Current Developments in Solid-state Fermentation i
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Current Developments in Solid-state Fermentation !
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Editors
Ashok Pandey Carlos Ricardo 8occol Christian Larroche
Springer ASIATECH PUBLISHERS, INC. New Delhi
ISBN: 978-0-387-75212-9
e-ISBN: 978-0-387-75213-6
Library of Congress Control Number: 2007938881
2008 Springer Science+Business Media, LLC All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary fights. 987654321 springer.com
Published by N.K. Muraleedharan for Asiatech Publishers, Inc. E-20, Arya Nagar, CGHS, Plot No. 91, I.P. Extension, Patparganj, Delhi 110092 Ph.: +91-11-22724601
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There could not be any better view than the above about the application of solid-state fermentation for developing bioprocesses involving micro-organisms, especially filamentous fungi. Over the period of last two decades, there has been significant resurgent in solid-state fermentation due to numerous benefits it offers, especially on engineering and environmental aspects. SSF has shown much promise in the development of several bioprocesses and products, which include high volumetric productivity, relatively higher concentration of the products, less effluent generation, and simple fermentation equipments, etc. This resurgent gained further momentum during the last 5-10 years with the development of knowledge-base in the fundamental and applied aspects. A good deal of information has been generated in the published literature and patented information. Several commercial ventures have come up based on SSF in different parts of the world. It was, thus, thought crucial to publish a document allowing to get state-of-the art information in this area, in order to demonstrate that the wellestablished liquid stirred tank is not always the best technical solution. During 2001, a book was published by Asiatech Publishers, Inc. on SSE The book was well received globally. The present book is based on the previous work, although that was an authored volume while this one is an edited work. Also, the coverage in the present volume is much wider and comprehensive. The book covers a wide range of topics in the field of solid-state fermentation. The contents of the book have been distributed in four parts. The Part 1 deals with the General and Fundamentals aspects of SSF and comprises eight chapters. The Chapter 1 is Introductory and describes the history, development and scientific elaboration of SSE The Chapter 2 discusses various general issues
Preface vi
related with SSF. The Chapter 3 describes the factors that influence SSF, which include physio-chemical and biological factors. The Chapters 4 and 5 are on kinetics and water relations in SSF, respectively. The Chapter 6 describes the designs of different bioreactors (fermenters) developed and used for carrying out SSF in laboratory, or at commercial scale. The Chapter 7 is on instrumentation and controls in SSF and the chapter 8 describes the use of informatics in SSF. The Part 2 of the book comprises four chapters, which are on the production of bulk chemicals and products in SSE These include industrial enzymes, organic acids, spores and mushrooms. The Part 3 of the book has also four chapters, which are on the use of SSF for the specialty chemicals such as gibberellic acid, antibiotics and other commercially valuable secondary metabolites, pigments and aroma compounds. The fourth and last part of the book (Part 4) deals with the use of SSF for miscellaneous application such as SSF for the food and feed applications, agro-industrial residues as substrates in the SSF and the production of silage and vermicompost. All the chapters have incorporated the most significant developments taken place during the last 5-10 years with state-of-art information. We are hopeful that the book would be useful to the students, teachers, researchers and professionals interested in the area of the industrial biotechnology and microbiology.
Ashok Pandey Carlos Ricardo Soccol Christian Larroche
Contents
1. Introduction ........................................................................................ 3
Ashok Pandey, Carlos Ricardo Soccol & Christian Larroche 2. General Considerations about Solid-state Fermentation Processes .......... 13
Ashok Pandey, Christian Larroche & Carlos Ricardo Soccol 3. Factors Affecting Solid-state Fermentation .............. :. ........................... 26
Jose A Rodriguez-Leon, Carlos R Soccol, Ashok Pandey & Daniel E. Rodriguez 4. Kinetics in Solid-state Fermentation .................................................... 48
Jose A Rodriguez-Leon, Carlos R Soccol, Ashok Pandey & Daniel E Rodriguez 5. Water Relations in Solid-state Fermentation ......................................... 74
Patrick Gervais 6. Aspects o f D e s i g n o f Bioreactors in SSF ......................................... 117
G Giovannozzi Sermanni & Nicola Tiso 7. Instrumentation and Controls in SSF ................................................ 145
Wilerson Sturm, Dario Eduardo Amaral Dergint & Carlos Ricardo Soccol 8. Informatics in SSF .......................................................................... 168 .
Wilerson Sturm, Carlos R Soccol, Dario Eduardo Amaral Dergint, Jose A Rodriguez-Le6n & Deiva Canali Navarro Vieira Magalhaes
viii Contents
9. Production of Enzymes .................................................................... 181
Sudheer Kumar Singh, George Szakacs, Carlos Ricardo Soccol & Ashok Pandey 10. Production of Organic Acids ............................................................ 205
Carlos R Soccol, Luciana PS Vandenberghe, Cristine Rodrigues, Adriane Bianchi Pedroni Medeiros, Christian Larroche & Ashok Pandey 11. Production of Spores ....................................................................... 230
Sumitra Ramachandran, Christian Larroche & Ashok Pandey 12. Mushroom Production ..................................................................... 253
Leifa Fan, Carlos Ricardo Soccol & Ashok Pandey
13. Gibberellic Acid Production .............................................................. 275
Cristina Maria Monteiro Machado & Carlos R Soccol 14. Production of Antibiotics and Other Commercially Valuable Secondary Metabolites ..................................................................... 302
Javier Barrios-Gonzdlez & Armando Mejia 15. Production of Pigments ............ ......................................................... 337
J~lio Cesar de Carvalho, Carlos Ricardo Soccol, Sumathy Babitha, Ashok Pandey & Adenise Lorenci Woiciechowski 16. Production of Aroma Compounds ..................................................... 356
Carlos R Soccol, Adriane BP Medeiros, Luciana PS Vandenberghe, Marlene Soares & Ashok Pandey
17. Solid-state Fermentation for Food and Feed Applications ................... 379
Maria A. Longo, Francisco J Deive, Alberto Dominguez & M ~ Angeles Sanromdn 18. Agro-industrial Residues as Substrates in SSF ................................... 412
Reeta Rani Singhania, Carlos Ricardo Soccol & Ashok Pandey 19. Preservation of Forage Crops by Solid-state Lactic Acid ................... 443 Fermentation-Ensiling: Zwi G Weinberg 20. Potential of Vermicomposting Technology in Solid Waste Management ................................................................. 468
Vinod K Garg, Renuka Gupta & Anoop Yadav
Contributors
Sumathy Babitha
Leifa Fan
3iotechnology Division National Institute for Interdisciplinary Science & Technology, ~formerly Regional Research Laboratory) Trivandrum-695 019, India
Institute of Horticulture Zhejiang Academy of Agricultural Sciences 198 Shiqiao Road 310021, Hangzhou-ZJ, P. R. China
Javier Barrios-Gonz~ilez
Department of Environmental Science and Engineering, Guru Jambheshwar University of Science and Technology, Hisar 125 001, India
Departamento de Biotecnologia Universidad Aut6noma Metropolitana Iztapalapa, San Rafael Atlixco 186, Col. Vicentina 39340 M6xico D.F., M6xico
Vinod Kumar Garg
Patrick Gervais
Bioprocess Engineering and Biotechnology Division, Federal University of Paran/t CEP 81530-970 Curitiba-PR, Brazil
Laboratoire de G6nie des Proc6d6s Alimentaires et Biotechnologiques ENSBANA 1, Esplanade Erasme 21000 Dijon, France
Francisco J. Deive
Renuka Gupta
Department of Chemical Engineering Isaac Newton Building University of Vigo Lagoas Marcosende 36310 Vigo, Spain
Department of Environmental Science and Engineering, Guru Jambheshwar University of Science and Technology, Hisar 125 001, India
Jfilio Cesar de Carvalho
Dario Eduardo Amaral Dergint
Christian Larroche
Departamento de Eletr6nica Universidade Tecnol6gica Federal do Paranfi CEP 80230-901, Curitiba- PR, Brazil
Laboratoire de G6nie Chimique et Biochimique (LGCB), CUST - Universit6 Blaise Pascal, 24, avenue des Landais, B.P. 206, F- 63174 Aubi~re Cedex, France
Alberto Dominguez
Department of Chemical Engineering Isaac Newton Building University of Vigo Lagoas Marcosende 36310 Vi~o, Spain
x
Contributors
Maria A Longo
Daniel E Rodriguez
Department of Chemical Engineering Isaac Newton Building University of Vigo Lagoas Marcosende 36310 Vigo, Spain
Bioprocess Engineering and Biotechnology Division, Federal University of Paran~i CEP 81530-970 Curitiba-PR, Brazil
Cristina Maria Monteiro Machado
Embrapa Vegetables BR 060 km 09 70359-970 Brasilia-DF Brazil Deiva Canali Navarro Vieira Magalhies
Departamento de Eletrrnica Universidade Tecnol6gica Federal do Paranfi CEP 80230-901, Curitiba- PR, Brazil Adriane BP Medeiros
Bioprocess Engineering and Biotechnology Division, Federal University of Paranfi CEP 81530-970 Curitiba-PR, Brazil AMejia
Departamento de Biotecnologia Universidad Aut6noma Metropolitana, Iztapalapa, San Rafael Atlixco 186, Col. Vicentina, 09340 Mrxico D. F., Mrxico Ashok Pandey
Biotechnology Division National Institute for Interdisciplinary Science & Technology, (formerly Regional Research Laboratory) Trivandrum-695 019, India Sumitra Ramachandran
Laboratoire de Grnie Chimique et Biochimique (LGCB), CUST- Universit6 Blaise Pascal, 24, avenue des Landais, B.P. 206, F- 63174 Aubi&e Cedex, France C Rodrigues
Bioprocess Engineering and Biotechnology Division, Federal University of Paran~ CEP 81530-970 Curitiba-PR, _Brazil
Jose A Rodriguez-Le6n
Bioprocess Engineering and Biotechnology Division, Federal University of Paran~i CEP 81530-970 Curitiba-PR, Brazil M" Angeles Sanrom~in
Department of Chemical Engineering Isaac Newton Building University of Vigo Lagoas Marcosende 36310 Vigo, Spain G Giovannozzi Sermanni
Agrobiology and Agrochemistry Departmen Tuscia University Viterbo, Italy Sudheer Kumar Singh
Biotechnology Division National Institute for Interdisciplinary Science & Technology, (formerly Regional Research Laboratory) Trivandrum-695 019, India Reeta Rani Singhania
Biotechnology Division National Institute for Interdisciplinary Science & Technology, (formerly Regional Research Laboratory) Trivandrum-695 019, India Maarlene Soares
Bioprocess Engineering and Biotechnology Division, Federal University of Paran~i CEP 81530-970 Curitiba-PR, Brazil Carlos Ricardo Soccol
Bioprocess Engineering and Biotechnology Divi~on, Federal University of Paran~ CEP 81530-970 Curitiba-PR, Brazil
Oontributors xi George Szakacs
Department of Agricultural Chemical Technology, Technical University of Budapest 1111 Budapest, Gellert ter 4 Hungary Nicola Tiso
Agrobiology and Agrochemistry Department Tuscia University Viterbo, Italy Wilerson Sturm
Bioprocess Engineering and Biotechnology Division, Federal University of Parand CEP 81530-970, Curitiba-PR, Brazil Lueiana PS Vandenberghe
Bioprocess Engineering and Biotechnology Division, Federal University of Paran~i CEP 81530-970 Curitiba-PR, Brazil
Zwi G Weinberg Forage Preservation and By-Products Research Unit, Department of Food Science Agricultural Research Organization The Volcani Center Bet Dagan 50250, Israel Adenise Lorenci Woiciechowski
Bioprocess Engineering and Biotechnology Division, Federal University of Parand CEP 81530-970 Curitiba-PR, Brazil Anoop Yadav
Department of Environmental Science and Engineering, Guru Jambheshwar University of Science and Technology, Hisar 125 001, India
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1.1 BIOPROCESS DEVELOPMENT Solid-state (substrate) fermentation (SSF) is generally defined as the growth of the micro-organisms on (moist) solid material in the absence or near-absence of free water. In recent years, SSF has shown much promise in the development of several bioprocesses and products. It seems that two terms, solid-state fermentation and solid substrate fermentation have often been ambiguously used. It would be logical only to distinguish these two terms. Solid substrate fermentation should be used to define only those processes in which the substrate itself acts as carbon/energy source, occurring in the absence or near-absence of free water; solid-state fermentation should define any fermentation process occurring in the absence or near-absence of free water, employing a natural substrate as above, or an inert substrate used as solid support. The history, development and scientific elaboration of SSF have been reviewed by several authors from time to time. Evidently, food fermentation and production of enzymes were the areas where SSF originated. The recorded history of SSF was described in Asia before the birth of Christ on cheese making by Penicillium rouquefortii. Egyptians were reported to make bread using SSF process in 2000 BC. The use of soy sauce koji in China was reported in the years 1000 BP and probably in the years 3000 BP (koji process involves fermentation of steamed rice as solid substrate by the fungal strain of Aspergillus oryzae). The koji process migrated from China to Japan by the Buddhist priests in seventh century. During this period, there were mentions of several fermented foods such as tempeh, miso etc., in many South-East Asian countries. Tempeh and miso use steamed and cracked legume seeds as solid substrate and fermentation is carded out using non-pathogenic fungal strains such as Rhizopus sp.
During the 18th century, for the first time, SSF was used for the production of vinegar from the apple pomace. The period also saw the development of leather tanning process using gallic acid. The period of late 19th century saw the development of composting and solid waste treatment using SSF processes. The beginning of 20th century witnessed for the first time the production of primary metabolites such as enzymes and organic acids using micro-organisms in SSE In these processes, mostly fungal cultures were used as producing organisms. It was this period exactly when maiden concepts appeared to develop fermenters (bioreactors) suitable for SSF processes, which led to the development of drum-type of fermenters. The period of 1940's has been termed as the 'Golden Era' of fermentation industry, which saw the dramatic discovery and development of the wonder drug, penicillin. Penicillin was produced using liquid as well as solid culturing techniques. However, this was the period, when, for the reasons best known to the researchers of that period, much attention was paid on the development of liquid fermentation processes and some how or other, knowingly or unknowingly, SSF got totally neglected. This was typically the case with the penicillin, which continued for all other fermentation products. Consequently, there were no serious efforts by the researchers to develop SSF systems, except a few isolated studies, which still continued focusing SSE Even with such low profiles, during the period of 1950-60, reports were published describing steroid transformations in SSF using fungal cultures, which was yet another milestone achievement in the history of SSE This was again followed by the period of 1970's when fungal cultures were successfully cultivated in SSF for the production of mycotoxins, which resulted a significant impact on cancer research. During this period, yet another important application oriented finding of SSF research was on the production of protein enriched cattle feed (singlecell protein). Enormous work, since then has been carried out on this process using a large number of substrates and micro-organisms, and various processes with techno-economic feasibility have been successfully developed. Thus, though historically known since centuries, SSF gained a fresh attention from researchers and industries all over the world since recent few years, mainly due to few major advantages which it offers over liquid (submerged) fermentation (SmF), particularly in the areas of solid waste management, biomass energy conservation and its application to produce high v a l u e - low volume products such as biologically active secondary metabolites, etc., apart from the production of food, feed, fuel and traditional bulk chemicals. _
Attempts were made to trace the history of SSF describing the general features and also the aspects of fermenter design in SSF (Pandey 1991, 1992, 2003, Pandey et al., 2001, Durand 2003). These reviews discussed various developments since historical time. During 1991-2006, more than 1400 publications have
appeared in various joumals, proceedings and books, apart from several important publications in book form, or special issue of joumals. A few reviews have also been presented discussing some particular features of SSF from time to time. A special review by CW Hesseltine was on the Thom Award Address, which reprinted his work on SSE This very well signified the biotechnological potential of SSF globally. Significantly, it has been CW Hesseltine who first consolidated the scientific information on SSF in 1977 (Pandey 2003, Pandey et al., 2000, 2001, Hoelker 2004, Robinson et al., 2001, Mitchell et al., 2002, Tengerdy and Szakacs 2003, Weinberg and Ashbell 2003, Gervais and Molin 2003, Pandey and Ramachandran 2005). Current decade has witnessed an unprecedented spurt in SSF for the development of bioprocesses such as bioremediation and biodegradation of hazardous compounds, biological detoxification of agro-industrial residues, biotransformation of crops and crop-residues for nutritional enrichment, biopulping, and production of value-added products such as biologically active secondary metabolites, including antibiotics, alkaloids, plant growth factors, etc., enzymes, organic acids, biopesticides, including mycopesticides and bioherbicides, biosurfactants, biofuel, aroma compounds, etc. in SSF system. During the past time, most of such processes were eventually termed as 'low-technology' systems but presently seen to be a promising one for the production of value-added 'low volume-high cost' products such as biopharmaceuticals. SSF processes offer potential advantages in bioremediation and biological detoxification of hazardous and toxic compounds. With the advent of biotechnological innovations, mainly in the area of enzyme and fermentation technology, many new avenues have opened for the application of SSE Over the past few years, the increasing demand for the natural products in the food industry has encouraged remarkable efforts towards the development of biotechnological processes for the production of flavour compounds. The use of SSF as a means to improve economical feasibility of these processes would be of potential benefit (Longo and Sanroman 2006). Holker et al., (2004) opined that despite the increasing number of publications dealing with solid-state (substrate) fermentation (SSF), it was very difficult to draw general conclusion from the data presented. The authors remarked that this was due to the lack of proper standardisation that would allow objective comparison with other processes. Research work has so far focused on the general applicability of SSF for the production of enzymes, metabolites and spores, in that many different solid substrates (agricultural waste) have been combined with many different fungi and the productivity of each fermentation reported. They further commented that on a gram bench-scale SSF appeared to be superior to submerged fermentation technology (SmF) in several aspects. However, SSF up-scaling, necessary for use on an industrial scale, raises severe engineering problems due to the build-up of temperature, pH, 02, substrate and moisture gradients. Recently, Viniegra-Gonzalez and Favela-Torres (2006)
made a critical review of the phenomenon of resistance to catabolite repression of enzyme synthesis by SSE commenting the practical and theoretical importance of such phenomenon, together with the current ideas to explain it. Mathematical models have been considered as important tools for optimizing the design and operation of SSF bioreactors. Such models must describe the transport phenomena within the substrate bed and mass and energy exchanges between the bed and the other subsystems of the bioreactor, such as the bioreactor wall and headspace gases. The sophistication with which this has been done for SSF, has improved markedly over the last decade, or so (Mitchell et al., 2003). Mathematical models also must describe the kinetics of microbial growth, how this is affected by the environmental conditions and how this growth affects the environmental conditions. This is done at two levels of sophistication. In many bioreactor models the kinetics are described by the simple empirical equations. However, other models that address the interaction of growth with intraparticle diffusion of enzymes, hydrolysis products and 02 with the use of mechanistic equations have also been proposed, and give insights into how these microscale processes can potentially limit the overall performance of a bioreactor (Mitchell et al., 2004). An important development has been in developing sensors and measurements in SSF processes. In a review, Bellon-Maurel et al., (2003) discussed current on-line methods and innovative applications of methods with a potential to measure parameters in SSE Given the complexity and heterogeneity of the solid medium, process variables are not easily accessible and measurable. Direct measurements of temperature, pH, and water content are considered employing classical sensors, and indirect measurements of the biomass by respirometry or pressure drop (PD). More recent methods such as: aroma sensing, infrared spectrometry, artificial vision, and tomographic techniques (X-rays, Magnetic Resonance Imaging or MRI) should be explored.
1.2 ASPECTS OF DESIGN OF FERMENTER FOR SSF Design of fermenter for SSF processes is an important aspect. However, in spite of strong resurgent of SSF in last ten years, bioreactor design aspects have not been given enough attention by the researchers, although there are certainly path-breaking developments. Present knowledge, however, does not provide state-of-art information about an ideal fermenter for SSF processes. Table 2 gives an overview of different types of bioreactors used in solid-state fermentation as fermenters. As is evident, most of the designs are based on two models: tray type or drum type with or without mixing devices and modifications. Koji process for soy sauce is considered as a representative of SSF processes. Traditionally this has been carried out in wooden trays. Attempts were also made to operate koji process in drum type of bioreactors. However,
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Table 1. History and development of solid-state fermentation
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Table 2. Developments in design of fermenter for solid-state fermentation
Source: Pandey 1991, Pandey et al., 2001, Meien et al., 2004, Chen et al., 2005,Ye et al., 2006,
Fem~indez-Fem~indez & P6rez-Correa, 2006, Rodrfguez-Couto et al., 2006.
not much successes were achieved. As early as in 1964, a 5-gallons rotating drum type of bioreactor was used for the production of fungal enzymes. Some researchers proposed some modifications such as dividing the drum by baffles (three- or four-chambered) to achieve improved mixing and better product formation. While initially drum-type of bioreactors were thought to be useful for processes such as protein enrichment of cattle feed, several attempts were made to use them for production of other products such as enzymes and mycotoxins. For the ease of handing and cost-effectiveness, cement mixers of various sizes have also been tried as bioreactor for SSF processes. A breadmaking blender was modified to suit the process requirements of cattle feed production using agricultural residues. Drum-type of bioreactors have often been used for the bioprocesses where mixing of the substrate during fermentation was recommended useful, which could be achieved by the rotation. There has not been any clear principle behind the extent of mixing of the substrate. While most of the researchers have used a low rotation speed (1-15 rpm), some have used high rates of rotation. One disadvantage, in particular with high rates of rotation, was the damage to fungal mycelia. However, there are contradicting reports concerning the damage per purporated to be cast by mixing. For example, in some reports the mixing (hand or mechanical) of a 3-day duration tray Koji for soya sauce production was considered to be essential while other reports stressed the serious check to enzyme production and heat generation due to the mixing. In case of the composting processes, mixing in long drums mounted on a gentle incline position on continuous mode has been considered to produce excellent effect. During the last 20 years, the concept of column and deep trough type of bioreactor design emerged. These were reported to be useful for the product developments with efficient process controls, particularly for heat removal. However, much is still to be done to realize an optimally suitable size of column for multiple purposes. Moreover, scale-up of column bioreactors poses difficulties. Durand (2003) reviewed the various reactor designs for SSF, focusing on the differences between lab-scale and industrial-scale designs. He highlighted the main designs that have emerged over the last 10 years and the potential for scaling-up for each category of reactor. Robinson and Nigam (2003) reviewed the bioreactor designs and their use for protein production under SSF conditions using various agricultural by-products. The advantages and disadvantages of various bioreactors and their potential for scale-up are described. SSF was proposed as a suitable low-tech strategy for protein enrichment for animal feed by converting a previously low value substance into a more nutritionally valuable one. Recently, Khanahmadi et al., (2006) described the performance of continuous solid-state bioreactors having two different solid substrates flow
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patterns, namely plug flow and completely mixed flow. The performance was quantified for both steady-state and transient operation using a simple mathematical model.
References Bellon-Maurel V, Orliac O & Christen P, 2003, Sensors and measurements in solidstate fermentation: A review, Process Biochemistry, 38, 881-896. Chen I-IZ, Xu J & Li ZI-I, 2005, Temperature control at different bed depths in a novel solid-state fermentation system with two dynamic changes of air, Biochemical Engineering Journal, 23, 117-122. Couto SR & Sanrom~in MA, 2006, Application of solid-state fermentation to food industryA review, Journal of Food Engineering, 76, 291-302. Durand A, 2003, Bioreactor designs for solid-state fermentation, Biochemical Engineering Journal, 13, 113-125. Fermindez-Fermindez M & P6rez-Correa RJ, 2006, Realistic model of a solid substrate fermentation packed-bed pilot bioreactor, Process Biochemistry, 42 (2), 224-234. Gervais P & Molin P, 2003, The role of water in solid-state fermentation, Biochemical Engineering Journal, 13, 85-101. I-I61ker U, H6fer M & Lenz J, 2004, Biotechnological advantages of laboratoryscale solid-state fermentation with fungi, Applied Microbiology and Biotechnology, 64,175-186. Khanahmadi M, Mitchell DA, Beheshti M & Roostaazad R, 2006, Continuous solidstate fermentation as affected by substrate flow pattern, Chemical Engineering Science, 61,2675-2687. Longo MA, Sanromffn M.A, 2006, Production of food aroma compounds: Microbial and enzymatic methodologies, Food Technology and Biotechnology, 44, 335-353. Mitchell DA, Von Meien OF, Krieger N & Dalsenter FDH, 2004, A review of recent developments in modeling of microbial growth kinetics and intraparticle phenomena in solid-state fermentation, Biochemical Engineering Journal, 14, 15-26. Mitchell DA, Von Meien OF & Krieger N, 2003, Recent developments in modeling of solid-state fermentation: Heat and mass transfer in bioreactors, Biochemical Engineering Journal, 13, 137-147. Mitchell DA, Berovic M & Krieger N, 2002, Overview of solid-state bioprocessing, Biotechnology Annual Review, 8, 183-225. Meien OF, Luz Jr LFL, Mitchell DA, P6rez-Correa RJ, Agosin E, Fermindez-Fermindez M & Arcas JA, 2004, Control strategies for intermittently mixed, forcefully aerated solidstate fermentation bioreactors based on the analysis of a distributed parameter model, Chemical Engineering Science, 59, 4493-4504.
/m Pandey A, 2003, Solid-state fermentation, Biochemical Engineering Journal, 13, 81-84. Pandey A, 1992, Recent process developments in solid-state fermentation. Process Biochemistry, 27 (2), 109-117. Pandey A, 1991, Aspects for design of fermenter in solid-state fermentation. Process Biochemistry, 26 (3), 355-361. Pandey A, Soccol CR, Rodriquez-Leon JA & Nigam P, 2001, Solid-statefermentation in Biotechnology, Asiatech Publishers, New Delhi, India. Pandey A, Soccol CR & Mitchell D, 2000, New developments in solid-state fermentation: I bioprocesses and products. Process Biochemistry, 35 (10), 1153-1169. Pandey A & Ramachandran S, 2005, Process developments in solid-state fermentation for food applications, In- Food Biotechnology, 2nd edition, K Shetty, G Paliyath, A Pometto & RE Levin (eds), Taylor & Francis, New York, pp 87-110.
Robinson T & Nigam P, 2003, Bioreactor design for protein enrichment of agricultural residues by solid-state fermentation, Biochemical Engineering Journal, 13, 113-125 Robinson T, Singh D & Nigam P, 2001, Solid-state fermentation: A promising microbial technology for secondary metabolite production, Applied Microbiology and Biotechnology, 55, 284-289. Rodriguez-Couto S, L6pez E & Angeles-Sanrom~in M, 2006, Utilisation of grape seeds for laccase production in solid-state fermentors, Journal of Food Engineering, 74, 263-267. Tengerdy RP & Szakacs G, 2003, Bioconversion of lignocellulose in solid substrate fermentation, Biochemical Engineering Journal 13, 169-179. Viniegra-Gonzaqez G & Favela-Torres E, 2006, Why solid-state fermentation seems to be resistant to catabolite repression?, Food Technology and Biotechnology, 44, 397-406.
Weinberg ZG & Ashbell G, 2003, Engineering aspects of ensiling, Biochemical Engineering Journal, 13, 181-188. Ye SD, Ying SH, Chert C & Feng MG, 2006, New solid-state fermentation chamber for bulk production of aerial conidia of fungal biocontrol agents on rice, Biotechnology Letters, 28,799-804.
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2.1 INTRODUCTION SSF offers numerous advantages over submerged fermentation (SmF). These include high volumetric productivity, relatively higher concentration of the products, less effluent generation, and simple fermentation equipments, etc. The major factors, which affect microbial growth and activity in SSF include the selection of a suitable micro-organism and substrate, pre-treatment of the substrate, particle size (inter-particle space and surface area) of the substrate, moisture content and water activity (aw) of the substrate, relative humidity, type and size of inoculum, temperature of fermenting matter, removal of metabolic heat generated during respiration, period of cultivation, maintenance of uniformity in environment of SSF, and the gaseous atmosphere, i.e. oxygen consumption rate and carbon dioxide evolution rate. Based upon the type of micro-organisms involved, SSF processes can be classified into two main groups, natural (indigenous) SSF, and pure culture SSF using individual strains, or a mixed-culture. Composting and ensiling are the two best examples of SSF processes, which involve natural micro-flora. Bioprocesses involving pure culture SSF are also known since long. One such unique example is Koji process utilizing a culture of Aspergillus oryzae. In industrial SSF processes, however, generally pure cultures are used as it helps in optimum substrate utilization for the targeted product. Examples are the production of enzymes, organic acids, bioactive secondary metabolites, etc. Examples of SSF processes involving mixed (pure) cultures are bioconversion of agro-industrial residues such as wheat straw for protein enrichment in which a cellulolytic organism (e.g. a fungal strain of Chaetomium cellulolyticum) and a yeast strain (e.g. Candida utilis) are used. In nature, SSF is mostly carried out by the mixed cultures in which several micro-organisms show development and symbiotic co-operation.
Selection of a suitable strain is one of the most important criteria in SSE The vast majority of wild type micro-organisms are incapable of producing commercially acceptable yields of the desired strains product. The importance of the micro-organism can be seen from the fact that culture of Aspergillus niger can produce as many as 21 types of enzymes (Table 1) while one enzyme alone can be produced by several microorganisms in varying quantities. For example, alpha amylase can be produced by as many as 64 different micro-organisms (Table 2). It is also important to ensure that the selected microbial strain is best suited for SSF as some times the same strain's potential could be not best exploited in SSF but in other systems. Such an example is illustrated in Table 3. As is evident, the strain of Rhizopus formosaensis produced glucoamylase enzyme in varying concentrations when grown as surface culture in submerged, or solid-state fermentation, or as submerged culture. Yet another crucial aspect involves the screening of the strain for its efficiency to produce the desired end-product as the sole product, although there could be other associated activities but these should be in trace amounts only. This could be exemplified from the results described in Table 4, which showed a case study involving the production of alpha amylase by a strain of Trichoderma viride. Indeed this study involved screening of various carbons sources as well. With all the substrates, there was production of another enzyme, namely protease in varying concentrations. These results showed that although corn starch gave the best yields of alpha amylase, the organism also produced simultaneously protease in significant quantities, which, in fact was more than the targeted end-product, i.e. alpha amylase. Thus, corn starch was not a suitable substrate for this process using the selected strain. When lactose was used as the substrate, alpha amylase production was almost negligible and protease production was dominant. However, yield of protease in this case was almost half to that produced by corn starch, which showed that although strain produced only protease as major end-product, this was not suitable for that (protease production) also, as with other substrates, enzyme yields were higher than this case. The results demonstrated that the strain was neither a suitable choice for the production of alpha amylase, nor for protease from the substrates used in the experiment. From these examples, it could be concluded that the selection of the strain for any process development, and so for SSF as well, is an extremely significant step and must be studied with utmost care. While doing so, it would be necessary to keep in mind all the necessary associated factors such as process technique, substrate, associated products formation, etc. The selection of a substrate for SSF process depends upon several factors, mainly related with the cost and availability and, thus, may involve their screening. Agro-industrial residues, particularly of tropical origin offer potential advantages for their application as substrates. In SSF process, the solid substrate not only
Table 1. Spectrum of enzymes obtainable from the strains of
Aspergillus niger
Table 2. Micro-organisms reported to produce alpha amylase
m Table 3. Glucoamylase production by a strain of Rhizopus formosaensis
Table 4. Screening of alpha amylase production by a strain of Trichoderma viride
supplies the nutrients to the microbial culture growing in it, but also serves as an anchorage for the cells. The substrate that provides all the needed nutrients to the micro-organisms growing in it should be considered as the ideal substrate. However, some of the nutrients may be available in sub-optimal concentrations, or even not present in the substrates. In such cases, it would be necessary to supplement them externally. It has also been a practice to pre-treat (chemically, or mechanically) some substrates before use in SSF processes (e.g. lignocellulosics), which makes them more easily accessible for microbial growth. Among the several other factors, which are important for the microbial growth and activity in a particular substrate, particle size and moisture level/water activity are the most critical. Generally, smaller substrate particles would provide larger surface area for the microbial attack and, thus, should be considered as a desirable factor. However, too small substrate particles may result substrate agglomeration in most of the cases, which may interfere with microbial respiration/ aeration, and, thus, may result poor cellular growth. At the same time, larger particles provide better respiration/aeration efficiency (due to increased interparticle space) but provide limited surface for the microbial attack. Thus, it would be necessary to arrive at a compromised particle size for a particular process. Table 5 shows a typical example of particle size distribution in three different commercial samples of wheat bran, which is the most frequently used substrate in SSF processes. Sample A and B were obtained from a local market in India while sample C was prepared by mixing A and B in 1:1 ratio (w/w). Sample A contained 76% particle smaller than 500 microns while sample B has only 11% particles smaller than 500 microns. Sample C showed a wide
Table 5. Particle size distribution in a commercial samples of wheat bran
Source:
Pandey A, 1991, Bioresource Technololgy, 37, 169-172
distribution of particles of various sizes containing approximately 44% smaller and 56% large than 500 microns. When SSF was carried out using these samples by taking individual sized particles prepared from these samples by sieving and individual samples as well, best results on enzyme production were obtained by the substrate containing particles of 425-500 microns, followed by 500-600 microns. Substrates with lower particles resulted in lower enzyme activity and the same was true for bigger particles substrates. The lowest enzyme activity was obtained with the substrate containing particles bigger than 1.4 mm. The specific enzyme activity of sample A was much better than sample B but this was best in sample C, which showed a unique distribution of particles of different sizes. Although, enzyme titres obtained from sample C was not the same as from the best individual sized particles substrate, from the techno-economic feasibility point of view, it was the most appropriate to use the mixed substrate. Substrate moisture and water activity play very important role in SSE The water activity of the medium is considered as a fundamental parameter for the mass transfer of the water and solutes across the cell membrane. In fact, the control of this parameter could be used to control and modify the metabolic activity of the micro-organism. In general the types of micro-organisms that can grow in SSF system are determined by the water activity factor, aw. Water activity is defined as the relative humidity of the gaseous atmosphere in equilibrium with the substrate. Pure water has aw = 1.00 and aw decreases with the addition of solutes. Bacteria generally grow at higher aw values while filamentous fungi and some yeast can grow relatively at lower aw values. Due to this fact, filamentous fungi have often been preferred over the other groups
of micro-organisms for SSF processes. In case of fungal growth in SSF, higher water activity generally results sporulation, while low water activity with suitable range favours spore germination and mycelial growth. Research on the selection of a suitable substrate has mainly centred around tropical agro-industrial crops and residues. These include crops such as cassava, soybean, sugar beet, sweet potato, potato, and sweet sorghum, crop residues such as bran and straw of wheat and rice, hull of soy, corn and rice, bagasse of sugarcane and cassava, residues of coffee processing industry such as coffee pulp, coffee husk, coffee spent-ground, residues of fruit-processing industries such as pomace of apple and grape, wastes of pine-apple and carrot processing, banana waste, waste of oil-processing mills such as coconut cake, soybean cake, peanut cake, canola meal and palm oil mill waste, and others such as saw-dust, corn cobs, carob pods, tea waste, chicory roots, etc. Wheat bran has been the prime among all. Many processes have been developed that utilize these as raw material for the production of bulk chemicals and valueadded fine products. We would not go into details of these aspects here, as there is a separate chapter exclusively devoted to this in the next section. In relation to SSF processes using inert substrates, two approaches have been adopted; one, in which synthetic materials such as Amberlite, or polyurethane are used, and other which utilises natural materials such as sugarcane bagasse as the inert solid support. Since natural substrates create problems in the fermentation kinetics studies (due to their heterogeneous nature), such studies could better be performed using synthetic inert solid substrates.
2.2 ESTIMATION OF GROWTH IN SSF In SSF, estimation of biomass, which is essential for the kinetic studies, poses difficulties as generally the microbial cells remain attached with the substrate and it is difficult to separate them. In case of the fungal cultures, it is more difficult because fungal mycelia penetrate into the substrate particles. Generally the estimation of growth of microorganism in SSF is carried out by the indirect methods, although for model studies, some methods are used, which provide direct growth estimation. For example, gelatin could be used to grow microbial cells, e.g. Saccharomyces cerevisae in solid cultures and after the growth, gelatin could be melted at about 37~ and subsequently the cells could be recovered from this melted medium by centrifugation. For yeast cells, one another method has been applied which involved the washing of fermented matter with water and then counting the cells in the washed medium. However, the efficiency of method largely depends upon the efficiency of washing out the cells from the fermented matter.
m ,,,,,~,,~,,!~,,,~,~,,,~~i~~,,,,,,,,,!,~,~,,,~,,,~i~i~,,,~ ~~~i~~~~~!~!~i!~ Among the indirect or the other methods used for the estimation of microbial growth in SSF, assay of biomass components such as DNA, glucosamine, ergosterol and protein (Kjeldahl) or assay of metabolic activity (respirometry) have been considered useful. Estimation of glucosamine for fungal biomass assay has been considered as the most suitable and frequently used method. In recent times, particularly while using column type of bioreactors, estimation of oxygen utilization rate (OUR) and carbon dioxide evolution rate (CER) are considered to be most accurate for the determination of growth of the microorganisms in SSE Some more details about growth estimation methods have been provided in another chapter in the next section.
2.3 CONCEPT OF STERILITY Sterility is very often required in any SmF process because many contaminants could out-compete the process organism under the conditions of high water availability provided. Often SSF processes involve an organism, which grows quite rapidly under the low water conditions, and if an active inoculum is added to a (cooked) substrate, the process organism is able to out-compete the contaminating organisms. Thus, strict aseptic operation of the bioreactor may not be essential in SSF, although, of course, operation should be carried out in as clean a manner as possible. The less stringent design requirements for such bioreactors, and correspondingly lower costs could be considered as favourable point for the SSF process, providing an economic advantage over the SmF process. However, there are a number of products for which SSF has good potential but for which the process organisms grow generally relatively slowly, which could be overtaken by contaminants. For example, this is the case in the production of gibberellic acid by Giberella sp. In such cases, it would be essential to use a bioreactor, which can be operated under aseptic conditions. In such a case, the bioreactor costs would be expected to be similar to those for SmF bioreactors, and SSF would only be chosen if it could provide any specific advantage, such as higher product titres, or lower downstream processing costs, which finally could lead to better economic performance.
2.4 ACADEMIC RESEARCH VS. INDUSTRIAL APPLICATIONS In order to understand this, let's look into some fundamental questions. There is a lot of research going on into SSF - why?There are relatively few commercial applications (at least compared to SmF) - why? A general opinion about the choice of fermentation method for the production of any microbial product would normally be SmF, unless there appears a particular reason why SSF should be chosen. There is no question that SmF is intrinsically less problematic-
heat transfer is better, and homogeneity is much-much better. SSF would be chosen if (a) particular economic conditions favored it (therefore, in some parts of the world some enzymes are produced by SSF, whereas in other parts, the same enzymes are produced by SmF), (b) the product is only produced in SSF - or if produced in both systems, the SSF product is far superior (for example, fungal spores for use as biopesticides tend to be much more robust when they are produced in SSF compared to when they are produced in SmF, and some fungi simply don't sporulate well in SLF), (c) use of solids becomes an imperative (government regulations in response to environmental pressures caused by dumping of organic solids). Thus, although SSF has potential mainly in specific areas, under the conditions that it is "off the main track", it has received relatively little attention. Its potential to operate reliably at large-scale simply has not been investigated to the same degree as the SmF method. It is possible that SSF processes could be routinely operated at large-scale, following rational design rules - but we currently don't know enough to really be sure if this is the case or not. Certainly, there are a few quite successful SSF processes - such as enzyme production processes, various biopesticide production processes, etc, even if many of these are at relatively small scales. There is also the case with the koji industry. SSF should not be seen as a technology, which can simply replace SmF. In fact, SmF has many features, which would make it the preferred method in a case where SmF and SSF had similar economic performances. The greater homogeneity in a SmF system simply makes the process less problematic. The relatively few commercial SSF processes compared to the range of products, which have been investigated in the laboratory, could probably be a confirmation of this. However, there are a number of products for which SSF is the superior production technology, and a number of large-scale SSF processes have begun operating commercially. There is a continued need to develop SSF technology to allow such processes to operate at their full potential.
2.5 COMPARISON OF CHARACTERISTICS OF SSF AND SUBMERGED FERMENTATION Table 6 highlights the major differences in the characteristics of solid and submerged fermentation. As is evident, due to static nature of substrate and microorganism, the system poses difficulties for heat and mass transfer effects. Due to respiration, carbon dioxide evolves and being heavier than oxygen, remains accumulated in the substrate bed, which in turn results in increase in the temperature of the fermenting bed. This needs to be controlled. Two other characteristics of SSF, mainly low physical energy requirements and high human
Table 6. Comparison of characteristics of SSF and submerged fermentation
energy requirement led to an untrue assumption that SSF was a low technology. In fact, poor knowledge, or understanding of fundamental aspects of SSF is the main reasons behind these two aspects. Since last 10-15 years, scenario is changing fast and it is hoped that generation of data based knowledge on fundamental aspects of SSF would lead to the development of modem fermenters with automation as is the case of SmF.
2.6 ECONOMICALLY AND INDUSTRIALLY IMPORTANT ADVANTAGES OF SSF As has been pointed out in the beginning of this chapter, there are several industrially and economically important advantages, which SSF offers over SmF and essentially due to these reasons, there is strong resurgence of SSE A glimpse of Table 7 provides an insight about these advantages. Higher product titres in most o f the SSF process, less water need in up-stream processing resulting lesser wastewater generation in down stream processing (which heavily reduces the cost of down-stream processing) are the major advantageous point of SSF processes. Since fermenters used for SSF have no complicated design and have not much automated control systems (the points, which need to be studied and developed), SSF systems require lower capital investment. Moreover, since the substrates used are generally agro-industrial residues, fermentation media are generally simpler without requiring complex nutrients such as vitamins, etc. This also leads to economical advantage and lower recurring expenditure. In the absence of any rigorous mixing, there is no foam formation, which normally is faced in SmF and is controlled by addition of anti-foaming agents, which leads to increase in pollution load. One another advantage, which SSF offers is the application of fermented solids directly without isolating the product. An example is the production of glucoamylase enzyme using wheat bran admixed with corn flour in SSF by A. niger. After fermentation, wet fermented matter
Table 7. Economically and industrially important advantages of SSF
containing glucoamylase could be directly used for the hydrolysis of cassava flour to produce fermentable sugars. Hydrolysis efficiencies were as good as obtained with the purified enzyme. Fermented matter could be dried and stored at room temperature without any significant loss in the activity. However, this aspect should be evaluated according to the need of user.
References Aidoo K. E, Hendry R & Wood BJB, 1982, Solid substrate fermentations, Advances in Applied Microbiology, 28, 201-237.
Docile HW, Mitchell DA & Rolz CE, (Eds), 1992, Solid-state Fermentation, Elsevier Applied Science, London. Durand A, 1998, Solid-state fermentation, Biofutur, 181, 41-43. Hesseltine CW, 1999, A microbe's view of fermentation -Thom Award Address (Reprinted from Developments in Industrial Microbiology, 1981; 22, 1-18), Journal of Industrial Microbiology and Biotechnology, 22, 482-499. Jonas R, Pandey A & Tharun G (Eds), 2004, BiotechnologicalAdvances and Applications in Bioconversion of Renewable Raw Materials, Doehring Druck, Braunschweig, Germany Joshi VK & Pandey A, (Eds), 1999, Biotechnology: Food Fermentation. Educational Publishers & Distributors, New Delhi, Vols I & II.
Lonsane BK, Ghildyal NP, Budiatman S & Ramakrishna SV, 1985, Engineering aspects of solid-state fermentation. Enzyme and Microbial Technology, 7, 258-265.
!iiiiiiiiiii!FiiiFiiFiiiii!iiii! ............hi................!........!ii!! ............ii.... .... Mitchell DA, Krieger N, Stuart DM & Pandey A, 2000, New developments in solid-state fermentation: II Rational approaches for bioreactor design and operation, Process Biochemistry, 35, 1211-1225. Mitchell DA, Pandey A, Sangsurasak & Krieger N, 2000, Scale-up strategies for packedbed bioreactors for solid-state fermentation, Process Biochemistry, 35, 167-178 Pandey A (Ed), 2004, Concise Encyclopedia of Bioresource Technology, Haworth Press, New York, USA.
Pandey A (Guest Ed), 2003, Special Issue on solid-state fermentation, Biochemical Engineering Journal, 13, 79-218. Pandey A (Ed), 1998, Advances in Biotechnology, Educational Publishers & Distributors, New Delhi.
Pandey A (Ed), 1996, Solid-state Fermentation, Special Issue of Journal of Scientific and Industrial Research, 55 (10-11), 311-482. Pandey A (Ed), 1994, Solid-state Fermentation, Wiley Eastern Publishers, New Delhi. Pandey A, 1992, Receent developments in solid-state fermentation, Process Biochemistry, 27, 109-117.
Pandey A, 1991, Aspects for design of fermenter in solid-state fermentation, Process Biochemistry, 26 (3), 355-361. Pandey A & Soccol CR, 2000, Economic utilization of crop residues for value addition A futuristic approach, Journal of Scientific and Industrial Research, 59 (1), 12-22. Pandey A & Soccol CR, 1998, Potential applications of cellulosic residues for the production of bulk chemicals and value added products. In- Trends in Carbohydrate Chemistry, (Eds. P. L. Soni & V Kumar), Vol. 5, Surya International Publications, Dehradun, India, pp 83-88.
Pandey A, Webb C, Soccol CR & Larroche C (Eds), 2006, Enzyme Technology, Springer Science, USA, p 740. Pandey A, Soccoi CR & Mitchell DA, 2000, New developments in solid-state fermentation, Process Biochemistry, 35, 1153-1169. Pandey A, Nigam P, Soccol CR, Singh D, Soccoi VT & Mohan R, 2000, Advances in microbial amylases. Biotechnology and Applied Biochemistry, 31, 135-152.
Pandey A, Soccol CR, Nigam P, Soccol VT, Vandenbereghe & Mohan R, 2000, Biotechnological potential of agro-industrial residues: II Cassava bagasse. Bioresource Technology, 74 (1), 81-87 Pandey A, Soccol CR, Nigam P & Soccol VT, 2000, Biotechnological potential of agroindustrial residues: I Sugarcane bagasse, Bioresource Technology, 74 (1), 69-80. Pandey A, Benjamin S, Nigam P, Krieger N & Soccol VT, 1999, The Realm of microbial lipases in biotechnology, Biotechnology and Applied Biochemistry, 29 (2), 119-131.
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Pandey A, Selvakumar P, Soccoi CR, Soccol VT, Krieger N & Fontana JD, 1999, Recent developments in microbial inulinases - Its production, properties and industrial applications, Applied Biochemistry and Biotechnology, 81 (1), 35-52. Pandey A, Selvakumar P, Soccol CR & Nigam P, 1999, Solid-state fermentation for the production of industrial enzymes, Current Science, 77 (1), 149-162. Pandey A, Azmi W, Singh J & Banerjee UC, 1999, Fermentation types and factors affecting it. In - Biotechnology: Food Fermentation, (Eds VK Joshi & A Pandey), Educational Publishers & Distributors, New Delhi, Vol. I, pp. 383-426. Raimbault M, Soccol CR & Chuzel G (Eds), 1998, Intemational Training Course on Solid-state Fermentation, Oct 6-10, 1997, Curitiba, Brazil, published by ORSTOM, Montpellier. Raimbault M (Ed), 1988, Solid-state fermentation in bioconversion of agro-industrial raw materials, Proceedings of the Seminar on SSE July 25-27, 1988, ORSTOM, Montpellier, published by ORSTOM, Montpellier. Roussos S, Soccol CR, Pandey A & Augur C (Eds), 2003, New Horizons in Biotechnology, Kluwer Academic Publishers, Dordrecht, The Netherlands, p 449. Roussos S, Lonsane BK, Raimbault M & Viniegra-Gonzalez G (Eds), 1995, Advances in Solid Substrate Fermentation, Kluwer Academic Publishers, Dordrecht. Roussos S, Raimbault M, Prebois JP & Lonsane BK, 1993, Zymotis, a large scale solid state fermenter- design and evaluation, Applied Biochemistry and Biotechnology, 42, 37-52.
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3.1 INTRODUCTION To analyze the factors that may influence in solid-state fermentation, it is necessary to take into account a consideration which kind of factor we are considering. Generally, two types of factors exist:
Biological factors: These factors are related with the biology, metabolic process and reproduction of a living species or organism. These determine the behaviour of the particular species in a specific way.
