 140±164. PETRACCO M (2005a), `Grinding'. In Viani R and Illy A, Espresso Coffee: the Science of Quality, 2nd edn, San Diego, CA: Elsevier Academic Press, 215±229. PETRACCO M (2005b), `Percolation'. In Viani R and Illy A, Espresso Coffee: the Science of Quality, 2nd edn, San Diego, CA: Elsevier Academic Press, 259±287. PICTET G (1987), `Home and catering brewing coffee'. In Clarke RJ and Macrae R, Coffee, Vol. 2, New York: Elsevier Science Publishing, 221±252. REYMOND D, CHAVAN F and EGLI RH (1962), `Effect of storage conditions on the sensory quality of ground Arabica coffee', Food Sci Technol, 4, 595±598. SARAGONI P, AGUILERA JM and BOUCHON P (2007), `Changes in particle of coffee powder and extension to caking', Food Chem, 104, 122±126. SPADONE JC and LIARDON R (1989), `Analytical study of the evolution of coffee aroma compounds during storage'. Proceedings of the 13th International Scientific Colloquium on Coffee, Paipa, 145±158. SPEER K and KOLLING-SPEER I (2001), `Lipids'. In Clarke RJ, Vitzthum OG, Coffee: Recent Developments, Oxford: Blackwell Science Ltd, 33±49.

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and HOLSCHER W (1991), `Storage related changes of low-boiling volatiles in whole beans'. Proceedings of the 14th International Scientific Colloquium on Coffee, San Francisco, 156±174. VERMEIREN L, DEVLIEGHERE F, VAN BEEST M, DE KRUIF N and DEBEVERE J (1999), `Developments in the active packaging of foods', Trends Food Sci Technol, 10, 77±86. VITZTHUM OG and WERKHOFF P (1978), `Aroma analysis of coffee, tea and cocoa by headspace technique'. In Charalambous G, Analysis of Foods and Beverages: Headspace Techniques, New York: Academic Press. WATERMAN KC and ADAMI RC (2005), `Accelerating testing: prediction of chemical stability of pharmaceuticals', Int J Pharm, 293, 101±125. YAMANASHI H, MIZUNO C and YOSHIDA K (1992), `Relationship between changes of fresh roasted flavour and tritable acidity of stored ground coffee', Japan Soc Food Sci Technol 39, 7, 615±619. STEINHARDT H

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22 The stability and shelf life of fruit and vegetables M. J. Sousa Gallagher and P. V. Mahajan, University College Cork, Ireland

Abstract: Fruit and vegetables (F&V) are living tissues and highly perishable products needing optimal post-harvest technologies in order to maintain their storage stability and extend shelf life. Growing consumer demand for convenience in food preparation and consumption, including product form, packaging, quality preservation, and year-round availability has been driving the F&V marketing system to one with an increased focus on value added and cost minimization by streamlining of distribution. Quality and stability of F&V depend upon the cultivar, pre-harvest practices, climacteric conditions, maturity at harvest, harvesting methodology and postharvest conditions, making shelf life prediction a difficult task when compared with other food products. Post-harvest deterioration can be controlled by reducing the storage temperature and respiration rate by modification of the gas atmosphere surrounding the product which would improve stability and extend shelf life of fresh produce. Controlled atmosphere (CA) and modified atmosphere packaging (MAP) technologies have evolved in order to provide this benefit to F&V during storage. Key words: fruits and vegetables, stability, shelf life, quality, temperature, respiration, controlled atmosphere, modified atmosphere packaging.

22.1

Introduction

Fruit and vegetables (F&V) are living tissues and highly perishable products needing optimal post-harvest technologies in order to maintain their storage stability and extend shelf life. The entire fresh F&V marketing system is rapidly evolving to one with an increased focus on value addition and cost minimization

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by streamlining of distribution. This trend is driven by growing consumer demand for convenience in food preparation and consumption, including product form, packaging, quality preservation, and year-round availability all of which are critical elements in the competitive strategies of retailers (Mupondwa, 2009). F&V quality and range on offer have a major influence on where customers shop. In order to meet consumer demand for greater convenience, new and more varied products have been introduced to the market. Fresh-cut F&V (minimally processed) and packaged salads are occupying more shelf space as they continue to gain acceptance by customers. The latest trend is to combine a range of fruits and/or vegetables into meal packs which are ready for consumption, with varying weight portions to meet the needs of families and individual consumers. Restaurants, fast-food outlets and institutional food-service operators are seeking to reduce labour costs by buying prepared, trimmed and cut produce that is ready for use. Fresh-cut F&V offers a number of advantages over bulk produce, including: cost control, waste reduction, variety and selection, consistent quality, and less in-store labour. Shipping costs are also reduced because most of the waste is eliminated at the processor/packer level. Post-harvest deterioration can be controlled by reducing the storage temperature. Another factor that can be controlled to minimize the quality deterioration in horticultural products is the respiration rate. This can be achieved by modification of the gas atmosphere surrounding the product. Two types of technologies have evolved in order to provide this benefit: controlled atmosphere (CA) storage and modified atmosphere packaging (MAP). CA storage is based on artificially creating and maintaining low oxygen (O2) and high carbon dioxide (CO2) concentrations during storage whereas in MAP, the atmosphere is modified naturally by the interplay of the respiration rate and package gas permeability. MAP represents a post-harvest innovation that enhances product quality, and which has a significant commercial impact, given the commercial value of the growing fresh-cut F&V market segment.

22.2

Stability and shelf life of fruit and vegetables

F&V shelf life is best defined as the period within which the product retains acceptable quality for sale to the consumer. Different quality criteria are important depending on the specific type of commodity and whether it is to be sold fresh as a whole or fresh-cut (minimally processed). For the F&V market, specific minimum quality standards exist in many countries and there is a trend towards international standardization of quality grades. The European Commission was one of the first organizations to develop international standards for fresh fruits and vegetables (MAFF, 1996a,b,c) and many of these standards have been adopted by the Organization for Economic Co-operation and Development (OECD). Usually, standards required for multiple retail outlets are considerably more stringent than these minimum standards and will be defined for the supplier by the retailer.

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Quality of fresh and fresh-cut F&V is a combination of attributes, properties or characteristics that determine the value for the consumer. Quality parameters include appearance, texture, flavour/aroma and nutritional value (Aked, 2000; Kader, 2002b). The relative importance of each quality parameter depends upon the commodity and whether it is eaten fresh or minimally processed. Consumers judge quality of fresh and fresh-cut F&V on the basis of appearance and freshness (`best before' date) at time of purchase. However, subsequent purchases depend upon the consumer's satisfaction in terms of textural and flavour quality when eating the product. Quality of whole F&V depends upon the cultivar, pre-harvest practices, climacteric conditions, maturity at harvest, harvesting methodology and postharvest conditions, making shelf life prediction a difficult task when compared with other food products. Handling procedures, conditions and time also impact on the quality of F&V, and consequently the quality of fresh-cut products. Additional factors that influence the quality of fresh-cut F&V include method of preparation (sharpness of cutting tools, size and surface area of the cut pieces, washing/treatment, and removal of surface moisture) and subsequent handling conditions (cooling rate, sanitation conditions, packaging, maintaining optimum conditions of temperature and relative humidity during distribution). F&V are not considered to be high-risk products with respect to food safety as they normally become completely undesirable for consumption long before any hazardous microorganisms or toxins might develop. There is, however, evidence that packing fresh vegetables in MAP may extend shelf life, while still allowing the growth of pathogenic bacteria, in particular Listeria spp. and Escherichia coli O157 (Phillips, 1996). In a study, labelled `multi-ingredient foods', 14 outbreaks over a 10-year period (1990±2000) were attributed to bagged salads as well as salad bars (Scruton, 2000). In response to consumer concerns, major retailers and food service restaurants developed programmes requiring their growers/suppliers to have independent third-party inspections to certify the good agricultural practices (GAPs) of their growing operations and good manufacturing practices (GMPs) of the harvest and handling of their F&V (Hodge, 1998; Beers, 1999). Processors of fresh and fresh-cut F&V have long understood their responsibility to provide a microbiologically safe, high-quality product to consumers. The National Association of Fresh Produce Processors released Recommended Sanitary Guidelines for the Produce Processing Industry (Hurst, 1992), setting GMPs and standardized processing procedures to ensure consistent quality and to improve processors' credibility in ensuring a safe product delivered to the consumer. 22.2.1 Loss of stability and quality deterioration Many factors can lead to loss of stability and quality in F&V, hence the common usage of the term `perishables'. Some factors are the consequences of fresh and fresh-cut F&V being living tissues showing physiological response to the harvesting or to minimal processing procedures as well as to post-processing

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handling and treatments and ultimately to the packaging environment in which they are enclosed (Toivonen and DeEll, 2002). Once separated from the mother plant, F&V are deprived of their source of water, nutrients and anti-senescence hormones, and normal factors like respiration and transpiration ultimately lead to senescence and weight loss of the product. The growth of pathogens or physical damage will cause a decrease in quality of F&V shown through their appearance which also stimulates senescence. Intrinsic physiology, quality and microbial growth on the F&V will have an influence on the response to minimal processing and packaging, and thus need to be considered. Several studies have indicated that the protection from mechanical damage and microbial infections keeps the F&V in good condition; however, it does not increase shelf life considerably (Mahajan, 2002). This is because of the metabolic processes in F&V, which continue even after harvest. Respiration is considered to be the major catabolic process, which leads the F&V to natural ripening, senescence and subsequent deterioration. Respiration F&V are living commodities and their rate of respiration is of key importance to shelf life. During the respiration process, O2 is consumed and CO2 is produced. Respiration is the oxidative breakdown of a substrate into simpler molecules, namely CO2 and H2O, with a concurrent production of energy (heat) for the maintenance of the normal structure and functions of the produce and by its nature, respiration leads to nutrient losses. Consequently, the rate of nutrient losses depends on respiration rate which is inversely proportional to the shelf life of F&V (Kader, 1987). There are distinct patterns of ripening for fruits called climacteric and nonclimacteric (Fig. 22.1) (Mahajan and Goswami, 1999). In the climacteric pattern (Fig. 22.1a), the respiration rate shows a decreasing trend to the lowest value, called the pre-climacteric minimum, followed by a sharp rise in respiration rate to the climacteric peak. This sudden upsurge is called respiratory climacteric and such fruits are called climacteric fruits. Therefore, respiratory climacteric is defined as a period in the ontogeny of fruit during which a series of biochemical changes are initiated by the autocatalytic production of ethylene, making the change from growth to senescence and involving an increase in respiration rate leading to ripening of the fruit. Non-climacteric fruits (Fig. 22.1b) show neither a rise in respiration rate nor an associated production of ethylene during the ripening process. In these fruits, ripening is normally completed on the parent plant. Table 22.1 gives a list of common climacteric and non-climacteric fruits (Kader, 2002a). Climacteric fruits (e.g., tomatoes, mangoes, bananas, avocados) can be harvested unripe and ripened artificially. During ripening, the respiration increases rapidly, and without control of temperature, the fruit will rapidly over-ripen and senesce, leading to breakdown of tissues, production of volatiles characteristic of the over-ripening fruit and water loss. Furthermore, the warmth and moisture, can lead to bacterial and fungal infections (Aked, 2000).

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Typical ripening patterns for (a) climacteric (b) non-climacteric fruits (from Mahajan and Goswami, 1999).

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Table 22.1 Fruits classified according to respiratory behaviour during ripening (from Kader, 2002a) Climacteric fruits

Non-climacteric fruits

Apple Apricot Avocado Banana Berries Fig Guava Kiwifruit Papaya Peach Pear Plum Sapota Melons

Blackberry Cherry Cranberry Grape Lemon Lime Litchi Orange Pineapple Pomegranate Raspberry Watermelon

In tissues like leafy crops (e.g., lettuce, spinach or broccoli), excessive respiration will eventually lead to metabolic collapse. Cell membranes will break down, allowing the contents to leak out, leading to bacteria to grow in these tissues giving rise to off-odour and yellowing due to breakdown of chlorophyll in the chloroplasts. A wide range of fresh-cut F&V shows significant increases in respiration when compared to whole F&V, and generally, this effect is seen when they are stored at higher temperatures. Therefore fresh-cut F&V generally have a shorter shelf life than the whole product. Another aspect of fresh-cut F&V is that of susceptibility to anaerobic metabolism, if respiration rate and film permeability are not taken into consideration in the design of the packaging. Ethylene The climacteric and non-climacteric fruits are distinguishable by their response to ethylene treatment. Ethylene is a plant hormone that plays a key role in the ripening and senescence of fruit and vegetables (Reid, 1992). In immature climacteric fruits, ethylene treatment, as low as 0.1 to 10 ppm, hastens the onset of the climacteric response and the associated ripening changes without appreciably altering the pattern or the magnitude of respiratory change. However, in non-climacteric fruits, it leads to an increase in ethylene production and respiration with no correlation with the inception of ripening. In climacteric fruits, ethylene application is effective only during the pre-climacteric stage, whereas in non-climacteric fruits, stimulation in the rate of respiration has been observed at any stage. In climacteric fruits, if sufficient concentration of ethylene over a long period is applied to cause respiratory rise, no return to the pre-climacteric stage will result on removal of ethylene. However, in nonclimacteric fruits removal of ethylene at any time will result in a return of the

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rate of gaseous exchange to the level of untreated control. Once climacteric fruits start to ripen, there is very little that can be done except to market them for immediate consumption. Hence fruits should be stored before the onset of climacteric rise. All plant cells produce low levels of ethylene; however, anything that causes stress to the plant tissues will stimulate synthesis. Stressors may include excessive water loss, physical damage or pathogenic attack. Wounding of plant tissues induces ethylene production with a response time from a few minutes to an hour after wounding, with maximal rates being produced between 6 and 12 hours (Abeles et al., 1992). Storage temperature also has an effect on woundinduced ethylene production, and low temperatures (0±2.5 ëC) reduce ethylene production. The potential effects of wound ethylene are dependent on the type and physiology of the F&V tissue. Moisture loss Harvested F&V rapidly lose water from their surfaces in a process known as transpiration. Transpiration is a major component of weight loss in F&V and their texture is adversely affected by excessive water loss, rendering the product unmarketable. Water loss in F&V is determined by many factors, probably the most important being the resistance of the outer cuticle (periderm) to transpiration. Plant organs are covered with specialized tissues, which serve to protect the plant from insect and pathogen attack, physical injury and excessive water loss. Produce varies in the percentage of water that can be lost before quality is markedly reduced. A 5±10% weight loss will cause significant wilting, shrivelling, poor texture and poor taste (Mahajan et al., 2008). However, peeling and cutting result in reduction or elimination of the resistance by these barriers to transpiration. The speed of post-harvest water loss is dependent primarily on the external vapour pressure deficit; however, other factors will influence the situation. Moisture loss occurs rapidly in a warm, dry environment especially among injured products, and it is affected by commodity characteristics such as surface area to volume ratio, presence of waxy substances in the skin, tenderness of the skin, and presence of protrusions on the skin surface. Two aspects are important to water loss: reduction of tissue bulk (i.e., increase in surface area to volume ratio), and removal of protective periderm tissues. Both mechanisms cause increase in water loss, as demonstrated by the fact that slicing of kiwifruit results in increased rates of water loss, and subsequent peel removal from the slices results in further increase in weight loss (Toivonen and DeEll, 2002). The peeling method of carrots influences the water loss of subsequently processed fresh slices. Coarse abrasion peeling results in three times greater weight loss of packaged slices as compared to slices made from hand-peeled carrots (BarryRyan and O'Beirne, 2000). The slicing process can also influence the water loss, with machine-sliced products losing water 30% faster than manually razorsliced carrots (Barry-Ryan and O'Beirne, 1998).

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22.3

Food and beverage stability and shelf life

Extending the shelf life of fruit and vegetables

Basic biological processes such as respiration, transpiration and biochemical transformations continue after harvest. However, these processes can be altered by manipulating different factors such as temperature, relative humidity (RH) and the concentration of biologically active gases such as water vapour, O2, CO2 and ethylene in fresh F&V. Beyond certain limits, especially gas atmosphere composition, and depending on stage of development of the commodity, physiological disorders may develop affecting negatively appearance, flavour and nutritional value. 22.3.1 Temperature Refrigeration dominates as the most fundamental of all post-harvest technologies. F&V should be stored above the critical temperatures at which they show symptoms of chilling injury. Many F&V benefit from prompt cooling immediately after harvest. Pre-cooling to remove field heat as quickly as possible after harvest is essential for slowing down the rate of deterioration of highly perishable products. Low temperatures slow down metabolic processes such as respiration and transpiration and delay the development of post-harvest diseases by inhibiting host ripening, by prolonging disease resistance associated with immaturity, and by directly inhibiting the pathogen at temperatures unfavourable to its development (Liu and Ma, 1983). The storage/shelf life of fresh produce is considerably extended if respiration can be slowed down using refrigeration. Lists of recommended storage conditions for a wide range of F&V are given in a number of publications (Kader, 1992; Thompson, 1996). Following pre-cooling, it is important that the cold-chain is maintained throughout the life of the product. This means that refrigeration should take place throughout transportation (Eksteen, 1998) and storage and preferably be maintained during retailing and in the home of the consumer. Typically, road and sea containers are refrigerated, as are the storage units at exporters, importers and retail distribution centres. Airfreight is rarely cooled and relies on adequate pre-cooling, good pack insulation and the speed of transport to maintain adequate quality (Frith, 1991). The cool chain tends to be broken in retail stores where F&V are rarely displayed in chilled sections, except for the fresh-cut F&V. The method chosen for cooling is largely determined by the type of product in question and the cost-to-benefit ratio (Mitchell, 1992; Kasmire and Thompson, 1992). These methods include room and forced air cooling, hydrocooling, and icing and vacuum cooling (Toivonen and DeEll, 2002). Choice of the pre-cooling method is dependent on the cooling needs and suitability of a commodity, type of packaging material used for the product, type of market and marketing system, and economic and other considerations.

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22.3.2 Oxygen and carbon dioxide Oxygen is closely tied to the rate of respiration of harvested F&V. Lowering of the O2 concentration greatly reduces the respiration rate. As the O2 concentration decreases, respiration rate decreases until the O2 concentration reaches the extinction point, responsible for the triggering of the transition point between aerobic and anaerobic respiration. Below the extinction point, anaerobic respiration starts accumulating acids, aldehydes, ketones and alcohols within the tissues, leading to loss of tissue integrity and off-flavours. Carbon dioxide generally enhances the retardation effect of low O2 concentrations. Commonly used atmospheres of about 2±4% O2 and 5±7% CO2 suppress respiration and delay ripening of F&V. Optimum ranges of O2 and CO2 levels can result in several advantages to the F&V, but unfavourable atmospheres can induce physiological disorders and enhance susceptibility to decay. Elevated CO2 induced stresses are additive and sometimes synergistic with stresses caused by low O2, physical or chemical injuries, and exposure to temperatures, RH, and/or ethylene concentrations outside the optimum range, and can be influenced by type of F&V, cultivar, stage of development and storage duration (Yahia, 2009). 22.3.3 Humidity Water is lost as water vapour from the internal air spaces within the F&V (intercellular spaces) to the surrounding atmosphere. This water loss occurs whenever there is a lower water vapour concentration outside than inside the F&V. It can be minimized by minimizing the driving force between water vapour pressure at the evaporating surface on the product and ambient water vapour pressure. The water vapour pressure is affected by the temperature of both the F&V and air, and the RH of the storage air. Good temperature and RH management is required to minimize the water loss from the stored F&V. Too much water vapour can encourage the development of moulds; however, not enough just promotes desiccation of F&V. The recommended RH for storing or shipping most F&V is in the range of 85±95% or slightly higher. 22.3.4 Ethylene It is well recognized that ethylene removal from storage rooms may beneficially affect storage life of climacteric and non-climacteric F&V (Knee et al., 1985). Wills et al. (1999) showed that the storage life of many F&V increases linearly with the logarithmic decrease in ethylene concentrations from 10 to < 0.005 l Lÿ1. The challenge of ethylene removal lies in the fact that even at very low concentration (< 0.1 ppm), it may induce ripening or cause physiological disorders in some horticultural products. 1-Methylcyclopropene (MCP) is an inhibitor of ethylene action and effectively delays ripening of fruits, providing many benefits to the fruit sector during storage and transportation. Both US and Canadian apple packing houses

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reported the use of MCP by applying it to harvested fruits in refrigerated and in CA storage rooms; other uses reported include applications in shipping containers, enclosed truck trailers and greenhouses (Mupondwa, 2009). Retailers of fresh-cut F&V use MCP in refrigerated or CA storage facilities. The storage environment will play a highly significant role in determining the rate of quality changes. Physiological processes leading to tissue senescence and deterioration can be minimized or controlled by an integrated approach involving proper cultivar selection, pre-harvest management, pre- and post-processing treatments, and appropriate packaging that provides optimal atmospheres.

22.4 Controlled and modified atmosphere packaging for longer shelf life The greatest utility and value in producing fresh perishable commodities come from the ability to extend their supply over and beyond the harvest season. There are two types of technologies that have evolved in order to provide this benefit: controlled atmosphere (CA) storage and modified atmosphere packaging (MAP). CA generally indicates more precise monitoring and control of concentrations, whereas in MAP the gas composition in the package would be established following equilibrium between product respiration rate and packaging permeability. 22.4.1 Controlled atmosphere storage Controlled atmosphere (CA) innovation lies at the heart of developments in the horticultural sector, and it is principally adopted for fresh F&V. CA has its most beneficial effects on climacteric F&V at the pre-climacteric stage by prolonging this stage. The effects are less marked in climacteric F&V at its ripening stage and in non-climacteric fruits at any stage. Climacteric fruits such as apples and pears are by far the leading crops for which CA technology has been adopted (Yahia, 2006), and to a lesser extent to cabbages, sweet onions, kiwifruit, avocados, persimmons and pomegranates (Kader, 2005). The major advantages of CA storage are: · substantially reduces the respiration rate of F&V (~50% of that in air at the same temperature) by precisely adjusting the storage atmosphere and maintaining it throughout the storage and distribution of the F&V · decreases not only production of ethylene, but also the rate of response of the tissues to ethylene · alleviates certain physiological disorders such as chilling injury of various commodities · affects post-harvest pathogens directly or indirectly and consequently retards decay incidence and severity · useful tool for insect control in some commodities · increases the availability of F&V even during off season.

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The stability and shelf life of fruit and vegetables 651 CA is used to extend the utility and useful marketing period of fresh F&V during storage, transportation and distribution, so as to maintain quality, nutritional, and market value of the produce, in comparison to that achieved via the use of refrigeration or cold storage alone. CA works by altering O2 and CO2 concentrations during storage (i.e., reducing O2 and increasing CO2). Different CA storage regimes such as low O2 (LO), ultra low O2 (ULO) and more recently dynamic controlled atmosphere (DCA) or system (DCS) (Prange et al., 2005) have been developed as a result of more accurate control of low levels of O2 facilitated by automated measuring and control systems (Hoehn et al., 2009). Control of O2 and CO2 determines indirectly the nitrogen (N2) concentration, which is by far the most abundant component, followed by CO2 and O2, and trace amounts of inert gases. Optimal temperature and relative humidity (RH) must be adhered to in conjunction with optimal levels of O2 and CO2 to assure successful storage outcomes. The storage conditions are narrowly defined depending on the type of F&V and may include setting the lowest temperature (to prevent freezing or chilling), the lowest level of O2 (to attenuate the rate of respiration and delay the development of senescence), ensuring the highest and safest level of CO2 (to minimize the rate of respiration and slow the senescence and ripening process), the lowest level of ethylene (to attenuate ripening and senescence) and maintenance of high levels of humidity (to reduce moisture loss from the stored product). 22.4.2 Modified atmosphere packaging (MAP) MAP of fresh produce relies on modifying the atmosphere inside the package, achieved by the natural interplay between two processes: the respiration of the product and the transfer of gases through the packaging, which leads to an atmosphere richer in CO2 and poorer in O2. To design a proper MA package for a particular product is a complicated task, due to the complexity of the system and several variables involved. The single most important factor is respiration rate of the product. When fresh-cut F&V is packed in MAP, it is exposed to high CO2 and/or low O2, and the sensitivity of it to modified atmospheres may be quite different from the whole F&V. The level of anaerobic metabolism is determined by the O2 threshold for anaerobic metabolism induction, as well as the handling temperature of the F&V (Lakakul et al., 1999). The target atmosphere for the real distribution chain must reflect a potential to exposure to non-ideal atmospheres. If the packages are exposed to higher temperatures during distribution, there is a risk of anaerobic metabolic accumulation with concomitant risk of off-flavours. The characterization of the respiration rate process is a central point in the design of MAP systems. Mathematical models as a function of temperature, O2/ CO2 concentrations describing O2 consumption and CO2 production are useful in packaging design and optimal MAP for extending shelf life of F&V. Traditionally, MAP has evolved by a `trial and error' approach that may have economic and safety hazard consequences; it is also an extremely time-

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consuming procedure. For example, a high respiring product packed inside a low permeability film means anoxic conditions (absence of O2), under which very dangerous pathogens thrive (e.g. Listeria). The `pack-and-pray' approach with in-house trial-and-error experiments is commonly employed for choosing a suitable packaging material for MAP. The result is that most commercial fresh produce packages in major supermarkets often deviate from the optimal MAP conditions, resulting in shorter shelf life and in some cases anoxic conditions (Mahajan et al., 2009). How to select efficiently and effectively a packaging for fresh produce? University College Cork has developed software called `Pack-inMAP' which can be used to select the optimum MAP conditions and recommend the best packaging material for the specified product. In the web-based software (www.packinmap.com), the user logs on, specifies their product and software recommends the optimal atmosphere and calculates the respiration rate. It then identifies the best packaging material and micro-perforations, if needed, for maximizing the shelf life of the specified product. The key elements of the software are: · · · · · · · ·

respiration rate database for fresh and fresh-cut F&V O2 and CO2 permeability database for packaging materials database on optimum MAP conditions mathematical algorithm to enable users to choose the best packaging materials and micro-perforations needed mathematical algorithm to simulate the O2 and CO2 levels in the package with time package design for individual as well as mixed products assessment of the effect of temperature abuse on product/package calculation of oxygen transmission rate (OTR) required for a specified product.

22.5

Future trends

Edible coatings can protect perishable fresh products from deterioration by retarding dehydration, suppressing respiration, improving texture quality, helping retain volatile flavour compounds and reducing microbial contamination. Despite significant benefits from using edible coatings for extending shelf life and enhancing quality and microbial safety of fresh produce, commercial application on a broad range of F&V are still very limited. Continued efforts are necessary to develop stable emulsion coatings with desired moisture-barrier properties and studies are needed on improving coating adhesion and durability on the surface of F&V along with sensory qualities and consumer acceptance. The hyperspectral imaging technique has been regarded in recent years as a smart and promising analytical tool for analyses conducted in research, control and industry. Hyperspectral imaging is a technique that generates a spatial map of spectral variation, integrating spectroscopic and imaging techniques to enable direct identification of different components and their spatial distribution in the

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tested sample. The advantages of hyperspectral imaging over the traditional methods include minimal sample preparation, non-destructive nature, fast acquisition times, and visualizing spatial distribution of numerous chemical compositions simultaneously (ElMasry and Sun, 2010). The utilization of hyperspectral imaging for the in-line inspection of F&V holds exceptional potential for not only increasing the quality and safety of food products but also offers a significant financial return for food processors by increasing the throughput and yield of processing industries. The hyperspectral imaging technique has been implemented in several applications such as defect detection or quality determination on F&V, e.g., strawberries (ElMasry et al., 2007; Nagata et al., 2004), apples (Kim et al., 2002; Li et al., 2002), cucumber (Cheng et al., 2004; Liu et al., 2006) and tomatoes (Polder et al., 2002). Hyperspectral imaging offers the incremental benefit of analysing the estimated physical, chemical and mechanical properties in various commodities (Lu, 2004; Nagata et al., 2005), both for in-line inspection and in the laboratory thereby significantly increasing production yields. The successful attempts to evaluate internal properties non-destructively were accomplished using spectral technology for prediction of soluble solids (Park et al., 2003; Peiris et al.,1999), firmness (Park et al., 2003; Peirs et al., 2002), moisture content (ElMasry et al., 2007; Katayama et al., 1996), and acidity (Lammertyn et al., 1998; Peirs et al., 2002). Through high-throughput chemometrics, food products can be analysed with hyperspectral sensing for disease conditions, ripeness, tenderness, grading or contamination. The hyperspectral imaging technique is currently tackling many challenges and may be considered the preferred analytical tool in identifying compositional fingerprints of food.

22.6

References

and CHACHIN K (1992). Studies on the physiological and chemical changes of fresh-cut bananas (Part 1). Effect of cutting modes on the changes of physiological activity and deterioration in fresh-cut green tip bananas, J. Japan Soc. Hort. Sci., 67, 123±129. AKED J (2000). Fruits and vegetables, In: D. Kilcast and P. Subramaniam (eds), The Stability and Shelf-Life of Food, Woodhead Publishing Ltd, Cambridge, pp. 249± 278. BARRY-RYAN C and O'BEIRNE D (1998). Quality and shelf-life of fresh-cut carrot slices as affected by slicing method, J. Food Sci., 63, 851±856. BARRY-RYAN C and O'BEIRNE D (2000). Effects of peeling methods on the quality of readyto-use carrots slices, Int. J. Food Sci., 35, 243±254. BEERS A, (1999). Major retailer demands verification that produce suppliers are using GAPs, Food Chemical News, 13 December. CHENG X, CHEN Y R, TAO Y, WANG C Y, KIM M S and LEFCOURT A M (2004). A novel integrated PCA and FLD method on hyperspectral image feature extraction for cucumber chilling damage inspection, Transactions of the ASAE, 47(4), 1313± 1320. ABELES F B, MORGAN M

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(1998). Transport of fruit and vegetables. In: R Heap, M Kierstan and G Ford (eds), Food Transportation. Blackie Academic and Professional, London, pp. 111± 28. ELMASRY G and SUN DA-WEN (2010). Principles of hyperspectral imaging technology. In: Da-Wen Sun (ed.), Hyperspectral Imaging for Food Quality Analysis and Control, Elsevier, London, pp. 3±43. ELMASRY G, WANG N, ELSAYED A and NGADI M (2007). Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry, J. Food Eng., (1), 98±107. FRITH J (ed.) (1991). The Transport of Perishable Foodstuffs, Shipowners Refrigerated Cargo Research Association, Cambridge. HODGE K (1998). Taco Bell demanding about food safety, Fresh-cut Magazine, 6(2), 12± 14. HOEHN E, PRANGE R K and VIGNEAULT C (2009). Storage technology and applications. In: E M Yahia (ed.), Modified and Controlled Atmospheres for Storage, Transportation, and Packaging of Horticultural Commodities, Woodhead Publishing Ltd, Cambridge, pp. 17±50. HURST W C (ed.) (1992). Recommended Sanitary Guidelines for the Produce Processing Industry, 1st edn, National Association of Fresh Produce Processors, Alexandria, VA. KADER A A (1987). Respiration and gas exchanges of vegetables. In: J Weichman (ed.), Postharvest Physiology of Vegetables, Marcel Dekker, New York, pp. 25. KADER A A (ed.) (1992). Postharvest Technology of Horticultural Crops, University of California, Publication 3311. KADER A A (2002a). Postharvest biology and technology: an overview. In: A A Kader (ed.), Postharvest Technology of Horticultural Crops, University of California, Publication 3311, pp. 39±48. KADER A A (2002b). Quality parameters of fresh-cut fruits and vegetables products. In: O Lamikanra (ed.), Fresh-cut Fruits and Vegetables, Science Technology and Market, CRC Press, Boca Raton, FL, pp. 11±20. KADER A A (2005). Controlled atmosphere, Department of Pomology, University of California, Davis, CA, http://una:usda.gov/hb66/013ca.pdf. KASMIRE R F and THOMPSON J F (1992). Selecting a cooling method. In: A A Kader (ed.), Postharvest Technology of Horticultural Crops, University of California, Publication 3311, pp 63±68. KATAYAMA K, KOMAKI K and TAMIYA S (1996). Prediction of starch, moisture, and sugar in sweetpotato by near infrared transmittance, HortScience, 31(6), 1003±1006. KIM M S, LEFCOURT A M, CHAO K, CHEN Y R, KIM I and CHAN D E (2002). Multispectral detection of fecal contamination on apples based on hyperspectral imagery: part I. Application of visible and near-infrared reflectance imaging, Transactions of the ASAE, 45(6), 2027±2037. KNEE M, PROCTOR F J and DOVER C J (1985). The technology of ethylene control: use and control in post-harvest handling of horticultural commodities, Ann. Appl. Biol., 107, 581±595. LAKAKUL R, BEAUDRY R M and HERNANDEZ R J (1999). Modelling respiration of apple slices in modified atmosphere packages, J. Food Sci., 64, 105±110. LAMMERTYN J, NICOLA B, OOMS K, DE SMEDT V and DE BAERDEMAEKER J (1998). Nondestructive measurement of acidity, soluble solids, and firmness of Jonagold apples using NIR spectroscopy, Transactions of the ASAE, 41(4), 1089±1094. EKSTEEN G J

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and GU W (2002). Computer vision based system for apple surface defect detection, Computers and Electronics in Agriculture, 36(2), 215±223. LIU M S and MA PC (1983). Postharvest Problems of Vegetables and Fruits in the Tropics, AVRDC Publication 83±197, Asian Vegetable Research and Development Center, Shanhua, Taiwan. LIU Y, CHEN Y R, WANG C Y, CHAN D E and KIM M S (2006). Development of hyperspectral imaging technique for the detection of chilling injury in cucumbers; spectral and image analysis, Applied Engineering in Agriculture, 22(1), 101±111. LU R (2004). Multispectral imaging for predicting firmness and soluble solids content of apple fruit, Postharvest Biology and Technology, 31(1), 147±157. MAFF (1996a) EC Quality Standards for Horticultural Produce: Vegetables. MAFF (1996b) EC Quality Standards for Horticultural Produce: Fresh Salads. MAFF (1996c) EC Quality Standards for Horticultural Produce: Fresh Fruit. MAHAJAN P V (2002). Studies on controlled atmosphere storage for apple and litchi using liquid nitrogen, PhD thesis, Agricultural and Food Engineering Department, IIT, Kharagpur. MAHAJAN P V and GOSWAMI T K (1999). Controlled atmosphere storage for horticultural crops ± a review paper, Indian Journal of Cryogenics, 22(4), 123±136. MAHAJAN P V, OLIVEIRA F A R and MACEDO I (2008). Effect of temperature and humidity on the transpiration rate of the whole mushrooms, J. Food Engineering, 84(2), 281± 288. MAHAJAN P V, SOUSA-GALLAGHER M J and OLIVEIRA J C (2009). Packaging design for fresh produce, Food Packages, 27, 20±23. MITCHELL E G (1992). Cooling methods. In: A A Kader (ed.), Postharvest Technology of Horticultural Crops, University of California, Publication 3311, pp. 56±62. MUPONDWA E K (2009). Economic benefits of controlled atmosphere storage and modified atmosphere packaging. In: E M Yahia (ed.), Modified and Controlled Atmospheres for Storage, Transportation, and Packaging of Horticultural Commodities, CRC Press, Boca Raton, FL, pp. 527±552. NAGATA M, TALLADA J G, KOBAYASHI T, CUI Y and GEJIMA Y (2004). Predicting maturity quality parameters of strawberries using hyperspectral imaging. ASAE/CSAE annual international meeting, Ottawa, Ontario, Canada, Paper No. 043033. NAGATA M, TALLADA J G, KOBAYASHI T and TOYODA H (2005). NIR hyperspectral imaging for measurement of internal quality in strawberries. ASAE meeting, Tampa, Florida, ASAE Paper No. 053131. PARK B, ABBOTT J A, LEE K J, CHOI C H and CHOI K H (2003). Near-infrared diffuse reflectance for quantitative and qualitative measurement of soluble solids and firmness of Delicious and Gala apples, Transactions of the ASAE, 46(6), 1721± 1731. PEIRIS K H S, DULL G G, LEFFLER R G and KAYS S J (1999). Spatial variability of soluble solids or dry-matter content within individual fruits, bulbs or tubers: implications for the development and use of NIR spectrometric techniques, HortScience, 34, 114±118. PEIRS A, SCHEERLINCK N, TOUCHANT K and NICOLAIÈ B M (2002). Comparison of Fourier transform and dispersive near-infrared reflectance spectroscopy for apple quality measurements, Biosystems Engineering, 81(3), 305±311. PHILLIPS C A (1996). Review: modified atmosphere packaging and its effect on the microbiological quality and safety of produce, Int. J. Food Sci. Technol., 31, 463±79. POLDER G, VAN DER HEIJDEN G W A M and YOUNG I T (2002). Spectral image analysis for measuring ripeness of tomatoes. Transactions of the ASAE, 45, 1155±1161. LI Q, WANG M

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and HARRISON P A (2005). Innovation in controlled atmosphere technology, Stewart Postharvest Rev., 3(9), 1±11. REID M S (1992). Ethylene in postharvest technology. In: A A Kader (ed.), Postharvest Technology of Horticultural Crops, University of California, Publication 3311, pp. 97±102. SCRUTON T (2000). 82 food poisoning outbreaks pinned on produce items, Packer, 107 (8): A7. THOMPSON A K (1996). Postharvest Technology of Fruits and Vegetables, Blackwell Science Ltd, Oxford. TOIVONEN P M A and DEELL J R (2002). Physiology of fresh-cut fruits and vegetables. In: O Lamikanra (ed.), Fresh-cut Fruits and Vegetables, Science Technology and Market, CRC Press, Boca Raton, FL, pp. 91±123. WILLS R B H, KU V V V, SHOHET D and KIM G H (1999). Importance of ethylene levels to delay senescence of non-climacteric fruit and vegetables, Aust. J. Exp. Agric., 39, 221±222. YAHIA E M (2006). Modified and controlled atmosphere for tropical fruits, Stewart Postharvest Rev., 5(6), 1±10. YAHIA E M (2009). Introduction. In: E M Yahia (ed.), Modified and Controlled Atmospheres for Storage, Transportation, and Packaging of Horticultural Commodities, CRC Press, Boca Raton, FL, pp. 1±16. PRANGE R K, DELONG J M, DANIELS-LAKE B J

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23 The stability and shelf life of bread and other bakery products S. P. Cauvain and L. S. Young, BakeTran, UK

Abstract: This chapter provides a brief overview of the types of bakery products and the processes used to manufacture them. The key `fresh' characteristics of bakery products are described. Factors affecting the shelf life stability of bread and other bakery products are discussed. Techniques suitable for evaluating changes in the properties of bread and other bakery products during storage are identified and means for ensuring the stability and extending the shelf life of bread and other bakery products are described. Key words: bread, cake, biscuits, cookies, pastry, staling.

23.1

Introduction

The term bakery products covers a diverse range of foods which are linked by the common thread that their recipes contain a significant proportion of wheat flour. The proteins in wheat flour have the special property that when hydrated with water and subjected to mechanical agitation, they form the visco-elastic material which is commonly referred to as gluten (Stauffer, 2007). While based on wheat flour, the significant formation of a gluten network is not common to all classes of baked products. Gluten formation is essential in the production of bread since the network which is formed enables the trapping of air bubbles which will later be inflated by the production of carbon dioxide gas from bakers' yeast fermentation (Cauvain, 2003a). The transition from flour, water, salt, yeast and other functional ingredients to a baked loaf of bread is commonly described as an example of a change from a foam to a sponge. In the foam gas bubbles which have been incorporated during mixing are separated by the gluten

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network and are therefore discrete from one another while in the sponge the gas cells are open and inter-connected. This transition gives bread its characteristic finished cellular structure (Cauvain and Young, 2006a). The other classes of bakery products which fit the foam to sponge model are the many varieties of cakes and sponges. However, in these products gluten formation is so limited as to play little or no part in the formation of the initial foam (Cauvain and Young, 2006a) and the foam stabilising mechanism is quite different from that in bread and relies more on the egg proteins, fats and emulsifiers (Cauvain, 2003b). The final cakes and sponges do have a cellular structure similar in many ways to that of bread but their eating characters are very different in part because of the lack of gluten formation in the mixed batter arising from differences in recipe and processing conditions. Gluten formation in dough used to manufacture biscuits, cookies and pastries is also limited, except in the case of laminated products (Cauvain and Young, 2006a).

23.2

A brief overview of the manufacture of bakery products

23.2.1 Bread The production of bread and other fermented products accounts for the greatest volume proportion of all manufactured baked products. Breads come in a wide variety of forms (Fig. 23.1) and apparently different processes but the underlying principles involved in their production are remarkably similar. Essentially the processes all involve the mixing of wheat flour, water, yeast, salt and other functional ingredients in the development of a gluten structure in the dough, the preparation and shaping of individual dough pieces, their fermentation and finally the heat-setting step called baking (Cauvain, 2001). The different breadmaking processes vary most in the manner in which the dough ingredients are mixed and the gluten network is developed. Cauvain (2007) divided the main breadmaking processes into four main groups:

Fig. 23.1 Bread varieties.

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straight dough bulk fermentation sponge and dough rapid processing mechanical dough development.

Each of the processes employed in the main breadmaking groups tends to yield slightly different characteristics in the final product which has implications for the shelf life and stability of the product as will be discussed below. The first process, straight dough bulk fermentation, is considered by some to be the most traditional. Its essential features are based on the mixing of the ingredients to form an homogeneous dough followed by resting of the dough in bulk for a prescribed time (floortime), depending on flour quality, yeast level, dough temperature and the bread variety being produced. Dough mixing is usually carried out at low speed and little energy is imparted to the dough. Because of this approach the development of a suitable gluten network relies heavily on the enzymic processes which take place during the fermentation period. The length of the bulk fermentation period may vary from 1 to 16 h depending on the requirements of the baker; commonly periods of 2±4 h are used. The second group, sponge and dough, have similar elements to those for bulk fermentation but in this case only part of the ingredients (the sponge) are given any significant fermentation. This is followed by the mixing of the sponge with the remainder of the ingredients to form an homogeneous dough and its immediate processing. The process is commonly used in North America. It is common to use the same type of flour in both the sponge and the dough making stages. The rapid processing group covers a heterogeneous collection of processes which have evolved based on different combinations of active ingredients and processing methods. A common element within this process group is the inclusion of functional ingredients to assist in dough development and the reduction of any individual fermentation period, in bulk or as divided pieces (but not including proof) to less than 1 h. The final group, mechanical dough development, is characterised by the mixing and development of the dough in one single operation and the absence of a bulk fermentation period. The best known and most widely used of the mechanical dough development processes is the one launched in the UK in 1961 ± the Chorleywood Bread Process (CBP) and it is in use in many countries around the world today (Cauvain and Young, 2006b). The essential features of the CBP are the mixing and development of a dough to defined energy input in 2±5 minutes, the control of mixer headspace atmosphere to achieve given bread cell structures and the addition of a bread improver (now ascorbic acid). An important aspect of the CBP that is not readily available in other breadmaking processes is the potential for direct control of the cell structure in the final bread by adjusting the pressure applied during mixing. This versatility enables a variety of bread types to be made from the same dough formulation and processing equipment (Cauvain, 1994; Cauvain and Young, 2006b).

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After leaving the mixer the processing of the dough to become bread follows essentially the same pattern whichever breadmaking process is used. The main steps are the sub-division of the bulk dough into unit pieces, their shaping, expansion through fermentation in the prover (proof), baking in the oven and cooling before consumption. 23.2.2 Cakes Cake batters are a complex emulsion and foam system (Cauvain, 2003b). Minute air bubbles are trapped in the batter by the surface active proteins in the egg, fat, a suitable emulsifier or a combination of all three. Because high levels of water and liquid egg are used in cake recipes, the resulting batter has a low viscosity and gluten formation is limited. The low viscosity of cake batters allows them to be easily deposited and there is seldom any post-depositor processing. The batter is held in pans or deposited directly onto the oven band (e.g. Swiss roll) to be quickly heat-set in the oven. Some of the wide variety of cake products are illustrated in Fig. 23.2. 23.2.3 Biscuits and cookies The levels of water used in the mixing of biscuit dough are low by comparison with bread, partly to limit the formation of gluten and partly to reduce the amount of water that needs to be driven off during baking to ensure that the final products have the hard-eating qualities which is a key characteristic of these products. The consistency of biscuit and cookies doughs plays a very important part in the choice and operation of a particular production process. Individual pieces may be formed from the bulk dough after mixing by sheeting followed by cutting (sheet and cut), by pressing dough into a mould and then extracting it for baking (rotary moulding) or by extrusion of a cylinder from which unit pieces are cut (wire-cut). There is seldom any post-forming processing and the pieces

Fig. 23.2 Cake varieties.

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Fig. 23.3 A selection of biscuit and cookie types.

usually move quickly to the oven for baking. A selection of biscuit and cookie types are illustrated in Fig. 23.3. 23.2.4 Pastry The main forms of pastry are either based on a short dough prepared in a similar manner to biscuit dough or laminated pastries. The former are usually shaped with some form of blocking die while the production of the latter is based on preparing dough sheets to encase layers of fat (Cauvain and Young, 2006a); with successive sheeting and folding the alternating layers of dough and fat yield a characteristic flaky structure. Puff pastry is the main example of a laminated paste and there are related products such as Danish pastry, croissant (Fig. 23.4) and crackers which are yeast-raised.

Fig. 23.4 Croissant.

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23.3 The key `fresh' characteristics of bakery products 23.3.1 Bread, rolls and buns This group of products is characterised by having a `crust', a dry, thin layer enclosing the soft, cellular structure of the crumb. Bread crust has considerably lower moisture content than that of the crumb; typically crust moisture contents are in the range 12±17%, while for the crumb they will range from 35 to 42%, depending on bread type. The low moisture crust has a hard and brittle eating character which may be accentuated by the thickness of the crust. All fermented bread products have an open, cellular crumb structure. A fundamental requirement of bread crumb is that it should be relatively soft combined with a degree of resilience or springiness and a degree of `chewiness'. An important contributor to the character of bread crumb is the nature of the cellular structure as determined by the size of the individual cells, their distribution throughout the product and the thickness of the cell wall material. The water activity of bread is high (around 0.95) and its mould-free shelf life relatively short, typically 4±10 days depending on storage conditions and whether preservatives are used. There are other short-term changes in both the crust and crumb of breads which affect its shelf life. 23.3.2 Cakes and sponges These may be classified as intermediate moisture foods with moisture contents in the range 18±30% of the product mass. Cake products do have a thin crust but it does not usually have significantly less moisture than the crumb. The cellular structure of cakes tends to be less well defined than that of bread though there is considerable variation. A key attribute of cakes is the relatively longer shelf life which they enjoy (often many weeks) compared with that of bread (a few days). 23.3.3 Biscuits, crackers and cookies These products are much smaller in unit size and weight than other bakery products. Their moisture contents are typically under 5% and the low moisture content coupled with the thinness of the products gives them a crisp, hard eating character though this may be moderated with higher recipe fat levels. The low moisture content and low water activity of products in this group (typically <0.5) mean that they have long mould-free shelf lives, typically many months. 23.3.4 Pastries Pastry products are a versatile medium which can be considered as an `edible packaging'. The intimate contact between pastry and the different fillings used yields a wide range of product textures, moisture contents and water activities. The pastry component tends to have higher moisture contents than biscuits but below that of cake. Typically fresh pastries have a firm and relatively crisp eating character when freshly baked. The shelf life of the pastry can be quite

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long but the migration of moisture from filling to paste (Cauvain and Young, 2008) reduces this life considerably so that typical shelf lives will range from a few days for meat-containing pastries (even when refrigerated) to a few weeks for pastries with sweet fillings.

23.4 Factors affecting the stability of bread and other bakery products 23.4.1 The nature of staling in bakery products The main physical changes which take place during the storage of bakery products are summarised in Table 23.1. The relative importance of each of these changes in baked product character will depend on the type of product being made as shown by the few examples recorded in Table 23.1. For example, the loss of crust crispness will be less important in pan breads than in hearth breads or baguette. All of the changes that occur during storage tend to be embraced by the term staling, although loss of perceived freshness may be a more appropriate term, because for cereal scientists staling has become mostly associated with the changes that occur in the crystallinity of the wheat starch in baked products during storage. In the oven, the wheat starch present in bread dough and cake batter undergoes the transformation known as gelatinisation. In the unbaked starch, it is the amylopectin fraction which contains ordered regions and is embedded in the non-crystalline matrix of the amylose, the other main constituent of the lenticular wheat starch granules (Schoch, 1945). The starch granules are largely insoluble in cold water, but when heated in an aqueous medium they begin to absorb water and swell. Penetration of the warm water into the granules Table 23.1

Physical changes in bakery product character during storage

Product character

Examples of the nature of the change during storage

Crust crispness

Loss of bread crust crispness through moisture migration from the crumb. Softening of biscuits through absorption of moisture from the atmosphere. Loss of pastry crispness through moisture migration from the filling. Increase in bread crust moisture because of moisture migration from the crumb. Dehydration of unwrapped bread crumb. In fruited bread products migration of water from crumb to fruit (Marston, 1983). Firming of bread crumb through starch retrogradation (staling) in the absence of moisture loss. Increased friability of cake crumb through staling or moisture migration in fruited products.

Product crispness

Crust moisture

Crumb firmness Crumbliness

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contributes to a loss of crystallinity in their structure, and as the temperature begins to rise, the intermolecular bonds of the starch polymers begin to break. This increases the number of hydrogen bonds available for the water present, and the viscosity of the starch±water mixture begins to increase. Further heating of the mixture results in a change from a viscous liquid to a solid, and this point is regarded as the gelatinisation temperature of the starch. In bread, gelatinisation occurs in the region of 60±65 ëC (140±149 ëF) while in cakes where large quantities of sugar are present in the batter, the gelatinisation temperature may rise to 90 ëC (194 ëF). On cooling, the starch polymers begin to lose their mobility and they `retrograde'. This retrogradation continues during storage and contributes to the firming that typically occurs with bread and cake crumb. Retrogradation is both time- and temperature-dependent, with the maximum staling rate for bread occurring around 4 ëC (Cauvain and Young, 2008). It is generally considered that the water level in the baked product needs to be greater than 20±30% for retrogradation to occur and, as noted above, the moisture content of bread crumb readily exceeds such levels. During storage, water is redistributed throughout the loaf structure. On the macroscopic scale this involves the movement of moisture from crumb to crust while on the microscopic scale there is movement between starch and protein. There is no consensus favoured view as to the direction of moisture movement with Wilhoft (1973) favouring a loss of moisture from the gluten to the starch during storage, and D'Appolonia and Morad (1981) favouring the reverse. This lack of clarity arises partly from the overlap in the glass transition temperature ranges for starch and gluten for a given moisture content, and partly from the close physical relationship of the polymers in the crumb. In bread crumb, the starch granules are attached to the continuous gluten network formed in the dough (Rao et al., 1992) and this close physical association provides a ready opportunity for moisture migration. Bread staling is a two-stage process involving both the amylose and amylopectin fractions of the starch. The generally accepted mechanism is that soon after leaving the oven the amylose fraction retrogrades and makes a significant contribution to the initial firming of bread so that it can be sliced commercially within the first couple of hours after leaving the oven. It has been known for some time that the longer-term firming (which takes place over several days and need not involve moisture loss) is associated with the amylopectin fraction of the starch (Schoch and French, 1947). Re-heating stale bread softens the crumb and restores the crust crispness to some extent. In the re-heating process there is some further loss of water from the product crust region and a moisture gradient is re-established in the product. After being refreshed, the subsequent rate of staling increases significantly by comparison with that which previously prevailed. Cake crumb also loses its freshness and becomes firmer during storage. As with bread this may arise even when the conditions are such as to prevent moisture loss. Two sub-processes contribute to cake staling: the loss of moisture from the crumb by diffusion to the crust, and an intrinsic firming of the cell wall

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material. These two sub-processes have different temperature relationships, the first having a positive and the second a negative temperature coefficient. Both crumb-firming effects are similar to those observed with bread but the maximum firming peak is between 15 and 25 ëC. 23.4.2 Moisture content In all baked products there is a direct relationship between product moisture content and the perception of product freshness. The nature of this relationship is very product-specific so that in some products (e.g., bread and cake crumb) higher moisture contents are equated with fresher products while in others (e.g., bread crust, biscuits and pastries) lower moisture contents are equated with fresher products. Because of these important relationships, knowledge of the moisture content of a baked product and in the case of a composite baked product (e.g., an apple pie), the moisture content of the individual components is very important. However, it must be recognised that while the level of moisture in a baked product is very important in the perception of its quality other properties such as water activity (see below) are at least equally important in understanding and ultimately, controlling product shelf life in the fullest sense of the term. 23.4.3 Moisture migration When baking is finished, the moisture content of the baked product crust is lower than that of its centre. The moisture gradient which is present after baking may remain in the product during cooling and for some time during storage but moisture will move from the areas of higher moisture to those with lower water until equilibrium of moisture content is reached. The rate at which equilibrium is achieved depends on many factors, some of which are discussed in more detail below. In bread the softening of the crust and the accompanying firming of the crumb is the best known example of the moisture migration effect. This phenomenon is most readily observed in oven-bottom or hearth breads, baguette and crusty rolls, where the softening of the crust detracts from the product character and leads to loss of consumer appeal as the formerly crisp eating crust assumes a `chewy' character. Pan breads, on the other hand, may actually benefit from this moisture migration phenomenon during storage since a crisp crust is largely undesirable with such products when they are sliced or eaten. In understanding the implications of moisture migration at the macro scale, it is necessary not only to know the moisture contents but also the relevant component masses involved. For example Cauvain and Young (2008) calculated that if the low moisture crust on a sandwich loaf increased in thickness from 1 to 2 mm then there would be a resulting decrease in the equilibrium moisture content of the crumb of 1.2%, a figure which has significant implications not only for the initial perception of product quality (crumb firmness) but also for

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the subsequent staling rate of the product. Such considerations go some way to explaining why the crumb of crusty bread loses its apparent freshness more rapidly than that in pan breads. In crusty breads, the more open cell structure also increases the rate of moisture diffusion through the crumb, which also encourages crumb drying and crust softening. Loss of perceived freshness as the result of moisture migration in cake products follows much the same lines as those for bread. However, cake products are not usually expected to have a crisp eating crust, and so changes in crust character are not a critical issue. In biscuits and pastries, the moisture contents are so low that moisture may migrate from the atmosphere into the product, rather than from product to atmosphere as with bread and cakes. This is a common mechanism by which cookies and pastries go soft or stale. One particular moisture migration phenomenon in biscuit, cookies and crackers (and occasionally in pastries) is that known as `checking'. This is the formation of cracks and splits without the products being subjected to external forces strong enough to fracture the product. It is most commonly seen in products with recipes that are low in fat and sugar, e.g. semi-sweet biscuits such as the UK Rich Tea product. It has long been known that checking is the result of moisture migrating within the product after baking (Dunn and Bailey, 1928) and it is associated with physical weaknesses in the baked product which make it susceptible to the effects of mechanical shocks experienced in cooling, wrapping and transport. The cracks are often radial in round products, although apparently more randomly distributed cracks may occur in products like crackers. Using a finite element modelling method, Saleem et al. (2005) confirmed the critical role that the moisture gradient played in biscuit checking and showed that when the relative humidity (RH) of the atmosphere surrounding the biscuit is low enough (26% RH) to allow both absorption and desorption to occur that the stresses which are set up can cause the biscuit to crack. If the atmospheric RH was high enough for the biscuit to absorb moisture from the atmosphere, the predicted stresses were insufficient to cause cracking. In practical terms a dilemma for the biscuit baker is whether to hold biscuits at a higher relative humidity and risk them absorbing water and going soft or to ensure that they stay at a low relative humidity and risk them checking.

