Advances in Agronomy, Volume 40

ADVANCES IN

AGRONOMY

VOLUME 40

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ADVANCES IN

AGRONOMY Prepared in Cooperation with the AMERICAN SOCIETY OF AGRONOMY

VOLUME 40 Edited by N. C . BRADY Science and Technology Agencyfor International Development Department of State Washington,D.C.

ADVISORY BOARD H. J. GORZ,CHAIRMAN M. A. TABATABAIT. M. STARLING

E. J. KAMPRATH R. J. KOHEL G. E. HAM G. H. HEICHEL E. L. KLEPPER R. A. BRICCS,Ex OFFICIO ASA Headquarters

1986

ACADEMIC PRESS, INC. Harcourt Brace Jovanovich, Publishers

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CONTENTS PREFACE............................................

vii

AGRONOMY OF WHITE CLOVER

J . Frame and P. Newbould I. Introduction ..........................................

I1. Morphology and Function...............................

Environment ......................................... Culture .............................................. Nitrogen Fixation., .................................... Quality .............................................. Grass/White Clover Dynamics ........................... Production and Management ............................ Potential Production ................................... X . Management Guidelines ................................ XI . Conclusions .......................................... References............................................

111. IV. V. VI. VII. VIII . IX.

1 4 10 20 38 41 45 49 67 69 70 75

AGRONOMIC VALUE OF UNACIDUIATED AND PARTIALLY ACIDULATED PHOSPHATE ROCKS INDIGENOUSTO THE TROPICS

L. L. Hammond. S. H . Chien. and A . U . Mokwunye I . Introduction .......................................... I1. Indigenous Phosphate Deposits in the Tropics............... I11. Agronomic Potential of Phosphate Rock for Direct Application .................................. IV . Physical Factors Influencing Expression of Agronomic Potential ................................. V. Soil Factors Influencing Expression of Agronomic Potential . . . VI . Climatic Factors Influencing Expression of Agronomic Potential ................................. VII. Partial Acidulation of Phosphate Rock ..................... VIII. Regional Findings on Direct Application of PR and PAPR .... IX . Summary and Conclusions .............................. References............................................ V

89 90 93 101

104 110 112 116 134 137

vi

CONTENTS CROP SIMULATION MODELS IN AGRONOMIC SYSTEMS

F. D. Whisler, B. Acock, D. N. Baker, R.E. Fye, H. F. Hodges, J. R. Lambert, H. E, Lemmon, J. M. McKinion, and V. R. Reddy I. Need for Crop Simulation Models and Types of Models. ......

11. Model Building. .......................................

111. Model Testing ........................................ IV. Model Applications .................................... V. Summary.. .......................................... References. ...........................................

141 146 175 180 204 204

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY IN SOIL

W. D. Gould, C. Hagedorn, and R. G. L. McCready I. 11. 111. IV. V.

Introduction. ......................................... Problems Associated with Urea Fertilizers. ................. Urea Transformations .................................. Methods to Alter the Efficiency of Urea. ................... Summary ............................................ References. ...........................................

209 21 1 216 220 23 1 232

LUPIN CROP AS AN ALTERNATIVE SOURCE OF PROTEIN

L. Lopez-Bellido and M.Fuentes I. Introduction.. ........................................ 11. Botany and Ecology of Lupin ............................ 111. Plant Breeding ........................................ IV. Plant Production ...................................... V. Chemical Composition and Use of Lupin Seed .............. VI. Perspectives .......................................... References............................................

INDEX.....................................................

239 242 260 268 284 288 290

297

PREFACE The contributions to this volume 0fAdvance.sin Agronomy cover a range of topics of current interest to crop and soil scientists.Two are crop specificand deal with important legumes. The first focuses on white clover (Frame and Newbould: Agronomy of White Clover), the important pasture legume in temperate regions. What is known about this crop, as well as its limitations, is given coverage. Another chapter is a review of the current and potential role of lupins as sources of plant protein for human and animal consumption (Lopez-Bellido and Fuentes: Lupin Crop as an Alternative Source of Protein). Two other contributions address issues involving soils. Hammond et al. (Agronomic Value of Unacidulated and Partially Acidulated Phosphate Rocks Indigenousto the Tropics) focus on the role of phosphorus in tropical agriculture and on practical means of using indigenous phosphate deposits to increase agriculturalproduction. Gould et al. (Urea Transformationsand Fertilizer Efficiency in Soil) review the transformations of urea and their implications for nitrogen supply and utilization. The worldwide significance of these transformations is shown by the serious losses of nitrogen resulting from the transformation of urea nitrogen to other forms. The article by Whisler et al. (Crop Simulation Models in Agronomic Systems) deals with the building and testing of crop simulation models for cotton, soybeans, and wheat. This pioneering work may well represent the beginning of a new area of computerized models to govern on-farm management decisions in not only the industrialized nations but also the Third World. I thank the contributorswho prepared the five chaptersthat constitute this volume. Researchers worldwide will appreciate their efforts. N. C. BRADY

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ADVANCES IN AGRONOMY. VOL. 40

AGRONOMY OF WHITE CLOVER J. Frame' and P. Newbould2 'The West of Scotland Agricultural College, Auchincruive, Ayr KA6 5HW, Scotland *The Hill Farming Research Organisation, Bush Estate, Penicuik, Midlothian Eli26 OPY, Scotland