Physico-chemical factors: These factors are related with the physico-chemical phenomena occurring in the system. These factors affect such mechanisms of the system that could be related with the transport phenomena of momentum, energy and mass with all the thermodynamics considerations that it could imply. Of course, all these factors are intimately related and cannot be considered as independent one from another. It is necessary to distinguish when a particular factor is affecting a particular response and when it is affected. In a specific SSF process, all the factors covered will be present at the same time. The duality that a factor could have as biological and as physico-chemical factor need to be considered. For example, in SSF the viscosity variation of air flowing though the solid matrix with temperature increase due to the heat evolved in the process is meaningless in comparison to the biological response to this increase. It is also very important to determine which factors are independent, or dependent. In SSF, factors are generally considered as independent, although this might not be the case. A factor can be independently related to the biological behaviour
but dependent when it is related to the physico-chemical process and v i c e versa. Consider, for example, temperature. It is well established that microorganisms grow better at a particular optimum temperature and have a relative narrow range of temperature for living. Here, the temperature is an independent factor. However, in the system temperature, will rise due to the effects of heat generation and transfer. In this sense, temperature is a dependent factor. It is very important to keep in mind above considerations. While analyzing the real factors that decide the development of a SSF process (as we shall see in future chapters from their interactions), these will have impact on: 9 strains selection, 9 design and characteristics of a particular medium for fermentation, 9 substrate conditioning, 9 importance of control of specific factors, 9 control criteria, 9 design of reactors.
3.2 CARBON SOURCE AND CARBON/NITROGEN RELATIONSHIP (C/N) Type, source and nature of carbon and nitrogen are among the most important factors for any fermentation process. Carbon source represents the energetic source that will be available for the growth of the micro-organism. It could be as simple as a pure monosaccharide compound such as glucose, or as complex as polymeric molecules such as cellulose, or starch. As a matter of fact in any fermentation process when selecting a proper energy, or carbon source, there could be two points of view: a)
Select the carbon source as a function of the micro-organism to be employed and the products to obtain. This means in the widest sense to formulate the proper medium.
b)
Select the adequate micro-organism in order to employ a particular substrate component. This point of view is related with the use of resources such as industrial residues, use of eventually harmful wastes to the environment or raw materials that could improve the economics of established technology. This, of course, means too that the media need to be formulated.
While dealing with media formulations, it is necessary to take into account the biomass composition. Cellular biomass presents as average 40-50% carbon, 30-50% oxygen, 6-8% hydrogen and 3-12% nitrogen. Other elements such as phosphorus, sulphur and metals are important as part of the cell and its metabolism but are present in such small quantities that need to be considered for their particular significance.
From all the principal components of cellular biomass, carbon source is the most important one and should be given significant consideration. The yield of a product in kinetic studies i s based on the consumption of carbon source ((Yx/s) Theoretically, this parameter has a value of 0.5 when the carbon sources are sugars. Nitrogen is the next most crucial factor that determines the growth of micro-organisms and needs to be calculated or determined to obtain maximum biomass. This is based on the yield (Yx/s) and the biomass composition. The other two components, oxygen and hydrogen are obtained through the organic carbon source. Generally, it is believed that the ratio between the mass of carbon and nitrogen (C/N) is most crucial for a particular process to obtain a specified product. This statement is valid when the metabolite to produce is non-growth associate or even partially associated. In the case when the metabolite is associated to growth it is better from the beginning of the process to bring the balanced medium. Besides, when dealing with fungi, it is necessary to take into account how the C/N ratio could induce or delay sporulation. Exercise 3.1 Determine the ratio of C/N that is needed to obtain biomass from a strain of Aspergillus niger. The empirical formula for this strain is CH1.77 00.72 No.085. Consider a 50% yield of biomass based on sugar consumption (g biomass produced/g sugar consumed), b) In a solid state fermentation process with an initial concentration of total reduced sugars of 30% dried basis, which is the amount of (NH4)2SO4 that must be added to the medium for obtain the maximum biomass and which is the ratio C/N in the medium. Solution: a)
Basis of calculation: 1 mol biomass
Molecular weight of biomass: 12.011 + 1.77 + 0.72(16) + 0.085 (14.008) = 26.5 g Carbon weight needed to produce 1 mol biomass: 12.011 g Nitrogen weight required to produce 1 mol biomass: 0.085 (14.008) = 1.19 g Ratio C/N weight in the biomass: 12.011/1.19 = 10.09 b) Basis of calculation: 100 g of medium dry weight basis Biomass to produce (g): 30(0.5) = 15 g of biomass Biomass to produce (mol): 15/26.5 = 0.566 mol biomass Nitrogen required: 1.19(0.566) = 0.67 g Weight ratio carbon/sugar considering total sugar as glucose" 12/(12 + 2 + 16) = 0.4 g Carbon present in the substrate: 0.4(30) = 12 g
Ratio C/N weight in the substrate: 12/0.67 = 17.91 Ratio N/(NH4)2SO4: 2(14) / 2(14) + 8 +32 + 4(16) = 0.212 (NH4)2SO4 required in the medium: 0.67/0.212 = 3.16 g Reader must take into account that the ratios of C/N in the biomass and in the medium are related by the yield and the biomass composition. Normally, a C/ N ratio of 16 is frequently found suitable for fermentation processes. From the Exercise 3.1, we can see that when a medium is formulated, it is very important to know not only the sources of carbon and nitrogen but also the chemical composition of biomass and the yield expected in the process. These considerations shall allow designing the medium in such a way that there will not an excess of any of the components. This means that the materials required would be used adequately and not in excess with the consequent waste of materials and increase in the production cost. As it has been pointed out before, it must be kept in mind that when we are dealing with the production partially, or not associated product with the growth, C/N could vary. Then a particular research about which is the best C/N ratio must be done.
3.3 TEMPERATURE Biological processes are characterized by the fact that they are developed in relatively very narrow range of temperature. High temperature limits for development could be found in many cases at values not higher than 60-80~ and with particular strains at utmost at 120~ The significance of temperature in the development of a biological process is such that it could determine effects such important as protein denaturization, enzymatic inhibition, promotion, or inhibition on the production of a particular metabolite, cells death etc. Importance of temperature in the growth of micro-organism brings to a classification considering the temperature, or the temperature range in which the microorganism grows.
3.3.1. Extremo-thermophiles There are some micro-organisms, which survive at temperatures as high as 400~ (for example those found on sea-beds in sulphur-chimneys). These may have optimum activity between 100-250~
3.3.2 Thermophiles These micro-organisms present capacity of growth at such temperatures as 80-95~ with optimum growth temperature in a range between 45-70~
3.3.3. Mesophiles The capacity of growth for these micro-organisms does not exceed a temperature of 50~ Optimum temperatures for growth lay between 30-45~
3.3.4. Psychrophiles These micro-organisms can grow at temperatures below 0~ for growth between 10-20~
with optimum
The above classification is somewhat arbitrary and no strict adherence should be given to the temperature ranges as these may vary according to different authors. If we know which kind of micro-organism we have, we can determine its adequacy for a particular process. Normally, the fermentation processes (SSF as well as SmF) develop with mesophilic microbial strains. However, the trend is to look for thermophilic ones that in some sense could allow solving the problems of heat evolution during the process. However, mesophilic strains are by far the most existent. Temperature rise due to exothermic characteristics of fermentation processes is one of the main difficulties faced in SSE Temperature control is more difficult in SSF processes when compared with SmF processes. In the case of SSF, the solid characteristics of the substrate lacks the homogeneity in the reactor and, therefore, results the existence of temperature gradients. Such facts make the heat exchange difficult in the system. A typical example of the temperature effect in SSF can be observed in the process of composting. This process is developed spontaneously through the growth of the natural micro-flora present in it. As temperature arises due heat evolution, the activity of micro-organisms belonging to mesophilic temperature range growth at environmental conditions trends to diminish and start to impose higher temperature range (thermophilic) micro-organisms. Undoubtedly the temperature control is one of the factors that decide the good development of SSF and must be taken into account when any SSF process is design.
3.4 MOISTURE AND WATER ACTIVITY (a.) Moisture is a factor that is intimately related with the definition SSF and with the characteristics of the biological material. The importance of water in the system is due to the fact that the great majority of viable cells are characterized by moisture content of 70-80%. From this simple observation, it is easy to arrive to the conclusion about the necessity to have a certain quantity of water available for new cell synthesis. Importance of moisture for SSF processes has been well documented.
In a general sense, it has been established that in the case of bacteria the moisture of the solid matrix must be higher than 70%. For yeast, the moisture range can be a little wide as 72-60% and in the case of fungi the range could be as wide as 70-20%. This certainty by itself could signify a great advantage for the development of a specific SSF process. In a case where the optimum moisture level for growth for employed micro-organism is relatively low, this could be a natural barrier to possible contaminants. In this case the need of a sterilization treatment could be less rigorous or even absent. In relation to water interchange in the system, a good measure is provided by the interchange between the substrate and airflow. The mass transfer mechanism between the different components of the substrate and the airflow is studied by Thermodynamics, based on the free energy concept. Any substance (A) present in a mixture has a vapour pressure that will correspond to the equilibrium between the concentration of the substance (A) in the mixture and the concentration of the substance (A) in the gaseous phase. This vapour pressure is evaluated from the Raoult's Law as: ea = P'AXA
where: Pa: vapor pressure of substance A in the gaseous mixture at a particular temperature.
P'A: vapor pressure of pure substance A in the gaseous mixture at a particular temperature. XA: molar fraction of A in the mixture. Considering that the gaseous phase is in equilibrium with the mixture (in our case with the solid substrate) and assuming that this phase is an ideal gas, the molar fraction of the substance (YA) in the gaseous mixture can be calculated as:
YA PA I'--AXA 1'1 et =
Where: Pt: total pressure of the gas in the system However assuming that Raoult's Law is applied only for ideal mixtures, therefore,
I i i iii!
iii i ii!
ii. . . .
iiii]iilJiiiiiiiiiiiiiiiiiiii!iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii!iiiiii ...........ilii!i_ii....
when we are dealing with non-ideal mixtures the former equation is modify by the following expression: Pa = ptAXA'YA
Where: ~/A: activity coefficient of substance A From the preceding equation, water activity (aw) is defined already as: P)v aw
=
.......
=
XA~
Pt
It must be noted that the concept of water activity (aw) was introduced as a definition in which the gaseous phase is considered as an ideal gas. This assumption at normal work pressures and temperatures are fair. Note that for the definition it was not necessary to consider the mixtures as ideal. The water activity (aw) is measured using different methods and equipments, which basically imply to measure the respective pressure between the mixture and the gaseous phase in equilibrium. At the same time it must be take into account that in the equation in which the water activity (aw) is defined as the ratio pw/Pt is the definition of the relative humidity of the gaseous phase. From this regard, values for the water activity (aw) were determined in which micro-organisms could grow or not. In the case of bacteria normally they can grow at water activities higher than 0.95 but in the case of fungi there are some that can grow even at such low water activities as 0.6. The importance of moisture and water activity (aw) imply that while preparing a substrate, it is necessary to consider the exact quantities to be added to the substrate in order to have the proper required for the system. Exercise 3.2 A solid-state fermentation will be developed to obtain protein enrichment of cassava flour. A strain of Rhizopus oryzae will be employed. This strain has 32% protein content on weight dry basis. The flour has moisture content of 12% and a starch content of 83% humid basis. As nitrogen source urea will be used. In addition, KH2PO 4 would also be used for the phosphorus requirements of 0.2% in dried biomass. Fermentation starts with a 10% w/p of a liquid inoculum of threedays old. The starting medium must have a 62% of initial humidity.
Calculate the quantity of the different components of the substrate that must be added. Make all the pertinent assumptions. Basis of calculation: 100 g humid substrate Total solid balance: a) Initial total solid in the substrate: 100 (1 - 0.62) = 38 g b) Initial cassava flour at to employ (assumed): 42 g c) Initial dry weight of cassava flour: 42(1 - 0.12) = 37 g d) % starch fermented from the cassava flour (assumed): 50 e) Fermented cassava flour: 37 (0.5)= 18.5 g f) Yield biomass/substrate (Yx/s) (assumed): 50% g) Biomass produced: 18.5 (0.5) = 9.25 g h) Protein produced: 9.25(0.32) = 2.96 g i) Nitrogen required in the process: 2.96/6.25 = 0.47 g j) Urea required in the process: 0.47/0.466 = 1.01 g k) KH2PO 4 required: 9.25 (0.002)/0.23 = 0.08 g Checking the total solid to add: 37 + 1.01 + 0.08 = 38.09
(see a)
Water balance: a) Total water required in the substrate: 100(0.62) = 62 ml b) Water added with the cassava flour: 42(0.12) = 5 ml c) Water added with the inoculum: 100(0.1) = 10 ml d) water to be added: 62 - 5 - 10 = 47 ml Substrate formulation with inoculum included: 42 g cassava flour 1 g urea, 0.08 g de KH2PO 4 47 ml water From the Exercise 3.2, it is observed that the media formulation in SSF is a little more complicated that when dealing with submerged fermentation conditioned for the initial moisture or the water activity that must be observed.
3.5 pH pH is one another among the other most important factors for any fermentation process. Each micro-organism possesses a pH range for its growth and activity with a optimum value in between the range. A very noticeable example about how pH influences in the microbial development is offered by the use of Lactobacillus sp. as preserving of storage fibers. The growth of the micro-
organism results in lowering the pH to level of ca. 3. This low pH avoids the growth of parasite micro-organism that could spoil the material, pH control is one of the problems not yet solved in SSF processes. This problem is due to the lack of proper equipment and electrodes to determine the pH in solid materials and the existence of pH gradients due to the heterogeneous characteristics of the process. An attempt to overcome the problem of pH variability during the SSF processes is obtained by the substrate formulation considering the buffeting capacity of the different components employed or by the use of buffer formulation with components that have no deleterious influence on the biological activity. In general, it can be observed that fungi have pH ranges for growth between 3.5-6.0, yeast between 4.5-7.0 and bacteria a little higher than the last ones. However, this should not be taken as a rule. It should be kept in mind that some Lactobacillus sp. and other bacteria can grow at such low pH as 2.
3.6 AERATION AND AGITATION These two factors have generally a determinant influence in SSF due to two fundamental aspects: demand in the aerobic processes, 9 heat and mass transport phenomena in a heterogeneous system.
9
0 2
02 demand does not present the difficulties from the physiological point of view observed in the submerged fermentation. It is not necessary to have mechanisms, physical or chemical that allow that the 02 be dissolved previously in a liquid phase before it could be employed for the metabolic process. In this sense, 02 demand in SSF can be satisfied with relatively low aeration levels. Considering the aeration levels, it is very important that they can be expressed through intensive and not extensive values in order to make independent levels from the scale in which the process is developing. A criterion to express the aeration in a particular system is obtained by the airflow intensity or VKgM. This value is the airflow expressed by unit substrate weight, commonly as 1 air Kg-lm -1. It must be made clear that the weight considered for the calculation was on dry or wet basis. Once the level of aeration is found as an intensive factor, this value could serve as aeration criteria for higher scales of the process. This indeed does not mean that the value can be taken as scale-up criteria, but could be used as a starting point at the new levels. Exercise 3.3 To develop the SSF of 100 g of substrate from the medium reported in Exercise 3.2 with an airflow of 2.5 l/h. Determine the
airflow that must be used to ferment 1 t of this substrate with a humidity of 60%. Solution:
Base for calculation 100 g substrate. VKgM: 2.5/(0.038)(60) = 1.1 1 air Kg-1
m -1
Airflow required for 1 t substrate: 1.1(400)(60) = 26400 1/h R. Other point to take into account with the aeration is the air quality at the entrance to the fermenter, in particular, the air moisture. Use of saturated air is a common practice to avoid substrate drying or change in water activity. This procedure is not always advisable. Airflow, as we will see in other chapter, is the main tool to transfer the heat evolved during the process. Water evaporation and heat transfer with the surrounding are the processes to keep the process temperature in proper limits. Obviously, a contradiction exists between the heat to eliminate and the moisture in the system, but as we will see, a variable flow of air and its quality could improve temperature control. As has been pointed out earlier, in heat transfer there occurs the existence of gradients owing to the heterogeneous nature of the system. Substrate heterogeneity causes too possible air canalisation. When air canalisation occurs, there will be non-aerated zones that could produce non-desired cell metabolism changes. A possible solution to solve heterogeneity problems is agitation. Agitation could improve the homogeneity and disrupt gradients. However, if it is fight that agitation improves homogeneity, there may exist problems related to the integrity of the microbial cell. This may be particularly true related to fungi mycelium. Some authors have reclaimed mycelium damage when agitation was used. Others have employed intermittent agitation, often with good results. In case of bacteria or yeast, agitation could favour the biomass drag related to airflow mainly when cells are not tight enough on substrate surface. It is, therefore, necessary to study agitation and analyse its influence particularly for a determinate process.
3.7 PARTICLE SIZE Particle size of the substrate has a particular importance related to substrate characterization and system capacity to interchange with microbial growth and heat and mass transfer during SSF process. It determines several parameters through which a heterogeneous system is characterized. One of these parameters is the void fraction (8), which is defined as:
t3-
V V0
where: (e): void fraction of the system. (Dimensionless) V : volume empty space with particle. (m 3) Vo: void volume. (m 3) In relation to particle size, however, it must be kept in mind that in SSF processes it does not remain constant and tends to diminish. Mycelium formation is the main cause for void fraction variation. This is particularly true in fermentation in which fungi are used. This variation could even provoke canalisation during the process. Matrix, or solid substrate characteristic is closely related with SSF systems. One of these characteristics is the surface on which the process develops. Several types of particle were employed. Synthetic materials such as Amberlite pearls or natural materials such as agro-industrial residues (e.g. sugarcane bagasse) can also be used as matrix for SSF processes. When dealing with agro-industrial natural materials, generally it is a practise to pre-treat them to achieve improved microbial attack. Reduction in particle size through milling is one of such pretreatment, which provides larger surface area for microbial growth. However, it must be underlined that particle size could show an optimum range. Very tiny particle could produce matrix contraction or compaction, enhance channelling problems, increasing mass and heat transfer problems etc. Considering first synthetic materials as matrix for SSF process and presuming that all the particles are spherical and equal, superficial area is defined as"
Sp = gD 5 Where: Sp 9 superficial area (m 2) Dp: sphere diameter (m) The superficial volume of the particle (sphere) is defined as: Vp =
1
6
rtD3p
Where: Vp: superficial sphere volume (m 3) From the above relations, the ratio surface/volume for a sphere can be obtained
as" Sp
6
When dealing with non-spherical particles, superficial surface and superficial volume are defined as" Sp = 6b D 2p
and
Vp -9
6a D 2p
respectively. In the last expressions, a and b are constants that express in some way the form of the particles and are determined experimentally. More useful is the ratio between the superficial surface/superficial volume obtained for any irregular particle from these expressions as:
Sp
6q)s
Vp
Dp
Where Cps = b/a 9s is called as the form factor. The form factor is estimated from measurements of particles in their possible dimensions, as for example, width and length. The reader could look for these methods in any book dealing with Chemical Engineering Process. As it is obvious, the form factor for a sphere is 1. What is important to distinguish in this section is that the above definitions and other complementary ones not only characterize the solid substrate but must be taken into account when dealing with such problems as mass and heat transfer in SSF processes. As a general conclusion from this chapter, the reader must keep in mind that all those factors that may affect the good
development, or a particular activity of any micro-organism. Such factors as the influence of growth factors, inhibition substances, growth promoters, etc., need to be considered as particular demands of a particular process. When considering these factors, it must take into account the particular characteristics of the solid matrix in SSF processes and its heterogeneous form.
ENERGY BALANCE IN A SOLID-STATE FERMENTATION PROCESS
3.8 INTRODUCTION One of the principal problems faced in solid-state fermentation is to describe the way in which the energy evolved in the process could be evacuated. Undoubtedly, this is a problem that determines not only the development of the process but its economic possibility too. As it could be expected, the energy produced during the fermentation is responsible for factors such as the temperature rise in the system, air demand, specific growth rate of the micro-organism employed and even the type of reactor to be used. In this sense, it is extremely important to perform an overall energy balance that may allow establishing these relationships among the factors already postulated.
3.9 OVERALL ENERGY BALANCE When an energy balance is attempted in a solid-state fermentation process, it must be taken into account the following mechanisms: -
Heat evolved that dissipates as heat transfer from the solid substrate to the air that flows through the bed. Heat transfer from the wall of the reactor to the surroundings. Metabolic heat produced during the fermentation.
In the first mechanism, it is very important to consider the air conditions such as air humidity, air temperature and air flow, while the second one is directed by the heat transfer coefficient through the fermenter wall and the temperature gradient between the system and the surroundings. In a macroscopic energy balance, these conditions are considered but it requires the estimation of the heat evolved during the process. The macroscopic balance in the fermenter at steady state is as follows" Ein + Eme t = Eou t + Esurr
Where:
Ein: energy in the inlet air (kcal/h) Emet: energy released by microbial metabolism (kcal/h)
3.1
Eout: energy in the outlet air (kcal/h)
Esurr: energy loss to surroundings through the wall of the fermentor (kcal~)
The energy in the air (Ein and Eout) may be estimated from the enthalpy of air. Air enthalpy is generally defined by: i=
3.2
(0.24 + 0 . 4 5 H ) T + ~, H
Where: i
~
H"
enthalpy of humid air (kcal/kg dry air). absolute humidity of air (kg water/kg dry air). latent heat of vaporization of water (kcal/kg water).
In the Equation 3.1, the energy loss to the surroundings is expressed as: 3.3
Esurr'- hA (Tou t - Tsurr)
Where: h A
9 heat transfer coefficient of the fermenter wall (kcal/m2/h/~ 9 wall surface area of fermenter (mZ). Tout " temperature of the outlet air (~ T~urr" emperature of the surroundings (~
Substituting Eq 3.2 and 3.3 in 3.1, rearranging and considering Emet as Qm it may be deduced that: W g
Qm - hA ( T~ =
- Tin )
0 . 2 4 ( T o u t - Ti~ ) + 0 . 4 5 ( ToutHou, - Ti, n ~ ) + ~( H out- H ~, )
3.4
In Eq. 3.4, it was considered that the temperature of inlet air was the same as the temperature of the surroundings and that Wg was the mass velocity of dry air (kg dry air/h). Furthermore in Eq 3.4, the t er m 0.45(Toutnout-Tinnin) corresponding to metabolic water production could be overlooked, therefore, Eq. 3.4 can be simplified to: Qm - h A ( Tout - T~. ) Wg =
0.24( Tou, - T~, )+ /q,( nou~ " H ~ , )
3.5
In Eq. 3.5, the term Qm may be estimated from the Eq. 3.1 already deduced which is related to the biomass synthesis rate (Rb). In relation to the biomass
synthesis appraisal for a particular process, it is required the model that describes such synthesis. Several models are reported for characterizing this behaviour in solid-state fermentation and among them the archetypal model that describes the exponential growth phase was also reported. Thus, if the model for the exponential growth could be applied, it may be postulated that: 3.6
X = Xo e~t
Where: X Xo kt t
9 9 9 9
cell mass produced at a particular time (kg) initial cell mass (kg) specific growth rate at the exponential phase (h-1) time (h)
Hence, from Eq. 3.6:
Rb-
dX dt
3.7
- t-tX oe ut
Relating the Eq. 3.5, 3.7 and 3.1, following is obtained:
Q ~ (1-rlT1)tYb 7 b l't
o e I.tt_ hA(Tout- Tin)
3.8
Wg= ~(nout
-
H in) @ 0.24(Tout- Tin)
It must be kept in mind that if other model is used to represent the growth of the micro-organism and not the exponential one, the procedure would be the same requiring solely that the Eq. 3.6 and 3.7 be defined for the new assumption. The inferences that could be done from Eq. 3.8 are remarkable. First of all this expression allows to consider the specific growth rate (it) of the micro-organism employed in the process as a function of the air demand and air quality, both of them acting as regulating factors. Accordingly, air demand and air quality must be considered variable components of the process. In this sense, they could be a medium for attempting the control of solid state fermentation processes. It must be denoted that normally the solid state fermentations reported anywhere consider the air demand of the process and its quality as constants.
not differ very much, this value was assumed as fair. The absolute humidity (H) and the latent heat of vaporization of water ()~) was taken from the psychrometric chart and the thermodynamic table as 0.036 kg water/kg dry air and 560 kcal/kg water, respectively, assuming saturated conditions and an average value for the latent heat of vaporization of water. Substituting the required values in Eq. 3.8 is obtained the expected expression for the heat evolved in this system as:
AQ Rq = ~
At
= 0.39
t.t e ~t
3.9
The general expression that considers the whole system for this particular process may be obtained from Eq. 3.8 and 3.9 and from the values already discussed:
0.39 t.te ut- 0.58(Tou~- 35) Wg =
0.24(Tou, - 35) + 560(H out-O.O36)
3.10
The Eq. 3.9 showed an exponential pattern like it was expected considering that it was assumed an exponential model for the growth of the micro-organism. On the other hand, in Eq. 3.10, the dry air demand (Wg) is expressed as a function of outlet temperature (Tout), the maximum specific growth rate deduced from the exponential phase (g) and the absolute humidity of the exhaust air (Hour). For resolving this equation, the variability of the absolute humidity (Hour) as a function of the exhausted air temperature from the fermenter must be calculated. From the definition of the absolute humidity and considering that the exhaust air that leaves the reactor is saturated, following expression is depicted:
H=
0.62 Ps 1-Ps
3.11
where" H
Ps:
~
absolute humidity (kg water/kg dry air) vapor pressure of saturated air (atm)
An empirical expression was reported for the partial pressure of saturated air (Ps) as a function of temperature from the modeling of the psychometric chart, so:
.
ax+bx2+Cx 4
p= = 2 1 8 x 10t(!.,.d~(a47-x~ ~
3.12
Where the coefficient values in the empirical equation are: a: b: c: d:
3.2438 5.8683 x 10-3 1.1702 x 10-8 2.1878 x 10 -3
and: x = 3 4 2 - Ts
3.13
Where: Ts: temperature of saturated air (~
It must be noted that this last expression relates the partial pressure of saturated air with temperature through Eq. 3.12, and hence the absolute humidity with temperature through Eq. 3.11. Other parameter that must be calculated is the dry air mass velocity (Wg), which was considered constant during the whole process and was estimated from the constant airflow employed (4 l/h) as already reported. Its value was 0.036 kg dry air/h. For this estimation it was considered that the inlet air was saturated at 35 ~ There are two possibilities for solving the equation system offered by Eq. 3.10 to 3.13. Specific growth rate (kt) could be considered as an independent variable or as a constant value during the process. In both the conditions, the system was solved for the outlet temperature. In latter case when we assumed the specific growth rate as constant, the value selected was 0.30 h -1. The results for the predicted temperatures are shown in Table 1. As it may be seen from the table, specific growth rate showed a tendency of decrease during the fermentation and after the first eight hours, it was 50% of the initial value. It could be quite possible that this pattem responded to the evolved heat in the process. As we may see, for a theoretical value for the specific growth rate of the order of 0.3 h-1 after 10 h of fermentation, the temperature would be of the order of 40~ This meant that it could be supposed that the process was auto regulated as has suggested by Eq. 3.10. One important conclusion from this behaviour is the need of change in the air demand, or the air quality during the process according the Eq. 3.10 in order
to preserve high specific growth rates and not to develop the process at constant air flow rates, or constant air quality as is often done. Considering the variation of the air flow, or the quality of air in the process, it is very important not to overlook the effect that the substrate humidity produces over the microbial growth, because the air quality determines the water mass transfer between the substrate and the flowing air and therefore, it could produce a drying in the system at a level that may not be allowed. Another conclusion not to be overlooked is to consider the design of reactor, or fermenter that allows a better heat transfer in order to diminish air flow requirements. As a general conclusion, it may be stated that the method here reported for the modeling of solid-state fermentation process seems to be fairly good and could bring a basis for the development of a mechanism of control in such processes.
Table 1. Comparison between the values reported in solid state fermentation system of cassava and the values estimated by the macrscopic heat balance based in the process electron balance,
*values estimated considering p at a value constant of 0.30 h-~
.................................................
...............
................
NOMENCLATURE A
Ein greet Eout surr
H h i 1
Ms N N Nb
No Ns nc nil ni
nn no
P Ps
Q Qo Qm
q
Ro
Rq Tin
Tout
Ts t X
Xo Ys
wall surface area of fermentor (m 2) energy in the inlet air (kcal/h) energy released by microbial growth (kcal/h) energy in the outlet air (kcal/h) energy exchanged with the surroundings (kcal/h) absolute humidity of air (kg water/kg air) heat transfer coefficient of the fermented wall (kcal/m2/h/oC) enthalpy of humid air (kcal/kg dry air) atomic ratio of oxygen to carbon in a substance (dimensionless) biomass produced in a period of time (kg) consumed oxygen in a period of time (kg) consumed substrate in a period of time (kg) available electrons in a molecule/atom carbon (equiv. available electrons/g atom carbon) available electrons in a molecule equiv, available electrons transfered to biomass equiv, available electrons transfered to oxygen equiv, available electrons transfered from substrate number of atom carbon in a molecule number of atom hydrogen in a molecule number of a particular atom in a molecule number of atom nitrogen in a molecule number of atom oxygen in a molecule atomic ratio of hydrogen to carbon in a molecule (dimensionless) vapor pressure of saturated air (atm) heat evolved during a period of time (kcal) heat evolution per equivalent of consumed oxygen (kcal/g equiv.) rate of metabolic heat (kcal/h) atomic ratio of nitrogen to carbon in a substance (dimensionless) rate of biomass synthesis (kg/h) rate of oxygen consumption or respiration rate (kg/h) rate of heat evolved in the process (kcal/h) rate of substrate consumption (kg/h) temperature of inlet air (~ temperature of outlet air (~ temperature of saturated air (~ time (h) mass velocity of air (kg dry air/h) cell mass produced in a particular time (kg) initial cell mass (kg) yield based on oxygen consumption (dimensionless) yield based on substrate consumption (dimensionless)
I[ll % 1] ~t t~b O"s
i~~
....
~
ii!J~ii~ii~
!!}j
~~iik!iiF .....ii.......!i..!.Jl..i...Jjii........Ji..!.iH...ii.i!.i.!i.!.i!....ii!i ........iii}i ...........
reductance degree of dry biomass (equiv available electrons/g atom carbon) reductance degree of substrate (equiv. available electrons/g atom carbon) biomass energetic yield or fraction of energy in the substrate which is converted to biomass (dimensionless) specific growth rate in the exponential phase (h-1) latent heat of vaporization of water (kcal/kg of water) weight fraction carbon in biomass (dimensionless) weight fraction hydrogen in substrate (dimensionless)
References Auria R, Palacios J & Revah S, 1992, Determination of the interparticular effective diffusion coefficient for CO2 and 02 in solid state fermentation. Biotechnology and Bioengineering, 39, 898-902. Carrizalez V, Rodriguez H & Sardifias I, 1981, Biotechnology and Bioengineering, 23, 321. Dale BE, Beba A, M'Nasria H, Alvarez-Martinez R, Nebot E, Nazmul Kerim M & Tengerdy RP, 1987, Memorias Simposium Latin Biotecnology, Antilla, Guatemala, p. 89. Desfargues C, Larroche C & Gross JB, 1987, Biotechnology and Bioengineering, 29, 1050. Erickson LE, Minkievich IG & Eroshin VK, 1978, Biotechnology and Bioengineering, 20, 1575. Erickson LE, Minkievich IG & Eroshin VK, 1979, Biotechnology and Bioengineering, 21,575. Minkievich IG & Eroshin VK, 1973, Folia Microbiologica, 18, 376. Minkievich IG, 1983, Biotechnology and Bioengineering, 25, 1267. Narahara N, Koyama Y, Yoshida T, Atthasapunna P & Tagushi H, 1984, Journal of Fermentation Technology, 62 (5), 453. Okasaki N, Sugama S & Tanaka T, 1980, Journal of Fermentation Technology, 58 (5), 471. Rairnbault M, 1981, Travaux et Documents de l' O.R.S.T.O.M. no. 27. Ramana Murthy MVR, Karanth NG & Raghava Rao KSMS, 1993, Biochemical engineering aspects of solid-state fermentation. Advances in Applied Microbiology, 38: 99-147. Rathbun BL & Shuler ML, 1983, Heat and mass transfer effects in static solid-substrate fermentations: Design of fermentors chambers. Biotechnology and Bioengineering, 25, 929-938.
Rodriguez Le6n JA, Bechstedt W, Echevarria J, Sierra N, Delgado G, Daniel A & Martinez O, 1986, Optimization of solid state fermentation of citrus dried peel by Aspergillus niger in a packed bed column. Acta Biotechnologica, 6 (3), 253-258. Rodriguez Le6n JA, Echevarria J, Sierra N, Daniel A & Martinez O, 1985, Solid-state fermentation of dried citrus peel. Biotechnology Letters, 7 (8), 577-580. Rodriguez Le6n JA, Garcia I & Sierra N, 1983, Thermal methods to study transformations of citrus wastes by solid fermentations, Boletfn Informaci6n Cientffico T~cnica del Instituto de Qufmica y Biologfa Experimental de la Academia de Ciencias de Cuba. 3 (1), 19-21.
Rodriguez Le6n JA, Sastre L, Echevarria J, Delgado G & Bechstedt W, 1988, A mathematical approach for the estimation of biomass production rate in solid state fermentation. Acta Biotechnologica, 8 (4), 299-302.
Rodriguez Le6n JA, Sastre L, Echevarria J, Delgado G & Bechstedt W, 1988, Acta Biotechnologica, 8 (4), 299-302. Rodriguez-Leon JA, Domenech F, Leon M, Mendez DE & Pandey A, 1999, Production of spores of Trichoderma harzianum on sugar cane molasses and bagasse pith in solidstate fermentation. Brazilian Archives of Biology and Technology, 41 (1), 69-76.
Rodriguez-Leon JA, Torres JA, Echevarria J &Saura G, 1991, Acta Biotechnologica, 11,9-14.
Rodriguez-Leon JA, Torres JA, Echevarria J & Saura G, 1991, Energy balance in solid state fermentation processes. Acta Biotechnologica, 11, 9-14. Sarrette M, Nout MJR, Gervais P & Rombouts FM, 1992, Effect of water activity on production and activity of Rhizopus oligosporus polysaccharides, Applied Microbiology and Biotechnology, 37 (4), 420-425. Sato K, Nagatani M, Nakamura K & Sato S, 1983, Growth estimation of Candida lipolitica from oxygen uptake in solid state culture with forced aeration. Journal of Fermentation Technology, 61 (6), 623-629. Saucedo-Castafieda G, Guti~rrez-Rojas M, Bacquet G, Raimbault M & ViniegraGonz~ilez G, 1990, Heat transfer simulation in solid substrate fermentation. Biotechnology and Bioengineering, 25, 802-808. Saucedo-Castafieda G, Lonsane BK, Navarro JM, Roussos S & Raimbault M, 1992, Importance of medium pH in solid state fermentation for growth of Schwanniomyces castellii. Letters in Applied Microbiology, 15, 164-167. Smits JP, Rinzema A, Tramper J, van Sonsbeek HM, Hage JC, Kaynak A & Knol W, 1998, The influence of temperature on kinetics in solid-state fermentation. Enzyme and Microbial Technology, 22, 50-57.
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Fermentation
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4.1 INTRODUCTION Kinetic studies in SSF are generally considered difficult as the heterogeneous nature of the SSF processes poses difficulty in biomass estimation. This is because the biomass cannot be separated from the fermenting substrate, a fact, which does not allow to obtain a homogeneous sample during the fermentation. These problems are particularly acute in the case of fungal growth and mycelium production. In this chapter we shall study different alternatives that allow kinetic performing in SSF in an objective and satisfactory manner. Undoubtedly, kinetic process is the procedure that describes the development of the process. Even with the difficulties that are encountered in SSF processes, kinetic procedure cannot be substituted by goodwill, subjectivism, or even by the simple and overall process description. Although the reader can consult several books related with submerged fermentation in which particular concepts of kinetics in fermentation are dealing, we prefer to introduce these concepts in a simple and gradual manner. The fundamental objective is that the reader could distinguish between the validity of a concept and the possible difficulty in its implementation. The importance of kinetic resides in the fact that these studies imply the determination of important parameters such as: 9 9 9 9 9
specific growth rate process yield process productivity heat evolved process control criteria
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9 strategy for the production of a particular product scale-up considerations
9
4.2 SPECIFIC GROWTH RATE A kinetic study or the kinetics of a process is determined by the variation of one or several variables during the fermentation time. From this point of view, any available (measured) variable can be chosen to determine kinetic characteristics. The selected variable will be related with other factors in the process. It must take into account how these factors are related and which is dependent or independent factor. Factors identification and their relationships eventually will permit the establishment of appropriate models describing the process or part of it, postulate studies for process optimization, determine control criteria etc. It must be underlined that kinetic means necessarily the determination of at least one variable with the time bearing in mind that time; at the same time, could be explicit or implicit in the models, which represent the process kinetic. In a fermentative process, the variable used to establish the process kinetic has been usually the variation of biomass (synthesis) in the system, variation of substrate content, variation of a product (metabolite), determination of 02 consumed or CO2 evolved, heat evolved, etc. Among these variables, biomass synthesis during the process and substrate consumption determination has to be conducted following the procedures that represent kinetically any fermentation process. Considering the biomass variation during running time in the process, in a general manner it can be said that this variation depends on several factors, hence, dx
~ = f ( x , s , T , etc.) dt
4.1
Where: X
~
t
9
S
"
T"
biomass concentration (g biomass/1) time (h) substrate (g substrate/1) temperature (~
First term in the equation 3.1 is a velocity or kinetic term. It represents a unit change (in our case biomass concentration) by time unit. Figure 4.1 shows a characteristic curve showing biomass synthesis in a process.
Figure 4.1 Variation: (a) cell concentration, and b) substrate content during a batch submerged process employing a strain of Lactobacillus acidophilus
From Figure 4.1, the process development can be described in a very simple manner and one can determine parameters such as: 9 9 9 9
Maximum cell concentration obtained in the fermentation Time delay in the rise of biomass content in the reactor Substrate consumed in the process at any time Yield biomass/substrate obtained in the process
However, although kinetic is implicit in the data, we cannot say anything about parameters that characterize it in a proper way. Monod (1942) was one of the first scientists that described mathematically a fermentation process. He proposed a model that related biomass synthesis with substrate consumed. The model is:
S
~--~max gsq-S
4.2
Where: specific growth rate (h-1) maximum specific growth rate (h -1) ktrnax : S : substrate concentration (g/l) Ks : ffinity constant biomassa/substrate (g/l) In the model proposed by Monod (4.2), time was not explicit but included in a term called specific growth rate (kt). This variable (as the name indicates) is related with velocity or rate (dx/dt) as well as with the intensity relating the velocity or rate term with the quantity of biomass present at a particular time
in the fermenter. The model proposed by Monod is, of course, process dependent. The parameters, It, ~tmax and Ks determine values for a particular process. At the same time it must be pointed out that specific growth rate is a definition and hence, is independent of the process. This definition is expressed as:
1 dX
//=~~
X dt
4.3
Where: X:
t :
biomass concentration at a particular time t (g/l) time (h) specific growth rate (h-1)
Specific growth rate (It) defined t~ough Eq. 4.3 permits the representation of kinetic pattern of microbial growth through different phases, known as growth phases and are expressed as: ,~
Lag phase: In this phase, the specific growth rate is practically null (~t = 0) and represents a stage in which microbial biomass do not start to multiply. The time this phase last is one of the characteristics to determine in the fermentation process. The period till which this phase lasts depends up on factors such as physiology of the micro-organism, environment, type of inoculum, etc.
Accelerated growth phase: This phase is characterized for the initiation of growth by the synthesis of new cells. During this phase m is >0. The lasting time of this phase is relatively short considering the whole process.
Logarithmic or exponential growth phase: This phase is characterized by the fact that the specific growth rate is constant during the whole phase. Logarithmic specific growth rate is at the same time the highest specific growth rate that can be attained in a fermentation process. This is the parameter that first characterizes fermentation from a kinetic point of view.
Desacelerated growth phase: In this phase, the biomass synthesis rate starts to demit in the process and it can be postulated that ~Lmax > ~ > 0.
Stationary growth phase: In this phase, a equilibrium is established between the quantity of cells that are synthesized and the quantity of cells that are no longer viable or loose their capacity to reproduce. In this phase it can be postulated that ~t = 0.
Negative growth rate phase: In this phase, more number of cells loose their capacity of reproduction or viability than the cells that can reproduce. In this phase the growth can be represented as kt < O. The study of each of the microbial growth phases can be done through the application of Eq. 4.3 using different available mathematical tools. A specific mathematical procedure can be found in the works of Kono and Asai (1969). Anyway, readers should keep in mind that the definitions given for the different phases could change according to different authors but their significance and proper mathematical definitions not.
4.3 MICROBIAL LOGARIHTMIC OR EXPONENTIAL GROWTH PHASE The microbial logarithmic or exponential growth phase is, as said before, the most important phase that distinguishes fermentation. It is characterize by the specific growth rate (kt) as constant and reaches the maximum value that can be obtained in the process. Is this value (kt = ktmax) a parameter that identifies immediately the significance of the process? Customarily when it refers about specific growth rate with anymore specification, it refers to the specific growth rate that belongs to the logarithmic phase that is the maximum specific growth which can be attained due to particular conditions. All through this book this appraisal will be considered except when other indications are given. Certainly the specific growth rate (kt) is a function of several variables or factors such as: temperature, pH, substrate and in solid state fermentation of substrate moisture and water activity (aw). Applying to Eq. 4.3, the statement that in the logarithmic or exponential phase kt = k, where k is a constant, can be stated that:
f
x dx
t
4.4
A from Equation (3.4):
In X-- =~tt Xo
4.5
Where: biomass concentration at time t of the logarithmic or exponential growth (g/l) Xo: biomass initial concentration at time t = to (g/l) ~t: specific growth rate at the logarithmic or exponential phase (h-i) t : time that corresponds to the biomass concentration X (h) X"
Regarding the initial biomass at time t = to, it must be recalled that in strictly sense, this corresponds to the biomass concentration at the initial exponential or logarithmic growth. Basically, the initial concentration at the beginning of the process is practically unchanged and therefore, initial biomass content can be taken as the value for the calculations. From Eq. 4.5, it is easy to obtain the doubling time value. This is other parameter that characterizes fermentation and it is the time that takes biomass concentration to achieve its double value. For the calculation, we considered that X = 2 Xo y to = 0 and integrating Equation 3.5 gave: In 2
0.693
t d = ~ = ~ ~[,/ max ~,/max
4.6
Where:
td: doubling time (h) Also, a very important parameter, the biomass productivity (P) related to the biomass synthesis, can be obtained considering the value of the specific growth rate (g). Biomass productivity is defined as: P = pX
4.7
Where: P: biomass productivity (g biomass/1 h) Other parameter directly related to the specific growth rate is substrate concentration although in its definition the specific growth rate is not explicit, the yield is based on substrate consumption (Yx/s) and is defined as"
So Yx/~ =
-
St
~ Xs-Xo
Where: Yras : yield based on substrate consumption (dimensionless) So : initial substrate concentration (g/l) St : final substrate concentration (g/l) X0 9 initial biomass concentration (g/l) Xt : final biomass concentration (g/l)
4.8
From the definitions, it could be concluded that the concepts and corresponding mathematical models or expressions were defined not considering the type of fermentation. In this sense, all these statement are equally valid for submerged fermentation as well as for solid- state fermentation. The only problem to overcome in case of solid-state process is the adequacy of proper measurements that allows the estimation of these parameters. Exercise 4.1 Determine from data reported in Figure 4.1: a) the beginning of the logarithmic phase, b) time at fermentation should be stopped case biomass synthesis is the only purpose of the fermentation, c) the yield based on substrate consumption, d) the initial of the stationary phase, e) the maximum specific growth rate that was attained in the process and f) time in which biomass duplicates. Solution:
To solve the present problem the following table is made from the date reported in Figure 4.1.
Note that negatives values for In X simple correspond to the natural logarithmic of decimal value and obviously do not alter the values to determine for the corresponding parameters, v. gr. ktmax. A graphic representation of In X vs. t allows a much easier estimate of the different questions asked in the problem and a more clearly picture of the process. Reader is suggested to compare this figure with Figure 4.1. Calculations: a) Beginning of the logarithmic phase: From the constructed graphic, it is observed that the exponential phase begins four hours after the beginning of the fermentation.