23.4.4 The mechanisms involved in moisture migration Moisture migrates in bakery foods by the following mechanisms: · By direct diffusion from the component with the higher moisture content to the one with the lower moisture content. · By vapour phase transfer, where the moisture migrates from the component with the higher equilibrium relative humidity (ERH) to the one with the lower ERH. · By the formation of surface water through syneresis within a gel as a result of crystallisation or aggregation of polymers.

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The direct diffusion of moisture arises when two or more components are in intimate contact with one another. It may occur at the macroscopic level and is aided by factors such as capillary action, or it may occur at the molecular level (Labuza and Hyman, 1998). The rate of diffusion between the components depends to a large extent on the differences in water activity between the components; the greater the difference in water activity, the faster the rate of diffusion. The effects of gravity can increase the rate of diffusion to lower sections of the product. There is also some impact from the physical nature of the materials in contact with one another and in particular the porosity of the materials. The structures of many baked products, with their macroscopically broken cells act like many small capillary tubes and moisture is drawn into them. If the material has a largely closed network with a dense, un-aerated structure, rates of moisture migration will be low. Moisture migration by vapour transfer is most evident with wrapped products. In this mechanism, moisture leaves a product component through surface evaporation to enter the surrounding atmosphere from where it can then be absorbed by another component. Vapour phase moisture transfer is not normally evident with unwrapped products because moisture at the surface is usually swept away by any air movement over the product. The role that product porosity may play in the transfer of moisture by vapour phase transfer in bakery products has probably been underestimated. The open cells of bread crumb are likely to play a significant part in the transfer of water vapour with migration occurring more rapidly through bread products with a more open structure (i.e., larger voids) such as baguette, than would be the case in a product with a fine cell structure (i.e., smaller voids) such as pan breads. The shrinkage of gels due to crystallisation or aggregation of polymers can cause loss of water from the surface of components. This problem is common with some starch gels, particularly those subjected to freezing and thawing. Surface water forms because of the breakdown of the gel and subsequent release of the previously `bound' water, which may evaporate to be absorbed by other components by diffusion, or be lost from the product leading to drying out and shrinkage of the gel, or the moisture may be transferred to another component. The staling of bread crumb is often quoted as an example of syneresis though more obvious examples are the breakdown of whipped cream foams and baked fillings like egg custards (Cauvain and Young, 2009a). 23.4.5 Equilibrium relative humidity (water activity) Equilibrium relative humidity (ERH) and water activity (aw) are terms used frequently in the description of bakery products as a means of explaining their potential stability. Water activity expresses the `availability' of the water in a given solution, whereas ERH applies, strictly speaking, to the atmosphere in contact with the solution. When the atmosphere and the solution are in equilibrium, the terms aw and ERH can be used interchangeably. The relationship under a defined set of conditions of atmospheric temperature and pressure is

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straightforward and described by the following equations: aw ˆ ERH/100 ERH ˆ 100  aw% Since ERH is based on the measurement of humidity, it is usual to express it as a percentage, while aw has no units. The scale for aw runs from 0 to 1, with 1 representing pure water; that for ERH runs from 0 to 100%, with 100% representing pure water. For each bakery product, there is a unique relationship between its moisture content and water activity. The precise relationship depends on whether the material being assessed is undergoing dehydration (e.g., drying or baking) or hydration (e.g., wheat flour proteins in dough mixing). The two different processes are usually described as desorption and adsorption respectively. The relationship between product moisture content and aw depends on the nature and composition of the ingredients and the processing that has been carried out to convert the ingredients into a baked product. The stability of a baked product is dependent on both its moisture content and its aw. Only in pure water are aw and moisture content identical, i.e. 1.0 and 100%, respectively. Once ingredients and their concentrations within a product are taken into account, along with their effects on the water availability, the moisture content and the water activity values can differ. However, it is true that as the moisture content of a given product increases or decreases, the water activity increases or decreases accordingly. 23.4.6 Microbial shelf life The concept of water activity was first used by Scott (1957) to show that aw rather than moisture content determined the microbial safety of food. The growth of microorganisms is generally considered to be inhibited if the osmotic pressure of the medium on or in which the organism is located is sufficiently high. Therefore knowledge of a product's aw or ERH is useful for identifying and understanding potential microbial issues. The ERHs of bakery foods covers a wide range running from 30% for biscuits up to 98% for creams and fillings. At values above 88% bacterial spoilage may occur but with many cake and bread products the main spoilage mechanisms involve mould growth. Research on the relationship between bakery product ERH and mould growth has led to the development of models for the prediction of product mould-free shelf life from a knowledge of its measured ERH and even to a computer-based system (ERH CALCTM) which allows the estimation of a product ERH from its formula and the subsequent prediction of its mould-free shelf life (Cauvain and Young, 2008). In general terms the microbial shelf life of bread is short and while the ERH of bread crumb is high enough to support bacterial growth, this is not usually a problem and the spoilage is limited to mould growth, typically within less than 4±8 days depending on the storage temperature of the products. Rolls and buns

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which contain low levels of sugar in the recipe usually have a longer mould-free shelf life than standard bread in the UK. The presence of sugar in US bread formulations (Cauvain and Young, 2007) partly accounts for the longer shelf life achieved with such products. When all baked products leave the oven their surfaces are sterile and so it is microbial contamination of the surface during cooling that leads to product spoilage. This is also true of bakery products which are sliced, e.g. cakes and bread, since the exposed surfaces tend to have higher ERHs than the product crust. While mould growth remains the main spoilage problem for bread, there is one special condition associated with bacterial spoilage. The flour used to make all breads contains spores of the bacterium Bacillus subtilis which can survive the combination of heat and time in the product centre achieved in baking a loaf of bread. In the cooled product the ERH is high enough to permit the spores to grow. Spoilage by this bacterium is characterised by an initial `fruity' odour, followed by softening of the crumb and eventually the formation of strands of crumb when the loaf is pulled apart. Bakers refer to the formation of these strands as `rope' (Cauvain and Young, 2001). The levels of contamination are higher in wholemeal flour because the bacteria spores are associated with the bran layers of the wheat grain and the problem is more readily observed in wholemeal and multi-grain breads than white. Acidification of the dough and the addition of suitable inhibitors in the recipe are commonly used to limit the problem (see below). 23.4.7 Rancidity While many bakery products contain high levels of fats, including dairy products, there are relatively few problems with oxidative rancidity. In part this is because the mould-free shelf life of the products is too short for the effects of oxidative rancidity to become apparent. The exception is low ERH products such as biscuits which have very long shelf lives. In this group the problem is associated with the auto-oxidation of the lipids that are present in the formulations. This usually occurs relatively rapidly in products with an aw of less than 0.3. Another group of bakery products which has become more popular over the last 15±20 years is the prepared pastry shell which the baker buys, fills and sells on. These shells include sweetened short and laminated pastries with low water activities, which often use butter and so may suffer with rancidity problems if stored for very long periods of time or in unsuitable conditions.

23.5 Evaluating the shelf life of bread and other bakery products 23.5.1 Sensory properties Subjective descriptions of the sensory properties of bakery foods may be used in the evaluation of their shelf lives and some of the key textural properties

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Fig. 23.5 Consumer squeeze test on bread.

relevant to cereal-based foods have already been introduced. Staleness is the allembracing term which is most often used to describe the changes in product textures as they lose their `fresh-baked' character. However, as discussed above, staleness in bakery foods is very product-specific and embraces a range of different product properties including moistness, firmness, hardness (softness), springiness, crispness, and so on. Moistness is directly related to product moisture content while firmness and hardness are generally used to describe a loss of softness in bread and cake crumb. The descriptor softness may be seen as a positive attribute in breadcrumb but is seen as a negative attribute for crusty bread products, biscuits and pastries. Fresh bread crumb is expected to exhibit springiness but cake crumb is not. Two key bread characteristics associated with freshness are the softness of the crumb and its ability to recover after the deforming force has been removed. These are most readily assessed with the fingers as shown by the common `squeeze' test applied to packaged bread by consumers (Fig. 23.5). When bread is cold on the retail store shelf, experience and subconscious training by others, leads individuals to reject packaged bread which is firm to the touch or remains `squashed' after the squeeze test. 23.5.2 Bread firmness and resilience The most commonly applied methods for objectively assessing bread and cakes use a compression or deformation test in which the product is compressed through a standard distance and the force required to achieve this measured, or by using a standard force and measuring the distance that the probe will travel in a fixed time. Owing to its cellular structure, bread crumb does not obey Hooke's Law which means that Young's modulus (stress/strain) varies with the amount of strain, the latter being measured as fractional compression (Cauvain, 2004). One of the earliest forms of objective measurement was to compress a sample of bread crumb of known thickness between two flat, parallel plates using a standard weight applied for a fixed period of time and recording the distance

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travelled by the upper plate. The equipment concerned was known as a Compressimeter. A second common form was to compress the sample using a cone with a defined angle (cone indenter). The mechanism of operation was similar to that of the Compressimeter but in this case the compressing weight was carried on a pan suspended below the bread sample with the cone pressing downwards through the bread crumb. In the case of both these pieces of equipment, additional texture information could be obtained by measuring the recovery or springiness of the sample after carefully removing the compressing force and measuring the height to which the sample recovered within a fixed period of time. The early forms of bread compression equipment have now largely been superseded by the development of motorised equipment linked with data acquisition and analysis by computer (Cauvain and Young, 2009b). One advantage of this approach is that the compressive force is applied at a fixed rate until the required degree of compression has been achieved, commonly 25 or 40% for bread (AACC, 1987). An alternative approach is to extract a core of bread or cake crumb of known dimension (diameter and height) from given locations in the slice cross-section and to compress them with a flat plate (Cauvain, 1991). The main advantage associated with this approach is that it is easy to adjust firmness data for variations in sample density and moisture, two properties which have a direct effect on the sensory perception of crumb firmness and so may mask the impact of ingredient and process changes in manufacture. The consumer squeeze test has been automated with the modern objective version comprising a pair of `fingers' which are used to compress the whole loaf (Cauvain and Young, 2009b). The test may be carried out even when the product is still in the wrapper to make the data more directly relevant to consumer perceptions of firmness. 23.5.3 Crispness The hardness or crispness of bakery products may be assessed using some form of puncture test with a needle or a small diameter cylindrical shaped probe. The test may be applied to bread crust, pastry products, biscuits, cookies and crackers. It is especially useful for following changes in crispness which arise from moisture migration in composite products (Cauvain and Young, 2008). 23.5.4 Texture profile analysis Multiple compression tests may also be used to determine a range of bread and cake crumb properties. Texture profile analysis (TPA) is a common multicompression technique used with bread crumb and the sample is subjected to two compressions in quick succession with withdrawal of the compressing force after each compression. In essence, TPA was designed to simulate the processes of biting and chewing in the mouth and the objective textural parameters were

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first identified by Bourne (1978) using an Instron Universal Texture Machine, and these have become commonly available and measured properties using modern generation texture evaluation equipment with computer data logging and analysis. 23.5.5 Moisture measurement The common method for measuring sample moisture content is by a form of oven drying method (Cauvain and Young, 2008). In general, the higher the moisture content of a baked product the lower will be its hardness value (i.e., it will be softer). 23.5.6 The measurement of ERH (water activity) Product ERH may be measured directly on a sample or may be calculated from ingredient and recipe data. For a detailed discussion of the different techniques involved in the measurement of ERH and its calculation, the reader is referred elsewhere (Cauvain and Young, 2008). Product ERH is important in the contexts of water availability for spoilage and in determining many of the quality attributes of bakery products. There are errors associated with the measurement of product ERH especially when there is insufficient water to ensure that all soluble ingredients in the recipe are in solution in the baked product. The process of baking involves the loss of water and the increased likelihood that soluble ingredients like sugars will come out of solution in the final product (recrystallisation). Thus, measured ERHs on biscuits, cookies and similar low moisture, high sugar products should be treated with caution. 23.5.7 Methods of assessing staling in bakery products As discussed above, softness combined with a degree of resilience or springiness and a degree of `chewiness' are key characteristics of bread crumb and the loss of these characteristics is most commonly associated with bread staling. It has been recognised for some time that starch retrogradation is a major contributor to these storage changes (Schoch and French, 1947) and it has become common practice to follow bread staling using thermal techniques. The most commonly used techniques are differential thermal analysis (DTA) and differential scanning calorimetry (DSC), though earlier work on bread staling was carried out with X-ray diffraction. The thermal analytical techniques are based on the principle that when a portion of bread or cake crumb is heated in a sealed pan (to prevent moisture loss), the starch component will melt and in doing so there will be a flow of heat from the sample at a given temperature. This flow of heat can be measured with suitable equipment. The magnitude of the heat flow and the temperature at which it occurs vary according to many factors, not least of which is the crystalline state of the starch at the moment of testing. For a given bread recipe

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Fig. 23.6 Examples of DSC endotherms.

the older the crumb sample the greater will be the heat flow because of the increased crystallinity of the starch as the result of retrogradation, and because of this close relationship DSC has largely become the method of choice when studying bread and cake staling. Examples of DSC endotherms for fresh and stale bread crumb are illustrated in Fig. 23.6. More recently, the range of techniques used to study bread staling has included nuclear magnetic resonance (NMR) because water plays a critical role in bread staling (Chinachoti, 1998). NMR is a non-invasive technique and unlike the thermal techniques is better able to differentiate between water held in the starch and gluten fractions in bread. This is an important distinction because, while the majority opinion is that it is the amylopectin fractions of the starch that are responsible for longer-term bread staling, there is sufficient evidence to support a view that gluten plays a greater role than previously assumed. In this context the potential for the migration of water at the microscopic level is important in understanding the final dynamics of bread staling (Chinachoti, 2003).

23.6 Ensuring stability and extending the shelf life of bread and other bakery products 23.6.1 Controlling moisture and its migration At the end of baking, the surfaces of baked products are sterile. In low moisture products such as biscuits and pastries the low moisture and low water activity ensure that there is limited opportunity for microbial spoilage (provided there is not absorption of water from the atmosphere). The surfaces of cakes and bread are also sterile after they leave the oven, but the presence of relatively high levels of water in the crumb present a different situation from that with biscuits and pastries. The moisture content and water activity of bread crust are usually too low to permit mould growth but during storage moisture moves from the moist crumb to the drier crumb zone raising the moisture content and water

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activity of the latter. In unwrapped bread the moisture evaporates to the atmosphere, but for wrapped bread equilibrium is reached between the crumb, crust and atmosphere in the wrapper surrounding the bread. Collectively the changes result in a reduction of the crumb moisture content and an increase in that of the crust, and raise the potential for mould growth. In cake products the equilibration of crust and crumb is even more rapid than that of bread with the result that cake products are susceptible to mould growth if the ERH is high. Extending product shelf life by decreasing moisture (and therefore ERH) is not really an option with bread and cakes because of the strong relationship between moisture content and the consumer perception of freshness as discussed above. In addition, in bread it is known that increased moisture in the baked product contributes to reducing crumb staling (see below). Thus, in most cases the extension of bread and cake shelf life will be viewed as the retention of moisture rather than the limiting of microbial growth. 23.6.2 Adjusting product ERH Since bread and cakes are expected to have relatively high moisture contents, an alternative for contributing greater product stability and longer shelf life is to adjust product ERH. Common means of lowering ERH are through the addition of salts, sugars and polyols. With most bread types the formulation options are limited because the initial ERH is so high and it would be the case that the levels of ingredient addition required to lower ERH and extend mould-free shelf life (mfsl) would significantly change product character. The problems of adjusting bread ERH can be appreciated by considering the relationship between ERH and mould-free shelf life shown in Fig. 23.7. When stored at 21 ëC bread with an ERH of 94% has a suggested mfsl of about 3.5 days. If we were to seek to

Fig. 23.7 Relationship between ERH and mould-free shelf life for bakery products (temperatures are in ëC ± note mould-free shelf life is a logarithmic scale).

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Potential effects of recipe changes to lower bread ERH

Ingredient

Potential for impact on ERH

Technological impact

Product quality impact

Water

Reduction in level will lower ERH

Reduction in recipe levels will lead to reduced processing efficiency

Shape and internal structure defects, drier eating, more rapid staling

Salt

Increase in level will lower ERH

Inhibition of yeast gassing activity

Salty taste

Sugar

Increase will lower ERH

Some inhibition of yeast gassing activity, softer dough which will be more difficult to process

Darker crust colour, sweeter taste, slower staling

Dextrose solids

Increase will lower ERH

Some inhibition of yeast gassing activity

Darker crust colour, slower staling

Polyols

Additions will lower ERH

Inhibition of yeast gassing activity

Slower staling

double that mfsl, then an ERH of 88% would be called for. Some ingredient and recipe options which might be used to achieve such a change are listed in Table 23.2 together with comments on the likely final product characteristics. It will be recognised from the ingredient effects listed in Table 23.2 that the options for adjusting cake ERH are much greater and an example of how recipe changes can affect mfsl is given in Table 23.3. Table 23.3 2008)

Modification of cake mfsl by recipe change (based on Cauvain and Young,

Ingredient Flour Sugar Dextrose Whole, liquid egg Fat Skimmed milk powder Baking powder Salt Water Glycerol Product moisture (%) Product ERH (%) Predicted mfsl at 21 ëC (days)

Standard recipe (weight in g)

Modified recipe (weight in g)

100.0 115.0 0.0 85.0 65.0 8.0 4.0 1.0 50.0 0.0

100.0 105.0 10.0 85.0 65.0 8.0 4.0 2.0 45.0 10.0

22.1 85.5 10

20.9 79.6 31

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ERH not only plays a role in ensuring the microbial stability of bakery products but also plays a major role in controlling the movement of moisture to the atmosphere. In general, the lower the ERH the slower the moisture will be released to the atmosphere by the product. In composite products ERH plays a vital role in controlling the movement of water between components and it is common practice to adjust ERHs to reduce differentials and so limit the driving forces for migration (Cauvain and Young, 2008). 23.6.3 Impacts of preservatives and pH The limited recipe options associated with the extension of the shelf life of bread and to a lesser extent cake means that manufacturers often turn to the use of preservatives as a means of limiting microbial activity. Williams and Pullen (2007) provide a comprehensive listing of the preservatives commonly used with bread and cakes; in general terms propionic acid and its salt and acetic acid and its salts are used with bread while sorbic acid and its salts are used with cake. A particular problem with sorbic acid and its salts is that they have an inhibitory effect on yeast activity and so they cannot be added to the dough without having an adverse effect on dough processing, proving and baking. One advantage of using sorbic acid in cakes is that the effectiveness of the addition is enhanced when the ERH is lowered (Cauvain and Young, 2008). In general, the pH range of bakery products will not significantly limit microbial activity during storage; in part this is because of the buffering potential of flour and some of the other commonly used recipe ingredients. 23.6.4 Impacts of packaging A key function of the packaging of baked products is to control moisture movement to and from the product. In the case of bread and cakes, packaging will be used to limit moisture losses, while with biscuits and cookies it will be used to prevent the absorption of water by the dry product. The movement of water through the packaging will be controlled by the permeability of the material; this is usually expressed as its `moisture vapour transpiration rate' (Cauvain and Young, 2008). In a few cases controlled moisture loss from the product may be used to preserve the initially crisp eating character of the product. One example would be filled short pastry products where the natural movement of water from moist filling to dry pastry softens the eating character of the latter; controlled loss of water helps lengthen the time for which the pastry stays crisp but does lead to progressive shrinkage of the filling. The other example where controlled moisture loss is used is with crusty bread products. In this case the approach is to wrap the product in a perforated film. The small holes in the wrapper allow some of the moisture that migrates from the moist crumb to evaporate from the crust which allows the latter to remain hard and crisp. However, the overall effect of the moisture loss is for the crumb

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to quickly dry out and become hard. The size and spatial distribution of the holes in the packaging can be very important in delivering the required crust retention (Cauvain and Young, 2008, 2009a). 23.6.5 Limiting staling (loss of freshness) in bread Under common storage conditions bread staling which arises because of the intrinsic firming of the crumb cannot be prevented though the rate at which it occurs can be slowed down. The mechanism by which this can be achieved involves changing the rate at which the starch component of the product retrogrades during storage. A reduction in the crumb firming rate can be achieved through the optimisation of moisture levels in the baked product (Zelesnak and Hoseney, 1986). Retention of water within the starch gel will depend on a number of different factors including the retention of water in the product (i.e., restricting moisture losses through the packaging effects) and limiting crust formation to reduce moisture migration from the crumb (Cauvain and Young, 2008). The movement of water at the microscopic level between starch and gluten will have an impact on the rate of firming but this will be difficult to influence given that the two components are in intimate contact in the bread crumb. The most common means of reducing the rate of staling in bread crumb is through the addition of `anti-staling' emulsifiers, such as glycerol monostearate (GMS) (Russell, 1983). This emulsifier is thought to complex with the amylopectin component of starch and to slow down the rate at which it retrogrades during storage (Knightly, 1988). Other emulsifiers (surfactants) can be involved in the reduction of bread staling (Chinachoti, 2003) though some of the mechanisms by which they do this are less clear compared with GMS. This is because commonly used surfactants such as sodium stearoyl lactyate (SSL) and diacetylated tartaric acid ester of mono- and diglycerides of fatty acids (DATA esters or Datem) play a role in improving gas bubble stability in the dough and gas retention (Williams and Pullen, 2007) as well as having the potential for interacting with both or either the starch and the gluten in the dough. It has become increasingly common to reduce staling in bread crumb using suitable enzyme additions. In part this is driven by the desire of bakers to move to `clean ingredient labels' (in Europe, at the time of writing, enzymes are classed as `processing aids' and as such do not need to be included on product labels). Enzyme additions include various forms of intermediate thermal stable alpha-amylases (Si, 1997) and lipases (Leon et al., 2002). In some cases enzymes may be seen as replacements for the addition of emulsifiers (Rittig, 2005). The addition of enzymes delivers the potential for a crumb softening effect by increasing bread volume; for example Cauvain and Chamberlain (1988) showed that to be the case with additions of fungal alpha-amylase. Thus, care should be taken in interpreting data associated with staling studies used to distinguish between the different effects of enzymes. The impact of enzymes may not be exclusively delivered by actions on flour components, e.g. the effect of lipase on added recipe fat.

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It is known that the treatment of bread with alcohol has a significant impact on reducing the rate of bread staling and acts as an anti-microbial agent (Pateras, 2007). The alcohol treatment is applied after baking and immediately before bagging or sprayed into the bag along with the product before sealing. Limiting alcohol losses with effective sealing of the pack and by choosing a suitable moisture vapour transpiration rate are very important. Some products may be double-wrapped to ensure that the alcohol is successfully retained. It has been known for a long time that bread stales at its fastest at temperatures around 4±8 ëC (Cornford et al, 1964) so that bread stored in a refrigerator firms faster than bread stored under ambient conditions. Once bread is held below its glass transition temperature, i.e. frozen, staling ceases. The temperature at which the maximum firming rate occurs depends on the formulation of the product and it is known that the addition of sugars will retard staling (I'Anson et al., 1990; Cairnes et al., 1991). Thus, fermented products such as rolls and buns which contain more sugar than bread have their maximum firming rate at higher temperatures, and in cake products which have even higher sugar levels, the maximum firming rate can be at around 20±25 ëC. While deep freezing will bring bread staling to a halt, the very act of freezing and thawing is the equivalent of 24 h of bread staling (Pence and Standridge, 1955) because the product must pass twice through the temperature of optimum staling, once on cooling and once on thawing.

23.7

Future trends

Loss of freshness (staling) remains a major concern to the manufacturers of bakery products. While much is known about the mechanisms involved, retaining the freshness of bakery products remains a significant challenge. This is because more than one chemical mechanism is involved and several physical factors can also contribute to the changes which occur during product storage. Specific formulation strategies have been evolved for many products which increase their stability and extend their shelf lives. A major problem for the baking industry is that baked products, especially bread, are sensitive to consumer perceptions and retail pressures. This is because baking still largely retains a wholesome, hearth-and-home image and today everyone can bake a loaf of bread if they have an automatic breadmaking machine. This probably means that ingredients lists on bread receive greater scrutiny by consumers and others. Increasingly there is retail and consumer pressure to have on offer `cleanlabel' products. This means that functional ingredients such as preservatives and emulsifiers are no longer seen as `desirable' in the product formulation despite their roles with respect to product stability and safety during storage; neither are `chemical-sounding names' or `E numbers' seen in a favourable light. Alternative ingredients for the baking industry are few. In the case of bread, acetic acid ± vinegar ± has achieved a degree of acceptability not enjoyed by

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calcium propionate but it does not deliver the same impact as an anti-microbial agent. Increasingly the baking industry is turning to enzymes in the pursuit of cleanlabel products. This approach will only be successful as long as enzymes remain processing aids and are not required to be listed on ingredient labels. The primary argument centres around the fact that the enzymes are denatured during baking and as such do not remain in the final product. This argument is weakening, not least because some forms of `anti-staling' enzymes are now being offered which survive the baking process and continue contributing to crumb softening during the post-baking storage. Two other factors will impact on the future usage of anti-staling enzymes. One is the increasing concern with respect to the source of the enzyme. Almost all of the enzymes in modern use, and certainly those used in baked products, are derived from microbial fermentation technology. The competitive nature of the enzyme-producing industry has led to the modification of existing microorganisms to increase yields of ever more sophisticated enzymes with greater specificity in their action. In the pursuit of this goal, genetic modification of micro-organisms has been used and while no genetically modified material is carried through the enzyme concentrate, such approaches may not satisfy bread purists. The other factor is the potential for allergic reactions to enzymes in flour and mixes. Concern centres on the individuals who handle flour and bakery mixes and this will certainly lead to a degree of openness on the presence of enzymes in bread improvers and the like. Once the `genie is out of the bottle' it will be hard to put it back in. The pressure to reduce sodium levels in baked products also offers new challenges for bakers. Attention on salt reduction has largely concentred on the problems facing plant bakers in the preparation and processing of the dough. Salt is a well-known food preservative and while its effects are small in terms of bread stability, if lower salt levels are combined with the reduction/elimination of other preservatives, there is no doubt that the shelf life of bread products will decrease. In cake manufacture salt plays a significant role in lowering product ERH with the benefits of longer mould-free shelf life and reduced water migration in composite products. So what are the `non-chemical' options for the baking industry? The main one will be through improved temperature control during storage and distribution. However, this is not always the most obvious option as illustrated with bread; while storing bread at refrigerated temperatures will extend its mould-free shelf life, it will also increase its rate of staling. This has been a particular problem for the sandwich-industry since the safe storage of such products requires their refrigeration which in turn, quickly leads to firm and inedible bread slices. For the purist bakers the answer put forward is to make and sell bread and other bakery products on a fresh, daily basis. This is not the panacea that it seems since consumer shopping habits in many countries have changed in the last 50 years and a daily trip to the bakery to buy a product which loses its fresh

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appeal within 24±48 hours may not be viewed favourably. Over the centuries bakers have responded to the many challenges placed before them by displaying great ingenuity; there is no reason to suppose that they will not continue to do so.

23.8

References

(1987) Approved Methods of the American Association of Cereal Chemists, AACC, St Paul, MN. BOURNE, M.C. (1978) Texture profile analysis. Food Technology, July, 62±6, 72. CAIRNES, P., MILES, M.J. and MORRIS, V.J. (1991) Studies of the effect of the sugars ribose, xylose and fructose on the retrogradation of wheat starch gels by X-ray diffraction. Carbohydrate Polymers, 16(4), 355±65. CAUVAIN, S.P. (1991) Evaluating the texture of baked products. The South African Journal of Food Science & Nutrition, 3(4), 81±6. CAUVAIN, S.P. (1994) New mixer for variety bread production. European Food Drink Rev., Autumn, 51, 53. CAUVAIN, S.P. (2001) Breadmaking, in (ed G. Owens) Cereal Processing Technology, Woodhead Publishing Ltd, Cambridge, pp. 204±30. CAUVAIN, S.P. (2003a) Breadmaking: an overview, in (ed. S.P. Cauvain) Bread Making: Improving Quality, Woodhead Publishing Ltd, Cambridge, pp. 8±28. CAUVAIN, S.P. (2003b) Nature of cakes, in (eds B. Caballero, L. Trogo and P.M. Finglas) Encyclopaedia of Food Science and Nutrition, 2nd edn, Academic Press, St Louis, MO, pp. 751±6. CAUAVIN, S.P. (2004) Improving the texture of bread, in (ed D. Kilcast) Texture in Food: Volume 2: Solid Foods, Woodhead Publishing Ltd, Cambridge, pp. 432±50. CAUVAIN, S.P. (2007) Breadmaking processes, in (eds S.P. Cauvain and L.S. Young) Technology of Breadmaking, 2nd edn, Springer Science + Business Media LLC, New York, pp. 21±50. CAUVAIN, S.P. and CHAMBERLAIN, N. (1988) The bread improving effect of fungal alphaamylase. Journal of Cereal Science, 8, November, 239±48. CAUVAIN, S.P. and YOUNG, L.S. (2001) Baking Problems Solved, Woodhead Publishing Ltd, Cambridge. CAUVAIN, S.P. and YOUNG, L.S. (2006a) Baked Products: Science, Technology and Practice, Blackwell Publishing, Oxford. CAUVAIN, S.P. and YOUNG, L.S. (2006b) The Chorleywood Bread Process, Woodhead Publishing Ltd, Cambridge. CAUVAIN, S.P. and YOUNG, L.S. (2007) Technology of Breadmaking, 2nd edn, Springer Science + Business Media LLC, New York. CAUVAIN, S.P. and YOUNG, L.S. (2008) Bakery Food Manufacture and Quality: Water Control and Effects, 2nd edn, Wiley-Blackwell, Oxford. CAUVAIN, S.P. and YOUNG, L.S. (2009a) More Baking Problems Solved, Woodhead Publishing Ltd, Cambridge. CAUVAIN, S.P. and YOUNG, L.S. (2009b) The ICC Handbook of Cereals, Flour, Dough & Products Testing: Methods and Applications, DEStech Publications Inc., Lancaster, PA. CHINACHOTI, P. (1998) NMR dynamics properties of water in relation to the thermal AACC

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characteristics of bread, in (ed. D. S. Reid) The Properties of Water in Foods; ISOPOW 6, Blackie Academic & Professional, London, pp. 139±59. CHINACHOTI, P. (2003) Preventing bread staling, in (ed. S.P. Cauvain) Bread Making: Improving Quality, Woodhead Publishing Ltd, Cambridge, pp. 562±74. CORNFORD, S.J., AXFORD, D.W.E. and ELTON, G.A.H. (1964) The elastic modulus of bread crumb in linear compression in relation to staling. Cereal Chemistry, 41, 216±29. D'APPOLONIA, B.L. and MORAD, M.M. (1981) Bread staling. Cereal Chemistry, 36, 236±46. DUNN, J.A. and BAILEY, C.H. (1928) Factors affecting checking in biscuits. Cereal Chemistry, 5, 395±430. I'ANSON, K.J., MILES, M.J. and MORRIS, M.V. (1990) The effects of added sugars on the retrogradation of wheat starch gels. Journal of Cereal Science, 11(3), 243±48. KNIGHTLY, W.H. (1988) Surfactants in baked foods: current practices and future trends. Cereal Foods World, 33, 405±12. LABUZA, T.P. and HYMAN, C.R. (1998) Moisture migration and control in multi-domain foods. Trends in Food Science and Technology, 9, 47±55. LEON, A.E., DRUAN, E. and BENEDITO DE BARBER, C. (2002) Untilization of enzyme mixtures to retard bread crumb staling. Journal of Agricultural and Food Chemistry, 50(6), 1416±19. MARSTON, P.E. (1983) Moisture content and migration in bread incorporating dried fruit. Food Technology Australia, 35, 463±5. PATERAS, M.C. (2007) Bread spoilage and staling, in (eds S.P. Cauvain and L.S. Young) Technology of breadmaking, 2nd edn, Springer Science + Business Media, LLC, New York, pp. 275±98. PENCE, J.W. and STANDRIDGE, N.N. (1955) Effect of storage temperature and freezing on the firming of a commercial bread. Cereal Chemistry, 32, 519±26. RAO, P., NUSSINOVITCH, A. and CHINACHOTI, P. (1992) Effects of surfactants and amylopectin recrystallization and recoverability of bread crumb during storage. Cereal Chemistry, 69, 613±18. RITTIG, F.T. (2005) Lipopan F BG ± unlocking the natural strengthening potential in dough, in (eds S.P. Cauvain, S.E. Salmon and L.S. Young), Using Cereal Science and Technology for the Benefit of Consumers, Woodhead Publishing Ltd, Cambridge, pp. 147±51. RUSSELL, P.L. (1983) A kinetic study of bread staling by differential calorimetry, Starch/ StaÈrke, 35, 277±81. SALEEM, Q., WILDMAN, R.D., HUNTLEY, J.M. and WHITWORTH, M.B. (2005) Modelling biscuit checking using the finite element method, in (eds S.P. Cauvain, S.E. Salmon and L.S. Young) Using Cereal Science and Technology for the Benefit of Consumers, Woodhead Publishing Ltd, Cambridge, pp. 439±44. SCHOCH, T.J. (1945) The fractionation of starch. Advances in Carbohydrate Chemistry, 1, 247±8. SCHOCH, T.J. and FRENCH, D. (1947) Studies on bread staling: 1. Role of starch. Cereal Chemistry, 24, 231±49. SCOTT, W.J. (1957) Water relation of food spoilage microorganisms. Advances in Food Research, 7, 83±127. SI, J.Q. (1997) Synergistic effect of enzymes for bread baking. Cereal Foods World, 41(10) 802±3. STAUFFER, C.E. (2007) Principles of dough formation, in (eds S.P. Cauvain and L.S. Young) Technology of Breadmaking, 2nd edn, Springer Science + Business Media LLC, New York, pp. 299±332.

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and PULLEN, G. (2007) Functional ingredients, in (eds S.P. Cauvain and L.S. Young) Technology of Breadmaking, 2nd edn, Springer Science + Business Media LLC, New York, pp. 51±92. WILHOFT, E.M.A. (1973) Recent developments on the bread staling problem. Bakers' Digest, 47, 14±21. ZELESNAK, K.J. and HOSENEY, R.C. (1986) The role of water in the retrogradation of wheat starch gels and bread crumb. Cereal Chemistry, 63(5), 407±11. WILLAMS, T.

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24 The stability and shelf life of fats and oils G. Talbot, The Fat Consultant, UK

Abstract: The main reactions resulting in rancidity in oils and fats are oxidation and hydrolysis. Oxidation can be sub-divided into three types: autoxidation, photo-oxidation and enzyme-catalysed oxidation. Autoxidation is the most important of these in terms of stability of oils and fats on storage but the mechanisms of all three types are discussed. Hydrolytic or lipolytic rancidity is the breakdown of triglycerides into constituent free fatty acids as a result of a reaction with water (usually in the presence of an active lipase catalyst). The factors affecting the oxidative stability of fats are discussed, these being atmosphere, agitation, temperature, light, shape and structure of storage tanks, materials used in storage tanks, and presence of old oil. The methods used to measure oxidative status of oils (i.e., peroxide value and anisidine value) are discussed as well as methods to evaluate the oxidative stability of the oils in terms of their induction periods. Here, the Rancimat and OSI methods are the most widely used but their development through earlier methods is traced. Finally, ways of optimising the conditions under which fats and oils are kept are proposed and the use of both synthetic and natural antioxidants discussed. Key words: oxidation, autoxidation, hydrolysis, rancidity, storage of fats and oils, peroxide value, anisidine value, Rancimat induction period, Oil Stability Index, pro-oxidants, antioxidants.

24.1

Introduction

There are two main reactions that can take place within oils and fats that result in their degradation to such an extent that their shelf life is compromised. These are oxidation and hydrolysis (also called lipolysis). Collectively, they are often

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termed `rancidity', although some scientists tend to reserve the use of that term more for the oxidation reaction. These breakdown reactions are not just encountered in oils and fats themselves but also in products containing oils and fats. So, for example, savoury snacks that have been fried in oil can suffer from oxidative rancidity just as much as can the oil they were fried in; confectionery coatings that have come into contact with water at some stage during their processing or storage can be affected by hydrolytic rancidity just as much as can the basic fats they contain. This chapter will first consider the mechanisms of the main reactions that result in rancidity in oils and fats. Then, the factors affecting the stability and hence shelf life of oils and fats will be discussed. This will dwell mainly on the oxidative stability of oils and fats as stability towards hydrolysis is more dependent on either processing conditions of fat-containing products or the quality of some of the non-fat components in these products. Later sections of this chapter will focus on methods of measuring the oxidative status of oils and fats and of measuring their likely stability. Finally, ways of ensuring stability and extending shelf life will be discussed. Many composite foods that contain oils and fats are the subjects of other chapters in this book and so, in the main, this chapter will focus on the fats themselves. Nevertheless, there will be occasions when comment will be made about applications in which fats are used. Finally, as far as this introduction is concerned, the terms `oils' and `fats' will be used somewhat interchangeably, although there is a general understanding that oils are usually liquid at ambient temperatures while fats are solid or semi-solid.

24.2

Mechanisms of oxidation and hydrolysis in fats and oils

The mechanisms of oxidation and hydrolysis are completely different as are the breakdown products that result in `rancidity'. As their names suggest, oxidation requires oxygen and hydrolysis requires water for the reactions to proceed. Oxidation can, though, be divided into three main sub-groups: · autoxidation · photo-oxidation · enzyme-catalysed oxidation. To understand better the mechanisms that come into play in the oxidation and hydrolysis reactions, it is necessary to have a grasp of some basic fat chemistry. Chemically fats are made up of a number of different types of molecule but the most common of these is the triacylglycerol or triglyceride. This is a tri-ester of glycerol with each of the three hydroxyl groups on the glycerol molecule being esterified with a fatty acid. Thus, the triglyceride molecule can be represented diagrammatically as shown in Fig. 24.1. The three fatty acid chains linked to the triglyceride molecule can all be the same (monoacid triglyceride), two the same and the third one different (diacid triglyceride) or all three can be

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The stability and shelf life of fats and oils 685

Fig. 24.1 Triglyceride molecule.

different (triacid triglyceride). In terms of both oxidation and hydrolysis it is the types of fatty acids in the triglyceride molecule that are important. Generally speaking, the fatty acids most commonly found in oils and fats can be divided into four main types: · · · ·

saturated cis-monounsaturated cis-polyunsaturated trans.

All of these acids are long chains of carbon atoms linked to each other, the only other atom present in the chain being hydrogen which is also connected to the carbon atoms. Saturated fatty acids contain no double bonds between the carbon atoms on the fatty acid chain so, apart from the end carbon atom which contains three hydrogen atoms (an end methyl group) all the other carbon atoms in the chain contain two hydrogen atoms (i.e., are methylene groups). The other three types of fatty acid all contain one or more double bonds between adjacent pairs of carbon atoms. In the case of monounsaturated fatty acids there is just one carbon±carbon double bond in the chain; in polyunsaturated fatty acids there is more than one carbon±carbon double bond in the chain. In many polyunsaturated fatty acids the double bonds are three carbon atoms apart. This means that two carbon atoms are separated by a double bond, the next carbon atom along the chain is a methylene group, and then there are two more carbon atoms separated by a double bond. This intermediate methylene group is, as we shall see, extremely important in the oxidation reaction. The cis and trans fatty acids differ in the geometry of these double bonds. Each carbon atom can have four bonds or links to other atoms. Where there is a double bond in a chain two of these links are to the next carbon atom thus forming the `double' bond. The remaining two bonds emerge from each carbon atom with an angle of about 120ë between them (see Fig. 24.2). One of these bonds links to the next carbon atom in the chain and the other links to a hydrogen atom. If the link to the rest of the chain on one carbon atom is on the same side of the double bond as the link to the rest of the chain on the second carbon atom, then the double bond is said to be in the cis configuration. If the links to the rest of the chain are on opposite sides of the double bond, then the double bond is said to be in the trans configuration. This can be seen structurally in the two diagrams in Fig. 24.2.

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Fig. 24.2 Cis and trans double bonds.

Saturated fatty acids have a fairly straight chain structure (Fig. 24.3a) whereas whenever there is a cis double bond in the chain there is a bend with an angle of about 120ë (Figs 24.3b and 24.3c). A trans double bond, however does not have this bend and is much closer to the structure of a saturated fatty acid (Fig. 24.3d). The physical properties, particularly the melting properties of fatty acids, are dependent on three main parameters: the chain length or number of carbon atoms in the chain, the degree of unsaturation or how many double bonds there are in the chain, and the nature or geometry of the unsaturation or whether it is in the cis or trans configuration. The longer the chain length, the higher is the melting point of the fatty acid; the greater the degree of unsaturation, the lower the melting point of the fatty acid. However, if that unsaturation is in the trans configuration, then the melting point again increases. The melting points of fatty acids typically found in oils and fats used in food are shown in Table 24.1. A triglyceride is made up of three fatty acid groups and so the melting point of a

Fig. 24.3 Examples of different fatty acid chain structures.

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The stability and shelf life of fats and oils 687 Table 24.1

Melting points of common fatty acids

Chain length: double bonds

Name

10:0 12:0 14:0 16:0 18:0 18:1 18:1 18:2 18:3 20:0

Capric Lauric Myristic Palmitic Stearic Oleic Elaidic Linoleic Linolenic Arachidic

cis trans cis,cis cis,cis,cis

Abbreviation C L M P St O E Li Ln A

Melting point (ëC) 31.6 44.8 54.4 62.9 70.1 16.0 44.0 ÿ6.5 ÿ12.8 76.1

triglyceride is a composite of the melting point of the three acids which it contains. This is not to say that it is a mathematical average of the melting points of its three constituent acids but is very closely related to such an average. A naturally occurring fat is composed of many triglycerides each melting at different temperatures and so, although it is possible to define a temperature at which it is fully molten, natural fats melt over a temperature range (known as its melting profile). 24.2.1 Autoxidation Autoxidation, as its name suggests, is self-starting or self-catalysed. Having said that, there are some factors, pro-oxidants such as heavy metal ions, that accelerate it and other factors, anti-oxidants, that slow it down. Autoxidation produces hydroperoxides and, in doing so, goes through four main stages: initiation, propagation I, propagation II and termination. Once hydroperoxides have been formed they can then break down further into aldehydes and ketones. It is mainly these breakdown products that have the flavours and aromas associated with oxidative rancidity. Fortunately, the first stage of autoxidation, initiation, is usually quite slow because, once the fat gets to the propagation stage, breakdown can occur much more quickly. Because the initiation stage takes a significant period of time to start, this is known as the `induction period' or `induction time'. In the initiation stage an atom of hydrogen breaks off the triglyceride molecule as a free radical leaving what is best termed a triglyceride free radical (see Fig. 24.4). This hydrogen atom can theoretically be any of the many hydrogen atoms on the triglyceride molecule, but it is usually one of the hydrogen atoms on one of the fatty acid chains and, if an unsaturated fatty acid is present then it is often one of the hydrogen atoms on the methylene group next to a carbon±carbon double bond. Free radicals are highly reactive species and so, once these free radicals have been produced, they react very quickly with other species.

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Fig. 24.4 Autoxidation mechanism.

In phase I of propagation, the triglyceride free radical that is formed reacts with a molecule of oxygen to produce a hydroperoxy free radical. This, too, is highly reactive and, in phase II of propagation, it attacks another triglyceride molecule extracting an atom of hydrogen to form a relatively stable hydroperoxide but, in doing so, produces another triglyceride free radical. This can then react with another molecule of oxygen thus propagating the whole oxidation reaction and producing more and more hydroperoxide. Only when two free radicals combine with each other does the final stage of termination take place. Mention has already been made of the methylene groups adjacent to carbon± carbon double bonds. The hydrogen atoms on these methylene groups are very sensitive to removal as free radicals during the initiation stage. Part of an unsaturated fatty acid chain is shown in Fig. 24.5 with the carbon±carbon double bond and the two methylene groups either side of this double bond. During the initiation stage one of the hydrogen atoms on one of these methylene groups is removed giving two possible triglyceride free radical structures (only the fatty acid chain sections are shown in Fig. 24.5). However, once these have been produced it is possible for the position of the double bond and hence the position of the free radicals to move along the fatty acid chain (as shown in the figure). The example given in Fig. 24.5 now shows four possible free radical positions. During the propagation stage these are converted into four possible hydroperoxides. The final stage of autoxidation is the breakdown of these hydroperoxides into aldehydes. The reason for this further breakdown is that the hydroperoxides formed during the propagation stage are themselves unstable and break down further into alkoxy free radicals (Fig. 24.6) by loss of a hydroxyl free radical. This alkoxy free radical can then split into two shorter chains at the point in the chain where the hydroperoxide grouping was. From these two chains an aldehyde can be either produced directly or indirectly via a further reaction with water. Bearing in mind the number of different chain lengths that are possible in fatty

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The stability and shelf life of fats and oils 689

Fig. 24.5 Influence of the methylene groups.

acids, the differing number of double bonds that can be present and the fact that during the propagation stage the peroxy free radical and the position of the double bond can move along the chain, the number of different aldehydes that can be formed during the breakdown of hydroperoxides is potentially very large. These aldehydes have different (rancid) flavour profiles depending on their chain length and their degree of unsaturation. Table 24.2 shows the way in which Hamilton (1994), for example, summarises them.

Fig. 24.6 Formation of aldehydes.

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Table 24.2 Flavours of aliphatic aldehydes (from Hamilton, 1994). Reproduced with kind permission of Springer Science and Business Media No. of carbon atoms C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12

Homologous series Saturated Fresh, pungent Fresh, milky

#

Fresh, green

2-enals

Sweet, pungent Sweet, green

#

#

Fresh, citrus

#

Sweet, fatty, green

#

#

Fatty

2,4-dienals

#

Sweet, fatty

Sweet, oily

#

Oxidation of linoleic acid, for example, can result in saturated aldehydes with chain lengths of 6 to 8 carbon atoms, 2-enals with chain lengths of 9 or 10 carbon atoms and 2,4-dienals with chain lengths also of 9 or 10 carbon atoms. The flavour thresholds of these aldehydes are very low, ranging from 0.02 ppm for trans,cis-2,4-decadienal up to 0.1 ppm for cis-2-decenal in paraffin oil (Forss, 1973) 24.2.2 Photo-oxidation Photo-oxidation can occur in the presence of both light and a photosensitiser. This has a different mechanism from that of autoxidation and exhibits no induction period. Heavy metal ions such as iron and copper are good photosensitisers as are molecules such as chlorophyll (which contains a copper ion), riboflavin and myoglobin. Two types of photo-oxidation have been identified. In Type I photo-oxidation the sensitiser is converted into an excited state in the presence of light: 1

light

Sens ÿ! 1Sens* ÿ! 3Sens*

An Intermediate I is then produced by a reaction between the excited triplet state of the sensitiser and an acceptor substrate: 3

Sens* ‡ X (acceptor) ÿ! [Intermediate I]

The Intermediate I can then react with triplet oxygen (i.e., oxygen in its normal state) to produce the products of oxidation: [Intermediate I] ‡ 3O2 ÿ! 1Sens ‡ XO2 Type II photo-oxidation is based on the direct reaction with singlet oxygen. Oxygen is normally present in the triplet state but in the presence of visible and

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The stability and shelf life of fats and oils 691 ultra-violet light and one of these sensitisers it can be converted into singlet oxygen. This is particularly reactive with the double bonds in an unsaturated fatty acid resulting in a number of different positional hydroperoxides and a shift of the double bond. The first stage of Type II photo-oxidation is the same as that of Type I, i.e. the excitation of the sensitiser molecule. This excited sensitiser can then react with normal triplet oxygen and convert it into singlet oxygen: 3

Sens* ‡ 3O2 ÿ! 1O2* ‡ 1Sens

The singlet oxygen that is formed can then react directly with the double bonds in the fatty acid chains: 1

O2* ‡ RH ÿ! ROOH

So, for example, photo-oxidation of linoleic acid which initially has its double bonds in the 9 and 12 positions can result in (a) a 12-hydroperoxide with double bonds in the 9 and 13 positions, (b) a 13-hydroperoxide with double bonds in the 9 and 11 positions, (c) a 10-hydroperoxide with double bonds in the 8 and 12 positions, and (d) a 9-hydroperoxide with double bonds in the 10 and 12 positions. 24.2.3 Enzyme-catalysed oxidation Many plant and animal tissues contain the enzyme, lipoxygenase, which can catalyse oxidative changes within the seeds. In a commercial sense this is not a problem to food manufacturers and to the shelf life of oils and fats but can be an issue as far as oil and fat processors are concerned. The formation of hydroperoxides within oilseeds such as soyabeans and any subsequent conversion of these into aldehydes means that some of the oil within the seed is oxidised even before it has been extracted. When the oil is expelled or extracted from the seeds the hydroperoxides and their breakdown products are extracted with it. Very few commercial oils and fats are used without refining, the main ones being cocoa butter, olive oil and butterfat, although more `virgin' speciality oils such as virgin rapeseed oil are appearing on the market. Refining of the oil will remove the oxidation products produced by lipoxygenase catalysis in the seeds. There are three main stages in oil refining: (a) neutralisation to remove free fatty acids, (b) bleaching to remove pigments, and (c) deodorisation to remove flavours and odours. Many oxidation products are removed during the bleaching stage when they are adsorbed on to the bleaching earth. The remainder and almost all of the volatile oxidation breakdown products are removed during deodorisation which is a high-temperature vacuum steam distillation process. The newer process of physical refining which removes free fatty acids and pigments by high temperature treatment also removes these oxidation products. Enzyme-catalysed oxidation is, therefore, more of a problem to the oil processor who has to remove these by-products rather than to the food manufacturer who will be generally using a refined oil.

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24.2.4 Hydrolytic (lipolytic) rancidity Hydrolytic or lipolytic rancidity can take two forms. In the first form, keto acids are produced by a reaction between a triglyceride and water in the presence of heat. These keto acids are fairly unstable and lose carbon dioxide to form methyl ketones and hydroxy fatty acids which, in turn, are precursors for formation of

-lactones and -lactones. Depending on their chain length the methyl ketones can have a range of objectionable or, depending on the substrate, acceptable (off-)flavours. The shorter-chain (C3) ketones are pungent and sweet; slightly longer (C7) ketones have a blue cheese note; longer (C11) ketones are fatty and sweet (Hamilton, 1994). In its second form hydrolytic rancidity needs water and an active lipase. The resulting hydrolytic breakdown of the triglyceride molecule releases one, two or three molecules of free fatty acid (Fig. 24.7). As the fatty acid molecules are released the triglyceride is converted first into a diglyceride, then a monoglyceride and, finally, into glycerol. Depending on the chain length of the free fatty acids produced, they have different flavour thresholds above which they are apparent as off-flavours (Table 24.3). Also dependent upon the chain length is the kind of off-flavour that might be produced. Free butyric acid (C4), for example, produces a sweaty, cheesy flavour whereas free lauric acid (C12) gives a soapy flavour. This is a particular problem with palm kernel oil and coconut oil

Fig. 24.7 Hydrolytic breakdown of triglycerides. Table 24.3 Flavour thresholds of saturated fatty acids (from Loders Croklaan, undated) Fatty acid Butyric acid Caproic acid Caprylic acid Capric acid Lauric acid Myristic acid Palmitic acid

Chain length

Flavour threshold (%)

C4 C6 C8 C10 C12 C14 C16

0.00006 0.00025 0.035 0.02 0.07 0.5 1.0

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The stability and shelf life of fats and oils 693 and products which use these oils because both of these oils contain about 50% lauric acid. The very objectionable soapy off-taste which is produced when hydrolysis of these oils occurs is apparent at levels of free lauric acid as low as 0.07%. The best strategies to avoid such hydrolytic breakdown are to either avoid having water present or to avoid any active lipase. In some products the former is not possible because water is an inherent part of the product (in some nondairy analogues, for example). Ensuring the absence of active lipase is a better strategy. Even small amounts of water can produce enough free lauric acid to give a soapy flavour. For example, condensation of water on the surface of a confectionery bar made with a palm kernel oil based cocoa butter substitute as it exits a cooling tunnel at too low a temperature has been known to be enough to give soapiness.

24.3 oils

Factors affecting the stability and shelf life of fats and

If we are to be able to control the stability and shelf life of fats and oils (and, in many cases, the food products that contain them), then it is important to know what the factors are that affect these parameters. Essentially, they fall into three main categories: (i) the chemical composition of the oil, (ii) the conditions under which the oil (and products containing the oil) are kept, and (iii) whether there are any pro-oxidants or antioxidants present. 24.3.1 Chemical composition The main aspects of composition that have an effect on oxidative and hydrolytic stability are the types of fatty acids present as ester linkages to the glycerol backbone of the triglyceride. In terms of hydrolytic stability the main aspect is not so much the effect that different fatty acids have on stability but the effect that they have on the off-flavours produced as a result of hydrolysis. This has already been mentioned in the previous section and is summarised in Table 24.3. As far as oxidative stability is concerned, however, then both the degree and nature of unsaturation are of great importance in defining the stability of the oil. Mention has already been made of the importance of the methylene group adjacent to a carbon±carbon double bond and the susceptibility of the hydrogen atoms on these methylene groups to being abstracted as free radicals. This, in itself, suggests that the more of these methylene groups there are in a fatty acid chain, the more susceptible will be that fatty acid to oxidation and this is, indeed, the case. A saturated fatty acid contains none of these specific methylene groups adjacent to double bonds (but does, of course, contain many methylene groups that are not adjacent to a double bond). A monounsaturated fatty acid will contain two of these susceptible groups, one either side of the double bond. A diunsaturated fatty acid will generally contain three such methylene groups

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Table 24.4 Effect of degree of unsaturation on relative rates of oxidation of C18 fatty acids at 100 ëC (adapted from Sonntag, 1979) Fatty acid

No. of double bonds

Relative rate of oxidation

0 1 2 3

1 10 100 150

Stearic acid Oleic acid Linoleic acid Linolenic acid

(although if the two double bonds are more than three carbon atoms apart there could be four such groups). Similarly, a triunsaturated fatty acid will generally contain four of these types of methylene group. All this would suggest that as the degree of unsaturation of an oil increases so its oxidative stability decreases. The relative rates of oxidation of the C18 series of fatty acids are shown in Table 24.4. These data indicate a tenfold increase in the relative rate of oxidation of these fatty acids as one double bond is introduced into the fatty acid chain ± changing from saturated stearic acid to monounsaturated oleic acid. A further tenfold increase in the relative rate of oxidation is seen as a second double bond is introduced ± changing from monounsaturated oleic acid to diunsaturated linoleic acid. Introducing a third double bond into the chain increases the relative rate of oxidation by a further 50%. These effects have resulted in the concept of `inherent stability' being defined by Erickson and List (1985). The `inherent stability' is defined as the decimal fraction of fatty acids multiplied by the relative rate of reaction with oxygen of each fatty acid. The relative rates of oxidation are those shown in Table 24.4. Using this definition, those oils which have a high degree of unsaturation will have a higher number for `inherent stability' which suggests that a better terminology may be `inherent instability'. Nevertheless, continuing with the term as defined by Erickson and List we can relate the calculated values of this to typical fatty acid contents for a range of common vegetable oils and fats (Table 24.5). As can be seen from this table, those oils with a greater degree of saturation have a lower number for `inherent stability'. In practice, these oils Table 24.5 Relationship between fatty acid content and `inherent stability' as defined by Erickson and List (1985) Oil Soyabean oil Sunflower oil Olive oil Palm oil Palm kernel oil a

Saturates

Monounsaturates

Polyunsaturates

`Inherent stability'a

16.0 11.5 13.0 51.1 81.9

23.5 19.7 79.1 37.8 15.3

60.5 68.6 7.9 10.8 2.4

7.0 6.8 1.5 1.3 0.27

See the text for a comment as to whether a better terminology would be `inherent instability'.