I. INTRODUCTION White clover (Triflium repens L.) is the most important pasture legume in temperate zones of the world. It is of value because of its wide climatic range, the high nutritional quality and digestibility of its herbage, and the significant contribution it makes to the economy of grass/white clover pastures by fixation of atmospheric nitrogen, especially in the absence of fertilizer nitrogen. While white clover is grown across a broad spectrum of climates, it is most frequently used in temperate mild to temperate cold climates; lacking a high density of roots (Evans, 1978) it is not productive during hot summer months (Russell and Webb, 1976), nor can it withstand extreme cold (Burdon, 1983). White clover is normally described as a creeping, much-branched perennial (Turkington and Burdon, 1983), but Hollowell ( 1966) has postulated that in some environmental and management situations it behaves like an annual, or even as a mixture of plants of both types. In studies of the whole Trifolium genus, both annual and perennial species are found with either simple tap-rooted stoloniferous or rhizomatous root habits which may be related to chromosome number (Taylor et al., 1979). Thus, the variation in longevity noted by Hollowell may have genetic as well as environmental connotations. The literature on all aspectsof the growth and performance ofwhite clover is enormous and the rate of publication continues to increase annually. This review is based largely on work in northwestern Europe and New Zealand, but literature on work from other countries is also cited where relevant. For example, the role of all clovers in the United States, but especially white clover, was reviewed recently by Carlson et a/.(1985) and by Gibson and Cope ( 1985). Thus, on the use of white clover in the United States and other recently reviewed subjects such as nitrogen fixation (La Rue and Patterson, 198 1) and competition in grass/legume pastures (Haynes, 1980), only brief mention is made in the present article for the sake of coherence. The aim is to describe the origins and morphology of the plant and its nutrient and enviI Copyri&t 8 1986 by Academic Resq Inc.

AU rights of reproduction in any form TcscTvcd.

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J. FRAME AND P. NEWBOULD

ronmental requirements, but major emphasis is given to the agronomic and management aspects of the plant and of swards containing it. A. ORIGINS

The TrijXum tribe of the Papilionoideae subfamily of the Leguminosae or Fabaceae consistsof about 250 speciesdistributed throughout the temperate and subtropical regions of the north and south hemispheres,particularly in Europe, northwest and central Asia, northeast Africa, parts of tropical Africa and South Africa, and western North and South America (Polhill et al., 1981; Heyn, 1981). About 25 species are of significance as food for grazing animals, of which 10 are agriculturally important (Evans, 1976). Wild white clover is the most important pasture legume in many parts of the temperate zones (Turkington and Burdon, 1983) and is also found in many regions outside the temperate zone where the climatic conditions are mild without extremes in temperature and precipitation (Ostrowski, 1972). There is controversy over the precise center of origin of white clover; Evans (1976) and Turkington and Burdon (1983) favor Eurasia, Zohary ( 1972) favored North America, and Polhil et al. (198 1) favored both Eurasia and North America. Taylor et al. (1979), expanding the centers of diversity, and therefore possibly the origins too, included Africa. Such confusion arises because wild clovers are distributed in patterns determined primarily by climatic and natural biotic pressures, while cultivated forms have been selected by man and his grazing animals. The dates of onset ofdeliberatepasture management and the introduction of sown legumes into European agricultureare unclear. Evans (1976) stated that red clover (Trifoliumprutense L.) was cultivated in southern Europe in the third and fourth centuries AD and was introduced into Spain in the sixteenth century, and through Holland and Germany to England in 1650. It is probable that regular use of white clover began in England at about the same time, since it was introduced or recognized in pastures in the early sixteenth century (Fussell, 1964). The settlement by Europeans of North America, Australia, and New Zealand resulted in a great increase in the distribution of forage legumes, and white clover in particular. However, until the stimulus provided recently, mainly from Australia, exploitation of the natural legumes in Mediterranean zones and in tropical areas of the American continent has commenced only in recent times (Tothill, 1978). B. PRESENT USE IN WORLD AGRICULTURE White clover grows on roadside verges and in natural pastures throughout the world where climatic and soil conditions are suitable (see Section II1,A

AGRONOMY OF WHITE CLOVER

3

and B), but it is seeded deliberately in pastures mainly in North America, New Zealand, and northern Europe. White clover is used principally as a component of mixed grass/clover swards, which are usually grazed in situ. It is not grown in monoculture because of the difficulties of keeping such swards weed free, low annual herbage production, its short growing season, and concern about bloat and possible reproductive problems in grazing livestock. It was rarely used as a conservation crop (hay or silage)because of the brittleness of its leaves when dried as hay, lack of bulk production, and problems with making well-fermented silage from it. The difficulties of making silage from clover alone or grass/clover mixtures have now been overcome by wilting, chopping, and the use of acid additives (Frame, 1976a; Castle ef al., 1983). It is estimated that half of 45 Mha of humid or irrigated pastureland in the United States contains white clover but there is uncertainty concerning the amount of seed used each year. Van Keuren and Hoveland ( 1985)noted that its area of adaptation includes most of the United States, although its companion grass vaned with differing soil and climatic conditions. Most of the home-grown Ladino clover in the United States is produced in California; annual production in recent years has been 1360- 1590 metric tons* (Rincker and Rampton, 1985). New Zealand provides the bulk of the United Kingdom [and European Economic Community (EEC)] white clover seed supply and that country exported about 4000 tons of the variety Grasslands Huia in 1980 (Lancashire, 1985). In the period 1975- 1984, between 50 and 60% of certified permanent pasture white clover produced was also exported. Since the variety GrasslandsPitau was released in 1978 about one-third of its total seed production has been exported (305tons). Figures for actual seed sales are hard to obtain but it appears that New Zealand exports about 4400 tons of white clover seed per year. Differences between production and exports suggest that the New Zealand farmers sow 1000- 1300 tons of white clover seed annually. In the same article, Lancashire (1985)indicated that if all the potential areas in New Zealand for sowing with Grasslands Pitau and the recently developed Grasslands Tahora white clovers were seeded, about 13,500 tons of seed would be required. In the EEC countries, about 3000 tons of white clover seed is used each year, of which the United Kingdom sows about one-third (Fitsen, 1985). The sources of the white clover seed supply in the United Kingdom, shown in Table I, help to illustrate the main seed-producing(and presumably seedusing) areas of the world (Anonymous, 1983a).White clover is also used as an amenity legume on roadside verges and other predominantly marginal land, and for permanent pastures which are grazed in sifu.The importance All tons mentioned in text are metric tons.