Fig 4.2 graphic representation of In X vs. t
b) Time at fermentation should be stopped because biomass synthesis is the only purpose of the fermentation: It is the corresponding time at the end of the exponential phase. From the figure it can be seen that the logarithmic phase ended at 10 h. This is the time when fermentation must be stopped. Going further is unproductive as we are concerned with biomass production only. c) Yield based on substrate consumption Yx/s" zSX
Yx/x=~=
2.45 - 0.08
10.0-5.1 overall, dimensionless)
=0.4837g de biomass/g de substrate consumed (as
Expressed as % Yx/s = 48.37 % It must be observed that to determine the yield, the final values in the yield expression correspond to the end of the logarithmic or exponential phase (in our case at 10 h). If we would consider all the time the fermentation ran, the estimate for the yield would be 30.54 %. This fact is very important to take into account. It'indicates that fermentation should be stopped at 10 h. After this time, endogenous process starts to became more important and consumed sugars are employed in major quantity than in exponential phase for this purpose. The reader must consider that in case a metabolite is the principle aim of the process, the analysis would be different mainly in case when secondary metabolites are produced. d) The initial stationary phase" From the graphic, it is taken at 14 h. e) Maximum specific growth rate (~)" The maximum specific growth rate that is reached in this process corresponds to the specific growth rate in the
logarithmic or exponential phase. From Eq. 3.5, it is obvious that the best way to estimate this value is making a lineal regression with minimum squared adjustment for In X vs t in time interval between 4 and 10. The slope corresponding to line fixing is the value of the specific growth rate, This value is constant during the whole phase and maximum (~max ---- ~). In our case: ~trnax = 0.540 h -1 r 2 = 0.9945 (It should be noted that the estimate was made considering only four points. Undoubtedly a better estimate could be done if there were more points to consider). f) Time in which biomass duplicates: This time is already calculated from Eq. 4.7, hence, 0.693 td
--
--
0.540
1.28h
4.4 KINETICS MEASUREMENT IN SOLID-STATE FERMENTATION As we have seen in the previous section, the concepts developed considering the parameters that characterize the development of a fermentation process do not have to take into account the type of the process considered. However, the way the original data need to be handled to estimate the different parameters, the corresponding mathematical expressions and the representative statistics that must be considered are strictly related with the kind of process. The principal kinetic pattern that is observed in a biochemical process is viewing the biomass synthesis during the time. In a submerged fermentation process this is normally done through measurement of biomass at a particular time by the so-called direct methods. Such methods include direct cell counting, dry biomass determination or optical density determination. However, these methods cannot be considered in a solid-state fermentation process due to the fact that biomass is partially, or completely attached, or imbedded to the solid surface. This causes difficulty in the measurement of whole biomass. Besides, the heterogeneous character of the system demands a more precisely acquirement of the samples, a fact that is not faced in submerged, or homogeneous fermentation. Considering all the above facts, several methods have been developed for biomass determination that we could divide as direct or indirect measurements. Direct
measurements are based on direct separation of biomass followed by normal standard procedures as established for submerged biomass determination (cell counting, etc.). The main problem with this method is the necessity of a whole extraction of biomass from the remained solid substrate. The employment of innocuous detergent in order to guarantee the whole extraction of the biomass from the sample was attempted. However, in the case of mycelium production, the method is not feasible due to the impossibility of a complete separation of biomass. Indirect measurements are based on the determination of a particular component of the cell, or the mycelium that is not present in the solid substrate. It includes: a) Glucosamine content determination: The method is based on the fact that glucosamine is a monomer component as acetylglucosamine of chitin. Chitin is an insoluble polymer present in the mycelium. The process consists in the depolymerisation of chitin, followed by the liberated glucosamine determination. Principal difficulties with this method are the lengthy analytical procedure, which takes about 24 hours and the sample adequacy as statistically representative. b) Ergosterol method: The method is based as the former one due to the presence of ergosterol in the biomass but presents same difficulties as glucosamine content determination. c) DNA determination: The basis of this method is the precise increase of the DNA content in the medium as the biomass develops due to the fact that DNA is a constant cellular component. The principal errors that could be made are related with sample adequacy and the possible consumption of cell DNA containing during the process. Another difficulty encountered is related with the DNA isolation and procedures with determination, which takes a long time. d) Protein determination: This may be the most intended method for direct estimation of biomass. The principal problems of this determination are how exactly protein content is determined and which part of the protein present in the substrate are not consumed, or transformed. It seems that when the solid matrix has no or high protein content, the method could work reliable. For protein estimation, it is usual to determine the N content by the Kjeldahl determination, previous precipitation of the present protein, but a more accurate procedure could be obtained by using an amino acid analyzer. As has been pointed out previously, all these methods are subject to an appropriate sampling. This is more significant at the initial stages of the process, or when
the problems with gradients are not solved. Besides, in particular processes biomass, or mycelium could be damaged by sample acquirement. This fact does not allow a response that could be taken into account to modify the process or to control it.
e) Metabolic Gas Balance Method: This method overcomes the sample adequacy, damage of biomass, or mycelium and is an on-line and fast delivery method. As a matter of fact, this method could be considered a direct measurement of the process's kinetics. 02 consumption and/or CO2 evolved during the process are linearly related with biomass synthesis in an aerobic system. But it is also an indirect method for biomass estimation. In an anaerobic process, CO2 evolved is a direct indication of biomass synthesis and associated product formation as it occurs in the alcoholic fermentation. The method considers the determination of exhaust gas (exhaust air) composition determination from the fermenter during fermentation. The procedure implies a balance for 02 and CO2 considering the airflow through the fermenter. A general scheme about volumetric composition of entrance and exhaust air in the fermenter is provided in Figure 4.3. The balance for 02 consumption considering this system is: 0 2
consumed
= 0 2
in
-
02 out
4.9
Assuming that in the reactor only pure air enters whose composition in % volumetric basis is 20.9 and 79.1 for O2 and N2, respectively. The volumetric flows for the entrance are obtained as: Vo2e "- (20.9/100) F e
4.10
VN2e -~ (79.1/100)F e
4.11
Where:
Vo2e: volumetric Oxygen flow at fermentor entrance (l/h) Vnze: volumetric Nitrogen flow at fermentor entrance (l/h) Fe " air flow at fermentor entrance (l/h) Volumetric flow at the exit for :each component of the air are estimated based on the volumetric composition of exit air and considering that this exhaust air is composed only by 02, CO2 and N2. Thus, we can postulate that: go2 s = (% O2s/100) Fs
4.12
VCO2sm~(% CO2s/100) Fs
4.13
!!!m % O2s
Fs % C02s %N2=100-%02-
%C02
% 02 = 20.9
Fe ~ N2 = 79.1
Figure 4.3. Volumetric composition of air in the flow at entrance and exit from a solid-state fermenter
VN2~= (100- % O2s - % CO2s)/100) Fs
4.14
Where: volumetric VCO2s" volumetric VN2s : volumetric Fs 9 volumetric Wo2 s
9
Oxygen flow at fermenter exit (l/h) Carbon Dioxide flow at fermenter exit (l/h) Nitrogen flow at fermenter exit (l&) airflow at fermenter exit (l/h)
The volumetric Oxygen consumed (VO2cons.) flow is obtained relating Eq. 4.9, 4.12 and 4.10 and reordering so: VO2~ons. = (20.9/100) F~ - (% O2s/100) F s
4.15
It must be noticed that air is a compressible fluid. This means that entrance and exit flow cannot be assumed to be the same because air density changes with air composition. The relation between F e and Fs is obtained considering that N2 is not consumed during the process, hence it can be stated that: gNzentra = VN2sal e
4.16
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Relating Eq. 4.11, 4.14 and 4.16, we obtain the relation between airflow at the entrance and exit of the reactor: 79.1Fe Fs =
4.17
%C02)
(1O0- ~
From Eq. 4.15 and 4.17, we obtain the volumetric oxygen consumed flow (VO2cons) considering the airflow measured at fermenter entrance as:
VOzcons = (0.209 -
0.791%02
(100- %02- %C02)
) Fe
4.18
The corresponding expression for the CO2 (WfO2evold.) evolved during the process is obtained in the same way. Assuming that there is no CO2 in the air at the entrance, the volumetric VCO2evold. is expressed as function of entrance airflow as: VCO2prod. =
0.791%CO2
Fe
(lO0-%Oz-%COa)
4.19
Molar, or gravimetric flow for respective gases in the air is calculated from the respective volumetric flows. Considering the volumetric 02 consumed and CO2 evolved and assuming that air at normal fermentation conditions can be assumed as a perfect gas, the molar or volumetric flows are readily achieved. From the ideal gas law it can be postulated that 1 mol of any component at normal conditions of temperature (273 ~ and pressure (1 atm) occupied 22.4 1. In this consideration, corrections for real temperature must be taken but for pressure can be neglected. Exercise 4.2 In a solid-state fermentation process at 30~ the entrance airflow and composition of exhausted air were measured as shown in Table 1. Represent in a graphic the gravimetric flow for oxygen consumed and carbon dioxide evolved during the process. From this data, it is very convenient to complement Table 1 as is reported in Table 2. Values reported in Table 2 for corrected entrance airflow (Fcorr.) correspond to correction made for temperature at entrance (30~ In this case, pressure correction was overlooked. Applying ideal gas law in this data and considering ideal gas constant as 0.082 atm 1/mol ~ the corrected entrance air flow (Fcorr.) is: Fcorr. = Fair(303/273) = 1.11 Fair 1/h
Table 1, Experimental data
Table 2. Results obtained from original data processing
VO2cons = (0.209-
V f O2evolv. -~
0.791%O2
(100- %02- %CO2)
0.791%CO2
(100- % 0 2 - %CO2)
Fcorr.
)Fcorr. 1 of O2/h
1 of CO2/h
moles O2/h = VO2cons./0.082 (303) moles CO2/h = VCO2prod./0.082 (303) g de O2/h = 32 VO2cons./0.082 (303) g de CO2/h = 44 VCO2cons./0.082 (303) From the data as above, the obtained graphic would be as shown in Figure 4.4:
Figure 4.4. 0 2 consumed and CO2produced 4.5 OXYGEN BALANCE DURING MICROBIAL GROWTH In every fermentative process, it is important totake into account, which part of the substrate, or energy obtained by biodegradation (redox processes) from the substrate is employed in the_endogenous process, which part is used for biomass reproduction and which part is employed in synthesizing non-constitutive metabolites of biomass. It is pointed out that the endogenous process is characterized by the synthesis of the material of each cell not considering cell duplication. The pattern of consumed oxygen during the whole fermentation in an aerobic process is an overall pattern that considers the oxygen consumption for growth and maintenance. Cell maintenance represents the endogenous metabolism and their significance implies that a balance for oxygen consumption must be done.
!!!i!!!! ,i i!, In general terms and considering a process in which only biomass and not extra-cellular metabolites are produced, it can be stated that: 02 consumed = 02 employed in + O2 employed in biomass endogenous synthesis process
4.20
The consumed oxygen can be calculated by the procedure already shown above, which considers the composition of air at the entrance and exit of the solid-state fermentation reactor and the particular flow for each component. The Oxygen Uptake Rate (OUR) in the process is defined as:
RO2cons =
AO2 ~
4.21
At
Where:
RO2 cons" 0 2 consumed at time interval Dt (g 02 employed in biomass synthesis (02
RO2 sin t
AO2 sint. -- ~
1
sint.)
O 2 / t l ).
is obtained by the expression:
AX
4.22
-"
At
Yx / o A t
Where: RO2sint. : 0 2
employed for biomass synthesis (g
O2/11 ).
Yrao
9 yield based on consumed O2 for biomass synthesis at time interval considered (g biomass/g O2)
DX
: biomass synthesized during time interval considered (g)
At
: time interval considered (h)
In Eq. 4.22, the 02 consumption rate (OUR) is related with the coefficient that defines the yield based on oxygen consumption (Yx/o). This yield can be defined through Eq. 4.8 considering 02 as the substrate in that expression. The oxygen employed for the endogenous process is estimated from the expression defined by Monod in which is employed the concept of maintenance coefficient as:
m-~ 1 X
eno
dt
4.23
Then considering in the former expression the 0 2 as substrate it can be postulated that:
RO2endog. =
mO2endogeno At
= mX
4.24
Where:
endog" O2 employed in endogenous process (g O2/h).
RO 2
m
9 maintenance coefficient (g O2/g biomas h).
X
9 biomass at a particular time (g).
Relating Eq. 4.20, 4.22 and 4.24, we get:
AO2 At
1 AX Yx / o At
+ mX
4.25
Equation 4.25 allows to estimate the quantity of biomass that exists at a particular time of the fermentation from the data of consumed 02 by finite determination of this consumption at particular time intervals From Eq. 4.25, it can asserted that:
-0
RO .... dt =
dt + mxdt -0 Yx i o -0
4.26
Term ~ R O 2 cons in Eq. 4.26 indicates that consumed 0 2 in time t=n can be evaluated from the relation between the oxygen consumption rate (OUR) and time. In Exercise 4.1,1this value is the area under the curve reported in Figure 4.1 in which it represents the OUR vs. t. A first explicit solution of Eq. 4.26 could be obtained if the function, which represents the curve reported in Figure 4.1 would be available. However, the solution of the differential Eq. 4.26 was postulated by numerical methods. Applying the Trapeze Rule to the numerical integration of the first term in the expression, we get:
;,=o dOzdtdt '="
(
-2At ( dO2)' =~
+ 2((dO2dt
(dO2)2 + ' " + - Z(dO2)n - 1)
~d02 "~
+(-;t ).)
4.27
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Where:
dO2)
--'~-.t = i "
02
consumed at the time interval i (g O2]h ).
At: time interval considered for the estimation (h). It can be postulated that considering the yield based on consumed 0 2 as constant (Yx/o = k) is obtained as:
i ;-,, y~~odX = 1 (X,-Xo) -o Yx l o
4.28
Where: X 0 : biomass at the beginning of the time interval At (g). Xn : biomass at the end of the time interval At t (g). The value of last term in Eq. 4.27 is achieved employing the same procedure already used for the determination of Eq 4.28:
S,
=o
mxdt = m
,',( 2
Xo +
+ X
+ ...X~ -1) + X~
)
4.29
It must be underlined that in the deduction of Eq. 4.29 the maintenance coefficient was considered also as constant (m = k) during the time interval. Relating Eq. 4.26, 4.27, 4.28 and 4.29 and rearranging, the following equation is attained:
=
2
at
=0+
=
i--1 'T-
--
-
-
i--1 4.30
Where to simplify the Eq. 4.30, it was considered that: a = mYx/oAt
4.31
The reader must keep in mind that the yields based on oxygen consumption as the maintenance coefficient are considered constant during the time interval evaluated. Eq. 4.30 allows to estimate the biomass value at a determined time t = tn if the preceding values of biomass are already known during the period. As it is noticeable, if previous values for biomass are unknown and the only value available is the initial biomass and OUR pattern during the whole period, corresponding biomass can be determined step by step by successive iterations.
Once the biomass values are estimated through Eq. 4.30 for the different time intervals in which OUR are measured, the specific growth rate value at the logarithmic or exponential phase can be achieved. As has been postulated before, this is one of the most important parameters to determine in any fermentation process and is not the only but the main parameter to define the kinetic of fermentation.
Exercise 4.4. Determine the 02 consumed in the process reported in Exercise 4.1. Solution: 0 2 consumed in the whole process, or in a particular time interval is obtained estimating ht and area under the surface from a figure that relates OUR vs. t as in Exercise 4.1. To solve the present exercise is better to construct the following Table.
As is observed, Dt values are constant except for interval between 20 and 24 h. In the preceding deductions, time interval was considered constant so when evaluating the area under the curve, this must be taken into account. Applying Eq. 4.27 in time interval from 0-20 h, we get: 2/2 [ 0 + 3.136 + 2( 0 + 0.064 + 0.064 + 0.064 + 0.384 + 0.8 + 0.672 + 0.832 + 1.664)] = 12.224 g de 0 2
O2consume d --
Through same equation (4.27) for time interval between 22-24 h, we obtained: O2consumed =
4/2 (3.136 + 1.664) = 12.16 g de 0 2
And, at last for time interval 24-30 h we get: O2consumed =
2/2 [2.944 + 0 + 2 (2.656 + 0.672 + 0.16)] = 9.92 g of 0 2
Total 0 2 consumed = 12.224 + 12.16 + 9.92 = 34.304 g
0 2
R.
4.6 RESPIRATION QUOTIENT AND SOME CONSIDERATIONS ABOUT KINETIC DETERMINATION IN SOLID-STATE FERMENTATION As it has been already discussed in the section 1.4, the kinetic of a solid-state fermentation can be studied considering the pattern of consumed 02 or oxygen uptake rate (OUR), achieving in an explicit manner the biomass value and pattern through Eq. 4.30. The constant term "a" in Eq. 4.30 is defined by Eq. 4.31. This determines the validity how to employ Eq. 4.30. The cases in which yield based on oxygen consumption (Yx/o), or maintenance coefficient (~t) after a particular interval are no longer constant must be checked. An element that provides an insight about the statement of constant coefficient for yield and maintenance is provided by the respiration quotient (Q), which is defined as: C 0 2produced
Q =
4.32
0 2consumed
Where: Q: respiration quotient (dimensionless) Considering the metabolic overall balance of an aerobic fermentation as sugars +
n 0 2
,,
I~
biomass +
n CO 2
4.33
where n is the number of the moles of 0 2 consumed and of C O 2 evolved during the process, is a straight forward determination that the value for the respiration quotient (Q) in such a process is 1. Take into account that the value for the respiration quotient could vary as a function of the stequiometry for other substrate. The following figure contains the values for the respiration quotient that correspond to the data from Exercise 4.1. In this, an acceptable pattern is obtained considering some values distortion due to measurement problems. In other word, there is
no evidence for another pattern, which does not stand with postulated in Eq. 4.33. The respiration quotient pattern can also indicate which kind of kinetics we are dealing with in a particular fermentation according to Gaden classification as function of microbial growth. The classification proposed by Gaden is: a) Associated growth: In this kinetic pattern, the product to achieve is obtained at the same time biomass is produced. An example of this kind of fermentation is given by those processes in which biomass, or a particular intra-cellular constituent, or a direct metabolite as result of normal growth is the principal goal. This pattern can be found in single cell protein and vitamins production. To this type of fermentation corresponds a respiration quotient constant and a value close to 1.
b) Partially associated growth: This pattern is mainly related with a process in which an extra-cellular metabolite is produced after growth in the exponential, or logarithmic phase starts. This type of fermentation represents very fairly the production of induced metabolites like in induced enzymes production. In such induced enzyme production processes, the enzyme synthesis is repressed by initial inhibitors, which in many cases are simple sugars. Substrate contains sugar and enzymes promoters. Initial sugar content allows an initial growth without enzyme production. When sugar level falls in the medium, the induced enzyme production starts to attack the so-called promoter, v. gr. a polysaccharide related with the particular enzyme to produce. In this case, it is normal to assume that after the start of induced metabolite production, the yield in the process changes and is not any more constant due to new energy requirements by the cells to synthesize the induced metabolite. Also, the maintenance coefficient is no longer constant. As a matter of fact, a fall could be expected in the yield and a augment in the maintenance coefficient values. These facts imply that:
It is necessary to estimate the values for yields and maintenance coefficient after the period a non-associated or a partially associated metabolite is produced due to variation in energy and oxygen demand for maintenance and microbial growth. The respiration quotient is no more constant after the non-associated metabolite production begins. The value of the quotient should be lower than 1 (in case substrates are polysaccharides from simple sugars units) because it would be a consumption of 02, not only related to biomass synthesis but to synthesis of a new product as well.
c) Non-associated growth: The kinetic pattern of this kind of process corresponds to a process in which a metabolite is produced under cellular stress or not normal conditions for microbial growth. Usually the metabolite synthesis initiates after the exponential growth phase is terminated or at its end. The maximum biomass can practically be achieved. In this process, it is valid also to assume that the respiration quotient has a value lower than 1 in case sugar or related molecules are the substrate. Thus, the values must be determined for particular processes and conditions. Based on this reasoning, one can postulate the following strategy when dealing with solid state fermentation 02 and CO2 pattern from these fermentations. If it is observed that in a time interval the respiration quotient is approximately 1 in case substrates are simple sugars or related substances, it is fair to assume that the yield based on oxygen consumption (Yx/o) and the maintenance coefficient (m) can be presumed to be constant in the whole time interval. If data shows a defined tendency in the sense that the respiration quotient is Q < 1, it is valid to assume a possible production of one or several non-constitutive metabolites that till then were not produced. From this period, it is indispensable to calculate new values for Yx/o Y m. When the value for the respiration quotient is bigger than 1, it must be considered, if we are dealing with an aerated fermentation, that the higher production of CO2 related to 02 corresponds to a bad functioning of aeration and the existence of anaerobic zones in the system that must be resolved at once. It must be kept in mind that all these considerations are based on simple sugar, or related carbohydrates, or polysaccharides. When dealing with other source of substrate, the particulars and the overall metabolic pathway must be taken into consideration in order to sustain a proper value for the respiration
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quotient. Undoubtedly, it is not only the consumed 02, or the CO2 evolved during a solid-state fermentation, the ones that represent the kinetic pattern. Closely associated with these is the respiratory quotient. By consideration of all these patterns one can solve Eq. 4.30 and have proper kinetic parameters.
4.7 PROCEDURES TO DETERMINE THE SPECIFIC GROWTH RATE IN SOLID-STATE FERMENTATION PROCESSES As we have seen in preceding sections, the problem to determine if it is feasible or not to consider the yield based on oxygen consumption (Yx/o) and the maintenance coefficient (It) constant in the whole time interval considered when dealing with Eq. 4.30 reduces. At the same, time it is necessary to know, or obtain the proper coefficient values for Yx/o and m. In that sense, following decisions could be considered: Take values for the coefficients Yx/o and m from former experiences. This decision is valid only when it is completely sure that there is no doubt about their values. Statistic procedures help in this assumption. However, it dose not seem very proper to assume coefficient values outside the experiment. Mainly, it may be loose information of the actual experience for which the values were assumed and their variation related to former experiences. Whatever the case be, the reader must have in mind how to deal with the assumptions and their validity. Another procedure consists in adjusting by trial and error process the parameters that coincide with values estimated by Eq. 3.30. This method implies to have the real biomass content for a particular time determined analytically and the corresponding patterns for consumed 02 and CO2. Certainly there is no need to have more than two or three values for real biomass in the fermentation. Biomass determination should be made at particular times when change in respiration quotient is expected. When it is certain that respiration quotient does not vary, only two determination must be made, that is at the beginning and the end of the fermentation, and then proceed to the trial and error estimation comparing values of biomass determined at chosen points and the ones predicted by equation 4.30. No need to mention that after the parameters Yx/o and rn estimated, biomass value for any point or at any time of the fermentation is already there. Obviously, this procedure could be burden and require for computer calculation but undoubtedly it is more proper than the former procedure of considering values outside the system. It is interesting to note that doing all these considerations, there has not been any need to distinguish if the fermentation is submerged, or solid and even
more the analysis made considering the 0 2 balance can be made with substrate balance. The only statement is that for solid-state fermentation the above procedure seems to be very proper in order to have on-line information about process kinetic and how is the process developing.
Exercise 4.6 The pattern for 02 consumption in a solid-state fermentation is reported in the two first column of the table reported in this problem. It was determined analytically that initial biomass was 0.2 g and at the end of the process 18.6 g. Determine the biomass kinetic pattern and show in a graphic form and calculate the maximum specific growth rate. To estimate the biomass synthesized in each time interval, we applied the Eq. 4.30. To do so, it is necessary to know, or estimate the values for Yrao and m. From Eq. 4.29, the consumed oxygen (O2cons.) will be: O2cons. -" 2 2(0+0.0027+2(0+0.0488+0.0461+0.0693+0.3418+0.7335+0.6163+
0.7553+1.4881+2.8140+2.6584+2.3798+0.6031+0.1410)) = 0.0027 + 2(12.6955) = 25.3937 g of 02 A first estimate could be done considering that the maintenance coefficient was negligible and therefore the consumed oxygen was used in biomass synthesis. From above considerations we can assume and calculate that: m = 0.0001 g O2/g biomass h Yx/o =
18.6-0.2 25.3938
(assumed).
= 0.725 g biomass/g 02 cons.
With these values the constant (a) of Eq. 4.31 is determined as" a = (0.0001)(0.725)(2)
= 0.000145
Calculation of X2: X2 = (1.45 (0.5 (0 + 0) + 0) + 0.2 - 0.000145 (0.2)) / 1.00007246 = 0.2
Calculation of X41 X4 = (1.45 (0.5 (0 + 0.0488) + 0) + 0.2 - 0.000145 (0.4)) / 1.00007246 = 0.2353 and so on successively As observed, an estimate for biomass at 30 h gave a value of 18.586. Comparing this result with the biomass content determined analytically, it could be well concluded that the initial assumptions seemed valid. The kinetic pattern of biomass synthesis is obtained plotting In Xn vs t as is showen in the figure as below:
The maximum specific growth rate corresponds to the specific growth rate in the exponential, or logarithmic phase. This value is estimated from the slope of the line observed in the figure through lineal regression. From figure it can be assumed that the exponential phase began at hour 4 and lasted till 26 hours. This was the time interval for estimating the specific growth rate and results give a kt = 0. 217 h -1 with a regression coefficient r = 0.9922.
References Aiba S, Humphrey AE & Millis N, 1973, Biochemical Engineering. Academic Press. New York. Brand D, Pandey h~ Leon JR, Brand I & Soccol CR, 2002 Relationship beteween coffee husk caffeine degradation and respiration of aspergillus sp. in solid-state fermentation. Applied Biochemistry and Biotechnology, 102, 169-178. Carvalho JC, Oishi BO, Brand D, Rodriguez-Leon JA, Pandey A & Soccoi, CR, 2006, Relation between growth, respirometric analysis and biopigments production from monascus by solid substrate fermentation. Biochemical Engineering Journal, 29 (3), 262-269. Leveau JY and Bouix M, Cinftiques microbiennes. In Biotechnologie, 4th edition. R. Schneider coordenateur. Tec Doc. Paris. Matchman SE, Jordan BR and Wood DA, Estimation of fungal biomass by!three different methods. Applied Microbial Biotechnology, 21, 108. 1985. Okasaki N, Sugama S and y Tanaka T, Mathematical model of surface Culture of koji mold. Journal of Fermentation Technology, 58, (5), 471. 1980. Rodriguez Leon JA, Echevarrfa J, Sierra N, Daniel A & Martfnez O, 1985, Solid-state fermentation of dried citrus peel. Biotechnology Letters, 7 (8), 577-580. Rodriguez Leon JA, Bechstedt W, Echevarria J, Sierra N, Delgado G, Daniel A & Martfnez O, 1986, Optimization of solid state fermentation of citrus dried peel by Aspergillus niger in a packed bed column. Acta Biotechnologica, 6 (3), 253-258. Rodriguez Leon JA, Sastre L, Echevarria J, Delgado G & Bechstedt W, 1988, A mathematical approach for the estimation of biomass production rate in solid state fermentation. Acta Biotechnologica, 8 (4), 299-302. Rodriguez-Leon JA, Torres JA, Echevarria J & Saura G, 1991, Energy balance in solid state fermentation processes. Acta Biotechnologica, 11, 9-14. Rodriguez-Leon JA, Domenech F, Leon M, Mendez DE & Pandey A, 1999, Production of spores of Trichoderma harzianum on sugar cane molasses and bagasse pith in solid state fermentation. Brazilian Archives of Biology and Technology, 41, (1), 69-76. Rodriguez-Leon JA, Bueno Gloria, Rodriguez DE & Delgado Grizei, True and apparent yields and maintenance coefficient and their significance on fermentation kinetics. New Horizons in Biotechnology, Editorial Kluver, 1,201-212, 2003. Sato K, Nagatani M, Nakamura K & Sato S, 1983, Growth estimation of Candida lipolitica from oxygen uptake in solid state culture with forced aeration. Journal of Fermentation Technology, 61 (6), 623-629.
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5.1 INTRODUCTION For the majority of filamentous fungal species, solid-state media are the natural life media. Growth can occur on the surface, or within the whole substrate, depending on the porosity. Industrial solid-state fermentations have been developed largely in traditional food industries such as cheese, Oriental fermentations, fermented vegetables, meat, and other products, and in biotechnological industries such as antibiotics and enzymes. The use of water-insoluble materials in microbial metabolism has been characterized in solid-state fermentation (Moo-Young et al., 1983). Since substrate utilization could also occur in a suspension, the definition of solid-state fermentation requires the absence, or near absence of solution in the interparticule volume (Hesseltine 1972; Lonsane et al., 1985). Such an absence has been related to the water holding capacity (WHC) of the support which could reach up to 10 g water/g of dry matter in the case of cellulose fibers (Grigelmo-Miguel & Martin-Belloso 1999). The empty or void space must then be mainly occupied by a gaseous phase (Durand et al., 1983). It is well recognized that the growth and metabolism of microorganisms always or almost always occur in the liquid phase. Solute as well as dissolved gas transfers take place in the aqueous film surrounding the microorganisms. So, even in solid-state fermentations, the microorganisms are in a liquid medium. Solute diffusion in the substrate must occur in the liquid phase, and gaseous diffusion in the substrate can occur in the liquid as well as in the gaseous phase. Thus, the replacement of the water phase by the gaseous phase increases oxygen transfer but prevents solute diffusion in most of the substrates (Gervais & Bensoussan 1994). Mostly, the three phases (gas, solid, and liquid) are
present in the liquid as well as in the solid media, but not in the same proportions, and so kinetic, diffusional, rheological, and thermodynamic (aw, osmotic pressure) properties are modified. It is difficult to give an exact definition of solid-state fermentations based on the proportion of each phase because the biophysical properties of the mixture depend on the nature of the liquid and solid components. Solid-state fermentations are generally characterized by a reduced liquid phase, (approximately the water-holding capacity of the substrate in the case of the water-liquid phase, i.e. no presence of free water) (Pandey, 2003) and present a high viscosity. Thus, mixing such media leads to great shear forces that drastically injure the microbial cells. Solid-state media could then be defined by high viscosity and no continuous possibility of mixing and could also be considered as heterogeneous media in terms of microbial population and solute concentration. Indeed, the gradients of water and solutes cannot be prevented in SSF as shown by works of Nagel et al., (2002). The major difference between liquid fermentations and solid-state fermentations reside in the mixing ability. Liquid fermentations are generally perfectly mixed reactions, and so each part of the reactor contains at any time the same quantity of microorganisms, nutrients, and metabolites. Perfect mixing of liquid fermentations prevents the formation of large boundary layers around the microorganisms. Such layers drastically limit the diffusion phenomena of nutrients and metabolites and prevent the removal of the heat of the fermentation process, which could represent quite high values, about 500 W/m 3 in moist solid substrate (Oostra et al., 2000) and so limit the metabolism of the microorganisms. In solid-state fermentations, four alternatives could be used in order to improve the homogeneity of the cell population and corresponding substrate concentration: -
Efficient mixing during, or just after the inoculation. Sequential mixing.
--
The use of mobile microorganisms, most often filamentous fungi; the forward growth of such microorganisms allows the occupation of new substrate with high levels of nutritive components (if solutes diffusion rate is limited and smaller than growth rate).
--
Forced aeration through the solid substrate, which allows the control of water content and therefore water activity; the removal of volatile compounds and CO 2 together with heat produced during the fermentation; and supply of 0 2 for aerobic metabolism.
Growth of filamentous fungi has been shown to be dependent on physicochemical parameters such as thermodynamics (aw, temperature) (Scott 1957; Gervais et al., 1988d) and chemicals (glucose, 02 and CO2, nutrient concentrations)
(Trinci & Collinge 1973; Trinci 1969). Numerous workers have shown the evidence of such dependence but there are many results that are sometimes difficult to synthesize. This chapter intends to identify and model the influence of the conditions of the medium hydration on the microbial development. First, some physical parameters, relating to the water state of the medium and implicated in the variations of metabolism, will be examined for solid-state media. Then, the mechanisms of the action of water at the cellular level will be discussed, particularly in the light of the works of our laboratory. The roles of water in biological systems are numerous and the mechanisms of action and interaction of this molecule with organic molecules are not totally elucidated. Two fundamental functions can be distinguished (Gervais et al., 1996): a solvent function on the level of the organism as well as of the cell, provides nutrients and scavenges wastes, or metabolites, under the dissolved form. a structural function which is implicated in the stability and the function of the biological structures organized at the molecular and cellular levels. At the molecular level, the role of water in the stabilisation of the structure of the biopolymers, such as proteins, nucleotides and carbohydrates, was recognized aboutthirty years ago (Schwan 1965; Kuntz 1971). At cellular level, the role of water molecules in the stabilisation of the lamellar structure of the plasma membranes and thus in the preservation of membrane permeability has been shown (Crowe et al., 1982; Wolfe & Steponkus 1983; Quinn 1985). In the intracellular medium, the molecules of water linked with other molecules, such as polyols, sugars or enzymes, contribute to the maintenance of the cellular volume, especially when the cell is placed in a hypertonic medium and particularly during desiccation or freezing conditions (Mazur et al., 1981). From these different functions, we can understand why water is essential to fungal metabolism in solid state fermentation: *If the quantity of the water becomes insufficient and does not allow a good diffusion of solutes and gas, the cell metabolism slows, or can stop, because of a lack of substrates or through too high concentration of inhibitive metabolites in or near the cell. *If the intracellular or extracellular quantity of water does not allow the maintenance of the functional properties of some enzymes (Todd 1972), their inactivity creates disequilibrium in the metabolic chain of the cells. *In the same way, if the transfer of water induced by water stress leads to a denaturation of the mechanical structure of the plasmic membrane, all the properties of permeability and transport through the membrane are affected
and the cell is then perturbed (Wolfe & Steponkus 1983; DeLoecker et al., 1978).
5.2. WATER CHARACTERISATION OF A SOLID-STATE MEDIUM In a heterogeneous system such as a solid-state medium, numerous parameters can describe the state of water. Two types of parameters can be distinguished:
Thermodynamic parameters, relative to steady state systems describe the energy state of water, the mainspring of water transfer between two systems such as cells and substrates. Evolution of biological systems is very low compared with that of physical systems, so such systems can be frequently considered at steady state.
Dynamic or kinetic parameters define the resistance of the medium to the water transfer. Solute diffusion as well as cellular absorption occurs in aqueous medium. The diffusional properties of water interact on these transfers, and the dynamic properties of water molecules are modified when they are near other molecules. The diffusion laws are deduced from the atomic theory of Brownian movement established by Einstein. The relation between the flow and the concentration gradient is given by Fick's law and the coefficient of proportionality is called diffusion coefficient or diffusivity; its value is closely dependent on water concentration in the medium. In fact, thermodynamic parameters and kinetic parameters, although fundamentally different, are always related to the water content of the medium and therefore dependent. Nevertheless, this degree of dependence is extremely variable and the limiting factors for the transfer of water in a system can have a kinetic or thermodynamic origin.
5.2.1 Thermodynamic parameters The parameters generally used to characterize the thermodynamic state of water in a system may be defined from the two fundamental laws of thermodynamics.
5.2.1.1 Chemical water potential The chemical water potential of a system is equivalent to the partial free energy of water:
-G-w
5.1
...........
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where T is temperature, P is pressure, w is the water suffix, n is the number of moles, j is the solute suffix, G is free energy, G w is the partial molar free energy of water, and ~tw is the water chemical potential in the solution. The potential difference can be estimated in relation to a standard reference state. For a solution:
l.tw _po
_ ~-w( p _ jr )
5.2
with
7r-RT(CM+A2C2+A3C3+...)
5.3
For a porous solid: //w _ / t o _ ~-w( p _ , t . )
5.4
hpg
5.5
with ~ r -
For a heterogeneoussystem: as a solid
state medium (solutes and porous solids)"
/2 w - / 2 ~ - Vw ( P - / r - ' t ' )
5.6
where pw~ is the chemical potential of pure water, r~ is the osmotic pressure, C is the solute concentration, M is the solute molar weight, Ai is the ith viriel osmotic coefficient, R is the perfect gas constant, volume, x is the suction pressure.
Vw
is the water molar
5.2.1.2 Water potential of a system The water potential (W) of a system is defined by:
~ Vw
(Pa)
5.7
The water potential W can be written as the sum of terms of different origins: kI/ - kI/p "1- kIJ s -I" kI'/m
5.8
where Wp = P, water potential pressure (hydrostatic pressure), Ws = -r~, osmotic
iiii
i iiii
water potential (solute effect: osmotic pressure), and (solid matrix effect: adsorption, capillarity).
!iii kI; m
=-re, matrix potential
Other parameters such as temperature or gravity can affect the water energy state of a system. Nevertheless, in biological systems, most of the time, only two components W= and ~I'tm c a n describe the systems. The distinction between 9 = and ltlJm is especially valid at the macroscopic level; at the molecular level, the same physicochemical phenomena such as adsorption and size effects are implicated.
5.2.1.3 Water activity The water activity concept is used to describe the equilibrium between a heterogeneous system and the surrounding water vapour phase (considered as a perfect gas.). The water activity of a solution is given by:
aw
- p ew o --
5.9
~'w " X w
w
where Pw is the partial pressure of water vapor equilibrated with the solution, Pw ~ is the pressure of water vapor above pure water in the same conditions, Xw is the water molecular fraction, and aw is the water activity coefficient (dependent on the concentration). Guggenheim (1967) demonstrated the relation between the chemical potential and water activity" l.tw - l.t ~ - R T l n a
w
5.10
and so, according to equation 5.6: RTlna
w
V-w
5.11
5.2.1.4 Thermodynamic properties of water: Molecular basis Case o f s o l u t i o n s
The thermodynamic water properties of a solution are related to three types of molecular interactions: solute-solute, solute-solvent and solvent-solvent. The hydration phenomenon corresponds to water-solute interactions and can be studied alone at solute concentrations corresponding to an infinite dilution, where the solute-solute interactions therefore become negligible. For electrolyte solutions,
this dilution threshold can be estimated using the Debye-Htickel's law; for nonelectrolytes, an objective method to estimate this threshold does not yet exist. The thermodynamic reference for the hydration term is composed by the ideal solution which presents no solute-water interaction. For this ideal solution, the aw value is exactly equal to the water molar fraction (aw = Xw), i.e. the water activity coefficient )'w is equal to 1. From this model, some deviations are observed which can be attributed to three types of phenomena: ~
Solute molecular size vs. solvent molecular size. Flory (1953), using the theory of the "liquid network", showed that the binary solution entropy and consequently its eventual deviation from an ideal solution depends on the respective size of the solvent and solute molecules.
2.
Solute molecule hydration or solvation.
3.
Other molecular interactions (solute-solute).
Case of Insoluble Substances The previous types of interactions can occur depending on the chemical nature of the polymers, hydrophilic or hydrophobic. But, in addition, the energy state of water is closely dependent on the thermodynamic level of the geometry of the medium and especially on the dimensions of the pores. Fisher & Israelachvili (1979) showed that the thermodynamic properties of liquids trapped in microscopic pores can be described by Kelvin's equation, the basis of the nucleation theory, for pore sizes as small as a few nanometres. The Kelvin equation can be written as:
lnPw=po
PwRT Mw [-a--~--(Pw-P~
5.12
where rm is the radius of the curve of the water meniscus in the pore, t~ is the surface tension at temperature T, and Pw is the water volumetric weight.
Pw - pO is negligible for RTln a w
ty
Mw
Pwrm
t7 rm
-~,
so:
5.13
5.14
and then RTlna
w
a
=
Vw
rm
=W
5.15
In this case, the energy state of water is dependent only on the curve radius of the meniscus and then on the particles or pore sizes of the material. The porosity of a heterogeneous system, such as a solid substrate, is modified during drying or hydration (bulking), as the curve radius of water meniscus decreases. Nevertheless, for definite water content the matrix water potential provides an estimation of liquid-gas and solid-liquid interactions, generated by very thin pore size (capillarity), which can characterize biological structures such as membranes or macromolecules.
5.2.2. Dynamic parameters These parameters allow the characterization of the water resistance to transfer in a medium. The parameters that are used are the coefficients of the rotational and translational diffusion of water. These coefficients are related to the friction coefficient by Einstein's equation: kT D
~
m ~
5.16
where D is the diffusion coefficient of a particle in a liquid, ~ is the friction coefficient, k is Boltzmann's constant, T is the temperature. The hydrodynamic model allows the calculation of ~ in the case of large molecules with a radius a, for the translational diffusion { = 6 rtarl (11= liquid viscosity) and for the rotational diffusion { = 8rca3rl . Water content is a parameter that represents the diffusional properties of a slightly hydrated medium. In fact, in the case of the study of the rotational diffusivity of the solute molecules (Le Meste & Voilley, 1988), as in the case of the translational diffusivity of water molecules (Simatos & Karel 1988), the relation proposed between diffusivity and water content is established for definite scales of water content. The thermodynamic and kinetic parameters of a medium are linked by the water content. Nevertheless, this link, represented by the sorption isotherm of the medium, can be formalized by equations only for simple model systems. In most cases, this link can only be established experimentally. Previous studies (Bruin & Luyben 1980) have confmned that the water diffusivity in polymer solutions is essentially dependent on the water content of the solutions.
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Le Meste & Voilley (1988) even showed an antagonism between the kinetic and thermodynamic parameters. A unique factor representing both the energy state of water and its solvent properties in a heterogeneous system does not exist. Nevertheless, it seems possible to draw general conclusions. For dilute solutions, the solute diffusion is not a limiting factor, and the solute nature has only a small influence. If the solvent and the solute molecules are of compatible sizes, there is little deviation from Raoult's law. In this case, thermodynamic factors allow the prediction of the water transfer in the system. For more concentrated solutions, homogeneous or heterogeneous, as found in solid-state media, the previous hypotheses are no longer true; the diffusion phenomena can become limiting according to the sorption properties of the solutes or solids. The physicochemical nature of the molecules can then interfere. For certain enzymatic activities, which can be developed over almost the total scale of water content (5-100% wt./wt.) (Bouanda 1983) or of the water activity (Goldberg et al., 1988), the previous considerations are particularly important to the understanding of the systems. For microbial activity there may be a hierarchy in the action of kinetic or thermodynamic parameters on the cellular physiology. In submerged cultivations, limitation would essentially be of a thermodynamic origin, but in solid state cultivation, limitation should be thermodynamic as well as dynamic in origin.
5.2.3 Water sensors For many years, several authors reviewed the principles and engineering aspects of SSF (Bellon-Morel et a1.,2003; Raghavarao et al, 2003). Because of the heterogeneity and complexity of the media and the variety of reactors, monitoring and controlling environmental factors like water activity pose problems in SSE As described below, water acts in numerous reactions: biomass development, metabolic reactions, enzyme activities, transport of nutrient, extra-cellular metabolite and gas. Water content is considered optimum when reaching the Water Holding Capacity (WHC) of the substrate (Durand et al, 1993), which varies between 30 and 85% (w/w) depending on the substrate. As water content is evolving during the fermentation (evaporation due to metabolic heat and substrate hydrolysis or metabolic water production) such variation must be taken in account in order to prevent any productivity decrease.
As water content "off-line" sensors process by dry weight measurement, KarlFisher titration or Proximity Equilibration Cell Method (Xavier & Karanth, 1992), they are difficult to integrate into control schemes due to the typically long
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delays in samples analysis; so recent works tend to optimize "on-line" rapid measurements to study water dynamics during SSF. In this way, various tomographic techniques, adapted from soil and food areas, like microwaves (Narayanan & Vu 2000), Magnetic Resonance Imaging (Maniette et al., 1999), X-rays and y-rays (Mohsenin 1984) are studied. Interest of "on-line" measurement of water activity during SSF was developed by several authors (Durand & Chdreau 1988; Barstow et al., 1988; Ramesh et al., 1990; De Reu et al., 1993; Ghildyal et al., 1994). The most common on-line system to measure water activity is the capacitive sensor, designed to regulate the circulating air humidity was improved by Gervais (1989) by separating the capacitive element from the medium by a thin ethylenepolytetrafluoride membrane which allows on-line and accurate measurements of water activity. Other sensors which are based on changes in electrical behaviour of an e l e m e n t - usually resistance- after water adsorption are described (Labuza et al., 1976). As these sensors have slow response times, an other approach is based on the modification of the optical absorbance of a mirror where dew condenses, resulting from the the atmosphere in equilibrium with sample (Bramorski et al., 1998; Aunia et al., 1995; Engel 1995).
5.3 WATER PROPERTIES RELATED TO FUNGAL DEVELOPMENT AND PHYSIOLOGY The introduction of the water activity concept (and then of the water potential) in microbiology dates from 1953 (Scott 1953). This parameter has been and still is widely used as a predictive criterion of the physiological functions of microorganisms and thus, of food preservation (although physicochemical factors like non-enzymatic oxidations also intervene). Ben-Amotz & Avron (1978) have used the influence of water activity or osmotic pressure to increase the glycerol production by unicellular algae. It is thus a statement to show the water activity (aw) effects on the physiology of microorganisms. Nevertheless, if there are numerous observations, the explanation is different. In recent years, the systematic utilization of this parameter has been debated by specialists to qualify the water situation of a medium (Franks 1995). For these authors, the thermodynamic considerations are insufficient to explain the water effect in a medium. Kinetic parameters should also be included. The respective influence of kinetic and thermodynamic parameters in fermentation media should be investigated.
5.3.1. Influence of water thermodynamic parameters 5.3.1.1 Cellular mechanisms It is recognized that there is no active water transport in cells and that water moves freely according to the gradient of the water potential. Thermodynamic
models relating the energy equilibrium of the intra- and extracellular media have been developed by many authors (Griffin 1981; Steudle et al., 1983). At equilibrium, the water potential of the protoplasm wP is equal to the water potential of the medium WE: W e = wP
5.17
The variation scale of ~Fe according to WE is dependent on the species. For xerotolerant species, WP can decrease to -40 MPa without damaging the cells. The protoplasmic water potential we can be restated in terms of its constituent elements as follows: LI/P
P
P
P
--lkI/p -+-kI-/s -.~-kI-/m
5.18
where ~P = P - n -x, with P the hydrostatic pressure, n the osmotic pressure, P P and1: the suction pressure. ~ p and ~ p are the water osmotic and matrix potentials P of the protoplasm, and ~p the turgor potential of the protoplasm created by the plasmic membrane and the cellular walls. This latter potential corresponds to the pressure permitting the initiation of cellular plasmolysis. For most P filamentous fungi, ~ p = - 1 MPa, a value that can rise t o - 3 MPa for xerotolerant species.
5.3.1.2 Fungal growth Growth of microorganisms is very sensitive to environmental parameters such as temperature (Suutari et al., 1990), water potential or water activity (Scott 1957). In the cell, there is no active water transport and water moves according to the water potential gradient between the intra- and extracellular medium. In heterogeneous media, water potential or water activity is related to the solute concentration, capillary forces and absorption properties of the insoluble solid substrate. Numerous workers have demonstrated the sensitivity of hyphal extension (Robertson & Rivzi 1968; Wilson & Griffin 1979; Robertson 1958) fungal spores germination and aroma production (Gervais et al., 1988b; Gervais et al., 1988c) to water stress. A variety of experiments have shown that a turgor pressure exists in hyphal tips (Money 1997). First of all, a theoretical approach (Gervais et al., 1999) could explicit the great importance of turgor pressure on the fungal growth.
5.3.1.2.1 Turgor pressure as a driving force" theoretical approach .'. Equilibrium state and cell wall tension: Cell turgor pressure is defined as the hydrostatic pressure due to the difference between the intracellular and extracellular osmotic pressures at a steady state characterized by a steady cell volume. Turgor pressure exists in all types of cells: microorganism, plant and animal cells. In all theses cases, cell turgor pressure corresponds to an overpressure which allows the cell morphology, elongation, division and hence the increase in biomass:
Pt = I-Ii -lie with Pt the turgor pressure, osmotic pressure.
5.19 11 i
the intracellular osmotic pressure,
II e
the external
The turgor pressure value is balanced by the cell wall resistance of the organisms (Pr), the higher the wall resistance the higher is the turgor pressure (Trinci 1978). This can be explained as follows: since the cell wall must be in equilibrium, it has to be under tension so that each surface element can balance the intra and extracellular osmotic pressures. This translates mechanically into a compensating pressure, given by the ratio of a surface tension over a curvature radius that is exactly as in the case of a soap bubble. It follows that for a given organism: et = er
5.20
where Pr will be a constant value unless wall geometry or properties are modified. The growth of individual cells is discontinuous and can be separated into two phases: a slow evolution phase and a rapid division phase corresponding to mitosis or budding. The turgor pressure was found to be constant for a cell at a specific physiological stage and the budding phenomena in yeasts was found to be related to a specific and localized hydrolysis of the cell wall which induces an important decrease in wall resistance and leads to a volumetric expansion of the cell wall through a passive flux of water into the cell.
.'. Non equilibrium state: fungal cell growth: For fungal species, it is largely admitted that the growth occurs continuously at the apex of numerous hyphae of a colony and at constant growth rate under fixed conditions of the medium (i.e. pH, temperature and water activity) through the continuous deformation induced by a constant overpressure exerted on the renewed thin membrane of the apex (Scott 1957; Gervais et al., 1988d), and the maintenance of the turgor pressure could not be sufficient to explain
the growth phenomena (Zhu & Boyer; Kaminky et al., 1992; Money & Harold 1993). Nevertheless, Trinci (1974) has observed oscillations of the mycelium growth rate just after spore germination. During hyphal elongation, synthesis of cell materials such as cytoplasmic organelles or membrane components must continuously occur in order to keep the cell wall constant in mechanical resistance in spite of the continuous deformation induced by the turgor pressure (Bartnicki-Garcia 1973). The most numerous components in the apical zone are the apical vesicles that originate in the Spitzenk6rper (or Vesicle Supply Centre): a central and dense component of the apex consisting of accumulated vesicles and presumably anchored to the apex walls (Howard 1981). Hence, cell growth is the result of a dynamic balance between the maintenance of an intracellular turgor pressure via solute synthesis and water input, and a synthesis of macromolecules which causes the membrane to provide a constant resistance despite elongation phenomenon (Wessels 1993). We give further details below. In the case of continuously growing cells such as filamentous fungal tips, the steady state conditions mentioned in the preceding section (see equation 20) can no longer be applied. So the evaluation of intracellular turgor pressure must take into account the type of system under consideration: it will be different between non-extending cells (such as bacteria, yeasts, or plant cells) for which both cell volume V and intracellular osmotic pressure ~i could be considered as constant, and extending non equilibrium cells such as fungi. In order to study more precisely the case of fungi, let us consider the example of fungal hyphae growth during a time interval dr. During this interval, dn~ moles of a solute j are synthesized or incorporated in the internal medium which induces a dI-I i increase in osmotic pressure, a s l-I i could be considered for diluted media as equal to:
Hi = RT 2_~Cj
5.21
j=l
with R = ideal gas constant; Cj = molar concentration of intracellular solute j; and T = temperature. Such an osmotic pressure increase, added to a continuous apex wall elongation (through vesicle incorporation), will simultaneously provoke a thermodynamic water flow into the cell which will decrease the Cj concentration and so will simultaneously reduce the osmotic pressure level of-dl-Ii as shown in the previous sentence. All these previous phenomena occur simultaneously, which leads to a continuous hyphal extension. Cell growth could then be attributed to a constant increase in the osmolytes concentration near the apical part which is continuously balanced through a water flow input therein. So in the case of filamentous fungi, growth regarded as volume variation (essentially due to water
input) should occur under a constant intracellular osmotic pressure (Hi). The increase in the cell volume is in turn limited by the cell wall's mechanical properties, which were previously discussed in this section. Assuming that the tension developed by the cell wall is constant in the apical part during hyphal growth (i.e. the continuously synthesized wall exhibits steady mechanical properties), it could be possible to calculate the cell pressure balance for extending fungi. In this case the sum of the exerted pressures is no longer equal to zero (as previously shown for non-continuously extending cells in equation 20) but equal to a pressure loss value (AP) which is the origin of the continuous apical extension, (that is, water inflow to the cell). At a time t, it could be written: (I'Ii-lie)
or
- Pr = ~
Pt -- Pr
= z~~
5.22
This very simple equation allows us to describe fungal growth; thus turgor pressure in extending cells is no longer counterbalanced only by the membrane pressure resistance (Pr) but also by the apical deformation (due to AP). Previous works (Money & Harold 1993; Lockhart 1965) have not considered the parameter AP in the turgor pressure evaluation or measurement in continuously extending cells. Now it is possible to relate the volume variation dV during the time dt to this constant pressure loss AP over time (as Hi, lie and Pr are constant) and to physical characteristics of the fungal apex through the application of an equation (Kedem & Katchalsky 1958) describing laminar water flow driven by pressure gradients between intra and extracellular media: 1 dV A dt = LpAP
or
dV ~dt -
5.23
ALpAP
with A = exchange surface where the water flow takes place (m2),
dV dt
m
water flow between intra and extracellular media (m3.sq), Lp = hydraulic permeability of the apex wall (m.s-l.pa-1), = ( I I i - I ' I e ) - Pr (Pa). Integration of previous equation 5.23 yields: V = (ALpz~)t + Vo
5.24
In obtaining (5.24) it is assumed that the surface A is constant versus time. Indeed the parameter A is relative to the surface of the apex where the water flow takes place, i.e. where the pressure gradient occurs. This apex wall surface corresponds to the cell's active volume which can be defined as the hyphal apex volume which is osmotically balanced or equilibrated through both continuous
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incorporation or synthesis of solutes and water input. Indeed it was shown by 14C glucose labelling (Trinci 1971; F~vre 1979; F~vre & Rougier 1982) that glucose incorporation was about ten times higher at the apex than in the subapical zone of Saprolegnia monorca. Such a local increase in solute incorporation (mainly sugars and ions) would immediately trigger a fast water input to the fungus, this is known to be many times faster than solute diffusion towards the rear of the apex (Mauro 1957). This confirms the view that the rate of hyphal growth will be only controlled by the water input in the apical part, as equation (5.24) estimates. With these assumptions, the fungal growth expansion is represented by equation 5.24. As the hyphal growth rate is unidirectional (x axis), the volume variation dV during the time dt could be written dV = dx. S and where dx is the axial hyphal extension and S is the section of the hyphal tube. Consequently, equation 5.23 becomes:
dx dt
--=
ALp zSaP S
or
Ap=
S dx Lpta--7-'d ----;
5.25
dx These equations imply that the hyphal growth rate ~ is constant for defined medium conditions (A, Lp, AP,, S are constant), a well known fact since Scott (1957). The expression of the turgor pressure could be easily obtained from the previous equation 5.25. Substituting AP by its value (Pt" Pr) given by equation 5.22 in equation 5.25 gives:
Pt --Pr +K --~
s with K=A---~p
5.26
Comparison of this equation with equation (20) allows us to conclude that in the case of growing tips the turgor pressure, considered as a potential pressure, is greater than the equilibrium value Pt " Pr (case of non-extending cells). Equation 5.26 trivially reduces to 5.20 when cell extension stops. This difference between non extending cells and growing tips is easily understandable, because in the case of continuous hyphal elongation, the part IK-~t j of the turgor pressure continuously drives the volume expansion and so cannot be measured just through the membrane pressure resistance Pr.