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The stability and shelf life of fats and oils 695 have a greater oxidative stability, hence the comment about the terminology of this parameter. A second aspect of the effect that the nature of the fatty acids present in the oil can have on its oxidative stability is whether the unsaturation is present in the cis or trans configuration. Sonntag (1979) states that `oleic and cis acids oxidise more readily than elaidic acid or trans isomers'. A more quantitative comparison can be made between rapeseed oil and hydrogenated rapeseed oil in which a significant proportion of the cis unsaturated fatty acids have been converted to trans double bonds. Perrin (1996) quotes Rancimat Induction Periods at 98 ëC for rapeseed oil of 17.5 hours; Rossell (1994) quotes Rancimat Induction Periods at 100 ëC for rapeseed oil hydrogenated to a melting point of 36±38 ëC of 207 hours, more than a tenfold increase in stability. The small difference in measurement temperature will have a minimal effect on the comparison of the two results. These relative effects of both nature and degree of unsaturation have become very important in recent years as the view of what kinds of fatty acid are nutritionally beneficial and detrimental have changed. One of the most aggressive processing environments for oils and fats is that of commercial deep-fat frying in which oils are maintained at about 180 ëC for a considerable period of time during which various products are fried in the oil. Typical products are potatoes, fish, chicken, etc. Some of these contain high amounts of water which is to varying degrees evaporated during the frying process. This means that not only are the oxidative stabilities of the fatty acids in the oil important in defining the life of the oil but the high temperature reaction of water with the oil will also result in some hydrolytic breakdown and release of free fatty acids. Traditionally many oils used for frying were based on animal fats (beef tallow and lard, for example). Then, for many reasons (concerns about the level of saturates in these fats together with ethical and religious issues associated with the use of animal fats) they were largely superseded by partially hydrogenated vegetable oils. These had an excellent oxidative stability but often contained up to 50% trans fatty acids. Towards the end of the 1990s there was considerable concern about the health implications of consuming trans fatty acids (Ascherio et al., 1996; Pietinen et al., 1997) and so these have been, in turn, largely replaced by non-hydrogenated vegetable oils. This, though has had a significant effect on the oxidative stability of both the oils and the products fried in the oils which inevitably pick up a proportion of oil during frying. To a large extent the oils used to replace these partially hydrogenated frying oils have been palm oil and palm oleine. While they are not as stable as the partially hydrogenated oils, they have a reasonably good oxidative stability and they contain no trans fatty acids. They do, though, contain a significant level of saturates (typically 40±50%) which is one of the reasons why their oxidative stability is so good. The first decade of the twenty-first century has, however, seen a move to reduce the intake of saturated fatty acids in many countries (Food Standards Agency, 2007) and so, yet again, there have been changes to ideas of what constitutes a `good' frying oil. Some manufacturers have turned to using

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high-oleic sunflower oil, a variety of sunflower oil rich in oleic acid (the traditional variety of sunflower oil is rich in linoleic acid). While this is lower in saturates than palm oleine it also has a lower oxidative stability. All of this has led some scientists to suggest that the best solution is one of compromise and to use a blend of palm oleine and high-oleic sunflower oil such that the palm oleine enhances the stability of the frying oil while the high oleic sunflower oil helps to reduce the level of saturates (Talbot, 2009). Mention has also been made that high temperature frying, particularly of substrates containing a lot of water, results in hydrolysis and the release of free fatty acids. These have a further pro-oxidant effect on the oil. Cold-pressed sunflower oil containing about 1.2% free fatty acid had a Rancimat Induction Period at 110 ëC of 16.6 hours. Addition of further quantities of free fatty acid up to a total level of 4% reduced the Rancimat Induction Period at 110 ëC to about 8 hours (Frega et al., 1999). 24.3.2 Storage conditions Once fats have been refined (or without refining, in the case of fats such as cocoa butter and olive oil) they are packed, transported and stored. The packaging of oils is usually in one of four forms: bulk liquid, smaller, typically, 1 tonne containers, in drums, or in cardboard cartons, usually termed `bag-inbox' because the fat is deposited into a plastic bag within an outer cardboard carton. The risks of oxidative and hydrolytic degradation differ between these different types of packaging. Generally, the shelf life of oils stored in bulk is shorter than that of oils packed in one or other of the specified containers and so optimisation of the storage conditions is very important. Oils packed in the 1 tonne containers or in drums are usually liquid at ambient temperatures (although heating elements can be incorporated into the 1 tonne containers) and so some elements of the factors affecting oxidative stability during storage will be important. Fats deposited into `bag-in-box' packaging will be solid at the storage temperatures and so protection from hydrolysis and odour pick-up become important factors. Clearly, the way that oils and fats are stored is an important factor in terms of defining their oxidative stability. The factors that will be considered in terms of storage effects will apply mainly to the storage of liquid oils although mention will also be made of storage of packed oils and fats. The main factors are: · · · · · · · ·

atmosphere agitation temperature light shape and structure of storage tanks materials used in storage tanks presence of old oil packed fats.

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The stability and shelf life of fats and oils 697 Atmosphere For oxidation to take place there must be oxygen present in the atmosphere around the oil or entrained within the oil. If there is no oxygen present then no oxidation can take place. Generally speaking, when bulk oils are produced they are delivered to the end users in large road tankers or bulk rail containers. As they are being pumped into these delivery tankers a stream of nitrogen can be pumped with them to displace the air in the tanker and provide a blanket of nitrogen in the headspace above the oil. This helps to protect the oil from oxidation during transport. When the oil is then pumped into a land storage tank, some of this nitrogen will be pumped with it and will help to maintain this atmosphere. However, as the oil is used from the tank its volume will be replaced by an atmosphere of some description. If this is simply air then the risk of oxidation will increase, whereas if it is possible to fill the space vacated by the oil with more nitrogen then the stability of the oil will be maintained. When nitrogen is used in this way in either a delivery tank or a bulk land storage tank care needs to be taken in cleaning the tank after use because there will still be a significant amount of nitrogen remaining in the tank and probably insufficient oxygen to sustain life. Breathing apparatus is often needed if personnel need to enter such tanks. Agitation Unless it is absolutely necessary to stir the contents of a land storage tank this should be avoided because of the risk of incorporating air or oxygen into the oil which can then provide the basis for oxidation to occur. Providing the oil is maintained at the correct temperature in the tank (see below) there should not be any occurrence of crystallisation in the oil and therefore nothing to settle out that would need dispersing. However, if there is any concern about the presence of particulate matter that might settle to the bottom, some slow agitation when the oil in the tank is being used may be necessary. In that case, even more care to ensure a nitrogen atmosphere above the oil should be taken. Temperature As a general `rule of thumb' the rate of oxidation of oils doubles for each 10 ëC increase in temperature. It is important, therefore, to ensure that the temperature of oils in storage tanks is no higher than it needs to be. The question then is `what does it need to be?' Ideally, the temperature of an oil stored in a bulk tank should be about 10 ëC above its slip melting point. The slip melting point is the melting temperature that is normally quoted for fats (although in the USA, the Wiley melting point is often used). The slip melting point is normally slightly below the full clear point of the fat and occurs when there is still about 4±5% solid fat present in the fat. Nevertheless, it is a good indicator of the end melting temperature of the fat. The problem that this causes is that if a number of different fats with different melting points are being stored in the same tank farm then, in theory, they should be held at different temperatures. This is often impractical and so, on the basis that most fats used in the food industry are

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molten at body temperature a storage temperature of 45±50 ëC is often recommended. Lower storage temperatures are not recommended (even though the rate of oxidation would be lower) because of the risk of partial crystallisation of higher melting triglycerides in the fat. Loading temperatures of bulk liquid oils into road tankers can be higher than this to allow for some cooling down of the oil during transport. In order to maintain these storage temperatures the tanks need to be heated (and lagged or jacketed) in some way. There are a number of ways in which storage tanks are heated. One way is to use internal coils in the tank containing hot water. This is preferable to using steam coils because of the better temperature control that can be achieved with hot water and because there can be a risk of local overheating when steam coils are used. A second way is to use electrical heating, i.e. thermostatically controlled tapes around the tank. This is more common in smaller tanks. The much smaller 1 tonne storage containers often use electrical heating either to maintain the temperature of the oil or to melt it out from solid before use. Alternatively, if a number of storage tanks are in the same room and need to be kept at the same temperature, then the room itself can be heated to, say, 45 ëC. Clearly, from an energy conservation point of view, it will be necessary to insulate the room very well, but this method completely avoids any problems of localised overheating of the oil. Light The problem of light-promoted photo-oxidation is not one that is normally encountered in storage of bulk oils because these are kept away from light in bulk tanks, drums or boxes. It can, though, be an issue in bottled oils, for example. Berger (1994) quotes some results from Becker and Niederstebruch who held a number of bottled oils in both dark and light conditions and measured a flavour score from a panel of 12 tasters. As well as being kept in the dark or in the light, some bottles were packed with an air atmosphere above the oil and some with a nitrogen atmosphere above the oil. A score above 7 was considered to be good; a score below 5 meant the oil was unpalatable. The scores found with soyabean oil as an example are shown in Table 24.6. Table 24.6 Effect of light and atmosphere on acceptability of bottled soyabean oil (from Becker and Niederstebruch, quoted by Berger, 1994) Atmosphere

Air Air Nitrogen Nitrogen

Light/dark

Dark Light Dark Light

Flavour score Fresh

48 days

7.2 7.2 7.1 7.1

4.5 3.6 5.9 5.1

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The stability and shelf life of fats and oils 699 Shape and structure of storage tanks Storage tanks should have a geometry such that there is as small a surface area/ volume ratio as possible. Many tanks are cylindrical ± as are many road tankers. The geometry of a road tanker is such that this ratio is quite large (but this is inevitable because of the need for such a design for transport). Turning the cylindrical tank of a road tanker on its end, however, gives a better design for a land storage tank because in that configuration the surface area is much smaller. As well as having this kind of geometry, it is important to ensure that drainage from the tank is at its lowest point otherwise old oil will build up at the bottom of the tank. Good and bad designs for storage tanks are shown in Fig. 24.8. As well as ensuring good drainage and a small surface area the inlet pipe to the tank should be curved so that when oil is pumped into the tank it flows against and down the wall rather than splashing directly into the tank. This avoids excessive turbulence and minimises aeration of the oil. A vent is also needed on the tank. This too should be curved as shown in Fig. 24.8 to ensure that no dirt or dust can fall into the tank. The tank should, ideally be totally enclosed ± even the act of simply putting a lid on the tank can help to protect against the build-up of oxidation (Fig. 24.9). Materials used in storage tanks The best material for oil storage tanks is stainless steel. However, mild steel can be used but it should, ideally, have a food grade epoxy resin inner coating to protect the oil against contact with iron. Similarly any contact with copper or its alloys should be avoided. Presence of old oil The main reason to have good drainage in the storage tank is to avoid the presence of old oil when the tank is refilled. If old oil is allowed to accumulate at the bottom of a storage tank then it will also accumulate residues of oxidised oil

Fig. 24.8 Good and bad storage tank designs.

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Fig. 24.9 Effect on oxidation of a lid on a storage tank (adapted from Berger, 1994).

and those components that will immediately begin the propagation phases with any new oil pumped on top without having to wait for the initiation stage to commence. This will radically shorten the life of the oil. Ideally, a tank should be cleaned before any fresh oil is pumped in. However, since cleaning a tank inevitably involves water, this should only be carried out if it is absolutely necessary, for example, if a large build-up of sediment can be seen at the bottom of the tank. It can also be carried out as part of the periodic maintenance performed during a factory shut-down. Any cleaning of the tank should be carried out using hot water only ± no detergents or cleaners. Depending on the state of the tank it may be necessary for an operative to enter the tank. In such a case then clearly clean clothing is a necessity as are rubber-soled boots. Polymerised and oxidised fat residues can be cleaned from the walls and base of the tank using a rubber spade. Any water used to either clean the tank or wash through any residues should be removed directly through the bottom valve and not through any subsequent pipework. Once the tank has been cleaned then it should be thoroughly dried to ensure no residual water comes into contact with the next batch of fresh oil. Although such cleaning is only carried out intermittently it is equally important that fresh oil should not be pumped on top of old oil on a day-to-day or week-to-week basis. This means that there should, ideally, be two storage tanks for each oil ± one in use and the other empty ready to be filled with the next delivery. The storage life of bulk oils is to some extent dependent on the nature of the oil and is usually specified on a product-by-product basis by the oil processor. Generally speaking, however, oils stored under the conditions described above should last for 10±14 days without encountering any oxidative problems. Packed fats The main requirement for packed fats, and this applies more to boxed fats than fats in drums or 1 tonne containers, is to ensure that they are kept on pallets

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The stability and shelf life of fats and oils 701 away from the floor and away from walls. Fats are able to easily pick up foreign odours and so boxed fats should also be stored away from, ideally in a different store from, any materials with strong odours such as mint or citrus flavours. It is even possible for fats to pick up odours from materials that have previously been stored on the same pallet and, from that point of view, it is preferable, if possible, to store boxed fats on fresh pallets. Excessive temperatures and high humidities should also be avoided in the area where packed fats are stored. An area where humidity can be a problem with packed products is with lauric fats (i.e., those based on palm kernel oil or coconut oil). Because of the risk of hydrolysis producing soapy off-flavours with these fats, small amounts of lecithin are often blended with the oil prior to packing. The lecithin acts as a water scavenger and thus inhibits hydrolysis of the fat. 24.3.3 Presence of pro-oxidants and antioxidants Two relatively minor components that can be present in oils and fats can have a major impact on their shelf life and storage stability. These are categorised as pro-oxidants and antioxidants. Pro-oxidants, as their name suggests, can promote or catalyse oxidation; antioxidants, on the other hand, inhibit it. The main pro-oxidants that are found in or have an influence on the stability of oils and fats are heavy metal ions, particularly copper, manganese and iron. This is why it is so important in specifying the materials from which tanks and their associated valves and pipework are constructed to avoid any copper (including brass and bronze) and to coat the inside of mild steel storage tanks with a food-grade epoxy resin. The levels of metal contaminant needed to give the same rate of oxidation in a vegetable oil are shown in Table 24.7. The easiest way to protect against such metal contamination at a low level is to include a metal sequestrant in the oil. The most commonly used sequestrant is citric acid which is usually added at a level of 50 ppm to refined oils and fats during the final stages of refining. Ethylene diamine tetra-acetic acid (EDTA) can also be used in the same way, although current national legislation should be checked before using EDTA as it is not permitted in all countries. Table 24.7 Levels of metal contaminants necessary to give the same rate of oxidation in a vegetable oil (from Loders Croklaan, undated) Metal

ppm

Copper Manganese Iron Chromium Nickel Zinc Aluminium

0.05 0.6 0.6 1.2 2.2 19.6 50.0

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Fig. 24.10 Chemical structure of tocopherols.

Fig. 24.11 Chemical structure of tocotrienols.

The use of added antioxidants will be considered in more detail in Section 24.5.2 but, at this stage it is sufficient to mention only those minor components found naturally in oils and fats that act as antioxidants. These are tocopherols and tocotrienols and have the general chemical structures shown in Figs 24.10 and 24.11. The levels at which they occur in oils and fats vary considerably and they are generally found at higher levels in more unsaturated oils such as soyabean oil and sunflower oil and at lower levels in more saturated oils such as olive oil and coconut oil. Palm oil is slightly anomalous in that (a) it contains a significant level of these natural antioxidants yet is a more saturated oil, and (b) it is the only common vegetable oil to contain high levels of tocotrienols. Typical levels of each of these antioxidants in commonly occurring vegetable oils are shown in Table 24.8.

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The stability and shelf life of fats and oils 703 Table 24.8 Typical tocopherol and tocotrienol levels in common vegetable oils (ppm) (from Gunstone et al., 1986) alphabetagammadeltaalphagammatocopherol tocopherol tocopherol tocopherol tocotrienol tocotrienol Castor Cocoa butter Coconut Corn Cottonseed Groundnut Mustard Olive Palma Rape Safflower Sesame Soyabean Sunflower Wheatgerm a

28 11

29

111 170

134 573 169 75 93 279 70 477 12 116 608 1179

18 40 5

412 317 144 494 7 61 178 44 244 737 11 493

16 6 34 17 398

310 17 2±4 39 10 13 31 7 10 32 275 118

2 20

274

398

trace

Also contains 69 ppm delta-tocotrienol.

24.4

Evaluating the shelf life of fats and oils

It is obviously useful to have some measure of oxidation and oxidative stability in order to be able to estimate the likely shelf life of an oil. Unfortunately, this is not as easy as it sounds. Analytical methods fall into two main categories: those that measure the oxidative status of an oil as it currently is, and those that give an estimate of its likely future stability. Analytical tests that fall in the first category essentially give a snapshot of how much oxidation there is in the oil at the time of measurement. These are the types of test that will be carried out by an oils and fats processor, for example, prior to packing a fat or delivering an oil, and some of them often form part of the specification of the fat. Tests that fall into the second category measure some form of induction period. This is an estimate of how long it will take before the oil begins the initiation process (i.e., the first stage of autoxidation). Ideally, oils should last weeks or months before this takes place and so the analytical tests used are accelerated tests. The means of acceleration is to carry out the test at high temperatures and, often, with air bubbling through the oil. It is not the intention in this chapter to go into the detailed methods of analysis of these parameters ± suggestions are made in Section 24.7 as to where such information may be found. Only the general principles and the reasons for carrying out these tests will be outlined.

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24.4.1 Measurement of oxidative status Peroxide value This is the most commonly used method to measure oxidative status. It essentially measures the level of (hydro) peroxides in the oil. It is usually carried out by measuring the amount of iodine liberated from potassium iodide by the peroxides in the oil. The method has undergone a number of changes and improvements over the years both to replace solvents such as chloroform by more `acceptable' ones and also to try to overcome possible sources of error. For example, there can be some absorption of the liberated iodine by unsaturated double bonds in the carbon chains of the fatty acids before it has been measured. For up-to-date methodology the reader is directed to either the BSI method (BS 684:2.14) or the AOCS method (Cd 8-53). The peroxide value (or PV) is expressed as meq O2/kg oil. Well-refined oils have peroxide values of less than 1.0 meq O2/kg oil and this is the maximum which is usually specified in a freshly-refined oil. However, peroxide values well in excess of this level can be measured without encountering any significant off-flavours. This is because the peroxides and hydroperoxides measured by the test are, in themselves, generally tasteless. They are, though, as we have seen in the discussion on the mechanism of autoxidation, only the precursor of things to come. On the other hand, it is also possible to have a fairly low peroxide value in a highly oxidised and rancid oil because the peroxides have all broken down further into aldehydes, ketones, etc., that give the off-flavours to the product. For this reason, it is important to know something of the history of the oil before interpreting peroxide value measurements. Anisidine value Whereas the peroxide value measures the components produced by the early stages of oxidation, the anisidine value measures the aldehyde and ketonic breakdown products of peroxides. This, then, is the measure of the materials that give the rancidity to oils and fats. 1 gram of fat is reacted with 100 ml of a solution of p-anisidine in iso-octane and the amount of reaction products determined spectrophotometrically at 350 nm in a 10 mm cell. The anisidine value (or AV) is defined as 100 times the absorbance of the solution resulting from this reaction. For an oil to still be acceptable the anisidine value should be less than 10. Considering the autoxidation reaction as a whole and how the resulting components relate to PV and AV, it will be obvious that in the early stages of autoxidation the PV will increase but, as the peroxides break down into aldehydes and ketones, the AV will increase and, eventually, the PV will begin to decrease again. This is why it is so important to know something about the history of the oil before drawing conclusions based on PV alone. Totox value To try to overcome this problem of PV measuring one part of the autoxidation process and AV measuring another part, the concept of the `Totox' (or total

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The stability and shelf life of fats and oils 705 oxidation) value was developed. This is simply an arithmetical combination of PV and AV but, rather than simply adding the two numbers together, the totox value is twice the peroxide value added to the anisidine value. This is because Holm and Ekbom (1972) found that one peroxide value unit decomposed to give two anisidine value units when oils were held at 200 ëC under vacuum. A further justification for this is that there are two oxygen atoms per peroxide molecule but only one oxygen atom per aldehyde molecule (Patterson, 1989). Despite the general consensus that anisidine values should be less than 10, Rossell (1994) describes a more stringent criterion that the totox value of an oil should be less than 10. Other methods The peroxide value, anisidine value and totox value are the most commonly used tests for oxidative status of an oil, but in addition to these are some other tests worth briefly mentioning that are occasionally used. · The thiobarbituric acid (TBA) test is also used to measure the amount of aldehydes present in the oil but, unlike the anisidine value, the test can be carried out on foods without the need to extract the oil. · The Kreis test is a colorimetric test involving the reaction of phloroglucinol with oxidised fat to give a red colour. A Lovibond colorimeter (often used to measure the colours of oils themselves) is used to assess the intensity of the red colour. · Various spectrometric and chromatographic methods for determining the levels of oxidised materials in oils have been developed. Headspace gas chromatography, for example, is particularly useful in analysing the volatile components produced as a result of oxidation but, by and large, these are very specific and non-standard methods. 24.4.2 Measurement of oxidation induction periods Mention has been made of the time taken for the initiation stage of oxidation to take place and that it is fortunate that in many oils and fats this is quite long because the longer it is the more stable is the oil. This is known as the `induction period' and is an indicator of the shelf life of the oil. However, at ambient temperatures and even at the 45 ëC storage temperature of bulk oils, the induction period is very long, too long to measure it as any kind of quality control tool and so accelerated methods have been developed. The ones most commonly used today are the Rancimat and OSI methods but these developed from a series of earlier methods, some of which are still in use. Historical methods One of the earliest of these methods was the Schaal oven test. In this test, the oil is kept in an open dish in an oven at either 63 ëC or 70 ëC for a period of time. Samples are taken daily or weekly for analysis, either by a trained taster or, better, by peroxide value. The PV results are plotted against time and a typical

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Fig. 24.12 Induction period curve.

induction period curve results (Fig. 24.12). This general curve is typical for all the methods which measure induction period including the more modern Rancimat and OSI methods. A different approach is taken in the Sylvester test. In this the sample is placed in a closed vessel held at 100 ëC and continually shaken. The oxygen in the headspace above the oil gets well mixed with the oil and eventually begins to oxidise the oil. As it does so, it gets used up and the pressure inside the vessel falls. Plotting the pressure drop against time also gives a typical induction period curve. This method was further developed in the FIRA-Astell test. The Swift test (also known as the active oxygen method or AOM) operates on a different principle from these earlier tests in that air is bubbled through the oil at 98 ëC. At intervals dependent on the stability of the oil, samples are taken and peroxide values measured. These are then plotted against time to again give an induction period curve. Rancimat induction period To a large extent the Rancimat method is a development of the Swift test in that it also involves bubbling air through a sample of oil at an elevated temperature. It has become very much the industry standard for measuring induction periods and, indeed, Rancimat induction period times have already been referred to earlier in this chapter. The difference between this and the Swift test is that it provides a continuous measurement. There is no necessity to take periodic samples for PV measurements. In the Rancimat equipment, marketed by Metrohm, air is bubbled through the oil and then passes into a container of distilled water. The conductivity of this water is measured and plotted on a chart recorder to also give a typical induction period curve (typical of Fig. 24.12). Some non-oxidised volatiles such as free fatty acid can also carry through on the air stream to the distilled water and cause an increase in conductivity but this is a slight and gradual increase compared with the sharper increase caused by oxidation products.

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The stability and shelf life of fats and oils 707 The induction period is measured from the recorder chart by taking tangents of both the baseline and the sharper slope after the induction period is finished. A line is dropped from where these tangents cross to the time axis to give a measure of the Rancimat Induction Period or RIP. RIP times are generally measured at 100 ëC, 110 ëC or 120 ëC. The higher temperatures are used for more stable oils, the lower ones for less stable oils so that measurements can be completed within a reasonable length of time. The general rule of thumb that says oxidation doubles in rate with every 10 ëC increase in temperature also holds with the Rancimat times. RIP100 (i.e., RIP measured at 100 ëC) times are about 4 times longer than RIP120 times. This gives a great temptation to extrapolate down to 20 ëC to try to estimate shelf lives at ambient temperatures. This is a dangerous thing to do and the temptation to do this should be resisted not least because between 120 ëC and 20 ëC there are differences in the ways in which oils oxidise which affect the extrapolation. OSI method The OSI, or Oil Stability Index, method is very similar to the Rancimat with one of the main differences being that disposable glassware and tubing are used. This overcomes one of the drawbacks of the Rancimat method in that the tubing and glassware used need to be thoroughly cleaned between measurements because any traces of dirt, old oil, etc., can significantly affect the results of the test.

24.5 oils

Ensuring stability and extending the shelf life of fats and

The ways of ensuring stability and extending shelf life of fats and oils are clearly to avoid anything which has an adverse effect on this and to introduce conditions or additives that are beneficial or which will extend their oxidative stability. Essentially these boil down to optimising storage conditions and using antioxidants in the oil. 24.5.1 Optimising storage conditions The factors that affect oxidation and oxidative stability have been discussed in Section 24.3; those that are particularly dependent on storage conditions are considered in Section 24.3.2. Without going through these again in great detail the ways of optimising storage conditions can be summarised as follows: · Atmosphere. If oils are to be stored or transported in bulk liquid form then, ideally, the headspace above the oil should be filled with nitrogen. Oils and fats processors should also be encouraged to give the refined oils a nitrogen sparge at the end of refining and should fill road tankwagons under a nitrogen atmosphere to ensure stability during transport. If it is not possible to store the oil under nitrogen then the tank should be enclosed so that any nitrogen that is

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·

· · ·

· ·

·

Food and beverage stability and shelf life

pumped through from the road tanker into the land tank is contained within the land tank. Agitation. Agitation of the oil during storage should be kept to an absolute minimum and only used if there is a danger of any oil crystallising from the bulk during storage. Providing the storage temperature is correct then this should not happen. Temperature. Bulk oils should be stored at no more than 10 ëC above their melting point. This should be high enough to avoid any crystals forming during storage yet not so high that oxidation proceeds at too fast a rate. Light. Light is not usually a problem in storing bulk oils and boxed fats but can be a problem in bottled oils. Particularly sensitive oils such as unrefined oils (e.g., extra virgin olive oils) should be kept in dark glass bottles. Shape and structure of storage tanks. Storage tanks should be designed to minimise the surface area:volume ratio. They should be enclosed and not open to the atmosphere. The entry point of oils being pumped into the tank should be designed such that oil is directed against the wall of the tank so that it fills down the walls and is not sprayed into the centre of the tank in such a way that it becomes aerated. The outlet from the tank should be at the lowest point to prevent a build-up of old oil. Materials used in storage tanks. Ideally stainless steel should be used, although mild steel with a food-grade epoxy resin coating is also acceptable. Copper and its alloys should be avoided. Presence of old oil. It is not good practice to pump fresh oil on top of old oil. Ideally, this means that for each oil stored there should be two land tanks ± one of which is being used, the other of which is empty and awaiting a delivery of new oil. Packed fats. Boxed fats should be kept in a cool, dry warehouse (ideally below 15 ëC and below a relative humidity of 60%). They should be stored on pallets (ideally new pallets) away from floors and walls.

In addition to these points, the presence of pro-oxidants from sources other than the storage tank materials should be avoided. The introduction of small amounts of citric acid into the oil at the end of refining helps to sequester the kinds of metal ion that can act as a pro-oxidant. If the supplier of oils and fats does not routinely do this then it should be requested. 24.5.2 Use of antioxidants Antioxidants have been briefly referred to in Section 24.3.3 but will be considered in greater detail here. An antioxidant has been defined as `any substance which is capable of delaying, retarding or preventing the development in food of rancidity or other flavour deterioration due to oxidation'. In simple terms antioxidants are molecules that are very reactive with free radicals and so react quickly with the ones that are formed during the initiation phase of autoxidation. Because they react so quickly with these free radicals they effectively remove them and thus prevent them from reacting further with oxygen to produce

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The stability and shelf life of fats and oils 709 hydroperoxides. In doing so, they prolong the induction period. Eventually, though, their activity is used up and oxidation can then proceed as before. Because of this they do not prevent oxidation from ever occurring but delay its onset. They do, though, need to be added to the oil when it has been freshly refined. If they are added later, say partway through the oil's induction period, they will have the effect of extending the induction period and delaying oxidation but the extent of the protection will not be as great as it would have been if they had been added to the fresh oil. They are also not an excuse for poor refining or poor storage of the oils. To obtain the optimum shelf life in an oil where antioxidants are being used, the oil must also have been well refined (with a very low peroxide value and free fatty acid content) and it must be stored in accordance with the recommendations given in Section 24.5.1. We should also be clear about what antioxidants will not do. · They will not improve the flavour and quality of oils where rancidity has already occurred · They will not improve poorly refined and stored oils · They will not prevent hydrolysis (although lecithin which can act as a water scavenger is sometimes added to boxed fats to slow down hydrolysis) · They will not prevent microbial degradation. It goes without saying that they should also be safe to use, give no flavour, odour or colour to the end product, be functional at low concentrations, be easily incorporated into the product, survive high temperature processes (if the oil is being used for baking or frying) and, of course, be cost-effective. Antioxidants are generally divided into two groups: synthetic and natural. The main synthetic antioxidants used in oils and fats are butylated hydroxyanisole (BHA), butylated hydoxytoluene (BHT), tert-butyl hydroquinone (TBHQ) and a range of gallate esters, the most common of which are propyl gallate and dodecyl gallate. The chemical structures of these antioxidants are shown in Fig. 24.13. The characteristics of these antioxidants are summarised in Table 24.9. Two terms in this table are worth clarifying. Carry-through is the ability of antioxidants to survive heat processes and still retain antioxidative properties after these. This is particularly important in fried and baked products in which it is desirable to maintain protection against oxidation in the product after frying or baking. Most of the synthetic antioxidants have these characteristics, the main exception being propyl gallate which breaks down above its melting point of 146±148 ëC, a temperature well below the normal operating temperatures of industrial (and domestic) fryers. Synergism is the ability of two antioxidants to perform better together than either can alone. BHA has a particularly high degree of synergism and performs well in conjunction with both BHT and the gallate esters. Also important in terminology is the improvement given to oxidative stability by the use of antioxidants. This goes under a number of names ± stabilisation factor (F), protection factor (PF), antioxidant activity (AA) ± but all refer to the

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Fig. 24.13 Structures of synthetic antioxidants. Table 24.9 Characteristics of synthetic antioxidants (from Coppen, 1994) BHA

Melting point 50±52 ëC `Carry-through' Very good Synergism With BHT and gallates Solubility in: water 0% animal fat 30±40% vegetable oil 40%

BHT

TBHQ

Gallate esters Propyl gallate

Dodecyl gallate

69±70 ëC Fair±good With BHA

126±129 ëC Good

146±148 ëC Poor With BHA

95±98 ëC Fair±good With BHA

0% 20±30% 20±30%

1% 5±10% 5%

0.35% 1% 1%

0.0001% 1%

same relationship, the induction period of the product with an antioxidant divided by the induction period of the product without the antioxidant. In other words, this factor is the extension of shelf life given by antioxidants. If the F or PF or AA is 2 then the induction period doubles when the antioxidant is used. As consumers are increasingly reacting against additives in general but synthetic additives in particular, the use of natural antioxidants in place of these synthetic additives is becoming more commonplace. The rate at which these are being developed is such that there is now a much wider range of natural antioxidants available than there has ever been of synthetic ones. Traditionally, the main natural antioxidants have been the tocopherols and tocotrienols that are found naturally in many oils and fats, albeit to varying extents (see Table 24.8).

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The stability and shelf life of fats and oils 711 One antioxidant that falls between the scope of synthetic and natural is ascorbyl palmitate. Ascorbic acid (vitamin C) has antioxidative properties but poor solubility in oils and fats. By converting it into the palmitate ester the solubility is marginally improved but it often needs a monoglyceride to be present to help solubilise it. More firmly in the arena of natural antioxidants are a range of herb extracts with rosemary, sage, thyme and oregano being particularly effective. Gerhardt and SchroÈter (1983) compared the stabilisation factor of a number of these herbal extracts at a level of 0.2% in lard at 99 ëC. Rosemary and sage were particularly effective, increasing the stability of lard 17.6 times and 14.2 times, respectively. Rosemary contains a number of different antioxidatively active components: carnosol, carnosic acid, rosmanol, rosmadiol, epirosmanol, isorosmanol, rosmaridiphenol, rosmariquinone and rosmarinic acid. Many of these components are also found in sage extract, perhaps not surprisingly because both herbs are members of the Labiatae family. Carnosic acid, carnosol and rosmarinic acid are thought to be the most active components in sage but more components with antioxidative activity are being isolated (9-ethylrosmanol ether and luteolin-7-O- -glucopyranoside, for example). Also used as antioxidants (and also from the Labiatae family) are extracts of oregano, thyme, summer savory, marjoram and common balm (Yanishlieva et al., 2006). The relatively low levels of tocopherols found naturally in olive oil, for example, have already been commented upon. To some extent this is unusual because oils which need protection are often given this by nature ± for example, the more unsaturated and, therefore, oxidatively unstable oils usually contain higher natural levels of tocopherol. There are, however, other naturally occurring antioxidants in virgin olive oil such as 3,4-dihydroxyphenolethanol (3,4-DHPEA) whose level correlates much better with the stability of the oil as measured by Rancimat than does the level of tocopherols (Baldioli et al., 1996). In addition to what might be called `mainstream' antioxidants, there are many minor components that are found in oils and in other foods that are being increasingly considered to have antioxidant effects. In the main these are considered to be antioxidants in the sense of reducing oxidation and removing free radicals in the body. Many so-called `superfoods' contain such antioxidants. The types of components that fall into this category that are also found at low levels in vegetable oils and fats are phytosterols and phenolic compounds such as flavonoids. Olive oil, for example, is rich in phytosterols some of which protect the oil during frying. It has been found, for example, that vernosterol,
7 -avenosterol and fucosterol prevented the formation of polymerised material during frying when present at a level of 0.2% (Przybylski and Eskin, 2006). The distinction between what might be termed functional antioxidants (i.e., those added to oils to enhance oxidative stability) and metabolic or biological antioxidants (those whose effect is in the body) is becoming more blurred, particularly in how oxidative stability is measured. The Rancimat or OSI methods are still the industry standards for measuring oxidative stability in oils and fats

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Table 24.10 ORAC measurements of natural extracts with antioxidative properties (from www.nutracitrus.com, 2009) Ingredient

ORAC

Vitamin C (ascorbic acid) Olive leaf extract (25% oleuropein) Green tea extract (70% catechin) Red wine extract Pomegranate extract (Nutragranatea) Bilberry extract (25% anthocyanins) Lemon extract (Nutralimona) Onion extract (Nutracepaa) Strawberry extract (Nutrafragariaa)

2460 4780 4900 6800 7057 8900 9096 15000 19000

a

Brand names are from Nutracitrus, Spain.

whereas the method used to determine antioxidative capacity in biological terms is the ORAC (Oxygen Radical Absorbance Capacity) method. Table 24.10 shows the ORAC measurements of a range of natural extracts that are produced and marketed as natural antioxidants. One group of biologically active antioxidants that are being used as more mainstream natural antioxidants in oils are the polyphenols from green tea. These are all members of a group of components known as catechins. The ones that have a high antioxidant activity are gallocatechin (GC), epigallocatechin (EGC), epicatechin (EC) and epigallocatechin gallate (EGCG), collectively known as green tea flavonoids. With such a wide range of active components now available as `natural' antioxidants, how do they compare with each other ± and with the synthetic antioxidants? Making a direct comparison is difficult because their activity and effects are often dependent upon the matrix. Some antioxidants are more effective in animal fats than in vegetable oils, some have a different relative activity in oil-in-water emulsions and in specific food products than they do in a straight oil phase. For example, Gerhardt and SchroÈter (1983) not only compared herb extracts in lard (as described above) but also looked at the same extracts in an oil-in-water emulsion and in mayonnaise. While rosemary and sage were the most effective antioxidants in lard, clove and curcuma were the best in an oil-inwater emulsion and oregano was best in mayonnaise. However, Metrohm (undated) have compiled a table of the antioxidant activity of a range of different active antioxidant components, both natural and synthetic. Data extracted from this are shown in Table 24.11. This shows just how effective some of the natural antioxidants are, particularly those from rosemary and green tea extracts.

24.6

Future trends

Three main trends for the future in terms of stability of oils and fats can be identified. The first concerns the oils themselves. Oils such as soyabean oil have

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The stability and shelf life of fats and oils 713 Table 24.11 Antioxidant activity of different antioxidant components using a lard substrate (from Metrohm, undated) Antioxidant BHA BHT -tocopherol Epigallocatechin gallate Epigallocatechin Epicatechin gallate Epicatechin Gallic acid Carnosol Carnosic acid

Antioxidant activitya 4.49 2.86 6.19 13.40 12.32 7.35 2.46 14.70 9.63 14.23

a

Antioxidant activity is the Rancimat Induction time with the antioxidant divided by the Rancimat Induction time without the antioxidant.

quite a low oxidative stability due to their high degree of unsaturation, particularly the 7±8% of linolenic acid that is present in the oil. In the past, the stability of soyabean oil has been improved by giving the oil a minimal degree of hydrogenation, enough to convert the linolenic acid into the more stable linoleic acid. This was inevitably accompanied by a degree of formation of trans fatty acids that are now unacceptable to the food industry and to consumers. It also meant that the oil had to be declared on ingredients labels as `hydrogenated'. Newer hydrogenation catalysts are being developed that will allow the degree of unsaturation to be changed (i.e., converted from linolenic to linoleic) without the same degree of trans fatty acids being formed. This would then make the oil more acceptable to consumers who do not wish to consume trans fatty acids but the oil would still need to be declared as `hydrogenated'. How acceptable this will be as a strategy depends to some extent on the nationality of the consumer. Consumers in the United Kingdom, for example, have been `educated' by the media and retailers that `hydrogenated fat' is bad for you so it is likely that any oil that has been hydrogenated will be shunned, whether or not it contains any trans fatty acids. Consumers in the United States, on the other hand, seem to be more concerned about whether trans fatty acids are present rather than whether the oil has been hydrogenated or not, thus giving this strategy more of a chance. Along the same lines new varieties of oils such as soyabean oil with lower levels of unsaturation are being developed using genetic modification. The same comment applies ± such oils are more likely to be accepted in the United States than they are in Europe. The second trend that can be identified is that there will be continuing development in oil refining techniques to reduce to even lower levels any components that could compromise the quality of the oils, both when fresh and on storage. Coupled with this, more industrial users of oils are likely to install the infrastructure in terms of tanks, etc., needed to maintain the oil in a good oxidative state for longer.

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The third, and arguably, the most important trend will be in the area of natural antioxidants. Over the past 10±20 years the use of these has grown from a point where the main, often the only, natural antioxidant to be used was a mix of tocopherols to a point now where more and more plant extracts are being studied and commercialised that have antioxidative properties. The herb extracts such as those from rosemary and sage are now quite mainstream; the lipidsoluble components in green tea are becoming so. Other plant sources will be found with even higher antioxidant properties. Spices such as cinnamon, turmeric and ginger, for example, have very high ORAC measurements ± could they also have good antioxidant properties in oils and fats?

24.7

Sources of further information and advice

Further information on methods of measuring oxidative status and oxidation induction periods can be found in the following sources: · American Oil Chemists Society (AOCS) methods of analysis · British Standards Institute (BSI) methods of analysis · Information on measurement of the Rancimat Induction Period can be obtained from Metrohm. Background information on oils and fats is available from a number of sources including The Lipid Handbook, 3rd edn (Gunstone FD, Harwood JL, Dijkstra AJ, CRC Press, 2007, ISBN: 9780849396885). Information on oxidative stability and rancidity in general can be found in Rancidity in Foods, 3rd edn (Allen JC and Hamilton RJ, Blackie Academic and Professional, 1994, ISBN: 9780751402193). Information on antioxidants can be found in Antioxidants in Food: Practical Applications (Pokorny J, Yanishlieva N, Gordon M, Woodhead Publishing Ltd, 2001, ISBN 9781855734630).

24.8

References

et al. (1996). `Dietary fat and risk of coronary heart disease in men: cohort follow-up study in the United States'. British Medical Journal 313, 84±90. BALDIOLI M, SERVILLI M, PERRETTI G, MONTEDORO GF (1996). `Antioxidant activity of tocopherols and phenolic compounds of virgin olive oil'. J. Am. Oil Chem. Soc. 71, 1589±1593. BERGER KG (1994). `Practical measures to minimise rancidity in processing and storage'. Rancidity in Foods. Ed. Allen JC and Hamilton RJ, chapter 4, 70±75. Blackie Academic and Professional, Glasgow. COPPEN PP (1994). `The use of antioxidants'. Rancidity in Foods. Ed. Allen JC and Hamilton RJ, chapter 5, 93. Blackie Academic and Professional, Glasgow. ERICKSON DR, LIST GR (1985). `Storage, handling and stabilization of edible fats and oils'. Bailey's Industrial Oil and Fat Products, Vol. 3. Ed. Applewhite TH, p. 275. John Wiley and Sons. New York. ASCHERIO A, RIMM EB, GIOVANNUCCI EL

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The stability and shelf life of fats and oils 715 (2007). `Draft saturated fat and energy intake programme'. http://www.food.gov.uk/consultations/ukwideconsults/2007/fatenergyprog (accessed 15 December 2009). FORSS DA (1973). `Odor and flavor compounds from lipids'. Prog. Chem. Fats and Other Lipids, 13 177±258. FREGA N, MOZZON M, LERCKER G (1999). `Effects of free fatty acids on oxidative stability of vegetable oil'. J. Amer. Oil Chem. Soc. 76(3), 325±329. È TER A (1983). `Antioxidative Wirkung von Gewu GERHARDT U, SCHRO È rzen'. Gordian 31, 171±172, 174±176. GUNSTONE FD, HARWOOD JL, PADLEY FB (1986). The Lipid Handbook. Chapman and Hall, London. HAMILTON RJ (1994). `The chemistry of rancidity in foods'. Rancidity in Foods. Ed. Allen JC and Hamilton RJ, chapter 1, 1±21. Blackie Academic and Professional, Glasgow. HOLM U, EKBOM K (1972). Proceedings, International Society for Fat Research Congress. Gothenburg, Sweden. LODERS CROKLAAN (undated). Facts About Fats No. 4. Loders Croklaan, Wormerveer, The Netherlands. METROHM (undated). Determination of antioxidant activity by the Rancimat method. Application Bulletin No. 232/1e. Metrohm, Herisau, Switzerland. NUTRACITRUS (2009). Products. http://www.nutracitrus.com/spip.php?rubrique3&lang=en (accessed 15 December 2009). PATTERSON HBW (1989). Handling and Storage of Oils, Fats and Meal. Elsevier Applied Science, London and New York. PERRIN JL (1996). `Determination of Alteration'. Oils and Fats Manual. Vol. 2. Ed. Karleskind A, 1222. Intercept Ltd, Paris. PIETINEN P, ASCHERIO A, KORHONEN P et al. (1997). `Intake of fatty acids and risk of coronary heart disease in a cohort of Finnish men. The Alpha-Tocopherol, Beta Carotene Cancer Prevention Study'. Am. J. Epidemiol. 145, 876±887. PRZYBYLSKI R, ESKIN N (2006). `Minor components and the stability of vegetable oils'. Inform 17(3), 187±189. ROSSELL JB (1994). `Measurement of rancidity'. Rancidity in Foods. Ed. Allen JC and Hamilton RJ, chapter 2. Blackie Academic and Professional, Glasgow. SONNTAG NOV (1979). `Reactions of fats and fatty acids'. Bailey's Industrial Oil and Fat Products. Ed. Swern D. Vol. 1, 4th edn, 138. John Wiley & Sons, New York. TALBOT G (2009). `Frequent frying ± but what's the best oil?' Food Marketing and Technology, Issue 2, 8±11. YANISHLIEVA NV, MARINOVA E, POKORNY J (2006). `Natural antioxidants from herbs and spices'. Eur. J. Lipid Sci. Technol. 108 776±793. FOOD STANDARDS AGENCY

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25 The stability and shelf life of confectionery products P. Subramaniam, Leatherhead Food Research, UK

Abstract: The high level of sugar present in confectionery products makes confectionery products less prone to microbiological spoilage. The shelf stability of these products therefore tends to be based on physical and chemical changes which affect sensory quality. This chapter covers the changes occurring in chocolate products, sugar glass, toffee, gums and jellies and aerated confectionery. Some deterioration related to the changed state of the sugars can be considered as a common problem occurring in most confectionery products, whilst other changes are specific to the product type, relating to the ingredients present and the structure of the product. Key words: sugar and chocolate confectionery, toffee, sugar glass, gums and jellies, aerated confectionery, shelf life. Note: This chapter is a revised and updated version of Chapter 10 `Confectionery products' by P. J. Subramaniam in The Stability and Shelf-life of Food, ed. D. Kilcast and P. Subramaniam, Woodhead Publishing Limited, 2000, ISBN: 978-1-85573-500-2.

25.1

Introduction

Confectionery products, in comparison with other foods, are generally stable and have relatively long shelf lives. The high level of sugar present in confectionery products makes them less prone to microbiological spoilage. Therefore, physical and chemical changes, which lead to a deterioration of flavour, texture, colour or odour of the product, are the main causes of spoilage. However, the shelf life of some confectionery products is shortened by the presence of ingredients that are inherently unstable, e.g. cream, making them prone to microbial spoilage. The

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level and type of microbial spoilage of a food product can be predicted to a large extent by its water activity (aw). Food products with a water activity lower than 0.75 will be stable against microbial spoilage (Groves, 1995) and could be said to be ambient-stable products. Since most confectionery products have a very low water activity, they are able to be stored under ambient conditions.

25.2

Factors affecting shelf life

25.2.1 Product composition The shelf stability of confectionery products, as is the case for all food products, is governed by their composition. Although the high level of sugar in these products imparts significant microbial stability in most cases, microbial spoilage can occur if the products containing ingredients that are prone to microbial spoilage. The presence of other ingredients, such as fats, will make the product prone to chemical and physical changes. Since the presence of sucrose or other sugars is common to all standard confectionery products, some deterioration related to the changed state of the sugars can be considered as a common problem occurring in most confectionery products. The stability of some confectionery products is directly related to the stability of particular ingredients in the products. An example of such ingredients is lactose, which when incorporated into confectionery, can cause the premature crystallization and graining of products such as toffee. There are, of course, many ingredients that are added to confectionery products to increase their stability. Examples of such ingredients include antioxidants to minimize oxidation, humectants to retain moisture, and emulsifiers to reduce separation of water and oil from products. 25.2.2 Product structure Product structure determines the textural attributes of a product. Therefore, a study of the microstructure of a product can help us to understand how the ingredients and processing parameters affect the sensory characteristics of the product and also how these influence product stability. Different textural characteristics can be obtained in a product based on the same recipe by changing the processing conditions to bring about a change in the structure of the products. A simple example of such a change is that of toffee, which changes from being a chewy product to being a product with a very short texture (fudge) through the physical beating of the mix, which causes crystallization of the sugar. Since the toffee product has one phase and the fudge two separate phases (syrup and crystalline), the equilibrium relative humidity (ERH) of the two products are very different. The ERH is related to the concentration of sugars in the syrup phase in the case of fudge. The stability of the products under a standard set of storage conditions will therefore be different. Another example of structural influence on shelf stability can be found in the case of aerated confectionery. Aerated products have a lower density than non-

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aerated products and are often more fragile to handle. Air can become trapped in the porous structure of any aerated product, which can then accelerate oxidative changes (e.g., fat rancidity and oxidation of vitamins) and thereby reduce the shelf life of the product. In the case of very sensitive products, oxidation can be minimized by replacing the air with nitrogen or carbon dioxide during the stage of beating. However, it should also be borne in mind that these gases can also cause some tainting of the products. Nitrogen and carbon dioxide can dissolve in the fat phase, and carbon dioxide is soluble in water, which can then lead to a change in the flavour of the product. Most of the changes in the textural attributes of products during storage, referred to as ageing, are caused by structural changes in the product. The subsequent product-specific sections cover this subject in more detail. 25.2.3 Moisture migration and equilibrium relative humidity The driving force for moisture absorption from the environment by the product or moisture migration within a multi-component product and/or the environment is determined by the differences in the ERH of the individual components and the relative humidity of the environment. ERH is the humidity at which the product neither loses nor gains moisture from the environment. The migration of moisture is essentially a diffusion process but there is also the potential for moisture to migrate as a result of capillary flow if there are holes or cracks within the product (Talbot, 2009). The greater the difference between the ERH of adjacent components, the greater will be the tendency for moisture migration, leading to quality deterioration, particularly textural changes. The ERH, which is related to aw (aw  100 ˆ ERH), of a range of confectionery products is given in Table 25.1. Moisture migration can be minimized by formulating the adjacent components of products to have similar ERH values. However, this may sometimes mean an unacceptable change to the product characteristics. In cases where it may be difficult to change the formulation, moisture migration needs to be reduced by applying a physical barrier, to stop the movement of moisture within the product. Fats and fatty coatings such as chocolate have been used as moisture barriers. The influence of composition of special fat blends on effectiveness as moisture barriers has been studied by Talbot (1991, 1994, 2009). Fats with high solid fat contents were found to be very good moisture barriers. The addition of sugar to these fats improved their performance. Although liquid oils were shown to be ineffective as moisture barriers at ambient conditions, it is possible that they could exhibit moisture-barrier properties at freezer temperatures. The temperature at which barrier fats are applied was found to be critical to their performance. A fat applied at a temperature of 50 ëC was shown to provide a better moisture barrier than when applied at 40 ëC or 20 ëC, which, when combined with rapid cooling, produced imperfections in the barrier, allowing moisture migration. This study also showed that, at solid fat contents of 20±60%, shorter-chain fats (C8±C14) were more effective than long-chain fats.

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Table 25.1 Typical equilibrium relative humidity values for confectionery products (adapted from Lees, 1980) Type of confection Biscuits/wafers Boiled sweets Butterscotch Caramels Gums and pastilles Liquorice paste goods Fudge Nougat (grained) Jellies Marshmallow Fondant centres Plain chocolate Marzipan Coconut ice

Equilibrium relative humidity (%) Less than 30 20±30 Less than 40 45±55 50±65 53±66 60±70 60±70 65±75 65±75 75±80 70±72 68±84 73±76

Based on these findings, commercial speciality fats have been developed to be used as moisture barriers in products. Many of the fats used industrially as moisture barriers have been based on hydrogenated vegetable oils but in recent years hydrogenation has become less acceptable, even the amount of fat in the final product is very low. Therefore non-hydrogenated fats are being developed (Talbot, 2009). Gums have also been used to coat sensitive ingredients against both moisture and fat migration. A common example is the use of gum Arabic solution to coat nuts prior to chocolate panning or adding into multi-component confectionery bars. Edible coatings consisting of various hydrocolloids are also being developed for the same purpose. 25.2.4 Storage conditions The ERH of a product indicates its tendency either to absorb or to lose moisture, depending on the relative humidity (RH) of the environment. The humidity of air in cool temperate climates will range between 45 and 55%, but can be as high as 80% in tropical regions. Products with a higher ERH than the RH of the environment will tend to dry out, but those with a lower ERH than the RH of the environment will absorb moisture during storage. From Table 25.1 it can be seen that products such as fondant and marzipan will have a tendency to dry out, but products at the other extreme, with low ERH values, such as high-boiled sweets (sugar glass) will be prone to moisture pick-up from the environment. Any such changes in the moisture content during the storage will lead to major changes in the sensory quality of the product. The choice of correct packaging is vital to minimize moisture transfer between product and the environment.

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25.2.5 Packaging The use of appropriate packaging is most important in maintaining the quality of the products and achieving the required shelf life. The role of packaging and the factors governing the choice of packaging for any particular product are covered in detail in Chapter 7. The water vapour permeability required for individual confectionery products depends on the ERH of the product. Products such as sugar glass require good barrier properties to minimize moisture pick-up by the products. However, products with high ERH values will tend to sweat if the permeability is too low. The build-up of moisture on the surface in such cases could then lead to mould growth on products. In addition to the considerations relating to the permeability to moisture and oxygen, the requirements relating to pack format and performance on the packing line, such as ability to be twist-wrapped, sealed and printed, are important factors that will influence the choice of packaging materials for products.