4

J. FRAME AND P. NEWBOULD Table I Sources of White Clover Seed Supply in 1980 in the United Kingdoma

Country New Zealand Denmark United Kingdom United States Australia Netherlands Other countries (Belgium, Italy, West Germany)

Metric tons 709 378 61 47 20 15 4

96 57.5 30.6 4.9 3.8 I .6 I .2 0.3

From Anonymous (1983a).

ofall legumes to man was well described recently by Iseley (1982)but, just as with the grain legumes, the full potential of forage legumes remains to be realized (Gladstones, 1975; Rogers, 1976). Although use of white clover is substantial in some parts of the world, this review discusses the many soil, botanical, and cultural problems which hinder its wider exploitation.

II. MORPHOLOGY AND FUNCTION A. ROOTS

White clover plants develop an extensivelybranched tap root system from the primary seedling. Thereafter, adventitious roots with numerous lateral branches arise from the nodes of the stolons which develop from the mother plant (Erith, 1924; Hector, 1936). Early in the root’s life, rhizobial infection takes place and large numbers of nodules develop, mainly on the finer branches of the root system. These nodules may be club shaped, ellipsoidal, or sometimes palmate. The clover tap root system is short lived (Stuckey, 1962; Gibson and Trautner, 1965;Carlson et al., 1985),so the plant is eventually dependent on the roots which develop from stolon nodes (Hollowell, 1966). Tall-growing clover types such as Ladino or Grasslands Pitau with large leaves develop a well-defined tap root system compared with prostrate, small-leaved varieties such as Kent Wild White (Caradus, 1977). This may render the small-leaved types less vulnerable to loss of their tap root system; since they are also highly

AGRONOMY OF WHITE CLOVER

5

stoloniferous, their persistence will be enhanced relative to the larger-leaved types. Work by Haycock (1982) has indicated that both types of root systems have similar potentials for supporting leaf growth. Estimates of tap root longevity vary from less than 1 year to 2 years (Westbrooksand Tesar, 1955; Spedding and Diekmahns, 1972). Thus, Hollowell (1966) has described the white clover plant in terms of an annual which may behave as a perennial through asexual propagation. White clover explores the upper layers of soil but has the disadvantage compared with grasses of shorter root hairs and a smaller “root hair cylinder” (Evans, 1977). Evans (1978) found that white clover roots reached the same depth as those of perennial ryegrass and cocksfoot, with most roots of all species occurringin the upper (0-200 mm) soil layers. However, white clover had much less root mass in these upper layers, from which the bulk of soil nutrients and moisture is extracted (Bland, 1968; Evans, 1978). In New Zealand, Caradus and Evans (1977) found new root production peaked in autumn and fell gradually throughout winter to a minimum in spring and summer. Possibly because of lower winter temperatures in England, the production of new roots was highest in spring, but there was also a smaller peak in autumn (Garwood, 1968). Severe shading can lead to a marked loss of both roots and nodules, with little subsequent new growth (Butler et al., 1959;Chu and Robertson, 1974). With recurring defoliation, a balance between death and regeneration of roots occurs, leading to a rapid turnover of root and nodule tissue (Evans, 1973); defoliating white clover every second day drastically reduced root elongation.

B. LEAVES The first photosynthetic organs are formed after germination from the two cotyledons in the seed. The first true foliage leaf is unifoliate and round, but later emerging leaves consist of three leaflets, ovate to circular in shape, and with the edges either entire or serrate. There is a pair of leaflike stipules at the base of each petiole (Hector, 1936). In most genotypes there are inherited characteristic marks, whitish or red, on the upper surfaces of the laminae. The leaves are arranged alternately on the main stem, and then arise from stolons, one per node. Successive petioles are progressively longer until they reach normal length (Brougham, 1958a,b; Wilman and Asiegbu, 1982b). Leaflet size and shape are functions of the clover variety, and the position of the leaflet on the stolon. Leaflet size is currently used for classifying varietal type (Anonymous, 1985b). Further detailed accounts of the morphology of leaves (and other parts) may be found in Erith ( 1924), Hector ( 1936),Gibson and Hollowell ( 1966),Spedding and Diekmahns ( 1972), Burdon ( 1983),and Carlson et al. (1985).