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Turgor pressure as a driving force" experimental approach An experimental approach of this theory has been proposed in a previous work (Gervais et al., 1999) where the hyphal growth rate of A. orizae has been shown to be related to the pressure AP as proposed in equation 5.25 (see Table 1). The measured AP part of the turgor pressure is plotted in Fig. 1 against hyphal extension rate. It can be seen that the higher the AP, the higher the apical rate. The variability of the AP measurements has not clearly allowed showing a linear relation between the two parameters as expected from equation 5.25. Nevertheless, the relationship between the two parameters is clearly an increasing function. Further experiments will allow us to explore this relation. Table 1: Evaluation of AP values for Aspergillus orizae cultivated at different levels of water potential.
*Values into brackets represent confidence intervals at 95%.
Figure 1: Representation of the hyphal extension rate as a function of the pressure •P.
The theory developed here allowed us to better understand the role of turgor pressure in fungi and mobile microorganisms. For such organisms a main part of the turgor pressure (AP) was shown to be continuously used for cell volume expansion.
5.3.1.3 Radial growth rate and hyphal orientation An increase in the osmotic pressure (or decrease in the water activity for a heterogeneous medium) of the extracellular medium leads to a two-phases cell response (Zimmermann 1978): (1) A very fast but passive exit of cell water, for a few seconds, with a corresponding decrease in cell volume for protoplasts or decrease in turgor pressure for cells with walls. For such cells, the variation of the turgor potential is related to cellular volume modifications through the elastic properties of the cellular walls, defined by the elastic volumetric coefficient ~ according to the equation: AV AP = e - V
5.27
This coefficient is related to turgor pressure and cellular volume; it can vary from 5 bars to 600 bars according to species and pressure conditions. This first phase, can lead, in the case of large gradients of osmotic pressure, to either an exit of most of the free water from the cell, and thus to a metabolically inert cell that can survive over long periods, or to cellular death essentially due to the alteration of membrane properties (Cudd & Steponkus 1987; Gervais et al., 1996b). (2) A second compensation phase during which the cell allows the input of permeable solutes or the biosynthesis of intracellular metabolites. This accumulation in response to a hydric stress has been identified in microorganisms, plant and animal cells (Gilles 1975; Hellebust 1976; Luard 1982) and allows the cell to recover its initial volume and to grow again at lower aw value (depending on the fungal strain, generally above 0.90). For a given aw value the turgor pressure maintenance or more specifically the AP value has been shown (see previous section) to be the driving force of the fungal growth rate. Numerous experiments have demonstrated the influence of the water activity of the culture medium on the survival, growth, and metabolism of microorganisms cultivated on different types of medium (Mossel 1975; Troller 1980; Richard-Molard et al., 1982; Jackobsen 1985). In all cases, optimum growth and metabolic production occurred at media aw values of less than 1.
Macroscopic considerations Numerous authors (Gervais et al., 1988d; Bull & Trinci 1977; Raimbault 1981) have described the macroscopic development of a fungal colony. From a point inoculum, the growth is isotropic and then circular. After a lag phase due to the germination of the spores and after a short exponential phase, colony radial
extension rate reaches a constant value (Scott 1957; Grajek & Gervais 1987a). Water activity of the medium, which is a thermodynamic parameter, was found to have an effect on radial growth and biomass production (Gervais et al., 1988d; Raimbault 1981; Trinci & Bandury 1967) . There is an optimal water activity value for radial extension rate which depends on the fungal species. Nevertheless Inch & Trinci (1987) pointed out that colony radial growth did not always provide a relevant variable for estimating the effect of environmental factors on mould growth. Previous results about fungal radial extension rate as a function of the water activity of the medium (Gervais et al., 1988b) have confirmed that the colony diameter was linearly time-dependent (Trinci 1969). For each water activity, a mean extension rate could be approached using the slope of the corresponding radial growth. The radial extension rate values were then related to the water activity value as shown in Fig. 2. The shape of the curves obtained was characteristic of the answer of a microorganism growth to a variation of water potential as proposed previously (Scott, 1957; Griffin 1981). The optimum growth always occurred in a medium in which the water activity was clearly less than 1, corresponding to a water osmotic potential scale between -0.1 MPa and -10 MPa. From Fig. 2, the optimal water activity value for growth was found to be 0.99 for Trichoderma viride TS; below 0.90 no development occurred. These values allowed this fungus to be classified in a group constituted of moderately water-sensitive fungi. Moreover, these results have been confirmed 1100
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by a study of the growth of this fungus led on sugar-beet pulp (Grajek & Gervais 1987a). For Penicillium roqueforti, the optimal water activity value was found to be 0.97 and development occurred over the whole range studied. However, at 0.90 the time lag was greater than five days. This fungus could be classified as a xerotolerant species. Otherwise, for the whole range of water activities studied, growth occurred faster in Trichoderma viride TS than in Penicillium roqueforti. The maximal radial extension rate values were 390 and 140 mm/h, respectively. This difference could be attributed to the nature of the microorganisms while the culture parameters, such as temperature and pH, were optimized.
Microscopic considerations Microscopic observations of colony growth on solid media reveal that hyphae tend to grow away from each other, and this has been explained by chemotropism (Robinson & Griffith, 1977); that is, each growing tip depletes substrates around itself and thus causes neighbouring tips to grow away toward more favourable conditions. Moreover, hyphae are subjected to steric interactions with other hyphae and tips as the colony growths. At short distances, binary interactions (tip-hyphae) involve a local spatial rearrangement, resulting in a slowing down of the tip extension rate. This leads to a maximum biomass surface density for given environmental conditions, whereas hyphal extension provides an alternative to motility, enabling hyphae to extend toward new food sources, branching provides a means to optimize colonization and substrate utilization. Growth of new tips is a process driven by complex intracellular mechanisms characterized by cytoplasm polarization (Prosser, 1990), so there is uncertainty about when and where a new tip will branch out of a hypha. One way of describing this mechanism is to assume that tips are generated by a stochastic process, characterized by a branching probability. Then, growth of new tips is also subjected to the same steric interactions just mentioned. That is, tips near colony center are likely to stop growing prematurely, so a maximum of (arrested) tip surface density arises therein. At the colony edge, tips are initially free to grow and extend. Therefore, tip growth is modulated by the local biomass surface density, incorporating a bias to the local growth rate. Therefore, the visual aspect of a growth colony can be explained by microscopic events: hyphal growth rate, branching frequency and direction of hyphal growth. Molin et al., (1992) have tried to describe the microscopic characteristics of hyphal growth and to study the effect of water activity on these parameters. The study was performed using image analysis, as previous authors (Adams & Thomas 1988) did for submerged cultures. This work was also intended to
link microscopic events with the macroscopic behaviour of a filamentous fungal colony.
Comparison between apical and radial growth rate allows to evaluate the hyphal orientation The relationship between radial growth rate and hyphal growth rate is not necessarily an equality: Vr may be different from Vh. The observation of a colony front shows that hyphae grow in all directions and the contribution of each apex to colony expansion is the projection of apex elongation upon the reference radial axis. The distribution of tip orientations could be measured by the angular deviation from the radial orientation (~h). Hyphal growth rate (Vh) and radial growth rate (Vr) measurements were made on two filamentous fungi solid cultivations: Trichoderma viride TS, Rhizopus oligosporus CBS 338.62. Five water activities were tested: the optimal aw of each fungus (0.995 for R. oligosporus and 0.990 for T. viride), two lower values (0.970 and 0.950) and another value close to 1 (0.998). The microscopic and macroscopic results of growth versus aw are presented in Table 2 and Figure 3.
Table 2: Dispersion in tip axes (V r /Vh) and tips orientation ( ~ ) versus water activity
*Optimal awfor R. oligosporus radial extension rate. **Optimal % for T. viride radial extension rate.
The optimal aw for radial growth rate was also optimal for the hyphal growth rate. Hyphal growth rate was always greater than radial growth rate, showing that the hyphae do not simply extend in the radial direction. The value of the ratio Vr/Vh given in Table 2 was always greater than 0.64, implying that the dispersion in tip axes was not evenly distributed. It means that the angles Oth, representative of the tips orientations, were not uniformly distributed onto 2 n radians.
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Water activity Figure 3: Colony extension rate (V.: ........... ) and hyphal growth rate (V h" - - - - - - ) versus water activity for R. oligosporus (r-I) and T. vMde (0). Standard deviation in brackets.
Hyphal Orientation Measurements as a function of the medium aw The means of the angles (O~h) were always found to be close to 7z as shown in Table 2, so that the tip orientations were centred around the radial direction of the colony for each fungus species and each water activity value. Angles distribution was not uniform. The angles were distributed according to a normal distribution with a mean of ~ radians and a standard deviation (a) which varied with water activity. The normality of these distributions was tested and Lhe tests showed that the distributions were not different from normal distributions. The more the water activity deviated from the optimal growth value, the higher
was the standard deviation. Orientation towards the colony margin, which signifies good spreading orientation, decreased when the medium became unfavourable. Apices of T viride were found to grow more radially than those of R. oligosporus. The previous described work (Molin et al., 1992) has shown that hyphae which were in the front of the colony had a favoured direction of growth which was the radial axis of the colony. The distribution of tip orientations was not uniform, but followed normal distribution and the standard deviation depended on the species and on aw values. Hence, the adjustment of filamentous fungi to the changing water activity environment would imply modifications in hyphal growth rate and in orientation of this growth. Furthermore, the use of the colony radial extension rate as the only growth criterion could induce some bias for the interpretation of experimental results about environmental parameter effects on fungal growth, since the hyphal growth rate is not always linearly linked to the radial extension rate.
5.3.1.4 Biomass evolution of a fungal SSF In a recent work (Ferret et al., 1999), a quantitative model predicting biomass growth on solid media has been developed. The model takes into account steric interactions between hyphae and tips at the microscopic level (competition for substrate and tips-hypha collisions). These interactions induce a slowing down of the hyphal, population-average extension rate and are responsible, at the microscopic level, for the distribution of tip orientations observed at the colony border. At the macroscopic level, a limiting value of the colony radial extension rate is attained. A mathematical model that combines hyphal branching, tip diffusion, and biomass growth was proposed to explain such behaviour. The main role of the substrate aw was particularly studied and integrated in this model. Experiments using Gibberella fujikuroi at different water activity levels were performed to validate the model; good agreement between experiments and simulations was achieved. Most parameters can be measured by simple image analysis on the peripheral growth zone, and they have clear physical meaning; that is they correspond to properties of single, leading hyphae. The model can be used to describe two-dimensional (2D) solid media fermentation experiments under varying culture conditions. The model was also extended by same authors to a three-dimensonal (3D) SSF of Gibberella fujikuroi grown on stacked amberlite spheres in a glass column. Steric growth limitations were found to be closely linked to the way of stacking the spheres which is related to the very old Kepler problem. The use of the rhombic dodecahedron surrounding each amberlite sphere has allowed developing an efficient model (Ferret et al., 2004).
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Others complex models that address the interactions of microbial growth with intraparticule diffusion of enzymes, hydrolysis products and 02 with the use of mechanistic equations have also been proposed and give insights into how this microscale processes can potentially limit the overall performance of a bioreactor. Models of this type have been recently reviewed by Mitchell et al., 2004. For many bioreactor models, the SSF kinetics are described by simple empirical equations. For instance, a recent kinetic model was applied to obtain noise free CO2 production rate values which in turn was used in water and energy balances. Finally, the evolution of other relevant variables including total and active biomass, 02 consumption rate, secondary metabolite production and dry mass degradation were also obtained (Lekanda & Perez-Correa 2004). An other empirical model for maximum biomass and maximum specific growth rate of A. niger as a function of the moisture content of the medium (steamed wheat bran) has been proposed by Hamidi-Esfahani et al., (2004).
5.3.1.5 Sporulation Solid-state fermentation is largely used for fungal spore production (Dorta et al., 1996) and it has been shown that spore size is different from that obtained from submerged cultivations (Feng et al., 2000). Water is a main parameter inducing sporulation and recent work (Dorta & Arcas 1998) has shown that sporulation pattern for Metarhizium anisopliae is directly related to water content even if others parameters as light frequency (Masangkay et al., 2000) and oxygen concentration are known to influence conidiation. Results obtained in our laboratory on the sporulation of two species are presented in Figure 4. A final numeration of the spores was performed after 10 days of culture. For the two fungi, sporulation did not occur in the youngest mycelial filaments, particularly in the peripheral zone. The intensity of sporulation was weaker for Trichoderma viride TS than for Penicillium roqueforti, certainly due to the pH conditions. The sporulation of Trichoderma viride TS attained a maximum for aw = 0.98 and the values decreased above as well as below this value. Maximum sporulation values of Penicillium roqueforti were obtained at aw of 0.96 as shown in Figure 4. For both fungi, optimal aw values for sporulation were slightly lower than optimal values for growth. Nevertheless for Trichoderma viride the minimal aw value allowing sporulation (c. 0.96) was greater than for growth (c. 0.92).
5.3.1.6 Germination The germination of a mould spore is a physiological reaction of a resting cell to modifications of the environmental conditions. The resting state of a spore
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---1
Water activity Figure 4: Influence of the substrate water activity on the sporulation intensity of T. viride TS (0) and P. roqueforti (A).
is controlled by the internal presence of metabolic blocks, nutrient penetration barriers, self-inhibitors, and low water content (Smith 1978). After a certain time lag, three successive structural changes are observed during germination (Gottlieb 1978): the swelling of the mould spore, the emergence of a germ tube, and the elongation. Hydration of the medium is an important parameter of germination (Snow 1949). Germination has been observed in pure water for Alternaria and Cladosporium (Dickinson & Bottomley 1980). Penicillium frequentans and Trichoderma viride have been identified as strains with self-feeding spores (Sheridan & Sheeman 1980). However, other authors have shown that the conidia of P. notatum and T. lignorum needed carbon and nitrogen to germinate (Martin & Nicolas 1970). When the water availability was limited, the water activity (aw) of the medium strongly influenced the mould development (Gervais et al., 1988b). This parameter is widely used for quantifying the availability and the energy state of water. Nevertheless, aw alone cannot explain the biological variations; when the medium aw was adjusted by solutes the nature of the solute has an effect (Beuchat 1983). Only a few authors have tried to describe germination of conidia as a function of time. An empirical model for spore germination of Alternaria solani has been described, and further extended in order to develop a complex box model of germination (Waggoner & Parlinge 1975). A model proposed for conidial germination in Colletotrichum graminicola (Lapp & Skoropad 1976) fitted the
data well, but the parameters had little biological significance. The model proposed in a previous work (Gervais et al., 1988c) was based on a first order system application to germination which has been tested on T. viride and P. roqueforti. Water activity values from 0.94 to 0.99 were favourable to the germination of P. roqueforti; and the most favourable values for T. viride TS were 0.94 to c. 1. P. roqueforti germinated at minimum aw value of 0.86, which was higher than 0.83 found previously (Magnan & Lacey 1984) with glycerol-agar medium. But the absence of nutrients reduced the range of aw values where germination and growth were possible (Snow 1949). The influence of the low water activity values on germination is not well understood (Charlang & Horowitz 1974). The loss of an essential substance for germination for Neurospora crassa, Aspergillus nidulans and Penicillium ch~ysogenum at low water activity has been suggested (Charlang & Horowitz 1971; Charlang & Horowitz 1974). According to Gottlieb 1978 water allows the diffusion of self-inhibitors out of the spore. In all cases, the membrane permeability is important. Dehydration of the membrane would produce a molecular rearrangement of phospholipids leading to a rigidification and a loss of permeability of the membrane (Quinn 1985). The rearrangement would occur at an aw value which corresponds to the minimum water activity value observed for germination.
5.3.1.7 Metabolite production The production of secondary metabolites is also dependent in numerous cases on the water energy state in the medium which can be evaluated by thermodynamic parameters. Thus, the toxin production by filamentous fungi cultivated on solid support is related to the medium aw; the ochratoxin A production by Penicillium viridicatum is optimal for an aw of 0.87 (Northolt et al., 1984) and for an initial substrate water content of 31% (Lindenfelser & Ciegler 1975). In the same way, the water activity value of the substrate during giberellic acid production by G. fujikuroi was found to drastically decreased during SSE although optimal value was evaluated at 0.99 (Corona et al., 2005). Some hypotheses have been made on the influence of a decreased water activity on the metabolism of microorganisms. A new metabolic cycle of glycerol initiated by high concentrations in glycerol was discovered by Ben-Amotz and Avron (1981) in the halophilic alga Dunaliella. The result of this cycle is to transfer redox equivalents from NADH to NADPH at the expense of one ATE The enzyme of this cycle was found to be specific and had a very high Km to glycerol.
Since an increased synthesis of [3-carotene was found to follow the decrease in aw, it could he postulated that the intracellular accumulation of glycerol started the glycerol cycle which resulted in a transfer of redox equivalents from NADH to NADPH which favoured biosynthesis pathways and particularly ~-carotene synthesis. The synthesized solutes responsible for osmoregulation, called compatible solutes, are essentially polyols, amino acids and ions. The organic solutes thus defined interfere with enzymatic activities and are generally very water-soluble. With regard to the rate of some syntheses in response to a water stress (3 minutes for the isofluoride synthesis by Ochramonas malhamensis) (Krauss 1974), it seems that these syntheses could be initiated by the membrane deformation.
Water activity and enzymatic reactions Water activity can act through the osmoregulation process of the cell or through a direct enzymatic action, as previously described by numerous authors (Beuchat 1983; Nishio et al., 1979). We have confirmed such a direct action by a study on enzymatic activity related to the mass of enzyme produced versus water activity. The influence of water activity (aw) on the biosynthesis of polygalacturonase, D-xylanase and 13-glucosidase in a solid culture system of Trichoderma viride was previously studied (Grajek & Gervais 1987b). It was found that the production of enzymes was strongly affected by the water activity of the substrate and slightly by the nature of the aw depressor used. The maximum polygalacturonase and D-xylanase production occurred at aw 0.99 whatever the depressor used whereas ~-glucosidase formation was favoured between aw 0.96 and 0.98 depending upon the solute (0.96 for sorbitol, 0.97 for glycerol, 0.98 for NaC1). The influence of water activity on the catalytic effect of enzymes using sodium chloride, glycerol and sorbitol as aw depressors was also investigated and shown to be drastically influent as proposed in Figure 5. It should be noticed that the optimal value for enzymatic synthesis was found to be different from the optimal value found for catalytic activity. Recent work proposed an optimal 55% moisture content value for a maximum xylanase production by Trichoderma longibrachiatum (Ridder at al 1999). Nevertheless, in the case of xylanase production by Aspergillus tereus, the optimal water content was found to be 75%. A water content of 71% corresponding to a water activity of 0.921 was found to increase the production of cyclodepsipeptides in solid state fermentation by Metarhizium anisopliae (Liu & Tzeng 1999). The Doehlert experimental design was applied by Taragano and Pilosof 1999 to optimize water activity, pH, and fermentation time conditions for Aspergillus niger 148 pectinolytic activities production in solid-state (SSF) and submerged (SmF) fermentation. The
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Figure 5: Effect of water activity on the product release in hydrolir reaction using enzyme solution from T. viride TS; aw depressors: NaCl (D), glycerol (A), sorbitol (O) for A: Polygalacturonir acid => Galacturonir acid; B: Xylan => Xylose and C." Cellobiose ~ Glucose.
fermentation technique had a great influence on the composition of pectinases produced by the fungus. Production of polygalacturonase was 5-fold higher in SmF than in SSE However, pectin lyase production was 3 times higher in SSF than in SmF. Pectinesterase was only a 30% higher in SSF than in SmF. Optimization of the process was based on minimum pectinesterase production and maximal pectin lyase production. The optimal conditions to obtain this composition by a SSF process were: initial pH 6.5-7; initial aw 0.93-0.94, and 2 days of fermentation. For the SmF process they were initial pH 5.5-6.2, initial aw above 0.99, and 3 days of fermentation. The results suggest that A. niger 148 overproduces pectin lyase under the optimized SSF culture conditions, as the concentration in the fermentation extract was around 0.25 g/l, representing --- 65% of total extracellular proteins produced by the fungus. In the same way, comparison of exopectinase production by Aspergillus niger was studied between solid state and submerged fermentation (Diaz-Godinez et al., 2001). In this case an enhancement of enzyme activity was observed in SSF for high water activity (0.99) with sucrose addition (40g/L) linked to high level of biomass production. In order to increase production of different metabolites by Aspergillus strains, parasexual crosses between selected strains may be considered and recent works have shown the drastic effect of water activity on invertase production in SSF by improved diploide strains of Aspergillus niger (Montiel-Gonzalez et al., 2004). Lipase production by Candida rugosa
was enhanced by mixed solid substrate fermentation proposed by Benjamin and Pandey (1998) with an initial aw value of 0.92.
Water activity and fungal aroma production The 2-heptanone bioconversion of the fungus Trichoderma viride TS from octanoic acid has been studied in Roux flasks. A continuous aeration (50 ml/h) allowed the heptanone produced, which is a highly volatile compound (Tallu 1986) to be analysed. In this case, sequential headspace chromatographic analysis was used (Gervais et al., 1988c). Aroma production versus aw of the liquid or solid media is shown in Figure 6. Production value was dramatically affected by the water activity variation of the media. In the solid medium the 2-heptanone production increased as the aw value of the medium decreased. Such results were obtained by the analysis of the extracellular medium and resulted from the excretion availability of the cell which combines intracellular production and permeability properties. Variation of water activity in solid fermentation media could lead to great modifications in intracellular accumulation and in extracellular excretion of aroma produced by moulds (Gervais et al., 1990). Enzyme inhibition and cell membrane permeability variation are involved in such mechanisms. This conclusion may be of great interest in the attempt to optimize metabolite production such as aroma, antibiotics, enzymes by means of aw control. A sensor that allows the continuous measurement of the osmotic pressure of a liquid medium could be used with this aim (Gervais 1989). In a previous work (Gervais & Sarrette 1990) it was shown that the aroma production by microorganisms is dependent not only on physicochemical factor like pH, 18 16 = ,~, 14 ._o =
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temperature (Latrasse et al., 1985) or water activity (Gervais et ai., 1988c), but also on the physiological state of the fungus. Maximum aroma production always occurred around 4.5 days which corresponded to a particular physiological state of the mycelium. In a recent work, Larroche et al., 1999 have studied the production of 2,5-Dimethylpyrazine (2,5-DMP) and tetramethylpyrazine (TFMP) using Bacillus subtilis IFO 3013 grown in solid substrate conditions. The optimal cultivation temperature was 40~ pH had to be monitored at 7.5, aeration rate had to be higher than 0.1 VVM and ground soybeans used as substrate were suspended in water. Optimization studies showed that the best way to increase the two above aroma compounds (until 2 g/L) involved massive enrichment of the medium with L-threonine and acetoin. Medeiros et al., 2000 have also determined the optimal initial moisture of the solid-substrate allowing optimizing the aroma production by Kluyveromyces marxianus.
5.3.2 Influence of Water Dynamic Parameters In the case of solid-state fermentations, the presence of an insoluble matrix generates a matrix potential (Wm) through the intermediary of water-solid reactions. The presence of solutes in the liquid medium gives another kind of potential linked with solute-liquid interaction, the osmotic potential (qJs)- These two potentials make up the total water potential of a fermentation medium if temperature, gravity, and pressure are constant. By measuring the respective effects of the matrix potential and the osmotic potential, Griffin (1981) has determined that these two potentials have a different effect on the growth of microorganisms at the same pressure. For the same value of aw, the growth measured on media with only solid-liquid interactions, i.e. the matrix potential, is always less than the growth measured on media with only solute-liquid interactions, i.e. the osmotic potential. However, these two types of potential should always have the same effect on the growth of microorganisms at a thermodynamic level. Some authors have suggested that this variation is due to the interference of diffusion phenomena with the growth of micro-organisms (Adebayo & Harris 1971; Griffin 1972). In unpublished work, we have demonstrated that variations in kinetic properties of the culture medium in relation to hydration can explain the physiological modifications of micro-organisms. The hydration of the solid substrate was related to the growth of the filamentous fungus Trichoderma viride (Gervais et al., 1988a). Experimental design was intended to discriminate the respective influence on the fungal growth of thermodynamic and kinetic (or dynamic) parameters related to water. For the same thermodynamic level of water (aw) and by adding silica gel to the medium, it was found that the decrease in water content could generate diffusional limitation of the fungal growth.
The results shown in Figure 7 show that for the same aw value, the increase in glucose concentration significantly increases the radial extension rate for very low water content value (Medium C: 2.22 g water/g insoluble dry matter), but has no action for high water content values (Medium A: 63.4 g water/g insoluble dry matter). In order to confirm the assumption of a diffusion limitation, the diffusion of glucose in previous media (A, B and C) was evaluated. The translational diffusion coefficient proposed (see Table 3) was determinated following Lyrett's method. Glucose diffusivity was found to decrease sharply when silica gel was added to the media. These results confirm the hypothesis that diffusion could be limited when the water content of the fermentation was decreasing. The rotational diffusivity (Drot) measurements determinated by using electronic spin resonance are also presented in Table 3. Similar results described previously showed a decrease in diffusivity of solutes and water molecules when there was a decrease in water content (Karel 1976; Biquet & Guilbert 1986). The values for the Drot[Otrans ratio in Table 3 show that this ratio stays almost constant whatever the water content is, implying that the tortuosity of the media used had little or no influence on solute diffusion in these media. The limiting factor on the growth of microorganisms was the diffusion rate of solutes in the gel and not the tortuosity of the medium. When there was a large amount of polymer, the water content was reduced and solute and water diffusion decreased for the same aw. The higher the proportion of the matrix potential, the lower the water content became. In fact, analysis of the sorption curves showed that insoluble polymers required a smaller quantity of water in order to reach the same aw as most solutes. MacDonald & Duniway 1978 carried out experiments on the same kind of soils as those used by Griffin & Luard (1979) and Griffin (1981). It can be deduced that in order to obtain a matrix potential level that corresponds to water activities 0.98 and 0.99 in their culture medium, extremely low water contents were required. Thus, diffusional factors combined with low water content in the culture can limit the growth of microorganisms in such solid media.
Table 3: Diffusion coefficients of glucose (and their ratio) in different silica gel media of different water content (A, B, C)
Figure 7: Radial growth rate of T. virideTS grown on gels with water activity 0.99. [ ( ~ ) Medium A (63.4 g water/g insoluble dry matter); ( ~ ) Medium B (5.47 g water/g insoluble dry matter); ( ~ ) Medium C (2.22 g water/g insoluble dry matter)]. 5.4 CONCLUSIONS In solid-state fermentation, water mass transfers are strongly related to other physico-chemical control parameters and especially to aeration and heat, and it is necessary to have a global approach for optimization.
5.4.1. Water and aeration Aeration has essentially two functions (Chahal 1983; Tabak & Cook 1968): (1) oxygen supply for aerobic metabolism and (2) removal of CO2, heat, water vapour, and volatile components produced during the metabolism. The aeration rate must also depend on the thickness of the layer and the porosity of the medium. The effects of pO2 and pCO2 in the gas environment are important variables and must be optimized for each medium, microorganism, and process (Raimbault & Alazard 1980; Lonsane et al., 1985; Bajracharya & Mudgett 1985; Huang et al., 1985; Levonen-Mufloz & Bone 1985). Aeration also has very important effects on hydration properties and heat regulation in solid-state fermentations. As shown previously, the water potential could be monitored through the relative humidity of the air, and most of the heat evolved would be transferred to the air latent heat of water vaporization. Sato et al., 1982 estimated this latent heat to account for about 80% of the total heat evolved. Such a ratio has been confirmed more recently by Sangsurasak & Mitchell (1998). The aeration in solid-state fermentations which controls air distribution in the medium can be characterized by means of residence time distribution determinations (Gervais et al., 1986).
As defined by Moo-Young et al., (1983), the most important O2 transfer mechanism is interparticles mass transfer. The dew point of the air used for aeration must be defined as a function of the air inlet temperature in order to control the relative humidity of the solid substrate. Modification of the air status occurs when air is passing through the solid bed. The relative humidity of the air generally increases due to evaporation; such phenomena can be localized and lead to heterogeneity in the medium if the flow rate is too slow. To prevent this type of problem, the temperature and water content of the substrate bed could be controlled by saturating the air at the air inlet but manipulating its temperature, coupled with a strategy of water replenishment when the water content of the bed falls below a threshold. Recent paper (Von Meien et al., 2004) has tested different control strategies based on classic proportional integral derivative (PID) and advanced dynamic matrix control (DMC) algorithms for an intermittently stirred, forcefully aerated SSF bioreactor. Pressure drop could also vary as the chemical composition of the solid state evolved. An air flow rate control loop could prevent these variations (Aunia et al., 1995). However, from a general point of view, gas diffusion (O2, CO2) occurs at very high rates with regard to the solute diffusion rates in liquid media and even at higher rates in the gas phase of solid state media. Therefore such diffusion will not generally constitute a limiting factor in SSF.
5.4.2. Water and heat Temperature regulation is directly related to water potential and aeration. Temperature is a factor that strongly influences culture growth, and in aerobic fermentations, a large amount of heat is produced during microbial growth, as shown by Gonzalez-Blanco and colleagues (Gonzales-Blanco et al., 1990) for A. terreus. A great limitation of solid-state fermentations is the difficulty of removing excess heat due essentially to the low thermal conductivity of the solid substrate. For instance, Oostra et al., (2000) have measured a thermal conductivity value of the bed of 0.1W.m-I.K-1. Saucedo-Castanada and colleagues (Saucedo-Castanada et al., 1990) have estimated the dimensionless B iot and Peclet numbers corresponding to the heat transfer during cassava solid-substrate fermentation by A. niger. It was shown that conduction through the l 1-fixed bed was the main heat transfer resistance. To maintain the optimal culture conditions, it was necessary to immediately eliminate the heat generated. Convective heat transfer from the reactor wall was not effective due to low mixing and internal heat transfer limitations. The method of evaporative cooling that inserts partially saturated air at lower temperature is the most interesting, as proposed by Durand et al., (1983) and Grajek (1987).
In practice, only air is used for temperature control in solid-state fermentations. The heat capacity of the air at maximal water saturation is less than the heat capacity of water for cooling in submerged fermentations. For these reasons, solid-state fermentations need a large quantity of air, exceeding the amount necessary for microbial respiration. At a semi-industrial scale, the limitation in cooling technique in solid-state fermentations enhances the use of thermophilic strains, as realized by numerous workers (Moo-Young et al., 1977; Viesturs et al., 1981; Moo-Young et al., 1983; Chahal 1983). From the previous considerations, the physicochemical requirements of solidstate fermentations can be summarized as follows: It is generally beneficial to keep the level of water content just below the water holding capacity of the solid substrate in order to optimize 02 requirements without limiting the liquid diffusion of nutrients. It is important to adjust the forced aeration with air with controlled relative humidity to optimize heat, CO2 and volatile evacuation, and 02 requirements. Since respiration produces water, endothermic evaporation phenomena will be the major energetic factor of heat evacuation. It is necessary to take into account the depth of the fermentation bed and to calculate the air temperature and the air flow rate in order to prevent rapid water saturation of forced air and condensation in the upper part of the bed. Indeed, residence time of air must be sufficiently short in order to not be saturated at the exit of the bed. It is necessary to take into account the evolution of the water sorption properties of the solid substrate during the fermentation to optimize water activity requirements, which are of major importance for growth. Indeed, the division of high-molecular-weight polymers by extracellular enzymes such as cellulases could lead to drastic decreases in water activity for the same water content, as shown previously. Therefore, the relative humidity of the forced air must be adjusted during the fermentation.
References Adams HL & Thomas CR, 1988, The use of image analysis for morphological measurements on filamentous microorganisms, Biotechnology and Bioengineering, 32, 707-712.
Adebayo AA & Harris RF, 1971, Fungal growth responses to osmotic as compared to matrix water potential, Soil Science Society of America Journal, 35, 465-469.
Aunia R, Ortiz I, Villegas E & Revah S, 1995, Influence of growth and high mould concentration on the pressure drop in solid-state fermentations, Process Biochemistry, 8,751-756. Bajracharya R & Mudgett R, 19.85, Effects of controlled gas environments in solidsubstrate fermentations of rice, Biotechnology and Bioengineering, 22, 2219-2235. Barstow LM, Dale BE & Tengerdy RP, 1988, Evaporative temperature and moisture control in solid substrate fermentation, Biotechnological Techniques, 2, 237-242.
Bartnicki-Garcia S, 1973, Fundamental aspects of hyphal morphogenesis, In- Microbial Differentiation, JM Ashworth & Smith JE (eds), Cambridge University Press, London, pp 245-267. Bellon-Maurel V, Orliac O & Christen P, 2003, Sensors in solid state fermentation: a review, Process Biochemistry, 38, 881-896.
Ben-Amotz A & Avron M, 1978, On the mechanism of osmoregulation in Dunaliella, InDevelopments in Halophic Microorganisms, Vol. 1, Energetics and Structure of Halophic Microorganisms, SR Caplan & M Ginzburg (eds), Elsevier-North-Holland Press, Amsterdam, pp 529-536. Ben-Arnotz A & Avron M, 1981, Glycerol and ~-carotena metabolism in the halotolerant alga Dunaliella: a model system for biosolar energy conversion, Trends in Biochemical Sciences, 297-299.
Benjamin S & Pandey A, 1998, Mixed-solid substrate fermentation. A novel process for enhanced lipase production by Candida rugosa, Acta biotechnologica, 18, 315-324. Beuchat LR, 1983, Influence of water activity on growth, metabolic activities and survival of yeast and moulds, Journal of Food Protection, 46, 135-141. Biquet B & Guilbert S, 1986, Diffusivit6s relatives de l'eau dans les .aliments mod61es humidit6 interm6diaire, Lebensmittel Wissenschaft Technologie, 19, 208-214. Bouanda R, 1983, Contribution ?~l'6tude de 1'activit6 enzymatique en milieu faiblement hydrat6: influence de la mobilit6 du substrat, Th6se de doctorat, Universit6 de Bourgogne, Dijon, France. Bramorski A, Christen P, Ramirez M, Soccol CR & Revah S, 1998, Production of volatile compounds by the edible fungus Rhizopus oryzae during solid state cultivation on tropical agro-industrial substrates, Biotechnology Le#ers, 20 (4), 359-362. Bruin S & Luyben KCA, 1980, A review of recent developments, In- Advances in Drying, Vol 1, A Majumdar (ed), Hemisphere, Londonl pp 155-215. Bull AT & Trinci APJ, 1977, The physiology and metabolic control of fungal growth, In- Advances in Microbial Phy~;m,~gy, AH Rose & Tempest DW (eds), Academic Press, New York, pp 1-84.
Chahal DS, 1983, Growth characteristics of microorganisms in solid state fermentation for upgrading of protein values of lignocelluloses and cellulases production, American Chemical Society Symposium Series, 207, 421-442.
Charlang GW & Horowitz NH, 1971, Germination and growth of Neurospora at low water activities, Proceedings of The National Academy of Sciences, 68, 260-262. Charlang GW & Horowitz NH, 1974, Membrane permeability and the loss of germination factor from Neurospora crassa at low water activity, Journal of Bacteriology, 117, 261-264. Corona A, Saez D & Agosin E, 2005, Effect of water activity on gibberellic acid production b7 Gibberella fujikuroi under solid-state fermentation conditions, Process Biochemistry, 40, 2655-2658. Crowe JH, Crowe LM & Deamer DW, 1982, Hydration dependent phase changes in biological membrane, In Biophysics of Water, E Franks & S. Mathias (eds), Wiley, Chichester, pp. 295-299. Cudd A & Steptonkus PL, 1987, Osmotic dehydration-induced lamellar to hexagonal-II phase transitions in liposomes of rye plasma membrane lipids, Cryo. 87: 24th Annual meeting, Society for Cryobiology, Edmonton, Canada, pp 33-35. De Loecker R, Penninck F & Keremans R, 1978, Osmotic effects of rapid dilution of cryoprotectants: I. Effect of human erythrocyte swelling, Cryoletters, 8, 131-136. De Reu JC, Zwietening MH, Rombouts FM & Nout MJR, 1993, Temperature control in solid substrate fermentation through discontinuous rotation, Applied Microbiology and Biotechnology, 40, 261-265. Diaz-Godinez G, Soriano-Santos J, Augur C & Viniegra-Gonzalez G, 2001, Exopectinase produced by Aspergillus niger in solid-state and submerged fermentation: a comparative study, Journal of Industrial Microbiology and Biotechnology, 26, 271-275. Dickinson S & Bottomley R, 1980, Germination and growth of Alternaria and Cladosporium in relation to their activity in the phylophane, Transactions of The Britisch Mycological Society, 74, 309-319. Dorta B, Ert01a RJ & Arcas J, 1996, Characterization of growth and sporulation of Metarhizium anisoplae solid-substrate fermentation, Enzyme and Microbial Technology, 19, 434-439. Dorta B, Arcas J, 1998, Sporulation of Metarhizium anisoplae in solid-state fermentation with forced aeration, Enzyme and Microbial Technology, 23, 501-505. Durand A, Arnoux P, Teilhard de Chardin O, Chereau D, Boquien CY & Larios de Anda G, 1983, Protein enrichment of sugar-beet pulp by solid state fermentation, InProduction and Feeding of Single-Cell Protein, MP Ferranti & A Fietcher (eds), Applied Science Publishers, London and New York, pp 120-123. Durand A & Ch6reau D, 1988, A new pilot reactor for solid-state fermentation: application to the protein enrichment of sugar beet pulp, Biotechnology and Bioengineering, 31, 476-486. Durand A, Renaud R, Almanza S, Maratray J, Diez M & Desgranges C, 1993, Solid state fermentation reactors: from lab scale to pilot plant, Biotechnology Advances, 11, 597-597.
Engel E, 1995, Etude de l'influence de 1'activit6 de l'eau sur la croissance, la sporulation et la production d'ar6mes de Ceratocystis fimbriata cultiv6e en milieu solide, M6moire d'Ing6nieur ENSBANA, Universit6 de Bourgogne, France. Feng KC, Liu BL & Tzeng YM, 2000, Verticillium lecanii spore production in solidstate and liquid-state fermentations, Bioprocess Engineering, 23, 25-29. Ferret E, Simeon JH, Molin P, Jorquera H, Acuna G & Giral R, 1999, Macroscopic growth of filamentous fungi on solid substrate explained by a microscopic approach, Biotechnology and Bioengineering, 65, 512-522. Ferret E, Molin P, Acuna G, Perez-Correa R & Gervais P, 2004, In- Steric approach for growth kinetics Gibberella fujikuroi on 3D solide substrate, CAB9 9th International Symposium On Computer Applications in Biotechnology, Pons NM & Van Impe JFM (eds), Elsevier Limited, Nancy, 321-326. F~vre M, 1979, Digitonin solubilization and protease stimulation of b-glucan synthetases of Saprolegnia, Zeitschrift fur pflanzenphysiologie, 95, 129-140. F~vre M & Rougier M, 1982, Autoradiographic study of hyphal cell wall synthesis of Saprolegnia, Archives of Microbiology, 131, 212-215.
Fisher LR, & Israelachvili JN, 1979, Direct experimental verification of the Kelvin equation for capillary condensation, Nature, 277, 548-549. Flory PJ, 1953, Statistical thermodynamics of polymer solutions, In- Principles of Polymer Chemistry, EJ. Flory (ed), Cornell University Press, New York, pp 495-540.
Franks F, 1995, Water and aqueous solutions: Recent advances, In- Water Properties of Foods, D Simatos & JL Multon (eds), Martinus Nijhoff, The Netherlands, pp 1-23. Gervais P, Bazelin C & Voilley A, 1986, Patterns of aeration in a solid substrate fermentor through the study of the residence time distribution of a volatile tracer, Biotechnology and Bioengineering, 28, 1540-1543. Gervais P, Belin JM, Grajek W & Sarrette M, 1988a, Influence of water activity on the aroma production by Trichoderma viride growing on solid substrate, Journal of Fermentation and Bioengineering, 66, 403-407. Gervais P, Bensoussan M & Grajek W, 1988b, Water activity and water content: comparative effects on the growth of Penicillium roqueforti on solid substrate, Applied Microbiology and Biotechnology, 27, 389-392. Gervais P, Fasquel JP & Molin P, 1988c, Water relations of fungal spore germination,
Applied Microbiology and Biotechnology, 29, 586-592. Gervais P, Molin P, Grajek W & Bensoussan M, 1988d, Influence of water activity of a solid substrate on the growth rate and sporogenesis of filamentous fungi, Biotechnology and Bioengineering, 31,457-463. Gervais P, 1989, New sensor allowing continuous water activity measurements of submerged or solid-substrate fermentations, Biotechnology and Bioengineering, 33, 266-271.
Gervais P, 1990, Water activity: a fundamental parameter of aroma production by microorganisms, Applied Microbiology and Biotechnology, 33, 72-75. Gervais P & Sarrette M, 1990, Influence of age of mycelium and water activity of the medium on aroma production by Trichoderma viride grown on solid substrate, Journal of Fermentation and Bioengineering, 69, 46-50. Gervais P & Bensoussan M, 1994, Solid-State Fermentations of the Genus Aspergillus, In- Aspergillus, J.E. Smith (ed), Plenum Press, pp 101-140. Gervais P, Marechal PA & Molin P, 1996, Water relations of solid-state fermentation, Journal of Scientific & Industrial Research, 55, 343-357 Gervais P, Molin P, Marechal PA & Herail-Foussereau C, 1996b, Thermodynamics of cell osmoregulation: passive mechanisms, Journal of Biological Physics, 22, 73-86. Gervais P, Abadie C & Molin P, 1999, Fungal turgor pressure is directly involved in the hyphal growth rate, Microbiological Research, 154, 81-87.
Ghildyal NP, Gowthaman MK, Raghava Rao KSMS & Karanth NG, 1994, Interaction of transport resistances with biochemical reaction in packed-bed solid-state fermentors: effects of temperature gradients, Enzyme and Microbial Technology, 16, 253-257. Gilles R, 1975, Mechanism of ion and osmoregulation, In- Marine Ecology, O Kenne (ed), Wiley-Interscience, England, pp 259-347. Gonzalez-Blanco P, Saucedo-Castaneda G & u G, 1990, Protein enrichment of sugar cane by-products using solid state cultures of Aspergillus terreus, Journal of Fermentation and Bioengineering, 70, 351-354. Gottlieb D, 1978, In The Germination of Fungus Spores, D Gottlieb (ed), Meadowfield Press, Durham, pp 1-11. Goldberg M, Parvaresh F, Thomas D & Legoy MD, 1988, Enzymatic ester synthesis with continuous measurement of water activity, Biochimica et Biophysica Acta, 957, 359-362 Grajek W, 1987, Cooling aspects of solid state fermentation and thermophilic fungi, Journal of Fermentation Technology, 66, 675-679. Grajek W & Gervais P, 1987, Effect of the sugar-beet pulp water activity on the solid state culture of Trichoderma viride TS, Applied Microbiology and Biotechnology, 26, 537-541. Grajek W & Gervais P, 1987b, Influence of water activity on the enzyme biosynthesis and enzyme activities produced by Trichoderma viride TS in solid-state fermentation, Enzyme and Microbial Technology, 9, 658-662. Griffin DM, 1972. General ecology of soil fungi, In- Ecology of Soil Fungi, University Press, London, pp 2-67. Griffin DM & Luard EJ, 1979, Water stress and microbial ecology, In- Strategies of Microbial Life in Extreme Environments, M Shilo (ed), Verlag Chemie, Weinheim, pp 49-63.
Griffin DM, 1981, Water and microbial stress, Advances in Microbiology and Ecology, 5,91-136 Grigelmo-Miguel N & Martin-Belloso O, 1999, Characterization of dietary fiber from orange juice extraction, Food Research International, 31, 355-361. Guggenheim EA, 1967, Thermodynamics" An advanced treatment for chemists and physicists, North-Holland, Amsterdam, 5th Ed. Hamidi-Estafani Z, Shojaosadati SA & Rinzema A, 2004, Modelling of simultaneous
effect of moisture and temperature on A. niger growth in solid-state fermentation, Biochemical Engineering Journal, 21, 265-272. Howard RJ, 1981, Ultrastructural analysis of hyphal tip cell growth in fungi Spitzenk6rper, cytoskeleton and endomembranes after freeze-substitution, Journal of Cell Science, 48, 89-103. Hellebust JA, 1976, Osmoregulation, Annual Review of Plant Physiology, 27, 485-505. Hesseltine CW, 1972, Solid state fermentation, Part 1, Biotechnology and Bioengineering,
14,517-532. Huang SY, Wei CH, Malancy GW & Tanner RD, 1985, Kinetic responses of the koji solid state fermentation process, In- Topics in Enzyme and Fermentation: Biotechnology, A. Wiseman (ed), John Wiley & Sons, New York, pp 88-108. Inch JMP & Trinci APJ, 1987, Effects of water activity on growth and sporulation of Paecilomyces farinosus in liquid and solid media, Journal of General Microbiology, 133,247-252. Jakobsen M, 1985, Effect of aw on growth and survival of bacilliaceae, In- Properties of Water in Foods, D Simatos & Multon JL (eds), Martinus Nijhoff, Dordrecht, pp 259-272. Kaminky SGW, Garril JA & Heath BI, 1992, The relation between turgor and tip growth in Saprolegnia ferax : turgor is necessary but not sufficient to explain apical extension rates, Experimental Mycology, 16, 64-75. Karel M, 1976, Technology and application of new intermediate moisture foods, InIntermediate Moisture Foods, R Davies, GG Birch & Parker KJ (eds), Applied Science Publishers, London, pp 1321 -1354. Krauss H, 1974, Osmoregulation in Ochromonas, In- Membrane Transport in Plants, U Zimmermann and Dainty J (eds), Springer, Berlin, pp 90-94. Kedem O & Katchalsky A, 1958, Thermodynamic analysis of the permeability of biological membranes to non-electrolytes, Biochimica et Biophysica Acta, 27, 229-246.
Kuntz ID, 1971, Hydration of macromolecules: hydration of polypeptides, polypeptides conformation in frozen solutions, Journal of the American Chemical Society, 92, 514-518. Labuza TP, Acott K & Tatini SR, 1976, Water activity determination: a collaborative study of different methods. Journal of Food Science, 41, 910-917.