25.3

Chocolate and chocolate products

Chocolate is composed of cocoa mass, sugar, cocoa butter, lecithin and, in the case of milk chocolate, milk solids. In certain countries, other vegetable fats may also be permitted. Cocoa butter (CB) is the important fat present in chocolate. Cocoa butter has a unique composition, its fatty acids comprising about 25% palmitic (C16), 36% stearic (C18) and 35% oleic (C18:1), with minor amounts of other fatty acids (Padley and Timms, 1978). The triglyceride composition is simple, being about 12% POP, 43% POS and 35% SOS (where P = palmitic, O = oleic, S = stearic). The triglyceride composition is affected by the origin of the cocoa beans. The percentage of solid fat in a typical CB at different temperatures is shown in Table 25.2. The level of liquid fat present in a product is significant not only in determining the sensory (particularly textural) quality but also in influencing the shelf life of chocolate products. The fast-melting characteristic of CB between 30 ëC and 35 ëC is responsible for the fast meltdown of chocolate in the mouth. A high solid fat content at body temperature would be perceived as an unpleasant waxy mouthfeel. Table 25.2

Solid fat content of cocoa butter

Temperature (ëC) 0 20 25 30 35 40

Solid fat (%) 83 83 76 55 1 0

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Table 25.3 Deteriorative changes and typical shelf lives for chocolate products (adapted from Martin, 2000) Product

Major deteriorative changes

Plain chocolate bar Milk chocolate bar White chocolate bar Milk chocolate-coated peanuts Chocolate bars with raisins Chocolate-coated wafer

Fat bloom, sugar bloom, stale flavour Fat bloom, sugar bloom, stale flavour Fat bloom, sugar bloom, stale flavour Fat bloom, rancidity in peanuts, sugar bloom, stale chocolate Fat bloom, stale chocolate flavour, drying of raisins Staling of wafer, fat bloom, sugar bloom, stale chocolate flavour Fat bloom, sugar bloom, drying out of fondant Sugar bloom, change in caramel texture, fat migration causing fat bloom Fat bloom by fat migration, softening of shell, rancidity of nut paste

Chocolate-coated fondant Chocolate shells with soft caramel centre Chocolate shells with praline centre

Typical shelf life at temperate conditions (months) 24 16 16 12 12 12 18 12 12

The limitation in shelf life of chocolate products can be due to various deteriorative processes. The most common deteriorative change is the development of fat bloom, the causes of which are discussed later in the chapter. Apart from bloom, many other deteriorative changes take place during the storage of chocolate products. These include major changes in the sensory attributes, causing the staling of the product. In the case of solid chocolate, these changes are likely to be induced by the changes in the polymorphic state of CB or by rancidity development (Subramaniam, 2009). However, in the case of enrobed and shell-moulded products, the changes may be driven by migration of moisture and/or fat from the centre component into the chocolate, and viceversa. The typical shelf life for chocolate products, adapted from Martin (2000) is given in Table 25.3. 25.3.1 Fat bloom The polymorphic nature of cocoa butter affects the processing and the shelf stability of chocolate products. It is generally accepted that cocoa butter can exist in six polymorphic forms, although many believe forms V and VI to be identical. The relationship between CB forms and classification according to Xray patterns is shown in Table 25.4, adapted from Wille and Lutton (1966). Forms I to IV are referred to as unstable as they have a tendency to convert to the higher forms V and then VI. Although form V will eventually convert to the higher form, form VI, it is termed stable, as this conversion occurs over a long time (12±18 months) at 20 ëC. During the manufacture of chocolate, a tempering stage is necessary to ensure

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Food and beverage stability and shelf life Table 25.4 Polymorphic forms of cocoa butter (adapted from Wille and Lutton, 1966) Form (DSC)

X-ray pattern

I II III IV V VI

Gamma Alpha Beta-prime Beta-prime Beta Beta

Melting point (ëC) 17.3 23.3 25.5 27.5 33.9 36.3

that all the CB crystallizes in the stable form, which generally is in form V. Tempering to give form V crystallization results in a bloom-stable product, with a high level of gloss and a good snap. However, new tempering processes have been developed that use seeding to temper chocolate, which claim a higher level of bloom-stability. Some new tempering methods are described by Smith (2009). The crystallization of fat on the surface of the chocolate is referred to as fat bloom. During storage of a well-tempered chocolate under standard storage conditions, the polymorphic transformation continues, and form V of CB transforms to form VI. This transformation is commonly accepted as being responsible for bloom in chocolates stored under cool ambient conditions. Some believe that cold storage (lower than 18 ëC) will prevent this polymorphic transformation of form V to VI, keeping the chocolate free of bloom indefinitely (Cebula and Ziegleder, 1993). In addition to this, two other common causes of bloom in chocolate are the melting and re-crystallization of the fat due to storage at high temperatures, and crystallization of fats due to incompatibility of CB with other added fats. In the case of chocolate-coated products, particularly with a nut oil-based filling, the migration of oils from the centre into the chocolate coating during storage makes the coating prone to bloom formation. Incorrect processing, such as inadequate tempering and forced cooling during manufacture, can also cause the cocoa butter in the chocolate to crystallize in an unstable form and cause bloom formation. The progression of bloom on products can be monitored by measuring the surface gloss of products objectively by using a gloss meter or subjectively by comparing the surface with tiles of known levels of light reflectance, since bloom is often preceded by a dulling of the surface. However, in some cases, the product can remain very glossy, but show the presence of bloom crystals. Hence, low-power microscopy is useful in confirming the presence of bloom on the surface of samples. The bloom structures produced can vary with composition and conditions causing bloom (Groves and Subramaniam, 2008). 25.3.2 Sensory changes during storage Although fat bloom is a major problem limiting the shelf life of solid chocolates, sensory changes occurring during storage are also known to be important in

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Table 25.5 Number of weeks to ten-unit change in sensory attributes at different storage temperatures Product

Sensory attribute

Plain chocolate bar

Surface gloss Flavour impact Stale flavour Crumbliness Hardness Surface gloss Marzipan staleness Marzipan mouthfeel Marzipan breakdown rate in mouth Marzipan texture Surface gloss Stale flavour in wafer Stale texture in wafer Breakdown rate of wafer in mouth

Chocolate-coated marzipan

Chocolate-coated wafers

20 ëC

24 ëC

28 ëC

20 ëC/28 ëC cycling every 12 h

26 ± 27 ± 42 28 ± 17 ±

6 ± 8 8 9 8 ± 8 ±

6 4 4 6 10 3 4 3 3

8 4 6 5 4 4 10 4 8

16 28 36 36 ±

8 10 ± 18 13

2 4 2 4 8

5 8 4 8 9

determining their shelf life. In many cases, the sensory changes precede bloom development. Research work carried out at the author's laboratory has studied the sensory changes in a plain chocolate containing only CB as the fat and milk chocolate containing milk powder (Subramaniam et al., 1997). These changes were monitored both at 20 ëC/50% RH and under a set of accelerated storage conditions of 28 ëC/70% RH. Changes in the plain chocolate samples stored under the two conditions were monitored at two-week intervals up to 12 weeks. The samples stored at 20 ëC/50% RH continued to be monitored at two-month intervals up to 12 months. The time taken to produce a ten-unit change in the attributes of the plain chocolate is shown in Table 25.5. The results of the samples stored at 28 ëC/70% RH confirmed that the sensory changes could precede the onset of bloom (which occurred after four weeks). Similarly, the deteriorative changes (flavour and texture) in milk chocolate were found to be accelerated by storing the samples at 28 ëC/70% RH. As in the case of the plain chocolate, sensory changes were noted prior to the bloom development in samples. Samples were found to decrease in smoothness, lose chocolate and caramel flavour, and develop a stale flavour before the appearance of bloom. The shelf life of many commercial chocolate products has also been found to be limited by sensory characteristics. Typical times for unacceptable levels of changes are given in Table 25.6. Nuts incorporated into chocolate are sensitive not only to oxygen but also to moisture pick-up. As they absorb moisture, they develop a soft texture, which causes the product to be perceived as stale. Dried fruit remains fairly stable (two years) when coated with chocolate and does not show significant changes in texture.

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Table 25.6 Typical shelf lives for chocolate products based on sensory changes Product

Deteriorative changes

Time to change at temperate ambient conditions

Plain chocolate

Stale flavour, change in bitterness Stale flavour Softening of nuts, stale chocolate Stale chocolate (dry texture in fruit)

12 months

Milk chocolate bar Milk chocolate-coated peanuts Chocolate bars with dried fruit

12 months 12 months 12 months (24 months)

Loss of chocolate flavour and the development of stale notes in the chocolate component are thought to be related to changes in the crystalline state of the CB. As the CB begins to transform from form V to form VI during storage, it is thought to affect the rate of flavour release from the chocolate. Others relate the development of `cardboard-like' stale flavour to oxidative rancidity (Martin, 2000). The presence of antioxidants in the cocoa liquor is said to reduce the susceptibility of plain and milk chocolate to oxidative rancidity. The lack of these naturally present antioxidants in white chocolate makes it prone to rancidity and very sensitive to light, thus giving a shorter shelf life relative to that of milk and plain chocolates. Further research is required to improve understanding of the causes of flavour changes in chocolate during storage. 25.3.3 Sugar bloom Sugar bloom, or the crystallization of sugar, on the surface of chocolate products is caused by moisture absorption on the surface. Moisture can be caused by condensation of water on the products, poor storage conditions such as high humidity or, in the case of multi-component product, moisture movement within the product. The condensation of water on products can occur during the cooling stage of the chocolate, when the cold surface of the product comes into contact with warm ambient air at the end of the cooler. To prevent this from occurring, the cooled product should always be warmed in a final stage, before leaving the cooler. A product temperature of higher than 13 ëC is said to prevent such condensation on the surface of the chocolate. Chocolate can pick up moisture if stored under high humidity conditions. However, since the ERH of chocolate is about 70%, the humidity of the air needs to be higher than this to cause a pick-up of moisture by the products. 25.3.4 Anti-bloom agents Many different ingredients claim to have anti-bloom properties to improve shelf life, including speciality fats, emulsifiers and other more novel ingredients, such

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as water-soluble fibre (Subramaniam et al., 1999). Butterfat (milkfat) has been traditionally incorporated into chocolate recipes to delay the onset of bloom, but has the negative effect of causing softening of the chocolate. The level of addition is kept below 4% to avoid over-softening of the product (Welch, 1972; Minifie, 1980). High-melting fractions of butterfat are offered as an alternative to overcome the softening (Jebson, 1974; Timms, 1980; Dimick et al., 1993). CBEs (cocoa butter equivalents) can be added to chocolate but only from restricted sources and only where legislation permits (Yates, 2009). Anti-bloom filling fats are also available for delaying the bloom formation on chocolatecoated products. These fats are said to act by migrating with the liquid fat portion from the centre into the coating and stabilizing the fat phase in the chocolate. The effectiveness of some of these commercial fats has been tested, and the anti-bloom effect of anti-bloom fats proven to be significantly greater than that of butterfat (Subramaniam et al., 1999). The incorporation of anti-bloom fats into chocolate did require some modifications to the processing conditions. Since butterfat slows down the rate of crystallization of the CB, the seed temperature reached during tempering needs to be lower than that for the CB-based chocolate. Similarly, the incorporation of some of the commercial anti-bloom fats may require modifications to the tempering conditions to account for a change in the rate of crystallization of the fat. A wide range of emulsifiers has been studied for anti-bloom effect; however, only a small number have proved to be useful. The emulsification properties are not directly related to the anti-bloom property of the emulsifiers. The best surfactants are said to be those that are solid at room temperature, with a high melting point. Sorbitan monostearate (SMS), sorbitan tristearate (STS), ethoxylated sorbitan esters of fatty acids and lactylated mono-diglycerides have been suggested as having anti-bloom properties in chocolate (Garti et al., 1986; Sùndergaard, 1987). Blends of SMS and ethoxylated SMS have been found to be particularly effective in delaying bloom. Lecithin is also claimed by some to delay bloom progression. However, more research is required to study the effectiveness of emulsifiers relative to that of the anti-bloom fats in delaying bloom. The fractionation of CB separates the liquid triglycerides, called oleines, from the solid material, called the stearines. The addition of CB stearines into chocolate is also said to improve the anti-bloom property of chocolate, but only by increasing the hardness of the product (Weyland, 1992). Stearine can be made to be particularly rich (over 90%) in SOS, the highest-melting triglyceride, thus increasing heat resistance. Apart from the obvious considerations of effectiveness and cost relating to the use of different anti-bloom agents, a vital factor to consider is whether the ingredient is permitted in chocolate in the country of use because of changes in legislation. A major advantage of butterfat is that it can be used without restriction. In those countries where vegetable fats are not permitted in chocolate,

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possible options would be to add an anti-bloom fat into the filling of chocolateenrobed products or to coat the inside of the chocolate shell with a barrier fat to reduce fat migration from the filling to the chocolate. Restrictions also apply to the use of emulsifiers in chocolate, which need to be considered. 25.3.5 Moisture migration Moisture pick-up is not a major problem in the case of chocolate bars, but is an issue to consider in chocolate products that contain components that are high in moisture content or which have a tendency to absorb moisture from the atmosphere (e.g., chocolate-coated wafer). The chocolate coating acts as a moisture barrier in enrobed products. Therefore, any imperfections in the coating, such as cracks and pinholes, can allow moisture migration into the centre. Even when the coating is perfect, a certain amount of moisture can move through thin layers of chocolate. The mechanism of migration of moisture from one phase to another within a multicomponent product occurring by a diffusion process is described in detail by Talbot (2009). Moisture migration through the chocolate coating into the centre component during storage can change the structure of the centre and cause stresses in the chocolate layer. An example of this effect is seen in wafers, which expand to the point of cracking the chocolate coating (of thickness 0.065 cm) on absorbing enough moisture to increase the moisture content of the wafer by 1% (Barron, 1973). Increasing the thickness of the chocolate coating will make the product more stable against such stresses caused by the centres. In order to minimize moisture pick-up by the wafer centres, they are conditioned in humiditycontrolled storage rooms, which reduces their tendency to absorb moisture during storage. The opposite, moisture loss through the chocolate coating, is a problem during the storage of chocolate products containing centres with high ERH values. The loss of moisture from centres (such as marshmallow) causes them to shrink away from the coating, making them susceptible to cracking. Improving the quality of coating to reduce pin-holing and increasing the coating thickness can help to improve the shelf life of these products. Moisture migration can also occur within multi-component products, where adjacent layers of components are widely different in ERH. Reformulation of the components to achieve similar ERH values in adjacent layers may be possible in some cases. However, in cases where this is not an option, some form of moisture barrier needs to be applied to reduce moisture movement. Barrier films will need to have low permeability to moisture to minimize moisture migration and fats are the most hydrophobic of common food ingredients and the more likely to be accepted as barrier materials. The properties of different barrier materials based on fats, waxes, proteins and carbohydrates are discussed in detail by Talbot (2009). In many products, chocolate itself is applied to act as a moisture barrier.

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25.3.6 Accelerated storage tests Accelerated storage tests can be used to predict the shelf life of chocolate under normal ambient storage conditions. The procedure for setting up such tests and test regimes is described by Subramaniam (2009). When dealing specifically with chocolate products, it is important that the storage temperature is set below that of the melting point of the chocolate. In general, 24 ëC and 28 ëC are suggested for milk and dark chocolate, respectively to prevent the fat phase from melting and giving rise to changes not usually seen under normal ambient storage conditions. Temperature cycling is said to lead to a faster rate of bloom development than isothermal storage at elevated temperatures. The literature is full of examples where various cycling tests have been used. The tests claim particularly to accelerate the rate of fat migration, owing to the continuous melting and re-crystallization of the fat. However, in the case of solid chocolate products, no advantage is gained by the use of temperature cycling. In fact, plain chocolatecoated wafer and marzipan products were found to bloom faster under isothermal conditions of 28 ëC/70% RH than under temperature cycling between 20 ëC and 28 ëC every 12 h, as can be seen from Table 25.7. The results of the study indicated that a storage time of approximately 4 weeks at 28 ëC/70% RH indicates a bloom-free shelf life of 18±24 months at 20 ëC for plain chocolate. However, this relationship is likely to change depending on the chocolate composition. The recommended accelerated test temperature for milk chocolate is lower (24 ëC) because of the lower melting temperatures. The results of accelerated tests are very useful for estimating the real shelf life of products under normal storage conditions. However, it is important that all results are validated to confirm the relationship between the rate of ageing under accelerated conditions and the rate under normal test conditions.

25.4

Sugar glass

The sugar glass product is perhaps the simplest of all the confectionery products, containing sugars, water, acid, flavour and colouring. The range of products now Table 25.7

Time to bloom development at various storage temperatures

Product

Time to bloom (weeks) 20 ëC/50% RH

Plain chocolate bar Plain chocolate-coated wafer Plain chocolate-coated marzipan

>78 >78 >78

28 ëC/70% RH

20 ëC/28 ëC cycling every 12 h

1±4 1±4 1±4

10 8 6

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varies from the traditional high-sugar products to the newer sugar-free products. The composition is important in determining the characteristics of the sugar glass. 25.4.1 Structure and influence of composition on glass transition High-boiled sweets, often referred to as sugar glasses, are products of very low moisture (typically 1%), formed by cooking sugar solutions to high temperatures. The products have an amorphous glassy structure formed by the cooling of the melt supersaturated with sugars. This gives rise to the hard and brittle texture. The glassy structure can change to a viscous liquid state over a small temperature region close to room temperature. This change is called glass transition and the temperature at which it occurs is referred to as the glass transition temperature (Tg). Such a phase transition is critical to the shelf life of glassy products as it is accompanied by substantial changes in the physical properties of the glass matrix, such as volume, heat capacity and viscosity (Kristott and Jones, 1992), which lead to the promotion of sugar crystallization (graining). The measurement of glass transition temperature can therefore be useful in predicting the relative stability of the sugar glass products against graining, the primary cause of deterioration of these products. Any product stored below its Tg should remain in the glassy state. The influence of moisture content, syrup composition and storage temperature on the rate of graining has been investigated (Lecomber, 1967; Branfield, 1971). The studies found that graining did not occur below a specific moisture content, referred to as the `threshold moisture content', even if initiated. A low threshold moisture content was found to give a high Tg or a higher level of stability against crystallization (Roberts and Randall, 1982). However, the relationship between Tg and graining rate has been found to be complicated, and therefore this relationship is not always valid for products with a wide range of compositions. In the case of products containing a mixture of different sugars, the crystallization behaviour was thought to be related to the type of sugar present in the highest concentration in the products. Nevertheless, moisture content has been shown to have the most dramatic effect on glass transition, as even a marginal increase in moisture can cause a significant decrease in Tg (Levine and Slade, 1986, 1988, 1989; Roos and Karel, 1991a, b, c, d). Other compositional factors affecting Tg include the degree of polymerization and average molecular weight of the ingredients (Kristott and Jones, 1992). The viscosity of the supercooled melts has also been found to be important. Increasing the viscosity of the melt has been found to act against graining. In contrast, the higher the level of supersaturation the greater the risk of graining. 25.4.2 Shelf life improvement The most common changes limiting the shelf life of sugar glasses are stickiness and graining. The high level of hygroscopicity (ERH of 20%) of these products

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causes them to absorb moisture at normal ambient conditions. The increase in moisture content causes the product to become sticky and adhere to the wrapper. Surface moisture dilutes the sugar concentration and lowers the viscosity promoting the crystallization of sucrose and inducing graining. Susceptibility to graining can be reduced by decreasing the level of invert sugar produced during cooking. The use of lower-DE (dextrose equivalent) glucose syrup or maltose syrup can increase the viscosity of the mix and thereby improve the stability against graining (Groves, 1982). Care during the manufacture of the products, retaining a temperature and low humidity in the packing area can also help to improve the shelf life of the products.

25.5

Toffee

There are no clear differences in the definitions of toffee and caramel. However, in Europe, the term toffee is often used to describe a hard-boiled chewy product of low moisture content (typically 7.5%), and the soft-textured and the flowable products with higher moisture and fat contents are referred to as caramels. Fudges have the basic composition of toffees but are grained to give a short texture. 25.5.1 Structure and composition Toffees and caramels are made by blending sucrose, corn syrup, milk ingredient (typically sweetened condensed milk), fat, emulsifier and flavouring. The mix is then homogenized and cooked to a high total solids content. The structure of a toffee is that of fat droplets dispersed in a highly concentrated sugar matrix, in which the milk solids not fat are dispersed. Butterscotch products, which have a very low moisture content of less than 3%, have a glassy sugar matrix, but the caramels used in multi-component bars have been found to have a more syruplike sugar matrix. The flavour and texture characteristics of the products are determined by both the ingredients and the processing parameters used. Heat-induced interaction between the proteins (amino acids) and reducing sugars, referred to as the Maillard reaction, is responsible for the development of the caramel flavour and colour. The rate of this reaction increases with increasing temperature, heating time, and free amine and aldehyde groups. The reaction is promoted by alkaline conditions and, therefore, increasing the pH of the mix as far as possible will increase flavour and colour development. In the case of toffee and caramel products, a value of pH 6 would be adequate to produce a good quality product. The combination of corn syrup with sucrose affects the final level of sweetness, flavour profile and texture. The regular grade of 42 DE syrup is commonly used in toffee. However, other grades are used in special cases. The higher-DE syrups result in softer and darker products, which are more likely to cold flow (lose shape) during storage. The low-DE syrups (less than 42 DE)

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have a higher viscosity and are recommended for the manufacture of toffees for tropical climates as they reduce the tendency to cold flow (Lees, 1976). Highmaltose corn syrups are also recommended for use in products formulated for tropical storage conditions because they are less hygroscopic. However, these have a lower level of sweetness, which has to be compensated for in the formulations. Other syrups showing limited use are high-fructose corn syrup (HFCS) and invert sugar. These affect the colour, viscosity and stickiness of caramels. Fat plays an important role in toffee, acting as a mouth lubricant by reducing stickiness and affecting flavour release. In most toffee systems, the fat is present as droplets of various sizes along with a certain small amount of free fat. The free fat is important in contributing mouthfeel and flavour. The level of emulsification of the fat has an important bearing on flavour in that too much emulsification can lead to a lack of flavour. However, homogenization is also important in determining the level of smoothness achieved in the toffee. Butterfat was the only fat used in the traditional toffee. Although butterfat still makes an important contribution to the flavour in toffee, other fats are used in the recipes to improve storage stability. Traditionally, the most commonly used fat has been hydrogenated palm kernel oil (HPKO) but now a range of special fat blends with different melting points are availble for use in toffee formulations. The ideal fat should melt sharply at a temperature of about 40 ëC (104 ëF). Higher-melting fats are used in toffees intended for tropical climates. 25.5.2 Microstructural changes affecting texture The structure of a toffee is that of fat droplets dispersed in a highly concentrated sugar matrix, in which the milk solids not fat are dispersed. The microstructure of toffee products can vary from a glassy sugar matrix in the case of lowmoisture toffees to a syrup-like matrix in the case of soft caramels (Groves, 2005). The milk component is said to be the most important in toffee manufacture, as it affects not only the flavour and colour but also, most importantly, the texture. A study carried out by Dodson et al. (1984) showed that the two major milk proteins ± casein and whey ± have different functions in toffee. The roles of the milk proteins are shown in the schematic diagrams in Fig. 25.1. The study showed that, during cooking, the whey protein denatures and gradually unfolds and associates to form a membrane around the fat globules. The casein micelles gradually associate with the whey around the membrane, making the membrane more rigid. As the temperature increases, these changes become more rapid, the protein chains interacting with each other to form large molecular weight complexes, which produce a network to give rise to the plastic and elastic properties that give toffee its shape, body and stability against cold flow during storage. During cooking and shearing, the membrane breaks down, causing the fat to coalesce to some extent, which increases the fat globule size in the cooked toffee. The extent of the breakdown of the fat droplets is said to be related to the size of the casein micelles present. The increase in the droplet size

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Fig. 25.1 Schematic diagram of toffee emulsions adapted from Dodson et al. (1984) containing SMP (left), and whey only (right), showing globules (a) before cooking, (b) after cooking, and (c) structure of cooked samples under transmission electron microscope (TEM).

affects the rate of flavour release from the toffee during mastication. A low calcium content in the milk has been found to give rise to small casein micelles and a finer emulsion in the cooked toffee. The use of high levels of whey proteins without the presence of casein was found to give a darker-coloured toffee with a lower viscosity, which lacked body. The products tended to be very unstable during storage as they had a greater tendency to cold flow. Examination of their microstructure showed that a protein (casein) network had not formed to give a firm texture (Dodson et al., 1984). 25.5.3 Shelf life assessment The major deteriorative changes in toffee during storage include loss of shape or distortion (cold flow), rancidity and staleness development, and changes in the

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texture, causing the product either to become soft and sticky or to grain (crystallize), which reduces the chewiness of the sample (Jackson, 1973). Loss of shape can be the result of a high residual moisture content or the use of an unbalanced formulation lacking in milk protein, to produce a structure that will not collapse. The use of a low-DE glucose syrup has been found to improve stability against cold flow (Jackson, 1973). The tendency to cold flow can be predicted to some extent by the glass transition temperature of the product. The glass transition temperature (Tg) is the temperature at which the product changes from a glassy state to a plastic state, where the product will deform and flow. The Tg of a product reduces with an increase in the moisture content. The ERH of a standard toffee with a moisture content of about 7% was measured and found to be approximately 52%. Generally, when the humidity level of the storage environment increases above the ERH value, the product picks up moisture during storage, inducing graining on the surface. The surface therefore becomes soft and sticky and will adhere to the wrapper. Once graining starts, it progresses quickly to the centre of the sweet, giving a shorter texture. Graining is accelerated at high temperatures and delayed at low temperatures. However, low temperatures have the negative effect of increasing stickiness of the product. Stickiness is also promoted by the presence of high levels of invert sugars (more than 4%), but high proportions of milk solids and fat reduce stickiness and give an improved shelf life (Jackson, 1973). Graining can be delayed by increasing the amount of glucose syrup in the formulation (Groves, 1982). Toffee products can also lose moisture from the surface if stored in dry conditions. Toffee samples stored unwrapped at 20 ëC/ 50% ERH have been found to show surface hardening after 1 week. The effect of toffee composition on moisture pick up or loss has been studied to find out if products of similar ERH show the same behaviour during storage (Subramaniam and Tyler, 2007). Toffees of different formulations but with similar ERH (48±50%) stored at 26 ëC/55% RH were found to show some differences in behaviour. The exact cause of the differences could not be pinpointed, but it was clear that the onset of graining (crystallization of sucrose) causes a loss of moisture from the toffee, whilst all toffees showing a continued moisture pick-up during storage remain ungrained. Shelf life assessments on products should be carried out at typical ambient storage conditions using temperature- and humidity-controlled environments. The changes in the sensory characteristics are monitored by the use of a trained profile panel, which will assess changes in attributes such as those given in Table 25.8. The measurement of moisture content and textural changes by an instrumental method will aid in the interpretation of the shelf life data collected by the sensory panel. Instrumental cut tests, such as the incisor test, have been found to be useful in measuring the hardness of toffee samples using a texture analyser. This test mimics biting and involves attaching the samples to a fixed metal blade and then cutting through the sample using a similar blade moving down at a controlled speed until the two blades are 1 mm apart.

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733

Sensory attributes monitored during storage of toffee

Attribute

Definition

Colour Uneven surface Hardness on first bite

Brown shade of toffee Uneven samples have rough surfaces or protrusions Force required to break through sample as assessed on front teeth The degree to which the sample adheres to the tongue and roof of the mouth The feeling of gritty particles in the mouth The texture of the sample is not uniform throughout Overall toffee flavour expected in the fresh sample Level of sweetness Flavour of old toffee variously described as musty, cardboard-like and tasting of packaging Rate at which the sample dissolves

Stickiness Graininess Uneven texture Toffee flavour Sweetness Staleness Meltdown

25.6

Gums and jellies

25.6.1 Physical characteristics and microstructure Gums and jellies can be made to contain a wide range of gelling agents, giving different textural properties to the sweets. The soft jellies tend to have higher moisture content and ERH than gums. Typical texture, moisture content and ERH found for different jelly products are shown in Table 25.9. The sweets are coated with either sugar crystals or special glazing agents in order to protect them from the influences of humidity from the surrounding air, to stop them from sticking together, and to improve their appearance. The presence of a rigid sugar coating also reduces compression damage of products in the case of their being packed tightly in large bulk packs. A complete coating Table 25.9 Texture, moisture content and equilibrium relative humidity of non-sugar coated gums and jellies containing different gelling agents Product

Texture

Pectin jelly Agar jelly Pectin/starch jelly Starch jelly Gelatin gum Gum Arabic gum Starch/gelatin gum

Short, soft Short, rubbery, soft Slightly chewy, soft Chewy, soft Chewy, firm Hard, chewy Chewy, hard

Moisture content (%)

ERH (%) measured at 25 ëC

17.0 18.0 14.5 15.0 15.0 12.5 13.5

67 70 62 60 58 58 60

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of the surface is important in achieving a high level of storage stability against moisture absorption. Very fine caster sugar is normally used for the coating as the coarser sugar sticks poorly to the surface and gives a less attractive appearance. The success of the sugar-coating operation depends on even wetting of the samples. For jelly sweets, the wetting is done by steam, which needs to be controlled so that the surface does not become too wet. If the sweets are too wet, the moisture will transfer to the sugar and cause large lumps to form on the surface. The sweets need to be tumbled in the sugar at a controlled speed so that they do not rest on each other during tumbling, which can lead to uncoated patches on the surface. For very firm sweets, it is also possible to wet them with gum Arabic solution. If the sweets are to be oiled or glazed, a similar method to sugar sanding is used but without the need to pass through the steam or wetting zone. In the case of sweets that require a thicker and denser coating of sugar on the surface, another process is carried out, termed crystal coating or wet crystallization. In this case, the sweets are submerged in a supersaturated sugar solution, to cause the crystallization of sugar on the surface of the sweets. The supersaturated solution is prepared by boiling sugar and water. This leads to the formation of a continuous solid layer of crystals once the sugar solution is drained off. The products that are coated by this process are more stable to humidity changes. The textural characteristics of the gums can be related to the microstructure of the sweets, and therefore the use of a combination of sensory assessment and microscopic examination can be very useful in understanding the changes occurring during product storage. A study carried out by Lewis (1993) related the microstructure of three fruit pastilles to the texture as assessed by a sensory panel. The results showed that sweets made with the same ingredients but by different processes can give rise to very different textures. In this study, all the pastilles were known to contain gelatin and starch, but the products had been made by different manufacturers. Figures 25.2±25.4, adapted from Lewis (1993), show the stereo light micrograph view (a) and schematic diagrams of the structures (b) of the three pastilles. A star diagram of the texture attributes of the pastilles, adapted from Lewis (1993), is shown in Fig. 25.5. The sensory results showed that pastille 1 had a hard initial bite but softened fairly quickly on chewing; pastille 2 had a hard initial bite and continued to be tough during chewing; pastille 3 was found to have a soft initial bite and remained soft during chewing. Examination of the microstructure found that the hardness on first bite corresponded with the level of development of the layer of crystallized sugar on the surface of the sweets. The texture on chewing could also be related to the microstructure of the pastilles. Sample 1 was found to have a more substantial crystal layer than samples 2 and 3. A structure containing a protein (gelatin) continuous matrix with some dispersed starch was found to give pastille 2 the toughness experienced on chewing. The soft texture of pastille 3 was found to be the result of a starch-continuous structure containing inclusions of protein. In the

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Fig. 25.2 Pastille 1 ± appearance under light microscope (a) and schematic diagram of corresponding structure (b).

Fig. 25.3 Pastille 2 ± appearance under light microscope (a) and schematic diagram of corresponding structure (b).

Fig. 25.4 Pastille 3 ± appearance under light microscope (a) and schematic diagram of corresponding structure (b).

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Fig. 25.5 Star diagram of texture attributes of pastilles 1, 2 and 3, adapted from Lewis (1993).

case of pastille 1, the starch appeared to be dispersed in a syrupy matrix and the protein in the form of discrete pockets within the matrix, making it easier to break down during chewing. Microscopy is a useful tool in understanding textural changes and can be used to develop products that have improved storage stability. 25.6.2 Changes during storage The shelf life of gums and jellies can be assessed by storing the products under controlled storage conditions simulating ambient storage and then monitoring the changes in moisture content, ERH and sensory characteristics. Instrumental texture analysis such as that described for toffees has been used successfully to measure changes in the texture. A trained sensory profile panel can be used to characterize the changes relating to product deterioration. Table 25.10 shows some useful attributes that can be monitored during storage. Microscopy has been used to understand the changes occurring in gum and jelly products during storage. The texture of gum products changes during storage, either becoming hard as a surface crust develops on sweets owing to the loss of moisture, or softening as a result of the absorption of moisture under high ambient humidity. The effect of composition on changes in texture during storage has been studied (Eeles et al.,

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Sensory attributes assessed during the storage of fruit gums

Attribute

Definition

Gloss Hardness on first bite Stickiness on first bite Chewy Gelatinous Stickiness

Amount of shine on surface Resistance to bite as assessed on front teeth The degree to which the sample adheres to front teeth Effort required to break down sample Texture of raw jelly The degree to which the sample adheres to the teeth and mouth surfaces during chewing on molars Degree to which sample holds together as a mass Speed at which sample breaks down prior to expectorating Sweet taste of sucrose Level of fruit flavour and type of flavour Old fruit flavours Flavours not associated with fruit gums variously described as cardboard, scented, etc.

Cohesive Breakdown rate Sweetness Fruit flavour Staleness Others

2002). Products (starch gums, gelatine gums, starch/gelatine gums and gum Arabic gums) were subjected to sensory, microscopic and instrumental analysis during storage at 20 ëC and 28 ëC in sealed packaging and at 20 ëC/50% RH and 28 ëC/70% RH over a period of 10 weeks. The results suggested that the effect of moisture content on sensory attributes such as chewiness depended on the recipe. The differences between ERH of the sweet and storage environment provide the driving force for moisture change and all gum formulations were found to dry out during 20 ëC/50% RH storage as predicted from their initial ERH values. Only the starch gums were consistently found to gain moisture in the more humid 28 ëC/70% RH conditions, which seemed to relate to a lower initial ERH. Sensory changes in the softer starch gums were as expected in that these sweets became less chewy and less rubbery at higher levels of moisture. However, the harder textured gum Arabic and gelatin gums behaved differently and became more chewy as the level of moisture increased. The textural differences seemed to relate to the microstructure.

25.7

Aerated confectionery

25.7.1 Composition and structure Aerated confectionery products have air dispersed as small bubbles throughout the matrix, which reduces the density of the products. Density measurement is often used as a means of characterizing the products. Confectionery products such as gums, jellies and boiled sweets have a dense structure and density ranging from 1.3 to 1.5 g/cm3. The density of aerated products can vary greatly.

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Table 25.11 Aerated confectionery classified according to method of aeration Method of aeration

Product

Beating or whipping of air Expansion of small gas bubbles under pressure or vacuum Pulling of mass followed by folding Chemical aeration, e.g. production of gas (CO2) through the decomposition of carbonate

Marshmallow, nougat Chocolate, honeycomb High-boiled sugar, toffee, chews High-boiled sugar

The more delicate of the aerated products, such as marshmallows, have low densities of about 0.2 g/cm3 and firmer-textured products such as nougat will be denser at 1.1 g/cm3. The basic ingredients used in the manufacture of aerated confectionery are the same as those present in other standard products with the exception of the presence of air or some other gas and, in some cases, also a whipping agent. Although classed in the same category, the aerated structures of different confectionery products are created by different methods. Table 25.11 shows categories of confectionery products according to their methods of manufacture. The structure and therefore the physical stability vary depending on the method used to incorporate air or gas into the products. Confectionery foams formed through beating or whipping, such as marshmallow, can be considered as colloidal systems, where gas (air bubbles) is the dispersed phase and the sugar syrup acts as the continuous phase. In these products, a whipping agent (e.g., gelatin or egg albumen) is required to change the properties of the interphase between the air bubble and the liquid (such as surface tension) in order to allow air to be incorporated. The interphase needs to be stable after aeration if the products are to remain stable, without the collapse of the air bubbles that have been created. The presence of fats causes destablilization of foams by lowering the surface tension of the interphase (De Koster and Westerbeek, 1989). Therefore, in the case of products such as nougat, where fat is an ingredient, it needs to be blended slowly at the final stage of processing after aeration. In the case of aerated products formed by pulling, the air becomes trapped between layers of the sugar matrix, giving a denser structure compared with that formed through whipping. Aerated confectionery formed through pulling and through beating can be grained by the addition of icing sugar or fondant to give shorter-textured products. The graining process, which occurs during storage, needs to be controlled to achieve the desired texture in the final products, without the formation of large sugar crystals, which reduce acceptability and shelf life. 25.7.2 Deteriorative changes during storage Aeration allows a means of creating novel and interesting textures. Air is a cheap ingredient, but can be effectively used to increase product volume and

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The stability and shelf life of confectionery products Table 25.12 Product Marshmallow Nougat Pulled sugar Aerated chews

739

Typical shelf lives of aerated products Typical shelf life at temperate conditions (months) 9 10 6 9

thereby give the perception of increased value in products. However, the presence of air in the products can also affect their storage stability. Typical shelf lives at normal ambient conditions are shown in Table 25.12. The incorporation of air can make the product more susceptible to physical damage during handling and storage. The presence of oxygen, together with the increased surface area during aeration, also reduces the shelf life by promoting oxidative changes that affect the flavour of products. This is a particular problem in the case of confectionery products that contain ingredients sensitive to oxygen, such as fats and nuts. In the case of sensitive products, the replacement of air with either nitrogen or carbon dioxide during processing can help to reduce the rate of flavour deterioration and extend shelf life. Common faults limiting the shelf life of confectionery foams include the collapse of air bubbles, drainage of the syrup and shrinkage of the product during storage. Products such as marshmallow have a relatively high moisture content and ERH. The loss of moisture from the foams during storage can cause the air cells to collapse which causes product deterioration. Product shrinkage can occur prematurely, limiting the shelf life, if the aerated structure is not stable. Figure 25.6 shows an aerated jelly product where the presence of starch

Fig. 25.6 Aerated jelly product soon after production (left), and after storage for a few weeks (right), showing premature shrinkage.

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in the product formulation was found to interfere with the air cell interphase, causing the cells to collapse and cause the product to shrink prematurely. Three particular foam destabilization mechanisms (often influenced by each other) have been identified depending on type of product and processing conditions used (De Koster and Westerbeek, 1989). The first is disproportionation (Ostwald ripening), which involves the growth of large bubbles at the expense of loss of small bubbles. This effect can be reduced by tightly controlling the size of the bubbles, making them as large as possible (without affecting mouthfeel characteristics), narrowing the size distribution, using nitrogen gas during whipping and forming a strong hydrocolloid network around the bubbles to stop them from deforming. The second problem is weeping or the drainage of the liquid syrup, due to the difference in the density of the liquid and gaseous phases. This problem can be reduced by increasing the viscosity of the syrup phase, increasing the level of aeration and decreasing the size of the bubbles. The third physical process, coalescence of the bubbles caused by the rupture of the film between the bubbles is said to be as important as the former two processes. Stabilization against coalescence can be achieved by changing the properties of the interphase, eliminating overbeating of the mix and limiting ingredients such as fats that destabilize the interphase.

25.8

Sources of further information and advice

(2009) Industrial Chocolate Manufacture and Use, 4th edn. Oxford Blackwell Science. JACKSON, E.B. (1995) Sugar Confectionery Manufacture, 2nd edn. Glasgow: Blackie. LEES, R. (1980) Faults, Causes and Remedies in Sweet and Chocolate Manufacture. Surbiton: Specialised Publications Ltd. MINIFIE, B.W. (1989) Chocolate, Cocoa and Confectionery: Science and Technology, 3rd edn. New York: Van Nostrand Reinhold. MEINERS, A., KREITEN, K. and JOIKE, H. (1984) Silesia Confeserie Manual No. 3: The New Handbook for the Confectionery Industry, Vol. 2. Neuss: Silesia-Essenzenfabrik Gerhard Hnke KG. TALBOT, G. (2009) Science and Technology of Enrobed and Fillled Chocolate, Confectionery and Bakery Products. Cambridge: Woodhead Publishing Ltd. BECKETT, S.T.

25.9

References

(1973). `The expansion of wafer and its relation to the cracking of chocolate and confectioners' coatings'. Flour Milling and Baking Research Association Report No. 59. BRANFIELD, A.C. (1971). `The stability of high boilings'. British Food Manufacturing Industries Research Association Technical Circular No. 482. CEBULA, D.J. and ZIEGLEDER, G. (1993). `Studies of bloom formation using X-ray diffraction from chocolates after long term storage'. Fette Wissenschaft Technologie, 95 (9), 340±3. BARRON, L.F.

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and WESTERBEEK, J.M.M. (1989). `Prolonging the shelf-life of aerated foods'. Food Technology International Europe, London: Sterling Publications, pp. 159±61. DIMICK, P.S., THOMAS, L.N. and VERSTEEG, C. (1993). `Potential use of fractionated anhydrous milkfat as a bloom inhibitor in dark chocolate'. INFORM, 4, 504. DODSON, A.G., BEECHAM, J., WRIGHT, S.J.C. and LEWIS, D.F. (1984). `Role of milk proteins in toffee manufacture. Part I. Milk powders, condensed milk and whey'. Leatherhead Food Research Association Research Report No. 491. EELES, M.F., GROVES, K.M.H. and MURPHY, O.C. (2002). `Microstructure of confectionery gums and its relationship to shelf life'. Leatherhead Food Research Association Research Report No. 806. GARTI, N., SCHLICHTER, J. and SARIG, S. (1986). `Effect of food emulsifiers on polymorphic transitions of cocoa butter'. J. Am. Oil Chem. Soc., 58 (12), 1058±60. GROVES, K.H.M. (2005). `Microscopy: a tool to study ingredient interactions in foods', in Ingredient Interactions: Effects on Food Quality, 2nd edn. Ed. A. Gaonkar and A. McPherson. New York: Marcel Dekker, pp. 21±48. GROVES, K.H.M. and SUBRAMANIAM, P.J. (2008). `The influence of ingredients on the microstructure of chocolate'. AgroFood industry hi-tech, May/June, 19 (3), 8±10. GROVES, R. (1982). `Shelf-life'. The Manufacturing Confectioner, 10, 53±7. GROVES, R. (1995). `Shelf-life and preservatives'. Candy Industry, 160 (6), 28. JACKSON, E.B. (1973). `The influence of glucose syrup and other carbohydrates on the physical properties and shelf-life of caramels: toffees: fudge'. Confectionery Production, 4, 207. JEBSON, R.S. (1974). `The use of fractions of milkfat in chocolate, XIX', 19th International Dairy Congress, Brussels, Belgium, International Dairy Federation. KRISTOTT, J.U. and JONES, S.A. (1992). `Crystallisation studies of confectionery sugar glasses'. Leatherhead Food Research Association Research Report No. 699. LECOMBER, L.V. (1967). `The laboratory production of high-boiled sweets of known lowmoisture contents and some investigations on their graining'. British Food Manufacturing Industries Research Association Research Report No. 137. LEES, R. (1976). `Manufacture of caramels and toffee'. Confectionery Production, 42 (8), 363±4. LEES, R. (1980). Faults, Causes and Remedies in Sweet and Chocolate Manufacture, Surbiton: Specialised Publications Limited. LEVINE, H. and SLADE, L. (1986). `A polymer physico-chemical approach to the study of commercial starch hydrolysis products (SHPs)'. Carbohydrate Polymers, 6, 213±44. LEVINE, H. and SLADE, L. (1988). `Collapse phenomena ± a unifying concept for interpreting the behaviour of low moisture foods', in Food Structure ± Its Creation and Evaluation, London: Butterworths, pp. 149±80. LEVINE, H. and SLADE, L. (1989). `Influences of the glassy and rubbery states on the thermal, mechanical and structural properties of doughs and baked products', in Dough Rheology and Baked Product Texture: Theory and Practice, Westport, CT: Van Nostrand Reinhold/AVI, pp. 157±330. LEWIS, D.F. (1993). `Development of the food microscopist'. Food Structure, 12 (3), 275±84. MARTIN, A.V. (2000). `Chocolate confectionery', in Man, D. and Jones, A (eds), Shelf-life Evaluation of Foods, 2nd edn. Gaithersburg, MD: Aspen Publishers, pp. 169±81. MINIFIE, B.W. (1980). `Bloom, microbiological and other spoilage problems', Chocolate, Cocoa and Confectionery: Science and Technology, 2nd edn. Westport, CT: AVI Publishing Company Inc., pp. 494±518. DE KOSTER, P.G.

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and TIMMS, R.E. (1978). `Analysis of confectionery fats II. Gas liquid chromatography of triglycerides'. Lebensmittel-Wissenschaft und -Technologie, 11 (6), 319±22. ROBERTS, R.T. and RANDALL, N. (1982). `An investigation of a method to predict the onset of graining in sugar confectionery by pulsed nuclear magnetic resonance'. Leatherhead Food Research Association Research Report No. 395. ROOS, Y. and KAREL, M. (1991a). `Plasticizing effect of water on thermal behaviour and crystallisation of amorphous food models'. J. Fd. Sci., 56 (1), 38±43. ROOS, Y. and KAREL, M. (1991b). `Phase transitions of amorphous sucrose and frozen sucrose solutions'. J. Fd. Sci., 56 (1), 266±7. ROOS, Y. and KAREL, M. (1991c). `Water and molecular weight effects on glass transitions in amorphous carbohydrates and carbohydrate solutions'. J. Fd. Sci., 56 (6), 1676±81. ROOS, Y. and KAREL, M. (1991d). `Phase transitions of mixtures of amorphous polysaccharides and sugars'. Biotechnol. Prog., 7, 49±53. SMITH, K. (2009). `Ingredient preparation: the science of tempering', in Science and Technology of Enrobed and Filled Chocolate, Confectionery and Bakery Products, Ed. G. Talbot, Cambridge: Woodhead Publishing Ltd, pp. 313±43. SéNDERGAARD, C. (1987). `Emulsifiers for stabilising chocolate and related products'. Grinstead Technical Paper TP304-1e, FIE. SUBRAMANIAM, P.J. (2009). `Shelf-life prediction and testing', in Science and Technology of Enrobed and Filled Chocolate, Confectionery and Bakery Products, Ed. G. Talbot, Cambridge: Woodhead Publishing Ltd, pp. 233±54. SUBRAMANIAM, P.J. and TYLER, R. (2007). `Moisture migration ± effect of barriers and compositional effects'. Leatherhead Food Research Association Research Report No. 929. SUBRAMANIAM, P.J., ROBERTS, C.A., KILCAST, D. and JONES, S.A. (1997). `Accelerated shelflife testing of chocolate products'. Leatherhead Food Research Association Research Report No. 738. SUBRAMANIAM, P.J., CURTIS, R.A., SAUNDERS, M.E. and MURPHY, O.C. (1999). `A Study of fat bloom and anti-bloom agents'. Leatherhead Food Research Association Research Report No. 759. TALBOT, G. (1991). `Putting the lid on moisture migration'. Candy Industry, January, 53±6. TALBOT, G. (1994). `Minimisation of moisture migration in food systems'. FIE lecture. TALBOT, G. (2009). `Product design and shelf-life issues: moisture and ethanol migration', in Science and Technology of Enrobed and Filled Chocolate, Confectionery and Bakery Products, Ed. G. Talbot, Cambridge: Woodhead Publishing Ltd, pp. 211±32. TIMMS, R.E. (1980). `The phase behaviour of mixtures of cocoa butter and milkfat'. Lebensmittel-Wissenschaft und -Technologie, 13 (2), 61±5. WELCH, R.C. (1972). `Cocoa and Cocoa Butter', Proceedings of the 26th Annual PMCA Conference, Pennsylvania, PMCA, pp. 41±3. WEYLAND, M. (1992). `Cocoa butter fractions: a novel way of optimising chocolate performance'. The Manufacturing Confectioner, 72 (5), 53±7. WILLE, R.L. and LUTTON, E.S. (1966). `Polymorphism of cocoa butter'. J. Am. Oil. Chem. Soc., 43, 491±6. YATES, P. (2009). `Formulation of chocolate for industrial applications', in Science and Technology of Enrobed and Filled Chocolate, Confectionery and Bakery Products, Ed. G. Talbot, Cambridge: Woodhead Publishing Ltd, pp. 29±52. PADLEY, F.B.

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26 The stability and shelf life of vitaminfortified foods R. Burch, Leatherhead Food Research, UK

Abstract: There are many products on the market which have been fortified with vitamins either to replace those lost during processing or to enable a nutritional claim to be made on the product. Most vitamins degrade to some extent during processing and storage, and many factors such as heat, light and the presence of oxygen may affect their stability. Factors affecting the different vitamins are presented, and ways to reduce degradation over shelf life are discussed. Key words: vitamins, shelf life, stability, analysis.

26.1

Introduction

Vitamin-fortified foods range from products such as breakfast cereals and milk powder to sports drinks and confectionary products. In developing countries staple foods such as flour and oil may be fortified in order to reduce the incidence of vitamin deficiencies caused by the lack of more expensive components of the diet (fish and meat, for example). Consequently there are a large number of factors which must be considered when discussing shelf life of vitamin-fortified products, depending on matrix, packaging and the nature of individual vitamins. Foods may be fortified in order to obtain a product about which a claim may be made, or in some cases vitamins are added back to products to compensate for losses of naturally present vitamins during processing. Table 26.1 shows the recommended daily allowances (RDAs) for vitamins. In all cases, where the level of a vitamin is stated on the packaging,

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Table 26.1 Recommended daily allowances (RDAs) for vitamins Vitamin Vitamin A Vitamin D Vitamin E Vitamin C Thiamin Riboflavin Niacin Vitamin B6 Folacin Vitamin B12 Biotin Pantothenic acid

RDA 800 g 5 g 10 mg 60 mg 1.4 mg 1.6 mg 18 mg 2 mg 200 g 1 g 0.15 mg 6 mg

As specified in Council Directive 90/496/EEC of 24 September 1990 on nutrition labelling for foodstuffs.

that vitamin must be present at that level at the end of its shelf life. All vitamins degrade to a greater or lesser extent during processing and storage, so it may be necessary to add excess vitamin during product manufacture to ensure that the correct level of vitamin is maintained. This procedure needs careful control, in that the addition of excess vitamin incurs added cost, and may also lead to excess consumption since the vitamin content at the beginning of the storage period will be in excess of that stated on the label. For some vitamins, where there are upper maximum recommended limits this may be of concern to particular consumers. For both of these reasons, knowledge of the degradation patterns of vitamins and ways to minimise losses on storage are important for both the food industry and the consumer. A search of the scientific literature reveals little data that could be used to predict the pattern of vitamin degradation in food products. Much of the work on vitamin loss in foods is likely to have been carried out within the food industry, since the information is highly product-dependent. The many factors affecting vitamin degradation mean that each combination of ingredients, processing method, packaging and storage conditions is likely to lead to a different rate of vitamin loss. A study carried out at Leatherhead Food Research on levels of folic acid, vitamin B12, vitamin B5 and biotin demonstrated the different stabilities of different vitamins in different matrices, with their associated differences in packaging and storage conditions. Folic acid in fortified margarine was relatively stable over a six-month storage period, whereas it degraded by as much as 50% in a fortified liquid dietary supplement stored at room temperature. Vitamin B12 was also far more stable in the refrigerated margarine than in the liquid dietary supplement or a confectionary product also stored at room temperature (Wilson, 2006). Experimental studies to determine the kinetics of vitamin loss must therefore be carried out to determine the length of time a product can be stored before its vitamin content drops below the required level.

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26.2 Factors affecting the stability and shelf life of vitaminfortified foods Vitamin degradation occurs in food during processing as well as during storage. Many studies, therefore, have concentrated on losses of vitamins during processing, and fewer studies have been published on losses during storage. The factors to be considered, however, are likely to be the same. Although conditions during processing tend to be more extreme, particularly in the case of higher temperatures, storage will be for longer periods of time. Even a slightly raised temperature will increase the rate of degradation of a heat-labile vitamin, which could lead to significant losses over the storage period. Table 26.2 summarises the factors reported to affect degradation of vitamins during processing and storage. 26.2.1 Vitamin A Vitamin A in the diet comes from two sources: retinol, which comes from animal sources, and carotenoids, the most important of which is -carotene, from plant sources. Both types are sensitive to oxygen, light and acid pH. Isomerisation of retinol under these conditions leads to the formation of isomers that have lower biological activity. Stability of -carotene can be improved by the inclusion of sulphur dioxide in the system, and ascorbic acid has also been shown to have a protective effect, most likely by acting as an antioxidant (Berry Ottaway, 2008). Losses of vitamin A in infant formula have been shown to be up to 21% after 18 months at 25 ëC, increasing to 29% when stored at 40 ëC (Chavez-Servin et al., 2008). Such losses lead to overfortification by manufacturers to compensate for losses during storage ± reported to be by as much as 200% in the case of vitamin A in infant milks (Albala-Hurtado et al., 2000). 26.2.2 Vitamin B1 (Thiamin) There are many factors that cause the degradation of thiamin in foods, including the presence of sulphites and both oxidising and reducing agents. It is particularly susceptible to heat and alkaline conditions. Thiamin stability is reduced by the presence of copper ions (Berry Ottaway, 2008) and Li et al. (2008) showed that thiamin stability was poor in a product also fortified with encapsulated ferrous fumarate, but that different forms of iron fortification did not result in the same losses of thiamin. This demonstrates the necessity of considering the whole range of factors when looking to extend shelf life of vitamin-fortified products. In the case of thiamin, low pH products are better for reduction of degradation, so fruit drinks would be expected to be ideal. However, fruit juices often contain sulphites as preservatives, which accelerate the degradation (Berry Ottaway, 2008). Moisture content has also been shown to affect the stability of thiamin on storage, with higher moisture content leading to a faster rate of loss.

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Table 26.2 Factors affecting vitamin stability during processing and storage Vitamin

Factors affecting stabilitya

Vitamin A and carotenes Vitamin C

Stable in inert atmosphere, losses occur when heated in presence of oxygen. Also light sensitive. Unstable in presence of oxygen. Light, pH and presence of metal ions also factors in degradation. Susceptible to alkaline pH, light and heat. Also adversely affected by acids. Unstable in the presence of oxygen, light, peroxides and strongly oxidative conditions. Relatively stable to heat. Unstable in presence of light, and under alkali conditions. Gradually decomposed by atmospheric oxygen. Unstable at alkaline pH, stability better in acid solutions. Decomposed by both oxidising and reducing agents. Stable to oxidation and heat, sensitive to light. Light sensitivity enhanced at high temperatures and pH values. Stability also affected by other ingredients present. Susceptible to thermal degradation; losses influenced by pH, oxygen content, metal ion concentration, antioxidant levels. Losses reduced in the presence of ascorbic acid. Folate stable in dry products in absence of light and oxygen. Folate sensitive to sunlight, air and light and being heated in acid solutions. Resistant to light, air and heat at pH 5±7. Degraded at low pH. Resistant to heat, air and oxidation, but hydrolysed in solutions at extremes of pH. Resistant to heat, acid and alkaline but sensitive to light in neutral and alkaline solutions. Decomposition catalysed by metal ions. Pyridoxal and pyridoxamine less stable than pyridoxine. Susceptible to oxidising and reducing agents. Stability affected by pH and presence of other vitamins. Stable when heated in presence of light, and in neutral or acidic solutions. Degraded in alkaline solutions.

Vitamin D Vitamin E Vitamin K Thiamin Riboflavin Folates

Pantothenic acid Niacin Vitamin B6

Vitamin B12 Biotin a

Reviewed in Leskova et al. (2006).