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J. FRAME AND P. NEWBOULD

The process of leaf initiation, development, growth, and senescence is affected by the prevailing temperatures and light. The processes which influence numbers and development of the leaves and stolons are markedly temperature dependent, whereas the processes governing differentiation and size are mainly light dependent (Brougham, 1962). The longevity of clover leaves, which determine their photosynthetic usefulness to the plant, was reported by Brougham (1958a,b) to be between 28 to 38 days from time of emergence. In late autumn and winter the leaves in the older parts of the stolons generally die away, leaving mainly undeveloped leaves near the stolon apices (Davies and Evans, 1982), but there can be a steady but slow production and loss of leaf throughout winter. This is followed by a net increase in dry weight when spring temperatures and radiation improve. One of the factors which contributes to clover’s reputation for unpredictability is its greater variation than grass in number of leaves per unit area of ground, from site to site, from year to year, and from one time of year to another (Hollington and Wilman, 1985). The ability of white clover to achieve a high level of leaf expansion at low temperatures and light intensities is an important breeding objective (Cooper, 1969; Breese, 1979; Rhodes, 1984, 1985). This ability is particularly desirable in colder environments such as the uplands of the United Kingdom (Munro and Hughes, 1966). Genotypes adapted to low temperatures have been identified (Eagles and Othman, 1981;Ollerenshaw and Baker, 1981; Ollerenshaw, 1983)and considerable differences in the response of different genotypes to changes in temperature have been observed (Beinhart, 1964; Williams and Hoglund, 1978). White clover leaves growing in a grass/clover sward are not significantly shaded, since successivepetioles extend longer and keep pace with increasing height of sward canopy (Mitchell, 1956b;Dennis and Woledge, 1982, 1983). The photosynthetic capacity of the clover laminae is apparently not reduced even in the mixed swards of high leaf area commonly used in the United Kingdom. Dennis et al. (1984) concluded that clover production was more affected by the number of growing points at the beginning of a growth period than by any differences in sward structure or light environment during regrowth. The removal of leaves and/or petioles and stolons in cutting or grazing of white clover plants occurs during utilization. Knowledge of the physiological responses of the plant to defoliation is needed to understand agronomic responses (see Section VII1,D and E). The phenotypic plasticity of the plant is well known (Hill, 1977); King ( 1963)showed that heavy grazing of indigenous white clover populations resulted in small-leaved prostate forms of white clover. In subsequent work King et al. (1978) found that acropetal movement of assimilates occurs in white clover such that partial defoliation

AGRONOMY OF WHITE CLOVER

7

has only a small effect on the growth of terminal leaves, which are the main source of clover production (Beinhart, 1963). This suggests that growth and spread of white clover plants will be more rapid if defoliation of the central leaves can be avoided. More importantly, the rate offormation, number, and size of internodes were not significantly depressed by partial defoliation. Recently, Boatman and Haggar (1984) concluded that “white clover seedlings have a considerable ability to recover from leaf removal, especially if only laminae of old leaves are removed, but the growth reduction following removal of petioles as well as laminae appears to be especially severe.” Further detailed work on this subject and on the light responses of white clover leaves formed at different positions in the canopy of a mixed grass/ white clover sward is required, but the complexity of the interacting factors involved is clearly evident. Studies are especially needed of the developmental morphology of modern white clover varieties (Arnott and Ryle, 1982). C. STOLONS The seedling develops a short primary stem with a number of nodes. Stolons emerge from the axils of the leaves and if growth is unhindered, the clover plant forms a rosette with a network of freely branched stolons. Barley (1953) showed photographically that stolons are present on and just below the soil surface. As the center of the plant dies, individual stolons take on an independent existence (Erith, 1924;Spedding and Diekmahns, 1972;Chapman, 1983). Growth and survival of white clover are therefore strongly dependent on stolon development and replacement (Knight, 1953a,b; Beinhart, 1963;Schillingerand Leffel, 1964;Gibson and Hollowell, 1966; Hollowell, 1966). The buds which develop in the axils of the stolon-borne leaves bear secondary stolons or inflorescences, depending on the season of the year. Stolon production is influenced by temperature, light, and flower initiation (Brougham, 1962, 1965; Beinhart, 1963). Since each inflorescence produced eliminates the potential of a stolon bud to proliferate (Knight, 1953b), profuse flowering can be detrimental to plant persistence; conversely, if seed is set and shed, the longevity of the clover stand will be assisted. Severe grazing by sheep of stolons and therefore removal of terminal apices gives stolons less chance to assimilate material and exploration of temtory may be curtailed (Clark et af.,1984a). Wild white clover types, which are strongly stoloniferous, will have better potential persistence than less stoloniferous large-leaved types (Davies, 1970; Munro el a!., 1975;Baines et af.,1983). This gives the wild white types an advantage under severe grazing, exemplified by continuous sheep stocking (Evans and Williams, 1984) and a better ability to colonize bare spaces

8

J. FRAME AND P. NEWBOULD

(Burdon, 1983; Turkington and Burdon, 1983). It has been suggested that a grass/clover mixture provides a more stable association than a grass monoculture due to the ability of clover to proliferate by stolons and colonize bare ground (Hams and Thomas, 1973). Increased length, diameter, and weight of stolons were factors contributing to the positive effect on white clover performance of increased interval between defoliations ( Wilman and Asiegbu, 1982a,b;Frame, 1985~).Fertilizer N application adversely affected stolon weight (Boyd and Frame, 1983; Frame, 198%). The length and diameter of stolons were reduced less in large-leaved than small-leaved varieties (Wilman and Asiegbu, I982b). Vigor of clover growth in spring was related to the amount of stolon which overwintered (Hams et al., 1983). Two genotypic extremes with differing stolon-branchingability were referred to by Beinhart et al. (1963) and Gibson et al. ( 1 963). The stolons of “non-viney” genotypes were freely branching and spread outward radially while “viney” genotypes were less stoloniferous and sparsely branched. In Switzerland, Boller and Nosberger (1 983) noted that an alpine clover ecotype allocated a higher proportion of dry matter to the stolonsthan did a valley ecotype. In perceiving a model ofwhite clover for New Zealand hill country, dense stolon branching, small leaves, and a prostrate habit were identified as desirable characteristics (Caradus and Williams, I98 1). Smith (1 949) found a stronger association of winter injury with the large Ladino clover stolons compared with the smaller stolons of common white clover types. Recent studies in New Zealand have increased awareness of the distribution pattern of stolons in grazed pastures. Hay (1983) and Hay et al. (1 983) reported the effect of season or time of year on three “vertical classes” of stolon: aerial, surface,and buried. Buried stolon formed a large percentage of stolon total weight, and increased from a minimum in autumn to a maximum in spring. Earthworm casting rather than stock trampling was the more important factor involved. Aerial and surface stolon both peaked in summer and were least in early spring. Environmental conditions such as drought reduced the amount of stolon and modified its distribution in favor of buried stolon (Hay and Chapman, 1984). Total stolon weight and weight per unit length were greater under cattle grazing than sheepgrazing (Hay et al., 1983; Hay and Chapman, 1984). Further longer term work (Hay, 1985) confirmed that white clover underwent an annual cycle of burial of stolons in winter, reemergence of growing points in spring and surface stolon development over summer (Fig. 1). Hay (1983) identified three ways buried stolon assisted white clover persistence: initiation of subsurfacebranch stolon capable ofgrowing vertically to the soil surface and redirection of stolon apices to the surface; initiation of branch stolons where a vertical branch reached the soil surface; production of budlike structures, with several growing points, from vertically grown stolons.