Lapp MS & Skoropad WP, 1976, A mathematical model of conidian germination and appressorial formation for Colletotrichum graminicola, Canadian Journal of Botany, 54,2239-2242. Larroche C, Besson I & Gros JB, 1999, High pyrazine production by Bacillus subtilis in solid substrate fermentation on ground soybeans, Process Biochemistry, 34, 667-674. Latrasse A, Degorce-Dumas JR & Leveau JY, 1985, Production d'ar6mes par les microorganismes, Science des Aliments, 5, 1-26. Lekanda JS & Perez-Correa JR, 2004, Energy and water balances using kinetic modeling in a pilot-scale SSF bioreactor, Process Biochemistry, 39, 1793-1802. Le Meste M & Voilley A, 1988, Influence of hydration on rotational diffusivity of solutes in model systems, Journal of Physical Chemistry, 92, 1612-1616.
Levonen-Mufloz E & Bone DH, 1985, Effect of different gas environments on benchscale solid state fermentation of oat straw by white-rot fungi, Biotechnology and Bioengineering, 27, 382-387. Lindenfelser LA & Ciegler A, 1975, Solid-substrate fermentor for ochratoxin A production, Applied Microbiology, 29, 323-327. Liu BL & Tzeng YM, 1999, Water content and water activity for the production of cyclodepsipeptides in solid-state fermentation by Metarhizium anisoplae, Biotechnology Letters, 21,657-661. Lockhart JA, 1965, An analysis of irreversible plant cell elongation, Journal of Theoretical Biology, 8, 264-275.
Lonsane BK, Ghildyal NP, Butiatman S & Ramakrishna SV, 1985, Engineering aspects of solid state fermentation, Enzyme and Microbial Technology, 7, 258-265. Luard EJ, 1982, Growth and accumulation of solutes by Phytophthora cinnamomi and other lower fungi in response to changes in external osmotic potential, Journal of General Microbiology, 128, 2583-2590. MacDonald JD & Duniway JM, 1978, Influence of the matrix and osmotic components of water potential on zoospore discharge in Phytophthora, Phytopathology, 68, 751-757. Magnan N & Lacey J, 1984, Effect of temperature and pH on water relations of field and storage fungi, Transactions of The Britisch Mycological Society, 82, 71-81. Maniette F, Cambert M, Franconi JM & Marchal P, 1999, Etude par imagerie RMN des transferts d'eau lors de l'6gouttage des caill6s de fromagerie, In-AGORAL 99 Onzi~mes rencontres scientifiques et technologiques des industries alimentaires, Tec & Doc (ed), Nantes, 405-410. Martin JF & Nicolas G, 1970, Physiology of spore germination in Penicillium notatum and Trichoderma lignorum, Transactions of The Britisch Mycological Society, 55, 141-148.
Masangkay RF, Paulitz TC, Hallett SG & Watson AK, 2000 Solid substrate production of Alternaria alternata f. sp. phenoclease conidia, Biocontrol Science and Technology, 10, 399-409. Mauro A, 1957, Nature of solvent transfer in osmosis, Science, 26, 252-253. Mazur P, Rail WF & Rigopoulos N, 1981, Relative contributions of the fraction of unfrozen water and of salt concentration of the survival of slowly frozen human erythrocytes, Biophysical Journal, 36, 653-675. Medeiros ABP, Pandey A, Freitas RJS, Christen P & Soccol CR, 2000, Optimization of the production of aroma compounds by Kluyveromyces marxianus in solid-state fermentation using factorial design and response surface methodology, Biochemical Engineering Journal, 6, 33-39. Mitchell D, Von Meien OF, Krieger N & Dalsenter FDH, 2004, A review of recent developments in modelling of microbial growth kinetics and intraparticle phenomena in solid-state fermentation, Biochemical Engineering Journal, 17, 15-26. Mohsenin N, 1984, Electromagnetic radiation properties of food and agricultural products, Gordon & Breach publishers, New-York. Molin P, Gervais P, Lemi~re JP & Davet T, 1992, Direction of hyphal growth: a relevant parameter of the development of filamentous fungi, Research in Microbiology, 143, 777-784. Money NP, Harold FM, 1993, Two water molds can grow without measurable turgor pressure, Planta, 190, 426-430. Money NP, 1997, Wishful thinking of turgor revisited: the mechanics of fungal growth, Fungal Genetics and Biology, 21, 173-187. Montiel-Gonzalez AM, Viniegra-Gonzalez G, Fernandez FJ & Loera O, 2004, Effect of water activity on invertase production in solid state fermentation by improved diploid strains of Aspergillus niger, Process Biochemistry, 39, 2085-2090.
Moo-Young M, Chahal DS, Swan JE & Robinson CW, 1977, SCP production by Chaetomium cellulolyticum: A new cellulolytic fungus, Biotechnology and Bioengineering, 19, 527-538. Moo-Young M, Moriera A.R & Tengerdy RP, 1983, Principles of solid state fermentation, In- The Filamentous Fungi, Vol. 4, Fungal Technology, JE Smith, DR Berry, & B Kristiansen (eds), Edward Arnold Publishers, London, pp 117-144. Mossel DDA, 1975, Water and microorganisms in foods: a synthesis, In- Water Relation of Foods, RB Duckworth (ed), Academic Press, New York, pp 347-361. Nagel FJ, Van As H, Tramper J & Rinzema A, 2002, Water and glucose gradients in the substrate measured with NMR imaging during solid state fermentation with Aspergillus orizae, Biotechnology and Bioenginering, 79, 654-663. Narayanan RM & Vu KT, 2000, Microwave measurement of moisture content in powdered foods, Journal of food Process Preservation, 24, 39-56
Nishio N, Tai K & Nagai S, 1979, Hydrolase production by Aspergillus niger in solidstate cultivation, European Journal of Applied Microbiology and Biotechnology, 8, 263-270. Northolt MD, Van Egmont HP & Paulsch WE, 1984, Ochratoxine: A production by some fungal species in relation to aw and temperature, Journal of Food Protection, 42, 485-490. Oostra J, Tramper J & Rinzema A, 2000, Model-based bioreactor selection for largescale solid-state cultivation of Coniothyrium minitans spores on oats, Enzyme and Microbial Technology, 27, 652-663. Pandey A, 2003, Solide-State fermentation, Biochemical Engineering Journal, 13, 81-84. Prosser Jl, 1990, Comparison of tip growth in prokaryotic and eukaryotic filamentous microorganisms, In- Tip growth in plants and fungal cells, Heath IB (ed), Academic Press, San Diego, pp 233-258. Quinn PY, 1985, A lipid phase separation model for low-temperature damage to biological membranes, Cryobiology, 22, 128-146. Raghavarao KSMS, Ranganathan TV & Karanth NG, 2003, Some engineering aspects of solid-state fermentation, Biochemical Engineering Journal, 13, 127-135. Raimbault M & Alazard D, 1980, Culture method to study fungal growth in solid fermentation, European Journal of Applied Microbiology, 9, 199-209. Raimbault M, 1981, In- Fermentation en milieu solide-Croissance de champignons filamenteux sur substrat amylac6 (O.R.S.T.O.M., Paris), pp 1-291. Ramesh MV & Lonsane BK, 1990, Critical importane of moisture content of the medium in alpha-amylase production by Bacillus licheniformis M27 in a solid-state fermentation system, Applied Microbiology and Biotechnology, 3, 201-205. Richard-Molard D, Bizot H & Multon JL, 1982, Water activity, essential factor of the microbiological evolution of foods, Science des Aliments, 2, 3-17. Ridder ER, Nokes SE & Knutson BL, 1999, Optimization of solid-state fermentation parameters for the production of xylanase by Trichoderma longibrachiatum on wheat bran in a forced aeration system, Transactions of the ASAE, 42, 1785-1790. Robertson NF, 1958, Observation of the effect of water on the hyphal apices of Fusarium oxysporum, Annals of Botany, 22, 159-173. Robertson NF & Rizvi SRH, 1968, Some observations on the water relations of the phyphae of Neurospora crassa, Annals of Botany, 32, 279-291. Robinson PM & Griffin PJ, 1977, Effect of restricted aeration on chemotropism, morphogenesis and polarity of lateral branch induction in Geotrichum candidum, Transactions of The Britisch Mycological Society, 68, 311-314. Sangsurasak P & Mitchell DA, 1998, Validation of a model describing two-dimensional heat transfer during solid-state fermentation in packed bed bioreactors, Biotechnology and Bioengineering, 60, 739-748.
Sato K, Nagatami M & Sato S, 1982, A method of supplying moisture to the medium in a solid state culture with forced aeration, Journal of Fermentation Technology, 60, 607-610. Saucedo-Castaneda G, Gutierrez-Rojas M, Bacquet G, Raimbault M & ViniegraGonzales G, 1990, Heat transfer simulation in solid substrate fermentation, Biotechnology and Bioengineering, 35, 802-808. Schwan liP, 1965, Electrical properties of bound water, Annals of New York Academy of Sciences, 125: 344-354. Scott WJ, 1953, Water relations of Staphylococcus aureus at 30~ of Biological Sciences, 6, 549-564.
Australian Journal
Scott WJ, 1957, Water relation of food spoilage microorganisms, Advances in Food Research, 7, 83-127. Sheridan JJ & Sheeman PJ, 1980, Development of a technique for the germination of the fungal spores, Irish Journal of Agricultural Research, 19, 155-159. Simatos D & Karel M, 1988, Characterization of the condition of water in foods: physicochemical aspects, In- Food Preservation by Moisture Control, CC Seow (ed), Elsevier Applied Science, London, pp 1-41. Smith J., 1978, A sexual sporulation in filamentous fungi, In- The Filamentous Fungi, JE Smith & Berry DR (eds), Edward Arnold, London, pp 214-235. Snow D, 1949, The germination of mould spores at controlled humidities, Annals of Applied Biology, 36, 1-13. Steudle E, Tyerman SD & Wendler S, 1983, Water relations of plant cells, In- Effects of Stress on Photosynthesis, R Marcelle, H Clijster & M Van Poucke (eds), Martinus Nijhoff, The Hague, pp 95-109. Suutari M, Liukkonen K & Laakso S, 1990, Temperature adaptation in yeasts 9the role of fatty acids, Journal of General Microbiology, 136, 1469-1474. Tabak HH & Cooke WM, 1968, The effects of gaseous environment on the growth and metabolism of fungi, Botanical Review, 34, 126-252. Tallu B, 1986, Aroma production, Postgraduate in Food Sciences, University of ClermontFerrand, France.
Taragano VM & Pilosof AMR, 1999, Application of Doehlert designs for water activity, pH, and fermentation time optimization for Aspergillus niger pectinolytic activities production in solid-state and submerged fermentation, Enzyme and Microbial Technology, 25, 411-419. Todd WG, 1972, Water deficits and enzymatic activity, In- Plant Response and Control of Water Balance, Vol. 3: Water deficits and plant growth, T.T. Kozlowski (ed), Academic Press, New York, pp 117-216. Todd GW, Water deficits and enzymatic activity, Water Deficits and Plant Growth, 3, 177-216.
Trinci APJ & Bandury GH, 1967, A study of the growth of the tall conidiophores of Aspergillus giganteus, Transactions of The Britisch Mycological Society, 50, 525-539. Trinci APJ, 1969, A kinetic study of the growth of Aspergillus nidulans and other fungi, Journal of General Microbiology, 57, 11-24. Trinci APJ, 1971, Influence of the peripheral growth zone on the radial growth rate of fungal colonies, Journal of General Microbiology, 67, 325-334. Trinci APJ & Collinge A, 1973, Influence of L-sorbose on the growth and morphology of Neurospora crassa, Journal of General Microbiology, 78, 179-192. Trinci APJ, 1974, A study of the kinetics of hyphal extension and branch initiation of fungal mycelia, Journal of General Microbiology, 81,225-236. Trinci APJ, 1978, Wall and hyphal growth, Science Progress, 65, 75-99. Troller JA, 1980, Influence of water activity on microorganisms in foods, Food Technology, 5, 76-82. Viesturs UE, Aspite AF, Laukevics JJ, Ose VP, Bekers, MJ, 1981, Solid state fermentation of wheat straw with Chaetomium cellulolyticum and Trichoderma lignorum, Biotechnology and Bioengineering Symposium, 11, 359-369. Von Meien OF, Luz LFL, Mitchell DA, Perez-Correa JR, Agosin E, FernandezFernandez M & Arcas JA, 2004, Control strategies for intermittently mixed, forcefully aerated solid-state fermentation bioreactors based on the analysis of a distributed parameter model, Chemical Engineering Science, 59, 4493-4504. Waggoner PE & Parlinge JT, 1975, Slowing of spore germination with changes between moderately warm and cold temperatures, Phytopathology, 65, 551-553. Wessels JGH, 1993, Wall growth, protein excretion and morphogenesis in fungi, New Phytologist, 123, 397-413. Wilson JM, Griffin DM, 1979, The effect of water potential on the growth of some soil basidiomycetes, Soil Biology & Biochemistry, 11, 211-212. Wolfe J & Steponkus PL, 1983, Tension in the plasma membrane during osmotic contraction, Cryoletters, 4, 315-322. Xavier S & Karanth NG, 1992, A convenient method to measure water activity in solid state fermentation systems, Letters in Applied Microbiology, 15, 53-55. Zimmermann U, 1978, Physics of turgot and osmoregulation, Annual Review of Plant Physiology, 29, 121-148. Zhu GL, Boyer JS, 1991, Turgot and elongation growth in Chara cells, Plant Physiology, 96,38.
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6.1 INTRODUCTION It is well known that the solid-state fermentation (SSF) is a new technology with which antibiotics, enzymes, fine chemicals can be obtained by new bioprocesses with improved efficiency (Giovannozzi-Sermanni & Porri 1989; Pandey et al., 2000) if compared to the classical submerged fermentations. SSF processes can be defined as "the growth of microorganisms, mainly fungi, on moist solid materials in the absence of free-flowing water"(Cannel & MooYoung 1980). In the last few decades SSF has grown quickly in interest and importance and has been used for the production of antibiotics, alkaloids, aroma compounds, plant growth factors, enzymes, biofuel, and also for the bioremediation of polluting compounds. To understand tiae importance of the SSF, following must be kept in mind: 9 the biological sustainability is associated to the atmospheric content of carbon dioxide. 9 the content of carbon dioxide in the atmosphere increases continuously making the chemical energy obtained by the photosynthesis in sufficient to control its rise to which a quote coming from fossil carbon utilization is added (Fig. 1). 9 the needs of chemical energy requested by human societies are increasing rapidly. 9 the availability of water is dependent on environmental conditions and it is decreasing in many countries. 9 celluloses, hemicelluloses, lignines, starch and oils could be utilized by new technologies to avoid their loss through wild uncontrolled biological processes.
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From the above considerations, it seems that the better controlled biological utilization of lignocelluloses by environmentally friendly applications can deeply contribute to improve the sustainability. The degradation of water insoluble copolymers has as first steps hydrolytic and oxyreductive reactions, occurring in three-phases (gaseous, liquid and solid phases) systems and can help to efficiently solve problems through SSF, since in recent years studies have demonstrated their superior product yields and simplified downstream processes (Pandey et al., 1999). These factors increase to the possibility of producing more stable products, with less energy requirements, and make SSF a very attractive alternative to the conventional liquid fermentation, especially in the developing countries. The use of solid matter has serious implications in the engineering aspect of bioreactor design and operation. It is interesting to note that few enzymes, necessary for the biosynthesis and biodegradation of the lignocelluloses have been working in nature at least since 350 millions of years, but until now they are poorly utilized by means of controlled biological processes. These enzymes belong to hydrolytic enzymes (cellulases, hemicellulases, polyphenolases, pectinases, etc.) and oxidative ones (polyphenoloxydases, peroxydases, etc.).
6.2 CHEMICAL, BIOCHEMICAL AND MICROBIOLOGICAL SHORT OUTLINES Lignocelluloses are copolymers, characterized by highly complex chemical structure. Celluloses, lignins and hemicelluloses, chemically linked each other,
contain large quantities of chemical energy. The agricultural and forestry resources provide immense quantities of such materials but the amount of unutilized lignocellulose can reach easily the 50%. Keeping in mind that more than 3000 million tons of cereal straws roughly are produced per year worldwide and that these residues are mostly disposed of by burning and humification, it results a terrific loss of energy. As a consequence, the chemical energy of unutilized lignocellulosic matter constitute a huge source of energy which could be used for many applications beside the buming and humification. Cellulose, homopolymer of 1,4-glucose units, hemicellulose, heterogeneous carbohydrate polymer, and lignin, polymer of phenylpropanoidic units interconnected by a great variety of linkages, contain energy which can be utilized by a series of biochemical breakdown reactions, fundamental aspect for efficient applications. Therefore, first of all it is necessary the depolymerization of the water insoluble lignocellulose takes place to produce soluble compounds, and this degradation can start by few enzymes which allow the formation of lower molecular weight water soluble copolymers (Crestini et al., 1998) (Fig.2). It is interesting to note that simple phenolic compounds can have also effects on redox enzymes activity (Giovannozzi-Sermanni 1981).
6.3 ROLE OF MAIN PARAMETERS IN SSF 6.3.1 General considerations Targeting a SSF production for a possible industrial interest, two are the ways to approach the problem:
Fig. 2. Pathways of biodegradation of lignocelluloses by enzymes.
the characteristics of the wanted products determine the choice of the starting matter, generally a low-cost agricultural resource simply available. the possibility to use huge amount of available residues encourages the development of new processes to produce value-added goods, by improving also the biological sustainability. Therefore, the choice of microorganisms is of great importance, which are dependent on parameters such as pH, temperature, moisture content, etc. Consequently the development of devoted bioreactors useful to utilize the set of parameters chosen for the process is of paramount importance. Also, some physical and engineering specifics not directly dependent on the biochemistry of the process must be considered, such as employed materials, analytical controls, economical factors, maintenance, pretreatment and downstream treatments, etc.
6.3.2 Parameters affecting the bioprocess The most important parameters characterizing an SSF process are the following"
water activity and moisture content of the substrate. This variable has influence on biodegradation processes, biosynthesis and secretion of metabolites (Perez-Guerra et al., 2003). temperature and heat transfer. This affects directly bioprocesses characteristics, spores germination, cells growth and the efficiency of the process. pH. It determines the enzyme activities, given that each of them can be dependent on different optimal pH values. aeration. It determines the 02 and CO2 concentration inside the bioreactor, regulating the removal of CO2 and volatile compounds (such as ethylene), the relative humidity, and it improves the heat transfer. nutrient diffusion. It affects the nutrient concentration and regulates the actions of enzymes over the solid substrate (normally water insoluble). mixing. It helps heat removal, gas exchange, water content, uniformity and influences the process conditions. septic conditions. It is required to avoid the release of the process organism in the environment and the entry of polluting microorganisms.
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particle size (density). It regulates the utilization of the substrate by the microorganism at a molecular level, the gas-liquid interfacial area and the thickness of the wet fungal layer. It makes the oxygen utilization dependent on this parameter (a too small particle size may interfere with microbial respiration, causing poor growth; a large particle size provides only a limited surface for microbial attack) (Pandey et a1.,1999).
physico-mechanical properties of the solid matrix. The matrix should have wide surface area and should stand gentle stirring or compression if required by the chosen fermentation to avoid sticking behaviour during the process.
microbiological inoculum. Its type, relative humidity, amount, etc. influence the growth rate.
biomass uniformity. It is of fundamental importance to maintain uniform biochemical reactions all over the biomass. morphology of the microorganism. The most important characteristics are to penetrate into a solid substrate with a low water activity, assimilating complex and variable mixtures of nutrients, the capacity of adherence and i.e. the presence or not of septum in the hyphae for mechanical resistance. Most of the above parameters are strictly interconnected, but few of them appear to be of major importance in the development of new processes.
6.3.2.1 Temperature and heat transfer Respiration during the growth, which is dependent to the oxygen consumption and CO2 formation, is highly exothermic and heat generation is directly related to the level of metabolic activities of the microorganisms. The removal of metabolic heat during large-scale SSF is one of the most critical issues since microbial growth is particularly sensitive to the rise of temperature, given that the heat generation produces thermal gradients (Schutyser et al., 2003; SaucedoCastafieda et al., 1990). Many approaches are available using different cooling techniques to enhance the heat transfer and to control the microbial growth, such as mixing, forced aeration, evaporative cooling, utilization of cooling jackets and additional cooling surfaces, that are just the most used systems to achieve the best thermal conditions. These approaches and their role in designing will be considered in detail in par. 6.4.
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6.3.2.2 Water activity and moisture content Water has a solvent function providing nutrients and scavenges wastes, and a structural function which, is involved in the stability and the function of the biological structures (Gervais & Molin 2003). Water in SSF systems is present in a complexed form within the solid matrix or as a thin layer either absorbed on the surface of the particles, or in the capillary region of the solid. The excessive lack of free water does not allow good diffusion of the nutrients and gas exchange, and can cause a loss of the functional properties of some enzymes and a disequilibrium on the metabolic chain of the cells. On the other hand, an excess of water can perturb the transport phenomena at cellular and macroscopical level. Water requirements should be defined in terms of water activity (aw), a thermodynamic parameter related to the chemical potential of water. Aw is well correlated to the relative humidity (RH) as follows: aw = RH/100 = P/P0 where p = vapour pressure of water in the substrate and P0 = vapour pressure of pure water at the corresponding temperature (Raimbault 1998). A reduction in aw normally extends the lag phase of the microbial growth, causing a low biomass production.
6.3.2.3 pH The substrate and medium acidity has great importance in the bioprocess, not only because the pH partly screens the microbial growth from a large number of competitors but also because partly gives a fight habitat for the microorganism. In fact the metabolic regulation routes, among other factors, may be controlled by pH (Fig. 3) (Giovannozzi Sermanni et al., 1978).
6.3.2.4 Aeration The rate limiting step in an aerobic submerged liquid fermentation (SmF) is usually the transfer of 02 from the gas phase to the liquid phase. Therefore the single most important consideration in the design and scale up of bioreactors for submerged liquid fermentations is to provide a sufficiently high rate of O2 transfer into the liquid medium. Regarding to the SSF processes, especially in packed bed bioreactors, both heat and mass transfer are important, and SSF in packed bed bioreactors, overheating is a major problem (Saucedo-Castaneda et al., 1992; Gowthaman et al., 1993), due to unidirectional flow of air. As the air passes through the column and removes heat from the substrate, the air warms up, loosing its cooling efficiency through the column. Consequently, a
Fig. 3. Influence of pH on the possible regulation of cellulose and lignin degradation by mycelial and microbial metabolism (pH stat) (modified from Giovannozzi et al., 1978). temperature gradient is established along the column with the highest temperature at the outlet end of the bed. In a rotating drum bioreactor, the gas exchange is obtained by passing the air through the biomass. In this way, it is possible to maintain a constant chosen 02 and CO2 value as shown in Fig. 4, and the total fluxed air during the fermentation and the gas exchange can be recorded continuously to maintain the reproducibility of the process. For example, after few days of fermentation the CO2 and the 02 levels can be modified and maintained at a chosen value. In an earlier study, Fung and Mitchell (1995) showed that maximum 02 uptake rates were higher in a baffled rotating drum than in an unbaffled one, so that 02 limitation could occur in the unbaffled drum too (Marsh et al., 1998).
6.4 GENERAL ASPECTS OF SSF BIOREACTOR DESIGN The use of solid matrix, either as an inert support or substrate support, has relevant implications on the engineering aspect of bioreactor design and operation (Robinson & Nigam 2003). Maximization of the rate of formation and the yield of product within the bioreactor are a key of the optimizing the bioprocess. Nevertheless, SSF bioreactor systems have not yet reached a high degree of
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Fig. 4. Control of O a and CO 2 levels in a rotating drum bioreactor by using fresh sterile air fluxes.
development, mainly due to the problems associated to the solid beds like poor mixing, heat transfer and material handling. Some of the desired features of a solid-state bioreactor system are the following (Raghavarao et al., 2003): the constitutive material has to be cheap, inert and resistant to the corrosion and abrasion. the system has to be preferably microbiological contamination-free to prevent accidental hazardous due to biological pollution. the control and regulation of the operational parameters must be efficient. the uniformity of biomass must be provided. the bioreactor design has to simplify the maintenance, the loading-unloading and the product recovery (according to the labour cost of the countries where the SSF process is developed). It is possible to classify the categories of bioreactor for SSF by their size and by the quantity of dry solid substrate involved, so that a lab-scale would process from few grams to few kilograms, a prepilot-scale from few to several kilograms, a pilot-scale several kilograms and an industrial-scale up to several tons. During the scaling-up of the process, the availability of bioreactors designs decreases considerably due to the reasons shown in 6.4.3 and 6.4.4.
6.4.1 Lab-scale SSF at laboratory-scale shows several biotechnological advantages, if compared to SmF, such as high fermentation productivity, high end-concentration of products, high product stability, low catabolic repression, cultivation of microorganisms able to grow on water-insoluble substrates, and often the demand on sterility is not requested (H61ker et al., 2004). It is also possible at lab-scale to remove properly the metabolic heat generated by the fermentation, keeping the culture vessel in a temperature-controlled environment (water bath, cooling jacket, etc.).
Approximately 90% of all industrial enzymes are produced by SmF, frequently using specifically optimized, genetically manipulated microorganisms. However, almost all these enzymes could also be produced in SSF using wild-type microorganisms (Filer 2001; Pandey et al., 2001). It has been shown that enzyme production in solid state is higher than in submerged fermentation (Viniegra-Gonz~ilez et al., 2003). It is very interesting also that the stability of the produced enzymes at high temperature or extreme pH, are better in SSF (Deschamps and Huet 1985; Acuna-Arguelles et al., 1995). Catabolite repression or protein degradation by proteases, severe problems in SmF, were often reduced or absent in SSF (Solis-Pereira et al., 1993; Aguilar et al., 2001). Since 1959, when the first example of laboratory-scale fermentor was described (Giovannozzi, 1959) (Fig. 5), studies on laboratory-scale system represent a powerful aid to develop SSF bioprocesses and a useful front of data for modelling the process.
The solid-state bioreactor f contains a metal net basket a which is filled with lignocellulosic matter. The funnel e may contain substrate useful for the growth of microorganisms. All the apparatus can be sterilized in a steam pressure oven. The substrate of funnel can be inoculated with microorganisms chosen for the trial. After few days the liquid culture is transferred into the bottom part of the bioreactor so that the matter contained in the basket is inoculated with a single chosen microorganism. Then the liquid phase is pumped away through the r tap. The bottom b part of the bioreactor can be utilized to contain different kinds of liquids useful for the trial. Through d and c taps equipped with sterile filters it is possible to control the gaseous phase composition of the bioreactor, particularly oxygen and carbon dioxide. Hence this solid state bioreactor, the first described in the scientific literature, permits to control and to follow the bioconversions of lignocellulosic matter and to test the effects of different microorganisms on the biodegradation of them.
Fig. 5. Lab-scale fermenter (Giovannozzi 1959).
It is significant to note that recent equipments organized in batteries and computer controlled (Fig. 6), useful for a systematic investigation, utilizes single units very similar to the first one already shown. Laboratory equipments such as Petri dishes, jars, wide mouth Erlenmeyer flasks, Roux bottles, roller bottles are of some help for their simplicity and easiness in handling. In the last few decades, more complex lab-scale units have been developed, such as the one patented by an OSTROM team between 1975-1980. It consists of a small column filled of inoculated medium, humidified, and thermoregulated by a waterbath. It is useful for screening studies and for the first step of parameters optimization. The small quantity of used medium (few grams), and the geometry of the glass column guarantee an easy maintenance of the temperature in the reactors. The design of this reactor, however, does not permit sampling during the fermentation and hence, during the process, one entire column has to be utilized for each analysis. A new generation of small reactors was developed by an INRA-team in France. Such reactors have a working volume of about 1 1, a relative humidity probe, a cooling coil on the air circuit and a heating cover for the vessel (Fig. 7). These changes enhanced the regulation of the water content during the process. Each reactor is automatically controlled by a computer. Several teams have designed bioreactors based on continuous mixing of the solid substrate/support. Such characteristic is suggested by the aptitude of some filamentous fungi to agglomerate. Therefore, to avoid such behaviour which alter deeply the biological efficiency the mixing can be useful. The bioreactors can be perforated drums (Fig. 8-1), like the one described by Kalogeris et al., (1999), rotating drums (Fig. 8-2), or horizontal paddle mixers (Fig. 9). All those drum bioreactors are designed to allow adequate mixing of the medium and good aeration.
Fig. 6. Schematic packed column bioreactor system. 1) air pump, 2) air filter, 3) humidifier, 4) air distributor, 5) battery of columns in water bath, 6) silica gel columns, 7) gas sampler, 8) chromatograph, 9) PC unit (redrawn from Medeiros et al., 2001).
Fig. 7. Schematic and photography of a lab-scale sterile fermenter: 1) heating cover, 2) insulating jacket, 3) biomass temperature probe, 4) stainless steel sieve, 5) air inlet temperature probe, 6) relative humidity probe, 7) heaters, 8) level probe, 9) water temperature probe, 10) massic flow meter (redrawn from Durand 2003).
Fig. 8. Schematic of a rocking drum bioreactor (1), a rotating drum bioreactor (2), and photography of a lab-scale battery of drums controlled by a PC unit device (3).
Fig. 9. Photography of a paddle mixer. Schematic of a stirred horizontal bioreactor: 1) air inlet, 2) air outlet, 3) cooling jacket, 4) paddles, 5) motor, 6) temperature probe (redrawn from Durand 2003).
With or without a water-jacket, this type of reactors is required for the continuous mixing to increase the contact between the reactor wall and the solid medium and also to provide oxygen to the microorganisms. For rotating drum bioreactors, as an horizontal cylinder, the mixing is obtained by the tumbling motion of the solid medium which may be aided by baffles on the inner wall of the rotating drum (perforated or not). With these bioreactors, agglomeration of substrate particles during the growth of the mycelium can happen.
6.4.2 Pre-pilot and pilot plants Only a few designs of bioreactors have been studied and applied to pilot-scale, or industrial level. The limited application of SSF for large-scale is due to some further important parameters present for the scaling-up, such as: the mycelium hyphae, which can be damaged by heavy mechanical stirring, particularly if they have no septa, allowing only few possible designs to respect the aeration and heat removal needs. the solid medium, which can agglomerate during the process causing shrinkage, air channelling and problems during the operations. That makes difficult the heat removal and the gas transfer and severely restricts the design strategies available. the procedures of inoculation, control and the difficulties associated to the sterilization or pasteurization of large volumes as well. Particularly beyond three days of mycelial growth, it could be prohibitive working in non-sterile conditions (Fig. 10). 9 the versatility of the reactor for a flexible usage in different conditions.
Fig. 10. Scheme of an SSF pilot plant and related controls.
the maintenance and the procedures of filling, emptying, cleaning of the bioreactor. 9 the maintenance of uniformity, difficult for large volumes of biomass. Few of the previous described bioreactors have been used to develop the industrial and pilot plants that can be divided in categories based on the mixing and aeration strategies adopted (Table l) (Mitchell et al., 2000): 9 static, pulsed mixed, continuosly mixed. 9 unforced or forced aeration (trough the biomass). Table 1. Summary of most used bioreactor typologies.
6.4.2.1 Static beds without forced aeration (tray bioreactors) This category is the oldest and the simplest in design, typified by the tray fermenters used in the Koji process. The solid substrate is loaded on trays (made of wood, plastic or metal, perforated or not) in thin layers (typically 5 -
15 cm) and placed one above the other with a gap of few centimetres into a thermostated room as shown in Fig. 11. There is fully empirical and experimental evidence of poor heat and mass transfer in trays, limiting the thickness of the substrate bed, that must be not more than a few centimetres. Hence, such reactors are restrictive in the volume of the solid matrix used: only thin layer can be used to avoid overheating and to guarantee aerobic conditions. Temperature and relative humidity are the only external parameters that can be controlled. The scale-up in this case is easy (increasing the number of trays used), but requires large operational area, intensive labour and it is difficult to apply for sterile processes.
Fig. 11. Schematic of a koji-type reactor: (1) water inlet, (2) UV tube, (3) (4) (5) air blowers, (6) (7) air filters, (8)air outlet, (9) humidifier, (10) heater, (11) Air inlet, (12) Trays, (redrawn from Durand 2003).
6.4.2.2 Static beds with forced aeration (packed beds) In a packed-bed bioreactor, conditioned air is usually blown through a sieve which supports the substrate. Experimental work demonstrates that the temperature gradients limit considerably the bioreactor performance. These bioreactors have been reported being interesting for their efficient process controls, especially for heat removal, which is due to an ample exchange surface. Strategies to prevent overheating problems have been examined (Ashley et al., 1999), finding more useful the mixing if tolerated by the microorganism than the periodic air reversal. Packed-bed bioreactors show some limitations such as irregular growth and poor heat removal if scaled up (Robinson & Nigam 2003). Targeting a particularly efficient heat removal, Roussos et a1.,(1993) developed the Zymotis bioreactor equipped with vertical rectangular cooling plates closelyspaced and inserted directly into the bed (Fig. 12). The geometry of such type
of bioreactor is particularly promising, but the loading-unloading operations can be uneasy and appears difficult to obtain septic conditions when large volumes are utilized.
Fig.12. Zymotis bioreactor; photography(Durand 2003) and schematic.
6.4.2.3 Pulsed mixing without forced aeration (discontinuously rotating drum) The drum bioreactor intermittently rotates operating like a tray bioreactor during the static periods.The pulsed stirring prevents the agglomeration of the mycelium and the shear is less effective on the mycelium than in a continuous rotating drum. This design has been demonstrated scalable up to 4 m 3 (Fig. 13). This rotating drum can work intermittently or continuously and is equipped by an internal sterile aeration system that allows air circulation trough the substrate if required, a regulation of internal gas phase composition (automatically or manually controlled), a cooling/heating jacket and a sterile inoculation system. By the way it shows some limitations in heat transfer control, that is the greatest barrier in scaling up.
6.4.2.4 Pulsed mixing with forced aeration (intermittently stirred beds) It is possible to enhance the homogeneity of the cell population and the substrate concentration in the SSF systems adopting sequential mixing and by imposing forced aeration through the solid substrate it is possible to allow the control of water content, water activity, the removal of volatile compounds, CO2 and
Fig. 13. Rotating drum bioreactor (4m 3) at University of Tuscia; inside view of the bioreactor with complete mycelial colonization at the end of a fermentation before unloading (Giovannozzi-Sermanni et a11994).
heat generated during the fermentation. The geometry is similar to the one used for packed bed, but it includes a mixing system for the biomass like a screw or an other kind of agitation device (Fig. 14). The capacity of such kind of bioreactor has been scaled up to several tons. The intermittently stirred bed bioreactors are promising for non-sterile processes, but their design can be complex and not simply scalable, if sterile conditions are needed.
6.4.2.5 Continuously mixed without forced aeration (continuously rotating drums) This type of bioreactor consists of a continuously rotating horizontal drum that holds the substrate bed. It can be equipped with baffles and within the air is not forcefully blown through the bed. The effect of the rotational speed and the other mixing parameters on the fermentation was largely studied by several
Fig. 14. Schematic of a cylindrical (1), conical (2), screw mixers and an helical blade mixer (3).
teams (Schutyser 2003). To increase the performance of such bioreactor, it is possible to use a baffled geometry and/or use high rotational rates (up to 1050 rev. min 1).
6.4.2.6 Continuously mixed with forced aeration The most important types of this category of bioreactor are: 9 the rocking drum bioreactor. 9 the gas-solid fluidized bed. 9 the continuously stirred aerated bed. Frequently, water is replenished, by spraying it as a fine mist on the biomass or dripping it into the substrate trough perforated tubes. This allows high evaporative cooling. It has been reported that the continuous mixing improves the heat transport to the fermenter wall reducing the need of evaporative cooling and, consequently, the problems related to the substrate drying. The evaporative cooling retains its importance for large scale mixed bioreactors (Nagel et al., 2001).
6.4.2. 7 Other designs In the last few years, some interesting unusual novel designs for SSF bioreactor have been proposed. These designs are based on unusual features and for this reason, they differ visibly from the previous typologies. A patented solid-state fermentation based on periodic air-forced pressure oscillation (SFPAPO) has been described by Chen & Sun (Fig 15). An immersion bioreactor, based on intermittently immersion in a liquid medium has been described (Rivela et al., 2000; Rodriguez-Couto & Sanrom~in 2006). It consists of a jacketed cylindrical
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glass vessel with a round bottom, inside which several wire mesh baskets filled with colonized support are placed. They can move upwards and downwards by means of a pneumatic system, remaining more time outside than inside the medium (Fig. 16).
Fig. 16 Scheme of an immersion bioreactor (mechanical agitation; humidified air): (1) medium, (2) sampling port, (3) air inlet, (4) water cooling, (5) compressor, (6) pneumatic system, (7) gas exit, (8) time controller. (redrawn from Rivela et al., 2000).
6.4.3 Scaling-up SSF scaling-up, essential for uses at industrial scale, raises severe engineering problems due to the increase of temperature, pH, 02, substrate and moisture gradients. Hence, most published reviews also focus on progress towards industrial engineering. The scale-up of bioreactors is usually based on empirical criteria, related to transport processes (Hsu & Wu 2002), but the application of mathematical modelling techniques to describe the phenomena within the system is the basis of the most significant improvements in designing and scaling-up SSE Lenz et al., (2004) and Pandey (2003) have shown to these be a powerful aid for the designing and the defining of large-scale bioreactors (Raghavarao et al., 2003). A large-scale prototype of an intermittently stirred bed ( l t o n capacity) designed at INRA has been described by Durand & Chereau in 1988 (Fig. 17). An important concept in the design a bioreactor is the possibility to let take place in one single vessel as many major operations as possible. The pilot plant described by Grant et al., in 1978 is a good example in this respect. In this bioreactor, it was possible to hydrolize (121~ 30min, 0.5N H2SO 4, 7:3 liquid:solid) the substrate (100kg of ryegrass straw per batch), to treat it with ammonia to raise the pH (to 5.0), to inoculate it (with Candida utilis) and to conduct the fermentation holding the material stationary with air blowing up through it, as shown in Fig. 18.
Fig.17 A. Schematic of a large-scale mixed reactor: (1)inoculated biomass, (2) agitation device, (3) probes, (4) air inlet, (5) cooling water, (6) steam, (7) air conditioner, (8) blower, (9) regulator, (10) (11) valves, (12) screw conveyer, (13) outlet (redraw from Xue et al., 1992) B. photographies of a large scale bioreactor (INRA-Dijon, France) (Durand 2003, Durand et al., 1996),
On the same concept, a novel efficient design of integrated matrix bioreactor, called the PLAFRACTOR TM, consisting of a computer controlled device, using complex fermentation control algorithms, has been patented (Suryanarayan & Mazumdar 1999; Suryanarayan 2001). All the operation, such as sterilization, cooling, inoculation, control of fermentation condition, extraction of the product and post-sterilization of the substrate, are all done in one single equipment, maintaining all the advantages of SSF (Fig. 19). A particularly interesting novel design was scaled-up and reported by Hongzhang et al., (2002). It consists of a cylindrical steel container with the capacity of 70 m 3, used as the fermentation vessel, loaded by trays made up of stainless steel mesh placed horizontally, or vertically. In order to enhance the biological
Fig. 18. Pilot plant (2,270 I): operations and photography (Grant et al., 1978). activity by external stimulation, thermal and mass transfers, the fermentor is supplied by two dynamic changes of air consisting of internal/external circulation and periodic air pressure pulsation (Fig.20). This system provides sufficient gas exchanges, more room for fungal propagation and efficient heat removal without disrupting the mycelia. On these basis, the reactor design was scaledup from 8 1 to 50 1, 25 m 3 and 70 m 3.
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Fig. 19 Plafractor TM bioreactor: schematic with; (1) fluids into communicating channels, (2) fluids out from non-communicating channels, (3) air/steam/ inoculum in, (4) vent, (5) extraction fluid in, (6) extract (Suryanarayan 2003).
Fig. 20 Photography of of the 70 m3 industrial bioreactor (a); schematic diagram of external (b); and internal (c); circulation of (d): air; schematic of the reactor: 1. door, 2. trays, 3. vessel, 4. fan system; (e); diagram of the periodic pressure changes (drawn from Hongzhang et al., 2002).
6.5 APPLICATION One interesting example of the application of SSF enzymes production is given by the preparation of cellulose for paper mills, where the opening of the fibres needs large amounts of thermal, mechanical and chemical energy. Enzymes produced by SSF of wheat straw have been used to prepare paper pulps from annual plant residues. By the rotating drum bioreactor after seven days of fermentation with a Lentinus edodes strain, a well colonized biomass is obtained (Fig. 14). With the aid of a press, it is squeezed and the liquid phase is used as a source of enzyme, particularly redox enzymes. Enzymatic mixture applied to annual plant residues have excellent technical properties of high yield paper obtained with kenaf bast strands, cereal straws. With corn stalks (Giovannozzi Sermanni et al., 1994) remarkable improvements of freeness and strength properties with respect to the control are also obtained, as well as a higher lignin extractability. Previous investigations, carried out on wheat straw and corn stalks, showed that the enzymatic incubations produced chemical modifications, which were not evident after the pre-treatment only. In fact, positive effects, in terms of lignin extractability, were recorded after alkaline cooking. This phenomenon suggested the possibility of a lignin functionalization, which rendered it more extractable under alkalineconditions and/or a physical modification of the biotreated material, such as an enhanced porosity, which facilitated the accessibility of the cooking liquor, thereby improving its effectiveness. The cellulose content of enzyme treated-samples (ET) did not differ from the corresponding controls, confirming the poor cellulolytic capability of the Lentinus edodes strain. By incubating recycled fibers with enzymatic cocktails containing cellulases and hemicellulases, the results suggest that the enzymes could act on the surface of the fibers (peeling effect), removing those components with a great affinity for water, poorly contributing to the hydrogen-bonding potential of fibers (Pommier 1989). The biotreatments have poor, or no effects on the opacity and brightness, whereas the latter parameter was reduced by 20 and 15% in wheat straw and corn stalks samples, respectively. The phenomenon increases the strength properties accompanying reduced optical properties during biomechanical pulping of loblolly pine chips (Akhtar et al., 1992; 1993). The enzyme treatment show a significant energy savings during fiberization and refining. The results obtained by using hexoenzymes allows to obtain the following main results: the amounts of alkali employed in the cooking process for enzymaticallytreated samples is reduced by 40 % with respect to the untreated controls
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(4% vs 7% NaOH on o.d. weight basis). All comparisons are made at the same freeness values of pulps (30-35 S.R. degrees). significant energy savings during fiberization and refining operation (50%) are observed in enzyme treated samples. no significant differences in the optical properties are observed between the controls and the enzymatically-treated samples, with the exception of kenaf and wheat, being the brighmess values of ET samples lower than the corresponding CT samples.
6.6 CONTROLS Monitoring these processes requires the measurement of environmental parameters (temperature, pH, water content and activity) and the carbon cycle (biomass, substrate concentration, CO2). However, given the complexity and heterogeneity of the solid medium, these variables are not easily accessible and measurable (Bellon-Maurel et al., 2003). Temperature sensors are generally inserted radially at various distances from the centre of the fermentor and linked to control systems. At the industrial scale, temperature regulation is linked to the moisture content of the solid phase. Direct measurements of temperature, pH, and water content are considered employing classical sensors, and indirect measurements of the biomass by respirometry or pressure drop (PD). More recent methods have been tested and successfully tested, such as: aroma sensing, infrared spectrometry, artificial vision, and tomographic techniques (X-rays, Magnetic Resonance Imaging or MRI). Therefore, the study and development of novel on-line methods and innovative applications of methods with a potential to measure parameters in SSF are an important task to improve the performance of the bioreactors.
6.7 CONCLUDING REMARKS The abundance of scientific literature on the solid-state bioreactors makes difficult to organize a comprehensive treatment of the issues given the complexity of the matter. Many solid materials can be utilized for SSF such as soils, animal residues, hides, but without any doubt the most attractive solid-state substrates for new processes are the lignocelluloses, present all over the Planet. By keeping in mind that the amounts of agriculture residues can reach up to the 50% of totally produced biomass, the paramount importance of the SSF is obvious for utilizing the enormous amount of available chemical energy improving at the same time the biological sustainability.
The practical approach for the production of metabolites and enzymes can be related to different areas (paper deinking, paper recycling, agricultural residues utilization, pesticides biodegradation, fodders, olive and seeds oils residues, pruning, fuels, paper pulp production, etc.) and each of them can require some different sets of biotechnological conditions. As it results from the data of the scientific literature, for obtaining profitable results, it is necessary to have dedicated bioreactors, which can take into account same particular characteristics of the new processes such as hyphen fragility if filamentous fungi are used and/or dissipation of heat due to the metabolic respiration. Hence, the CO2/O2 ratios of gas phase inside the bioreactor are important to judge and to define the more useful bioconversion conditions. In fact, these ratios can describe the bioreactor like a living cell, where the biochemical activity can determine different respiratory quotients. Nevertheless, the description in the literature of many different solid state bioreactors suggests that a bioreactor suitable for all the bioconversion conditions seems still under progress, being perhaps the working flexibility the best aspect to achieve.
Acknowledgements Giovanni Giovannozzi shows appreciation and thanks to N. Tiso for the hard work on the literature references.
Bibliography Acuna-Arguelles ME, Gutierrez-Rojas M, Viniegra-Gonzdlez G & Favela-Torres E, 1995, Production and properties of three pectinolytic activities produced by Aspergillus niger in submerged and solid-state fermentation, Applied Microbiology and Biotechnology, 43, 808-814. Aguilar CN, Augur C, Favela-Torres E & Viniegra-Gonzdlez G, 2001, Production of tannase by Aspergillus niger Aa-20 in submerged and solid-state fermentation: influence of glucose and tannic acid, Journal of Industrial Microbiol Biotech, 26, 296-302. Akhtar M, Attridge MC, Myers GC, Kirk TK & Blanchette RA, 1992, Biomechanical pulping of loblolly pine chips with different strains of the white-rot fungus Ceriporiopsis subvermispora, Tappi Journal, 105-109.
Akhtar M, Attridge MC, Myers GC & Blanchette RA, 1993, Biomechanical pulping of loblolly pine chips with selected white-rot fungi, Holzforschung, 47, 36-40. Ashley VM, Mitchell D A & Howes T, 1999, Evaluating strategies for overcoming overheating problems during solid-state fermentation in packed bed bioreactors, Biochemical Engineering Journal, 3, 141-150.
iii!!!!i!i!!!i. . . .!!!!!!H . . . . . . . .!!!!!!!!!! .... ............................................................ !!!!!!!!!!!!!!! BeUon-Maurel V, Orliac O & Christen P, 2003, Sensors and measurements in solid state fermentation: a review, Process Biochemistry, 38, 881-896. Cannel E & Moo-Young M, 1980, Solid state fermentation systems, Process Biochemisrty, 15,2-7. Crestini C, Sermanni GG & Argyropoulos DS, 1998, Structural modifications induced during biodegradation of wheat lignin by Lentinula edodes, Bioorganic & medicinal Chemistry, 6, 967-973. Deschamps F & Huet MC, 1~85, Xylanase production in solid-state fermentation: a study of its properties, Applied Microbiology and Biotechnology, 22, 177-180. Durand A, 2003, Bioreactor designs for solid state fermentation, Biochemical Engineering Journal, 13, 113-125. Durand A & Chereau D, 1988, A new pilot reactor for solid-state fermentation: Application to the protein enrichment of sugar beet pulp, Biotechnology and Bioengeneering, 31,476-486.
Durand A, Renaud R, Maratray J, Almanza S & Diez M, 1996, INRA-Dijon reactors for solid-state fermentations: design and applications, Journal of Industrial Scientific Research, 55, 317-332. Filer K, 2001, The newest old way to make enzymes, Feed Mix, 9, 27-29. Fung CJ & Mitchell DA, 1995, Baffles increase performance of solid state fermentation in rotating drums, Biotechnology Techniques, 9, 295-298.
Gervais P & Molin P, 2003, The role of water in solid-state fermentation, Biochemical Engineering Journal, 13, 85-101. Giovannozzi-Sermanni G, 1959, Un dispositivo atto allo studio dei processi trasformativi dei materiali solidi, Attualit~t di laboratorio, AnnoV No. 1. Giovannozzi-Sermanni G, Basile G & Luna M, 1978, Biochemical changes occurring in the compost during growth and reproduction of Pleurotus Ostreatus and Agaricus Bisporus, Mushroom Science X (Part II), Proceeding of the Tenth International Congress on the Science and Cultivation of Edile Fungi, France. Giovannozzi-Sermanni G, D'Annibale A, Perani C, Porri A, Pastina F, Minelli V, Vitale NS & Gelsomino A, 1994, Characteristics of paper handsheets after combined biological pretreatments and conventional pulping of wheat straw, Tappi Journal, 77, 151-157. Giovannozzi-Sermanni G, D'Annibale A, Porri A & Perani C, 1992, Depolymerization of water soluble lignocellulose by mycelium, culture broth and phenol-oxidases of Lentinus edodes, Agroindustry Hi Tech, 3, (6), 39-42. Giovannozzi-Sermanni G & Luna M, 1981, Laccase activity of Agaricus Bisporus and Boletus Ostreatus, Mushroom Science XI, Proceeding of the Eleventh International Scientific Congress on the Cultivation of Edile Fungi, Australia.