26.2.3 Vitamin B2 (Riboflavin) Riboflavin is one of the most stable vitamins, being stable to heat and atmospheric oxygen. However, it is susceptible to reducing agents, unstable at higher pH, and particularly sensitive to light (Berry Ottaway, 2008). During processing and storage riboflavin is stable where other vitamins are often destroyed. However, the presence of oxygen during storage increases the rate of loss, as does the presence of metal sulphates. Higher water activity in low-moisture foods has also been shown to increase loss of riboflavin. Light is the critical factor in riboflavin loss,

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however, with the loss being dependent on light intensity, exposure time and wavelength ± sunlight has a greater effect than fluorescent light, with light at 450 nm being the most destructive (reviewed by Choe et al., 2005). Riboflavin in milk has been shown to be stable to heat treatments during processing, and during subsequent frozen storage in amber bottles (Haddad and Loewenstein, 1983). 26.2.4 Niacin Niacin (nicotinic acid and nicotinamide) is also particularly stable, being resistant to atmospheric oxygen, heat and light (Berry Ottaway, 2008). 26.2.5 Pantothenic acid Free pantothenic acid is unstable, and so the vitamin tends to be sold as calcium or sodium salts, or as the alcohol form (D-pantothenol), which are more stable to oxygen and light if protected from moisture. The compounds are hydrolysed in aqueous solutions at both acid and alkaline pH, but are more stable in the narrow pH range 6 to 7 (Berry Ottaway, 2008). 26.2.6 Folic acid The folic acid used for fortifying foods differs from naturally occurring folates in the number of glutamic acid groups. Commercially available folic acid is relatively stable to heat and oxygen, and in solution at neutral pH but becomes less stable in acid or alkaline media. It is also susceptible to oxidising and reducing agents, and light (Berry Ottaway, 2008). Stability has been demonstrated in a number of matrices under different storage conditions. In a total parenteral nutrition admixture, folic acid was found to be stable for 48 hours independent of temperature (room temperature or refrigeration) or light (Louie and Stennett, 1984). Folate in a fortified orange juice matrix packaged in glass bottles and kept at less than 8 ëC in the absence of light was found to be stable over a 35-day storage period. The same study found that under conditions of household juice consumption (removal of an aliquot from the same package each day, with light and room temperature exposure for 15 minutes each time before replacing in the refrigerator) losses were also low (less than 7%) (Ohrvik and Witthoft, 2008). The stability of folate in this matrix was suggested to be due to the ascorbic acid content having a protective effect. This is in contrast to the folate content in tomato pureÂe (unfortified) which decreased on storage over a 12-month period by as much as 70% regardless of storage temperature (stored at 8, 22 or 37 ëC in the dark) (Iniesta et al., 2009). 26.2.7 Pyridoxine (vitamin B6) Three compounds are grouped together as pyridoxine: pyridoxol, pyridoxal and pyridoxamine. The vitamin is normally stable to oxygen and heat, but sensitive to light, and decomposes more rapidly in the presence of metal ions (Berry Ottaway, 2008).

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26.2.8 Vitamin B12 Vitamin B12 consists of a number of different compounds with similar structure, cobalamin being the main one. It is degraded by oxidising and reducing compounds, and in alkaline solutions and strong acids and is light sensitive (Berry Ottaway, 2008). A study of B12 in nutritional supplements suggested that light sensitivity is apparent even in amber bottles stored at 4 ëC in the light. Additionally, presence of sugars, iron and particularly vitamin C accelerated the loss of B12 in liquid dietary supplements (Yamada et al., 2008). 26.2.9 Biotin Biotin is relatively stable to oxygen and daylight, although degraded by UV light and if heated in strongly acid or alkaline solutions (Berry Ottaway, 2008). 26.2.10 Vitamin C Vitamin C is one of the vitamins most affected by heat; heat treatment during processing of milk causes significant losses, increasing with increasing temperature (Haddad and Loewenstein, 1983). Storage temperature also has an effect ± storage of infant formula fortified with vitamin C lost 20±34% vitamin C after 18 months at 25 ëC, compared with 28±49% losses at 40 ëC over the same period (Chavez-Servin et al., 2008). Ascorbic acid oxidises reversibly to dehydroascorbic acid, which then oxidises irreversibly to diketoglutonic, oxalic and threonic acids. Major factors influencing the stability of vitamin C added as a fortificant include temperature, the form of the vitamin and the food matrix itself. Higher temperatures increase rate of degradation, as does the presence of oxygen or metal ions. Higher moisture content (e.g. of bread) reduces vitamin C retention on storage, and comparison of liquid matrices shows that pH has an effect, with greater retention of ascorbic acid in acidic drinks than milk. Different forms of the vitamin degrade at different rates; phosphate derivatives are more stable than ascorbic acid alone and encapsulation of the vitamin aids retention (Steskova et al., 2006). 26.2.11 Vitamin D Dietary vitamin D occurs in two forms: ergocalciferol (D2) and cholecalciferol (D3). Both forms are sensitive to light and acidic conditions, and degrade in the presence of oxygen, although there is some debate on the importance of different factors. It has been shown that cheese fortified with vitamin D in either waterdispersible or oil-soluble forms was stable over a 9-month period when stored at room temperature or refrigerated to 4±6 ëC (Upreti et al., 2002). Similarly in another study with fortified Cheddar cheese and low-fat cheese, vitamin D3 was stable for one year of refrigerated storage (Wagner et al., 2008), suggesting that cheese is a possible vehicle for supplementation of the diet with vitamin D.

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26.2.12 Vitamin E Naturally occurring vitamin E comprises tocopherols and tocotrienols. Tocopherol is oxidised by air, but is stable to heat in the absence of air. Studies of -tocopherol in UHT processed milk suggest that the processing conditions affect the subsequent losses, but that in all cases increased storage temperature led to increased rate of loss. Perhaps surprisingly it was also shown that whilst short-term frozen storage did not lead to losses of -tocopherol, frozen storage of greater than 4 months led to significant losses (up to 21%). Loss of tocopherol from milk powder was affected by water activity, with higher water activity leading to a higher initial rate of loss. Over an extended storage period the effect of water activity was less marked, with losses of 18% seen at both aw 0.3 and 0.44 after 60 days (Vidal-Valverde et al., 1993). Loss of vitamin E in infant formula has also been shown to be affected by temperature; losses of 13± 18% were seen at 25 ëC after 18 months, compared with 23±28% losses on storage at 40 ëC (Chavez Servin et al., 2008). Piironen et al. (1988) showed that tocopherols and tocotrienols were stable in many products (biscuits, butter and margarine, frozen strawberries, blueberry jam) but that significant losses of up to 20% after 2 months and over 80% after 12 months were seen in wheat and rye flour stored at room temperature. 26.2.13 Vitamin K Vitamin K is relatively stable to heat, but is affected by light and is decomposed in alkaline conditions. Isomerisation of both vitamin K1 and K2 is likely due to the presence of double bonds in the structures of both forms (Berry Ottaway, 2008). In a study of vitamin K1 levels in total parenteral nutrition admixtures, vitamin K showed relatively good stability (upwards of 75% retention after storage) over a 20-day storage period at 4 ëC or ambient air temperature and under various packaging (glass bottle or single- or multi-layer plastic bag) and matrix (presence or absence of lipids and trace elements) conditions. Exposure to sunlight did have an effect, however, with 50% loss after 3 hours' exposure (Billion-Rey et al., 1993). Vitamin K1 in juice from sea buckthorn berries was similarly relatively stable, with losses of only 18± 32% after 7 days' storage. Losses were the same at a range of temperatures (6, 25 and 40 ëC), suggesting that the losses were independent of storage temperature (Gutzeit et al., 2007).

26.3 Ensuring stability and extending the shelf life of vitaminfortified foods The shelf life of vitamin-fortified foods can be extended in a number of ways, dependent on the vitamin (or combination of vitamins) and the matrix in which it is incorporated. Packaging, storage conditions and the form in which the vitamin is added are all variables that can be optimised, in combination, to prolong the shelf life of vitamin-fortified products.

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Protection of vitamins that are easily oxidised may be aided by selection of packaging that is impermeable to oxygen, such as glass or specially-coated plastics, and by minimising the headspace above the product. Losses of vitamin C in fortified milk were shown to be far greater in three-layered high density polyethylene opaque bottles than six-layered bottles which also contained an oxygen barrier, ethylene vinyl alcohol (Gliguem and Birlouez-Aragon, 2005). Similarly, vitamin C in orange juice is lost more quickly when packaged in monolayer PET than juice bottled in glass or multilayer PET, but use of an oxygen scavenger coupled with liquid nitrogen and aluminium foil in the cap can increase the shelf life of juice in monolayer PET (Ros-Chumillas et al., 2007). De-aeration of the product during processing to reduce levels of oxygen present will also reduce losses of, for example, vitamin C in fruit juices and drinks. Opaque packaging or packaging which reduces the transmission of light, for example amber glass may be used to protect light-sensitive vitamins. For example, riboflavin in milk has been shown to be lost faster when packaged in a clear glass container than when packaged in a brown bottle or carton (Choe et al., 2005). Selection of the chemical form and commercial preparation in which the vitamin is to be added can also affect the stability of the vitamin in the product. Alcohols such as the tocopherols and retinol are more stable as their esters, so these tend to be the commercially available forms (e.g., retinyl acetate and palmitate, tocopherol acetate). Encapsulation or coating of vitamins will reduce their exposure to oxygen and other factors in the food matrix such as pH, metal ions or other vitamins, thereby protecting the vitamin from degradation. Examples of vitamins that are commercially available in encapsulated form are Vitamin A, Vitamin B12 and Vitamin K. Vitamins that are easily oxidised may be purchased as a preparation which contains a protective antioxidant, which may itself be another vitamin (i.e., tocopherols, vitamin E) or a synthetic antioxidant such as BHT. Commercially, companies have developed different preparations of vitamins both to improve stability and to allow incorporation of vitamins into different product matrices. Therefore selection of the form may not be simply on the basis of the most stable, but also whether it is compatible with the product; incorporation of water-soluble vitamins into fat-based products, and vice versa poses problems unrelated to the stability of the vitamins themselves, but must be taken account of for the production of an acceptable product. Microencapsulation of Vitamin A, for example, converts an oil-soluble vitamin into beadlets which can be added to dry products such as flour and sugar. Table 26.3 shows some commercially available forms of vitamins.

26.4

Evaluating the shelf life of vitamin-fortified foods

In order to determine the shelf life of vitamin-fortified foods it is necessary to carry out storage trials, measuring the concentrations of the added vitamins periodically. The use of robust analytical methods is therefore essential, to

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Examples of commercially available forms of vitamins

Vitamin

Commercial forms

Vitamin A Vitamin D Vitamin E Vitamin K Vitamin B1 Vitamin B2 Vitamin B6 Vitamin B12 Niacin Pantothenic acid Biotin Folic acid Vitamin C

Acetate, palmitate, propionate Vitamin D3 Tocopherol, tocopheryl acetate Vitamin K1 Thiamine hydrochloride, mononitrate Riboflavin, Sodium riboflavin-50 -phosphate Pyridoxine hydrochloride Cyanocobalamin Nicotinic acid, nicotinamide Calcium-D-pantothenate D-biotin Folic acid Ascorbic acid, sodium ascorbate, calcium ascorbate, ascorbyl palmitate, ascorbic acid phosphate

ensure that analytical variability is kept to a minimum so that the real trend in vitamin levels can be seen. Ideally the use of a standard method that has been validated and tested in several laboratories is desirable, although choice of method may be limited by availability of equipment and costs of carrying out the analysis. Additionally there may not be a standard method available which is suitable for the matrix of interest, or for the form in which the vitamin has been added. In any case the method selected should be validated in-house, and the variability of results obtained on different days should be less than the acceptable or expected vitamin loss. A reference material should be analysed during the validation process and subsequently with each sample set during the storage trial to check that the method is performing within the limits determined during the validation. There are a number of standard methods for the analysis of vitamins in foodstuffs. There are standard methods for vitamins A, B1, B2, B6, C, D, E and K1 that involve analysis by HPLC. Other methods use non-chromatographic procedures: determination of vitamin A content of dried skimmed milk uses a colorimetric procedure whilst there is a method for B6 which uses a microbiological assay. For vitamins A and D there are specific HPLC methods for determination of the vitamins in dried skimmed milk. As discussed above, vitamins for the fortification of foods may be added in forms other than those in which they occur naturally. There is therefore a need to ensure that the method selected is suitable for the accurate measurement of the vitamin in the form in which it has been added. For routine analytical laboratories this may pose a problem if the form is unknown, but for analysis of fortified samples in a storage trial the form in which the vitamin was added will be known, and therefore the correct method can be identified and used. It is also important to determine which chemical compounds are included in the definition of individual vitamins, so that the label reflects the true vitamin

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content. For example measurement of vitamin C involves reduction of dehydroascorbic acid to ascorbic, so that both forms can be captured in the measurement. Dehydroascorbic acid is the active form of the vitamin, and is formed when ascorbic acid is oxidised, so it is likely that both forms will be found in a food, particularly after storage, and both count towards the total vitamin C content. Further oxidation products, however, do not have vitamin activity, so are not included in the analysis. There are many other methods reported in the literature for the analysis of vitamins in foods, which may have been developed for specific matrices, or in order to improve the sensitivity or selectivity of existing methods. Newer technologies have also brought new possibilities for the sensitive and accurate determination of vitamins. Increasing availability of liquid chromatography coupled with mass spectrometry (MS) means that new methods are being developed using this technique. The advantage of using MS detection is its specificity; methods may be developed which are more efficient in terms of sample clean-up or are less dependent on chromatographic separation to achieve good results. Other relatively new methods for vitamin analysis include those based on the specificity provided by immunoaffinity techniques, where the target analyte binds to a protein. ELISA (enzyme-linked immunosorbent assay) kits for the analysis of some vitamins are available commercially, and have the advantage of specificity and the possibility of high throughput with a relatively short analysis time.

26.5

Future trends

Assessing and controlling vitamin levels of vitamin-fortified foods will always be an issue, and new developments are likely to be in commercial forms of vitamin preparations or in novel packaging. Packaging that actively removes or reduces factors which would increase vitamin loss could lead to increased shelf life or reduce the need to store products in refrigerated conditions. Use of time± temperature indicators on packaging could also be of great benefit both to manufacturers and consumers. At present assumptions must be made regarding the conditions under which products are transported and stored, and the temperatures used in estimating the shelf life may in some cases be worse than those the product actually encounters. Time±temperature indicators reflect the actual conditions, and when correctly calibrated could be used to indicate when a fortified product had reached the end of its shelf life with respect to the vitamin content stated on the label.

26.6

Source of further information and advice and EITENMILLER, R.R. (2000) Modern Analytical Methodologies in Fat and Water-soluble Vitamins. Wiley, New York.

SONG, W.O., BEECHER, G.R.

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References

and MARINE-FONT, A. (2000) Stability of vitamins A, E, and C complex in infant milks claimed to have equal final composition in liquid and powdered form. J. Food Sci., 65, 1052±1055. BERRY OTTAWAY, P. (2008) The stability of vitamins in fortified foods and supplements in Berry Ottaway, P. (ed.), Food Fortification and Supplementation. Woodhead Publishing Ltd, Cambridge, pp. 88±107. BILLION-REY, F., GUILLAUMONT, M., FREDERICH, A. and AULAGNER, G. (1993) Stability of fatsoluble vitamins A (retinol palmitate), E (tocopherol acetate), and K1 (phylloquinone) in total parenteral nutrition at home. J. Parenter Enteral Nutr., 17, 56±60. CHAVEZ-SERVIN, J.L., CASTELLOTE, A.I., RIVERO, M. and LOPEZ-ABATER, M.C. (2008) Analysis of vitamins A, E and C, iron and selenium contents in infant milk-based powdered formula during full shelf-life. Food Chem., 107, 1187±1197. CHOE, E., HUANG, R. and MIN, D.B. (2005) Chemical reactions and stability of riboflavin in foods. J. Food Sci., 70, R28±R36. GLIGUEM, H. and BIRLOUEZ-ARAGON, I. (2005) Effects of sterilization, packaging and storage on vitamin C degradation, protein denaturation, and glycation in fortified milks. J. Dairy Sci., 88, 891±899. GUTZEIT, D., BALEANU, G., WINTERHALTER, P. and JERZ, G. (2007) Determination of processing effects and of storage stability on vitamin K1 (phylloquinone) in sea buckthorn berries (Hippophae rhamnoides L. ssp. rhamnoides) and related products. J. Food Sci., 72, C491±497. HADDAD, G.S. and LOEWENSTEIN, M. (1983) Effect of several heat treatments and frozen storage on thiamine, riboflavin and ascorbic acid content of milk. J. Dairy Sci., 66, 1601±1606. INIESTA, M.D., PEREZ-CONESA, D., GARCIA-ALONSO, J., ROS, G. and PERIAGO, M.J. (2009) Folate content in tomato (Lycopersicon esculentum). Influence of cultivar, ripeness, year of harvest, and pasteurisation and storage temperatures. J. Agric. Food Chem., 57, 4739±4745. LESKOVA, E., KUBIKOVA, J., KOVACIKOVA, E., KOSICKA, M., PORUBSKA, J. and HOLCIKOVA, K. (2006) Vitamin losses: retention during heat treatment and continual changes expressed by mathematical models. J. Food Comp. Anal., 19, 252±276. LI, Y., DIOSADY, L.L. and JANKOWSKI, S. (2008) Effect of iron compounds on the storage stability of multiple-fortified Ultra RiceÕ. Int. J. Food Sci. Technol., 43, 423±429. LOUIE, N. and STENNETT, D.J. (1984) Stability of folic acid in 25% dextrose, 3.5% amino acids, and multivitamin solution. J. Parenter Enteral Nutr., 8, 421±426. OHRVIK, V. and WITTHOFT, C. (2008) Orange juice is a good folate source in respect to folate content and stability during storage and simulated digestion. Eur. J. Nutr., 47, 92±98. PIIRONEN, V., VARO, P. and KOIVISTOINEN, P. (1988) Stability of tocopherols and tocotrienols during storage of foods. J. Food Comp. Anal., 1, 124±129. ROS-CHUMILLAS, M., BELISSARIO, Y., IGUAZ, A. and LOPEZ, A. (2007) Quality and shelf life of orange juice aseptically packaged in PET bottles. J. Food Eng., 79, 234±242. STESKOVA, A., MOROCHOVICOVA, M. and LESKOVA, E. (2006) Vitamin C degradation during storage of fortified foods. J. Food Nutr. Res., 45, 55±61. UPRETI, P., MISTRY, V.V. and WARTHESEN, J.J. (2002) Estimation and fortification of Vitamin D3 in pasteurised process cheese. J. Dairy Sci., 85, 3173±3181. ALBALA-HURTADO, S., VECIANA-NOGUES, M.T., VIDAL-CAROU, M.C.

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and MEDRANO, A. (1993) Effects of frozen and other storage conditions on -tocopherol content of cow milk. J. Dairy Sci., 76, 1520±1525. WAGNER, D., ROUSSEAU, D., SIDHOM, G., POULIOT, M., AUDET, P. and VEITH, R. (2008) Vitamin D3 fortification, quantification, and long term stability in cheddar and low fat cheeses. J. Agric. Food Chem., 56, 7964±7969. WILSON, P. (2006) Vitamins ± shelf life prediction modelling. Food Quality and Analysis Forum Report, Leatherhead Food Research, Leatherhead, UK. YAMADA, K., SHIMODAIRA, M., CHIDA, S., YAMADA, N., MATSUSHIMA, N., FUKUDA, M. and YAMADA, S. (2008) Degradation of vitamin B12 in dietary supplements. Int. J. Vitam. Nutr. Res., 78, 195±203. VIDAL-VALVERDE, C., RUIZ, R.

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27 The stability and shelf life of milk and milk products D. D. Muir, Consultant, UK

Abstract: The shelf life of milk and milk products can conveniently be considered separately in two product groups. In short shelf life products the key to control lies in manipulation of the microbial content. Not only must pathogens be excluded but spoilage organisms must be removed, destroyed or inactivated. Successful strategies to achieve this end include heat treatment, spore removal and stringent control of the cold chain. In contrast, the shelf life of intermediate and long life products is largely determined by enzymic deterioration or by chemical processes. In all cases the quality of the raw material is paramount and strict precautions must be taken to exclude extra-cellular degradative enzymes. In this group of products specific action may also be required to control creaming, lipid oxidation and calciuminduced aggregation of protein. This end is achieved by homogenisation to control creaming in emulsions and by the use of processing aids to control chemical reactions. The shelf life of cheese is particularly difficult to define because the nature of the biochemical reactions associated with ripening usually results in a substantial window within which the organoleptic properties are acceptable to the consumer. Key words: spoilage bacteria, spore removal, creaming, oxidation, calciuminduced aggregation. Note: This chapter is a revised and updated version of Chapter 9 `Milk and milk products' by D. D. Muir and J. M. Banks in The Stability and Shelf-life of Food, ed. D. Kilcast and P. Subramaniam, Woodhead Publishing Limited, 2000, ISBN: 978-1-85573-500-2.

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27.1

Food and beverage stability and shelf life

Introduction

There is no straightforward objective definition of the shelf life of milk and milk products because criteria that may be appropriate for one product may be inadequate for another. For this reason, in this chapter shelf life is defined as: `the period following manufacture during which the product meets consumer expectations'. This definition is somewhat elastic, not least because the expectations of individual consumers vary. Nevertheless, its utility lies in the recognition that, in a diverse range of products, the end of shelf life may be signalled by changes in appearance, smell or flavour. The essence of the definition is that a change in quality of sufficient magnitude to influence consumer opinion has taken place. Changes limiting shelf life may be physicochemical, chemical or biochemical in nature. Examples of three such processes include the following: · physicochemical changes ± creaming of fat, gelation of protein solutions, syneresis of curds and crystallisation of minerals · chemical reactions ± non-enzymic browning and oxidation of fat · biochemical transformations ± growth of micro-organisms, enzymic degradation, ripening of cheese and fermentation. This chapter will highlight the various transformations that limit the shelf life of milk and milk products. As a general background, brief consideration will be given to the composition and important chemical properties of milk components. The bacterial flora of milk with reference to their potential for limiting shelf life will then be considered and the effect of temperature on growth of spoilage bacteria discussed. Finally, examples will be given of the factors influencing the shelf life of specific products together with comments on methods of control.

27.2

Chemical composition and principal reactions of milk

Milk was designed by nature to provide complete nourishment for the newborn and, as might be expected, is a highly complex mixture. The four main chemical classes present in milk, irrespective of species, are fat, protein, carbohydrate and mineral and each component plays a key nutritional role. In Europe, most milk is now derived from the dairy cow and the composition of typical mid-lactation milk is shown in Table 27.1. Transformation of milk protein and fat are responsible for most of the changes that govern shelf life. 27.2.1 Milk protein The proteins in milk are classified into two families: caseins and whey proteins. Their respective abundance is shown in Table 27.2. Casein is the most important group constituting over 80% of the protein in bovine milk in mid-lactation milk. Casein is split into five main classes, s1-, s2-, -, - and -caseins, as shown in Table 27.3. The primary structure of each casein found in bovine

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Composition of typical mid-lactation milk Concentration (g lÿ1)

Constituent Fat Protein: casein whey protein Non-protein nitrogen Lactose Ash Total solids

Proportion solids (%)

37.0 27.6 34.0 6.4 1.9 48.0 7.0 127.0

28.9 26.6

g

1.5 37.5 5.5 100.0

Table 27.2 Milk protein

Table 27.3

Fraction s1 s2

 a

Milk protein

(%)

Casein Whey protein -lactoglobulin -lactalbumin bovine serum albumin minor `proteins'

82.2 9.6 3.8 1.4 3.0

Relative abundance and selected properties of caseins Molecular weighta

Proportion whole casein (%)

Serine phosphate residues

Calcium sensitivity

Sugar residues

23 000 25 000 24 000 11 600±20 500 1 980

38.1 10.2 35.7 3.2 12.8

7±9 10±13 5 0 or 1 1

++ +++ + ÿ ÿ

ÿ ÿ ÿ ÿ +

Molecular weight of monomer.

milk, together with the genetic variants, has been defined. All the caseins are modestly sized and are thought to possess little organised structure. As a result, the caseins cannot be denatured by heating. The caseins are phosphoproteins (Table 27.3) and the extent of their reaction with multivalent ions such as calcium is highly dependent on the number of serine phosphate groups present on the molecule. This ability to interact with other ions is an important aspect of the functionality of caseins, e.g. in cheese making or in the production of fermented products. In addition it plays an important role in determining the stability of in-can sterilised milk products (evaporated milk and cream) and is the primary cause of age gelation in UHT sterilised milk and cream and in cream liqueurs.

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Table 27.4 Main minerals in milk

Calcium Magnesium Sodium Potassium Chloride Inorganic phosphate Citrate Zinc, selenium, molybdenum and iodine

Total (mmol lÿ1)

Diffusible (mmol lÿ1)

30.1 5.1 25.5 36.8 30.3 20.9 9.8

9.5 3.3 ± ± ± 11.2 9.2

trace levels

In raw milk, caseins are associated with calcium and phosphate in small particles called micelles, with an average size of approximately 100 nm. The mineral content of milk is shown in Table 27.4. About two-thirds of the calcium and about half the phosphate are bound to the colloidal, i.e. micellar, phase. The partition of calcium (and phosphate) between the micellar and the serum phase may be manipulated by technological means. Calcium can be withdrawn from the micelle by addition of sequestrants, such as tri-sodium citrate, hexametaphosphate or polyphosphate. In the micellar structure there is a network of scasein and calcium phosphate within which -casein is loosely held. The surface of the micelle is rich in -casein although some of this component is also located within the micellar structure. The `hairy' micelle model best fits the known behaviour of casein micelles. The essence of this model is that a spherical core of s- and -casein is stabilised by `hairs' formed by the extension of surface -casein. Another important property of caseins is derived from their primary structure. Within the caseins, the acidic amino groups (carboxyl and ester phosphate) are unevenly distributed along the polypeptide chains. As a result, the proteins have highly charged polar regions and contrasting domains of a hydrophobic nature. Such heterogeneity confers very good emulsifying properties on the molecules because the polar regions can associate with the aqueous phase while the hydrophobic regions bind well to lipids. As a result, casein stabilises fat droplets in solutions or in semi-solid matrices such as meat emulsions. In contrast, the whey proteins are globular proteins with classical tertiary structures. The structure of the main whey protein, -lactoglobulin, is stabilised by disulphide bridges. Such links are disrupted by heat treatment above 65 ëC and, as a result, the proteins are denatured. On the other hand, un-denatured whey proteins are not greatly affected by multivalent ions and do not readily precipitate from solution. Four types of reaction can influence the functional properties of milk protein: 1. Protein degradation can take place as a result of attack by milk plasmin or by bacterial enzymes. This affects functionality e.g., emulsification capacity. 2. The second important reaction of milk proteins occurs when they react with reducing sugars ± the Maillard reaction. This reaction is characterised by

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browning of products but, in its early stages, there is a significant loss of nutritive value because lysine, an essential amino acid, reacts very readily with reducing sugars. The extent of loss of lysine depends on the severity of heat treatment, the pH of the product and the amount of reducing sugar present. By careful avoidance of such prejudicial conditions during manufacture, the nutritive value of milk proteins can be conserved. Nevertheless, the Maillard reaction can limit the shelf life of dried milk products. 3. Acidification forms the basis of production of all fermented milks. The gels of fermented milks, such as yoghurt and quarg, are formed by acidification of milk. As the pH is reduced, the casein precipitates selectively. The first signs of aggregation occur around pH 5 and, once the pH falls to 4.6, all the casein becomes insoluble. 4. Another property of casein is its ability to aggregate in the presence of calcium under specific conditions. As described above, casein micelles are stabilised by -casein that behaves like a `hairy' layer at the micellar surface. Chymosin, the principal enzyme in calf rennet, can selectively break down the surface -casein and reduce micellar stability. If the temperature of the rennet-treated milk is above 10 ëC and calcium is present (as it always is in milk, see Table 27.4), aggregation takes place and a rennet gel is formed. 27.2.2 Milk fat Milk fat consists almost entirely of triglycerides (triacylglycerols), i.e. esters of fatty acids with the molecule glycerol. Fatty acids in milk are derived from a number of sources and the pathways from feed to milk are not straightforward. Fat consumed by the cow is first hydrolysed to free fatty acid in the rumen or first stomach. Because of the strongly reducing conditions in the rumen, unsaturated fatty acids are hydrogenated. The saturated acid then passes to the gut where it is absorbed into the circulating blood. Some fatty acid is stored in the animal's fat reserves, after re-conversion to triglyceride. Another portion is broken down to provide energy for the animal, while the remainder passes to the mammary gland where it can be re-esterified into milk triglyceride. Such preformed fatty acids are predominantly of chain length 16 or higher, though chain lengths of 12 and 14 can be found when the cow is fed diets rich in these acids. However, the cow also has the ability to synthesise fatty acids with chain lengths from 4 to 16 in the mammary gland. These acids can account for over a third of the total triglyceride. A further complication arises from the presence of a specific enzyme in several tissues of the cow. This enzyme is capable of taking a saturated fatty acid of chain length 18 (stearic acid) and converting it to the mono-unsaturate (oleic acid). As a result of this series of transformations the fatty acid composition of milk is fairly heterogeneous, as shown in Table 27.5. The distribution of the fatty acids in the triglycerides adds another layer of complexity, because the distribution among the three potential sites for esterification is not random. The short chain acids are preferentially linked to the hydroxyl group at one end of the molecule.

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Fatty acid composition of milk fat

Fatty acid

Mole (%)

4:0 6:0 8:0 10:0 12:0 14:0 14:1 16:0 16:1 18:0 18:1 18:2 18:3 Carbon number

9.6 4.0 2.0 3.5 3.6 9.9 2.1 24.7 3.2 10.5 22.6 3.0 1.4 42.7

As with milk protein, fat occurs naturally as a complex structure. Milk fat globules range in size predominantly from 1 to 10 m in diameter (median 3 m). The globules are spherical droplets of triglyceride coated by a double membrane rich in phospholipid. The milk fat globule membrane (MFGM) is fragile and is damaged and disrupted by physical treatment. This reaction forms the basis of butter-making. By arranging optimum conditions for disruption of globule membrane, the droplets are induced to clump. The fat surface exposed by removal of the membrane is very hydrophobic and quickly associates with the exposed fat surface on other droplets. This process is called churning. The clumps of granules are first washed to remove protein, lactose and minerals (as buttermilk) then physically worked to yield a plastic mass ± butter. Milk fat is susceptible to several important reactions: · raw milk has an abundance of lipoprotein lipase, an enzyme that will rapidly hydrolyse milk fat to free fatty acids, · bacterial lipase causes serious degradation of milk fat, · the delicate MFGM is also susceptible to enzymatic degradation and, · another important reaction is oxidation. Reaction is initiated by free radicals of oxygen at the unsaturated bonds (especially conjugated double bonds) in fatty acids. The reaction is catalysed by light and by heavy metals such as copper. Phospholipids in milk are more prone to attack in milk than are the triglycerides which are mostly saturated. Lipid oxidation is best controlled by exclusion of oxygen, light and potential contaminants, hence packaging plays a key role. Milk fat droplets in raw milk are readily susceptible to creaming. The rate at which fat globules rise depends on the density difference between the fat globule and the serum, the viscosity of the serum which is influenced by temperature, the concentration of a cold agglutinin and fat globule size. In practice, creaming

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is inhibited by reduction of the fat globule size by homogenisation. The milk fat globules are reduced in size by pumping at very high pressure (up to 400 bar) through a small slit or orifice. The size reduction results in an increase in specific surface area and this newly-formed fat surface is immediately coated with milk protein from the serum phase. The threshold globule size below which creaming does not occur is ca 0.8 m diameter. Control of fat emulsion size is critical in products that are prone to creaming.

27.3

Bacteria in milk and related enzyme activity

27.3.1 Psychrotrophic Gram-negative bacteria The bacteria in freshly drawn milk from a healthy cow are largely derived from the environment within which the cow is kept ± the byre and milking parlour ± and from the equipment through which the milk passes and in which it is stored. The majority of milk in Western Europe is cooled and refrigerated promptly after milking. As a result, conditions favour the survival and subsequent growth of organisms adapted to a low-temperature environment. Many such bacteria have an optimum growth temperature between 20 and 30 ëC but also grow, albeit more slowly, at refrigeration temperature. They are known collectively as psychrotrophs. Psychrotrophic bacteria from farm bulk tanks and from creamery silos have been extensively studied because of their potential commercial importance. Typical results for creamery silo milk collected in South-west Scotland and from a farm bulk tank are presented in Table 27.6. The Gram-negative bacteria, which make up over 90% of the total flora, are classified according to genus. Bacteria of the genus Pseudomonas were by far the most common organisms, about half being of the fluorescent type. The main species Pseudomonas fluorescens is Table 27.6

Typical bacteria in creamery silo milk Isolates in genus (%)

Bacterial genus

Lipolytic

Proteolytic

Lipolytic + proteolytic

50.5 31.5 15.8

5 32 2

2 1 2

71 11 31

0.0

5

9

36

1.3 0.0 0.9 85

6 25 0

6 6 0

24 41 92

Creamery Farm

Pseudomonas fluorescing 33.5 non-fluorescing 44.1 Enterobacteriacea, Aeromonas, 8.5 Pasturella or Vibrio Acinetobacter, Moraxella or 6.2 Brucella Flavobacterium 4.0 Chromobacterium 2.2 Alcaligines 1.5 Number of isolates 735

Isolates with stated activity (%)

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characterised by the production of a diffusible fluorescent pigment during growth on an appropriate medium. Although the optimum temperature for growth lies between 25 and 30 ëC, Pseudomonads will also grow at temperatures just above freezing. The genera are widely distributed in water and in the soil. The second most common family of psychrotrophic bacteria in raw milk is that of the Enterobacteriaciae. These organisms are also small, motile, Gramnegative rods. Their optimum growth temperature tends to be higher (i.e. >30 ëC) than that of the Pseudomonads but they adapt well to growth at refrigeration temperature. The usual source of coliform contamination of raw milk is from the digestive tract of the cow via faecal contamination of the bedding or udder. Some strains of Escherichia coli produce verotoxins and constitute a food-poisoning hazard. A number of other types of psychrotroph are also frequently found (Table 27.6), albeit at low frequency. Included in the list of common contaminants are bacteria of the genera Flavobacterium, Chromobacterium and Alcaligenes. They are all Gram-negative rods capable of low-temperature growth and, like the Pseudomonads, are commonly found in soil and water. Many of the psychrotrophic bacteria isolated from milk produce extracellular enzymes that degrade milk fat and protein (Table 27.6). Some genera have great destructive potential. For example, over 70% of isolates classified as P. fluorescens exhibit both proteolytic and lipolytic activity. At least 20% of all psychrotrophs isolated from raw milk can cause protein breakdown and lipolytic rancidity. It is also worth noting that all genera examined possessed some degree of extra-cellular degradative activity and thus pose a significant threat to milk quality and to products manufactured from milk. 27.3.2 Heat-resistant bacteria The psychrotrophic bacteria considered above are almost all killed by modest heat treatment (e.g. pasteurisation, 72 ëC/15 s). However, some survivors from the natural flora, given suitable conditions, are able to promote spoilage. Bacteria typical of those isolated from milk and cream are shown in Table 27.7. In general, only Bacillus spp. and Corynebacteria are found in any number, though thermoduric micrococci and lactococci are occasionally recovered. The coryneforms, micrococci and lactococci are usually incapable of further growth in pasteurised product provided the temperature is held below 6 ëC. Bacillus spp. are the other major thermoduric group of organisms and are of greater technical significance because of their ability to grow under refrigeration conditions. Of the Bacillus spp. found, B. cereus, B. licheniformis and B. coagulans predominate. The vegetative cells of the bacilli are readily destroyed by pasteurisation and it is the spore form of the organism which is heat stable. These residual spores may, given the correct conditions, germinate after heat treatment and subsequently grow in pasteurised products. The degradative activity associated with thermoduric bacteria isolated from pasteurised cream is shown in Table 27.7. Coryneforms are largely inactive but the Bacillus spp. have, in general,

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The stability and shelf life of milk and milk products Table 27.7

Heat-resistant bacteria in creamery silo milk Bacillus spp.

Proportion isolates, %a Heated at 63 ëC/30 min Heated at 80 ëC/10 min

54 61

Enzyme activity, % Lipolytic only Proteolytic only Lipolytic + proteolytic Phospholipase Tri-butyrin hydrolase Inactive Number of isolates

0 34.1 37.0 80.4 16.8 12.1 316

a

763

Coryneform 46 37 0 3.3 10.0 0 20.0 66.7 30

No Gram-negative organisms were found.

great potential for spoilage. Almost 40% of isolates could degrade both milk fat and protein while 80% of isolates exhibited phospholipase activity. As indicated earlier, phospholipase action can destroy the native MFGM, resulting in destabilisation of the fat emulsion in milk. In summary, the psychrotrophic thermoduric floras of milk are able to survive pasteurisation, can subsequently grow in product and also possess the extracellular enzyme activity necessary to induce spoilage. Thus they constitute a significant threat to the shelf life of pasteurised product.

27.4

Raw milk enzymes

As reported above, the bacterial flora of milk are associated with extra-cellular enzyme activity which can lead to spoilage of milk and milk products. However, bacterial enzymes are not the only enzymes present in raw milk. Bovine milk is a biologically active product and around 50 different enzyme activities have been reported in clean, freshly drawn milk. Fortunately, only two of these native enzymes have a substantial impact on the quality or shelf life of milk and milk products. Therefore we will consider only native enzymes with relevant activity. 27.4.1 Lipoprotein lipase Milk lipase is a lipoprotein lipase that catalyses the breakdown of milk triglycerides to produce free fatty acids (FFAs). Some of these FFAs have low organoleptic thresholds and produce odours and flavours that are described variously as rancid, bitter, soapy or unclean. The purified enzyme is relatively unstable and can be inactivated by heat, ultraviolet light, acid or oxidising reagents. In milk, the association of the enzyme with casein affords some protection but it is generally accepted that the enzyme is almost completely

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inactivated by high-temperature short-time (HTST) pasteurisation (i.e., heat treatment at 72 ëC for 15 s). In milk, the enzyme is not normally active since the potential substrate ± milk fat droplets ± is encapsulated by MFGM. Two distinct types of lipolysis by lipoprotein lipase are recognised. When freshly drawn milk is found to be rancid the condition is referred to as spontaneous lipolysis and is influenced by stage of lactation, season, diet and plane of nutrition. Nevertheless, spontaneous lipolysis is not a determinant of shelf life because the fresh milk is unacceptable and is totally unsuitable for processing. On the other hand, induced lipolysis can lead to spoilage of products which have not been heat treated. The key factor for expression of enzyme activity is damage to the MFGM. Two common types of damage occur ± first, the membrane may be damaged by physical means such as foaming, agitation or homogenisation; and second, the integrity of the membrane may be prejudiced by temperature cycling. In all cases, the end result is similar: lipolysis proceeds. Thus products which contain active lipase must be treated with extreme care. 27.4.2 Plasmin Although more than one proteinase has been identified in raw milk, the major proteinase is a serine proteinase with trypsin-like activity called milk plasmin. At acid and neutral pH, the enzyme is stable to pasteurisation but, at alkaline pH, it is rapidly inactivated. Some plasmin activity resists UHT processing (heat treatment at 140 ëC/3 s). Nevertheless, the occurrence of plasmin in milk is associated with physiological conditions in which the tight junctions in the basal membrane of the mammary gland are `leaky' and allow some passage of blood components into the milk. For example, in very early lactation, very late lactation and when disease is present in the udder, abnormally high concentrations of plasmin are found in milk. Provided plasmin levels are low in milk, problems will not be manifested in short shelf life products. However, even modest levels of proteinase activity may be deleterious in long life products. This aspect of proteinase activity will be discussed later.

27.5

Control of the quality of short shelf life products

Short shelf life products are those with a normal shelf life of three weeks or less. Such products include pasteurised milk and cream, cottage cheese, yoghurt and some ranges of dairy desserts. The changes that occur in fresh products after manufacture are associated with physical separation of phases and with the growth of micro-organisms. Chemical changes, the action of raw milk enzymes and pathogens, have no significant effect on the shelf life of fresh dairy products. Physical separation, i.e. creaming, may be a consideration and is controlled by reducing the fat globule size by homogenisation or by increasing product viscosity. However, the main limitation on shelf life of fresh dairy products is spoilage by bacteria, moulds and yeasts that grow at refrigeration temperature (<8 ëC).

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27.5.1 Pasteurised milk and cream The shelf life of pasteurised milk and cream is governed by the same factors. Historically, shelf life was limited by the ingress of Gram-negative spoilage bacteria after the pasteurisation process. This problem is now universally recognised and is under strict control. Nevertheless, once the Gram-negative contamination is excluded, steps must still then be taken to moderate the outgrowth, albeit slow at refrigeration temperature, of psychrotrophic sporeforming bacteria. Post-heat treatment contamination Gram-negative spoilage bacteria pose a risk to shelf life. These bacteria are completely inactivated by pasteurisation but are regularly found in pasteurised products. They are post-heat treatment contaminants (PHTC). A schematic of processing sequences for pasteurised milk and cream is shown in Fig. 27.1. The most commonly used sequence relies entirely on pasteurisation to reduce the bacterial load and to inactivate enzymes with degradative potential. Provided the process downstream of the heat exchanger is aseptic, Gram-negative psychrotrophic bacteria play no part in spoilage. However, this situation is sometimes not realised in practice. Most problems arise in the filling line where open containers permit ingress of contaminants. This can be kept to a minimum by flooding the filling line with a curtain of sterile air. Nevertheless, disruption of the high-speed packaging line by physical misalignment of containers is inevitable. When this occurs, operator intervention is inevitable and the integrity of the aseptic environment is breached. The key to limiting PHTC lies in stringent exclusion of contamination during the filling and packaging operations. In particular, it is essential to control the number of stoppages on high-speed lines. Measurement of the extent of PHTC is not straightforward. The number of contaminating bacteria required to induce spoilage depends on the storage

Fig. 27.1

Schematic for production of pasteurised milk.

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temperature of the product. During storage at 8 ëC, ten colony-forming units (cfu) per litre of a typical pseudomonad would reduce shelf life by several days. Because of the difficulty of enumerating low numbers of bacteria, preincubation techniques have been introduced to enhance the process. A necessary prerequisite for success is that the growth of Gram-positive organisms is inhibited during the pre-incubation to allow selective growth of the Gramnegative flora. Successful methods use a cocktail of inhibitors (penicillin, crystal violet and nisin) to inhibit the growth of Gram-positive bacteria during preincubation at 21 ëC for 24/25 hours. After pre-incubation, the extent of PHTC may be assessed by enumeration of bacterial numbers using ATP-photometry (rapid), visual counting (rapid), impedimetry (slow) or by plate-counting (slow). The pre-incubation step is rate-limiting and the overall measurement takes at least 25 hours. Nevertheless, routine estimation of the extent of PHTC is an essential tool for quality control. Heat-resistant organisms Provided PHTC is absent, the shelf life of pasteurised milk and cream is anticipated to be at least 8±10 days at storage temperatures in the range 6±8 ëC. Outgrowth of spore-forming bacteria (mainly Bacillus spp.) forms the ultimate limitation on shelf life. Because these bacteria are not inactivated by pasteurisation and can grow, albeit slowly, at refrigeration temperature, three strategies have been explored to control their growth: · destruction of spores by heat treatment · control of growth by low-temperature storage · reducing the number of spores in milk. The simplest method of reducing the numbers of bacterial spores in milk is to increase the severity of pasteurisation. Unfortunately, spores are not effectively destroyed until temperatures in excess of 110 ëC are employed. Typically, heat treatment at 120 ëC for 30 s will destroy almost all psychrotrophic spore-forming bacteria. However, this severe treatment induces flavour changes in the product and reduces its appeal to the consumer. The effect of heating temperature on the sensory character of milk has been explored in the laboratory and flavour change is detected once the heating temperature exceeds 82 ëC (15 s hold). As a result, high-heat treatment is not often used for extending the shelf life of liquid milk or cream. Although many Bacillus spp. grow at refrigeration temperature, growth is slow. Significant extension of shelf life can be achieved by storing product at or below 4 ëC throughout its shelf life. This condition is readily achieved at the dairy and in the distribution chain but is likely to be ignored by retailers and customers. Despite scientific and technological advances leading to improved milk quality, the shelf life of the product can easily be spoiled by temperature abuse. The best strategy to control spoilage of milk by spore-forming bacteria is to reduce the number of spores in the raw milk supply. This objective can be

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achieved on the farm by implementing a detailed protocol for the milking operation. For example, washing and drying of the udder before milking and the use of teat disinfectant have significant effects. Spores can be removed from milk at the processing factory by high-speed centrifugation. The separation exploits the density difference between the spore and the milk serum. However, the process is not absolute and clarifiers and bactofuges ± specially designed to remove spores ± achieve an efficiency of ca 95% in a single pass. The equipment is situated upstream of the pasteuriser (e.g., sequence B in Fig. 27.1). Inclusion of a bactofuge in the processing line might extend the shelf life of pasteurised milk by up to three days. However, there is an inevitable increase in processing cost and the waste stream from the bactofuge or clarifier may be as high as 5% of the raw material. These costs must be offset against the further extension in shelf life by three days. Another method of removing bacterial spores from raw milk is to employ membrane filtration. Spores (and vegetative bacterial cells) are readily removed from skim milk using cross-flow ultrafiltration with ceramic membranes with a nominal pore size of 1.4 m ± typically a five log-cycle reduction in bacterial count is achieved. Unfortunately, a proportion of the native milk fat globules is similar in size to bacteria and must be removed by centrifugal separation before the microfiltration step. The cream portion is heat-treated independently. A typical processing sequence (C) is shown in Fig. 27.1. It is claimed that a shelf life in excess of 21 days can be attained by application of this process. Filtered milk sales accounted for 6.2% of total liquid milk sales (5.0 billion litres) in 2009 and grew by 10% despite the premium price. This indicates the value consumers place on extended shelf life. 27.5.2 Yoghurt and fermented milk Yoghurt and fermented milk are inherently safe. A milk base, usually fortified with protein, is severely heated to denature the whey protein and inoculated with a lactic acid starter. The starter converts lactose to lactic acid and, as a result, the pH of the mixture falls. Several concurrent changes take place: calcium phosphate is solubilised, the integrity of the casein micelles is weakened and, as the isoelectric point of the protein (pH 4.6) approaches, a gel is formed. The yoghurt is then cooled to inhibit further growth of starter. The combination of severe heat treatment, low pH and a dense population of living starter bacteria (typically 107±109 cfu mlÿ1) inhibit growth of spoilage bacteria. Nevertheless, yeast and mould may thrive under these conditions and can spoil the product. Precautions to exclude their ingress follow the same principles as avoidance of PHTC described for milk and cream. Notwithstanding these minor problems, yoghurt may deteriorate during storage owing to fermentation continuing after the manufacturing process is complete. The product continues to develop acidity and syneresis may occur with the formation of an unsightly layer of serum. This limits shelf life but may be avoided by prudent selection of starter bacteria that `stop' when the product is cooled.

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27.5.3 Cottage cheese Cottage cheese is a minor dairy product but has a high added value. It is manufactured by a process in which a curd is formed, annealed and then coated with a cream dressing. The curd is made by acidification of skim milk by lactic starter bacteria (some rennet is added but this is not the primary cause of clotting). After the curd is cooked and washed, a cream dressing is added, together with fruit, herbs, or spices in some cases. The shelf life of the product is essentially determined by the microbiological quality of the cream dressing and microbial status of the other additives, as well as their pH. Particular attention must be paid to the quality of the water used to wash the curd. The factors which affect the shelf life are similar to those found for other pasteurised milk products. PHTC can be enhanced if the additives ± herbs, etc. ± are not properly treated before addition. The problems associated with PHTC can be ameliorated by culturing the cream dressing with lactic acid starter. The resultant drop in pH effectively inhibits growth of most commonly occurring Gram-negative rods. However, yeast and mould can grow at the acid pH values achieved and must be strictly controlled.

27.6 Factors influencing the stability of long shelf life products The stability of short shelf life dairy products depends on the moderation of the growth of and subsequent degradation by spoilage micro-organisms. In contrast, the shelf life of intermediate and long life dairy products is largely determined by enzymic degradation or by chemical deterioration. In this section, degradative enzymes in dairy products, their heat resistance, methods of detection and strategies for inactivation are considered. 27.6.1 Heat-resistant enzymes A notable feature of the spoilage bacteria found in raw milk is their almost universal ability to produce extra-cellular degradative enzymes. While the bacteria, mostly Gram-negative psychrotrophs, are readily killed by pasteurisation, such heat treatment has little effect on the extra-cellular degradative enzymes. In this section the effect of UHT processing, a heat treatment designed for sterilisation, on proteinase, lipase and phospholipase activity will be discussed. UHT treatment represents the most severe heat treatment applied to dairy products other than those like evaporated milk and sterilised and clotted creams which are in-container sterilised. An overwhelming proportion of the psychrotrophic flora found in milk produces heat-stable enzymes. Typical results from work conducted in my own laboratory are shown in Table 27.8 for the residual proteinase, lipase and phospholipase C activity found after treating cell-free supernatants at 140 ëC for 5 s. Of the bacterial types examined, only Acinetobacter, Aeromonas and

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Residual enzyme activity after heat treatment Residual enzyme activity (%)

Type of degradation Lipolysis Proteolysis Hydrolysis of phospholipid

Pasteurisation

UHT treatment

59 66 30

31 41 21

Bacillus spp. had residual activities below 10%. The fluorescent Pseudomonads that predominate in the flora of refrigerated milk and are enzymically active had residual enzyme activities ranging between 14 and 51%. In addition, very high residual levels of phospholipase C survived UHT treatment. When enzymes from 46 isolates exhibiting both proteolytic and lipolytic properties were compared, there was little difference in the ability of the enzyme to withstand either pasteurisation or UHT sterilisation. These results are typical of those found throughout the world for enzymes from ex-farm milk, e.g. enzymes isolated from ex-farm milk in New Zealand were equally heat-resistant. The effect of stage of growth cycle on the thermostability of cell-free extracts from eight cultures of psychrotrophs grown for 2±3 days at 30 ëC and at 30 ëC for 14 days has been studied. At the extremes of the logarithmic phase of the growth cycle, the heat stability of the enzymes after pasteurisation or UHT treatment was the same. Furthermore, there was little difference in the thermostability of extra-cellular protease produced by psychrotrophic cultures grown at temperatures ranging from 2 to 30 ëC. Therefore, the spoilage bacteria found in raw milk have the potential to produce extra-cellular degradative enzymes irrespective of the conditions of growth. Once produced, these enzymes are not destroyed by simple heat treatment. Consequently, these enzymes play a key role in the spoilage of intermediate and long shelf life products. 27.6.2 Potential methods of reducing the effect of heat-stable enzymes Significant inactivation of extra-cellular proteinase and lipase is observed above the optimum temperature for maximum activity. For example, heat treatment at 55 ëC for 1 h promoted a marked reduction in proteinase activity. The most efficacious combination was UHT treatment followed by low-temperature inactivation at 55 ëC for 1 h. Proteinase and lipase activity were reduced by this treatment to 17 and 7% respectively of their original value. Nevertheless, the logistics of holding large volumes of sterile milk for extended periods has precluded the application of these findings. The overwhelming conclusion to be reached is that, once extra-cellular enzyme activity is present in a product, it is almost impossible to inhibit its action. Attention must therefore be focused on detection of the degradative ability.

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27.6.3 Methods of detection of extra-cellular enzyme activity The simplest method of detecting extra-cellular enzyme activity is to use a diffusion assay. Agar or another suitable gel is cast with an indicator component and cell-free supernatant is inoculated into a well cut in the agar. Enzyme activity is then detected either as a zone of clearing or by a colour reaction with a suitable indicator compound. In our experience, skim milk agar is an effective indicator medium for proteolytic activity. Enzyme activity is detected as a zone of clearing or a zone of precipitation around the agar well. The concentration of proteinase present is directly proportional to the square of the true zone radius (that is, allowing for the diameter of the well) and there is also a relation between the area cleared and incubation time. A similar principle may be used for detecting lipase activity using tributyrin agar as the substrate. Furthermore, a high correlation exists between the ability to hydrolyse tributyrin and hydrolysis of butterfat. Diffusion using egg yolk emulsion in a blood agar base is also effective for detection of phospholipase activity. Various colorimetric assay methods have also been developed based on liberation of a dye from a substrate by the enzyme action. The use of hide powder azure for proteinase detection is an apparently robust technique for use in quality control laboratories. It is reported to be sufficiently sensitive to detect the proteinase activity of 2:5  106 cfu mlÿ1 of an enzymically active pseudomonad grown in refrigerated whole milk. An equally robust colorimetric assay for lipase is based on the hydrolysis of colourless -naphthol-caprylate to yield -naphthol which is readily complexed with an azo dye.

27.7

Control of the stability of long life milk products

In response to consumer pressure for more sophisticated and diverse food, the number of intermediate and long life dairy products in the market place has increased significantly. As a result, it is impractical to give comprehensive details of the factors controlling the shelf life of every product in this class. Moreover, generalisations are dangerous because of the specificity of many shelf life problems. To illustrate the diversity of the problem, a range of specific examples has been selected and the key factors controlling shelf life are outlined for each type of product in turn. 27.7.1 Butter and spreads Preservation of milk fat by conversion into butter involves separation of milk into cream and skim milk. The cream is subject to phase inversion by physical disruption of the natural MFGM. When the membrane is damaged, the fat globule surfaces lose their stability in the aqueous phase and coalesce (or churn) to form fat-rich granules. After washing with clean water to remove milk solids, the granules are physically worked into a uniform mass that is called butter.