AGRONOMY OF WHITE CLOVER

9

100 1

1981

1982

1983

FIG.1. Mean percentageby weight of stolon in aerial (U),surface(e),and buried (0)classes at each sampling, autumn 1981 (March)to summer 1983 (January) in New Zealand. (From Hay, 1985.)

Clearly, detailed investigations into stolon distribution strata are warranted in grazing studies on grass/white clover swards in future. In the past, clover regeneration following declines in contribution, and sometimes apparent disappearance, has been largely attributed to germination of buried seeds or from plants which had become dwarfed for self-preservation.

D. INFLORESCENCES Globular inflorescencesare borne on long peduncles arising from the axils of the leaves, and are produced from the nodes of the stolons, although not at the basal nodes (Erith, 1924;Turkington and Burdon, 1983).The peduncles are usually about twice as long as the petioles of the leaves in whose axils they develop. The flowers, 20-40 per flowerhead, are white or pink and are typically arranged in a raceme. The flowering phase and inflorescencesare less important as determinants of herbage production in clover than in grasses, but persistence is adversely affected by profuse flowering (Knight, 1953b; Gibson, 1957). Flowering, which extends over several weeks, is influenced by many factors including genotype, temperature, photoperiod, and management. It is enhanced by long days (14- 16 hr) and - 20°C optimum temperatures following short days and low temperatures (Norris, 1984a;Carlson et al., 1985).However, there is considerablevariation among varieties in their temperature requirements for floral development (Norris, 1984b, 1985). Flowering can be delayed by cutting or grazing (Zaleski, 1961). In the United Kingdom, inflorescences are formed from May to July

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J. FRAME AND P. NEWBOULD

(Speddingand Diekmahns, 1972). Cross-fertilizationby insect pollination is enforced by self-incompatibility. The seed ripens 3 -4 weeks after pollination. The seeds are heart shaped and mainly yellow to brown in color. A proportion of the seed has impermeable coats, referred to as “hard” seed, and these can remain viable in the soil for a number of years. Burdon ( 1983) gave the seed size of indigenous clover in the United States as 1.O X 1.1 X 0.6 mm with a mean 1000-seed weight of 0.5 -0.8 g. Duke (198 1) cited 1,764,000 seeds/kg for white clover, while Wheeler (1950) had cited 1,543,000. Our own investigations led to values of 1,374,000- 1,642,000 seeds/kg for a range of varieties of differing leaf size types. However, data on seed size and many other morphological characteristics of the host of white clover varieties used in agricultural practice are scarce. This is not surprising since, for example, 43 varieties are listed in the EEC Common Catalogue (Anonymous, 1985~).

Ill. ENVIRONMENT As indicated in Section I,B, white clover is adapted to widely vaned environmental conditions. Its responses to these and to cultural influences are largely determined by physiological characteristics and processes, a theme recently reviewed for clovers, including white, by Kendall and Stringer (1985). The objective of this section is to describe and discuss briefly the relationships between selected environmental factors and the agronomic responses of white clover.

A. CLIMATE

In company with most plants, the growth and flowering ofwhite clover are affected by radiation, day length, temperature, soil water, and, in exposed places, wind. For growth within Britain, Burdon ( 1983)concluded that white clover was unrestricted by general climatic trends although areas subject to severe frosts or to prolonged droughts were not conducive to its growth and survival. Its distribution is widespread over all aspects and slopes though generally restricted to unshaded sites, but restricted at one extreme by intolerance of drought and at the other by the combined effects of low temperature on growth, N fixation, and the availability of plant nutrients. The broad requirements for white clover to grow well, as far as they are known, are described below under separate headings. While little can be done to alter most of the climatic factors, i.e., they are permanent limitations, understanding ofthe effects is necessary for plant breeders and agronomists so that the plant’s potential can be fully exploited.

AGRONOMY OF WHITE CLOVER

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1. Light

The early work of Blackman ( 1938),Black ( 1957),and Brougham ( 1958a) indicated that white clover was essentially a sun-loving plant to which shade was inimical. Most of the evidence suggests that the quantity of light energy, rather than its quality or intensity, is the most important factor (Black, 1957).Once the leaf area index (LAI) of white clover has reached 3 - 4 and all the light is intercepted, the amount of light energy may be a limitation to production. There is some evidence that legumes, and white clover in particular, require more light at the red end of the spectrum than, say, grasses (Wamngton and Mitchell, 1976). It is certainly our observation that white clover does not grow well in a growth chamber with warm white fluorescent lamps alone; a small number of tungsten filament bulbs must also be in position. The photosynthetic efficiency of white clover leaves is affected by the light environment in which they are formed, just as in grass (Woledge, 1978). However, if shaded, white clover has the ability to extend its petioles and thus place the developing leaves in a high light intensity (Dennis and Woledge, 1983). It has also been suggested that white clover leaves at the base of a mixed sward have the ability to find sun flecks, so improving its chances of survival in the presence of taller growing companion grasses (Boller and Nosberger, 1985). Both radiation and temperature influence the growth rate of white clover in spring (Davies and Evans, 1982); this is shown by the rapid growth in February and mid-March in Wales of the many new, small, branch stolons formed over winter. The critical day length for white clover is 13.5 hr (Spedding and Diekmahns, 1972). On the basis of flower initiation, Thomas ( 1961) described white clover as a short-long-day plant. Flowering, a prerequisite for seed production, is influenced by both temperature and day length to contrasting degrees for different varieties. With a 16-hr day length at 10°Conly 10%of a group of varieties flowered, whereas at 18 and 26°C most plants flowered (Norris, 1985). Thomas ( 198la) has shown in the field and with six varieties ofwhite clover, that defoliation has a stimulating effect on inflorescence initiation in plants that have stopped initiation in long days.