Giovannozzi-Sermanni G, Perani C & Porri A,1990, Biodelignification and metabolites production in different solid-state fermentation condition, Biotechnology in pulp and paper manufacture, Ed. Chang HM & Kirk TK, Butterworth Heinemann, 47-55.
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Giovannozzi-Sermanni G & Porri A, 1989, The potentiality of solid-state biotransformation of lignocellulosic materials, Chimicaoggi, March, 15-19. Gowthaman MK, Ghildyal NP, Raghava Rao KSMS & Karanth NG, 1993, Interaction of transport resistances with biochemical reaction in packed bed solid state fermenters: the effect of gaseous concentration gradients, Journal of Chemical Technology and Biotechnology, 56, 233-239. Grant GA, Han YW & Anderson A W, 1978, Pilot-scale semisolid fermentation of straw, Applied and Environmental Microbiology, 35 (3), 549-553. Hiilker U, Hiifer M & Lenz J, 2004, Biotechnological advantages of laboratoryscale solid-state fermentation with fungi, Applied Microbiology and Biotechnology, 64,175-186.
Hongzhang C, Fujian X, Zhonghou T & Zuohu L, 2002, A novel industrial-level reactor with two dynamic changes of air for solid-state fermentation, Journal of Bioscience and Bioengineering, 93 (2), 211-214. Hsu Y & Wu W, 2002, A novel approach for scaling-up a fermentation system, Biochemical Engineering Journal, 11, 123-130. Kalogeris E, Fountoukides G, Kekos D & Macris BJ, 1999, Design of a solid-state bioreactor for thermophilic microorganisms, Bioresourse Technology, 67, 313-315. Lenz J, Hiifer M, Krasenbrink J-B & Hiilker U, 2004, A survey of computational and physical methods applied to solid-state fermentation, Applied Microbiology and Biotechnology, 65, 9-17.
Marsh A J, Mitchell DA, Stuart DM & Howes T, 1998, O2 uptake during solid-state fermentation in a rotating drum bioreactor, Biotechnology Letters, 20 (6), 607-611. Martinez AT, Camarero S, Guillen F, Gutierrez A, Munoz C, Varela E, Martinez M J, Barrera JM & Ruel K, 1994, Progress in biopulping of non-woody materials, Chemical, enzymatic and ultrasctructural aspects of wheat straw delignification with lignolytic fungi from the genus Pleurotus, FEMS Microbiological Reviews, 13 (2-3), 265-274. Medeiros ABP, Pandey A, Christen P, Fontoura PSG, de Freitas RJS & Soccol CR, 2001, Aroma compounds produced by Kluyveromyces marxianus in solid state fermentation on a packed bed column bioreactor, World Journal of Microbiology & Biotechnology, 17, 767-771. Mitchell DA, Krieger N, Stuart DM & Pandey A, 2000, New developments in solid-state fermentation II. Rational approaches to the design, operation and scale-up of bioreactors, Process Biochemistry, 35, 1211-1225. Nagel F-JJI, Tramper J, Bakker MSN & Rinzema A, 2001, Temperature control in a continuous mixed bioreactor for solid-state fermentation, Biotechnology and Bioengineering, 72 (2), 219-230.
Pandey A, 2003, Solid-state fermentation, Biochemical Engineering Journal, 13, 81-84.
Pandey A, Soccol CR & Mitchell D, 2000, New developments in solid-state fermentation: I-bioprocesses and products, Process Biochemistry, 35, 1153-1169. Pandey A, Soccol CR, Rodriguez-Leon JA & Nigam P, 2001, Solid-state Fermentation in Biotechnology: Fundamentals and Applications, Asiatech, New Delhi.
Pandey A, Selvakumar P, Soccol CR & Nigam P, 1999, Solid-state fermentation for the production of industrial enzymes, Current Science, 77 (1), 149-162. Prrez-Guerra N, Torrado-Agrasar A, L6pez-Macias C & Pastrana L, 2003, Main characteristics and applications of solid substrate fermentation, Electronic Journal of Environmental, Agricultural and Food Chemistry, 2 (3), 343-350. Pommier J-C, Fuentes J-L & Goma G, 1989, Tappi Journal, 72 (6), 187-191. Raghavarao KSMS, Ranganatham TV & Karanth NG, 2003, Some engineering aspects of solid-state fermentation, Biochemical Engineering Journal, 13, 127-135. Raimbault M, 1998, General and microbiological aspects of solid substrate fermentation, Electronic Journal of Biotechnology, 1 (3), 15. Rivela I, Rodrigez Couto S & Sanrom~n A, 2000, Extracellular ligninolytic enzyme production by Phanerochaete chrysosporium in a new solid-state bioreactor, Biotechnology Letters, 22, 1443-1447.
Robinson T & Nigam P, 2003, Bioreactor design for protein enrichment of agricultural residues by solid-state fermentation, Biochemical Engineering Journal, 13, 197-203. Rodriguez Couto S & Sanrom~n M A, 2006, Application of solid-state fermentation to food industry - A review, Journal of Food Engineering, 76 (33), 291-302 Roussos S, RaimbaultM, Prebois J-P & Lonsane BK, 1993, Zymotis, a large scale solidstate fermenter, Applied Biochemistry and Biotechnology, 42 (1), 37-52. Saucedo-Castafieda G, Gutirrrez-Rojas M, Bacquet G, Raimbault M & ViniegraGonz~lez, 1990, Hest transfer simulation in solid substrate fermentation, Biotechnology and Bioengineering, 35 (5), 802-808. Saucedo-Castafieda G, Lonsane BK, Navarro JM & Roussos S, 1992, Applied Microbiology and Biotechnology, 37, 580-582. Schutyser MAI, 2003, Mixed solid-state fermentation: numerical modelling and experimental validation. Schutyser MAI, Weber FJ, Briels WJ, Rinzema A & Boom RM, 2002, Heat and Water Transfer in a Rotating Drum Containing Solid Substrate Particles, Biotechnology and Bioengineering, 82 (5), 552-563. Solis-Pereira S, Favela-Torres E, Viniegra-Gonz~lez G & Gutierrez-Rojas M, 1993, Effect of different carbon sources on the synthesis of pectinases in Aspergillus niger in submerged and solid-state fermentation, Applied Microbiology and Biotechnology, 39, 36-41.
Suryanarayan S, 2001, In: Proceeding of the International Conference on New Horizons in Biotechnology, Trivandrum, April 18-21. Suryanarayan S, 2003, Current industrial practice in solid state fermentations for secondary metabolite production: the Biocon India experience, Biochemical Engineering Journal, 13, 189-195.
Suryanarayan S & Mazumdar K,1999, Solid-state fermentation, World Patent no. WO 99/57239.
Viniegra-Gonz~iles G, Favela-Torres E, Aguilar CN, R6mero-Gomez S, Diaz-Godinez & Augur C, 2003, Advantages of fungal enzyme production in solid state over liquid fermentation systems, Biochemical Engineering Journal, 13, 157-167. Xue M, Liu D, Zhang H, Qi H & Lei Z, 1992, A pilot process of solid state fermentation from sugar beet pulp for the production of microbial protein, Journal of Fermentation and Bioengineering, 73 (3), 203-205.
i i i!i!!
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Instrumentation and Control in SSF
,, iiiiii
Wilerson Sturm, Dario Eduardo Amaral Dergint & Carlos Ricardo Soccol
i i Di' 7.1 INTRODUCTION This chapter has the purpose of explaining some of the Instrumentation and Control concepts and their application in solid-state fermentation. When dealing with instrumentation, it is important to keep in mind that it could be divided in four parts: Sensors, Actuators, Control, and Communication Network. Some of the newest technologies appear first in industrial sensors and controlling systems, indeed some of them are specific necessities developed. Industrial automation and control demands large amounts of investment, thus these devices suppliers do not have doubts about using the more updated technology, even if costs are high. However, the usual sensors and control devices are more and more cost effective due to electronic industry development and the demand and supply behavior. Nowadays, it is possible to choose between the centralized or distributed control systems. According to Rana and Taneja (1988), in the centralized control system, there is only one control device, but with high velocity and processing power, which is responsible for analyzing all the process signals and making decisions. The distributed control system normally uses some industrial network to interconnect the sensors, controllers, operator terminals, and actuators, which embraces the number of parts of a controlled process. Smith (2004) asserts that in the future, the computer will be an integral part of most bioreactor systems.
7.2 SENSORS This section discusses about the usual sensors and some specific ones, but the approach is only for the industrial processes or pilot plants, because the sensor could mean a large scope of devices. Thus, here we will focus only at industrial variables.
According to Yacynych and Twork (1990), improved sensor technology could be the driving force for new control strategies development, which could result more productive fermentations. However, there is a lack of good sensor probes that allow on-line analysis on the chemical components of the fermentation process, what means difficulties in real time control(Smith 2004). Yacynych and Twork (1990) have described the challenges to develop sensors, which could be readily implemented for more effective process control. Other feature to take into account is the necessity of sterilization when working with a bioreactor, hence, any sensor must be capable of sterilization conditions in situ, during steam sterilization for instance, or remotely, before being applied to the process (Bryce and Mansi 1999).
7.2.1 Temperature sensors Temperature variable control or, at least, monitoring is present in almost every industrial plant in (Sturm 2004). It has been stated that any SSF control system should include temperature measurements, for instance monitoring the temperature distribution and measuring inlet and outlet air temperature so that the energy and water balances could be kept under control (Pandey 2004). There are many types and protection constructions for temperature probes, but two of them are more usual in industrial applications: thermocouples and Ptl00 (Pandey 2004). Normally, these devices are externally protected with a stainless steel tube, or even ceramic materials tubes depending on the application conditions. Thus, an external protection with stainless steel could be appropriate for SSF process, taking into account the chemical components and sterilization. 7.2.1.1 Thermocouple A thermocouple construction is very simple. Two different metallic, or alloy, wires are welded at one edge, called hot junction and the other edge, called as the cold junction, is kept opened. Discovered in 1821 by T.J. Seebeck, the socalled Seebeck Effect could be explained as the appearance of a low electrical voltage signal when there is some difference between the temperature at the hot junction and the cold one, which is connected to the instrument. Because of the proportionality with the difference, it is necessary to measure the temperature, close to the instrument or cold junction, and add to the final result. Its installation must be made under strict technical conditions to use this sensor, because an inversion, bad union, or different materials used as conductors could result in error. Low cost, wide measuring range and its fast and linear response are responsible for their popularity among the process engineers. The more usual are the types called T, copper and constantan, type J, iron and constantan, and K, chromel and alumel alloys, depending on the temperature range and the costs. Nowadays, the low signal generated in their terminals is not quite a
problem because of the new high input impedance circuits and the use of programmable microcontrollers, instead of circuitry based equipments (Sturm 2004).
7.2.1.2 PtlO0 or RTD The Ptl00 or RTD, Resistance Thermometer Detector, construction is based on a kind of insulating ceramic material with a Platinum wire winding around it. The signal present in its terminals is an electrical resistance directly proportional to the temperature. Ptl00 is a standard; Pt comes from Platinum and the number 100 is 100 ohms at 0~ with a variation rate of 0.4 ohm per degree Celsius. Ptl00 are stable, precise, with fast response, and do not need periodic calibration, although they are more expensive and fragile compared to thermocouples. This fragility is due to the insulating base, which could disrupt when under strong vibration or mechanical impact. Normally, this kind of temperature sensor is installed using three wires, so that the error caused by the line resistance can be minimized in the internal measurement circuit. The following figure shows the usual protection for both Thermocouples and Ptl00; however, there are many other possibilities, including cheaper ones.
7.2.1.3 Thermistor The thermistor is a thermal resistor, constructed with semiconductor materials to present more sensibility (McComb 1999). This is one of the most cheap solutions in measuring the temperature. However, it's low linearity and narrow range of temperature demands more electronics, less accuracy, and more specific application uses. It can provide a negative temperature coefficient, known as NTC or positive temperature coefficient, the PTC. Using technologies such as microcontrollers and instrument amplifiers, it is possible to enlarge the scope of its applications, but keeping in mind their limitations.
7.2.1.4 Integrated sensor Nowadays, many integrated sensors are available. These devices are semiconductor based, but have an internal circuit able to turn the output more linear and
accurate. The range of temperature could be about -55 to 150~ One usual sensor is the National Semiconductor, LM35 as described in National 2000, with small packages and very stable signal. This chip integrates internal circuits responsible for the linearization and calibration, thus it needs less external circuits to work.
7.2.2 Flow s e n s o r When facing a flow sensor application, it is necessary to pay attention in many specification and performance data, because the variety of choices is vast (Liptak, 1993). It is necessary to know the material in which the flow has to be measured, liquid or gas, and its range for a specific bioreactor. Other characteristic to keep in mind is the losses in the energy flow, translated in losses caused by the turbulence and fluid friction into the sensor or transducer. These losses impact indirectly in costs (Sturm 2004).The air flow is often recorded on-line by a flow meter fitted at the exit of the reactor, including rotameters, which is only a monitoring device and not a sensor, thermal mass flow meters, anemometers, and differential pressure sensors (Christen et al., 2003). It is very important to measure the flow at the entrance and exit of the bioreactor to make sure about volumetric gas evaluation (Pandey 2004).
7.2.2.1 Flow s e n s o r b y differential pressure The following figure shows an example of differential pressure application, using two tubes, Pitot and Venturi. The difference between these two pressures, indicated as h or the differential high between two liquid columns, is proportional to the fluid velocity so that the flow can be calculated (Sturm 2004).
7.2.2.2 Flow sensor type venturi tube This sensor is a differential pressure device. Giovanni B. Venturi in 1797 postulated that fluids under pressure when pass through convergent tubes increased their velocity and loose pressure but the opposite occurred in the divergent tubes. Using pressure sensors, the flow can be measured (Liptak, 1993). For instance, in the following figure, velocity indicated as V2 would be higher than V1, due
to the different areas indicated as S1 and $2, although the pressure in S1 would be higher than $2.
This sensor does not add much resistance to the fluid flow as an advantage, but due to the pressure measurement needs, it is not low cost choice in much of the cases.
7.2.2.3 Flow sensor by thermal dispersion When fluids pass through the heated sensors, it causes loss of temperature due to the convective cooling effects at a rate proportional to the fluid velocity (Soloman 1998). The heated sensor must be at a constant temperature, above the temperature of the gas flow being measured. The electrical energy required to maintain a constant temperature in the velocity sensor is proportional to the cooling effects on the measured gas flow, so that the velocity could be inferred. This kind of sensor is, in present time, very accurate and has a large scale of application ranges, though it is not an inexpensive technology yet. The resolution, no moving parts, and accuracy together with a real time measure possibility could be advantageous, hence a good analysis about the costs and benefits must be made.
7.2.2.4 Orifice plate This differential pressure flow sensor consists of a plate installed in the tube, which measures the flow with a central or eccentric orifice (Saleh, 2002). When the fluid faces the orifice in the line, it causes a pressure change before and after the hole. The difference between the pressure before and after the orifice is proportional to the fluid's velocity, hence, the flow can be estimated with a quite accuracy. This kind of solution is very simple to install and at low cost, but has the disadvantage of adding resistance to the flow crossing the orifice. Thus, when there are many sensors in the same line, it could be prohibitive.
7.2.2.5 Turbine sensor The turbine flow sensor may be the low cost model because of its simplicity. This sensor consists of a kind of turbine blade inserted inside the tube, by
which the flow is measured (Herman and Alerich 1998). The moving fluid causes the turbine to turn. The speed of blade's turning is proportional to the flow. The electrical signal is determined by this speed.
7.2.2.6 Magnetic sensor The magnetic flow sensor works based on the Faraday's Law, which states that when there is a conductor moving through a magnetic field, a voltage will be induced into the conductor, depending on the strength of the magnetic field and the conductor velocity (Cheremisinoff 1988). In this case, the conductor is a moving liquid. This sensor works only with the conductive liquids, thus could be useful in measuring the water flow or any other liquid addictives addition to the fermentation process. There are many advantages in using this kind of sensor, such as accuracy and less resistance to the fluid flow, but it is not a low cost solution. The following figure is a schematic view of a magnetic flow sensor, where E1 and E2 indicate the electrodes of output electrical signal.
7.2.3 Humidity sensor Depending on the bioreactor type, humidity control is as critical as temperature control concerning to the bioreactor performance because of its influence on oxygen transfer, hence causes a reduction in the growth rate (Pandey, 2004).There are mainly two types of humidity sensors, and their construction is based on the sensitive polymers coating of an electrode base-plate (Soloman, 1998). One of these is a capacitive sensor, whose output signal causes a capacitance change depending on the humidity. The other type is a resistive output sensor that changes electrical resistance according to the humidity changes. In comparison with the capacitive, this sensor has a slower output response, but for most
processes, it is enough. The capacitive humidity sensor is faster than the resistive but is more expensive.
7.2.3.1 Moisture and water activity In solid-state fermentation, it is very crucial that exact quantity of water is added to the substrate so as to achieve a suitable water activity (aw) (Pandey et al., 2001). In SSF process, the water activity is variable because of the evaporation and metabolism (Dorta et al., 1994). Water activity could be more important factor than the water content for microbial growth and metabolism, (Tsao and Brainard 1999). It is important to keep in mind that water activity is closely related, but not equal to the water content. Water content is often measured off-line by dry weight determination, but it is not the same of water available for the activity of the microorganism. One of the most common methods to measure water activity is the capacitive sensor, designed to regulate the circulating air humidity (Christen et al., 2003). It is possible to measure the relative gas humidity in a cell separated from the solid phase by a hydrophobic membrane (Gervais 1989). In a chamber, a capacitive element absorbs the water vapour in equilibrium with the surrounding environment, which makes the dielectric constant of the capacitor to change. This change can generate an electrical signal to be measured proportionally to the water activity. However, there is still very slow response for most bioreactors process.
7.2.4 pH s e n s o r Variations in pH result are indicators of changes in the metabolic activity in SSF (Christen et al., 2003). Flat-ended electrodes are normally used to measure pH directly on the surfaces of solid substrates, but off-line and usually can be made by measuring the pH of aqueous suspensions or extracts of the solid sample (Scheper and Berovic 2000).There are new pH probes models, without the necessity of temperature compensation and filling of solution, and can be connected to interfaces which are able to output standard signals and industrial communication networks protocols (Myrvoll 2003). But in SSF, due to the lack of free water, it is difficult to control pH accurately.
7.2.5 0 2 and C O 2 s e n s o r s
In SSF, the 02 consumption and CO2 produced allow to estimate the growth kinetics of the microorganism (Pandey et al., 2001). This also helps in determining the respiratory quotient, defined as the ratio of CO2 produced and 02 consumed. Oxygen has a strong affinity for a magnetic field and this property is not shared by many other gases (Liptak 1994). In SSF, this is the only gas which has paramagnetic property, thus, it is one of the most common characteristics
to use in measuring oxygen consumption direct from the process. In deflection type sensor, the paramagnetic behavior of oxygen is compared to another gas, both inside a magnetic field. The more concentrate is the oxygen sample, the more unbalanced is the system, which measures how deflected is some mechanical device. However, this kind of sensor is quite expensive, although very accurate. The thermal type sensor is based on the paramagnetic property of the oxygen and the flow of the oxygen changes the thermal balance of a temperature sensor, proportionally to gas concentration, generating an electrical output signal. This sensor has the disadvantages of its sensitivity to heat and low precision (Christen et al., 2003). There is a type of oxygen sensor which operates like a metal/air battery (Jardine and McCallum 1994). Oxygen in contact with the cathode is reduced to hydroxyl ions, with a balancing reaction of lead oxidation at the anode, thus an electrical current is generated proportionally to the rate of oxygen consumption, following the Faraday's Law (mentioned in the section about magnetic flow sensor). This kind of sensor's lifetime depends on the availability of lead, which stops working when all the lead is oxidized. For continuous monitoring applications an absolute, non-dispersive infrared (NDIR) gas analyzer based upon a single path, dual wavelength, infrared detection system could be a low cost, low maintenance CO2 analyzer (Liptak 1994).Infrared spectrometry is commonly used to record CO2, allowing to evaluate microbial growth, to validate gas diffusion models, and to monitor fermentation processes (Christen et al., 2003). Accordingly to Brown et al., (1989), using proper columns balances, it is possible to resolve 02 and CO2 simultaneously performing a gas chromatography with two concentric columns. Christen et al., (2003) stated that one column must be filled with a porous polymer or silica gel to retain CO2 from the air and the other with a molecular sieve, which was able to separate 02. Each compound can be quantified by a heat conductivity detector, or catharometer. This solution could be used on-line to store and analyze data.
7.3 ACTUATORS Sensors and actuators are the components of the control system, which come into contact with the fermentation process, thus need to be designed to facilitate sterilization, asepsis, insertion, and removal (Omstead 1990). In the specific case of SSF, some actuators could be outside of the process itself. Actuators such as micro switches, limit switches and contactors are electrically very simple, because of their mechanics and well-known function. This section will discuss about newest and more complex actuators.
7.3.1 Motor To perform many kind of movement it is necessary to apply an electric motor. The ventilation is indirectly or directly accomplished by a motor attached to an air pump or compressor as well as the rotating parts to achieve the proper mixing of the fermenting substrate. Motors are often supplied by Alternating Current (AC), or Direct Current (DC). In industrial application, the AC supplied motors are most common (Valkenburgh 1993). Using a Frequency Inverter, an electronic device, it is possible to change the speed of three phase motors. Day by day, these devices are turning more cost effective, using thyristors such as SCR. It is common nowadays to use the insulated gate bipolar transistors, IGBT, with high frequency and updated technologies (Bradley 1995). Hence, it is possible to control some variables by changing a motor velocity. The use of servomotor is normally prohibitive because it is often expensive; however, it has advantages in controlling speed and position with high accurate rates.
7.3.2 Valve The correct use of valves is indispensable for instrumentation design. There are many types of the valves. Mechanical and manually activated models are of lower cost, but these are not very useful in automated control loop. Motorized and Proportional Valves as explained by Janocha (2004), could be the correct alternative for controlled processes. These kinds of valves are able to vary from completely closed until completely open, depending on the input signal, often used 4 to 20 mA as control signal for proportional types. Hence, to accomplish with the automatic control requirements such as accuracy and resolution, these could be used to control the air inlet flow, pressure component, other substances volume to be added to the process, etc. 7.3.3 Heater power control There are two main ways to control the heater power in the industrial applications by Phase Angle and Pulse Width Modulation (PWM) (Ibrahim 2002). Phase Angle is one of the most common methods to control the heater power, where the start of each mains power supply half-cycle, applied to resistance heater, is delayed by an angle. In electricity it means some amount of time, but it is important to keep in mind that each full-cycle lasts just around 16.6 miliseconds when taking account the frequency of 60 Hz. Electronic components called thyristors are used in order to change the triggering angle, so that the power is delivered to the heater element. The other method PWM, or Duty Cycle is able to turn on and off very fast in order to cut a number of full-cycles and leaving the other cycles applied to the heater element. Both of them are useful in temperature control with electrical heaters because they are able to apply from zero to the full available power to process heating depending on the
controller signal. Accordingly to Rexford and Giuliani (2004), it turns the control loop more accurate and reliable, but generates electrical noise which can cause some equipments malfunction.
7.4 CONTROL When dealing with control strategies, some terms appear very often such as Setpoint, SP, which is the desired value of some parameter under control, Manipulated Variable, MV, which is the variable that is changed by the control strategy to act directly for the process, and Present Value, PV, which is the value at the analyzed or real time. A controlled parameter must maintain its value, i.e. should stay at stable value, or as close as possible considering the tolerances, and when faced with a disturbance, must return to the previous state as soon as possible.
7.4.1 On-Off control One of the most simple control methods or strategies is the so-called On/Off control (Montague 1997). Its action is shown in the following figure. Here, a temperature control is used as an example. The heating power is either fully switched on when the temperature is below the Setpoint or fully turned off when it is above. As a result, the temperature oscillates around the Setpoint, the amplitude and the time period of the oscillation is a specific function of the process, or the thermal lag between the heating energy source and the temperature sensor. To minimize the output "bouncing" as the measured temperature crosses the Setpoint, the controller does not turn on and off at precisely the same point. Instead, a small differential known as hysteresis is used, whose value depends on the process behavior to maintain the Setpoint at the average value of total oscillating curve. On/Off control is satisfactory only for the non-critical process applications where some oscillation in the present value is permissible.
7.4.2 PID control Where there is a more critical process application, On/Off control would not reach the results needed. In this case, the PID, Proportional Integral and Derivative method could be the correct choice, and is widely used in the industrial plants. To achieve the strategic comprehension, this method will be analyzed in details.
7.4.2.1 Proportional control A proportional controller takes place to perform better than the On/Off control type by applying power to the heater, for example, to a temperature control application, proportionally to the difference in temperature between the process and the Setpoint. This difference is usually called error. P is known as the proportional gain of the controller. When this gain is increased, the system tends to respond faster to the changes in Setpoint value, or facing a disturbance, but becomes progressively faded and eventually unstable. The final process temperature is used to stabilize below the set-point with this system because of a kind of equilibrium between the energy supplied to the system and the resistance from it. In other words, the proportional amount of energy is too weak to reach the set point, taking into account that the proportional action will be linked to the error and close to Setpoint this value tends to be little (Montague (1997). This error is normally called steady-state error.
7.4.2.2 Proportional and derivative control When only proportional controller is used at high gain, the amount of PV may reach above the Setpoint, and problems could appear. In order to minimize these problems, a term proportional to the time-derivative of the error signal can be added to the output signal or control signal (Omstead 1990). This term is the variation rate of error in relation to the time. Normally, it is called derivative time and expressed in seconds, depending on the controller manufacturer. This technique is known as PD control. Its response is faster than the proportional control.
7.4.2.3 Proportional integral and derivative control- PID The PD control described above can deal properly with the overshoot and stability problems associated with the proportional control but it does not solve the problem with the steady-state error. This error can be eliminated, at least minimized, by the use of relatively low gain, achieved by adding an integral term to the control function which becomes: Ger de S c - P.e + ~ l e.dt + T d ~ + B Ti Jo dt
Where: Sc is the output signal of control; P is the proportional band; G is a constant; Ti is the integral Time; e is the error or (SP- PV); Td is the derivative time; and B is a kind of Bias (Bryce and Mansi 1999). The following figure shows the usual behavior of PID control.
The mathematical difficulties with the Integral and Differential Calculus eventually encountered in the previous function can be more easily understood with a time sampled function, generating a table of values and the equation changes to:
DMVN = r e
EN
At
EN ~ + - - E N TI
"~d
--:-:(CVN 2CVN ,+CVN 2)
)
/~t
MV N = MVN , + AMV N Where Kc represents the proportional gain, TI the integral time, Td the derivative time, CVN is the controlled variable, SPN is the Setpoint and MVN is the controller output at the current sample N. The current error is calculated as EN=SPN-CVN (Birol et al., 2002).
7.4.2.4 Advanced PID control In many years of continuous development of new control application techniques, some algorithms have been added to the usual PID. Some manufacturers offer more specialized control devices. One of these advances is the Fuzzy Logic algorithm working together with the traditional PID (Shaw 1998), which is able to recognize situations when fuzzy logic would offer certain advantages
over the traditional control strategies, particularly in controlling the highly nonlinear and time-variant plants and processes.
7.4.3 MMI and SCADA A MMI system (Man Machine Interface), or HMI (Human Machine Interface) could be explained as the connecting point between the operator and the machine. Most of the cases, it is an operator panel or a Personal Computer (PC), or a workstation (Evrendilek et al., 1997). Nevertheless, in the both cases, the transmitting and receiving data are from the sensors and actuators in the process. Widely used in industry plants processes, Supervisory Control and Data Acquisition (SCADA) systems could be used in the biotechnological processes also. The pioneer SCADA masters were normally strongly manufacturer-based software, as well as hardware, with no interchangeability between the different manufacturers products and at that time the investment were high (Strauss 2003). The development and cost effective personal computer, nowadays present in every industrial plant, actually forced suppliers of SCADA software to develop their products to be compatible with PC use, with low cost devices. Using a PC as a SCADA-MMI system, the following items will be necessary: SCADA Software: Software program able to work together with the PC like a SCADA system; Programmable Logical Controller (PLC) Communication card, or some communication standard protocol for the whole devices; Communication driver: It is a kind of translator between the SCADAMMI system and the process devices. The bioreactor can be connected, or in communication, with the SCADA system, whose function is to collect all the data and store it for later retrieval and supposed to be analyzed. It ought to be kept in mind that the SCADA is not a database, and usually cannot give answers to database type queries but using resources to present the operator with comprehensive information on plant status (Bryce and Mansi 1999). The control function distributed in the process, performed by the controller loops or PLC. Most of the applications are proprietary in nature using proprietary hardware and commercial software pack, because there is almost no open source SCADA software available (Gorodeckij et al., 2003). However, there are many efforts to create and to tum into available open software tools, with its own advantages and disadvantages of course (Goodman 2001).These solution methods have a strong and close relation with communication networks, which are discussed in the next section.
7.5 COMMUNICATION NETWORK For the bioreactor automation, it is necessary to plan for the communication system. This planning is necessary to certify all the devices such as sensors, actuators, interfaces, and management systems, to be interchangeable and operational. The correct choice can guarantee maintenance, evolutionary and flexible control requirements also. With this point of view, this section presents the technologies still in use, and the trends for the communication devices.
7 . 5 . 1 . 4 to 20mA The 4 to 20mA communication method had spread when the electronic elements in control devices and sensors took place. It was developed in the sixties of last century (TEI 2006). This communication system has the following features: connection by metallic twisted pair wires, normally shielded to avoid electrical noise, which accomplished the communication and power supply; polarization of electrical current of 4mA through the communication wire; range of data transmission from 4 to 20mA; high noise immunity; easy circuit design and maintenance; system low cost; fast identification of system fault by loop current monitoring such as wire disruption, bad contact, and circuit malfunction; high connection distances (Dergint 1990). This kind of devices could present some inconveniences due to the increasing process control complexity. For each control signal, it is necessary to have a different twisted pair of wires, hence, with many control nodes, the maintenance, identification, installation or position changes could turn into a serious problem (Dergint 1990). 7.5.2 Serial communication Due to electronics evolution, new and more sophisticated communication protocols take place, allowing the bidirectional data transfer between the two equipments. Two patterns can be pointed out, parallel and serial communication. The parallel communication is almost obsolete due to the short interconnection distance between the equipments. For instance, GPIB an 8 bit parallel communication developed for workbench instruments connection is still in use today (GPIB tutorial 2005). This system's advantage is the automatic bit rate speed operation, which allows working with different equipments from different manufacturer. It has been reported that with the component integration and increasing velocity of electronics, the serial communication is the trend for the interconnection devices nowadays (Wong 2006). These included the RS485 and communication protocols such as Fieldbus (Thomesse 1998).
7.5.2.1 RS 485/RS 232 The most well-known serial communication is the RS232, useful to devices connect printers, mouse to Personal Computers, but today almost disused due
to connection distance available (30 meters maximum), and peer to peer connectivity (Dergint 1990). However, the electrical protocol RS485 is quite different from the RS232 (Wong 2006). It uses differential transmission, allowing distances in kilometers. Using the multipoint connection, it is possible to use until 32 elements per bus, and some manufacturers actually offer up to 128 devices. Combining the low cost, it is one of the most usual options for the industrial environment complex processes. The following figure shows the RS485 devices bus connection, where D - Driver; R - Receiver; T - Transceiver; and T R - Termination Resistor.
7.5.2.2 USB/FireWire The USB connection uses a serial communication protocol also. It has replaced RS232 system and is useful to interconnect office's devices such as printers, scanners, web cam, photograph cameras, etc. Due to the low cost, many other devices are now available with this interface. The basic features are: connection up to 127 devices, 5 meters distance and transmission velocity from 12 Mbps (Mega bits per second) for USB 1.0 to up to 480Mbps for USB 2.0 (Axelson 2005). FireWire is an USB protocol competitor and is useful for the similar applications (Axelson 2005). Technically, it shows more reliable performance than the old USB versions; however, this protocol is not so well-known among the PC framework users. Its features are 127 devices connection, distance of 5 meters and transmission speed of 400 Mbps (1394a) and 800 Mbps (1394b) (Wong 2006).
7.5.3 FieldBus Fieldbus is a network developed for the industrial automation environments. It took place in the 1980s but began popularizing in the beginning of twenty first
century. This delay occurred because of many proprietary and non-proprietary systems competition and sophisticated framework levels and sub-levels requirements such as memory availability and low cost (Smar 2001). Today, the field buses can be divided in SensorBus, DeviceBus and FieldBus. The following figure shows this distinction.
Nevertheless, with the technological evolution and its consequent production cost reduction, the trend is the FieldBus application in the whole process. In general terms, DeviceBus and SensorBus could be considered Fieldbus network simplifications (LeBlanc 2000). The FieldBus framework complies with a three layers simplification from the OSI (Open System Interconnection) at ISO (International Standard Organization), which has totally seven layers (Betlem and Roffel, 2004). However, as can be observed in the following figure, the framework is organized in three layers OSI plus one, Physical, MAC (medium access control), LLC (logical link control), Application and User (Wright et al., 2003).
The physical layer makes the interconnection with the medium, which has two types, RS485 based and IEC 1158-2 standard. The latter is more expensive and possesses some advantages compared to RS485, such as data and power supply at the same bus, communication protocol normally using the diphase
Manchester method, which is superior in comparison with the RS serial types, galvanic insulation between the devices and the bus to (Lewis 2001).
Actually, every FieldBus standard supports the physical medium described above, especially IEC 1158-2 (61158), with differences in data link layer, subdivided in MAC and LLC. MAC has the task of managing the medium access and LLC to certify the reliable messages exchanging. Over these layers two basic mechanisms are implemented which are master-slave and producer-consumer. Profibus uses the multi master framework with the sequential monitoring over the slave nodes, and FIP (Factory Instrumentation Protocol) applies producerconsumer (Dergint 1990). It also implements cyclic and event communication mechanisms. They are important for the process control algorithms application. The application layer has tasks, such as writing and reading devices variables and has a directory for process configuration also. The User layer was introduced in FieldBus to assure the devices inter operation. Hence, this as well as the usual control PID 4 to 20mA, could be interchanged with different manufacturers devices without new configuration (Lewis 2001). The User layer defines three types of the Function Blocks: Resource Block, Function Blocks and Transducer Blocks. Resource Block describes the Fieldbus device characteristics, such as
device number, manufacturer, and series number. Function Block defines the control system behavior. The input and output parameters can be connected through the Fiseldbus. Each Function Block execution is precisely scheduled. There can be many Function Blocks in one User Application. Fieldbus Foundation defined 10 standard Function Blocks for the basic control specified by the FF-891 standard part 2 specifications.
The initial set of 10 function blocks includes from the analog and digital inputs until PID algorithm control, as pointed out by Appendix D 2002 and Override and Split Range Control. Advanced function blocks intends to cover 20 (19 in Foundation) operations including ramp generators and dynamic compensators, FF-891 standard part 3 specifications. The function blocks can be inside a field device providing required function; for instance, a flow meter can have a function block inside with the analog input, and a proportional valve can have a PID control function block together with an analog output, hence, these two devices could make a complete flow loop control. Finally, the Transducer Blocks turn unattached the Function Block from the local input and output functions required for the sensors and output command of hardware, containing information such as calibration, date, and sensor type. Usually, each input and output Function Block has one Transducer Block. The following objects are defined in the User Application: Link Objects, Trend Objects, Alarm Objects, View Objects which can be useful for Man Machine Interfaces.
7.5.4 Profibus (Process Field Bus) Profibus was developed to support the manufacturers need and became the standard DIN V 19245 in 1989/1995. In 1997, it was defined in the international standard EN 50170, 1996 and 1999 it was included in IEC 61158/IEC 61784
standards (Wright et al., 2003). Profibus is the widely employed model, and is an open field network, which is not dependant of Manufacturers and allows communication between different brand devices without any specific adjustment (Betlem and Roffel 2004). The framework complies with OSI reference model and ISO 7498 standard, using 1, 2, and 7 layers (Dergint 1990). Profibus allows real time and high velocity applications and complex communication tasks. Its standard form can be separated in three subdivisions: Decentralized Periphery- DE master-slave, low cost, high velocity and manufactory oriented; Process Automation- PA, intrinsically safe, adopt User Layer and process oriented; Fieldbus Message S y s t e m - FMS, multi-master/peer to peer, IEEE 802.4 simplification, presented in IEEE 1984 for heavy communication tasks, without critical time requirements. Basic Features are: maximum of 127 stations, making use of repeaters; Non Return to Zero-NRZ coded (DP) and diphase Manchester L (PA); physical medium is twisted pair or fiber optics; electrical standard RS485 or IEC 1158-2; bus velocity using RS485 (DP) from 9600 till 12Mbps and using IEC 1158-2 (PA) of 31,25 kbps; maximum cable length of 1200 meters, using 9600 bps bit rate (DP) and 1900 meters per bus at (PA).
7.5.5 WorldFip It was developed foremost to support industrial process requirements. In 1989, it was defined in French standard NFC 46-600 and nowadays accepted in international standard EN 50170/3 and EN 50254/3 as well as included in IEC 61158. Its framework is very flexibl6, especially because it adopts producerdistributor-consumer as exposed in EN 50170, 1996. It is also an open field network, using OSI reference model in conformity with ISO 7498, using 1, 2, and 7 layers (Betlem and Roffel, 2004). Its basic features are: identifiers are coded using 16 bit integers; up to 65535 variables can be named; producerdistributor-consumer to simplify distributed system projects; maximum of 256 nodes with repeaters; diphase Manchester L coded; physical medium is twisted pair or fiber optics; electrical standard IEC 1158-2; bus velocity using IEC 1158-2 of 31,25 kbps or 1Mbps or 2,5 Mbps; maximum cable length of 40 km (Wright et al., 2003).
7.5.6 Zigbee ZigBee implements a low cost and low power consumption wireless network, based in IEEE 802.15.4 standard (Wheeler 2006). Its specification was ratified on 14th December 2004 and 13th June 2005 and the ZigBee Alliance became public available specification. The cost estimation is only U$ 1.00 per node. The frequency band work is distributed among the countries as: 915 MHz in the USA, 868 MHz in Europe and 2.4 GHz in most countries.
The ZigBee protocol is supposed to be on-board applications working with low rate of data transmission and low power consumption (Yacoub and Yang 2006). It can be suitable for industrial control, on-board sensors, medical data logging, and so forth. Due to low consumption, a ZigBee system could work more than one year with the same battery. The Basic Features are: three device types, ZigBee coordinator(ZC), ZigBee Router (ZR) and ZigBee End Device (ZED); cable length from 10 to 100 meters depending on the specific environment conditions; the physical medium access protocol uses "carrier sense, multiple access/collision avoidance" (CSMA/CA), transmission based in fixed timing schedule, and for real time requirements uses Guaranteed Time Slots (GTS); Addressing space of up to 64 bit address devices with 65535 networks; topologiesstar, peer-to-peer and mesh.
7.6 CONCLUSIONS This chapter had the purpose of exposing and discussing about the Instrumentation and Control for a specific area, solid-state fermentation. Attempts were made to focus here only the current devices, equipments and communication methods for the process considered as well as the new strategies and trends. Depending on the process size and behavior, it would be necessary to analyze what kind of method would be useful. There are many variables to be taken into account, such as control type and accuracy needs, stability, number of control loops, distance between the process and the control system, response time and tolerances, specific sensors availability, control and communication network interfaces necessity, and at last but not the least important, the budget. Because of vast quantifies of manufacturers and suppliers, as well as the different technologies, it is necessary to know how to identify not exactly the very best solution, but the most adequate one.
Acknowledgments The authors acknowledge Conselho Nacional de Desenvolvimento Cientifico e Tecnologico-CNPq and CAPES for financial support.
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References Appendix D, 2002, PID Function Block, Rosemount Model 3244MV MultiVariable Temperature Transmitter with Foundation Fieldbus, FIELDBUS-FBUS_34A, Rosemount, www. emers onproce s s. com/ro semount/document/manual s/3 244 ff/3 244f_pid. pdf, accessed on 20/11/2006. Axelsom, 2005, Jan. Usb Complete, pp 196-198, Madison: Lakeview Research LLC. Betlem BB & Roffel B, 2004, Advanced Practical Process Control, p 309, Springer: New York. Birol G, Undey C & Cinar A, 2002, A Modular Simulation Package for Fed-Batch Fermentation: Penicillin Production, Computers and Chemical Engineering, 26, 15531565.
Bradley DA, 1995, Power Electronics. pp 39-42, CRC Press: London. Brown PR, Giddings JC & Gruchka E, 1989, Advances in Chromatography, p 73, Marcel Dekker: New York.
Bryce CFA & Mansi EM, 1999, Fermentation Microbiology and Biotechnology, pp 203-236, Taylor & Francis: London.
Cheremisinoff NP, 1988, Flow Measurement for Engineers and Scientists, pp 311-312, Marcel Dekker: New York. Christen P, Veronique BM & Orliac O, 2003, Sensors and measurements in solid-state fermentation: a review, Process Biochemistry, 38, 881-896. Dergint DEA, 1990, Um Barramento de Campo para Automa~ao da Garantia da Qualidade da Produ~o; 1990, Dissertation; CEFET-PR, Curitiba, Brasil. Dorta B, Bosch A, Arcas I & Ertola R, 1994, Water balance in solid-state fermentation without forced aeration, Enzyme and Microbial Technology, 16, 562-565.
EN 50170, 1996, General Purpose Field Communication System, European Standard, ~.l
.FC.
Evrendilek C, Wilhelmsen D, Gezer E & Ince AN, 1997, Planning and Architectural Design of Modern Command Control Communications and Information Systems, pp 106-107, Springer: Massachusetts.
Gervais P, 1989, A new sensor allowing continuous water activity measurement of submerged or solid substrate fermentations, Biotechnology and Bioengineering, 33, 266-271.
Goodman G, 2006, Puffin Projects Lead Open Source Parade, 23 April 2001. www.isa.org, accessed on 17/11/2006.
Gorodeckij VI & Popyack L (eds), 2003, Computer Network Security, p 171, Springer: New York.
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GPIB Tutorial, 2006, TransEra Corporation's, http://www.transera.com/htbasic/ tutgpib.html, accessed on 13/11/2006. Herman SL & Alerich WN, 1998, Industrial Motor Control. p 143, Thomson Delmar Learning: New York. Ibrahim D, 2002, Microcontroller-Based Temperature Monitoring and Control, pp 203204, Newnes: Oxford. I E E E - 1984, International Standard 802.4: IEEE standards for local area networks: tokenpassing buss access method and physical layer specifications.
Janocha H, 2004, Actuators: Basics and Applications. pp 167-170, Springer: New York. Jardine FM & McCallum RI, 1994, Engineering and Health in Compressed Air Work, pp 334-335, Spon Press: London. Leblanc C, 2000, The Future of Industrial Networking and Connectivity;Dedicated Systems; 2000 Q1, http://www.dedicated-systems.com, accessed on 11/11/2006. Lewis RW, 2001, Modelling Control Systems, IET: London. Liptak BG, 1993, Flow Measurement, CRC Press: Pennsylvania. Liptak BG, 1994, Analytical Instrumentation, CRC Press: Pennsylvania. McCombs DM, 1999, Detecting the World, CMP Books: Berkeley. Montague G (ed), 1997, Monitoring & Control of Fermenters, pp 89-92, Institution of Chemical Engineers (IChemE): London. Myrvoll F (ed), 2003, Field Measurements in Geomechanics, Taylor Francis: Lisse (UK). National Semiconductors Corporation, 2006,. LM35 Data Sheet, www.national.com, accessed 10/11/2006. Omstead DR, 1990, Computer Control of Fermentation Processes,CRC Press" Boca Raton. Pandey A, Soccol CR, Rodriguez-Leon JA & Nigam P, 2001, Solid-state Fermentation in Biotechnology: Fundamentals and Applications, Asiatech Publishers, Inc. New Delhi, India. Pandey A (ed), 2004, Concise Encyclopedia of Bioresource Technology, Haworth Press: New York. Rana SP & Taneja SK, 1988, A Distributed Architecture for Automated Manufacturing, International Journal of Advanced Manufacturing Technology, 3, 5. Rexford KB & Giuliani PR, 2004, Electrical Control for Machines, Thomson Delmar Learning: New York. Saleh JM, 2002, Fluid Flow Handbook, McGraw-Hill Professional: New York. Scheper T & Berovic M, 2000, New Products and New Areas of Bioprocess Engineering, Springer: Berlin.
Shaw IS, 1998, Fuzzy Control of Industrial Systems, Springer: Massachusetts. SMAR, 2001, Fieldbus Tutorial a Foundation: fieldbus technology overview, www.smar.com.br, accessed on 15/11/2006. Smith JE, 2004, Biotechnology. Cambridge University Press: Cambridge. Soloman S, 1998, Sensors Handbook, McGraw-Hill Professional: New York. Strauss C, 2003, Practical Electrical Network Automation and Communication Systems, Newnes: Burlington. Sturm W, 2004, Sensores Industriais: Conceitos Teoricos e Aplicaq6es Praticas, Papel Virtual Editora: Rio de Janeiro. TEI Controls Inc. "4-20 mA Description", E.U.A, www.teicontrols.com/4-20.html, accessed on 20/11/2006. Thomesse JP, 1998, A Review of the Fieldbuses, Annual Reviews in Control, 22, 35-45 Tsao GT & Brainard AP, 1999, Recent Progress in Bioconversion of Lignocellulosics, Springer: New York.
USB 2.0 Specification; Universal ~Serial Bus, http://www.usb.org/developers/docs/, accessed on 13/11/2006. Valkenburgh AV, 1993, Basic Electricity, Thomson Delmar Learning: Indianapolis. Wheeler A, 2006, ZigBee Wireless Networks for Industrial Systems - White Paper, Jun2006. www.microcontroller.com, accessed on 13/11/2006. Wong H, 2006, Overview of Serial Communications; Web Presentation, National Semiconductor, www.national.com/AU/design/0,4706,0_34_,00/html, accessed on 13/ 11/2006. Wright E, Park J & Mackay S, 2003, Practical Data Communications for Instrumentation and Control, Newnes: Oxford. Yacoub M & Yang GZ, 2006, Body Sensor Networks, Springer: London.
Yacynych AM (ed), 1990, Sensors in Bioprocess Control, Marcel Dekker: New York.
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!iiiiiiiiiWilerson ii Sturm, Carlos R Soccol iiii!iii!!iDario ii! Eduardo Amaral Dergint, iii!i!iii!iiJose ii~ A Rodrfguez-Le6n & i!iiiiiii!i!Deiva ii!ilil Canali Navarro Vieira Magalh~es 8.1 INTRODUCTION The technological progress in informatics and computation sciences has been increasing faster than most could imagine or even understand, not only because of its velocity but essentially because of its large scope of applications. With constant improvements of performance features and relative drop of prices, these equipments are more and more cost effective. One of the areas where the demand for more computing power is most notorious is in biotechnology, especially in DNA researches, where it could turn into the driving force of development because of the need to store and analyze the enormous amount of genomic and proteomic data. However, almost the same has been taken place in all other biotechnology areas. Actually the advances are not only in hardware specifications. Indeed there are new programming techniques, new and powerful languages, and even new entire programming frameworks. Together with the hardware performance these software developments allow more complex problems solution. This chapter will discuss some of the new techniques, solutions and challenges concerning the computing uses in biotechnology and show some examples of implementation like Fersol2 software, for instance.
8.2 PROGRAMMING LANGUAGES A major problem to design simulation system is the task of choosing an adequate programming language. Normally, it is necessary to make equilibrium between the following criteria that are considered more important in this situation: rapid implementation, normally to analyze non complex problem; independence of operational system (OS), normally Windows or Linux; velocity, when the algorithms are CPU intensive; flexibility, simulating and controlling a real-time system; evolutive, developed blocks are easily re-utilizable by objects; diffused, easy to find skilled people to use a language. Here the languages analyzed are C++, C#, Java and VB (Visual Basic) which fit with the criteria presented.
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Obs.: More positive is better: - single negative, + single positive, ++ double positive. In the context of biological simulations, VB are most utilized to make simple analysis. However, if the objective is to make evolutive platform, languages like C++, C# and Java must be considered. But, with the above criteria, the best language is C#. This language is new, but has some interesting characteristics: JAVA like, C++ like, and open standard. This hybrid nature makes C# flexible and powerful to develop virtually any application.