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Butter should comprise at least 80% fat and contain less than 16% water in the form of very small, evenly distributed water droplets. Control of shelf life of butter is multi-factorial. Raw material quality is especially important because the droplets of aqueous phase entrained in the fat phase have the potential to support bacterial growth. Consequently, heat treatment of raw milk must be efficient and levels of heat-stable extra-cellular enzyme must be low. The psychrotrophic count in the raw milk should not exceed 5  106 cfu mlÿ1. After heat treatment, the total bacterial count in the cream should be <103 cfu mlÿ1 with fewer than one yeast, mould or coliform organism detected per ml. Furthermore, dispersion of the water droplets within the butter must be maintained. Coalescence of droplets to form free water offers the potential for rapid spoilage even when contamination is slight. Even under optimum production conditions the shelf life of butter is limited at room temperature. Butter is best stored at ÿ25 ëC and sweet cream, salted butter keeps satisfactorily for several years. Oxidation is an important feature of shelf life. The problem is not as great as might be expected because of the low temperatures employed for prolonged storage. Moreover, slightly oxidised flavours are expected by many consumers and are disguised by salt addition. Nevertheless, shelf life can be usefully prolonged by exclusion of oxygen during packaging and during storage. Various barrier types of wrapping have been employed with success. Dairy-based spreads are manufactured by margarine-based technology and may have fat contents from 37.5 to 76.3%. Usually the amount of butterfat present is low but, in contrast to butter, high levels of milk protein may be incorporated to stabilise the product. Because of the high water content, the water-in-oil emulsion may have limited stability and this limits shelf life, especially when the product is subject to temperature cycling. A further problem associated with the large increase in water content is the potential for bacterial growth and spoilage. As a result, the shelf life of spreads is often limited, especially at storage temperatures above 4 ëC or when preservatives are not incorporated in the blend. 27.7.2 Dried milk products Preservation of milk by drying involves heat treatment to reduce bacterial load, concentration by evaporation to about 45±52% solids before atomisation into a stream of hot air. The milk droplets are converted into a powder within a short time (5±30 s) and are separated from the air-stream by cyclones or bag filters. The essential feature of spray drying is that the moisture content of the powder is reduced to a level at which no bacterial growth occurs and there is little damage to the functionality of the milk components. Shelf life is determined by three factors: quality of the raw material, the drying process itself and the conditions under which the powders are stored. The heat treatment applied during processing ensures that the final bacterial load of

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powder is low. For all but low-heat1 powders the bacterial load bears little relation to raw milk quality. Nevertheless, heat-resistant, extra-cellular enzymes are not destroyed. The bacterial count in the raw milk should not exceed a level at which extra-cellular enzymes from psychrotrophic bacteria can initiate degradation ± this threshold is about 2  106 cfu mlÿ1. The second factor to influence the shelf life of dried milk is the nature of the drying process. It has been found that the extent of heat treatment applied to the milk during powder manufacture (measured by the extent of whey protein denaturation) is associated with a reduction in the solubility of dried skim milk during storage for six months at 30 ëC. The final and most important factor controlling shelf life of dried milk is the condition in which it is stored. Although storage conditions are more critical for whole milk powder than for its fat-free analogue, the moisture content of all powders must be maintained in the critical range of 2±4% if deterioration is to be avoided. Skim-milk powder stored in barrier bags at normal ambient temperature has a shelf life of at least one year and the deterioration observed during storage for a further year is slight. However, if moisture penetrates the powder, rapid deterioration occurs even when enzyme activity is absent. The main cause of deterioration is associated with protein/lactose interaction. Such deterioration is exacerbated by storage of powder at high temperature. In the case of dried whole milk, autoxidation of milk fat affects shelf life. Where addition of antioxidants is permitted, a useful extension of shelf life can be achieved but their use is associated with marked consumer resistance. To ameliorate the problem, dried whole milk is given a very severe heat treatment during manufacture. Such heating results in the liberation of free sulphydryl groups in the proteins and these reactive groups compete with lipids for oxidants. In addition, the oxygen level of the powder may be reduced by replacing the air with an inert gas but special rigid packaging must be used, adding significantly to the cost. In summary, control of moisture content and protection from exposure to oxygen hold the key to extending the shelf life of powders. Because all the reactions associated with powder deterioration are temperature sensitive, where possible, powder should be stored in the cold (4±8 ëC) and out of direct strong light. 27.7.3 In-can sterilised cream In contrast to butter and dried milk, the shelf life of sterilised cream is determined by chemical reactions involving minerals and protein. Bacteriological and enzymic deterioration are unusual in products sterilised in cans because of the severity of the heat treatment. Almost all the sterilised cream (23% butterfat)

1. Heat classification of powders measures the severity of heat treatment. Low-heat powders have minimal heat treatment, i.e. equivalent to pasteurisation.

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manufactured at present in the UK contains the sodium salts of orthophosphate and those of carbonate and citrate. These stabilisers inhibit calcium±protein interaction with considerable success. In addition, storage at refrigeration temperature has beneficial effects. Serum separation is almost completely inhibited and viscosity is increased. There is little penalty in terms of cream texture if storage is carried out at 6 ëC but severe problems can occur if sterilised cream is frozen. 27.7.4 Evaporated milk Full cream evaporated milk is mainly confined to international trade and usually contains 9% fat and 31% total solids. Control of quality must take into account: (a) cream separation during storage, (b) age-gelation and (c) deposition of calcium salts. Cream separation is avoided by manipulation of the homogenisation conditions during manufacture. Homogenisation should be as severe as possible without prejudicing heat stability. Age gelation is inhibited by application of a severe heat treatment to the milk before concentration and by addition of mineral stabiliser. Finally, mineral deposition is moderated by limiting the use of mineral stabiliser. Where extended shelf life is required, the addition of small amounts of lecithin to the concentrate can promote a useful increase in stability. While manufacture of in-can sterilised concentrated milk is well established and the control factors are known, successful manufacture of the equivalent UHT concentrate is more difficult. UHT sterilised concentrate is very susceptible to premature age-gelation and stringent conditions must be applied to the raw material to avoid contamination with bacterial proteinase. 27.7.5 UHT processed milks and creams UHT treatment is based on the principle that the thermal characteristics of bacterial destruction are substantially different from the rates of chemical reaction. By increasing the temperature of heat treatment and reducing exposure time (e.g. to 4 s at 142 ëC), equivalent bacterial lethality can be maintained to that used in heat sterilising canned milk or cream but with a significant reduction in chemical interaction such as Maillard browning. In UHT milk, the main cause of premature spoilage is a result of proteolytic action. Two sources of heat-stable enzyme can cause problems. Although plasmin has been implicated, its concentration in mid-lactation milk from normal, healthy cows is low and it is likely to be of secondary importance in spoilage. On the other hand, enzyme from psychrotrophic bacteria is important and the general rule is that product should not be manufactured from raw milk in which the bacterial load exceeds 106 cfu mlÿ1. The shelf life of UHT cream is substantially shorter than that of milk even when proteolysis is absent. For UHT single cream (18% butterfat), the main customer complaint is associated with feathering when the cream is added to hot coffee. The problem has been identified as one of calcium-induced aggregation

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and can be ameliorated, but not overcome, by the careful use of mineral stabilisers that interact with calcium. In commercial practice, additions of sodium carbonate and tri-sodium citrate have been found to extend the period before the onset of feathering in hot coffee. Storage temperature also has a significant effect on shelf life and, although not necessary for bacteriological stability, refrigeration promotes a marked improvement in shelf life. 27.7.6 Cream liqueurs Cream liqueur is a class of compound beverage containing a substantial proportion of dairy ingredients, e.g. 16% butterfat and 3% sodium caseinate. Shelf life is determined by the onset of gelation, by creaming and fat plugging and, infrequently, by precipitation of calcium citrate-rich deposits. The liqueurs are made by emulsifying cream in a solution of sodium caseinate to yield a dispersion of fat particles. Sugar, colour and flavour are then added and the mixture treated by severe homogenisation to obtain a very fine dispersion of the fat. Creaming during storage is related to the efficiency of homogenisation and it has been established that, by ensuring that all fat particles are less than 0.8 m in diameter, creaming does not occur on extended storage. The second problem which may limit the shelf life of liqueurs is the onset of gelation. This defect is associated with calcium interactions with milk protein and can be avoided by addition of tri-sodium citrate, reduction of the calcium content of cream (e.g., by increasing the fat content), by the use of anhydrous milk fat as a lipid source, or by use of the citric acid ester of glycerol monostearate to replace some of the protein present for emulsification. The third defect of cream liqueurs is associated with the use of tri-sodium citrate as an inhibitor of age-gelation. On prolonged storage, crystalline particles may form a deposit, largely of calcium citrate. This salt becomes progressively less soluble as temperature increases and its formation can be slowed by reducing processing temperatures after citrate addition or by reduction of the concentration of added salt. 27.7.7 Cheese Cheese is a family of products ranging in shelf life from several days to many years. It is thus difficult to generalise and, for this reason, only a single type ± Cheddar ± representing the most popular variety consumed in the UK and the most important cheese in international trade will be considered here. The standard of identity limits the moisture to an upper limit of 36% and the fat in dry matter to a minimum of 48%. Nevertheless, the `Cheddar' label spans a wide range both in terms of flavour and texture. The major classification is on the basis of maturity. `Mild' Cheddar may have been matured for only 3 months while `extra-mature' cheese may be 18±24 months' old. The time that a cheese spends at the optimum acceptability depends heavily on the type. For example, mild cheese may have an optimum acceptability after maturation for 3 months

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but flavour development may then proceed so rapidly that by 4 months the product has developed so much flavour (and of an atypical or unbalanced nature) that it is unacceptable to the average consumer. In contrast, a cheese that reaches optimum flavour after maturation for 18 months may continue to mature slowly and be perfectly acceptable after maturation for 2 years. As a result, shelf life has little general meaning in the context of cheese ripening. The complexity of flavour development in cheese lies in the fact that it is a biologically and chemically active product. Manufacture is simple in theory but complex in practice. A lactic acid starter culture is added to heat-treated milk and, after a short ripening period during which the pH drops, the milk is coagulated by addition of rennet. The active ingredient of rennet is the enzyme Chymosin that cleaves the -casein specifically. This action results in destabilisation of the micellar casein in the presence of calcium ± in large excess in acidified milk ± and a protein gel forms in which milk fat globules are entrapped. The coagulum or cheese curd is then cut into small pieces, and syneresis is encouraged by scalding, stirring and piling of the curd. After further curd processing and salting, the curd is pressed. The pressed curd is then ripened by storage in permeable packaging at between 6 and 12 ëC (sometimes complex temperature profiles are used). During ripening, simultaneous reactions occur which lead to breakdown of the curd texture and development of flavour. Proteolysis is the key reaction controlling maturation rate but its origin and control are complex. Lipase action plays a secondary role in flavour development in Cheddar cheese but is important in other varieties, e.g., Parmiggiano Reggiano. In Cheddar cheese excessive bacterial lipase activity produces cheese with undesirable rancid or soapy flavour attributes. Clear guidelines for the relation between bacterial load in raw milk and off-flavour development associated with excessive lipolysis in Cheddar cheese have been established. Rancid flavours developed in cheese after only 16 weeks' storage when the psychrotroph count of the raw milk used for manufacture reached a threshold of between 2  106 and 8  106 cfu mlÿ1. The perception of the maturity of Cheddar cheese is closely related to flavour and aroma intensity which are, in turn, associated with the extent of protein breakdown. Nevertheless, the quality of the cheese depends on the flavour balance. For example, a high quality vintage Cheddar will possess a complex mixture of flavour attributes but none to excess. In isolation, acid, bitter, sulphur, fruity or faecal flavours will render cheese of restricted acceptability yet the presence of such attributes at low levels combined with creamy and nutty flavour notes add to the desirability of a fine strongly flavoured product. The maturation rate of cheese depends not only on the amount and type of enzyme present but also on the composition of the product, because composition determines the environment in which enzyme (and subsequent chemical) activity can be expressed. Guidelines proposed by the New Zealand Dairy Research Institute relate cheese composition to the ultimate quality of long-hold mature product and these have stood the test of time. The compositional ranges for first and

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Fig. 27.2 Boundary composition for manufacture of long-hold, premium quality Cheddar cheese. Adapted from Gilles and Lawrence (1973). MNFS ˆ moisture in non-fat solids; FDM ˆ fat in dry matter; S/M ˆ salt in moisture; pH ˆ pH of cheese. Inner ring ˆ premium grade; outer ring ˆ first grade.

premium grade cheese are shown schematically in Fig. 27.2. Four factors are important: salt in moisture (S/M), moisture in non-fat solids (MNFS), fat in dry matter (FDM) and pH. It has been found both in New Zealand and in the UK that by careful control of cheese composition, optimal quality and shelf life can be attained. The enzyme nature and activity together with the environment (determined by composition) determine flavour compounds or their precursors. Although the role of some chemical components in flavour development is known (e.g., sulphydryl compounds and eggy character, hydrophobic peptides and bitterness or fatty acid esters and fruity character), the impact of many other chemical compounds remains unresolved. Although space does not permit detailed consideration of other cheese varieties, similar principles apply, i.e. shelf life is controlled by initial composition and by subsequent proteolysis. Flavour defects are usually associated with either residual enzyme activity derived from psychrotrophic bacteria or by a gross imbalance in initial composition.

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777

Conclusions

The examples given illustrate the complexity of control of the shelf life of intermediate and long life dairy products. Each type of product is associated with specific problems and the critical control points may be different for apparently similar defects. Some defects, such as those associated with enzymic degradation, are common to a range of goods. Clearly, raw material quality is paramount. The available evidence has implicated the heat-stable extra-cellular enzymes of the common psychrotrophic bacteria found in milk with both proteolytic and lipolytic defects. Manufacturers of long life products would therefore be well advised to ensure that the psychrotroph count is not allowed to exceed a level of 106 cfu mlÿ1 if they wish to avoid potential problems. In contrast to short shelf life products, chemical reactions can limit the durability of long shelf life products. High fat products are prone to oxidation and, short of excluding oxygen and controlling storage temperature, there is little scope for significant alleviation of the problem. The other major chemical reaction limiting shelf life in several products is calcium-induced aggregation of milk protein. Unlike fat oxidation, control of this problem is often possible. Modifications to processing conditions, especially those involving heat treatment and homogenisation, are often successful and the addition of the appropriate mineral stabiliser can often be effective. Cheese poses a particular problem for not only is composition important but the starter culture and coagulant used significantly affect the rate of ripening. It is perhaps inappropriate to define a shelf life for cheese since many varieties are acceptable to the consumer for a large part of their maturation period ± albeit with sub-optimal flavour or texture. In conclusion, no panacea can be provided for control of the shelf life of dairy products. Each must be considered in turn and, as new products are developed, it is anticipated that further problems will emerge.

27.9

Dedication

The contribution of Dr Jean M. Banks, to the original work on which this revision is based, is gratefully acknowledged.

27.10

Bibliography

(1988), Ultra-High-Temperature Processing of Milk and Milk Products. Reading, Elsevier Applied Science. CROSS HR and OVERBY AJ (1988), Meat Science, Milk Science and Technology. Amsterdam, Elsevier Science Publishers BV. FOX PF (1995a), Cheese: Chemistry, Physics and Microbiology, Volume 1 General Aspects, 2nd edn. Cork, Springer. BURTON H

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(1995b), Cheese: Chemistry, Physics and Microbiology, Volume 2 Major Cheese Groups, 3rd edn. Cork, Springer. GILLES J and LAWRENCE RC (1973), New Zealand Journal of Dairy Science and Technology 8 148±151. GOMLEY T R (1990), Chilled Foods. The State of the Art. London, Elsevier Applied Science. HORNE DS, LEAVER J and MUIR DD (1997), Caseins and Caseinates: Structures, Interactions, Networks. Hannah Symposium. International Dairy Journal incorporating Netherlands Milk & Dairy Journal, Special Issue, 1999, 9(3/6) 161±417. JEREMIAH LE (1995), Freezing Effects on Food Quality. New York, Marcel Dekker. LAW BA (1997), Microbiology and Biochemistry of Cheese and Fermented Milk, 2nd edn. Berlin, Springer. MCKELLAR RC (1989), Enzymes of Psychrotrophs in Raw Food. Boca Raton, FL, CRC Press. MUIR DD (1996a), The shelf-life of dairy products. 1. Factors influencing raw milk and fresh products. Journal of the Society of Dairy Technology 49(1) 24±32. MUIR DD (1996b) The shelf-life of dairy products. 2. Raw milk and fresh products. Journal of the Society of Dairy Technology 49(2) 44±48. MUIR DD (1996c) The shelf-life of dairy products. 3. Factors influencing intermediate and long life dairy products. Journal of the Society of Dairy Technology 49(3) 67±72. MUIR DD (1996d) The shelf-life of dairy products. 4. Intermediate and long life dairy products. Journal of the Society of Dairy Technology 49(4) 119±124. MULDER K and WALSTA P (1974) The Milk Fat Globule: Emulsion Science as Applied to Milk Products and Comparable Foods. Wageningen, Pudoc, CAB. RENNER E (1989) Micronutrients in Milk and Milk-based Food Products. London, Elsevier Applied Science. SPREER E (1998), Milk and Dairy Product Technology. New York, Marcel Dekker. TAMIME AY (2009a) Dairy Fats and Related Products. Chichester, Wiley-Blackwell. TAMIME AY (2009b) Dairy Powders and Concentrated Products. Chichester, WileyBlackwell. TAMIME AY and ROBINSON RK (2007) Yogurt Science and Technology, 3rd edn. Cambridge, Woodhead Publishing. TOUCH V and DEETH HC (2009), `Microbiology of raw and market milks', in Tamime AY Milk Processing and Quality Management. Chichester, Wiley-Blackwell, 48±71. FOX PF

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28 The stability and shelf life of seafood F. ToldraÂ, Institute of Agro-chemical Technology and Food (CSIC), Spain and M. Reig, Universidad PoliteÂcnica de Valencia, Spain

Abstract: Spoilage is a natural process where the seafood experiences a deterioration, starting with loss of color and taste, followed by changes in texture and color as well as development of off-flavors. The spoilage is mainly due to the action of microorganisms and endogenous enzymes. The numerous biochemical reactions (proteolysis, lipolysis, glycolysis and oxidation) taking place in post-mortem muscle and the main methodologies used to evaluate shelf life ± analysis of generated biogenic amines, total volatile bases and trimethylamine, nucleotides and nucleosides, the assessment of changes in color and texture, sensory analysis, sensors for specific properties and the analysis of microorganisms involved ± are briefly described in this chapter. Key words: seafood shelf life, fish shelf life, seafood spoilage, off-flavors, amines.

28.1

Introduction

Large varieties of species are consumed as seafood and within each species lay many further variables. There are thousands of species of fish, for example, but the differences in their age and weight when captured are huge. The composition and potential presence of contaminants in seafood also depend on the areas where they are caught (in the case of wild fish) or the type of feed they are given (in the case of aquaculture). There are, therefore, many sequential problems related to the shelf life of seafood, such as the origin, where and how the seafood was captured, the methods of transportation and further processing before they reached the manufacturing industry stage and finally the method of commercial

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distribution. A good knowledge of the changes due to biochemical and microbial reactions may therefore contribute to reduce the perishability of seafoods.

28.2

Factors affecting the stability and shelf life of seafood

Spoilage is a natural process in which seafood deteriorates, starting with a loss of color and taste and followed by changes in texture and color as well as the development of off-flavors. The spoilage is mainly due to the actions of microorganisms and endogenous enzymes and is closely related to the shelf life. Fish captured in the ocean are usually exhausted of glycogen because of the intense exercise. They lack the ability to generate lactic acid in post-mortem muscle which leaves their pH level near neutrality, a favorable condition for microbial growth. Physical damage from handling can also increase the spoilage rate. In general, the spoilage is slower in large fish than in small fish and lean fish tend to be less spoiled than fatty fish (Hyldig et al., 2007a). Thicker skins protect better from microorganisms than thinner ones. Numerous biochemical reactions like proteolysis, lipolysis, glycolysis and oxidation take place in post-mortem muscle (Nielsen and Nielsen, 2006) and, depending on their rate and intensity, the shelf life will vary. These biochemical reactions are briefly described below. 28.2.1 Proteolysis Proteolysis is a biochemical phenomenon consisting of the degradation of proteins and the generation of small peptides and free amino acids. Muscle proteases, mainly cathepsins B and L, which are active at slight acid conditions, and calpains, which are active at neutral pH, are able to act at the pH found in post-mortem fish and break down the structural myofibrillar proteins generating large peptides and protein fragments. This breakdown has a softening effect on the texture of the fish. Further problems ensue if these large peptides become hydrolyzed by muscle peptidases which generate small peptides and free amino acids. These can be used as substrates by microorganisms for growing and/or transforming amino acids into other compounds like biogenic amines or offflavors like ammonia. Proteolysis constitutes an important group of reactions during fish processing. In fact, proteolysis has a high impact on texture and, thus, the tendency of fish towards softness because it contributes to the breakdown of the myofibrillar proteins responsible for muscle network. Proteolysis also generates peptides and free amino acids that have a direct influence on taste and act as substrates for further reactions contributing to aroma (ToldraÂ, 2006; Toldra et al., 2009). In general, proteolysis has sequential stages. First, calpains and cathepsins act on major myofibrillar proteins generating protein fragments and intermediate-size polypeptides. These generate fragments and polypeptides are then further hydrolyzed to small peptides by di- and tri-peptidylpeptidases. Finally, dipeptidases, aminopeptidases and carboxypeptidases act on those small peptides to

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generate free amino acids. The role of 20S proteasome, even detected in fish muscles, has not been further clarified (Nielsen and Nielsen, 2006). Proteomics is bringing new analytical tools to the analysis of the breakdown of proteins in post-mortem muscle (Hollung et al., 2009). The progress of proteolysis varies depending on the processing conditions, the type of muscle and the amount of endogenous proteolytic enzymes. For instance, the increase in temperature favors the enzymatic action and a slightly acid pH would enhance the activity of lysosomal cathepsins. The junction between the myofibrils and connective tissue is also hydrolyzed by proteases (Taylor et al., 2002). Collagen fibres can also be degraded by proteases and affect the texture of the fish (Sato et al., 2002). 28.2.2 Lipolysis Enzymes involved in lipolysis are characterized as having the ability to degrade lipids. These enzymes receive different names depending on their mode of action. Lipase enzymes are those enzymes which act against triacylglycerols and are able to release long chain fatty acids. Esterase enzymes hydrolyze short chain fatty acids. Phospholipases are found in the skeletal muscle and hydrolyze fatty acids at positions 1 or 2 in phospholipids (Aaen et al., 1995). The main enzymes are lysosomal acid lipase and acid phospholipase, both located in the lysosomes and having optimal acid pH within the range 4.5±5.5. These lipases are able to generate long chain free fatty acids in positions 1 or 3 of triacylglycerols, which is the case with the lysosomal acid lipase (Fowler and Brown, 1984) or in position 1 of phospholipids for the acid phospholipase. Lysosomal acid lipase may also hydrolyze di- and monoacylglycerols, but at a lower rate (Imanaka et al., 1985; Negre et al., 1985). These enzymes exhibit higher activity in oxidative muscles than in glycolytic muscles. Large variations in the lipase activity of different fish species have been reported (Nayak et al., 2003). Lipolysis is a very important contributory factor to the quality of fish and seafood products. Free fatty acids are generated during this process and these, along with polyunsaturates (which are abundant in fish), may be further oxidized to create volatile compounds with rancid (i.e., hexanal) or unpleasant aromas which may impair the sensory quality of the fish. In addition, an excess of lipolysis generates a large number of free fatty acids that may then be oxidized and produce the development of yellowish colors in fat. 28.2.3 Oxidative reactions The lipolysis and generation of free polyunsaturated fatty acids, susceptible to oxidation, constitute a key stage in flavor generation. The susceptibility of fatty acids to oxidation and the rate at which they degenerate depend on the unsaturation (Shahidi, 1998a). So, linolenic acid (C18:3) is more susceptible than linoleic acid (C18:2) and this is more susceptible than oleic acid (C18:1). Oxidation has three consecutive stages (Shahidi, 1998b). First is the initiation, which consists of the formation of free radicals being catalyzed either

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enzymatically by muscle lipoxygenase or chemically by light, moisture, heat and/or metallic cations. Two important pro-oxidants are hemoglobin and myoglobin which are especially abundant in darker muscles (Hui et al., 2006). The second stage, propagation, consists of the formation of peroxide radicals by the reaction of the free radicals with oxygen. When peroxide radicals react with double bonds, they form primary oxidation products or hydroxyperoxides which are very unstable. Many types of secondary oxidation products are released after the breakdown through a free radicals mechanism. Some of them are potent flavor-active compounds that can impart off-odors and off-flavors to seafoods during cooking or storage. The last stage of the oxidation process is the final oxidative reaction which occurs when these free radicals react to one another and thereby become inactive. Thus, the result of these oxidative reactions is the generation of volatile compounds responsible for the final positive aroma like some esters or the development of off-flavors usually rancid aromas like those attributed to hexanal. So, it is important to have a good control of these reactions because oxidation may give undesirable volatile compounds with unpleasant off-flavors. Lipid oxidation may also be related to protein oxidation so that some proteins cross-link and generate textural defects (Tironi et al., 2002). As mentioned above, enzyme oxidation is one of the relevant mechanisms. Endogenous lipoxygenase contains iron and catalyzes the incorporation of molecular oxygen in polyunsaturated fatty acids, especially arachidonic acid, and esters containing a Z,Z-1,4-pentadien (Marczy et al., 1995). They receive different names, 5, 12 and 15 lipoxygenase, depending on the position where oxygen is introduced. The final product is a conjugated hydroperoxide. They usually require mM concentrations of Ca+2, and their activity is stimulated by adenosine triphosphate (ATP) (Yamamoto, 1992). Lipoxygenase has been found to be stable during frozen storage and is responsible for rancidity development (Grossman et al., 1988). Some oxidation is needed to generate volatile compounds with desirable flavor properties. However, an excess of oxidation may lead to off-flavors, rancidity and yellow colors in fat. The primary oxidation products, or hydroperoxides, are flavorless, but the secondary oxidation products make a clear contribution to flavor. There are a wide variety of volatile compounds formed by oxidation of the unsaturated fatty acids. The most important are: · aliphatic hydrocarbons that result from autooxidation of the lipids, · alcohols, mainly originated by oxidative decomposition of certain lipids, · aldehydes, that can react with other components to produce flavor compounds, and · ketones produced either through -keto acid decarboxylation or through fatty acid -oxidation. Other compounds, like esters, may contribute to characteristic aromas (Shahidi et al., 1986). Oxidation rates may vary depending on the type of product or processing conditions. Processing conditions like curing or smoking also give a

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characteristic flavor to the product. Some caution must be taken, however, with the presence of polycyclic aromatic hydrocarbons (PAH) which are carcinogenic compounds generated during the incomplete pyrolysis of wood used to produce smoke (Varlet et al., 2010). Lipid oxidation may also be induced by processing treatments like irradiation or high pressure (Hui et al., 2006). 28.2.4 Off-flavors Some off-flavors may be detected at the levels of the product to be consumed due to the feed with certain organisms or specific compounds (Hyldig et al., 2007a). This is the case with the mineral oil off-flavor caused by a planktonic mollusk, the iodine-like flavor in some fish caused by compounds formed by algae, sponges and Bryozoa (Anthoni et al., 1990) and oil taint from hydrocarbons found in fish near oil spills (Martinsen et al., 1992). An ocean-like flavor may also be found in seafood, usually due to high concentrations of bromophenol compounds (Hyldig, 2007). These bromophenol compounds are present in marine algae (Whitfield et al., 1999). A muddy-earth tainted flavor may be found in freshwater fish (Howgate, 2004). This off-flavor appears to be related to the presence of microbial metabolites like geosmin and 2-methyl-isoborneol, which tend to accumulate in the lipids. The general schemes for the breakdown of nucleotides as well as proteolysis and lipolysis, followed by bacterial transformation reactions and oxidation, leading to the generation of off-flavors, are shown in Fig. 28.1.

28.3

Microorganisms involved in seafood spoilage

The most common seafood spoilage bacteria include the Pseudomonas fluorescens, P. putida, P. fragi and P. perolens, Alteromonas nigrifaciens, Shewanella putrefaciens, Brochothrix thermosphacta and B. campestris,

Fig. 28.1

Scheme of enzymatic reactions affecting shelf life by generation of off-flavors in postmortem seafoods.

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Photobacterium phosphorous, Aeromonas hydrophila and A. salmonicida and, finally, some lactic acid bacteria which can be associated to the storage of fish especially in vacuum or modified atmosphere packaging (Levin, 2010; Nychas and Drosinos, 2010). Foodborne pathogens include Vibrio parahaemolyticus, V. vulnificus and V. cholera, Listeria monocytogenes and Salmonella spp. Adequate methods for the detection of such microorganisms may be found in the standards produced by the International Organization for Standardization (ISO) like ISO/TS 21872-1:2007 for Vibrio parahaemolyticus, V. vulnificus and V. cholera, ISO 11290-1 and 11920-2 for Listeria monocytogenes and ISO 6579 for Salmonella (RodrõÂguez-LaÂzaro and HernaÂndez, 2010).

28.4

Evaluation of the shelf life of seafood

There are different methodologies which are used to evaluate shelf life. These include the analysis of certain chemicals like biogenic amines, total volatile bases and trimethylamine generated during post-mortem storage, the analysis of nucleotides and nucleosides, the assessment of changes in color and texture, sensory analysis (quality index methods), the use of sensors for specific properties and the analysis of microorganisms involved. Fish freshness is relevant not only for quality attributes for fresh consumption, but also for its quality and safety during further processing and commercialization (Barat et al., 2006). Shelf life is highly variable depending on the fish itself and the postmortem storage conditions. Methods to detect fish spoilage are briefly discussed below. 28.4.1 Analysis of generated chemical compounds Some chemical compounds are closely related to seafood spoilage. The most representative compounds are: · ammonia which is formed by bacterial deaminase action on certain free amino acids, · trimethylamine which is associated with the characteristic spoilage odor and is formed by bacterial reduction of trimethylaminoxide (TMAO) through the TMAO-ase demethylase, · the action of bacterial decarboxylases on certain amino acids like lysine, tyrosine, arginine or phenylalanine to generate biogenic amines like cadaverine, tyramine or phenylethylamine, · the action of bacterial enzymes on sulfur containing amino acids (i.e., cysteine or methionine) to generate unpleasant volatile compounds like hydrogen sulfide, mercaptans, etc., · microbial generation of volatile short chain acids like formic acid and acetic acid and · oxidation of fatty acids to develop rancid odors.

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Rapid methods to assess spoilage have been developed. The determination of biogenic amines can be performed with standardized high performance liquid chromatography (HPLC) methods (Ruiz-Capillas and JimeÂnez-Colmenero, 2010). The biogenic amine index is used as a criterion of fish spoilage based on the content of amines like histamine, cadaverine, putrescine, spermine and spermidine (Mietz and Karmas, 1977). The measurement of trimethylamine generated from trimethylaminoxide (TMAO) or dimethylamine and È zogul, formaldehyde can also be helpful to state the degree of spoilage (O 2010). The analysis of volatile compounds is also useful as a quality indicator (JoÂnsdoÂttir et al., 2008). Other authors consider the content of some biogenic amines as an indicator of fish freshness (Ruiz-Capillas and Moral, 2001). Total bases and trimethylamine may be extracted with solid phase microextraction (SPME) and afterwards analyzed by gas chromatography coupled to a flame ionization detector or even a mass spectrometer (Nychas and Drosinos, 2010). 28.4.2 The assessment of changes in color and texture The color of fish, as measured through a Minolta-type camera to obtain L, a and b values, tends to change from reddish to brownish during post-mortem storage, and the fish flesh appearance, as measured subjectively through sensory assesors, also changes from an initial bluish, translucent, smooth and shining appearance to an opaque aspect (Schubring, 2003). Measurements of firmness and parameters extracted from the stress relaxation curves are well correlated with texture attributes like firmness, dehydration or water loss and thus can be useful to establish a degree of freshness (Careche et al., 2003). 28.4.3 Analysis of nucleotides and nucleosides Adenosine triphosfate (ATP) experiences a rapid degradation to ADP and AMP through enzymatic action in post-mortem muscle. AMP is then enzymatically transformed into inosine monophosphate (IMP). Part of IMP remains accumulated in post-harvest fish while the rest is dephosphorilated into inosine at a slower rate (Massa et al., 2005). The disappearance of IMP has been linked with lack of freshness in some fish species. Further enzymatic action of the enzyme nucleoside phosphorylase transforms inosine into hypoxanthine, which can be further oxidized by the enzyme xanthine oxidase to xanthine and uric acid (Aristoy et al., 2010). The speed of each enzymatic reaction depends on the fish species. For instance, IMP remains in many fish species, while AMP is the major nucleotide in crustaceans (Mendes et al., 2001). The kinetics for the degradation of IMP vary depending on the fish species (Howgate, 2006). The variations in the content of IMP and the increase of its degradation products inosine and hypoxanthine during storage under refrigeration have been proposed È zogul et al., 2007). However, there are failures in using as freshness indicators (O these compounds individually as freshness indicators. The main reasons are due to effects of many variables like processing conditions, presence of bacteria,

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mechanical handling of fish, etc. (Surette et al., 1988). The next step, therefore, consists of the use of indexes measured as ratios which are found to be more useful. The K value is defined as the ratio of inosine and hypoxanthine in relation to the sum of ATP and its related compounds and has been used as one of the freshness indexes to evaluate the quality changes in post-harvest fish (Pacheco-Aguilar et al., 2000; Aubourg et al., 2007; Castillo-YaÂnÄez et al., 2007). Due to the rapid disappearance of ATP, ADP and AMP, early postmortem in all fish species, other indices have been proposed. A K 0 index or Ki index is defined as the ratio of inosine and hypoxanthine in relation to the sum of IMP ‡ inosine and hypoxanthine (Karube et al., 1984). Another ratio has also been used due to the constant increase of hypoxanthine during the post-mortem storage. This ratio of hypoxanthine to AMP is an alternative method of measuring fish freshness (Massa et al., 2002; MaÂrquez-RõÂos et al., 2007). 28.4.4 The use of sensors for specific properties Some sensors have been used and proposed for fast, low-cost, non-destructive fish freshness monitoring with the additional advantage that they can be used either in situ or on site in a wide range of situations. Electrical measurements like conductance or capacitance have been used to detect post-mortem changes caused by the disruption of cell membranes (OehlenschlaÈger, 2003). Potentiometry is very simple since it measures the electric potential of electrodes versus a reference electrode. It was successfully used recently with gold and silver wires for the analysis of the changes of sea bream stored under refrigeration, being well correlated with the Ki index (Gil et al., 2008). Furthermore, it could be a useful tool for a rapid measure of fish freshness (Barat et al., 2008). The dielectric properties of individual fish were measured using an open-ended coaxial sensor and data treated by multivariate analysis for an estimation of quality. The results consisted of a calibration equation to predict the number of days on ice using the quality index method (Kent et al., 2004). The color and turbidity of the mucus on the skin and the coarseness of muscle fibres on the surfaces of fillets can be calculated with image analysis (Kroeger, 2003). The degree of spoilage during chilled or frozen storage can be measured through visible spectroscopy by examining the changes in spectral images (Heia et al., 2003). The onset of fish spoilage has been followed by detecting volatile  lafsdoÂttir degradation compounds with electronic noses (Di Natale et al., 2001; O et al., 2003; Amari et al., 2006). Some authors have also proposed the use of multi-sensor devices to estimate fish freshness (Olafsdottir et al., 2004). 28.4.5 Quality index methods There are several quality index methods (QIM) which are easy to use and perform, but are, at the same time, very useful for an effective and objective sensory evaluation in order to grade the quality or to evaluate the remaining shelf life of refrigerated fish. The quality parameters are:

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color and appearance, mucus, odor and texture of skin, pupils and form of eyes, color and appearance of mucus and odor of gills and odor and presence of blood in abdomen (Hyldig et al., 2007b).

Each parameter is given a description and a score between 0 and 3. Further description of QIM methods applied to different fish species can be found elsewhere (Hyldig et al., 2010). The EU scheme and the standards established for certain fishery products, as described by the European Council Regulation 2406/96, can be used at points of sale and evaluate not only freshness, but also other attributes like the presence of parasites, injuries, etc. Other methods to detect the spoilage status include the measurement of the refractive index of eye fluid so that four categories (very good, fair to good, poor and not marketable) can be assigned depending on the refractive index value (Levin, 2010). 28.4.6 Analysis of microorganisms involved The growth of microorganisms in fish, mostly if they are Gram-negative bacteria, is an essential factor for shelf life. This flora can be detected either by measuring its metabolites like hydrogen sulfide or via semi-quantitative measurements based on color, fluorescence or short wavelength near infrared after growing in appropriate and specific growth mediums (Nychas and Drosinos, 2010). For instance, different substances can be added to associate to bacterial cells so that the color intensity is proportional to the measure of cell concentration in the fish under evaluation. Modern molecular techniques like polymerase chain reaction (PCR), reverse transcriptase (RT-PCR), ELISA tests and oligonucleotide probe have been developed and are currently used to detect main seafoodborne pathogens like Vibrio species, L. monocytogenes and È zogul, 2010; RodrõÂguez-LaÂzaro and HernaÂndez, 2010). Salmonella (O

28.5

Future trends

Further studies are needed to relate all the variables involved ranging from fish catching through transportation, processing and commercialization until reaching the consumer. It is also very important to have full characterization of the raw fish species. This is very important for fish grown through aquaculture, including farm systems, type of feeds, and presence of any contaminants or veterinary drugs. The concerns and negative attitude of consumers towards farmed fish must also be taken into account. Consumers associate farmed seafood with a loss of flavor and the possible presence of diseases as well as other ethical considerations like mass production and animal welfare (Olsson et al., 2006). Changing these views and attitudes is an important challenge for the aquaculture industry.

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Hygienic manipulation and strict cold preservation conditions are essential to slow down spoilage. The use of non-thermal technologies (i.e., high pressure or irradiation) and modified atmosphere packaging may also contribute to an extension of shelf life of several days even though caution must be taken to control side effects like excessive oxidation and rancid odors.

28.6

Sources of further information and advice

Further information may be found in the following books and reviews: Handbook of Meat, Poultry and Seafood Quality, edited by LML Nollet, T Boylston, F Chen, PC Coggins, MB Gloria, G Hyldig, CR Kerth, LH McKee and YH Hui. Wiley-Blackwell, Ames, IA, 2007. Food biochemistry and food processing, edited by YH Hui, WK Nip, LML Nollet, G Paliyath and BK Simpson. Wiley-Blackwell, Ames, IA, 2006. Handbook of Analysis of Seafood and Seafood Products, edited by LML Nollet and F ToldraÂ. CRC Press, Boca Raton, FL, 2010. Handbook of Muscle Foods Analysis, edited by LML Nollet and F ToldraÂ. CRC Press, Boca Raton, FL, 2009.

28.7

References

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29 The stability and shelf life of meat and poultry M. G. O'Sullivan, University College Cork, Ireland

Abstract: This chapter begins by discussing the factors affecting the stability and shelf life of meat and poultry, including microbial loading and factors affecting meat colour, flavour and tenderness. The methods of shelf life analysis will then be reviewed for microbiological shelf life analysis as well as chemical and sensory analysis. Finally, the packaging of meat and poultry will be discussed, including the use of `high O2 MAP', `low O2 MAP' and `vacuum packaging' with respect to ensuring and extending shelf life, as well as future trends in packaging technologies. Key words: shelf life, microbial, chemical, sensory, modified atmosphere packaging (MAP).

29.1

Introduction

The factors that affect the shelf life and stability of meat and poultry are numerous, complex and interconnected. The manner in which meat is produced will ultimately affect shelf life and stability. As with any food product, food safety is the principal concern with producers, followed only then by sensory quality. Maintaining the appropriate level of hygiene pre- and post-production is essential to ensure the absence of pathogenic microorganisms and keeping the microbial loading within regulatory tolerance limits. Once manufactured the meat or poultry product must then be stored within specifications to obtain the desired shelf life. In the case of fresh meats and poultry this is generally done using refrigerated storage and in protective packaging such as modified atmosphere packaging (MAP). The storage conditions will then bring in to play various sensory factors that will affect the stability and shelf life of the product.

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The three sensory properties by which consumers most readily judge meat quality are: appearance, texture and flavour (Liu et al., 1995). Over the years producers have optimised these conditions to maintain food safety, but also to maintain optimal sensory quality. However, this is not always easy as optimising one sensory parameter can have a negative effect on another sensory parameter. The use of MAP for storage of meat highlights this issue. High O2 systems with atmospheres of O2 and carbon dioxide (CO2) higher than ambient levels are provided for red meat colour and inhibition of spoilage microorganism growth (McMillin, 2008). In European countries such as Ireland, UK and France, beef steaks are commonly displayed under 70% O2 and 30% CO2 concentrations in MAP, whereas the concentrations used in the USA are 80% O2 and 20% CO2. Oxygen functions to maintain myoglobin in its oxygenated form, carbon dioxide functions to inhibit the growth of aerobic spoilage bacteria and nitrogen acts as a filler gas to maintain pack shape. An oxygen-rich atmosphere (70± 80%) promotes the oxymyoglobin pigment of myoglobin (Zakrys et al., 2008) and gives a red colour in raw meat enjoyed by the consumers (Zakrys et al., 2009). However, this high O2 environment promotes lipid oxidation which can result in off-flavour development in the resulting cooked meat (Rhee and Ziprin, 1987; Estevez and Cava, 2004) as well as decreased tenderness due to protein oxidation (Zakrys et al., 2008, 2009). Torngren (2003) and Jayasingh et al. (2002) also reported that MA packing with O2 and CO2 decreased meat tenderness. Thus the desired food safety and colour sensory effects must be balanced against any negative effects caused by high levels of O2 and subsequent oxidation issues.

29.2 Factors affecting the stability and shelf life of meat and poultry 29.2.1 Microbial loading The species and population of microorganisms on meat are influenced by animal species; animal health, handling of live animals, slaughter practices; plant and personnel sanitation, and carcass chilling; fabrication sanitation, type of packaging, storage time, and storage temperature (Nottingham, 1982; Grau, 1986; McMillin, 2008). The safety of foodstuffs is ensured mainly by a preventive approach, such as implementation of good hygiene practice and application of procedures based on hazard analysis and critical control point (HACCP) principles (EC 2073/2005). Such practices ensure the absence of pathogenic microorganisms during production and minimise the microbial load within the regulatory guidelines. The European regulatory guidelines, EC 2073/2005, present comprehensive and specific tolerance limits for microbial loading by which meat and poultry production must comply. For example, the aerobic colony count for cattle, sheep, goats and horse carcasses after dressing, but before chilling, must not exceed 5.0 log cfu/cm2 daily mean log. For minced meat aerobic colony counts should not exceed 5  106 cfu/g, and 500 cfu/g for

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E. coli at the end of the manufacturing process. Salmonella must be absent in the carcasses of cattle, sheep, goats, horses and pigs after dressing but before chilling and absent in poultry carcasses of broilers and turkeys after chilling. The regulation also defines the sampling criteria which must be enforced for each specific meat and poultry product. The sampling rules for poultry carcasses, for example, for Salmonella analyses, a minimum of 15 carcasses shall be sampled at random during each sampling session and after chilling. A piece of approximately 10 g from neck skin shall be obtained from each carcass. On each occasion the neck skin samples from three carcasses shall be pooled before examination in order to form 5  25 g final samples. Salmonella must be absent from these pooled samples (EC 2073/2005). Meat products that may also contain nitrites include bacon, bologna, corned beef, frankfurters, luncheon meats, ham, fermented sausages, shelf-stable canned, cured meats, perishable canned, cured meat (e.g., ham) and a variety of fish and poultry products (Pennington, 1998). The shelf life of meats can be extended significantly by curing as the nitrate/nitrite has a strong anti-bacterial effect, particularly to the growth of Clostridium botulinum. Nitrite is strongly inhibitory to anaerobic bacteria, most importantly Clostridium botulinum and contributes to control of other microorganisms such as Listeria monocytogenes (Sebranek and Bacus, 2007). The packaging environment used for meat or poultry products has a specific effect on the microorganisms that grow in the product over the course of shelf life. Increased levels of CO2 inhibit microbial growth in refrigerated storage, with 20±40% CO2 used in MAP (Clark and Lentz, 1969). Levels of 20±60% CO2 are required for effectiveness against aerobic spoilage organisms by penetrating membranes and lowering intracellular pH (Smith et al., 1990), High O2 modified atmosphere packaged meat spoils aerobically with the spoilage flora being dominated by Pseudomonas. Oxygen also stimulates the growth of aerobic bacteria and inhibits the growth of anaerobes (McMillin, 2008). One major concern in MAP containing CO2 is the inhibition of normal aerobic spoilage bacteria and the possible growth of psychrotrophic food pathogens, which may result in the food becoming unsafe for consumption before it appears to be organoleptically unacceptable (Devlieghere et al., 2003). From a microbial loading perspective Zakrys-Walliwander et al. (2011a) showed that microbiological growth of lactic acid bacteria (LAB) was the highest for commercially packaged sirloin steaks (75% O2, 25% CO2, 5% N2) in comparison to non-commercially packaged samples (80% O2, 70% O2 and 50% O2). Thus, LAB bacteria were dominant in MAP meats and due to their metabolic activity the spoilage appeared as off-flavours and off-odours. Consequently commercially packaged beef steaks were the least acceptable by sensory naive assessors in comparison to other modified atmosphere packaged samples. This is an important finding which suggests that slightly better plant hygiene in this case, especially with respect to LAB bacteria, could have a beneficial effect on the subsequent consumer quality of the meat packaged under MAP conditions.

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29.2.2 Factors affecting meat colour One of the primary purchase criteria of fresh meat is meat colour. In red meats, consumers relate the bright red colour to freshness, while discriminating against meat that has turned brown in colour (Hood and Riordan, 1973; Morrissey et al., 1994). This is more an issue with red meat due to the greater concentration of myoglobin present in the muscle compared to chicken, but poultry such as turkey, duck and ostrich have higher concentrations of myoglobin which can also make them susceptible to discolouration during retail display. Raw poultry can vary from blue white to yellow in colour for the white muscle such as breast meat and red in colour for thigh and leg meat due to varying myoblobin concentrations. Also the colour of chicken skin can vary depending on whether the birds have been fed conventionally or corn fed. The appearance of corn-fed poultry also differs in flesh colour from broilers fed on a standard wheat-based diet, not only because of the corn-rich diet, but also because of the addition of marigold to the feed (Kennedy et al., 2005). Skinless chicken breast meat has a neutral colour; however, the light source used in a meat display case can have a significant effect on the customer impression and decision to purchase fresh poultry. In terms of the buying decision, Barbut (2001b) found that there was a strong preference to buy chicken breast under fluorescent light compared to other light sources (incandescent or metal halide). Carpenter et al. (2001) noted a strong association between colour preference and purchasing intent with consumers discriminating against beef that is not red (i.e., beef that is purple or brown). Meat colour or bloom develops through interaction with the air which permeates the gas permeable packaging materials used to overwrap meat, with meat discolouration typically preceding lipid oxidation. Meat held in packs containing greater than 21% O2 may induce oxidative processes, thereby resulting in lipid oxidation (Jackson et al., 1992). Discolouration in retail meats during display conditions may occur as a combined function of muscle pigment oxidation (oxymyoglobin to metmyoglobin) and lipid oxidation in membrane phospholipids (Sherbeck et al., 1995). The muscle protein myoglobin is primarily responsible for beef colour, but also lamb and pork colour, but to a lesser extent, due to the proportionate lower levels of the myoglobin pigment in these respective muscles. The myoglobin pigment can exist in three forms; deoxymyoglobin (purple) is rapidly oxygenated to oxymyoglobin (cherry red) on exposure to air. As meat ages, myoglobin oxidises to metmyoglobin (brown) and this is associated with a lack of product freshness (Kropf, 1993). The degree of meat redness depends on the state of myoglobin oxygenation or oxidation (Fig. 29.1). High-oxygen atmospheres (80% O2), which are typically used to package beef cuts promote pigment oxygenation, which prolongs the period of time before metmyoglobin is visible on the muscle surface. Retail fresh meats, whole cuts or MAP, are usually presented to consumers in refrigerated retail display cabinets. The lighting of these cabinets will also affect colour shelf life and stability. Barbut (2001a) reported that incandescent light

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Fig. 29.1

797

Schematic diagram of oxidation of oxymyoglobin and deoxymyoglobin to metmyoglobin.

increased beef and pork colour desirability due to its spectrum consisting of more red wavelengths. Fluorescent lighting used in this study had virtually no luminance in the red region and, thus, the beef was considered less desirable than beef displayed under incandescent lighting. To maximise appearance, yet minimise photo-oxidation, recommended lighting is 1614 Lux (150 foot candles) of fluorescent lighting, which should have a colour temperature of 3000±3500 K (lamps such as Deluxe Warm White, Natural, Deluxe Cool White, SP 3000, SP 3500). Cool White or lamps giving unreal pink, blue, or green tints should be avoided (Mancini and Hunt, 2005). When conducting pilot shelf life experiments using meat, it is important to measure the lighting using a light intensity meter in the case of retail display cabinets and to also log temperature fluctuations using a data logger to ensure that readings are within required limits in order to acquire consistently reproducible data (Fig. 29.2).

Fig. 29.2 Retail display cabinet used to simulate commercial retail display conditions. It is important when using such equipment that the light intensity (LUX) is recorded as well as operating temperature fluctuations using a data logger.

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Finally, Carpenter et al. (2001) showed that once a decision to purchase beef is made in the market by the consumer, whether the beef is cherry red freshbloomed beef, the brown of discounted beef, or the purple of vacuum-packaged beef, eating satisfaction at home will depend only on the beef quality attributes of tenderness, juiciness, and flavour (Carpenter et al., 2001). 29.2.3 Factors affecting meat flavour Conditions that make some meat desirable and others undesirable are formed by many factors, including pre-harvest animal environment and diet, post-harvest handling and consumer preferences. Lipid oxidation reactions are free radical generating chain mechanisms that occur in the polyunsaturated fat that is present in muscle tissue which can result in off-flavour development in the resulting cooked meat. The concentration of polyunsaturated fat varies with species and is higher in poultry meat followed by pork, lamb and beef. Thus meats like chicken are particularly susceptible to lipid oxidation. Duck meat has higher lipid content than chicken and turkey meat and is more susceptible to oxidation as it contains high levels of unsaturated fatty acids (around 60% of total fatty acids) and also high levels of haemoglobin and myoglobin (BaeÂza et al., 2002). However, ostrich meat contains high amounts of polyunsaturated fatty acids compared to beef and chicken making it even more susceptible to oxidation (Horbanczuk et al., 1998; Sales and Oliver-Lyons, 1996). The proportion of polyunsaturated fat in muscle can also be altered by feed intervention. Feeding a more unsaturated diet will result in greater concentrations of polyunsaturated fat within the muscle tissue which in turn affects meat flavour and reduces oxidative stability. Lipid oxidation is a reaction that occurs in all MA packaged meats and its development depends on the level of oxygen that comes into contact with the polyunsaturated lipid fraction in meat, especially while contained within the primary pack. The breakdown products of lipid oxidation have been associated with the development of off-flavours, off-odours and loss of meat colour (Faustman and Cassens, 1989). Meat flavour develops during cooking when a complex of thermally-induced reactions occurs between non-volatile components of lean and fatty tissues, resulting in a large number of reaction products. Over 1000 volatile compounds have been identified in cooked meat (Elmore and Mottram, 2009). Typically fresh red meats are stored in MAP containing 80% O2 : 20% CO2 (Georgala and Davidson, 1970) and cooked meats are stored in 70% N2 : 30% CO2 (Smiddy et al., 2002). However, Zakrys et al. (2008) reported that sensory panellists expressed a preference for beef steaks stored in packs containing 50% O2 and 80% O2, despite detecting oxidised flavours under these conditions. In general, muscle foods are susceptible to oxidative activity of their lipid, protein, pigment, vitamin and carbohydrate composition (Kanner, 1994). The oxidation of polyunsaturated fatty acids in meat causes the rapid development of meat rancidity and also affects colour, nutritional quality and meat texture (Kanner, 1994; Zakrys et al., 2009). Lipid autoxidation causes flavour deteriora-

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tion and off-odours (Lillard, 1987) through a complex process whereby unsaturated fatty acids react with molecular O2 via free radical mechanisms to form fatty acyl hydroperoxides or peroxides (Gray, 1978). Factors influencing lipid oxidation include fatty acid composition, pro-oxidants, enzymes and heat (Lillard, 1987). Antioxidants are compounds that inhibit or retard the free radical generating chain mechanism of lipid oxidation (O'Sullivan et al., 1998). Dietary supplementation with the antioxidant vitamin E increases the concentration of tocopherol in muscle and reduces the susceptibility of the muscle to lipid oxidation (Morrissey et al., 1998). Many studies have been conducted on the basis that incorporation of -tocopherol in to the cell membrane will stabilise the membrane lipids and consequently enhance the quality of meat storage. Oxidation studies with chicken (Jensen et al., 1995), turkeys (Marusich et al., 1975), pigs (O'Sullivan et al., 1997, 1998), cattle (Faustman et al., 1989), veal (Shorland et al., 1981) and fish (Frigg et al., 1990) have all demonstrated reduced lipid oxidation in muscles and adipose tissue from animals supplemented with dietary -tocopherol compared to the same muscles from nonsupplemented animals. 29.2.4 Factors affecting meat tenderness Tenderness has often been described as the most important factor in terms of high eating quality, especially in beef and is principally an issue with red meats compared to poultry. It has been shown that a certain level of tenderness is crucial in order that meat quality can be acceptable (Huffman et al., 1996) and that tenderness of beef is such an important quality attribute to consumers that they are willing to pay more for this tenderness (Boleman et al., 1997). Tenderness of meat is also affected by aging, type of rigour (Pearson, 1987), chilling, freezing and storage. It is well established that stretching of the muscle by certain hanging methods (H-bone suspension) improves tenderness of meat. Stretched muscle has greater sarcomere lengths resulting in increased tenderness (Fisher et al., 2000). Rowe et al. (2004) reported that increased protein oxidation (PO) during the first 24 h post-mortem can substantially decrease beef tenderness even in steaks aged 14 days. Zakrys et al. (2008) evaluated the sensory scores of MAP beef M. longissiumus dorsi muscle stored under a range of atmospheres (0%, 10%, 20%, 50% and 80% O2), samples packed with 50% and 80% O2 were tougher than low O2 treated samples. Lund et al. (2007) investigated the effect of MAP (70% O2/30% CO2) and skin packaging (no O2) on protein oxidation and texture of pork M. longissimus dorsi muscle during storage for 14 days at 4 ëC and found that the high O2 atmosphere resulted in reduced tenderness and juiciness of the experimental meat samples. High O2 MAP has been shown to be detrimental to beef tenderness (Seyfert et al., 2005; Zakrys et al., 2010, 2011a,b) and pork due to protein cross-linking

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caused by oxidative processes (Lund et al., 2007; McMillin, 2008). Zakrys et al. (2011a) showed that protein oxidation increased cooked meat toughness due to storage in higher MAP oxygen atmospheres.