2. Temperature Temperature has effects on the availability of soil nutrients, germination, the growth of white clover roots and shoots, winter survival, photosynthesis and respiration, and nitrogen fixation. It is difficult to identify which process is most affected at any one time, but it is commonly believed that the minimum temperature for shoot growth ofwhite clover is 5.8"C,as for most grasses, but that active N fixation requires a temperature of 9°C (Martin,

12

J. FRAME AND P. NEWBOULD

1960). Thus, Munro (1 970) was able to conclude that the temperature requirement for white clover to grow and fix N ranged from 9 to 27' C with an optimum of 25 "C. In temperate zones, white clover is distributed widely on an altitudinal basis despite considerable variations in temperature with altitude. For example, in the United Kingdom it appears from sea level to over 900 m (Snaydon, 1962). In Norway and Switzerland it persists at 1200 and 1800 m, respectively (Erith, 1924); in Colorado, it grows at 3350 m (HultCn, 1970), and at 6000 m in the Himalayas (Turkington and Burdon, 1983). Cold-hardiness during establishment can be critical (Spedding and Diekmahns, 1972), since survival at - 10°C is minimal (Rachie and Schmid, 1953). It also appears that temperature may affect sward photosynthesis in the field since photosynthetic rates at 15"C were about twice those at 5 "C ( Woledge and Dennis, 1982). Respiration, i.e., senescence losses, are also sensitive to temperature but both white clover and perennial ryegrass, a common companion grass, appear to respond in the same way. The climate of the United Kingdom results in a short growing season since air temperatures do not reach the minimum level until late May and they decline again in late September (Williams, 1970). Woledge and Suarez (1983) concluded that white clover could be at a disadvantage compared with grass in spring because of its production of a large root :shoot ratio and small leaf area at low temperatures. The shoots of white clover grow best at about 24°C (Mitchell, 1956a). At this favorable growth temperature, 14C-labeled assimilates move at about 30 cm per hour, but at 10°Cthey move at about 20 cm per hour. When plants grown at 20°C were transferred to a lower temperature the rate oftranslocation was reduced and almost ceased at 5 "C; however, plants grown at 5 "C were adapted to lower temperatures in terms of translocation (Hoshino et al., 1966). There are, unfortunately, only limited studies on the response of white clover to temperature. The results demonstrated good growth in the range 18-30°C with an optimum of24"C (Brougham et al., 1978).The temperature range encountered during the British growing season, both lowland and upland, is therefore suboptimal for the most part, but particularly in early and late season. Generally, white clover is observed to start growth 2-3 weeks later and to cease earlier than many ryegrasses used in the United Kingdom (Williams, 1970). Kleter ( 1968) concluded that the percentage of white clover in permanent grassland in the Netherlands was strongly related to spring temperatures, particularly in April. There is general agreement that day temperatures influence growth more strongly than night temperatures and that growth is best when night temperatures are equal to or only slightly lower than day temperatures; also, the optimal temperature for growth falls as light intensity falls (Spedding and

AGRONOMY OF WHITE CLOVER

13

Diekmahns, 1972). Davies and Evans (1982) investigated earlinessofgrowth in two extreme types of clover and found differences due to lamina size and petiole length rather than differing ability to grow at low temperatures. Laissus (1983), working in Normandy, France, noted that decreases in soil temperature at 100 mm were related to a decline in white clover production. Consequently, he concluded that compact or cold soils (with a high waterholding capacity) were not suited to white clover. There is little work on selecting white clover material with ability to make significant growth at low temperatures (Ollerenshawet al., 1980; Eagles and Othman, 198 I ;Haycock and Ollerenshaw, 1982). Obviously such a characteristic would be valuable for hill and upland areaswhere spring growth is at a premium. Fertilizer N use in these areas is low, and vigorous clover growth and rhizobial N fixation are vital to sward production, particularly in grass/ clover reseeds sown to supplement the frequently clover-deficient native swards. Alcock et al. (1974) noted that on sheltered hill plots, rapid increases in LA1 and dry matter of Aberystwyth S 1 84 white clover could be due to soil heating effects. Information on the winter hardiness of white clover varieties is scarce but there are indications that Grasslands Huia, the most widely sown variety in the United Kingdom, has limitations in this respect (Hunt el al., 1965). Vigor of early clover growth in spring was related to the amount of stolon which overwintered satisfactorily (Harris et al., 1983); the low stature and other morphological features of Aberystwyth S 184 enable it to enter spring with more stolon and leaf than other varieties. Norris (1981) stated that white clover leaves were produced from nodes and lateral buds at the expense of food reserves in the stolons. The hazard of winter damage in upland areas due to low temperatures can be a major factor influencing why grassland potential is lower there than in the lowlands (Munro and Davies, 1973). Davies and Young (1967) noted the relationship between morphological adaptation and winter hardiness. Cold-tolerant plant populations from northern Europe were always smaller leaved, more prostrate, and more stoloniferous than Mediterranean populations, which were often erect types with small numbers of large plant parts. The Ladino type from southern Europe is particularly frost sensitive (Garaud, 1984).