8.2.1 Agent and multi-agent system Conjugated with the language, it is important to adopt a flexible and evolutionary methodology to develop the biotechnological simulating / controlling system. According to Jennings et al., (1998), the agents autonomous and the multiagent systems represent a new manner of analyzing, projecting, and implementing complex systems by software. This approach is made up of a very powerful whole of tools, techniques and metaphors which are very interesting for the development of software. According to this approach "An agent is a computer system, situated in some environment, which is capable of flexible autonomous action in order to meet its design objectives". This work intends to check this approach potentiality for the study of biological problems. The importance of the multiagent system lies in its capacity of complex problems resolution, that use to be difficult to identify and describe perfectly. The multiagent system is based on a certain number of agents which try to give a good response for a specific situation. To achieve that, they can exchange information and also be able to learn "how to move". The solution is a system evolution function, which is "itself' the result of a process of training. The training can be seen in two different levels: individual or by the system. The best manner of solving a complex, large and/or unforeseeable problem is to develop a number of specific functionalities and components modular which are specialized in the resolution of a particular aspect of the problem. Here, the modular or almost modular components are the agents. Another characteristic
of real problems is that they are open and distributed systems. In such a situation, it is impossible to know its components in advance and moreover, those behavior changes with time. Sycara (1998) defined a Multi-Agent System (MAS) as a loosely coupled network of problem solvers that worked together to solve problems that were beyond the individual knowledge or capabilities of each problem solver. Nowadays, the most problems solution is based on single agent. However, the MAS has a great difference; it is not necessary to know exactly what the system needs to do before its implementation. The system can be improved with a little effort when it turns necessary or when a solution is reached. The multi-agent system allows simulations closer to the real world, because it is possible to take into account a great diversity of variables and to articulate them to check the results. The constraints of this method are related to the system project and the results comprehension. Accordance to Dergint (1999), due to the system complex nature, it is still not easy to know or determine analytically the conclusion or the results obtained automatically. For instance, biological control and monitoring systems with MAS can use a heterogeneous strategy to find a solution, it gives characteristics as robustness and flexibility.
8.3 MODELING AND SIMULATION Accordingly to Harrington and Tumay (2000), computer simulation modeling allows to see the results of a process without investing time and resources to test the real one. Most of simulations are able to show results with a kind of time acceleration. It, thus, becomes clear that it brings the possibility of saving resources and time. However, it demands more complete mathematical models describing the process behavior. Instead of committing resources to implement a new real process, simulation allows to test some theories previously such as changing process parameters, process scale, and initial conditions, without the real costs and specially the whole kind of risks. In addition, there is the possibility of turning the simulation model into a control solution or, at least, part of that.
8.3.1 Examples of techniques There are many strategies for modeling and simulating industrial processes. Bioprocesses specifically have some peculiarities such as the uncertainties in the model parameters, normally described by ordinary differential equations, taking into account kinetic coefficients, for instance, and some not totally described relations as the yield and specific growth rate, depending on the product and microorganism involved, besides the processes behavior usually contain non-linearities. These characteristics lead to discuss about the importance
of making use of modem mathematical modeling techniques in accordance to Edelstein-Keshet (2004). In some cases it is unfeasible to take into consideration all the variables and its behavior, or even know all of them, hence new approaches are indispensable to face these kind of problem. The following sections show several examples of useful methods.
8. 3.1.1 Fuzzy logic The concept of Fuzzy Logic, accordingly to Zadeh (1965), was presented at first time not as a control methodology, but as a way of processing data, considering partial set membership rather than crisp set membership or nonmembership, as the so-called Classical Logic. As presented in Zadeh (1990), Professor Lotfi A. Zadeh explained that people do not require precise numerical information input, and yet were capable of highly adaptive control. Human beings often consider imprecise expressions like "tall", "expensive", or "not so far" (Sturm, 2005). However, the processing mode of a computer is limited to a one-or-zero, everything-or-nothing, or true-false mode of thinking. Gupta (1977) asserts that Fuzzy Logic is able to remove barriers between human being communication mode and computer processing mode. Professor Zadeh proposed the concept of linguistic or "fuzzy" variables, which invited to think as linguistic objects or words instead of numbers. Fuzzy Logic presents a rule-based approach to describe the process behavior rather than attempting to model the system mathematically or the modeling task is empirically-based, depending on human experience and not exactly technical understanding of the whole process. This approach allows to handle poor defined problems, where there are variables not exactly known, concerning to its behavior or importance to some specific process, which frequently happens in bioprocesses. Thus, it is not necessary to consider all the variables; in most cases it could be prohibitive and the nonlinearities are often absorbed by the proper Fuzzy Logic manner of describing problems and working with them.
8.3.1.2 Neural networks According to Norgaard et al., (2000), most of human abilities were learned by examples. That is how emerged the interest of transferring this didactic model into a computer's program. Neural Networks are a kind of approach designed to mimic the real human brain neural connections. Anthony and Bartlett (1999) mentioned that an Artificial Neural Network needs a training process, where examples were presented and were supposed to be learned. A neural network consists of a large number of simple neurons, which is often richly interconnected and each one is a part of program with normally very simple function to execute. The so-called synaptic weight associated with the connections between
neurons will determine the characteristics of the network. During the training process, the network automatically adjusts the values of synaptic weights. Actually, only one neuron has no function but the pattern of synaptic weight values in the whole network that carries information. The patterns are generated by the network and, because of that, it is not possible to describe analytically the whole process used to solve the problem. Norgaard et al., (2000) explains that the interest in using this approach is because of the ability of working with non-linear systems and the learning capacity. Sometimes researchers know the behavior of a specific Bioprocess, but are not able to describe each variable influence itself. Thus a Neural Network could be able to learn from the practical examples showed, even if the mathematical model is not understandable as an equation or something like that, but presenting the same results as the real process or manipulating the control parameters, leading to an adequate and stable work value.
8.3.1.3 Genetic algorithms (GA) According to the theory suggested by Charles Darwin in 1859, the biological alive species evolution would be due to the natural selection resulting from the competition for food and the reproduction ("struggle for life"). Holland et al., (1986) asserts that this mechanism of creation/selection is very simple, therefore, its application as software algorithms seems to be natural. The introduction of these mechanisms on computer solutions took place in early seventies and received the name of Genetic Algorithms known by the initials GA. The way that genetic algorithms treat a problem is very simple. Firstly, GA works in prospecting on a group of objects, not on an object. The group of objects is a whole population of different objects. Each element of the group receives a fitness value. This value allows the object to know which is the best solution to a given problem and the fitness is calculated in an objective way by the means of an evaluation function. This evaluation function is the process part which is guided by a known field. However, the process of prospecting is not guided in a specific knowledge field. The individuals or objects are coded by sequences of bits so that it is possible to make an analogy with the chromosomes. As in the biological creatures, the genetic operations on these sequences of bits are not found on a specific field of knowledge. The characteristics of the individuals are coded by chromosomes neutral sequences and the genetic operations are made on these chromosomes. Thanks to this characteristic of specific science field independence, the genetic algorithms are universal and of special interest to prospect in areas whose the results possibilities are not known. With a population and their fitness a new generation is created. The process of creation analogically follows the natural process of evolution where the most powerful individuals have more chance to reproduce. Rising generation,
thus, will replace, with a certain probability, the old individuals less adapted to their medium. GA turns possible to prospect in most of the target medium and in a short lapse of time. Normally the prospecting must finish when an optimum is found in target space. The probability of having found a good optimum increases accordingly to the number of individuals used in simulation.
8.4 THE FERSOL2 EXAMPLE The new software Fersol2 is based upon the so-called Fersol. This software was developed in 1987, running only on DOS operational system, using the methods described by in Rodriguez Leon et al., (1988) to manipulate solidstate fermentation (SSF) parameters. In SSE instead of what happens in submerged fermentation, the kinetic process behavior is very difficult to analyze. It is due to the impossible separation of biomass from the solid substrate and because of its heterogeneous characteristic (Pandey et al., 2001). The interest in studying kinetic process behavior is because of the fact that it allows many important parameters determination such as specific growth rate, process yield and productivity, heat evolved, process control criteria, strategy for the production of a particular product, and scale-up considerations (Pandey et al., 2001). The biomass synthesis is one of the most important patterns present in a fermentation bioprocess. In submerged fermentation process, this parameter can be normally measured through direct methods such as cell counting, dry biomass or optical density determination. Nevertheless, in SSF the proper characteristic is that the biomass will be attached to solid surface, hence, it is not so easy to measure directly. Thus, some indirect methods can be used as the determination of protein content or another cell component (Raimbault 1981; Okasaki et al., 1980; Matchman et al., 1985), or through the oxygen consumption and production of CO2 in (Nishio et al., 1979; Carrizalez et al., 1981; Koba et al., 1986). Regarding the software solution, the 02 consumed and/or CO2 evolved seems to be more adequate because of on-line measurement possibility and fast results (Pandey et al., 2001) and this method could be considered as a direct measurement of process kinetics, although in true sense it is still an indirect measure of biomass synthesis. To develop the Fersol2 software, it was decided that it should run on Microsoft Windows operational system because of the advantages and resources offered by the system. It was decided to use DotNet platform and C Sharp (C#) programming language, both with new concepts of programming, because of the performance, resources, and longevity concerning the time to turn obsolete. The platform allows to develop solutions which runs under Windows and Linux operational systems, adding more versatility.
8.4.1 Farsol2 calculations As pointed out in Pandey et al., (2001) and observing all the considerations, using some computing power it is possible to estimate the biomass (Xn) through an appropriate software solution. Making use of a mathematical set of method called Numerical Calculus, Fersol2 is able to calculate the integral and differential equations. As an example to evaluate the total oxygen consumed, it is useful the integral equation described by Pandey et al., (2001):
ftt
dt
From the Numerical Calculus, the numerical integration is applied by the Trapeze Rule, which leads to a discrimination of the theoretical equation, but in this specific case the values are taken from a table of oxygen quantity consumed, hence it is not quite a problem. The result is equivalent to the area under the oxygen consumption curve, determined by some periodic measures. On the other hand, some problems need an iterative method to solve. To determinate the biomass (Xn), making use of Metabolic Gas Balance Method described in Pandey et al., (2001), it is necessary to make an adjust in the biomass curve using the following equation:
Xn ~
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Where a = m.Yx/o.At. Taking into account some real measures of the biomass at a determined time and the initial process conditions, a kind of trial and error method is used to adjust the intermediary values. Numerical Calculus presents many iterative methods to solve this kind of problem because the trials should not be chosen randomly, it is necessary to maximize the convergence and it allows using some stop criteria to the number of iterations. In the present time the available computers, concerning to performance features, and the software development tools allow this kind of calculation without any additional care. Instead, some years ago the programmers should keep in mind the limitations of computing power, thus the algorithms were developed to adequate the problem complexity to the time to solve it, in other words there were some problems which could be unfeasible since would take much long to solve.
8.4.2 Fersol2 results As has been pointed out in the previous section, the Fersol2 software uses updated techniques to manipulate all the parameters. After adjusting the biomass values, it estimates many other process indicators such as, process yield based on consumed oxygen for biomass synthesis, specific growth rate at the logarithmic or exponential phase, and maintenance coefficient. It is possible to show virtually in only one window all the parameters, it turn easier to visualize the process behavior. The software interface is shown in the following figure.
It is possible to plot the curves of oxygen, biomass, and logarithmic biomass. The following figure 1 and figure 2 show the oxygen and the biomass curves. Using the Windows or Linux operational system and additional software as text editors or spreadsheet applications software as Microsoft Office's Excel and Word or the contents of Open Office, for instance, Fersol2 allows to export or import all the values and graphics; thus, it turns easier to analyze and produce documentation.
8.5 THE DATA ACQUISITION AND CONTROL SOFTWARE EXAMPLE Some of considerations pointed out in the previous section take into account the necessity of having on-line information about the fermentation process behavior, concerning to temperature, air flow, oxygen consuming, and CO2
Fig. 1.
Fig. 2. production, for instance. Sometimes to control or monitor a process it is necessary to consider real time analysis, which is all situation where there is a time window to execute some operation and/or fix some system fault, after this the error will be considered irreversible. Normally critical time applications are real time applications also. Nowadays it is possible to use the communication ports such as RS232 or, today more commonly, USB ports to make the acquisition of external sensor signals accordingly to Kelly and Bai, (2005). In addition, some protocols are getting more usual as Ethernet and Fieldbus in industrial
plants and a strong trend in wireless communication as BlueTooth will certainly be present in a great number of applications. The data transfer rate has been increasing and communication protocols became more friendly specially when using the updated Windows versions and appropriate programming platform. Thus, this kind of solution turned more cost effective. The controlling devices available in industrial commerce are normally open communication protocol and the development frameworks allow making the communication drivers more friendly by the programmers. Using adequate sensors and controlling devices, accordingly to Wang and Tan (2006), an acquisition or control software can read any parameter value and transfer it into the computer, besides the distributed control possibility allows to keep these parameters monitored even if the communication between process and computer is interrupted. In this case with eventual loss of data, of course, but keeping the advantage of maintaining the system under local control. Acquisition or control software can also display values on the screen such as tables and graphics in real time and making some calculations such as unit conversion and values statistics evaluation in accordance to Wang and Tan (2006).
8.6 CONCLUSIONS The Solid State Fermentation process carries many peculiarities that lead to the necessity of investigating new approaches to solve several kinds of complex problems. The technological advance, in informatics and computation sciences, allows the researchers and developers to use updated techniques with even more increased performance and resources availability. These characteristics permit using some sophisticated methods with cost effective performance. An evolutive solution software could be adequate because of its flexibility and adaptation capacity. Some of the solutions discussed demonstrate that the proper indirect measures necessity in SSF is, itself, a strong argument to make use of more complete mathematical models, with the consequent need to apply more accurate analysis, which is only possible using the informatics features available nowadays.
Acknowledgment The authors acknowledge Conselho Nacional de Desenvolvimento Cientifico e Tecnologico -CNPq for financial support and Universidade Federal do Parana - UFPR.
References Anthony, Martin, Bartlett & Peter L, 1999, Neural Network Learning: Theoretical Foundations. 403p. p 1,5. Cambridge University Press: Cambridge. Carrizalez V, Rodriguez H & Sardifia I, 1981, Determination of the specific growth rate of molds on semi-solid cultures. Biotechnology and Bioengineering, 23, 321.
Dergint Dario EA, 1999, Apprentissage Collectif et Milieux Innovateurs 9l~tude de Cas Grenoble et Simulations Multi-Agents - Thesis. p 567. UTC, Compi~gne. Edelstein-Keshet L, 2004, Mathematical Models in Biology. p 586. Siam: Philadelphia. Gupta MM, 1977, Fuzzy Automata and Decision Processes. New York: Elsevier.
Harrington H. James, & Tumay Kerim, 2000, Simulation Modeling Methods: To Reduce Risks and Increase Performance. p 1-3. p 379. McGraw-Hill: New York. Holland John H, Keith J Nisbett, Richard E Thagard & Paul R, 1986, Induction: Processes of Inference, Learning and Discovery. Cambridge, Mass: MIT Press.
Jennings Nicholas R, Sycara Katia & Wooldridge Michael, 1998, A Roadmap of Agent Research and Development- Autonomous Agents and Multi-Agent Systems. pp. 7-38. Boston: Kluwer Academic Publishers. Kelly Laurie & Bai Ying, 2005, The Windows Serial Port Programming Handbook. p 4, 5. CRC Press LLC: Charlotte.
Koba Y, Feroza B, Fujio Y & Ueda S, 1986, Journal of Fermentation Technology, 62, 2, p. 175. Matchman SE, Jordan BR & Wood DA, 1985, Estimation of fungal biomass by three different methods. Applied Microbiology and Biotechnology, 21, p. 108. Nishio N, Tai Tai & K Nagai S, 1979, Hydrolase production by Aspergillus niger in solid state cultivation. European Jounal of Applied Microbiology and Biotechnology, 8, p. 263. Norgaard M, Ravn O, Poulsen NK & Hansen LK, 2000, Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook. 246 p. Springer-Verlag London Limited: Great Britain. Okasald N, Sugama S & Tanaka T, 1980, Mathematical model of surface culture of koji mold, Journal of Fermentation Technology, 58, 5, p. 471.
Pandey A, Soccol CR, Rodriguez-le6n JA & Nigam P, 2001, Solid State Fermentation in Biotechnology: Fundamentals and Applications. Asiatech Publishers, Inc. New Dehli. India. Raimbault M, 1981, Travaux et Documents de 1'ORSTOM, No. 27, Paris. Rodriguez Le6n J A, Sastre L, Echevarria J, Delgado G & Bechstedt W, 1988, A Mathematical Approach for the estimation of biomass production rate in solid-state fermentation, Acta Biotechnologica, 8 (4), 299-302,
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Sturm Wilerson, 2005, Avalia~o do Potencial de Uso da L6gica Fuzzy para a Identifica~o
de Indicadores de CompetSncias no Currfculo Lattes. Dissertation. p 104. April-25-2005. Centro Federal de Educa~ao Tecnol6gica do Parami. Curitiba. Syeara Katia P, 1998, Multiagent Systems, AI Magazine, 79-92. Wang Lingfeng, Tan & Kay Chen, 2006, Industrial Automation Software Design, p 158,159 John Wiley and Sons: New Jersey. Zadeh LA, 1965, Fuzzy Sets. Information and Control, 8, 338-353. Zadeh LA, 1990, The birth and evolution of fuzzy logic. In: TURKSEN, I.B. Proceedings of NAFIP'90.
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iiii!iiiii iiiiiiiiiiiiiii!! !ii 9.1 INTRODUCTION The process of solid-state fermentation for food applications is one of the oldest knowledges available to humans. To many communities it is a part of their traditional knowledge to prepare the fermented food (Hesseltine, 1977). The expanded form of Japanese word for Koji relates to growth of mold. The traditional fermentations such as Koji, Tofu, miso, sauceges, pickles, ensilling are the extension of the traditional fermentation knowledge exploiting the GRAS strains of fungi and bacteria to carry out the fermentation. The processes provide extracellular fungal enzymes and have been the basis to initiate the microbial enzymes production by SSF in industrial environment. The koji process undoubtedly influenced the first production of microbial enzymes by SSF on industrial scale. The emergence of modem SSF based enzyme industry may be attributed to the entrepreneurship of Jokichi Takamine and later by Underkofler's efforts in producing mold bran enzymes for saccharification of grain (Bennett, 2001). The discovery of Penicillin in early thirtee's and streptomycin, chloramphenicol and tetracyclin's in early fifty's took the sheen of the emerging SSF process and emphasized on submerged fermentation. The SSF process development was still in its infancy and was considered not suitable for many of the potential large-scale applications. However, recently with lot of effort being put into value addition of agroindustrial residues and publications emphasizing the possibilities in SSF (Pandey, 1992, 1994, 1999, 2000, 2001; Pandey and Soccol, 2000; Lonsane & Ghildyal, 1992; Babu & Satyanarayana, 1996; Haltrich et al., 1996; Mitra et al., 1996; Selvakumar et al., 1996; Tengerdy, 1998) commercial operations using SSF process were developed in countries such as Japan, India, USA, and France. The successful operation of the companies utilizing the SSF process ensured that the process gets its due attention and apart from enzymes the pharmaceutical products and other secondary metabolites were also manufactured. The major
applications of solid-state fermentation involve processes exploiting fungal systems and to a lesser extent bacterial systems, however, recently some actinomycetes were also reported especially for production of bioactive compounds using SSF (Kota and Sridhar, 1998; Sircar et al., 1998; Saudagar et al., 2006). The fungal systems are an obvious choice, as these systems require solid support matrices for their growth under natural circumstances. In natural habitats fungi grow on wood, bark, leaves of plant, decaying organic matter and other moist surfaces. Given this tendency for adhered growth under natural environments fungi have been exploited for maximum extent. The enzymes being produced by SSF include cellulases, hemicellulases, pectinase, amylases, ct- and ~galactosidases, caffeinase, tannase, proteases etc. The major support matrices include bran's (wheat, rice, barly), oil cakes (sesame, soy, olive, coconut, mustard), bagasse (sugarcane, cassava, orange), coffee pulp and husk (Pandey and Soccol, 2000) and also substrates such as Jackfruit seed powder, tamarind seed powder. In the present chapter the authors are presenting a brief account of developments in SSF process during last five years as the earlier developments had already been discussed in various reviews and b-bok chapters.
9.2 MiCRO-ORGANISMS AND METHODS OF IMPROVING SSF PRODUCTIVITY The potential candidates for enzyme production using SSF process are bacteria and fungi. The bacteria from diverse habitat have been isolated and studied for fermentative applications however mesophilic and themophilic fungi have been more successfully utilized. A number of commercial enzymes such as alphaamylase and glucoamylases, pectinases, hemicellulases, phytases, xylanases and proteases are produced by fungi. The fungal systems used for koji preparations such as A. sojae, A. oryzae and other like A. niger are considered as GRAS strains (Generally Regarded as Safe). The fungal strains such as A. terreus, A. tamarii, A. ustus, Rhizopus oryzae, Rhizopus oligosporus and Penicillium sp. strains are also being frequently explored for production of enzymes. Apart from the commonly used fungal strains, bacterial strains such as Bacillus spp. are being increasingly exploited (Table 1). The yield enhancement of the SSF process has been mostly studied by traditional approach of screening for new culture with improved production and their process optimisation. However, now recombinant DNA approach using genetically engineered systems is also being explored. The approach is of potential importance given the ability to modify the host genome by introducing novel genes responsible for improved traits. The recombinant DNA approach has been successfully applied for studying the phytase, amylase, protease and biochemicals such as diacetal, folate, riboflavin, mannitol and lactic acid. The recombinant DNA approach
has been successfully exploited for improvement of lactic acid bacteria especialy for applications in dairy industry. The applications included flavour enhancement, resistance to bacteriophages, addition of nutritional components and stability and structure of end products. However, the recombinant approach requires the cultural conditions of the modified organisms to be examined to provide conditions that would fully exploit the increased potential of the culture. Also, the process of strain improvement involves the continual genetic modification of the culture, followed by reappraisals of its cultural requirements (Stanbury et al., 1995) and needs special training to cater to these requirements. The initial efforts in genetic modifications were concentrated using traditional approaches such as exposing to mutagenic agents such as ethyl methyl sulphonate, NNG, NTG and UV radiations. However, to exploit enzyme production fight metabolic regulatory elements need to be modified using recombinant DNA approaches. This approach of modifying the entire production pathways is called as metabolic pathway engineering. This requires complete knowledge of the pathway and various control elements working in it.
9.3 SUBSTRATES USED FOR THE PRODUCTION OF ENZYMES IN SSF The recent SSF process studies have explored a variety of substrates varying from agro-residues to wastes of industries such as potato chips, spent brewing grain, paper and wood processing industries. The wastes such as saw dust and wood chippings have a huge potential for cellulases and hemicellulases production. Substrates such as sugar cane bagasse, wheat bran, rice bran, maize bran, gram bran, wheat straw, rice straw, rice husk, soyhull, sago hampas, grapevine trimmings dust, saw dust, corncobs, coconut coir pith, banana waste, tea waste, cassava waste, palm oil mill waste, aspen pulp, sugar beet pulp, sweet sorghum pulp, apple pomace, peanut meal, rapeseed cake, coconut oil cake, mustard oil cake, cassava flour, wheat flour, corn flour, steamed rice, steam pre-treated willow, starch, etc. have been studied for SSF applications. Recently green gram husk was used as a good support for alkaline protease production (Prakasham et al., 2006). Also oil cakes and their combinations have been explored recently with much success for phytase, amylase and protease production. The other developments include the solid-state fermentation process using inert support material supplemented with chemically defined liquid media for production of enzymes, metabolites and biological control agents (Ooijkaas et al., 2000). The SSF process may have a major application in production of bio-control agents for large-scale field applications given the requirement of biocontrol agents at an economical price and ease of directly using the fermentation media. The several studies have already reported effect of substrate, its particle size and moisture level/water activity in the media.
Table 1. Microorganisms for enzyme production using SSF
9.4 SSF REACTOR DEVELOPMENT The delay in SSF being the major mode of fermentation can be partly attributed to the bioreactors initially available. During the initial phases mostly tray type of fermenters were in use with poor instrumentation support and also, heat generated during the process was poorly dissipated. Although recently research was directed on SSF reactor development however, simultaneous instrumentation development has so far been lagging. Initially, automated koji (tray) cultivation was most frequently applied (Pandey et al., 1999). Later on different bioreactor configurations such as periodic pressure solid state fermenter (Tao et al., 1999), immersion, expanded bed and tray type reactor (Couto et al., 2002), intermittent agitation rotating drum type (Kalogeris et al., 2003) and a new bioreactor "PlaFractor" (Suryanarayan, 2003) were developed for the production of enzymes, biocontrol agents and pharmaceuticals. The traditional tray type reactors consist stacked trays contained in a container with sterile humidified air being circulated for aeration and moisture maintenence. Although, the column bioreactors have been used for enzyme production studies (Pandey et al., 1996; Mitchell et al., 1999) however, these reactors suffering from differences in growth, enzyme synthesis and sporulation pattern in different segments of the column (Pandey et al., 1996) could not be used for industrial scale fermentation. Recently some efforts were made to improve upon the tray bioreactors by using spouted bed bioreactor. The studies suggested that intermittent spouting of tray reactor with air achieved high production levels of (~-amylase with yields comparable to packed bed bioreactor (Silva and Yang, 1998). Also, periodically dynamic changes of air have been found effective in controlling temperature instead of agitation and rotation that damage or disrupt fungal mycelia and reduce the porosity of the substrates (Chen et al., 2005).
9.5 FACTORS AFFECTING ENZYME PRODUCTION IN SSF SYSTEMS The various factor which need to be studied for successful SSF process development include: a suitable substrate and microorganism, the treatment requirement for easy substrate availability to micro-organism, substrate particle size, water content and water activity of the substrate, relative humidity, nature of inoculum, temperature stability, heat dissipation and maintenance of uniformity, duration of fermentation (Pandey et al., 1999). Although, the SSF systems have been known for their simplicity and relatively low level of instrumentation requirements but for process automation purposes more instrumentation support is necessary. Although, the PlaFractor fermenter developed at B iocon India, has been developed keeping the process automation requirements in mind. However, various aspects of SSF processes such as development of probes mainly for moisture measurement, control and regulation of process variables,
analytical procedures to specific media and measurement of the gaseous environment still need to be explored (Durand, 2003). Also, various problems of scale like mass compaction, shrinkage, and reduction of the heat transfer (Durand, 2003) etc. require careful studies. The factors affecting the fermentation scale-up in SSF are mainly poor heat removal (Mitchell et al., 2003) leading to problems in temperature control and oxygen limitation (dos Santos et al., 2004). The air being poor conductor of heat is not suitable for conducting the heat and also it requires maintaining certain level of moisture, which can only be done by providing humidified air. However, the disadvantage of poor heat removal can be used advantageously using thermophilic organisms which require elevated temperatures (Kalogeris et al., 2003)'
9.6 ENZYMES PRODUCED BY SSF Although much work has been carried out on SSF for the production of enzymes of industrial importance such as proteases, cellulases, ligninases, xylanase, pectinase, amylase, glucoamylase, etc., attempts are also being made to study SSF processes for the production of inulinases, phytases, tannase, phenolic acid esterase, microbial rennet, aryl-alcohol oxidase, oligosaccharide oxidase, tannin acyl hydrolase, a-L arabinofuranosidase, etc. using SSF systems. In the following sections, a brief account on production of selected enzymes in SSF systems would be discussed. 9.6.1 Cellulases and hemicellulases Cellulose is an insoluble molecule consisting of glucose units ranging from 2000-10000 residues while some chains may be still bigger in size. The glucose units are arranged linearly as ~-(1-4)-D-glucopyranose and form crystals. The intra-molecular and intra-strand hydrogen bonds hold the network. The cellulase has many uses as an anticake agent, emulsifier, stabilizer, dispersing agent, thickener, and gelling agent and also has water-holding capacity. The cellulases represent a group of enzymes capable in breaking cellulose. They comprise of endoglucanases (1,4-[3-D-glucan glucanohydrolases), exoglucanases or cellobiohydrolases (1,4-~-D-glucan cellobiohydrolases) and ~-glucosidases or cellobiases ([3-D-glucoside glucohydrolases). The cellulases have various applications ranging from extraction and/or clarification of fruit and vegetable juices, to baking, brewing, biostoning of denim and deinking of the recycled pulp and paper.
Trichoderma reesei is the most studied mesophilic fungus and five endoglucanases, two cellobiohydrolases and one ~-glucosidase have been already identified from this source. The other organisms studied include Aspergillus niger, Melanocarpus sp., Scymlidium thermophilum and Thermoascus aurantiacus. The cellulase
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production studies in Melanocarpus sp. and Scytalidium thermophilum suggested that expression profile of different components of cellulase complex in thermophilic fungi, Melanocarpus sp. MTCC 3922 is independently regulated while in Scytalidium thermophilum MTCC 4520 it is co-regulated (Kaur et al., 2006). The cellulose rich agricultural crop wastes such as wheat straw, rice straw, corncob, corn stover, wheat bran, etc. have been used for cellulase production. Similarly, the SSF has been extensively utilized for production of hemicellulases. The hemicelluloses are a group of complex carbohydrates containing xylans, uronic acid and arabinose. The main chain of xylans is built from 13-1, 4-1inked xylopyranosyl residues. The backbone is usually substituted to various degrees by residues of 4-O-methyl-D-glucuronic acid, D-glucuronic acid, or L-arabinofuranose, and in some cases is also esterified by acetyl groups (Biely, 2003). Due to the structural heterogeneity of the xylans, xylan-degrading enzyme systems include several hydrolytic enzymes. The best known of these are endo-~-l,4-xylanases, which attack the main chain of xylans, and 13-xylosidases which hydrolyze xylo-oligosaccharides to D-xylose (Haltrich et al., 1996). Xylanases have various applications including production of oligosaccharides, baking, starch recovery from wheat flours and aid in the extraction and clarification of fruit juices. The hemicellulases also find application in feed industry to improve the digestibility of feed and in paper and pulp industry for biopulping and help in reducing the consumption of chlorides for developing an ecofriendly process The xylanase production has recently been reported from lot of fungal systems such as Thermomyces lanuginosus, Thermoascus aurantiacus, Aspergillus awamori, A. niger, A. oryzae, Penicillium canescens, Ceriporiopsis subvermispora, Melanocarpus albomyces, P. thermophila J18 and Trichoderma reesei. The substrates used mostly for xylanase production include wheat bran, corn cobs, sugarcane bagasse, bagasse pulp, spent sulphite liquor, rice straw, wheat straw, sorghum flour and eucalyptus pulp. However, lignocellulosic materials especially wheat bran has been more successful in production with higher titers being attributed to its hemicellulose nature, favorable degradability and the presence of some nutrients in the carbon source (Sonia et al., 2005). Also, wheat straw is reported to be ideally suitable for xylanase production in T. aurantiacus and Penicillium canescens cultures (Kalogeris et al., 1999; Bakri et al., 2003).
9.6.2 Ligninases Lignins are three-dimensional phenylpropanoid polymers, considerably resistant to microbial degradation in comparison with polysaccharides and other naturally occurring biopolymers. Ligninases have applications in delignification of lignocellulosic materials, which can be used as the feedstock for the production of biofuels, paper pulp and animal feedstuff. These may also be used in pulp
bleaching, paper mill wastewater detoxification, pollutant degradation, or conversion of lignin into valuable chemicals. Lignin itself is good asphalt binder with applications in road constructions and also has fuel applications. The Ligninases comprise a group of enzymes represented by Lignin peroxidase (LIP, EC- 1.11.1.7), manganese peroxidase (MnP, EC- 1.11.1.13) and laccase (EC-1.10.3.2). LiP and MnP are heme-containing glycoprotein which require hydrogen peroxide as an oxidant. LiP oxidizes non-phenolic lignin structures by abstracting one electron and generating cation radicals, while, MnP oxidizes Mn(II) to Mn(III), which then oxidizes phenolic compounds to phenoxy radicals. This leads to the decomposition of lignin substructure. Laccases are multicopper phenol oxidases, which reduces oxygen to water and simultaneously catalyze the oxidation of aromatic pollutants like anilines and phenols. Several methods using laccase, immobilized laccase and laccase/mediator system have been developed for the treatment of the textile effluents. This enzyme decolorizes some azo dyes without direct cleavage of the azo bond through a highly nonspecific free radical mechanism, thereby avoiding the formation of toxic aromatic amines. Recently, laccases produced from various organisms such as whiterot fungus Daedalea quercina, Stereum hirsutum and Peniophora sp and Streptomyces cyaneus were studied for decolorization of synthetic dyes (Baldrian, 2004) and biopulping of softwood chips in SSF (Wolfaardt et al., 2004; Berrocal et al., 2004). The biological pretreatment studies of wheat straw resulted in better quality cellulose pulps.
9.6.3 Proteases Proteases constitute a very large and complex group of enzymes, which differ in properties such as substrate specificity, active site and catalytic mechanism, pH and temperature activity and stability profiles. Milk clotting enzymes have been in use to transform milk into products such as cheese. Use of proteases ,/ 4n baking is another important food application. The inability of the plant and animal proteases to meet the demands led to an increased interest in microbial proteases. Proteases from microbial sources are preferred to the enzymes from plant and animal sources because of their ease of manipulation for biotechnological applications. Microbial proteases are classified based on the pH range of their activity as acidic, neutral and alkaline proteases and based on the functional group at their active site as serine proteases, aspartic proteases, cysteine proteases, and metalloproteases. Neutral proteases are active within a narrow pH range, have pH optima near neutral, have relatively low thermal tolerance and have applications in preparation of food hydrolysates, baking, protein modification, in leather, animal feeds and pharmaceutical industries. Aspergillus oryzae is the predominant source of the
enzyme. Its affinity for hydrophobic amino acids is an advantage in minimizing the bitterness in protein hydrolysates. While, acid proteases may be classified into two groups based on weather their catalytic activity resembles rennin or pepsin. Rennins like enzymes are characterized by their ability to clot milk and have major commercial importance in cheese manufacture. The group of pepsin like acid proteases includes bovine and porcine pepsin and microbial acid proteases mainly from Aspergilli. The microbial acid proteases have applications in the hydrolysis of soybean protein in soy sauce manufacture, improvement of baking properties and digestive aids. Microbial pepsin-like acid proteases mainly produced by strains of Aspergillus and Rhizopus spp. are active in acidic pH and have moderate temperature tolerance. Solid-state fermentation for proteases has been a preferred mode of fermentation with fungal systems, because of the presence of extracellular enzymes making their recovery easier. The SSF processes usually being simpler can use cheaper agro-industrial residues such as wheat bran, rice bran, sesame oil cake, soybean oil cake, coconut oil cake etc. for production. The recovery also is easier because, the enzyme is produced in concentrated form. The neutral and acidic proteases are widely used in food industry for cheese ripening, meat tenderization, in brewing industry, and for production of protein hydrolysates, as a digestive aid and in bread making.
9.6.4 Lipases Lipases catalyse the hydrolysis of ester bonds at the interface between water insoluble fatty acid ester or glyceride phase and the enzyme-containing aqueous phase. Lipases find their application in hydrolysis of fats and oils, in transesterification, production of biosurfactants, digestive aid formulation, detergents, enantiomeric separations and steriospecific transformations. Lipases are being increasingly explored for tolerance to organic solvents with applications in organic synthesis for chiral selective reactions The chirality is a key factor in the efficacy of many drug products and agrochemicals, and thus the production of single enantiomers of chiral intermediates is becoming increasingly important in the pharmaceutical industry. Although, lipases from various microorganisms have been produced but commercially available lipases are mostly from Aspergillus niger and Rhizopus oryzae. The R. oryzae lipase has found application in bio-diesel production (Ban et al., 2001). Various agro-industfial residues such as coconut oil cake extract, cotton cake, soy cake, gingelly oil cake, olive oil cake, sugarcane bagasse, barley bran, wheat bran, babassu oil cake have been evaluated singly as well as in various combinations, for lipase production. Apart from fungal systems such as Aspergillus niger, Rhizopus oryzae, Penicillium restrictum
Penicillium simplicissimum, Trichoderma versicolour, and T. Hirsuta, bacterial systems such as Bacillus megaterium have also been studied recently for lipase production under SSF conditions.
9.6.5 Galactosidases and pectinases There has been considerable interest to produce t~- galactosidase (EC- 3.2.1.22), ~-galactosidase (EC- 3.2.1.23) and polygalacturoanase (PG, EC- 3.2.1.15) in SSF processes. These enzymes have application in the pharmaceutical and food industries. ~-Galactosidase (t~-D-galactopyranoside galactohydrolase EC 3.2.1.22) finds applications in industries ranging from beet sugar production to hydrolysis of raffinose and stachyose present in soybean, cowpea and other leguminous crops. The presence of these oligosaccharides is the reason of diarrhoea and flatulence caused by consumption of soy products and pretreatment with ct- galactosidase may help their enhanced applications in food and feed industries. Aspergillus oryzae has been mostly used as a source of tx-galactosidase. Although, recently actinomycetes have also been studied for ct- galactosidase production but the relative advantage of Aspergillus oryzae as a GRAS strain makes its enzyme acceptable for food and feed applications. ~i-Galactosidase (or lactase) hydrolyzes the milk sugar, lactose, to its components glucose and galactose and thus finds applications in milk and milk products meant for lactose intolerant peoples, for prevention of lactose crystallization in frozen and condensed milk products, for the reduction of water pollution caused by whey and also for increasing the sweetening properties of lactose. Although, production of ~-galactosidase has been studied with various orgaisms such as Trichoderma reesei, Aspergillus niger, Bifidobacteria, Lactobacillus acidophilus, Kluyveromyces fragilis, kluyveromyces lactis, Kluyveromyces marxianus. However, only Trichoderma reesei and Aspergillus niger have been studied for SSF production. The various substrates used for fermentation include arabinoxylan, wheat bran and lactose etc. and further exploitation using SSF is desired. The pectinases, a complex of pectin-degrading enzymes, consist mainly of pectin methylesterases, endo- and exo-polygalacturonases, pectin lyases and causes deesterification, chain splitting and glycoside-bond cleavage. They have been used extensively by fruit, wine and vegetable industries for various functions such as maceration, extraction, liquefaction, clarification and valorization. AspergiUus niger, A. carbonarius, A. sojae and Rhizopus sp. are the most frequently used fungi for pectinase production in commercial scale. A variety of substrates such as soy and wheat flour, sugar beet pulp, deseeded sunflower head, orange pomace, lemon pulp, orange bagasse, sugarcane bagasse have been studied singly and in combination for pectinase production.
9.6.6 Glutaminase L- glutaminase (L-glutamine amidohydrolase - E.C. 3.5.1.2) is the enzyme deamidating L-glutamine and plays a major role in the cellular nitrogen metabolism of both prokaryotes and eukaryotes. L-glutaminase is useful in the food industry as it increases the glutamic acid content of the fermented food thereby imparting a unique flavour. Besides its food value, ability of this enzyme to bring about degradation of glutamine poses it as a possible candidate for enzyme therapy, which may replace or combine with L-asparaginase in the treatment of acute lymphocytic leukaemia. However, not much is reported recently on L-glutaminase production. The recent reports on L-glutaminase production reported the exploitation of Zygosaccharomyces rouxii NRRL-Y 2547, Cryptococcus nodaensis, Beauveria sp and Streptomyces rimosus but only Zygosaccharomyces rouxii NRRL-Y 2547 and Beauveria sp. were studied for SSF applications. The substrates such as wheat bran and sesamum oil cake have been studied apart from inert supports such as polystyrene supplemented with glucose and L-glutamine.
9.6.7 Amylases The amylases can be broadly classified into two major classes of alpha-amylase and glucoamylase. The a-amylase (endo-1, 4-t~-D-glucan glucohydrolase, EC3.2.1.1) randomly cleaves the 1,4-a-D- glucosidic linkages between adjacent glucose units in linear amylose chain, and glucoamylase or amyloglucosidase (exo-1, 4-o~-D-glucan glucanohydrolase, EC- 3.2.1.3) hydrolyses single glucose units from the non-reducing ends of amylose and amylopectin in a stepwise manner. The glucoamylases are capable of hydrolysing both t~-1,4 and a-1,6 linkages. The enzymes have applications in the starch processing, food, fermentation, textile, detergent and paper industries. The amylases are used in baking industry to improve the quality of dough, in fermentation industry for glucose production for fermentative applications, in pharmaceutical for preparation of glucose syrups and in feed industry to act as a digestive aid. The Aspergillus oryzae has been a preferred organism for fungal alpha-amylases for food and pharmaceutical applications while both Apergillus and Rhizopus spp. have been used for glucoamylase production. The recent studies suggested that oil cakes/ meal such as coconut oil cake, soy meal may also be used efficiently in mix substrate fermentation for amylase production. The other in expensive substrates such as spent brewing grain, rice husk, rice flakes, cassava starch, sugar cane bagasse, orange bagasse, molasses, rice bran, maize meal, millet cereal, wheat flakes, barley bran, crushed maize, corncobs and crushed wheat have also been studied in solid state fermentation (SSF). However, in most of the studies wheat bran has been found to be the best substrate for amylase production in SSE Given the requirement of starch processing industry to have thermotolerant amylase, the efforts were directed in identifying thermostable amylases. The bacterial and actinomycetes amylases were found to be having thermostability
properties. However, for food related applications amylases from actinomycetes may not found much favour. The bacterial alpha-amylase from B. stearothermophilus GRE1, Bacillus subtilis, Bacillus licheniformis, Geobacillus thermoleovorans have been found to be moderate to highly thermostable while alpha-amylase from other sources such as Bacillus cereus MTCC 1305, Bacillus amyloliquefaciens and fungal systems such as Thermomyces lanuginosus have also been studied. The fungal glucoamylase production has already been reported using inexpensive nutrient sources such as wheat bran, tea waste and coconut oil cake. However, recently rice-processing waste (coarse, medium and fine waste) along with rice powder was also studied for glucoamylase production. The various isolates studied include Aspergillus sp. HA-2, AspergiUus niger, Scytalidium thermophilum,
Aspergillus awamori, Rhizopus oligosporus and Thermomucor indicae-seudaticae. The thermophilic mold Thermomucor indicae-seudaticae was reported for production of a thermostable and neutral glucoamylase optimally active at 40~ and pH=7, when grown in wheat bran moistened with a salt solution in 1:2.5 (w/v) ratio supplemented with 2% cotton oil seed cake (Kumar and Satyanarayana, 2004).
9.6.8 Phytase Phytases (myo-inositol hexakisphosphate phosphohydrolase, EC 3.1.3.8) catalyses the release of phosphate from phytate (myso-inositol hexaksiphosphate). Several cereal grains, legumes and oilseeds, etc. have their phosphorus stored in the form of phytate. The phytate phosphorus is not easily accessible for monogastric animals due to low inherent phytase activity and passes in manure. The areas with high density of cattle and swine farming suffer from ground water contamination due to the high-phytate phosphorus manure. The pollution of water bodies due to high phosphate manure has raised serious problems of water blooms and growth of toxin producers. Phytases appear of significant value in effectively controlling phosphate pollution. Although, phytase can be produced from a host of sources including plants, animals and micro-organisms. Microbial sources, however, are promising for their commercial exploitations. Strains of Aspergillus spp., chiefly A. ficuum and A. niger have most commonly been employed for industrial purposes. Apart from them Rhizopus oligosporus, Rhizopus oryzae, Mucor racemosus and Aspergillus ficuum have also been studied for phytase production. Given the desirability of thermostable phytase to survive the feed pelleting process search has now began for thermotolerant phytase and attempts have already been made to use genetic engineering to manipulate the phytase for thermostability. The traditional approach using thermophilic molds such as Sporotrichum thermophile has also been evaluated for thermostable phytase production. Recent studies suggest agro-industrial residues such as
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sesame oil cake, coconut oil cake, groundnut oil cake and soy oil cake are suitable as a single substrate as well as in combination for phytase production under SSF conditions.
9.6.9 Inulinase Inulin is a naturally occurring polyfructan in plants consisting of linear chains of 13 (2,1)-linked fructose residues attached to a terminal sucrose molecule. The polysaccharide is widely distributed in plants such as Jerusalem artichoke, Chicory, Dahlia and Asparagus. Microbial inulinases (2,1-13-D fructan fructanohydrolase (EC 3.2.1.7) are usually inducible and exo-acting enzymes, which catalyse the hydrolysis of inulin by releasing the end fructose molecule. Different Aspergillus, Staphylococcus sp. and Kluyveromyces strains have been studied for the production of inulinases. The solid-state fermentation for the production of inulinase using coconut oil cake and ssugarcane bagasse has been studied as support and carbon source for production of inulinase. The nitrogen supplementation in the form of corn steep liquor has also been studied. The optimum fermentation conditions for inulinase production were found to be: 36~ and 20 wt.% of corn steep liquor using Kluyveromycesmarxiana (Mazutti et al., 2006). However not much work has been reported of late in inulinase production using SSF and most of the work still remains in SmF conditions. Although, studies were conducted by immobilizing the conidia of Aspergillus niger 20 Osm producing extracellular inulinase on pumice stones and polyurethane sponge for use in repeated-batch processes, only some factors affecting inulinase biosynthesis by the mycelium were studied. It was observed that immobilization enabled repeated-batch enzyme production and as many as six subsequent 24 h batches could be fermented by using the same carrier (Skowronek and Fiedurek, 2006). However given the importance of inulinase in production of mannitol, inulo-oligosaccharides~low caloric oligosaccharides, bio-ethanol and also high fructose syrup for sweetening applications, improved inulinase production remains to be explored by SSE 9.6.10. Miscellaneous e n z y m e s The various other enzymes reportedly being explored using SSF process include tannase, chitinase, invertase, and alpha L-arabinofuranosidase etc. 9.7. RECOVERY OF THE ENZYMES Recovery process for enzymes depends upon the nature of product and its intended application. The higher end applications may require more purified enzymes while the industries such as textile, paper and pulp and feed industry may require the crude enzyme preparations. While the enzyme required for
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pharmaceutical and organic synthesis may be the purified one to avoid any side reactions leading to undesired by products. Since most of the enzymes are secreted in the medium hence, they may be simply extracted with water or buffer solutions after mixing for 30 min- 1 hr and removing the mycelia by centrifugation. Since most of the industries desire to have a cost effective downstream process and most of the enzyme preparations have been found useful even in the crude form, hence the enzyme extraction is the preferred mode of recovery. Extraction temperature and pH of the extractant may be sometimes important for enzyme stability. Further purification of enzyme preparations may be brought by ammonium sulphate or acid precipitation followed by ultrafiltration and column chromatography. However, this may lead to overall cost increase of final product.
9.8 CONCLUSIONS The SSF process has been found to be cost effective for many enzyme production processes vis a vis SmF. The increasing cost of feed for SmF, value addition to agro-industrial residues and ease of operation makes the SSF process more favourable. Also, SSF process requires less initial capital and incurs low operating cost and is suitable for agriculture-based economies. The production of industrial enzymes by SSF will have an important role in future biotechnologies. The focus in SSF application is required to study for enzyme specific SSF process development, development of host specific environments, SSF targeted fungi and bacteria and on their genetic improvement for desired tasks. The emerging trends also suggest development of IPR for SSF related processes. The SSF offers suitable conditions for microorganisms capable of growing at elevated temperatures and future developments may lead to their better exploitation of thermotolerant organisms and products by SSE
Reference Agrawal D, Patidar P, Banerjee T & Patil S, 2004, Production of alkaline protease by Penicillium sp. under SSF conditions and its application to soy protein hydrolysis, Process Biochemistry, 39, 977-981. Anto H, Trivedi UB & Patel KC, 2006, Glucoamylase production by solid-state fermentation using rice flake manufacturing waste products as substrate, Bioresource Technology, 97: 1161-1166. Babu KR & Satyanarayana T, 1996, Production of bacterial enzymes by solid-state fermentation, Journal of Scientific and Industrial Research, 55, 464-467.