29.3

Evaluating the shelf life of meat and poultry

Factors involved in the evaluation of shelf life for meat and poultry must consider microbiological safety and spoilage issues initially and then physiochemical parameters. These parameters are ultimately expressed as the sensory quality changes of flavour, aroma, texture and after-taste in meat and poultry products. 29.3.1 Microbiological shelf life The microbiological stability of meat and poultry is the primary parameter by which shelf life is set for all foods. Shelf life is defined in the European legislation as the `date of minimum durability'. The date of minimum durability of a foodstuff is defined in Council Directive 2000/13/EC on the labelling, presentation and advertising of foodstuffs as the date until which a foodstuff retains its specific properties when properly stored. All prepackaged foods must be date-marked (unless exempt in the legislation) (FSAI, 2005). The date mark in European countries itself can be a `best before' or `use by' date. The `bestbefore' date will reflect the quality e.g. taste, aroma, appearance, rather than safety of a food product. A food which is past its `best-before' date may not necessarily be unsafe to consume but it may no longer be of optimum quality. Typically, a `best-before' date is required on products such as canned, dried and frozen foods (FSAI, 2005). Food products which, from a microbiological point of view, are highly perishable and are therefore likely, after a short period of time, to constitute a danger to human health must have a `use-by' date (EC No. 2000/13/EC). The `use-by' date will indicate the date up until which the product can be safely consumed. Therefore, unlike the `best-before' date, the accurate determination of the `use-by' date to ensure product safety is critical (EC No. 2073/2005). The microorganisms that are principally found on the surface of animal carcasses are Gram-negative bacteria such as Actinetobacter, Aeromonas, Pseudomonas, Moraxella, Enterobacter and Escherichia. Gram-positive organisms such as Bronchotrix, other lactic acid bacteria and Micrococcaceae can also be found. The microorganisms quantified, in order to set shelf life limits, will depend very much on the product. Each specific meat product will have its own defined set of microbiological tests that must be used to quantify shelf life. Samples are analysed at specific regular time points for counts of spoilage bacteria, at specific incubation temperatures, and when a maximum is reached a shelf life period may be determined. A safe margin of time should also be built in to the shelf life to ensure that the microbial count limits are not

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reached during the normal shelf life of the product. European Commission regulation No. 2073/2005 outlines the microbial testing criteria and methods for foodstuffs including meat and poultry products. Apart from spoilage organisms the regulation specifies the maximum counts for pathogenic microorganisms in meat and poultry products. In many cases the regulation specified the complete absence of pathogenic microorganisms in a known weight of product, e.g., minced meat products and meat preparations made from poultry meat placed on the market during their shelf life and intended to be eaten cooked should be completely absent for Salmonella in 25 g of product (EC No. 2073/2005). Challenge testing can be used to determine the likelihood of the growth of particular microorganisms, such as those causing food poisoning. In this case selected microorganisms are inoculated into products and the growth of these monitored through a storage test (Kilcast and Subramaniam, 2004). Challenge testing can also be applied to study the possibility of the growth of selected resistant spoilage organisms that may contaminate the food from the factory or production environment (Kilcast and Subramaniam, 2004). 29.3.2 Chemical analysis As mentioned in earlier sections of this chapter, lipid oxidation in meat and poultry products can lead to quality deterioration which has the potential of limiting shelf life from a colour and flavour perspective. This is more an issue with cooked meat and poultry products. Generally the product will be spoilt due to microbial action before oxidation becomes an issue. However, it is necessary to establish the oxidative stability of meat and poultry products and this will vary depending on the amount of polyunsaturated lipid present. The method of Tarladgis et al. (1960) is regarded as the standard method for malonaldehyde (MDA) analysis. This method uses distillation and spectrophotometric analysis to quantify malonaldehyde in lipid-containing foods. MDA is a major carbonyl decomposition product of autoxidised, polyunsaturated lipid materials (Crawford et al., 1966). In the reaction, one molecule of malonaldehyde reacts with two molecules of 2-thiobarbituric acid (TBA) to form a malonaldehyde±TBA complex, which allows the resultant pink pigment to be quantitated spectrophotometrically. A more rapid method of quantifying MDA in foods has been described by Siu and Draper (1978) for a TCA extraction method for measurement of lipid oxidation. Using either of the above methods it is typical to monitor oxidative stability of meat and poultry over the course of the shelf life of the product under defined storage temperature and conditions. A typical shelf life study might involve placing the product in a commercial retail display cabinet and tracking MDA formation periodically over time. The samples are placed in a retail refrigerated display cabinet (Fig. 29.2) at 5  1 ëC, under a defined light source strength fluorescent light (e.g., 100 Lux) for the storage period of the study (O'Sullivan et al., 2003a). Although there are no legal limits to the amount of MDA that can form in foods, above a certain level it may become objectionable to consumers and thus

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influence any repeat purchase. TBARS have been correlated to sensory determined rancidity. Greene and Cumuze (1982) state the general population of meat consumers would not detect oxidation flavours until oxidation products reached levels of at least 2.0 mg/kg tissue. Similarly Campo et al. (2006) reported that a TBARS value of 2.28 could be considered as the limiting threshold for acceptability of oxidation in beef. This value indicates the point where the perception of rancidity overpowers beef flavour. Zakrys et al. (2008) found that sensory panellists preferred steaks stored in 50% O2 even though oxidised flavours were detected which could be attributed to adaptation, or familiarity with, oxidised flavours in meat (Zakrys et al., 2008). Tarladgis et al. (1960) showed that threshold TBARS values of 0.5±1.0 for fresh ground pork were highly correlated (0.89) to intensity of rancid odour 1.0 by trained sensory panellists (Tarladgis et al., 1960). In contrast, Jayasingh and Cornforth (2004) presented data which showed that consumers preferred cooked pork patties with TBARS of less than 0.5 compared with patties that had TBARS numbers greater than 1.4. 29.3.3 Sensory analysis Once the microbial safety of meat and poultry products has been established over the course of a defined storage period and conditions, the next step is to assess the sensory shelf life of a product. As presented above, there are legal obligations by food business operators to sell meat and poultry products that are safe to consume. There are no defined set sensory limits for negative sensory parameters by which meat and poultry should be sold; in any case these would be very difficult if not almost impossible to set. However, it is in the commercial interest of meat and poultry product producers to sell their products with optimum sensory quality. Meat and poultry products once produced and packaged will change with respect to sensory parameters over the course of the shelf life period. As discussed above, colour may change due to metmyoglobin formation as in the case of red meats, and flavour can change through lipid oxidation and the formation of off-flavours, which will affect the more polyunsaturated poultry meat to a greater extent than red meats. Also, texture can change due to drip loss or through protein oxidation in high O2 atmospheres. These changes will affect the appeal of the product to the consumer in the case of colour and repeat purchase in the case of flavour and texture. When determining the sensory profile of meat and poultry products, samples should be stored in the designed shelf life storage conditions. Again this could be in a commercial refrigerated display cabinet under a defined Lux strength light source. The test samples should then be tested at regular intervals over the shelf life as determined by microbiological safety limits. There are two types of sensory methods that can be employed in the sensory evaluation of meat products and poultry products. These are `difference' testing and `descriptive attribute' testing. Difference testing can be categorised into overall difference tests, to determine whether a sensory difference is detectable between samples and attribute-

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specific directional difference tests which ask whether a specified attribute is perceived as different between samples. Difference tests include the triangle test, duo-trio test, simple same-difference test and `A'±`not A' test (Lawless and Heymann, 1998; Piggott et al., 1998). Descriptive analysis is a method which involves the training of panellists to quantify specific sensory attributes for appearance, flavour, texture and aftertaste. The sensory terms are produced in collaboration with the panellists and the panel leader for the QDA (qualitative data analysis) method, whereas the Spectrum method uses a strict technical sensory vocabulary using defined reference materials. Free choice profiling (FCP) can also be used and this involves panellists developing their own descriptive terms (Delahunty et al., 1997). Descriptive terms can be determined from lexicons which have been designed by a number of authors for the sensory evaluation of meat and poultry products; Byrne et al. (1999a) and O'Sullivan et al. (2003b) for pork, Johnson and Civille (1986) for beef, and Lyon (1987) and Byrne et al. (1999b) for chicken. The starting list of sensory terms is compiled by individuals with sufficient product knowledge, using these lexicons as a starting point along with any additional terms that are deemed relevant or useful. This is usually undertaken with a subset of samples, such as samples at the beginning or end of the shelf life period along with an intermediate sample or alternative muscle or meat cut, depending on the design, that reflect the sensory variation in the full samples set to be profiled. This meta-list of terms can then be reduced by sensory term reduction protocols (Byrne et al., 1999a,b, 2001; O'Sullivan et al., 2003b,c). These sensory terms should fit the purpose of the analysis, correspond to the samples, have relevant definitions (Civille and Lawless, 1986; Civille, 1987; Piggott, 1991), must allow differentiation between sensations, identification of the object it describes, and recognition of the object by others seeing the term (Harper et al., 1974). In summary, the criteria by which a sensory term can be used in a sensory profile include: · · · ·

the sensory terms selected must be relevant to the samples, discriminate between the samples, have cognitive clarity and be non-redundant (Byrne et al., 1999a,b, 2001; O'Sullivan et al., 2003b,c).

The final sensory profile will display quantifiable sensory changes in meat or poultry products over the course of the shelf life, which is an important tool in defining sensory shelf life changes over time, but this does not reflect consumer sentiment or acceptance of these products. Consumer sensory assessment employing untrained or naõÈve assessors using simplified attribute lists can be used to measure consumer product acceptance or preference. Zakrys et al. (2009) used 134 consumers to evaluate MAP beef steaks (40%, 50%, 60%, 70% and 80% O2) which were stored at 4 ëC for 12 days. The consumers indicated a directional preference for steaks (which were cooked prior to evaluation) stored in packs containing 40% and 80% O2 and that higher O2 levels, greater than 40%, imparted greater meat toughness as determined by these consumers.

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29.4 Ensuring stability and extending the shelf life of meat and poultry 29.4.1 Packaging Consumer desire and demand for a wide range of fresh and minimally processed foods inspire food researchers to improve food quality, freshness and increase the shelf life of such products. The packaging of muscle-based foods is necessary to ensure that such products reach the consumer in a condition that satisfies the demands of the consumer on a number of levels, namely: nutrition, quality, safety, and convenience, as well as the ability to deliver a product shelf life that will endure the stresses of handling, transportation, storage, sale, and consumer contact. Food packaging of fresh muscle foods is carried out to avoid contamination, delay spoilage, permit some enzymatic activity to improve tenderness, reduce weight loss, and where applicable, to ensure a cherry-red colour in red meats at retail or consumer level (Brody, 1997; Zakrys et al., 2009). Fresh red meats may simply be placed on trays and over-wrapped with an oxygenpermeable film, or placed within a gaseous-modified atmosphere or vacuum packaged. Similarly cooked meats may be sold in a vacuum packaged format or gas flushed with CO2. There are four categories of preservative packaging that can be used with raw muscle foods. These are high oxygen modified atmosphere packs (high O2 MAP), low oxygen modified atmosphere packs (low O2 MAP), controlled atmosphere packs (CAP) (Gill and Gill, 2005) and vacuum packs (VP). Modern meat packaging methods maintain a low microbial load while optimising the sensory quality of a product. 29.4.2 High O2 modified atmosphere packs (MAP) MAP is defined as `a form of packaging involving the removal of air from the pack and its replacement with a single gas or mixture of gases' (Parry, 1993). MA packs usually contain mixtures of two or three gases: O2 (to enhance colour stability), CO2 (to inhibit microbiological growth), and N2 (to maintain pack shape) (Sùrheim et al., 1999; Jakobsen and Bertelsen, 2000; Kerry et al., 2006). Figure 29.3 displays pilot scale MA packaging equipment that allows packs to be flushed with varying levels of O2, CO2 and N2. The vast majority of meat products have been and continue to be offered in high oxygen pack formats (approximately 80% O2) in order to maintain bloom, with at least 20% CO2 to prevent selective microbial growth (Eilert, 2005). Typically, fresh red meats are stored in MAP containing 80% O2:20% CO2 (Georgala and Davidson, 1970), while cooked meat equivalents are stored in 70% N2:30% CO2 (Smiddy et al., 2002). High O2 concentrations in MAP packs promote the formation of oxymyoglobin (OxyMb) which is the cherry red form of myoglobin that is so appealing to the consumer and has a large influence on their desire to purchase. Despite increasing colour stability, this type of MAP has several detrimental quality effects, including premature browning of cooked meat, lipid oxidation which leads to development of undesirable flavours (Rhee and Ziprin, 1987;

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Fig. 29.3 Pilot scale MA packaging equipment that allows packs to be flushed with varying levels of O2, CO2 and N2. This equipment can also handle different pack sizes.

Estevez and Cava, 2004) and reduced tenderness (Lund et al., 2007; Mancini and Hunt, 2005). Meat in packages with greater than 21% O2 may induce oxidative processes and lipid oxidation can be a problem with meat in high O2 MAP (Jackson et al., 1992). Packaging under high O2 atmospheres increases lipid oxidation in beef (Jakobsen and Bertelsen, 2000; Zakrys et al., 2008, 2009); pork (Lund et al., 2007); and lamb (Kerry et al., 2000). The oxidation of polyunsaturated fatty acids, not only causes the rapid development of meat rancidity, but also affects the colour, the nutritional quality and the texture of beef (Kanner, 1994). Discolouration in retail meats during display conditions may occur as a combined function of muscle pigment oxidation (oxymyoglobin to metmyoglobin) and lipid oxidation in membrane phospholipids (Sherbeck et al., 1995).

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Packaging beef in MA packs and storing at low temperatures extends the product shelf life considerably (Young et al., 1983). MAP is one of the principal methods of maintaining and prolonging meat colour sensory quality. Beef and lamb are both red meats and share similar properties, but considerable differences in shelf lives are apparent between them due to their relative susceptibility to chemical and microbial spoilage. MAP is recognised as one of the most effective methods for shelf life extension of fresh meat and is widely used by the industry to reduce spoilage of minced meat (Koutsoumanis et al., 2008). In contrast to beef cuts, much of the surface of lamb is adipose tissue, which has a pH close to neutrality and has no significant respiratory activity (Robertson, 2006). The pH of beef is lower than that of lamb, thus making it less susceptible to microbial spoilage (Gill, 1989; Kerry et al., 2000). In order to optimise shelf life, sensory quality, and microbiological safety using MAP, the packaging system applied must be product specific (Church and Parsons, 1995). High O2 concentrations can also cause protein oxidation which has been shown to be detrimental for tenderness of beef and linked to increased toughness in MAP meat (Seyfert et al., 2005). Thus, protein oxidation may decrease eating quality by reducing tenderness and juiciness and enhancing flavour deterioration and discolouration (Xiong, 2000). Zakrys et al. (2009) showed that high O2 concentrations in MAP stored beef steaks had increased toughness scores after cooking, as determined by 134 consumers. As consumers use meat colour as a primary indicator of freshness and meat quality at the point of purchase, recent advances in MAP have focused on finding the correct blend of gases that maximises initial colour, colour stability, and shelf life, while also minimising microbial growth, lipid oxidation and gaseous headspace (Mancini and Hunt, 2005). Jakobsen and Bertelsen (2000) reported that while O2 levels higher than 20% were necessary to promote meat colour, package O2 contents higher than 55% did not result in additional colour stabilising benefits. Zakrys et al. (2008) showed that packaging beef steaks in MAP with 50% O2 promoted the overall quality of the product over its shelf life. With respect to poultry meat, Seydim et al. (2006) used high O2 atmospheres for packaging of ostrich meat and found that this reduced the shelf life to less than 3 days based on the results of lipid oxidation (TBA values and hexanal content) and loss in colour (redness). Lipid oxidation was the probable limiting shelf life factor for this high heme iron-containing meat. 29.4.3 Low O2 modified atmosphere packs (MAP) Low O2 MAP are generally packed with CO2 (usually enough to dissolve into the product) and also N2, while residual O2 may be present or included during the packing process. The CO2 acts as the antimicrobial and N2 as the pack shape stabiliser (Sùrheim et al., 1997). Low O2 packaging systems have been readily available for usage in the United States, but are not as widely implemented as their high O2 counterparts (Eilert, 2005). The absence of O2 in an O2-free MAP or controlled atmosphere packaging (CAP) system results in a significant shelf

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life extension, as these packaging formats offer hostile environments to obligate aerobic spoilage microorganisms. CAP packaging has been used commercially for shipment of chilled lamb to distant markets (Gill, 1989). However, CO2 may cause off-flavor or CO2 taint in the meat, which can be detected upon consumption (Nattress and Jeremiah, 2000). A lowering of meat pH is a result of CO2 absorption into the meat and is a consequence of carbonic acid being dissociated to bicarbonate and hydrogen ions (Dixon and Kell, 1989). CO2 is highly soluble in water, most of which is contained in the muscle, and also in fat tissue. This solubility is increased with decreasing temperature. When an atmosphere rich in CO2 is used, the high solubility of the gas in meat tissues must be taken into account (Gill, 2003). O'Sullivan et al. (2011) explored offflavour development by CO2 in commercial MAP CO2 and packs containing 100% CO2 using 10 trained panellists. `CO2 flavour' increased over time for all treatments and also directionally the most CO2 off-flavours were found in the samples cooked immediately after opening MA packs and also in the meat packed under 100% CO2. The presence of either low or residual concentrations of O2 produces the grey/brown oxidised metmyoglobin (MMb). Therefore, in some countries that utilise low O2 MAP, it is permissible to use carbon monoxide (CO) gas for meat colour enhancement and stabilisation. Within the EU, only Norway adopted the use of CO (0.3±0.5%) in primary packs in the mid-1980s; however, this practice has since ceased following a decision by the EU Parliament committee in 2004 not to allow the use of CO in meat packaging applications. However, in the United States, carbon monoxide (CO) may be used as a gas for meat colour enhancement as the FDA has approved the use of CO in low O2 beef packs. Industrially, CO has been added to beef packages to eliminate the disadvantages of commercial ultra-low O2 MAP because CO has a high affinity for myoglobin and forms a bright cherry-red colour on the surface of beef (Hunt et al., 2004; Jayasingh et al., 2002; Luno et al., 2000; Sùrheim et al., 1999). Carboxymyoglobin (COMb) is more resistant to oxidation than oxymyoglobin, owing to the stronger binding of CO to the iron-porphyrin site on the myoglobin molecule (Wolfe, 1980). It is apparent that there are distinct advantages for storage and display life of meat with CO in low O2 MAP, but consumers have a negative image of CO because of its hazardous nature and the concern that products may appear fresher than they actually are (Cornforth and Hunt, 2008). The declaration of CO for meat as generally recognised as safe (GRAS) in the US has a legal basis (Boeckman, 2006) and the FDA noted that while colour did not degrade in a package containing CO, offensive odours could still form normally in the product in the presence of CO (FDA, 2004). Cooked meat products are usually MA packed using a combination of 70± 80% nitrogen and 20±30% CO2. The nitrogen is used primarily to preserve pack shape and the CO2 to prevent the growth of spoilage bacteria. This packaging format is popular in the retail sector for packaging cooked chicken, turkey, ham and even beef.

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29.4.4 Vacuum packaging Vacuum packaging involves the evacuation of air from the packs prior to sealing and is used extensively in the meat and poultry industries. The first significant commercial application was for vacuum packaging of whole turkeys using rubber stretch bags (Purdue, 1997). Vacuum packaging (VP) was one of the earliest forms of MAP method developed commercially and still is extensively used for products such as primal cuts of fresh red meat and cured meats (Parry, 1993). VP extends the storage life of chilled meats by maintaining an O2 deficient environment within the pack (Bell et al., 1995). Respiration of the meat in vacuum packs will also quickly consume any residual O2, replacing it with CO2, which eventually increases to 10±20% within the package (Taylor, 1985; Parry, 1993; Gill, 1996). However, the amount of O2 remaining in the pack at the time of closure must be very small if the product is to be effectively preserved, as the capacity of the muscle tissue for removing O2 is limited (Gill and Gill, 2005). Low O2 permeability of the packaging film causes a change in meat colour from red to purple due to the conversion of OMb to DMb. From the consumers' perspective, these forms of myoglobin have been considered as unacceptable meat colours (Allen et al., 1996; Parry, 1993). Therefore, vacuumpackaged meat is unsuitable for the retail market. Also prolonged storage of meat in vacuum packs results in the accumulation of drip, which is also unappealing to consumers (Jeremiah et al., 1992; Parry, 1993; Payne et al., 1997). A solution to this maybe vacuum skin packaging (VSP), which uses a film that fits very tightly to the meat surface, leaving little space for the accumulation of drip (Hood and Mead, 1993).

29.5

Future trends

Active packaging is a recent technological development which has the potential of extending the shelf life of meat and poultry products. The most prevalent form of active packaging in the meat industry is based on oxygen scavenging. The scavengers are usually made from iron powders which are combined with acids or salts, or both and a humectant to promote oxidation of the iron (Gill and McGinnis, 1995). Active packaging has the advantage of maintaining the preservative effects of various compounds (antimicrobial, antifungal, or antioxidant), but without being in direct contact with the food product. This is an important development, considering the consumer drive towards clean labelling of food products and the desire to limit the use of food additives (O'Sullivan and Kerry, 2009). Rooney (1995) defined an active package as a material that `performs a role other than an inert barrier to the outside environment.' Looking to the consumers' demand for chemical preservative-free foods, food manufacturers are now using naturally occurring antimicrobials to sterilise and/or extend the shelf life of foods (Han et al., 2005). The aim of active packaging is to increase the display life of contained products, while maintaining their quality, safety, and sensory

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properties, without direct addition of the active agents to the product (Camo et al., 2008). Antimicrobial packaging is an active packaging method where antimicrobial agents are incorporated into or coated onto food packaging materials to prolong the shelf life of the packed food, usually by extending the lag phase and reducing the growth rate of microorganisms (Han, 2000; Suppakul et al., 2003; Floros et al., 1997). The major potential product applications for antimicrobial films include meat, fish, poultry, bread, cheese, fruits, vegetables and beverages (LoÂpez-Rubio et al., 2004).

29.6

Sources of further information and advice

and KERRY, J. P. (2010). Sensory quality of fresh and processed meat. In Kerry, J. P. and Ledward, D. A. (eds), Improving the Sensory and Nutritional Quality of Fresh and Processed Meats. Woodhead Publishing Ltd, Cambridge. O'SULLIVAN, M. G., KERRY, J. P. and BYRNE, D. V. (2010). Use of sensory science as a practical commercial tool in the development of consumer-led processed meat products. In: Kerry, J. P. and Kerry, J. F. (eds), Processed Meats Improving Safety and Nutritional Quality. Woodhead Publishing Ltd, Cambridge. KERRY, J. P. and BUTLER, P. (EDS) (2007). Smart Packaging Technologies. John Wiley and Sons, Chichester. O'SULLIVAN, M. G.

29.7

References

and MONAHAN, F. J. (1996). Effect of oxygen scavengers and vitamin E supplementation on colour stability of MAP beef. 42nd International Congress of Meat Science and Technology. Lillehammer, Norway. BAEÂZA, E., DESSAY, C., WACRENIER, N., MARCHEÂ, G. and LISTRAT, A. (2002). Effect of selection for improved body weight and composition on muscle and meat characteristics in Muscovy duck. British Poultry Science, 43, 560±568. BARBUT, S. (2001a). Effect of illumination source on the appearance of fresh meat. Meat Science, 59, 187±191. BARBUT, S. (2001b). Acceptance of fresh chicken meat presented under three light sources. Poultry Science, 80, 101±104. BELL, R. G., PENNY, N. and MOORHEAD, S. M. (1995). Growth of the psychrotrophic pathogens Aeromonas hydrophila, Listeria monocytogenes and Yersinia enterocolitica in smoked blue cod Parapercis colias packed under vacuum or carbon dioxide. International Journal of Food Science and Technology, 30, 515± 521. BOECKMAN, A. M. (2006). Regulatory status of carbon monoxide for meat packaging. Proceedings 59th Reciprocal Meat Conference. Champaign-Urbana, IL. ALLEN, P., DOHERTY, A. M., BUCKLEY, D. J., KERRY, J., O'GRADY, M. N.

BOLEMAN, S. J., BOLEMAN, S. L., MILLER, R. K., TAYLOR, J. F., CROSS, H. R., WHEELER, T. L.,

and (1997). Consumer evaluation of beef of known categories of tenderness. Journal of Animal Science, 75, 1521±1524. BRODY, A. L. (1997). Packaging of food. In Brody, A. L. and Marsh, K. S. (eds), The Wiley KOOHMARAIE, M., SHACKELFORD, S. D., MILLER, M. F., WEST, R. L., JOHNSON D. D.

SAVELL, J. W.

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Index

-terpineol, 556 abiotic deterioration, 246 Acaridae, 120 Acarus siro L., 120 accelerated shelf life testing, 51, 465, 482±503, 602±3, 633 basic principles, 483 combination of approaches, 500±1 dynamic methods, 496±8 schematic diagram, 497 future trends, 502±3 glass transition models, 493 initial rate approach, 483±5 extent of deterioration, 484 kinetic model approach, 485±7 data extrapolation schematic diagram, 486 multiple accelerating factors, 493±5 `no model' approach, 498±500 problems, 501±2 absence of a deterioration index, 501±2 statistical problems, 502 single accelerating factor, 487±92 Arrhenius model, 487±91 error in exponential or power law extrapolation, 491 error in linear extrapolation, 490 extrapolation error analysis in linear plot, 489

non-linear kinetic models, 491±2 accelerated storage tests, 727 acceleration ratio, 489±90 acceptability limit, 624±6 accuracy factor, 421, 441 acetaldehyde, 557 acetic acid, 784 acidification, 759 acoustic sensors, 387 acoustic technique, 47 activation energy, 309 additives, 44, 53 adsorption, 668 aerated confectionery, 737±40 aerated jelly product, 739 classification according to method of aeration, 738 composition and structure, 737±8 deteriorative changes during storage, 738±40 typical shelf lives, 739 Aeromonas hydrophila, 784 Aeromonas salmonicida, 784 affective tests, 356 aged bouquet, 558 air chilling, 11, 284 air freighting, 289 Alicyclobacillus, 589 almond moth see Esphestia cautella (Walker)

ß Woodhead Publishing Limited, 2011

818

Index

alternative forced choice test see paired comparison test amino acids, 33 ammonia, 784 amylose, 144 analysis of variance, 365 analytical tests, 356 sensory tests subjects, 357±8 monitoring, 358 recruitment, 357 screening, 357 training, 358 anisidine value, 704 ANN see artificial neural networks Anobiidae, 109±10 ANOVA see analysis of variance anti-bloom agents, 724±6 `anti-staling' emulsifiers, 677 `anti-staling' enzymes, 679 antimicrobials, 161±73 fermentates, 172±3 natamycin, 164, 167±8, 169±71 food legislation on natamycin use, 169±71 structure, 167 yeast and moulds sensitivity, 167 nisin, 161±4, 165±6 addition levels in food samples, 164 list of products and countries for approved use, 165±6 structure, 162 protective cultures, 168, 172 challenge test mould pool activity against reference control, 172 antimony, 267±8 antioxidants, 44, 53, 134, 173±6, 701±3, 708±12, 799 activity of different antioxidant components using lard substrate, 713 BHT, BHA, and TBHQ chemical structures, 175 mode of action against lipid radicals, 174 ORAC measurements of natural extracts with antioxidative properties, 712 oxidative cycle, 174 rosemary and green tea extracts, 175±6 synthetic antioxidants characteristics, 710 structures, 710

tocopherol and ascorbyl palmitate, 175 ants, 119±20 AquaLab Series, 76 Arabica coffee see Coffea arabica aroma, 373±4 Arrhenius equation, 39, 50, 51, 309, 316, 333, 464, 468, 471, 473, 501, 622, 624, 634±5 Arrhenius model, 436, 487±91, 502 Arrhenius plot, 332 Arrhenius-type relationship, 255 artificial neural networks, 13, 411 ascorbyl palmitate, 711 ASLT see accelerated shelf life testing Aspergillus flavus, 139 ASTM E 2454, 374 ASTM E 2454-05, 351 attenuated total reflectance, 89 autocatalytic processes, 388 automated optical density, 418 automatic commercialised apparatus, 78±82 Autosorp, 78, 82 autoxidation, 687±90 aldehydes formation, 689 flavours of aliphatic aldehydes, 690 influence of methylene groups, 689 mechanism, 688 -carotene, 745 -lactoglobulin, 758 Bacillus spp., 762, 766 Bacillus subtilis, 669 bacterial decarboxylases, 784 bacterial enzymes, 784 bacteriocins, 511 `bag-in-box', 696 bakery products ensuring stability and extending shelf life, 673±8 adjusting product ERH, 674±6 controlling moisture and its migration, 673±4 impacts of packaging, 676±7 impacts of preservatives and pH, 676 limiting staling in bread, 677±8 evaluating the shelf life, 669±73 bread firmness and resilience, 670±1 consumer squeeze test on bread, 670 crispness, 671 DSC endotherms, 673 ERH and mould-free shelf life, 674

ß Woodhead Publishing Limited, 2011

Index measurement of equilibrium relative humidity (water activity), 672 methods of assessing staling, 672±3 moisture measurement, 672 sensory properties, 669±70 texture profile analysis, 671±2 factors affecting stability, 663±9 equilibrium relative humidity (water activity), 667±8 mechanisms involved in moisture migration, 666±7 microbial shelf life, 668±9 moisture content, 665 moisture migration, 665±6 nature of staling, 663±5 rancidity, 669 future trends, 678±80 key `fresh' characteristics, 662±3 biscuits, crackers and cookies, 662 bread, rolls and buns, 662 cakes and sponges, 662 pastries, 662±3 manufacture overview, 658±61 biscuits and cookies, 660±1 bread, 658±60 cakes, 660 croissant, 661 pastry, 661 selection of biscuit and cookie types, 661 physical changes during storage, 663 stability and shelf life, 657±80 see also specific product Ball formula method, 196 Baranyi model, 427±8 barolos, 541 beaujolais nouveau, 541, 559 beer flavour instability, 531±3 binding of bisulfite to carbonyls, 533 sensory changes in flavour during ageing, 532 foam instability, 533±5 change in levels of hydrophobic peptides, 534 wort gravity on proteinase A, 535 light instability, 536±7 mercaptan formation in iso--acid, 537 physical instability, 529±31 typical polyphenol, 530 shelf life and stability, 527±37

819

biological instability, 528±9 gushing, 536 beer chill haze, 530 beer haze, 529±30 beeswax, 147, 148 `best before', 327 BET equation see Brunauer-EmmetTeller equation beverages chemical deterioration and physical instability, 29±55 chemical deterioration, 30±4 factors affecting the quality loss rate, 39±44 measurement, 44±8 physical deterioration, 34±9 predicting and monitoring, 49±53 prevention, 53±5 effects of distribution, display and consumer handling on shelf life, 273±99 microbiological spoilage, 3±18 evaluating, monitoring and measuring microbiological spoilage rate, 12±14 factors affecting the microbiological spoilage rate, 5±11 future trends, 17±18 microbes vs indigenous enzymes, 4±5 predicting microbiological spoilage, 14±15 preventing microbiological spoilage, 15±17 modelling chemical and physical deterioration, 459±77 factors influencing shelf life, 460±2 future trends, 476±7 mathematical models development, 462±6 predictive mathematical models, 466±76 modelling microbial shelf life, 405±51 approaches, applications and opportunities, 426±37 future trends, 446±51 predictive microbiology electronic sources, 437±46 predictive models classification by microbial response, 407±12 predictive models development, 412±26

ß Woodhead Publishing Limited, 2011

820

Index

packaging and shelf life, 244±69 future trends, 269 key package properties related to shelf life, 253±60 major packaging materials, 249±53 packaging in extending shelf life, 245±9 packaging migrants, 266±9 predicting shelf life, 260±5 processing and shelf life, 184±236 filling and packaging, 228±30 future trends, 235±6 hygiene, 234±5 low and intermediate moisture foods production, 209±11 main quality change factors and interaction with processing, 187±9 novel processes, 230±4 processing, 200±4 product and process design, 198±200 shelf life and stability, 189±98 thermal processing, 211±28 unit operations, 204±9 smart packaging for monitoring and managing shelf life, 303±21 BHA see butylated hydroxy anisole BHT see butylated hydroxytoluene bias factor, 421 biochemical reactions, 245±6 biochemical transformations, 756 biological instability, 528±9 Biosystemes, 78 biotic deterioration, 246 biotin, 748 bipolar scales, 361 biscuits key `fresh' characteristics, 662 manufacture overview, 660±1 bisulfite, 532±3 blanching, 221, 223 bordeaux, 541 Bostrichidae, 110±11 Box±Behnken design, 417 bread consumer squeeze test, 670 key `fresh' characteristics, 662 limiting staling, 677±8 manufacture overview, 658±60 potential effects of recipe changes to lower bread ERH, 675

stability and shelf life, 657±80 varieties, 658 bread staling, 664 Brettanomyces, 554 brewing, 527 British Standard BS EN ISO 9000:2005, 326 brown house moth see Hofmannophila pseudospretella (Stainton) Brownian motion, 66 Bruchidae, 110±11 bruising, 34, 188 Brunauer-Emmet-Teller equation, 468 butter, 770±1 butterscotch, 729 butylated hydroxy anisole, 134, 709 butylated hydroxytoluene, 134, 709 cadelle beetle see Tenebroides mauritanicus (L.) cake staling, 664±5 cakes key `fresh' characteristics, 662 manufacture overview, 660 mould-free shelf life modification by recipe change, 675 varieties, 660 caking, 96 calcium oxalate, 536 calpains, 780 CAP see controlled atmosphere packaging capacitive-based humidity sensors, 384 capillary viscometer, 387±8 caramel, 729 see also toffee carbon dioxide, 17 carbonation, 209 carbonic maturation, 545 Carbowax, 72 Cardinal model, 444 cardinal parameter models, 434 carotenoids, 745 Carpoglyphus lactis (L.), 120±1 carry-through, 709 casein, 756±8 category scales, 361 Cathartus quadricollis (GueninMeneville), 112 cathepsins, 780 CBP see Chorleywood Bread Process CCP see critical control points

ß Woodhead Publishing Limited, 2011

Index CDC model see continuous discrete continuous model cell density, 427 cell lag time, 431±2 centrifugation, 207 CFD see computational fluid dynamics challenge testing, 339, 507±21 basic principles, 508±19 choosing the right method of inoculation, 516 duration of trials and storage conditions, 516±17 factors affecting microbial growth and survival, 508±12 inoculum level and preparation, 514±16 pathogenic micro-organisms used, 512 pH and water activity values permitting microbial growth, 510 pH values, 510 redox potential, 511 sample analysis and data interpretation, 517±19 selection of challenge organisms, 512±14 steps, 509 water activity values, 509 future trends, 521 limitations, 519 mathematical models, 519±21 role in shelf-life evaluation, 507±8 charging time, 316 `checking', 666 Checkpoint TTI, 305±6, 313, 315 cheese, 33, 774±6 boundary composition for cheddar cheese manufacture, 776 chelating agents, 44 chemical analysis, 801±2 chemical deterioration, 30±4 enzymatic degradation, 32 extrinsic factors, 39±42, 414, 461 light, 40 packaging, 40±2 relative humidity, 40 temperature, 39±40 factors affecting the quality loss rate, 39±44 foods and beverages, 29±55 reactions in foods affecting quality, 31

821

future trends, 55 intrinsic factors, 42±4 common foods water activity, 42 moisture and water activity, 42±3 oxygen, 43±4 pH and total acidity, 43 product formulation and composition, 44 light-induced chemical changes, 33±4 lipid oxidation, 30, 31±2 measurement, 44±8 chemical measurements, 47±8 instrumental methods, 45±8 physical measurements, 46±7 sensory panels, 44±5 modelling, 459±77 modelling chemical reactions, 49±51 temperature dependence of chemical reactions, 50±1 non-enzymatic degradation, 33 predicting and monitoring, 49±53 food quality attributes kinetic modelling, 49±52 kinetic parameters determination, 51 other kinetic models, 51±2 time-temperature history, 52±3 prevention, 53±5 protein degradation, 34 chemical kinetics, 462 chemical reactions, 245, 756 chemical sense, 353 chill chain, 10±11 see also specific chilling chilled mirror hygrometer, 384 chilling, 226±7, 273, 274 chilling injury, 37±8 chocolate, 720±7 polymorphic forms of cocoa butter, 722 solid fat content of cocoa butter, 720 chocolate coating, 726 chocolate products, 720±7 accelerated storage tests, 727 anti-bloom agents, 724±6 deteriorative changes and typical shelf lives, 721 fat bloom, 721±2 moisture migration, 726 sensory changes during storage, 722±4 number of weeks to ten-unit change in sensory attributes, 723

ß Woodhead Publishing Limited, 2011

822

Index

shelf lives based on sensory changes, 724 sugar bloom, 724 time to bloom development at various storage temperatures, 727 cholecalciferol, 748 Chorleywood Bread Process, 659 CHP see combined heat and power churning, 760 CIELAB, 313 cigarette beetle see Lasioderma serricorne (F.) cis fatty acids, 685 citric acid, 701 classical Fickian diffusion equation, 90 `clean ingredient labels', 677, 678±9 Cleridae, 111 climacteric fruits, 644 coalescence, 740 Codex Alimentarius Commission, 192 Coffea arabica, 616 Coffea canephora, 616 coffee brews, 617 coffee concentrates, 617 coffee products critical events affecting stability and shelf life, 617±20 ensuring stability and extending shelf life of coffee, 620±4 ester hydrolysis and non-enzymatic browning, 623±4 intrinsic and extrinsic factors controlling the kinetics of critical events, 620 oxidation, 621±3 physical collapse, 623 volatile release, 620±1 evaluating the shelf life of coffee, 624±36 acceptability limit and proposed rejection risk level, 626 acceptability limit identification, 624±6 indicators of quality depletion, 628 main criteria for definition of shelf life acceptability limits, 625 methodology for definition of analytical indicators, 627 pH limit of coffee brews, 629 shelf life indicators identification, 626±9 future trends, 636

key unit operations to obtain the main coffee products and relevant effects, 616 main critical event leading to quality depletion during shelf life, 618 shelf life of roasted whole and ground coffee packed under 3.0 kPa oxygen partial pressure and stored at 22 ëC, 623 packed under different conditions, 622 shelf life testing under accelerated storage conditions, 633±6 temperature dependence of the coffee product quality depletion, 634 zero-order rate of decrease of acetylfuran, 635 shelf life testing under actual storage conditions, 629±33 hydrogen ion concentration of coffee brew, 632 probability of consumer rejection as function of storage time at 20 ëC, 630 total volatile peak area of ground roasted coffee, 633 stability and shelf life, 615±36 cold aeration, 122 cold chain, 274±5, 320±1 food cold chain, 275 residence times for typical perishable food, 275 sectors and influence on food quality and safety, 283±98 primary chilling/freezing, 283±6 retail display, 290±3 secondary processing, 286 storage, 286±7 temperatures, 283 transport, 287±90 TTI for shelf-life management and optimisation, 311±20 cold-tolerant Enterobacteriaceae, 6 Coleoptera, 107, 109±15 colloid mills, 205 colloidal stability, 529 colorimetric assay, 770 colour, 353±4, 383, 466±7 colour assessment, 373, 383 ComBase, 419, 437±40, 446, 450, 520

ß Woodhead Publishing Limited, 2011

Index ComBase Modelling Toolbox, 419, 437±40 ComBase predictor, 438 DMFit, 438 Perfringens Predictor, 438 ComBase predictor, 439±40 combined heat and power, 299 Commission Regulation (EC) No. 2073/ 2005, 325±6, 335±8, 345 Comobibloc, 588 competitive inhibition, 473 composite foods, 98, 99 Compressimeter, 671 compulsory shelf life limits, 625 computational fluid dynamics, 196, 477 computer vision system, 382 concentrated juices, 580 conduction, 214 conductivity hygrometer, 384 confectionery foams, 738 confectionery products aerated confectionery, 737±40 chocolate and chocolate products, 720±7 equilibrium relative humidity values, 719 factors affecting shelf life, 717±20 moisture migration and equilibrium relative humidity, 718±19 packaging, 720 product composition, 717 product structure, 717±18 storage conditions, 719 gums and jellies, 733±7 stability and shelf life, 716±40 sugar glass, 727±9 toffee, 729±33 see also specific product conjugated dienes, 390 consumer acceptability testing, 366 consumer squeeze test, 670, 671 continuous discrete continuous model, 431 continuous heat exchangers, 218 controlled atmosphere packaging, 41, 460 controlled atmosphere storage, 642, 650±1 convection, 214 cookies key `fresh' characteristics, 662 manufacture overview, 660±1 cooking, 224 Corcyra cephalonica (Stainton), 116

823

Corynebacteria, 762 cosmopolitan food mite see Lepidoglyphus destructor (Schrank) cottage cheese, 768 Couchman±Karasz equation, 142 Council Directive 2000/12/EC, 800 CPM see cardinal parameter models Crank's equations, 88 cream liquers, 774 crispness, 94±6, 671 critical control points, 192, 335, 520 cross-flow ultrafiltration, 767 cross-sensitivity, 394 cross-validation method, 502 Cryolog TRACEO, 450 cryoprotectants, 153 physical properties of common carbohydrates and polyols, 180±3 sweetener ingredients, 154±60 Cryptolestes ferrugineus (Stephens), 111±12 crystallisation, 97 Cucujidae, 111±12 Curculionidae, 112 dairy-based spreads, 770±1 Darcy's law, 65 DDI method see Dynamic Dewpoint Isotherm method Decagon, 82 decimal reduction time, 212 degradation reaction, 462±3 deoxynivalent, 536 Dermestidae, 112±14 Dermetes lardarius L., D. maculatus Degger, 112±13 descriptive analysis, 803 desorption, 668 deterioration index, 483±4, 501±2 deterministic approaches, 411 3,4-DHPEA see 3,4dihydroxyphenolethanol diagram pressure drop method, 78 Dictyoptera, 118 differential scanning calorimetry, 36, 47, 72, 137, 140, 672 differential thermal analysis, 72, 672 diffusion assay, 770 3,4-dihydroxyphenolethanol, 711 dimethyl sulphide, 557 direct determinations, 70

ß Woodhead Publishing Limited, 2011

824

Index

direct heating, 218±19 direct juices, 580 Directive 1994/35/EC, 155 Directive 1995/2/EC, 155±6 Directive 2000/13/EC, 326 disproportionation, 740 DMA see dynamic mechanical analysis DMFit, 419, 438 DMS see dimethyl sulphide domestic refrigeration, 296, 299 DON see deoxynivalent drawn and wall ironed process, 586 dried fruit mite see Carpoglyphus lactis (L.) dried milk products, 771±2 drugstore beetle see Stegobium paniceum (L.) dry matter, 84 drying, 209, 210 DSC see differential scanning calorimetry DTA see differential thermal analysis duo-trio test, 359 DVS see Dynamic Vapour Sorption DWI process see drawn and wall ironed process Dynamic Dewpoint Isotherm method, 82 dynamic mechanical analysis, 47 dynamic purge-and-trap headspace, 391 Dynamic Vapour Sorption, 80, 140 schematic design, 81 EC 2073/2005, 794±5 ECCS see electrolytically chromiumcoated steel `edible packaging', 662 EDTA see ethylene diamine tetra-acetic acid electric nose, 392±4 schematic diagram, 393 electrolytically chromium-coated steel, 250 electromagnetic radiation, 231 electromyography, 387 electron beams, 232 `electronic drift', 393±4 electronic tongue, 394±5 schematic diagram, 394 ELISA, 787 empirical models, 408 emulsifiers, 39, 44 emulsions, 38±9, 205±6 EN 441, 290

EN 23953, 290 Enterobacteriaciae, 762 enzyme, 677 enzyme activity, 770 enzyme-catalysed oxidation, 691 (eO) TTI, 306, 450 ephemeral/specific spoilage microorganisms, 5 ephemeral spoilage organisms, 5±10 Ephestia kuehniella Zeller, 117 epoxidised soy bean oil, 266±7 equilibrium moisture content, 260 equilibrium relative humidity, 35, 40, 75, 342, 667±8, 717, 718±19 adjustment, 674±6 defined, 40 measurement, 672 potential effects of recipe changes to lower bread ERH, 675 relation to mould-free shelf life for bakery products, 674 ergocalciferol, 748 ERH see equilibrium relative humidity ERH CALC, 668 ERH Calc, 342, 343 Escherichia coli, 762 Escherichia coli O157, 579 Escherichia coli O157:H7, 15 ESO see ephemeral spoilage organisms Esphestia cautella (Walker), 116 Esphestia elutella (Hubner), 116±17 E(S)SO see ephemeral/specific spoilage micro-organisms esterase, 781 ethylene, 646±7 ethylene diamine tetra-acetic acid, 701 ethylene vinyl alcohol, 252 EU Regulation (EC) No. 852/2004, 335 Eulerian co-ordinates, 85 European Council Regulation 2406/96, 787 evaporated milk, 773 EVOH see ethylene vinyl alcohol exponential mode, 436 F value, 211 failure time, 630 fat bloom, 721±2 fats and oils chemical composition, 693±6 effect of degree of unsaturation on relative rates of oxidation, 694

ß Woodhead Publishing Limited, 2011

Index fatty acid content and `inherent stability', 694 cis and trans double bonds, 686 different fatty acid chain structures, 686 ensuring stability and extending shelf life, 707±12, 713 optimising storage condition, 707±8 use of antioxidants, 708±12 measurement of oxidation induction periods, 705±7 historical methods, 705±6 induction period curve, 706 OSI method, 707 Rancimat induction period, 706±7 melting points of common fatty acids, 687 oxidation and hydrolysis mechanisms, 684±93 autoxidation, 687±90 enzyme-catalysed oxidation, 691 hydrolytic (lipolytic) rancidity, 692±3 photooxidation, 690±1 oxidative status measurement, 704±5 anisidine value, 704 other methods, 705 peroxide value, 704 totox value, 704±5 presence of pro-oxidants and antioxidants, 701±3 levels of metal contaminants needed to give same rate oxidation in vegetable oil, 701 tocopherol and tocotrienols levels in common vegetable oils, 703 tocopherols chemical structure, 702 tocotrienols chemical structure, 702 stability and shelf life, 683±714 affecting factors, 693±703 evaluating the shelf life, 703±7 future trends, 712±14 storage conditions, 696±701 agitation, 697 atmosphere, 697 effect of light and atmosphere on bottled soyabean oil acceptability, 698 effect on oxidation of lid on a storage tank, 700 good and bad storage tank designs, 699

825

light, 698 materials used in storage tanks, 699 packed fats, 700±1 presence of old oil, 699±700 shape and structure of storage tanks, 699 temperature, 697±8 triglyceride molecule, 685 fatty acid oxidation, 784 fatty acids, 759 FCM see food contact materials FCP see free choice profiling fermentates, 172±3 fermentation, 527, 535 fermented milk, 767 Fermi equation, 84±5 ferrous oxide, 43 FFA see free fatty acid fibre-optic-based techniques, 385 Fick equation, 84, 85, 86 Fickian theory, 84 Fick's law of diffusion, 66, 67, 86±7, 88, 90, 136, 254, 475 FID see flame ionisation detector FIFO see first-in-first-out filtration, 207±8, 527 fino sherries, 541, 559 first-in-first-out, 202, 311, 319 first-order reactions, 50, 632 flame ionisation detector, 391 flavour, 373±4 flavour instability, 531±3 floc, 582 flour mite see Acarus siro L. FMC Pea Tenderometer, 386 foam instability, 533±5 folic acid, 747 food contact materials, 266 food degradation, 459±77 factors influencing shelf life, 460±2 critical quality parameters, 461±2 degradation, 460±1 future trends, 476±7 mathematical models development, 462±6 basic reaction kinetics, 462±4 evaluation of goodness of fit of the model, 465±6 Q10 and accelerated shelf life tests, 465 rate constant dependence on temperature, 464

ß Woodhead Publishing Limited, 2011

826

Index

predictive mathematical models, 466±76 colour, 466±7 diagnosis plot between experimental data and secondary model predictions, 472 enzyme kinetic equations for inhibitory mechanisms, 474 experimental and predicted mass of mushrooms, 476 moisture content and water activity, 467±72 respiration, 472±3 sorption isotherms, 469±70 temperature on moisture uptake, 468 variation of water activity with time, 471 water loss or transpiration, 473±6 Food Hygiene (England) Regulations 2006, 325 Food Labelling Directive (2000/13/EEC), 594±5 Food Labelling Regulations 1996, 327 food products storage conditions, 15±16 ambient stable foods, 16 chilled foods, 16 frozen foods, 16 food quality deterioration advances in instrumental methods, 381±99 assessing food appearance, 382±4 electric nose, 392±4 electronic tongue, 394±5 future trends, 399 infrared spectroscopy, 395±8 lipid oxidation assessment, 388±92 microbiological testing, 398 relative humidity, moisture and water activity, 384±5 rheological properties of liquid and semisolid foods, 387±8 texture evaluation, 385±7 food storage trials, 325±47 challenge testing, 339 food deterioration and spoilage, 328±34 basic model, 333 biochemical and chemical changes, 329±30 biochemical and chemical changes in food, 331 changes in food during storage, 329

food spoilage organisms and changes they cause in food, 330 microbiological changes, 328±9 pathogenic microorganisms associated with chilled foods, 332 physical changes, 330 physical changes in food, 331 temperature-related changes, 330±3 future trends, 346±7 quality shelf life and storage trials, 339±45 accelerated storage trials, 341±2 assigning shelf life, 345 ERH Calc, 343 experimental design and sampling schedule, 341 published shelf life studies and their tests, 344 samples for storage trials, 340±1 shelf-life tests, 342±4 storage conditions, 340 safe shelf life, 334±8 food safety criteria applicable to products placed on the market, 336±7 food water activity, 384 foods, 135±47, 150±4, 155 accelerated shelf life testing, 482±503 basic principles, 483 combination of approaches, 500±1 dynamic methods, 496±8 future trends, 502±3 glass transition models, 493 initial rate approach, 483±5 kinetic model approach, 485±7 multiple accelerating factors, 493±5 `no model' approach, 498±500 problems, 501±2 single accelerating factor, 487±92 chemical deterioration and physical instability, 29±55 chemical deterioration, 30±4 factors affecting the quality loss rate, 39±44 measurement, 44±8 physical deterioration, 34±9 predicting and monitoring, 49±53 prevention, 53±5 cold chain, 274±5 food cold chain, 275 residence times for a typical perishable food, 275

ß Woodhead Publishing Limited, 2011

Index cold chain sectors and their influence on food quality and safety, 283±98 domestic transport and storage, 293±8 food temperature after 1 hour transport in the boot of a car, 295 initial and final temperature and enthalpy change per kg, 285 mean temperature and temperature range for cabinets examined, 292 overall mean temperatures for refrigerators in survey, 297 position of maximum temperatures, 291 positions of lowest and highest mean temperatures in refrigerators investigated, 297 primary chilling/freezing, 283±6 raw material and primary chilling and freezing methods, 286 retail display, 290±3 secondary processing, 286 storage, 286±7 temperature range in refrigerator types investigated, 298 temperatures, 283 temperatures in supermarket retail display cabinets, 293 temperatures measured in surveys of domestic refrigerators, 296 temperatures throughout the French cold chain, 284 transport, 287±90 typical minimum growth temperatures for microorganisms, 285 weight loss from meat samples with and without humidification, 293 weight loss from produce samples with and without humidification, 294 effects of distribution, display and consumer handling on shelf life, 273±99 future trends, 298±9 microbial challenge testing, 507±21 basic principles, 508±19 future trends, 521 limitations, 519 mathematical models, 519±21 role in shelf-life evaluation, 507±8

827

microbiological spoilage, 3±18 evaluating, monitoring and measuring microbiological spoilage rate, 12±14 factors affecting the microbiological spoilage rate, 5±11 future trends, 17±18 microbes vs indigenous enzymes, 4±5 predicting microbiological spoilage, 14±15 preventing microbiological spoilage, 15±17 modelling chemical and physical deterioration, 459±77 factors influencing shelf life, 460±2 future trends, 476±7 mathematical models development, 462±6 predictive mathematical models, 466±76 see also food degradation modelling microbial shelf life, 405±51 approaches, applications and opportunities, 426±37 future trends, 446±51 predictive microbiology electronic sources, 437±46 predictive models classification by microbial response, 407±12 predictive models development, 412±26 moisture loss, gain and migration, 63±100 conditions for moisture migration and foods affected by moisture transfer, 97±100 measuring, monitoring and predicting, 70±93 moisture transfer mechanism, 64±70 related to shelf life, 93±7 moisture movement in food systems, 135±44 bakery product, water activity and typical shelf life, 140 emulsifier type and complexing strength with amylose, 144 Fick's law, 136 glass transition, 137±8 humectant systems, 138±40 humectants as anti-crystallisation agents, 143

ß Woodhead Publishing Limited, 2011

828

Index

modified Couchman-Karasz equation, 143 Raoult's Law, 136±7 sample relative humidity and mass increase, 141 starch retrogradation or crystallisation, 144 water activity, 135±6 water adsorption and desorption kinetics, 140, 141 water and humectant ingredients as plasticisers, 137 water on physical properties, 140, 142±3 packaging and shelf life, 244±69 future trends, 269 key package properties related to shelf life, 253±60 major packaging materials, 249±53 packaging in extending shelf life, 245±9 packaging migrants, 266±9 predicting shelf life, 260±5 preservation by freezing, 150±4, 155 crumb structure and volume, 152 cryoprotectants, 153 fermentation conditions for yeast, 152 freeze-thaw stability, 151±2 frozen yeast dough, 150±1 glassy state formation, 154 storage stability, 152 strengthening the gluten network, 151 sucrose, 154 sucrose state diagram, 155 Surimi, 152±3 processing and shelf life, 184±236 filling and packaging, 228±30 future trends, 235±6 hygiene, 234±5 low and intermediate moisture foods production, 209±11 main quality change factors and interaction with processing, 187±9 novel processes, 230±4 processing, 200±4 product and process design, 198±200 shelf life and stability, 189±98 thermal processing, 211±28 unit operations, 204±9

reactions in foods affecting quality, 31 sensory evaluation methods for shelf life assessment, 350±75, 378±80 basic requirements for sensory analysis, 354±8 consumer acceptability testing, 366 discrimination tests, 358±61 future trends, 375 instrumental methods, 372±4 principles, 352±4 quantitative descriptive tests, 361±6 sensory shelf life data interpretation, 370±2 sensory shelf life testing standardisation, 374±5 sensory shelf life tests design, 368±70 sensory shelf life tests operation, 366±7 smart packaging for monitoring and managing shelf life, 303±21 spoilage due to water activity, 144, 145±7 foods and microorganisms that can cause food spoilage, 145 lipid oxidation (rancidity) and enzymatic browning, 146±7 water chemical reactivity, 146 storage life, 276±83 assessment, 276±7 chilled cuts of meat, 282 chilled products, 276 critical temperature for chilled products, 279 frozen products, 278 product processing and packaging factors, 277±83 storage temperature, 277 time for odour or slime to be detected on beef sides, 279 storage life experimental data beef, 280 lamb, 280 pork, 280 formic acid, 784 Fourier transform infrared spectroscopy, 13, 89, 396±7 free choice profiling, 364, 803 free fatty acid, 32, 47 freeze-thaw stability, 151±2 defined, 150 freezing, 226±7, 273, 283±6

ß Woodhead Publishing Limited, 2011

Index Fresh-Check TTI, 306 freshly squeezed juices, 579±80 fruit juices, 572±3 citrus fruit processing, 576 ensuring product stability and extending shelf life, 584±8 packaging, 585±8 processing, 584±5 factors influencing stability, 574±83 packaging and storage/distribution, 579±81 pasteurisation, 578±9 pressing, 577 separating juice and pulp and debris, 577±8 washing and inspection, 576±7 future trends, 591±3 carbonated soft drinks, 592 dilute-to-taste products, 592 fruit juices and ready-to-drink uncarbonated soft drinks, 591±2 processing trends, 593 key stages in fruit processing operation, 575 physical and chemical changes, 581±3 clarified products, 582 cloudy products, 581±2 colour and flavour changes, 583 oil rings, 582±3 shelf life determination, 588±91 accelerated shelf-life testing, 590±1 microbiological, 588±9 physicochemical testing, 589±91 soft fruit processing, 575 stability and shelf life, 571±93 fruit and vegetables controlled and modified atmosphere packaging for longer shelf life, 650±2 controlled atmosphere storage, 650±1 modified atmosphere packaging, 651±2 extending the shelf life, 648±50 ethylene, 649±50 humidity, 649 oxygen and carbon dioxide, 649 temperature, 648 fruit classification based on respiratory behaviour during ripening, 646 future trends, 652±3 loss of stability and quality deterioration, 643±7