3. Drought Strictly, this is a soil physical factor, but there is an obvious relationshipto climate. Foulds (1978) noted few indigenous white clover plants in areas subject to severe drought. The marked response of white clover to irrigation (Low and Armitage, 1959; Low and Piper, 1960; Stiles, 1966; Cowling,

14

J. FRAME A N D P. NEWBOULD

1982) has been interpreted as clover sensitivity to drought and in mixtures more so than grass. However, Kleter (1968), who surveyed Dutch permanent pasture, discovered no relationship between percentage clover in grass/ clover swards and summer rainfall. No consistent relationship was found between several growing-season weather parameters and total herbage or clover production since production was affected by a complex of interactive factors (Frame and Boyd, 1984). Recently Thomas ( 1984) showed that droughting28 - 56 days after sowing reduced the shoot growth of grass and clover monocultures equally but affected clover more than ryegrass in mixtures, possibly because the clover has less root mass in the upper soil layers (Evans, 1978). Thomas ( 1984) concluded that during drought, the clover content of a mixed sward could be maintained by frequent defoliation, albeit Evans ( 1978) noted that defoliation of clover every 2 days reduced root elongation. In Australia, Hartridge (1979) stressed that the amount of rain and the rainfall pattern determined the white clover content in a pasture. He considered that soil moisture content was the most important environmental factor limiting the production of pasture plants while temperature had the greatest effect on their persistence.

4. Wind White clover may suffer wind stress in exposed situations. It is, however, likely to be protected, at least partially, by associated grasses as it is commonly grown in mixtures, and by its waxy leaf cuticle. Taylor (1976) contrasted lowland and upland climates in the United Kingdom, and described the upland climate in terms of severe wind exposure, low temperatures, excessive precipitation, continual ground wetness, humidity and cloud cover, persistent winter frost and snow cover, sunshine deficiency, and low evaporation. Limited work on the effect of altitude on swards, especiallythe white clover component, has been conducted. In wind tunnel studies, Morse and Evans (1962) showed that clover plant growth was retarded at wind speeds above 0.3 m/sec. Excessive wind speeds (and hail or heavy rain) can induce nastic closure of the leaflets. Wind effects on grass have been demonstrated in wind tunnel experiments by Grace and Pitcairn (198 1). Wind caused increased leaf transpiration and reduced leaf extension, relative growth rate, and leaf area ratio; soil water stress exacerbated the effect. Wind shake of the grass also reduced grass leaf extension. Such effects in the mixed sward conceivably could assist white clover growth due to reduced grass competition but, although no experimental work has been done, it is likely that clover plants within the association could also be adversely affected.

AGRONOMY OF WHITE CLOVER

15

Damage to swards by wind-borne salt spray, particularly desiccation of foliage, can occur in exposed coastal areas (Copeman, 1979),and if clover is a sward constituent then it is likely to be damaged. Exposure to prevailing winds at the site of origin appeared to be an important factor associated with the frost tolerance of natural white clover genotypes (Ollerenshawand Haycock, 1984). In wind tunnel experiments with Grasslands Huia white clover, Bircham (1978) showed that the relative growth rate during wind was higher at 5.0 m/sec than at 10.0 m/sec. He attributed this to water stress; although wind had no direct effect on rate of transpiration, it closed the stomata of the most prominent leaves.

B. SOIL Many soil factors (parent material, texture, bulk density, drainage class, pH, organic matter content, availableplant nutrients, and microbial constituents) affect the growth of white clover and, because these factors interact, it is difficult to determine the dominant influencesfrom published data. However, it is generally accepted that white clover has more specific soil physical and chemical requirements than the accompanying grass (Jackman and Mouat, 1972; Whitehead, 1982; Rangeley and Newbould, 1985; Blue and Carlisle, 1985). 1. Physical

White clover is found on soils ranging in texture from coarse sand to heavy clay with very variable amounts of organic matter in the profile, but rarely in unamended peat ( Burdon, 1983).It is absent from continuouslywaterlogged soils and from shallow drought-prone soils and from strongly saline soils. In the United Kingdom the plant tolerates a range of soil pH from 5 to 6, but rarely occurs if the soil pH is less than 4.5 (Snaydon, 1962). Recent grassland surveys in the United Kingdom indicated that the proportion of clover in swards decreased as soil drainage class went from imperfect to poor to bad (Forbes et al., 1980);age of sward, soil pH, and available soil nutrients had less influence on clover content. McAdam (1983a) found in grazed swards in Northern Ireland that the proportion of swards with a continuous network of stolonsdeclined from 74 to 30% as the drainage class went from good, imperfect, poor, to bad. Clover growth appears to be better in sandy than clay soilsprovided there is no restriction in water supply (F. X. de Montard, personal communication). In New Zealand, there were indica-

16

J. FRAME AND P. NEWBOULD

tions of white clover decline as soil bulk intensity increased with grazing and treading (Edmond, 1974). In a survey of surface seeded pastures in the crofting areas of northern Scotland, Younie and Black (1979) found that the age of swards up to 17 years had little effect on the proportion of white clover, but indigenous vegetation type and soil organic matter content had big influences. A grazed, low-fertility soil previously growing Molinia caerulea had 5.6% clover while a peaty podzol growing Calluna vulgaris had 18%; the higher the percentage soil organic matter the lower was the percentage of white clover. 2. Soil p H Few workers have attempted to define the optimum soil pH needed in soil solution to maintain vigorous growth of white clover, although it is considered to be more sensitive than grass to low pH (Caradus, 1980). Andrew ( 1976), working in sand culture, found that growth of white clover under symbiotic conditions was almost nil at pH 4.0 and increased linearly from pH 4.0 to 6.0; nodulation was reduced below pH 5 . The addition of N to the cultures increased growth in the pH range 4-6 by about 60% provided calcuim ions were present. Most of the studies on this topic have been carried out in water or sand culture (Blue and Carlisle, 1985) so that the influences of A13+toxicity and soil acidity on rhizobia and plant roots have not been assessed. Present thinkingis to add sufficient lime to displace and hydrolyze the toxic amounts of soluble aluminum (Coleman and Thomas, 1967; Logan et al., 1985). In areas where the quantity of soluble aluminum falls below the levels that are toxic, the soil pH varies with soil type but ranges from 5.2 to 5.5. Rorison ( 1958) states that aluminum toxicity to the plant is not a problem if soils are limed to above pH 5.5. Thus the suggestion of Chestnutt and Lowe (1970) promulgated by advisers in the United Kingdom (Anonymous, 1985a) that white clover requires a pH not lower than 5.5 coupled with adequate calcium still seems the best policy.