Bakri Y, Jacques P & Thonart P, 2003, Xylanase production by Penicillium canescens 10-10c in solid-state fermentation, Applied Biochemitsry and Biotechnology, 108, 737-748. Baldrian P, 2004, Purification and characterization of laccase from the white-rot fungus Daedalea quercina and decolorization of synthetic dyes by the enzyme, Applied Microbiology and Biotechnology, 63 (5), 560-563. Ban K, Kaieda M, Matsumoto T, Kondo A & Fukuda H, 2001, Whole cell biocatalyst for biodiesel fuel production utilizing Rhizopus oryzae cells immobilized within biomass support particles, Biochemical Engineering Journal, 8, 39-43. Baysal Z, Uyar F & Aytekin C, 2003, Solid-state fermentation for production of t~amylase by a thermotolerant Bacillus subtilis from hot-spring water, Process Biochemistry, 38, 1665-1668. Bennett JW, 2001, Aspergillus and koji: history, practice and molecular biology. SIM News. 51, 65-71. Berrocal MM, Rodriguez J, Hernandez M, Perez MI, Roncero MB, Vidal T, Ball AS & Arias ME, 2004. The analysis of handsheets from wheat straw following solid substrate fermentation by Streptomyces cyaneus and soda cooking treatment, Bioresource Technology, 94, 27-31. Biely P, 2003, Diversity of microbial endo-B-1, 4-xylanases, Applications of Enzymes to Lignocellulosics, SD Mansfield & JN Saddler (eds), ACS Symposium Series 855, American Chemical Society, Washington, DC. pp 361-380. Binod P, Pusztahelyi T, Nagy, V, Sandhya C, Szakacs G, Pocsi I & Pandey A, 2005, Production and purification of extracellular chitinases from Penicillium aculeatum NRRL 2129 under solid-state fermentation, Enzyme and Microbial Technology, 36: 880-887. Bogar B, Szakacs G, Pandey A, Sabu A, Linden JC & Tengerdy RP, 2003, Production of phytase by Mucor racemosus in solid-state fermentation, Biotechnology Progress, 19, 312-319. Botella C, De Ory I, Webb C, Cantero D & Blandino A, 2005, Hydrolytic enzyme production by Aspergillus awamori on grape pomace, Biochemical Engineering Journal, 26 (2-3), 100-106
Chantasartrasamee K, Na Ayuthaya DI, Intarareugsorn S & Dharmsthiti S, 2005, Phytase activity from Aspergillus oryzae AK9 cultivated on solid-state soybean meal medium, Process Biochemistry, 40, 2285-2289. Chert HZ, Xu J & Li ZH, 2005, Temperature control at different bed depths in a novel solid-state fermentation system with two dynamic changes of air, Biochemical Engineering Journal, 123, 117-122. Couto SR, Moldes D, Liebanas A & Sanroman A, 2003, Investigation of several bioreactor configurations for laccase production by Trametes versicolor operating in solid-state conditions, Biochemical Engineering Journal, 15, 21-26. Di Luccio M, Capra F, Ribeiro NP, Vargas GDLP, Freire DMG & De Oliveira D, 2004, Effect of temperature, moisture, and carbon supplementation on lipase production by solid-state fermentation of soy cake by Penicillium simplicissimum, Applied Biochemistry Biotechnology- Part A: Enzyme Engineering and Biotechnology, 113-116, 173-180. dos Santos MM, da Rosa AS, DalBoit S, Mitchell DA & Krieger N, 2004, Thermal denaturation: is solid-state fermentation really a good technology for the production of enzymes? Bioresource Technology, 93, 261-268. Durand A, 2003, Bioreactor design for solid-state fermentation, Biochemical Engineering Journal, 13, 113-125. Ellaiah P, Adinarayana, K, Bhavani, Y, Padmaja P & Srinivasulu B, 2002, Optimization of process parameters for glucoamylase production under solid-state fermentation by a newly isolated Aspergillus species, Process Biochemistry, 38 (4), 615-620. Fadel M, 2001, High-level xylanase production from sorghum flour by a newly isolate of Trichoderma harzianum cultivated under solid-state fermentation, Annals of Microbiology, 51 (1), 61-78.
Gutarra MLE, Cavalcanti EDC, Castilho LR, Freire DMG & Sant'Anna Jr GL, 2005, Lipase production by solid-state fermentation: cultivation conditions and operation of tray and packed-bed bioreactors, Applied Biochemistry Biotechnology- Part A: Enzyme Engineering and Biotechnology, 121-124, 105-116. Haltrich D, Nidetzky B, Kulbe KD, Steiner W & Zupancic S, 1996, Production of fungal xylanases. Bioresource Technology, 58, 137-161 Haq IU, Idrees S & Rajoka MI, 2002, Production of lipases by Rhizopus oligosporous by solid-state fermentation, Process Biochemistry, 37:637-641
Hesseltine CW, 1977, Solid state fermentation - Part 1, Process Biochemistry, July/ August, 24-27. Jeya M, Thiagarajan S & Gunasekaran P, 2005, Improvement of xylanase production in solid-state fermentation by alkali tolerant Aspergillus versicolor MKU3, Letters Applied Microbiology, 41, 175-178. Kalogeris E, Fountoukides G, Kekos D & Macris BJ, 1999, Design of a solid-state bioreactor for thermophilic microorganisms, Bioresource Technology, 67, 313-315
Kalogeris E, Iniotaki F, Topakas E, Christakopoulos P, Kekos D & Macris BJ, 2003, Performance of an intermittent agitation rotating drum type bioreactor for solid-state fermentation of wheat straw, Bioresource Technology, 86, 207-213. Kang SW, Park YS, Lee JS, Hong SI & Kim SW, 2004, Production of cellulases and hemicellulases by Aspergillus niger KK2 from lignocellulosic biomass, Bioresource Technology, 91, 153-156. Kashyap DR, Soni SK, Tewari R, 2003, Enhanced production of pectinase by Bacillus sp. DT7 using solid-state fermentation, Bioresource Technology, 88, 251-254. Kaur J, Chadha BS & Saini HS, 2006, Regulation of cellulase production in two thermophilic fungi Melanocarpus sp. MTCC 3922 and Scytalidium thermophilum MTCC 4520, Enzyme and Microbial Technology, 38, 931-936. Kaur S, Vohra RM, Kapoor M, Beg QK & Hoondal GS, 2001, Enhanced production and characterization of a highly thermostable alkaline protease from Bacillus sp. P-2, World Journal of Microbiology Biotechnology, 17, 125-129. Kota KP & Sridhar P, 1999, Solid-state cultivation of Streptomyces clavuligerus for cephamycin C production, Process Biochemistry, 34, 325-328. Kovacs K, Szakacs G, Pusztahelyi T & Pandey A, 2004, Production of chitinolytic enzymes with Trichoderma longibrachiatum IMI 92027 in solid substrate fermentation, Applied Biochemistry and Biotechnology - Part A: Enzyme Engineering and Biotechnology, 118 (1-3), 189-204. Krishna C & Nokes SE, 2001, Influence of inoculum size on phytase production and growth in solid-state fermentation by Aspergillus niger, Transactions of the American Society of Agricultural Engineers, 44 (4), 1031-1036. Kumar S & Satyanarayana T, 2004, Statistical optimization of a thermostable and neutral glucoamylase production by a thermophilic mold Thermomucor indicae-seudaticae in solid state fermentation, World Journal of Microbiology and Biotechnology, 20, (8) 95-902. Lonsane BK & Ghildyal NP, 1992, Exoenzymes, in Solid Substrate Cultivation, HW Doelle, DA Mitchell & CE Rolz (eds), Elsevier Applied Science, London & New York, pp 191-209. Mahadik ND, Puntambekar US, Bastawde KB, Khire JM & Gokhale DV, 2002, Production of acidic lipase by Aspergillus niger in solid-state fermentation, Process Biochemistry, 38 (5), 715-721. Mazutti M, Bender JP, Treichel H & Di Luccio M, 2006, Optimization of inulinase production by solid-state fermentation using sugarcane bagasse as substrate, Enzyme and Microbial Technology, 39, 56-59. Mitchell DA, Pandey A, Sangsurasak P & Krieger N, 1999, Scale-up strategies for packed-bed bioreactors for solid-state fermentation, Process Biochemistry, 35, 167' 178.
Mitchell DA, von Meien OF & Krieger N, 2003, Recent developments in modelling of solid-state fermentation: heat and mass transfer in bioreactors, Biochemical Engineering Journal, 13, 137-147. Mitra P, Chakraverty R & Chandra AL, 1996, Production of proteolytic enzymes by solid state fermentation, Journal of Scientific and Industrial Research, 55, 439-442. Mo H, Zhang X & Li Zuohu, 2004, Control of gas phase for enhanced cellulase production by Penicillium decumbens in solid-state culture, Process Biochemistry, 39, 1293-1297.
Nampoothiri KM, Baiju TV, Sandhya C, Sabu A, Szakacs G & Pandey A, 2004, Process optimization for antifungal chitinase production by Trichoderma harzianum, Process Biochemistry, 39, 1583-1590. Ooijkaas LP, Weber F J, Buitelaar RM, Tramper J & Rinzema A, 2000, Defined media and inert supports: their potential as solid-state fermentation production systems, Trends in Biotechnology, 18, 356-360. Pandey A & Soccol CR, 1998, Bioconversion ofbiomass: A case study of lignocellulosics bioconversions in solid state fermentation, Brazilian Archives of Biology and Technology, 41,379-390.
Pandey A & Soccol CR, 2000, Economic Utilization of Crop Residues for Value Addition: A Futuristic Approach, Journal of Scientific ad Industrial Research, 59 (1), 12-22. Pandey A, 1992, Recent process developments in solid state fermentation, Process Biochemistry, 27, 109-117. Pandey A, 1994, Solid state fermentation - An overview, Solid State Fermentation, A Pandey (ed), Wiley Eastern Ltd, New Delhi, India, pp 3-10. Pandey A, Selvakumar P & Ashakumary L, 1996, Performance of a column bioreactor for glucoamylase synthesis by Aspergillus niger in SSF, Process Biochemistry, 31, 43-46.
Pandey A, Selvakumar P & Ashakumary L, 1996, Performance of a column bioreactor for glucoamylase synthesis by Aspergillus niger in SSF, Process Biochemistry, 31, 43-46. Pandey A, Selvakumar P, Soccol CR & Nigam P, 1999, Solid-state fermentation for the production of industrial enzymes, Current Science, 77, 149-162. Pandey A, Soccol CR & Mitchell D, 2000, New developments in solid-state fermentation. I. Bioprocesses and products. Process Biochemistry, 35, 1153-1169. Pandey A, Soccol CR, Rodriguez-Leon JA & Nigam P, 2001, Solid-state fermentation in biotechnology: fundamentals and applications. Asiatech Publishers Inc, New Delhi. Park YS, Kang SW, Lee JS, Hong SI & Kim SW, 2002, Xylanase production in solidstate fermentation by Aspergillus niger mutant using statistical experimental designs, Applied Microbiology Biotechnology, 58, 761-766.
Patidar P, Agrawal D, Banerjee T & Patil S, 2005, Optimisation of process parameters for chitinase production by soil isolates of Penicillium chrysogenum under solid substrate fermentation, Process Biochemistry, 40, 2962-2967.
Patil SR & Dayanand A, 2006a, Production of pectinase from deseeded sunflower head by Aspergillus niger in submerged and solid-state conditions, Bioresource Technology, 97 (16), 2054-2058.
Patil SR & Dayanand A, 2006b, Optimization of process for the production of fungal pectinases from deseeded sunflower head in submerged and solid-state conditions, Bioresource Technology, 97 (18), 2340-2344. Patil SR & Dayanand A, 2006c, Exploration of regional agrowastes for the production of pectinase by Aspergillus niger, Food Technology and Biotechnology, 44 (2), 289-292. Prakasham RS, Rao ChS & Sarma PN, 2006, Green gram husk-an inexpensive substrate for alkaline protease production by Bacillus sp. in solid-state fermentation, Bioresource Technology, 97 (13), 1449-1454. Purohit JS, Dutta JR, Nanda RK & Banerjee R, 2006, Strain improvement for tannase production from co-culture of Aspergillus foetidus and Rhizopus oryzae, Bioresource Technology, 97, 795-801. Ramachandran S, Patel AK, Nampoothiri KM, Chandran S, Szakacs G, Soccol CR & Pandey A, 2004a, Alpha amylase from a fungal culture grown on oil cakes and its properties, Brazilian Archives of Biology & Technology, 47, 309-317. Ramachandran S, Patel AK, Nampoothiri KM, Francis F, Nagy V, Szakacs G & Pandey A, 2004b, Coconut oil cake - a potential raw material for the production of alpha-amylase, Bioresource Technology, 93, 169-174.
Ramachandran S, Roopesh K, Nampoothiri KM, Szakacs G & Pandey A, 2005, Mixed substrate fermentation for the production of phytase by Rhizopus spp. using oilcakes as substrates, Process Biochemistry, 40, 1749-1754. Rattanakit N, Yano S, Wakayama M, Plikomol A & Tachiki H, 2003, Saccharification of chitin using solid-state culture of Aspergillus sp. S 1-13 with shellfish waste as a substrate, Journal of Bioscience & Bioengineering, 95, 391-396. Rodriguez JA, Mateos JC, Nungaray J, Gonzdlez V, Bhagnagar T, Roussos S, Cordova J & Baratti J, 2006, Improving lipase production by nutrient source modification using Rhizopus homothallicus cultured in solid-state fermentation, Process Biochemistry.
Roopesh K, Ramachandran S, Nampoothiri KM, Szakacs G & Pandey A, 2006, Comparison of phytase production on wheat bran and oilcakes in solid-state fermentation by Mucor racemosus, Bioresource Technology, 97, 506-511. Sabu A, Pandey A, Jaafar Daud M & Szakacs G, 2005, Tamarind seed powder and palm kernel cake: two novel agro residues for the production of tannase under solid state fermentation by Aspergillus niger ATCC 16620, Bioresource Technology, 96, 1223-1228.
Sabu A, Sarita S, Pandey A, Szakacs G, Bogar B & Soccol CR, 2002, Coconut oil cake as a substrate for the production of phytase by Rhizopus oligosporus, Applied Biochemistry & Biotechnology, 102/103, 251-260.
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Sandhya C, Sumantha A, Szakacs G & Pandey A, 2005, Comparative evaluation of neutral protease production by Aspergillus oryzae in submerged and solid-state fermentation, Process Biochemistry, 40, 2689-2694. Saudagar PS, Singh SK, Singhal RS & Pandey A, 2006, A solid-state fermentation process for the preparation of clavulanic acid, Indian Patent Application NF/042/ 2006. Selvakumar P, Ashakumary L & Pandey A, 1996, Microbial synthesis of starch saccharifying enzyme in solid cultures, Journal of Scientific & Industrial Research, 55, 443-449. Shah AR, & Madamwar D, 2005, Xylanase production under solid-state fermentation and its characterization by an isolated strain of Aspergillus foetidus in India. World Journal of Microbiology and Biotechnology, 21,233-243. Silva E & Yang ST, 1998, Production of amylases from rice by solid state fermentation in a gas-solid spouted-bed bioreactor, Biotechnology Progress, 14, 580-587. Silva D, Tokuioshi K, da Dilva Martins E, Da Silva R & Gomes E, 2005, Production of Pectinase by solid-state fermentation with Penicillium viridicatum RFC3, Process Biochemistry, 40, 2885-2889. Sircar A, Sridhar P & Das PK, 1998, Optimization of solid state medium for the production of clavulanic acid by Streptomyces clavuligerus, Process Biochemistry, 33, 283-289. Skowronek M & Fiedurek, J. 2006. Inulinase biosynthesis using immobilized mycelium of Aspergillus niger, Enzyme and Microbial Technology, 38, 162'167. Soares VF, Castilho LR, Bon EPS & Freire DMG, 2005, High yield Bacillus subtilis protease production by solid-state fermentation. Applied Biochemistry and Biotechnologypart A, Enzyme Eng & Biotechnology, 121-124, 311-319.
Sodhi HK, Sharma K, Gupta JK & Soni SK, 2005, Production of a thermostable oramylase from Bacillus sp. PS-7 by solid-state fermentation and its synergistic use in the hydrolysis of malt starch for alcohol production, Process Biochemistry, 40 (2), 525-534. Soni SK, Kaur A & Gupta JK, 2003, A solid-state fermentation based bacterial tx-amylase and fungal glucoamylase system and its suitability for the hydrolysis of wheat starch, Process Biochemistry, 39 (2), 185-192.
Sonia KG, Chadha BS & Saini I-IS, 2005, Sorghum straw for xylanase hyper-production by Thermomyces lanuginosus (D2W3) under solid-state fermentation, Bioresource Technology, 96, 1561-1569. Stanbury PF, Whitaker A & Hall SJ, 1995, Principles of fermentation technology, 2nd edition, Pergamon.
Sumantha A, Sandhya C, Szakacs G, Soccol CR, Pandey A, 2005, Production and partial purification of neutral metalloprotease fungal mixed substrate fermentation, Food Technology & Biotechnology, 43, 313-319.
Suryanarayan S, 2003, Current industrial practice in solid state fermentations for secondary metabolite production: the Biocon India experience, Biochemical Engineering Journal, 13, 189-195. Szendefy J, Szakacs G, Christopher L, 2006, Potential of solid-state fermentation enzymes of Aspergillus oryzae in biobleaching of paper pulp, Enzyme & Microbial Technology, 39, 1354-1360. Tao S, Beihui L, Zuohu L & Deming L, 1999, Effects of air pressure amplitude on cellulase productivity by Trichoderma viride SL-1 in periodic pressure solid-state fermenter, Process Biochemistry, 34, 25-29.
Tengerdy RP & Szakacs G, 1998, Perspectives in agrobiotechnology, Journal of Biotechnology, 66, 91-99. Tengerdy RP, 1998, Solid substrate fermentation for enzyme production, in Advances in Biotechnology, A Pandey (ed), Educational Publishers & Distributors New Delhi, pp 13-16. Trevino-Cueto B, Luis M, Contreras-Esquivel JC, Rodriguez R, Aguilera A & Aguilar CN, 2007, Gallic. acid and tannase accumulation during fungal solid-state culture of a tannin-rich desert plant (Larrea tridentata Coy.), Bioresource Technology, 98 (3), 721724.
Virupakshi S, Gireesh Babu K, Gaikwad SR & Naik GR, 2005, Production of a xylanolytic enzyme by a thermoalkaliphilic Bacillus sp. JB-99 in solid-state fermentation, Process Biochemistry, 40, 431-435. Wolfaardt F, Taljaard JL, Jacobs A, Male JR & Rabie C J, 2004, Assessment of woodinhabiting basidiomycetes for biokraft pulping of softwood chips, Bioresource Technology, 95, 25-30.
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i:i,{:~,ii:!,i:~i{.:i,:.,Christian i:,.:i,~.ii,:,:, Larroche & Ashok Pandey 10.1 INTRODUCTION The global market for fermentation products was estimated as $14.1 billion in 2004 and was expected to rise at an average annual growth rate (AAGR) of 4.7% to $17.8 billion in 2009. In this context, organic acids represent the third largest category among the other products. Total market value of organic acid is expected to rise to $3 million in 2009 (Marz 2005). Organic acids are among the most versatile ingredients in food and beverage industries. Citric acid, acetic acid, lactic acid, tartaric acid, malic acid, gluconic acid, propionic acid and fumaric acid are some of the organic acids used widely in various industries. They are obtained as the end-products or sometimes as the intermediate components of a particular biochemical cycle. Generally, organic acids are produced commercially either by chemical synthesis or fermentation. However, fermentation processes are the most commonly used method. All organic acids of tricarboxylic acid cycle can be produced in high yields in microbiological processes. Among fermentation processes, the production of organic acids is dominated by submerged fermentation. Table 1 presents some facts about global production of organic acids. Global production of citric acid has reached 1.4 million tons with annual growths of 3.5-4.0% in demand/consumption rate of citric acid. In terms of volume, citric acid and acetic acid together account for about three-quarters of food acidulants. The production of organic acids by solid-state fermentation (SSF) is associated with the historical development of SSF. Citric acid has been known to be produced in SSF for many years while other organic acids such as lactic acid, fumaric acid, oxalic acid and gluconic acid have been reported to be produced in SSF only during the last few years. Many by-products and residues of the agro-industries can be utilized in their production by solid-state fermentation, which minimizes environmental problems and also serves as economical alternative production method.
Table 1. Global production of organic acids
10.2 MICROBIAL PRODUCTION OF ORGANIC ACIDS A large number of microorganisms including bacteria such as Arthrobacter paraffinens, Bacillus licheniformis, Corynebacterium sp., Lactobacillus casei, L. helveticus, L. paracasei, Streptococcus thermophilus; fungi such as Aspergillus niger, A. aculeatus, A. carbonarius, A. awamori, A. foetidus, A. fonsecaeus, A. phoenicis, Rhizopus oryzae, Penicillium janthinellum; and yeasts such as Candida tropicalis, C. oleophila, C. guilliermondii, C. citroformans, Hansenula anamola, Yarrowia lipolytica, etc. have been employed for the production of organic acids (Ikeno et al., 1975, Kubicek and Rohr, 1986, Yokoya, 1992, Grewal & Kalra, 1995, Vandenberghe et al., 1999). In the case of citric acid production, some of them are not able to produce commercially acceptable yields due to the fact that citric acid is a metabolite of energy metabolism and its accumulation rises in appreciable amounts only under conditions of drastic imbalances. Among the strains, A. niger has remained the organism of choice for commercial production because it produces more levels of citric acid per time unit. The main advantages of using A. niger are its ease of handling, its ability to ferment a variety of cheap raw materials, and high yields. The problem associated with the production of citric acid by the yeasts is the simultaneous formation of isocitric acid. Efforts have been made to develop microbial strains which could produce high yields of organic acids. The most commonly employed technique has been by inducing mutations in parental strains using mutagens (Yokoya, 1992, Grewal & Kalra, 1995, Vandenberghe et al., 1999, Pandey et al., 2001, Ikram-ul-Haq et al., 2001). Among mutagens, y-radiation, UV-radiation and chemical mutagens
are often used. Among different approaches, one has been to combine the UV treatment with some chemical mutagens. The "single-spore technique" and the "passage method" are generally the principal methods of selecting strains. The first one has the disadvantage that mineral acid and organic acids (gluconic and oxalic acids) simulate the presence of citric acid (Kubicek and Rohr, 1986, Vandenberghe et al., 1999, Pandey et al., 2001, Rohr et al., 1983).
10.3 SUBSTRATES FOR ORGANIC ACIDS PRODUCTION Various agro-industrial residues such as cassava bagasse, coffee husk, apple pomace, soybean, potato residues, pineapple waste, wheat bran, kiwi fruit peel, kumara, okara, carob-pods, corn-cobs, sugarcane press-mud, citric pulp, etc. have been used in SSF for the production of organic acids. There has been an increasing trend towards efficient utilization and value-addition of these residues as they are generally very well adapted to solid-state cultures due to their cellulosic and starchy nature. Different organic acids have been produced using such residues as substrates, e.g. L (+) lactic acid (Soccol et al., 1994a,b, Shojaosati & Baboeipur, 2002), citric acid (Hang & Woodams, 1984, 1985, Pintado et al., 1998, Soccol et al., 1999, Soccol and Vandenberghe, 2003, Vandenberghe, 2000, Vandenberghe et al., 1999, 2000, 2004), oxalic acid (Leagon et al., 1999) and gluconic acid (Roukas et al., 2000, Singh et al., 2003). Table 2 summarizes the production of some organic acids produced by solid-state fermentation using different agro-industrial residues. 10.4 ORGANIC ACIDS PRODUCED BY SOLID-STATE FERMENTATION 10.4.1 Citric acid Citric acid (C6H807, 2-hydroxy-1,2,3-propane-tricarboxylic acid), a natural constituent and common metabolite of plants and animals, is the most versatile and widely used organic acid. Its global production of about 1.4 million tons was estimated by Business Communications Co. (BCC) in a recent study of fermentation chemical markets in 2004. The report showed that China accounted for 35-40 % of worldwide citric acid production (Graf, 2005, Food Production Daily, 2004). Citric acid is widely used to impart a pleasant, tart flavor to foods and beverages. It also finds application as a function of additive, detergents, pharmaceuticals, cosmetics and toiletries. 10. 4.1.1 Production Citric acid production by fermentation is the most economical and widely used method. More than 90 % of the citric acid produced in the world is obtained by fermentation which has its own advantages: operations are simple and stable; the plant is generally less complicated and needs less sophisticated control
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systems; technical skills required are lower; energy consumption is lower and frequent power failures do not critically affect the functioning of the plant. Citric acid production by fermentation can be divided into three phases, which include preparation and inoculation of the raw material, fermentation and recovery of the product. The industrial citric acid production can be carried out by three different ways: by submerged fermentation, surface fermentation and solid-state fermentation or "Koji" process (Yokoya, 1992, Grewal & Kalra, 1995, Vandenberghe et al., 1999, Soccol et al., 2006). In industrial citric acid fermentation, the large-scale spore production is made by using appropriate means and conditions such as direct inoculation in the production fermenter. Sometimes it is necessary to remove the remainder mineral of the raw material and add other nutrients such as phosphorous, magnesium and nitrogen for development of the mycelium and a good production of the citric acid. Several types of systems have been used for citric acid production in solidstate fermentation such as Erlenmeyer conical flasks, glass incubators, trays, rotating and horizontal drum bioreactors, packed-bed column bioreactor, singlelayer packed-bed, multi-layer packed-bed, e t c (Grewal & Kalra, 1995, Pandey et al., (2001), Vandenberghe et a1.,1999, 2004, Lu et al., 1997, Pintado et al., 1998, Prado et al., (2004). Classically, the solid-sate process has been carded out in trays with aeration. Higher yields (347 g/kg dry cassava bagasse) were obtained in flasks without any aeration, and very little sporulation was observed (Vandenberghe et al., 2004). Equivalent yields (309 g/kg of dry cassava bagasse) were obtained in column reactors only with variable aeration. This showed good perspective in using solid culture process for citric acid production in simple tray type fermenter. In fact, the scale-up study of production of citric acid showed that in tray bioreactors with 4-cm bed thickness 263 g/kg of dry cassava bagasse were attained (Vandenberghe et al., 2004). Several raw materials such as hydrocarbons, starchy materials including agroindustrial residues and molasses have been employed as substrates for citric acid production (Table 2) (Vandenberghe et al., 1999, 2000, Soccol et al., 2004, Yokoya, 1992, Hang & Woodams, 1984, 1985, 1998, Kolicheski, 1995, Vandenberghe, 2000, Soccol et al., 2004). To perform SSE the solid substrate is moistened to about 70%, depending on the substrate absorption capacity. The initial pH of the material is normally adjusted to 4.5-6.0 and the temperature of incubation is about 28-30 ~ depending on the microorganism used (Hossain et al., 1984, Xu et al., 1989, Vandenberghe et al., 1999, 2004, Pintado et al., 1998, Prado et al., 2004). The solid culture process is generally completed within 96 h under optimal conditions (Kubicek & Rohr, 1986, Vandenberghe et al., 1999). SSF processes also normally do not require complex nutritional
supplementation such as trace elements and also their presence may not be harmful (as it does in submerged fermentation). This is one of the important advantages of the solid culture (Grewal and Kalra, 1995, Vandenberghe et al., 1999, Soccol et al., 2004).
10.4.1.2 Chemical factors affecting the production Citric acid accumulation is strongly influenced by the type and concentration of carbon source (Soccol et al., 2004, Roukas & Kotzekidou, 1987). The presence of carbohydrates which are rapidly taken up by microorganisms has been found essential for a good production of citric acid (Yokoya, 1992). Among the easily metabolized carbohydrates, sucrose is the most favourable carbon source followed by glucose, fructose and galactose (Yokoya, 1992, Vandenberghe et al., 1999, Soccol et al., 2004). Table 3 shows the main factors that affect citric acid production.
Phosphorous: The presence of phosphate in the medium has a great effect on the yield of citric acid. Low levels of phosphate have positive effect on citric Table 3. Chemical factors affecting citric acid production
acid production. This effect acts at the level of enzyme activity and not at the level of gene expression. On the other hand, the presence of excess of phosphate leads to a decrease in the fixation of carbon dioxide, which in turn increases the formation of certain sugar acids, and the stimulation of growth (Kubicek & Rohr, 1986, Grewal & Kalra, 1995, Vandenberghe et al., 1999). Nitrogen: Citric acid production is directly influenced by the concentration and nature of the nitrogen source. Physiologically, ammonium salts are preferred such as urea, ammonium nitrate and sulphate, peptone, malt extract, etc. (Soccol et al., 2004). Acid anamonium compounds are preferred because their consumption leads to pH decrease, which is essential for the citric fermentation. However, it is necessary to maintain pH values in the first day of fermentation prior to a certain quantity biomass production. The concentration of nitrogen source required for citric acid fermentation is 0.1 to 0.4 g N/L (Yokoya, 1992, Kubicek & Rohr, 1986). High nitrogen concentrations increase fungal growth and sugar consumption but decrease the amount of citric acid produced (Vandenberghe et al., 1999). Trace elements: Trace metal ions have a significant impact on citric acid accumulation by A. niger (Roukas & Kotzekidou, 1987). Divalent metal ions such as zinc, manganese, iron, copper and magnesium affect citric acid production. It is crucial to take into account the interdependence of medium constituents. There is elevated production of citric acid only if a rigorous control of the trace elements availability is accomplished, but mainly in the submerged process. Lower alcohols: Lower alcohols in pure form inhibit citric acid production but if added as crude carbohydrates, enhance citric acid production. Methanol, ethanol, n-propanol, isopropanol or methylacetate neutralize the negative effect of the metals in citric acid production generally in amounts about 1 to 5 % (Ingram & Buttke, 1984, Dasgupta et al., 1994). Even so, optimal amount of methanol and ethanol depends upon the strain and the composition of the medium. Alcohols have been shown to act principally on membrane permeability in microorganisms by affecting phospholipid composition. Other studies showed that alcohols stimulate citric acid production by affecting growth and sporulation on space organization of the membrane or changes in lipid composition of the cell wall (Ingram & Buttke, 1984). Other compounds: Oils and fats are used in citric acid production to control the foam formation. In addition, some oils stimulate productivity and maintenance of fermentation processes. This lipids act as carbon sources and they are consumed during the fermentation, which is necessary to maintain its level above 0.05-0.3 % (Yokoya, 1992, Grewal & Kalra, 1995).
10.4.1.3 Physical factors affecting the production pH: The pH of a culture may change in response to microbial metabolic activities. The most obvious reason is the secretion of organic acids, such as citric acid, which causes the pH decrease. Changes in pH kinetics also depend highly on the microorganism. It is known that growth of Aspergillus sp., Penicillium sp. and Rhizopus sp. can results in decrease in pH very quickly to less than 3.0. For other groups of fungi such as Trichoderma, Sporotrichum, Pleurotus sp., pH is more stable between 4.0 and 5.0. The nature of the substrate and production technique also influences pH kinetics (Yokoya, 1992). It is desirable that initial pH must be very well defined and optimized depending on the microorganism, substrate and production technique.
Aeration: Since citric acid production is an aerobic process; oxygen supply has a determinant effect on its production. An interruption of aeration during batch fermentation could be quite harmful (Grewal & Kalra, 1995). Dissolved oxygen concentration influences the citric acid formation directly. It is important to maintain the oxygen concentration above 25 % saturation (Vandenberghe et al., 1999). Critical dissolved oxygen tension is 9-12 % of air saturation for growth phase and 12-13 % of air saturation for the production phase (Yokoya, 1992, Grewal & Kalra, 1995). The high demand of oxygen is reached by constructing appropriate aeration devices, which is also dependent on the viscosity of the fermentation broth. This is an additional reason why small compact pellets are the preferred mycelial forms of A. niger during the production. When the organism turns into developments of filaments, the dissolved oxygen tension rapidly falls to less than 50 % of its previous value, even if the dry weight has not increased by more than 5 %. Aeration should be performed through the medium during the whole process with the same intensity, although due to economic reasons, it is usually preferred to start with low aeration rates. The incorporation of the oxygen together with air in submerged process results in increment of citric acid production, but it is economically unviable (Yokoya, 1992). However, it is possible to circulate the oxygen in the fermenter since the carbonic gas is removed from the process. High aeration rates lead to high amounts of foam, especially during the growth phase, so the addition of antifoaming agents and the construction of mechanical "defoamers" are required to tackle this problem (Vandenberghe et al., 1999, Soccol et al., 2004). Forced aeration at the beginning of the process in solid-state fermentation packed-bed reactor affects metabolic rates, and thus, citric acid productivity. The study of citric acid production by A. niger in SSF revealed the importance of a CO2 rich atmosphere. It is known that an environment with high concentrations
of CO2 has a positive effect on citric acid synthesis. The high partial pressure of CO2 probably retards spore liberation of the filamentous fungi and favours citric acid synthesis with cassava bagasse as support/substrate. In fact, low oxygen environment is directly involved in the growth limitation, which is crucial for citric acid production. Low aeration rates (0.18 m3/kg dry CB/h) are supposed to limit the respiration activity of A. niger and, consequently, to turn the metabolism to citric acid synthesis and not to biomass production. It was also observed that strongly aerated cultures (0.3 m3/kg dry CB/h) increased sporulation. As the sporulation increased, the accumulation of citric acid decreased (Vandenberghe, 2000, Vandenberghe et al., 2004).
Production in semi-pilot scale: The influence of different percentages of gelatinized starch present in cassava bagasse on citric acid production by SSF was studied in horizontal drum and tray-type bioreactors. Gelatinization of starch of cassava bagasse was conducted in order to make starch structure more susceptible to its consumption by the fungus Aspergillus niger. Figure 1 shows the citric acid production in tray-type (TT) bioreactor with different percentages of TCB. The best result was 26.3 g/100g of dry CB with 80% of TCB and 4 cm of bed thickness. Citric acid values for 100 % of raw CB were negligible in TT bioreactors. Figure 2 presents citric acid production in horizontal drum (HD) bioreactor with different percentages of TCB. In this case, the best result was obtained with 100% of TCB yielding 26.9 g of citric acid/100g of dry CB. These results show the importance of the starch gelatinization, which surely made starch structure more accessible to fungus attacks. The influence of the TCB percentage on citric acid production was clearly observed in HD bioreactor where high degrees of gelatinization were favorable. On the other hand, in TT bioreactor, it was not necessary to gelatinize CB
Figure 1. Citric acid production in tray-type bioreactors with O, 40, 60, 80 and 100% of treated cassava bagasse in 2, 4 and 6 cm of bed thickness, Vandenverghe et at., (2004).
Figure 2. Citric acid production in horizontal drum bioreactor with O, 40, 60, 80 and 100% of treated cassava bagasse, Vandenverghe et at., (2004).
starch at high levels. This fact could be explained by the excessive material compaction, due to starch gelatinization, which limited the air insertion through out the medium. In HD bioreactor there was not high substrate compaction because it was revolved 3 or 4 times a day and its initial moisture was lower than in the process carried out in TT bioreactors (Table 4). There was no significant difference between the best results obtained in HD bioreactor (26.9 g of citric acid/100g of dry CB) and in TT bioreactors (26.3 g of citric acid/100g of dry CB).This proved that aeration was not a determinant factor for citric acid production in SSF, as it is in submerged citric acid fermentation. The study of the citric acid production for A. niger cultivated by SSF in trays also revealed the importance of the rich atmosphere in COe. The high partial pressure in CO2 probably delays the liberation of spores by filamentous fungus favoring the citric acid synthesis. The limitation of the growth is an important factor in the production of the citric acid. This fact was checked in previous studies in Erlenmeyer flasks where the limitation of Table 4. Citric acid production in bioreactors*
*Vandenverghe et at., (2004)
the growth provoked by a higher concentration of CO2 resulted higher citric acid accumulation (Vandenberghe, 2000). In trays higher bed thickness became more compact during fermentation than lower bed thickness. This was due to the fact that in more compact substrate layers there was more CO2 accumulation and, consequently, more citric acid production. The values for 80% of treated CB have not followed this trend, but in this case citric acid produced in 4 and 6 cm of bed thickness did not present significant difference as presented in Table 3. However, citric acid production for 100% of treated CB in all bed thickness was lower than 80% of treated CB due the excessive accumulation of CO2 caused by high compaction of the substrate. Another important factor to be considered was the fermentation time, which for trays (120h) was shortest than for the HD bioreactor (144 h). Moreover, energy consumption in trays was also lower considering the need of intermittent agitation of the substrate in HD bioreactor. Hence, the cost of the process conduced in TT bioreactors would be lower.
10.4.1.4 Recovery from SSF medium Citric acid from the fermented solid material is generally leached out using water. Recovery from the extracts is generally accomplished in three processes, precipitation, extraction and adsorption and absorption using ion-exchange resins. Precipitation is the classical method and it is performed by the addition of calcium oxide hydrate (milk of lime) to form the slightly soluble tri-calcium citrate tetrahydrate. The precipitated tri-calcium citrate is removed by filtration and washed several times with water. The precipitate is then treated with sulphuric acid to form calcium sulphate, which is removed by filtration. Mother liquor containing citric acid is treated with active carbon and passed through cation and anion exchangers. Several anion-exchange resins are commercially available. Finally, the liquor is concentrated in vacuum crystallisers at 20-25~ forming citric acid monohydrate. Anhydrous citric acid is prepared following the process of crystallisation at higher temperature than 25~
10. 4.1.5 Applications of citric acid As stated above, citric acid has got sevral industrial applications. Table 5 some of its significant used for different porposes.
10.4.2 Fumaric acid Fumaric acid is a useful intermediate in several chemical synthesis including esterification and polymerization, and in the manufacture of sizing resins for the paper industry (Petruccioli et al., 1996). It can easily be produced from
Table 5. Citric acid applications
Rhizopus arrhizus on an industrial scale, but fermentative production has long been abandoned for economic reasons and replaced by the cheaper acid-catalysed isomerization of maleic acid obtained by oxidation of benzene, or phtalic anhydride (Ueno, 2003). Biotechnological processes could possibly be developed using cheap and readily available substrates (Kosseva et al., 1998; Idris et al., 2003; Yan et al., 2001; Klinkenberg et al., 2001). Fumaric acid was produced in repeated batch processes using Rhizopus arrhizus NRRL 1526 immobilised in polyurethane sponge particles and cultivated in a fluidised-bed reactor. Acid production was optimized (12.3 g/l, 35.65% and 0.256 g/1 h of fumaric acid accumulation yield and volumetric productivity of the whole process, respectively) under the following conditions: carrier-particle concentration, 20% (v/v) of the working volume; glucose molasses, 50 g/l; ammonium sulphate, alternation of cycles with 0.0 and 0.5 g/1. 10.4.3 Lactic acid Lactic acid (C3H603: 2-hydroxypropionic acid) has an important position in the family of the carboxylic acids because of is applications in food and non-food industries. It is produced by fermentation (50%)and by chemical synthesis (50%). Lactic acid is present in plants and micro-organisms. Lactic acid has two enantiomers, L-(+) and D-(-)-lactic acid. The L-(+) isomer is used by human metabolism and is preferred for food use because D-(-) isomer is slightly toxic. Nevertheless, synthetic racemic (DL) lactic acid is the primary commercial form. Lactic acid is widely used in the food industry as tasteenhancing additive. Ferrous salts and the various L(+)-lactic acid salts are used in the pharmaceutical industry for their therapeutic qualities.
10. 4.3.1 Uses Lactic acid is used in foods, pharmaceutical, cosmetic and textile industries (Datta et al., 1995). The free acid is used as an acidulant and preservative in several food products such as cheese, meat, beer and jellies. Ammonium lactate is used as a source of non-protein nitrogen in feeds; sodium and calcium
stearoyl lactylates are used as emulsifiers and dough conditioners. Only the L(+) form of the lactic acid is metabolised in animal and human cells, because these cells can synthesize only L(+)-lactate dehydrogenase enzyme for the metabolism. Therefore, consumption of large quantity of D(-)-lactic acid results in its accumulation in the blood as unmetabolised. As a result of D(-)lactic acid accumulation, hyper-acidity of urine and decalcification may occur. In pharmaceutical industry, lactic acid is used for the adjustment of pH of pharmaceutical preparations and topical wart preparations, it dissolves wart tissues. Other applications are as a blood coagulant and dietary calcium source. Ethyl lactate is used in the preparation of anti-inflammatory drugs. Lactic acid is a good solvent, provides acidity in foods and beverages. Ethyl and butyl lactates are used as flavour ingredients. Lactic acid has some important applications in food industry such as for the production of fermented foods, in the pickling-process of gherkins, dill, olives, sauerkrauts, carrot and some leafy vegetables, and in the processing of oriental-foods. Lactic acid finds its application for the production of dairy products such as yoghurt, buttermilk, acidophilus milk, cottage cheese, creamy-cheese and fermented cheese etc. Recently, there has been increased interest in the lactic acid because of its application in the synthesis of biodegradable, biocompatible plastics and coatings. L(+)-lactic acid can be polymerised to form polylactic acid (PLA). This polymer can be used in the manufacture of new biodegradable plastics. The plastics prepared in such way are increasingly used in surgery for self-dissolving suture thread. Biodegradable plastics could play an increasing role in the industry by replacing or minimizing the use of non-degradable ordinary plastics to solve environmental pollution problems. These biodegradable plastics synthesized from lactic acid could be considered as a substitute for plastics manufactured from the petroleum products. Lactic acid has been used in manufacture of cellophane, resins, some herbicides and pesticides. Another important application of lactic acid is in textile and tanning industries.
10.4.3.2 Production The production of lactic acid by bacterial fermentation results into a racemic mixture of L(+) and D(-) isomers, although some strain can produce optically pure D(-)-lactic acid under specific conditions (Benthin and Villadsen, 1995). The fungal fermentation leads to the exclusive production of the L(+)isomer (Martak et al., 2003). The large-scale production of lactic acid is mainly obstructed by the cost of raw material. Application of agro-industrial waste residues in bioprocesses provides an alternative way to replace the costly raw materials (John et al., 2007). Notably improved productivity has been reached
with the employment of immobilized cells (Ogbonna et al., 1996, Ganguly et al., 2006). Recently, Singh et al., (2006) have discussed the metabolic engineering approaches for lactic acid fermentation. The initial efforts in LAB genetic modifications were concentrated mostly to develop LAB with enhanced qualities for food grade applications, using traditional approaches. The spontaneous mutations were also attempted by using insertion sequence (IS) elements. The LAB subjected to genetic improvement had been used in dairy industry for flavour enhancement, resistance to bacteriophages, addition of nutritional components and stability and structure of end products. Also various attempts have been made to develop efficient vector systems for metabolic engineering of lactic acid bacteria and expression systems for industrial Gram positive bacteria with low G+C content, controlled gene expression systems with the food grade inducer nicin etc. have been reported. However, with the recognition of polylactide as a biodegradable polymer, attempts were directed to reduce the cost of lactic acid production by genetically modifying the organism and also by using various cheaply available agro-industrial residues and process modifications to remove the lactic acid produced during the course of fermentation. Lactic acid production in SSF has been carried out using fungal as well as bacterial cultures. Strains of Rhizopus sp. have been common among the fungal cultures and that of Lactobacillus sp. among the bacterial cultures. Different crops such as cassa:~a and sweet sorghum and various crop-residues such as sugarcane bagasse, sugar cane press-mud, and carrot-processing waste can be used as substrates in fermentation for lactic acid production. A strain of R oryzae was used to evaluate the lactic acid production in different fermentation systems, using sugarcane bagasse impregnated with a nutrient solution. Both, the production level and productivity of lactic acid were higher in SSF with a yield of 137.0 g/1 and the productivity of 1.43 g/1 per h. One bacterial strain, L paracasei produced lactic acid in SSE Lactate concentration and yield were 90 g/kg and 91-95 %, respectively. The time required to complete SSF for lactic acid production is usually 120-200 h. Sugar cane press-mud has been used as substrate in SSF employing three bacterial cultures. L casei produced a higher concentration of lactic acid in comparison to L helveticus and Streptococcus thermophilus (Soccol et al., 1994a,b). A comparison in liquid and solid-state fermentation showed 93.8 and 137.0 g/1 of L(+)-lactic acid, and the productivity was 1.38 and 1.43 g/1/h in liquid- and solid-fermentations, respectively. John et al., (2006) exploited two agro-industrial wastes, cassava bagasse and sugarcane bagasse as raw material and inert support for L-lactic acid by solidstate fermentation. Gelatinised cassava bagasse was enzymatically hydroysed
and starch hydrolysate containing reducing sugars was used to impregnate the sugarcane bagasse. A maximum production of 249 mg/gds L-lactic acid was attained after 5 days with a conversion efficiency of 99%.
10.4.3.4 Extraction and recovery The traditional process on extraction and recovery of lactic acid after fermentation involves precipitation of calcium lactate and regeneration of lactic acid by addition of sulphuric acid followed by further purification steps, which are ion exchange and decolourisation. The extract is treated with hydrated lime for four purposes; this lime-treatment kills lactic acid bacteria, coagulates proteins, degrades residual sugars and solubilizes calcium lactate precipitated due to the reaction of lactic acid with calcium hydroxide and calcium carbonate present in fermenter. The solution is then filtered and the filtrate containing soluble calcium lactate is treated with sulphuric acid to precipitate calcium sulphate liberating lactic acid into the solution. The lactic acid solution is filtered to remove calcium sulphate precipitates and then bleached. The bleaching is perfon~aed by treatment with activated carbon. The bleached lactic acid solution is then concentrated to 3540% acidity in evaporator. The process of bleaching and evaporation is repeated 2-3 times to obtain lactic acid of different grades, such as technical-grade and food-grade lactic acid. Alternative processes are the extraction by liquid membranes, electrodialysis and ion exchange.
10.4.3.5 Factors affecting lactic acid SSF As mentioned above, in solid-state fermentation, aeration of the moistened medium is important. It controls the humidity of the solid support and simultaneously the heat-release of the fermentation metabolism. Aeration also provides the oxygen required for the fungal colonisation in solid medium. Therefore, the optimisation of aeration rate is very important in SSF and every SSF-process is different due to the use of different substrate and a different micro-organism. In one example of lactic acid production as described above, aeration rates of 0 to 100 ml/min per column reactor were tried; the maximal L(+)- lactic acid yield was obtained with the aeration rate of 20 ml/min. A decrease of 35% was caused in lactic acid yield at the aeration rate of 100ml/min. A higher aeration may cause a significant reduction in the lactic acid yield, which is directly related to an increase in the aerobic respiration rate of the fungus. Similarly, at very low or with a poor aeration, a significant amount of glucose may not be consumed in the fermentation that may result in decreased biosynthesis of lactic acid (Soccol et al., 1994a). Another important factor influencing the SSF is the inoculation rate of fungal spores. Various sizes of spore-inoculum using 105 to 108 spores in a suspension
form have been used to produce inoculum of A oryzae. The optimal seedinoculum has been found to be 10 6 spores per g glucose used. This inoculum size produced 120 g/1 lactic acid with complete glucose uptake and 75% yield of lactic acid. Inoculation rate and the lactic acid production are parallel. A similar variation in lactic acid yield has been observed as any variation occurred in inoculation rate (Ueno 2003). Lactic acid synthesis has been found to be affected by the glucose concentration in the fermentation medium. SSF using 12 to 24% glucose was performed to optimize sugar concentration for an enhanced yield of lactic acid. The optimum glucose concentration as the initial intake in the medium was 18%, producing 137g/1 lactic acid with a 76% yield. A higher concentration of glucose as 24% led to a decrease in lactic acid biosynthesis. Because of a partial consumption of glucose in the fermentation medium, a glucose concentration of about 16% produced 117 g/1 of lactic acid with a fermentation yield of 74%. If the glucose concentration used was lower as 12%, lactic acid production was reduced to 75 g/l, with a lower fermentation yield of 63% (Soccol et al., 1994b). The type of fermenter used is another factor affecting the product yield. A comparative study of SSF in column bioreactor and culture in Erlenmeyer flasks showed 77 and 74% fermentation yields, respectively. High quantities of fumaric acid production (20 g/l) were also noted, which in liquid fermentation was in small quantity (2.1 g/l). The culture conditions in SSF caused the synthesis of fumaric acid (Petruccioli et at., 1996).
10.4.4. Gluconic acid Gluconic acid is used in the food, beverages and pharmaceutical industries. It imparts a refreshing sour taste in many foods items such as wine, fruit juices etc. Sodium gluconate has a high sequestering power. It is a good chelator at alkaline pH; its action is comparatively better than EDTA, NTA and other chelators. Aqueous solutions of sodium gluconate are resistant to oxidation and reduction at high temperatures. It is an efficient plasticizer and a highly efficient set retarder. It is easily biodegradable (98 % at 48 h). It has an interesting property of inhibiting bitterness in foodstuffs. Concentrated gluconic acid solution contains certain lactone structures (neutral cyclic ester) showing antiseptic property. In the European Parliament and Council Directix~e No. 95/2/EC, gluconic acid is listed as a generally permitted food additive (E 574). The US FDA (Food and Drug Administration) has assigned sodium gluconate a GRAS (generally recognized as safe) status and its use in foodstuff is permitted without limitation (Ramachandran et al., 2006).
10. 4.4.1 U s e s Gluconic acid is a mild organic acid, which finds applications in the food industry. As stated above, it is a natural constituent in fruit juices and honey and is used in the pickling of foods. Its inner ester, Glucono-8-1acto