829

ethylene, 646±7 moisture loss, 647 respiration, 644±6 typical ripening patterns for fruits, 645 stability and shelf life, 641±53 FTIR see Fourier transform infrared spectroscopy fudges, 729 furaldehydes, 553 2-furfural, 556 Fusarium, 528 GAB equation see GuggenheimAndersonode Boer equation gallic acid, 564 gamma-type models, 432 gas chromatography, 48, 72, 382, 389, 390±2 gas chromatography-flame ionisation detector, 48 gas chromatography-mass spectrometry, 48 gas chromatography-olfactometry, 48, 391, 564 gas transmission rate, 256 GC see gas chromatography GC-FID see gas chromatography-flame ionisation detector GC-MS see gas chromatography-mass spectrometry GC-O see gas chromatographyolfactometry gelatinisation, 663 General Food Law Regulation (EC) 178/ 2002, 326 General Method, 196 Gibb's free energy, 154 GInaFIT, 419 glass, 250 glass transition, 35±6, 47, 52, 137±8, 728 concept, 36 models, 493 theory, 36 glass transition temperature, 35±6, 47, 52, 728 food carbohydrates, 160 glutathione, 564 gluten, 657±8 glycerol, 138 glycerol monostearate, 677 Glycyphagus domesticus (Degeer), 121

ß Woodhead Publishing Limited, 2011

830

Index

GMP see good manufacturing practice GMS see glycerol monostearate golden spider beetle see Niptus hololeucus Gompertz function, 427 goniometry, 88±9 good manufacturing practice, 194 graining, 728±9, 732 gram-negative bacteria, 508±9, 529 gram-positive bacteria, 509, 528±9 graphic scales, 361 `green beer', 528 green tea flavonoids, 712 growth boundary models see growth/nogrowth interface models growth models, 408, 410, 425±6 growth/no-growth interface models, 409, 410±11 growth/no-growth interface simulation module, 444 Growth Predictor, 520 growth rate, 427, 429 GTR see gas transmission rate Guggenheim±Andersonode Boer equation, 468 gum Arabic, 582 gums and jellies, 733±7 changes during storage, 736±7 physical characteristics and microstructure, 733±6 sensory attributes assessed during storage of fruit gums, 737 texture, moisture content and ERH of non-sugar coated gums and jellies, 733 gushing, 536 HACCP see Hazard Analysis and Critical Control Point Hage-Poiseulle's law, 65 `hairy' micelle model, 758 Hazard Analysis and Critical Control Point, 15, 192, 335, 339, 342±3, 461, 508, 520, 794 principles applied to quality, 193 haze formation, 529±30 HCA see high care areas HDPE see high density polyethylene headspace gas chromatography, 705 heat-resistant bacteria, 762±3 creamery silo milk, 763 heat-resistant enzymes, 768±9

residual enzyme activity, 769 heat-resistant organisms, 766±7 heat sealable films, 259 heat treatment, 16±17 hedonic scales, 362 hedonic tests, 356, 358 Henry's coefficient see solubility coefficient Henry's law, 87 HFCS see high fructose corn syrup high care areas, 194, 203 high density polyethylene, 251, 587 high fructose corn syrup, 730 high-gravity brewing, 533±4 high oxygen modified atmosphere packs, 804±6 high pressure processing, 593 high quality life, 277 high risk areas, 194, 203 high-temperature short-time pasteurisation, 764 higher temperature shorter time, 225 Hofmannophila pseudospretella (Stainton), 115 HOLDBAC YM-B, 172 HOLDBAC YM-C, 172 home delivery, 290 homogenisers, 205 Hooke's Law, 670 house mite see Glycyphagus domesticus (Degeer) HPKO see hydrogenated palm kernel oil HQL see high quality life HRA see high risk areas HTST see higher temperature shorter time human senses, 352±4 humectants, 44, 134±5, 137±9, 154±60 as anti-crystallisation agents, 143 physical properties of common carbohydrates and polyols, 180±3 sweetener ingredients, 154±60 systems, 138±9 and water ingredients as plasticisers, 137 humidity sensors, 384±5 hurdle concept, 434, 511 hurdle technology, 54, 208, 410, 434±6 hydrogen peroxide, 219, 220, 552 `hydrogenated fat', 713 hydrogenated palm kernel oil, 730 hydrolysis, 30, 146

ß Woodhead Publishing Limited, 2011

Index hydrolytic (lipolytic) rancidity, 692±3 saturated fatty acids flavour thresholds, 692 triglycerides hydrolytic breakdown, 692 hydrolytic rancidity, 146 hydroperoxides, 31, 32, 47 2-hydroxymethyl-5-furfural, 556 hygroscopic, 135 Hymenoptera, 119 hyperspectral imaging technique, 652±3 IGA-200 Multicomponent Gas/Vapour Analyser, 82 IGA series, 82 IMC see intermediate moisture content IMF see intermediate moisture foods immersion chilling, 11 implicit factors, 414 in-line filtration, 207 inactivation models, 412 Indian meal moth see Plodia interpunctella (Hubner) indices of failure, 248 indirect determinations, 70 indirect heating, 218 infrared hygrometers, 384 infrared spectroscopy, 382, 385, 395±8 ingredients antimicrobials, 161±73 challenge test mould pool activity against reference control, 172 fermentates, 172±3 food legislation on natamycin use, 169±71 natamycin, 164, 167±8, 169±71 natamycin structure, 167 nisin, 161±4, 165±6 nisin addition levels in food samples, 164 nisin list of products and countries for approved use, 165±6 nisin structure, 162 protective cultures, 168, 172 yeast and moulds sensitivity to natamycin, 167 antioxidants, 173±6 BHT, BHA, and TBHQ chemical structures, 175 mode of action against lipid radicals, 174 oxidative cycle, 174

831

rosemary and green tea extracts, 175±6 tocopherol and ascorbyl palmitate, 175 edible moisture barriers, 147±8 moisture barrier effectiveness, 148 moisture barrier permeability, 147 food spoilage due to water activity, 144, 145±7 foods and microorganisms that can cause food spoilage, 145 lipid oxidation (rancidity) and enzymatic browning, 146±7 water chemical reactivity, 146 foods preservation by freezing, 150±4, 155 crumb structure and volume, 152 cryoprotectants, 153 fermentation conditions for yeast, 152 freeze-thaw stability, 151±2 frozen yeast dough, 150±1 glassy state formation, 154, 155 storage stability, 152 strengthening the gluten network, 151 sucrose, 154 sucrose state diagram, 155 Surimi, 152±3 future trends, 176±7 moisture movement in food systems, 135±44 bakery product, water activity and typical shelf life, 140 emulsifier type and complexing strength with amylose, 144 Fick's law, 136 glass transition, 137±8 humectant systems, 138±40 humectants as anti-crystallisation agents, 143 modified Couchman-Karasz equation, 143 Raoult's Law, 136±7 sample relative humidity and mass increase, 141 starch retrogradation or crystallisation, 144 water activity, 135±6 water adsorption and desorption kinetics, 140, 141 water and humectant ingredients as plasticisers, 137

ß Woodhead Publishing Limited, 2011

832

Index

water on physical properties, 140, 142±3 molecular mobility, 148±50 change in log viscosity with temperature, 149 reaction rate superimposed on water activity and content, 149 physical properties of common carbohydrates and polyols, 180±3 role and influence on product stability and shelf life, 132±77 shelf life extension, 161±76 shelf life extension methods, 133±5 humectants, 134±5 microbiological, 133±4 oxidative, 134 sweetener as humectants or cryoprotectants, 154±60 Directive 95/2/EC (miscellaneous additive directive), 155±6 Directive 94/35/EC (sweeteners directive), 155 food carbohydrates glass transition temperatures, 160 increase in weight of test material vs relative humidity, 158 maltitol, 158±9 polydextrose, 159±60 sorbitol, 156±7, 158 sucrose and polydextrose solutions water activity, 160 sweetener ingredients as humectants, 156 xylitol, 157±8 `inherent stability', 694 initial rate approach, 483±5 inoculation, 514±16 inoculum, 514±16 inosine monophosphate, 785 insects beetle pests on wheat grains, 111 combating critical points in food chain, 121±6 contaminating stored food products, 107±21 other insects, 118±20 packaged foods penetration and contamination, 106±27 stored food moth pests, 117 see also mites; specific insect instant coffee, 617

Instron Universal Texture Machine, 46, 672 instrumental techniques electric nose, 392±4 schematic diagram, 393 electronic tongue, 394±5 schematic diagram, 394 food quality deterioration, 381±99 assessing food appearance, 382±4 future trends, 399 microbiological testing, 398 relative humidity, moisture and water activity, 384±5 rheological properties of liquid and semisolid foods, 387±8 infrared spectroscopy, 395±8 NIR spectrometer configurations, 396 lipid oxidation assessment, 388±92 analysis of volatiles with GC, 390±2 conjugated dienes, 390 gas chromatograph with olfactometric detector, 391 p-anisidine, 390 peroxide value, 389 thiobarbituric acid, 389 texture evaluation, 385±7 force±displacement curve, 386 intermediate moisture content, 467 intermediate moisture foods, 42, 210 intermodal freight containers, 289 International Institute of Refrigeration, 276 International Union of Pure and Applied Chemistry, 69 intrinsic factors, 42±4, 414, 460±1 IoF see indices of failure IRR see International Institute of Refrigeration irradiation, 232, 593 ISO 5495, 359 ISO 6579, 784 ISO 6658, 357 ISO 8586-1, 357 ISO 11290-1, 784 ISO 11290-2, 784 ISO/TS 21872-1:2007, 784 isotherms automatic commercialised apparatus, 78±82 DVS apparatus, 81

ß Woodhead Publishing Limited, 2011

Index general diagram of experimental device, 79 saturated salt solution method vs DVS instrument, 81 sorption and desorption kinetics, 80 conventional determination methods, 77±8 hygrometric method, 78, 79 manometric methods, 77±8 determination, 77±82 IUPAC classification, 69 IUPAC see International Union of Pure and Applied Chemistry jellies see gums and jellies Karl Fischer titration, 71, 385 khapra beetle see Trogoderma granarium (Everts) kinetic factor, 499 kinetic models, 460, 485±7 Knudsen diffusion, 65 Kreis test, 705 lactic acid bacteria, 6, 313, 317±18, 319, 528 Lactobacillus, 589 lag time, 427, 428 Lagrangian co-ordinate, 84, 85 laminated board containers, 587±8 Lasioderma serricorne (F.), 109, 123 LDPE see low density polyethylene leak indicators, 304 least shelf life first out, 311 Lepidoglyphus destructor (Schrank), 121 Lepidoptera, 115±18 lesser grain borer see Rhyzopertha dominica (F.) light instability, 536±7 lipase, 769, 781 lipid oxidation, 30, 31, 44, 146, 382, 388±92 lipolysis, 764, 781 lipoprotein lipase, 763±4 lipoxygenase, 782 Listeria monocytogenes, 15, 319±20, 329, 338, 423, 442, 784 Listeria monocytogenes-LAB growth model, 442±3 log logistic equation, 492 logistic model, 429±30 logistic regression, 411

833

long shelf life products, 341 long temperature long time, 225 low density polyethylene, 251 low oxygen modified atmosphere packs, 806±7 LSFO see least shelf life first out LTLT see long temperature long time lumped capacity model, 469 lypolysis, 683 3M Monitor Mark, 306, 308 machine vision system, 383 Magness±Taylor testers, 386 magnetic resonance imaging, 67, 384, 387 Maillard products, 553 Maillard reaction, 33, 43, 50, 71, 100, 729, 758±9 malonaldehyde, 801 malting, 527 maltitol, 158±9 malvin, 553 MAP see modified atmosphere packaging mashing, 527 `masque', 555 mass spectrometry, 391±2 mass transfer coefficient, 475 mathematical modelling, 195, 197 mathematical testing, 420 Matlab algorithms, 86 maturation, 527 MBT see 3-methyl-2-butene-1-thiol MCP see 1-methylcyclopropene; minimum convex polyhedron meat and poultry stability and shelf life, 793±809 ensuring stability and extending shelf life, 804±8 evaluation, 800±3 factors, 794±800 future trends, 808±9 meat colour, 796±8 oxidation of oxymyoglobin and deoxymyoglobin to metmyoglobin, 797 retail display cabinet, 797 meat flavour, 798±9 meat tenderness, 799±800 mechanical dough development, 659 mechanical hygrometer, 384 mechanistic models, 408

ß Woodhead Publishing Limited, 2011

834

Index

Mediterranean flour moth see Ephestia kuehniella Zeller medium shelf life products, 341 melting profile, 687 membrane filtration, 767 metal containers, 586±7 metals, 249±50 metering pump, 205 3-methyl-2-butene-1-thiol, 536 methyl salicylate, 124 1-methylcyclopropene, 648±9 mfsl see mould-free shelf life Michaelis±Menten kinetics, 51 Michaelis±Menten equation, 51±2, 473 microbial conditioning, 513 microbial loading, 794±5 microbial reactions, 245 microbial shelf life, 668±9 microbial shelf life modelling approaches, applications and opportunities, 426±37 Buchanan three-phase linear model, 429 hurdle effects quantification, 434±6 initial physiological state parameter on duration of lag phase, 428 modelling microbial growth, 426±34 relative rate of spoilage models, 436±7 Salmonellae generation time model, 433 foods and beverages, 405±51 future trends, 446±51 predictive microbiology electronic sources, 437±46 ComBase and ComBase Modelling Toolbox, 437±40 ComBase predictor, 439±40 Pathogen Modelling Program, 445±6, 447±9 Seafood Spoilage and Safety Predictor, 441±3 Sym'Previus, 443±5 predictive models by microbial response growth models, 410 growth/no-growth or growth boundary models, 410±11 inactivation and survival models, 412 microbial growth curve, 409

predictive models classification by microbial response, 407±12 predictive models development, 412±26 Box±Behnken design, 417 data analysis and modelling, 418±20 effects of pH, water activity and lactic acid on Listeria monocytogenes, 424 environmental variables, 423 experimental conditions, 414±18 limitations of using models, 425±6 model interpolation region, 422 model validation, 420±5 survivor curves, 413 microbial status, 312 microbiological safety, 594 microbiological shelf life, 800±1 microbiological spoilage, 4±5 evaluation, monitoring and measurement, 12±14 extrinsic factors, 10±11 food chill chain, 10±11 temperature effect, 10 transportation, 11 foods and beverages, 3±18 factors affecting the microbiological spoilage rate, 5±11 future trends, 17±18 implicit factors (intrinsic biotic parameters), 5±10 microbial association in foods, 8±9 yeasts and moulds in various commodities, 7 prediction, 14±15 prevention, 15±17 carbon dioxide application, 17 temperature application, 15±17 microwave processing, 231±2 microwave sterilisation, 232 mid-infrared spectroscopy, 387, 395 migration, 266 milk, 33, 34 stability and shelf life, 755±77 bacteria and related enzyme activity, 761±3 chemical composition and principal reactions, 756 control of the quality of short shelf life products, 764±8 main minerals, 758 mid-lactation milk composition, 757

ß Woodhead Publishing Limited, 2011

Index milk fat, 759±61 milk protein, 756±9 raw milk enzymes, 763±4 milk fat, 759±61 fatty acid composition, 760 milk fat globule membrane, 760 milk products control of quality of short shelf life products, 764±8 cottage cheese, 768 pasteurised milk and cream, 765±7 yoghurt and fermented milk, 767 control of stability of long life products, 770±6 butter and spread, 770±1 cheese, 774±6 cream liquers, 774 dried milk products, 771±2 evaporated milk, 773 in-can sterilised cream, 772±3 UHT processed milks and creams, 773±4 factors influencing stability of long shelf life product, 768±70 extra-cellular enzyme activity detection, 770 heat-resistant enzymes, 768±9 methods of reducing effect of heatstable enzymes, 769 stability and shelf life, 755±77 milk protein, 756±9 relative abundance and selected properties of caseins, 757 see also casein; whey proteins mill moth see Ephestia kuehniella Zeller minimal spoilage level, 406, 430 minimum convex polyhedron, 422 Minolta Chromameter, 383 mites combating critical points in food chain, 121±6 contaminating stored food products, 107±21 from other families, 120±1 packaged foods penetration and contamination, 106±27 see also specific mite modified atmosphere packaging, 6, 17, 41, 54, 256, 260, 282, 460, 642, 651±2 moistness, 670 moisture content, 467±72, 665

835

measurement, 384±5 moisture determination, 385 moisture loss, gain and migration conditions for moisture migration and foods by moisture transfer, 97±100 bread moisture transfer, 99 moisture transfer with atmosphere, 97±8 moisture transfer within the product, 98±100 food products, 63±100 isotherm determination, 77±82 automatic commercialised apparatus, 78±82 conventional methods, 77±8 DVS apparatus, 81 general diagram of experimental device, 79 saturated salt solution method vs DVS instrument, 81 sorption and desorption kinetics, 80 measuring, monitoring and predicting, 70±93 moisture transfer mechanism, 64±70 diffusion through homogeneous medium, 66 general considerations, 64±7 isotherms IUPAC classification, 69 mathematical expression for sorption isotherm description, 70 moisture transfer from dough to dry raisins after 3 days contact, 65 porous media, 66 sorption isotherm characterisation, 67±70 typical food adsorption and desorption isotherms, 68 predicting moisture transport phenomena, 83±93 diffusion coefficient from moisture absorption in edible carrageenanbased films, 91 dry biscuit moisture uptake, 86 from foodstuff to surrounding atmosphere and within foodstuff, 83±6 models assumptions and boundary conditions, 85 moisture transfer prediction in composite foods, 93 Schroeder paradox, 89

ß Woodhead Publishing Limited, 2011

836

Index

shelf life prediction for wrapped food model, 92 three-steps mechanism of moisture transfer through barrier layers, 87 through barrier packaging and/or edible coatings, 86±93 related shelf life caking index vs time for fish protein hydrolysates, 96 crispness, 94±6 crystallisation, 97 plasticisation, 94 softness, 95±6 starch-based extrudates vs water activity sensory crispness, 95 stickiness, caking and collapse, 96±7 related to shelf life, 93±7 water activity determination, 73±7 capacitance or resistive hygrometer, 75 capacitive sensor principle for relative humidity measurement, 75 chilled mirror dew point principle, 76 dew point hygrometer, 75, 76 manometric hygrometer, 76 relative humidity spectroscopy determination, 77 water content measurement, 70±3 chemical analysis, 71±2 gas chromatography, 72 physical techniques, 71 spectroscopic techniques, 72±3 thermal analysis, 72 water migration measurement, 82±3 concentration profile, 82±3 nuclear magnetic resonance imaging, 83 stray field nuclear magnetic resonance imaging, 83 moisture management, 134, 135 moisture migration, 665±6, 718±19 mechanism involved, 666±7 moisture sorption isotherm, 247 moisture transfer conditions for moisture migration and foods, 97±100 bread moisture transfer, 99 moisture transfer with atmosphere, 97±8

moisture transfer within the product, 98±100 mechanism in food products, 64±70 diffusion through homogeneous medium, 66 general considerations, 64±7 isotherms IUPAC classification, 69 mathematical expression for sorption isotherm description, 70 moisture transfer from dough to dry raisins after 3 days contact, 65 porous media, 66 sorption isotherm characterisation, 67±70 typical food adsorption and desorption isotherms, 68 predicting moisture transport phenomena, 83±93 diffusion coefficient from moisture absorption in edible carrageenanbased films, 91 dry biscuit moisture uptake, 86 from foodstuff to surrounding atmosphere and within foodstuff, 83±6 models assumptions and boundary conditions, 85 moisture transfer prediction in composite foods, 93 Schroeder paradox, 89 shelf life prediction for wrapped food model, 92 three-steps mechanism of moisture transfer through barrier layers, 87 through barrier packaging and/or edible coatings, 86±93 `moisture vapour transpiration rate', 676 monounsaturated fatty acids, 685 Morganella morganii, 442 Morganella psychrotolerans, 442 mould-free shelf life, 674 mould mite see Tyrophagus putrescentiae (Schrank) moulds, 6 MRI see magnetic resonance imaging MSL see minimal spoilage level MVS see machine vision system myofibrillar proteins, 780 N-acetyl-cysteine, 564 natamycin, 164, 167±8, 169±71

ß Woodhead Publishing Limited, 2011

Index food legislation on natamycin use, 169±71 structure, 167 yeast and moulds sensitivity, 167 natural cooling, 223 near infrared spectroscopy, 384, 395, 396, 398 neck rings, 582±3 Necrobia spp., 111 New Zealand Dairy Research Institute, 775±6 NFC see `not from concentrate' niacin, 747 nicotinamide, 747 nicotinic acid, 747 Niptus hololeucus, 113 NIR see near infrared spectroscopy nisin, 161±4, 165±6 addition levels in food samples, 164 list of products and countries for approved use, 165±6 structure, 162 NLME models see non-linear mixed effects models NMR see nuclear magnetic resonance `no model' approach, 498±500 non-climacteric fruits, 644 non-enzymatic browning, 494±5 non-linear kinetic models, 491±2 non-linear mixed effects models, 476±7 `not from concentrate', 572, 580 nougat, 738 nuclear magnetic resonance, 47, 66, 83, 137, 559, 564, 673 nucleotides, 785±6 o-diquinones, 552 OAV see odour activity value odour activity value, 564 odour response, 353 Oecophoridae, 115 Oenococcus oeni, 554 off-flavours, 783 scheme of enzymatic reactions in postmortem seafoods, 783 Ohmic heating, 230 oil-in-water emulsions, 38, 205±6 oil refining, 691 Oil Stability Index method, 707 oils see fats and oils oleic acid, 759 oligonucleotide probe, 787

837

olive oil, 711 oloroso sherries, 541 OnVu TTI, 306, 316 optical hygrometers, 384 OptiPa, 419 ORAC method see Oxygen Radical Absorbance Capacity method organic acids, 209 Oryzaephilus mercator (Fauvel), 114 Oryzaephilus surinamensis (L.), 114, 122 OSI method see Oil Stability Index method Ostwald ripening, 152, 740 OTRs see oxygen transmission rates oven drying method, 672 overall migration, 266 oxidation, 31, 134 see also specific oxidation oxidative rancidity, 30 oxidative reactions, 781±3 Oxygen Radical Absorbance Capacity method, 712 oxygen scavengers, 43±4 oxygen transmission rates, 249 p-anisidine, 390 `pack-and-pray' approach, 652 `Pack-in-MAP', 652 packaged foods beetle pests on wheat grains, 111 Coleoptera, 107, 109±15 Anobiidae, 109±10 Bostrichidae, 110±11 Cleridae, 111 Cucujidae, 111±12 Curculionidae, 112 Dermestidae, 112±14 Silvanidae, 114 Tenebrionidae, 114±15 Trogossitidae, 115 combating critical points in food chain, 121±6 arrival at the food processing facility, 121±2 bag stacks on pellets in store, 122 hole made by moth larvae, 124 mechanised `form-fill-seal' production line for packaging ham, 124 packaging, 122±4 contaminating stored food products, 107±21

ß Woodhead Publishing Limited, 2011

838

Index

Acaridae, 120 Tyrophagus putrescentiae (Schrank), 120 future trends, 126±7 food protection, 126±7 pest detection and control, 126 insects and mites penetration and contamination, 106±27 Blatta orientalis mouthparts, 109 properties of materials for food products packaging, 108 Lepidoptera, 115±18 Corcyra cephalonica (Stainton), 116 Ephestia kuehniella Zeller, 117 Esphestia cautella (Walker), 116 Esphestia elutella (Hubner), 116±17 Hofmannophila pseudospretella (Stainton), 115 Oecophoridae, 115 Plodia interpunctella (Hubner), 117±18 Pyralidae, 116 stored food moth pests, 117 from other families, 120±1 Carpoglyphus lactis (L.), 120±1 Glycyphagus domesticus (Degeer), 121 Lepidoglyphus destructor (Schrank), 121 other insects, 118±20 ants, 119±20 Dictyoptera, 118 Hymenoptera, 119 Psocoptera, 118, 119 other insects and mites associated with stored food, 119 storage and distribution, 125±6 in the larder, 125±6 at the retailer, 125 packaging, 40±2, 122±4, 228±30, 282±3, 527, 573±4, 585±8, 804 food and beverage shelf life, 244±69 future trends, 269 glass, 585±6 hole made by moth larvae, 124 key package properties related to shelf life, 253±60 barrier, 253±7 package closures and integrity, 258±60

permeability coefficients of foods packaging polymers and permeants, 255 surface area : volume ratio, 257±8 surface areas of different packages shapes, 257 laminated board containers, 587±8 major materials, 249±53 glass, 250 metals, 249±50 paper, 250 mechanised `form-fill seal' production line for packaging ham, 124 metal containers, 586±7 packaging migrants, 266±9 antimony, 267±8 epoxidised soy bean oil, 266±7 photoinitiators, 268±9 tin, 268 plastic containers, 587 plastics, 251±3 polyamides, 253 polyesters, 252±3 polyolefins, 251 regenerated cellulose, 253 substituted olefins, 251±2 predicting shelf life of packaged foods and beverages, 260±5 microbial shelf life, 265 moisture exchange and shelf life, 260±3 moisture sorption isotherm for cereal, 262 oxygen exchange and shelf life, 264 spinach soup gas permeability effect, 265 role in extending food and beverage shelf life, 245±9 moisture sorption isotherm, 247 see also vacuum packaging packed fats, 700±1 paired comparison test, 359 palm oil, 702 pantothenic acid, 747 paper, 250 parasitic wasps, 119 pass/fail criteria, 518±19 pasteurisation, 16, 17, 32, 232 psychrotrophic or acid tolerant sporefor mers, 16 treatments classification, 224±5 high temperature pasteurisation, 225

ß Woodhead Publishing Limited, 2011

Index low temperature pasteurisation, 225 ultra-high-temperature pasteurisation, 225 ultra pasteurisation temperature, 225 vegetative micro-organisms, 16 pasteurisation units, 221 pastilles, 734 appearance under light microscope and schematic diagram of structure, 735 star diagram of texture attributes, 736 see also gums and jellies pastry key `fresh' characteristics, 662±3 manufacture overview, 661 pastry shell, 669 Pathogen Modelling Programme, 445±6, 447±9, 520 pattern recognition techniques, 392 PCR see polymerase chain reaction pectin, 151, 152, 581±2 Pediococcus, 554 PEN see polyethylene naphthalate PEN2, 392±3 Perfringens Predictor, 438 Perkin Elmer DSC7, 142 peroxide value, 47, 389, 627±8, 704 peroxides, 388±9 PET see polyethylene terephthalate phosphine, 122 phospholipases, 781 Photobacterium phosphoreum, 441, 442 Photobacterium phosphorus, 784 photoinitiators, 268±9 photooxidation, 33, 690±1 physical instability foods and beverages, 29±55 future trends, 55 measurement, 44±8 chemical measurements, 47±8 instrumental methods, 45±8 physical measurements, 46±7 sensory panels, 44±5 physical deterioration, 34±9 chill injury, 37±8 crystal growth, 38 emulsion breakdown, 38±9 mechanical damage, 34±5 moisture change and glass transition, 35±7 starch gelatinisation and retrogradation, 37

839

physical deterioration modelling, 459±77 predicting and monitoring, 49±53 prevention, 53±5 physical reactions, 246 physiochemical changes, 756 piston homogenisers, 205 plasmin, 764 plastic containers, 587 plasticisation, 94 plastics, 251±3 polyamides, 253 polyesters, 252±3 polyolefins, 251 regenerated cellulose, 253 substituted olefins, 251±2 Plodia interpunctella (Hubner), 117±18 PMP see Pathogen Modelling Programme polydextrose, 159±60 food carbohydrates glass transition temperatures, 160 solutions and sucrose water activity, 160 water activity, 160 polyethylene naphthalate, 587, 592 polyethylene terephthalate, 587, 592 polymerase chain reaction, 398, 787 polystyrene, 252, 587 polyunsaturated fatty acids, 685 polyvinyl chloride, 251±2 polyvinylidene chloride, 252 polyvinylpolypyrrolidone, 530, 531, 553 Porapaq-Q, 72 post-fill or in-pack heating, 220±1, 222 retort types main characteristic, 222 post-heat treatment contamination, 765±6 pasteurised milk production, 765 Power Law model, 387 PPP see product processing and packaging practical storage life, 276±7, 281, 282 pre-adaptation, 513 pre-cooling, 648 pre-exponential factor, 50 pre-fill heating, 215, 217±19 design and construction scheme for continuous heat exchangers, 218 `precision viticulture', 543 predictive microbiology, 338 predictive models, 407 classification by microbial response, 407±12

ß Woodhead Publishing Limited, 2011

840

Index

growth models, 410 growth/no-growth or growth boundary models, 410±11 inactivation and survival models, 412 development for microbiological safety and stability, 412±26 data analysis and modelling, 418±20 limitations of using models, 425±6 model validation, 420±5 experimental considerations, 414±18 data generation, 417±18 experimental design, 414±17 microbial growth, 426±34 individual cell lag time, 431±2 primary growth models, 427±31 secondary growth models, 432±3 secondary lag models, 433±4 model validation, 420±5 domain of validity, 422±3 mathematical testing and examination, 420±1 product validation, 423±5 premature browning, 552 preservation, 246 preservatives, 44 pressure-assisted thermal sterilisation, 230±1 pressure shift freezing, 38 primary chilling, 10±11, 283±6 primary models, 408 primary packaging, 229±30, 245 principal component analysis, 365±6 pro-oxidants, 701±3 probability product failure, 464 processing, 200±4 filling and packaging, 228±30 primary packaging, 229±30 secondary packaging, 230 flow, 201±2 food and beverage shelf life, 184±236 hygiene, 234±5 low and intermediate moisture foods production, 209±11 main quality change factors and interaction with processing, 187±9 product and process design, 198±200 future trends, 235±6 heating mechanisms, 213±15 conduction, 214 convection, 214

radiation, 214±15 manufacturing areas, 202±4 novel processes, 230±4 irradiation ± pasteurisation and sterilisation, 232 microwave and radio frequency processing, 231±2 Ohmic, impedance or inductive heating, 230 pressure-assisted thermal sterilisation, 230±1 pulsed electric fields, 231 ultra high pressure treatment, 232±4 pre-fill and post-fill heating, 215±21, 222 aseptic packaging, 219±20 design and construction scheme for continuous heat exchangers, 218 post-fill or in-pack heating, 220±1, 222 pre-fill heating, 215, 217±19 retort types main characteristic, 222 types, 216 predictive modelling, 195±8 models for in-line heat treatments, 197±8 models for in-pack heat treatments, 196±7 shelf life and stability, 189±98 challenge studies, 194 factors controlling the types and rates of food quality changes, 190 HACCP principles applied to quality, 193 linking design to quality management using HACCP approach, 192 process factors influencing shelf life, 189±91 quality and shelf life management, 191±4 shelf life testing, 195 thermal processing, 211±28 blanching, 221, 223 chilling and freezing, 226±7 cooking, 224 heating mechanisms, 213±15 other effects of heating, 213 pasteurisation, 224±5 sterilisation, 225±6 thawing, 227±8 unit operations, 204±9

ß Woodhead Publishing Limited, 2011

Index filtration and reverse osmosis, 207±8 food materials and products transfer and weighing, 204 mixing, 207 preservation technology, 208±9 pumping and homogenisation, 205±6 size reduction, 206±7 product processing and packaging, 277, 281±3 packaging, 282±3 process, 281±2 product, 277, 281 product shelf life, 484 product validation, 423±5 progressive profiling, 365 protein aggregation, 759 protein degradation, 758 protein oxidation, 34 proteinase, 769 proteinase A, 535 proteolysis, 4, 34, 775, 780±1 proteolytic enzymes, 530, 531 Pseudomonas fluorescens, 6, 416, 761±2 Pseudomonas fragi, 6 Pseudomonas lundensis, 6 Pseudomonas putida, 416 Pseudomonas spp., 6 PSF see pressure shift freezing PSL see practical storage life Psocoptera, 118 psychotrophic Gram-negative bacteria, 761±2 creamery silo milk, 761 psychrometric charts, 76 Ptinidae, 113±14 ptinids, 113±14 puff pastry, 661 pulsed electric fields, 231 pulsed light, 233±4 PVC see polyvinyl chloride PVdC see polyvinylidene chloride PVPP see polyvinylpolypyrrolidone Pyralidae, 116 pyridoxine (vitamin B6), 747 Q10 factor, 465, 488 QCPs see quality control points QDA see quantitative descriptive analysis quality control points, 192 quality index, 309 quality index methods, 786±7 quantitative descriptive analysis, 362±3

841

vocabulary development, 363 quinones, 558 radiation, 214±15 radio frequency identification tools, 450 radio frequency processing, 231±2 rail transport, 288±9 rancidity, 282±3, 669, 684 Rancimat Induction Period, 695, 696, 706±7 Raoult's law, 136±7, 154 rapid methods, 785 rapid processing, 659 raw milk enzymes, 763±4 lipoprotein lipase, 763±4 plasmin, 764 ready-to-drink coffee, 617 Recommended International Code of Practice General Principles of Food Hygiene, 192 reduced extracts, 537 reference temperature, 309 reflectance spectrophotometer, 46, 383 refrigeration systems retail display, 290±3 mean temperature and temperature range for cabinets examined, 292 position of maximum temperatures, 291 temperatures in supermarket cabinets, 293 weight loss from meat samples with and without humidification, 293 weight loss from produce samples with and without humidification, 294 transport, 287±90 air freight, 289 home delivery, 290 intermodal freight, 289 road and rail transport, 288±9 refrigerators overall mean temperatures, 297 positions of lowest and highest mean temperatures, 297 temperature range, 298 temperatures measured in surveys, 296 Regulation (EC) No. 852/2004, 325 Regulation (EC) No. 1935/2004, 330 relative humidity, 35, 40, 42, 97, 135, 384 relative lag time, 428, 433±4

ß Woodhead Publishing Limited, 2011

842

Index

relative rate of spoilage, 436±7 models, 436±7, 441 relative to ideal scales, 362 remote temperature devices, 221 resistive-based sensors, 384 respiration, 472±3 respiration rates, 472±3 respiratory climacteric, 644 response function, 310 response surface models, 432 retinol, 745 retrograde, 664 reverse osmosis, 207±8 reverse transcriptase polymerase chain reaction, 787 rheological properties, 387±8 Rhyzopertha dominica (F.), 110, 123 rice moth see Corcyra cephalonica (Stainton) RIP see Rancimat Induction Period road transport, 288±9 Robusta coffee see Coffea canephora roll-on tamper-evident, 259 root mean square error, 420 ropiness, 554 rosemary, 711 roseÂs, 557 ROTE see roll-on tamper-evident RRS see relative rate of spoilage RTD see remote temperature devices rust-red grain beetle see Cryptolestes ferrugineus (Stephens) Safety Monitoring and Assurance System, 311±12, 319 Salmonella, 329, 579 Salmonella spp., 784 salt reduction, 521, 679 sample replication, 518 saturated fatty acids, 685 Scaal oven test, 705±6 scaling, 361±2 factors that affect type of scale used and its construction, 362 data-handling facilities, 362 expertise of assessors, 362 number of assessors, 362 purpose of test, 362 scale types, 361±2 Schroeder's paradox, 88 illustration, 89 SDE see steam distillation extraction

seafood stability and shelf life, 779±88 evaluation, 784±7 factors affecting stability, 780±3 future trends, 787±8 microorganisms involved in spoilage, 783±4 Seafood Spoilage and Safety Predictor, 437, 441±3 microbial spoilage models, 441±2 other relevant features, 442±3 relative rate of spoilage models, 441 second-order reactions, 50 secondary chilling, 11 secondary lag models, 433±4 secondary models, 408 secondary packaging, 230 secondary processing, 286 self-diffusion, 66 sensors, 786 sensory analysis, 802±3 sensory evaluation deterioration mechanisms and limiting changes beverages, 379 cereal and other dry products, 380 dairy products, 380 fruit and vegetable products, 378 meat and meat products, 379 developing the sensory plan, 603 case studies, 603±13 case study 1 experimental design, 608±9 case study 2 profiling experimental design, 612 case study comparison, 604±5 considerations before developing shelf life plan, 599±603 discrimination tests, 358±61 analysis, 360±1 difference from control test, 360 duo-trio test, 359 paired comparison test, 359 triangle test, 359±60 food shelf life assessment, 350±75, 378±80 consumer acceptability testing, 366 sensory shelf life testing standardisation, 374±5 future trends sensory specifications, 375 survival analysis, 375

ß Woodhead Publishing Limited, 2011

Index instrumental methods, 372±4 appearance, 372±3 aroma and flavour, 373±4 texture, 374 principles, 352±4 factors influencing quality of sensory data, 354 human senses, 352±4 main human senses and how they interact, 352 quantitative descriptive tests, 361±6 free choice profiling, 364 quantitative descriptive analysis, 362±3 scaling procedures, 361±2 simple descriptive procedures, 362 Spectrum method, 363±4 statistical analysis of scaled data, 365±6 time-related methods, 364±5 requirements for sensory analysis, 354±8 components, 355 data handling, analysis and presentation, 358 objectives, 355 sensory testing environment, 355±6 sensory testing procedures, 356 test procedures, 356±7 sensory shelf life data interpretation, 370±2 changes in consumer acceptability, 373 changes in sensory attributes following manufacture, 370 level of change of a given attribute, 372 non-linear attribute change, 371 sensory shelf life tests design, 368±70 partially staggered, drawn sample, stored sample, 369 sensory shelf life tests operation, 366±7 ethical considerations, 367 references for sensory shelf life assessment, 367 selection of tests for shelf life assessment, 366±7 soft drink shelf life assessment determining shelf life, 597±8 estimating shelf life, 597 future trends, 613±14

843

monitoring shelf life, 598±9 risk-based approached, 596 soft drink shelf life assessment, 594±614 test subjects selection and training, 357±8 analytical tests, 357±8 hedonic tests, 358 sensory shelf life, 595 shelf life, 14, 16, 132±3, 161±76, 186, 326, 334±8, 350±1, 459, 756 beer, 527±37 biological instability, 528±9 flavour instability, 531±3 foam instability, 533±5 gushing, 536 light instability, 536±7 physical instability, 529±31 bread and other bakery products, 657±80 affecting factors, 663±9 ensuring stability and extending shelf life, 673±8 evaluating the shelf life, 669±73 future trends, 678±80 key `fresh' characteristics, 662±3 manufacture overview, 658±61 coffee products, 615±36 critical events affecting stability and shelf life, 617±20 ensuring stability and extending shelf life of coffee, 620±4 evaluating the shelf life of coffee, 624±36 future trends, 636 confectionery products, 716±40 aerated confectionery, 737±40 affecting factors, 717±20 chocolate and chocolate products, 720±7 gums and jellies, 733±7 sugar glass, 727±9 toffee, 729±33 defined, 132±3 extension methods, 133 humectants, 134±5 microbiological, 133±4 oxidative, 134 fats and oils, 683±714 ensuring stability and extending shelf life, 707±12, 713 evaluating the shelf life, 703±7

ß Woodhead Publishing Limited, 2011

844

Index

factors affecting stability and shelf life, 693±703 future trends, 712±14 oxidation and hydrolysis mechanisms, 684±93 food and beverage distribution, display and consumer handling, 273±99 cold chain, 274±5 future trends, 298±9 sectors of cold chain, 283±93 storage life, 276±83 food and beverage packaging, 244±69 future trends, 269 major packaging materials, 249±53 packaging migrants, 266±9 food sensory evaluation, 350±75 fruit juices and soft drinks, 571±93 ensuring product stability and extending shelf life, 584±8 fruit juices, 572±3 future trends, 591±3 influencing factors, 574±83 packaging, 573±4 shelf life determination, 588±91 soft drinks, 573 fruits and vegetables, 641±53 controlled and modified atmosphere packaging for longer shelf life, 650±2 extending the shelf life, 648±50 future trends, 652±3 loss of stability and quality deterioration, 643±7 future trends, 176±7 IFST definition, 595 influencing factors, 460±2 critical quality parameters, 461±2 degradation, 460±1 ingredients for extension, 161±76 antimicrobials, 161±73 antioxidants, 173±6 ingredients role and influence, 132±77 edible moisture barriers, 147±8 food spoilage due to water activity, 144, 145±7 foods preservation by freezing, 150±4, 155 moisture movement in food systems, 135±44 molecular mobility, 148±50 sweetener as humectants or cryoprotectants, 154±60

meat and poultry, 793±809 ensuring stability and extending shelf life, 804±8 evaluation, 800±3 factors affecting stability, 794±800 future trends, 808±9 milk and milk products, 755±77 bacteria and related enzyme activity, 761±3 chemical composition and principal reactions, 756±61 control of the quality of short shelf life products, 764±8 control of the stability of long life milk, 770±6 raw milk enzymes, 763±4 stability of long shelf life products, 768±70 packaging in extending shelf life, 245±9 moisture sorption isotherm, 247 predicting shelf life of packaged foods and beverages, 260±5 microbial shelf life, 265 moisture exchange, 260±3 moisture sorption isotherm for cereal, 262 oxygen exchange and shelf life, 264 spinach soup gas permeability effect, 265 processing in food and beverage, 184±236 filling and packaging, 228±30 future trends, 235±6 hygiene, 234±5 low and intermediate moisture foods production, 209±11 main quality change factors and interaction with processing, 187±9 novel processes, 230±4 processing, 200±4 product and process design, 198±200 thermal processing, 211±28 unit operations, 204±9 quality and management, 191±4 HACCP principles applied to quality, 193 linking design to quality management using HACCP approach, 192 related key package properties, 253±60

ß Woodhead Publishing Limited, 2011

Index barrier, 253±7 package closures and integrity, 258±60 permeability coefficients of foods packaging polymers and permeants, 255 surface area : volume ratio, 257±8 surface areas of different packages shapes, 257 related moisture loss, gain and migration, 93±7 seafood, 779±88 evaluation, 784±7 factors affecting stability, 780±3 future trends, 787±8 microorganisms involved in spoilage, 783±4 sensory evaluation for soft drink assessment, 594±614 case studies, 603±13 considerations before developing shelf life plan, 599±603 determining shelf life, 597±8 developing the sensory plan, 603 estimating shelf life, 597 future trends, 613±14 monitoring shelf life, 598±9 risk-based approached, 596 sensory tests, 366±7 design, 368±70 interpretation of sensory data, 370±2 references for assessment, 367 shelf life assessment, 366±7 standardisation, 374±5 smart packaging for food and beverage monitoring, 303±21 future trends, 320±1 time-temperature integrators, 303±4 TTI principles and application for shelf-life monitoring, 304±8 TTI requirements and selection, 309±11 TTI use for shelf-life management and optimisation in cold chain, 311±20 and stability, 189±98 challenge studies, 194 factors controlling the types and rates of food quality changes, 190 models for in-line heat treatments, 197±8

845

models for in-pack heat treatments, 196±7 predictive modelling, 195±8 process factors influencing shelf life, 189±91 and storage trials, 339±45 testing, 195 vitamin-fortified foods, 743±52 affecting factors, 745±9 ensuring stability and extending shelf-life, 749±50, 751 evaluation, 750, 751±2 future trends, 752 wine, 540±64 changes during the shelf life, 551±8 evaluating the shelf life, 558±9 factors affecting stability and shelf life, 542±51 future trends, 564 preventing quality deterioration at or post-bottling, 559±63 sensory significance of shelf life changes, 563±4 shelf life decision system, 311 shelf life models, 460 shelf life tests, 342±4 Shewanella putrefaciens, 442 Shigella, 579 short shelf life products, 341 silica gel preparations, 530±1 Silvanidae, 114 single accelerating factor, 487±92 Sitophilus spp. (grain weevils), 112 SLDS see shelf life decision system slip melting point, 697 smart packaging monitoring and managing food and beverage shelf life, 303±21 future trends, 320±1 time±temperature integrators, 303±4 TTI principles and application for shelf-life monitoring, 304±8 TTI requirements and selection, 309±11 TTI use for shelf-life management and optimisation in cold chain, 311±20 SMAS see Safety Monitoring and Assurance System soft drinks, 573 sensory evaluation for shelf life assessment, 594±614

ß Woodhead Publishing Limited, 2011

846

Index

case studies, 603±13 considerations before developing shelf life plan, 599±603 determining shelf life, 597±8 developing the sensory plan, 603 estimating shelf life, 597 future trends, 613±14 monitoring shelf life, 598±9 risk-based approached, 596 stability and shelf life, 571±93 ensuring product stability and extending shelf life, 584±8 future trends, 591±3 influencing factors, 574±83 shelf life determination, 588±91 solid phase microextraction, 391, 785 solubility coefficient, 87 solvent extraction, 71 sopropylthioxanthone, 268±9 sorbic acid, 209 sorbitol, 138, 154, 155, 156±7, 158 increase in weight of test material vs relative humidity, 158 sorption isotherm, 67 zones, 68±9 sorption isotherms, 469±70 specific migration, 266 specific spoilage organisms, 406±7, 430± 1 spectral fingerprint, 392 spectrophotometry, 383 spectroscopic techniques, 72±3 microwave spectroscopy, 73 near infrared, 73 NMR spectroscopy, 72±3 spectroscopy, 559, 564 Spectrum method, 363±4, 803 SPME see solid phase microextraction spoilage criterion, 430 sponge and dough, 659 spray chilling, 11 square-root models, 432, 434, 436, 442 SSO see specific spoilage organisms stabilising agents, 530±1 stability, 198 staleness, 670 staling, 618, 663±5, 678 limiting in bread, 677±8 methods of assessment in bakery products, 672±3 Staphylococcus aureus, 139 state diagram, 36±7

static headspace, 391 steam distillation extraction, 390±1 steam injection processes, 219 stearic acid, 759 Stegobium paniceum (L.), 110, 123 sterilisation, 17, 32, 224, 225±6, 232 sterilised cream, 772±3 stickiness, 96±7, 728±9, 732 storage, 286±7 storage conditions, 287 optimum conditions, 340 typical or average conditions, 340 worst case conditions, 340 storage life, 276±83 storage temperature, 277 STRAFI-NMR see stray field nuclear magnetic resonance imaging straight dough bulk fermentation, 659 stray field nuclear magnetic resonance imaging, 83 sucrose, 154 state diagram, 155 water activity, 160 sugar, 521 sugar bloom, 724 sugar glass, 727±9 shelf life improvement, 728±9 structure and influence of composition on glass transition, 728 3-sulfanyhexan-1-ol, 556 sulphur dioxide, 209 `superfoods', 711 sur lies maturation, 544±5 Surface Measurement Systems, 78 Surimi, 152±3 surrogate strains, 514 survival models, 408±9, 412 Swift test, 706 Sylvester test, 706 Sym'Previus, 419, 443±5, 520 database, 443 growth/no-growth interface simulation module, 444 growth simulation module, 443±4 other relevant features, 445 growth curve fitting tool, 445 probabilistic module, 445 thermal destruction module, 445 synergism, 709 t-tests, 365 taste, 353

ß Woodhead Publishing Limited, 2011

Index TA.XT2 Universal Texture Analyser, 46, 385 TBA test see thiobarbituric acid test TBHQ see tert-butyl hydroquinone TC-NMR see time-domain nuclear magnetic resonance TCA see 2,4,6-trichloroanisole TCD see thermal conductivity detector TDLAS see Tunable Diode Laser Absorption Spectroscopy TDN see trimethyl-1,5dihydronaphthalene temperature, 10, 15±17 Tenebrionidae, 114±15 Tenebroides mauritanicus (L.), 115, 123 terroir, 542 tert-butyl hydroquinone, 134, 709 tertiary models, 408 TetraPak, 588 texture, 353, 374 evaluation, 385±7 texture profile analysis, 385, 386, 671±2 thawing, 227±8 thermal conductivity detector, 72 thermal processing, 211±28 blanching, 221, 223 chilling and freezing, 226±7 cooking, 224 heating mechanisms, 213±15 other effects of heating, 213 pasteurisation, 224±5 pre-fill and post-fill heating, 215±21, 222 sterilisation, 225±6 thawing, 227±8 thiobarbituric acid, 389 thiobarbituric acid test, 705 thiobarbituric acid value, 47±8 `threshold moisture content', 728 time-domain nuclear magnetic resonance, 73 time-intensity methods, 364±5 time-resolved spectroscopy, 384 time-to-detection measurements, 418 time±temperature indicators, 52±3 time±temperature integrators, 303±4, 450 principles of application, 304±8 diffusion-based 3M Monitor Mark TTI, 308 enzymatic Checkpoint TTI response scale, 307

847

Microbial TTI (eO) response scale, 307 polymer-based Fresh-Check TTI, 307 solid state photochromic OnVu TTI, 307 TT Sensor TTI, 307 properties, 305 requirements and selection, 309±11 applying TTI as quality monitors, 310 shelf-life management and optimisation and cold chain Check Points TTIs response, 315 field test simulated chill chain conditions, 314 lactic acid bacteria log counts and remaining enzyme activity, 320 lactic acid bacteria on MAP minced beef, 318 microbial load and rationale of SMAS-based split, 313 OnVu TTI response, 317 shelf-life management and optimisation in cold chain, 311±20 time±temperature tolerance, 502 tin, 268 tin-free steel, 250 tinplate, 249 tobacco beetle, 109 tocopherol, 711, 749 tocotrienol, 749 toffee, 729±33 microstructural changes affecting texture, 730±1 schematic diagram of toffee emulsions, 731 sensory attributes monitored during storage of toffee, 733 shelf life assessment, 731±3 structure and composition, 729±30 total oxidation value see totox value total viable count, 418 totox value, 704±5 TPA see texture profile analysis `traditional' pathogens, 519 trans fatty acids, 685 transpiration, 473±6 transpiration rate, 474 triangle test, 359±60 Tribolium castaneum (Herbst), 114±15, 122

ß Woodhead Publishing Limited, 2011

848

Index

Tribolium confusum J. du Val, 114±15 2,4,6-trichloroanisole, 551, 561, 563 triglyceride molecule, 685 trimethyl-1,5-dihydronaphthalene, 547 1,1,6-trimethyl-1,2-dihydronaphthalene, 556 trimethylamine, 784 tristimulus colorimeter, 46, 383 Trogoderma granarium (Everts), 113 Trogoderma variabile, 123 Trogossitidae, 115 TT Sensor TTI, 306 TTD measurements see time-to-detection measurements TTT see time±temperature tolerance Tunable Diode Laser Absorption Spectroscopy, 77 tunnel pasteurisers, 221±2 TVC see total viable count Tyrophagus putrescentiae (Schrank), 120 UHT processes, 212±13 UHTP see ultra-high-temperature pasteurisation UK Rich Tea product, 666 ultra filtration, 207 ultra high pressure treatment, 232±4 ultra-high-temperature pasteurisation, 225 ultra pasteurisation, 225 ultrasonic humidification systems, 292 ultraviolet hygrometers, 384 uncompetitive inhibition, 473 unipolar scales, 361 US Army Natick Soldier Systems Centre, 231 `use by', 327 UV beams, 232 vacuum cooling, 11 vacuum-oven drying, 71 vacuum packaging, 808 vacuum packing, 282 van der Waals forces, 69, 74 vegetables see fruit and vegetables Vibrio cholera, 784 Vibrio parahaemolyticus, 784 Vibrio vulnificus, 784 visual senses, 352±3 vitamin A, 745 vitamin B2, 746±7 vitamin B12 (riboflavin), 748 vitamin B1 (thiamin), 745

vitamin C, 748 vitamin D, 748 vitamin degradation, 745 vitamin E, 749 vitamin-fortified foods ensuring stability and extending shelflife, 749±50, 751 commercially available forms of vitamins, 751 factors affecting stability and shelf life, 745±9 biotin, 748 folic acid, 747 niacin, 747 pantothenic acid, 747 pyridoxine, 747 vitamin A, 745 vitamin B1, 745 vitamin B2, 746±7 vitamin B12, 748 vitamin C, 748 vitamin D, 748 vitamin E, 749 vitamin K, 749 factors affecting vitamin stability during processing and storage, 746 future trends, 752 recommended daily allowances for vitamins, 744 shelf life evaluation, 750, 751±2 stability and shelf-life, 743±52 vitamin K, 749 VITSAB Check Point, 450 volumetric titration, 72 Warner±Bratzleer shear fixture, 386 water activity, 35, 42, 43, 46, 53, 135±6, 147, 189, 191, 209, 246±7, 467±72, 667±8, 717 defined, 73, 74 determination, 73±7 food spoilage, 144, 145±7 foods and microorganisms that can cause food spoilage, 145 lipid oxidation (rancidity) and enzymatic browning, 146±7 water chemical reactivity, 146 measurement, 384±5, 672 sucrose and polydextrose solutions, 160 variation with time, 471

ß Woodhead Publishing Limited, 2011

Index Water Activity Group, 77 water-in-oil emulsions, 38, 206 water loss, 473±6 water vapour permeability, 87 water vapour transmission rates, 87, 249 waterproof packing, 282 weeping, 740 Weibull distribution, 463 Weibullian model, 503 wet and dry bulb psychrometry, 384 whey proteins, 758 wild beer see gushing wild yeast, 529 Williams±Landel±Ferry model, 52, 493 wine changes during the shelf life, 551±8 appearance, 552±5 gustatory changes, 555 olfactory changes, 555±8 evaluating the shelf life, 558±9 factors affecting stability and shelf life, 542±51 factors affecting stability and shelf life prior to bottling, 542±6 shift in colour of red wines during ageing, 546 vinification conditions, 542±6 viticultural conditions, 542±3 future trends, 564 preventing quality deterioration at or post-bottling, 559±63 bottle closure and orientation, 560±2 fining, filtration and disinfection, 559±60 storage container, 562

849

sulphur dioxide addition, 560 temperature control, 562±3 sensory significance of shelf life changes, 563±4 shelf life, 540±64 storage conditions of bottled wine, 546±51 changes that accrue under different storage temperatures, 549 differences in aroma composition as affected by ageing and storage temperature, 548 environmental contaminates, 551 light exposure, 550 oxygen exposure, 546±7 pH and acidity, 550 temperature, 547±9 vibration, 550 WLF model see Williams±Landel±Ferry model wort boiling, 527 wrapping, 282 WVP see water vapour permeability WVTR see water vapour transmission rates X-ray imaging, 384 xylitol, 157±8 yeast, 6 yoghurt, 767 Young's modulus, 96 zero-order reactions, 50, 631

ß Woodhead Publishing Limited, 2011