3. Available Plant Nutrients (P and K) Chestnutt and Lowe (1970) state that a soil P status not lower than 20 ppm available P and a soil available K status of 170 - 200 ppm were required to establish and maintain the growth of white clover. More recently, Goodman and Edwards (1983) reported that a P concentration of about 2.5 ppm was required by the varieties usually grown. These workers gave no figure for K but they emphasizedthat legumes “have a great demand for potassium” and the seedlings fail if K is not added to low-potassium-absorptivesoils.

17

AGRONOMY OF WHITE CLOVER

Even the recent review paper on clovers growing in soils in the United States (Blue and Carlisle, 1985) failed to give a target figure for available soil K. Most workers have tried to describe the quantities of the major nutrients needed to bring about responses in growth of white clover based on cutting experiments (Rangeley and Newbould, 1985) or on critical concentrations in the herbage (Whitehead, 1982). The requirements for satisfactory clover production and maintenance under grazing have received little attention. In mixed swards, clover is more sensitive than grasses to pH decrease or reduction in P (Caradus, 1980) and K supply (Floate et al., 1981). Thus, failure to maintain an adequate pH or supply of available P and K would express itself initially in clover decline. Care must also be taken to balance the input of the major nutrients since interactions between lime and P, lime and K, and K and P have been reported (Floate et al., 1981; Rangeley and Newbould, 1985). The former interaction was reviewed in detail by Haynes ( 1984).The response found for the interaction between P and K when white clover was grown in a peat soil in pots was considerable (Rangeley and Newbould, 1985);without added K there was no response to added P and the maximum production of shoots was found when the highest level of both P ( 1 50 kg/ha) and K (320 kg/ha) were used (Fig. 2). The vital importance of kg K/ha 1

41

1 h Y

L z

U

1

1

50

I

100

1 150

Phosphor u s (kg/ha

FIG.2. The response of white clover to potassium and phosphoruswhen grown for 9 weeks in pots of dry peat soil. (From Rangeley and Newbould, 1985.)

18

J. FRAME AND P. NEWBOULD

this interaction in the grazed situation, where nutrient cycling through the grazing animal can occur, was shown by Floate et al. (198 1). It is generally accepted that maintenance dressings of K are needed mainly when herbage is cut and removed from conservation. However, on a peat soil, despite the extra return of K (and N) in urine, there was little retention of the recycled K in the soil so that higher levels of K than usually prescribed were necessary on this soil. Thus, when P and K were applied together, large responses in herbage production, especially of white clover, were observed; but it should be noted that some of this extra production was due to the N recycled in the urine (Floate et al., 1981).

4. Nitrogen A small supply of soil mineral N is needed by clover until nodules are formed and N fixation commences; thus the use of “starter” fertilizer N is essential in soils of low fertility, such as hill soils (Haystead and Marriott, 1979). However, too much mineral N can depress nodule initiation and development (Sprent, 1979). Animal slurry N and urinary N apparently inhibit clover less than mineral N (Heniott and Wells, 1962; Drysdale, 1966). Further quantification of the breakdown and buildup of organic N in soil and of how these processes are influenced by soil conditions and farming practice is needed (Anonymous, 1983b). Knowledge of the interactions of soil N and N fixation by white clover is also important, and this subject (Section V,B) together with the effect of fertilizer N on the growth of grass/ white clover swards (Section VII1,C) are discussed later.

5. Trace Elements The trace element needs of white clover and/or Rhizobium, especially for the N fixation process, include Co, Cu, Mg, Mn, Mo, Ni, B, Zn, S, and possibly Se (Chestnutt and Lowe, 1970). Some soils in Scotland aredeficient in Cu, Co, or Mn but there is no evidence of Mo deficiency; by contrast some soils contain a small excess of Mo (Reith, 197 1). Experiments have shown that lack of Mo, Mg, and Mn under certain conditions of soil pH, calcium, and major nutrient availability may affect the growth and performance of white clover (Floate et al., 198 1). To ensure that no problems from trace element deficiencies interfered with tests of Rhizobium for inoculation on white clover seeds, Newbould et al. (1982) added the following mixture (in kilograms per hectare) to all their trial sites: 10 CuSO,, 2 CoSO,, 2 ZnS04, 0.2 Na2Mo04 2H20, 5 Na2B4O7,with the addition of 10 MnS04 for deep peat humist soils. The addition of lime to raise the pH to 5.5 and above can

-

AGRONOMY OF WHITE CLOVER

19

markedly affect the availability of some trace elements (Mengel and Kirkby, 1982). Mo is particularly affected by this soil amendment and while not interfering with the growth of white clover, enhanced uptake of this element together with S can induce copper deficiencyin livestockgrazing the herbage (Evans, 1984). A recent study with cores of acid soils from the northeastern United States showed that the use of lime-pelleted seed with a fertilizer combination of K, Mg, Mo, and P improved establishment and growth of white clover, and that application of B, Cu, and Zn depressed nodulation and production possibly because too much was added (Murphy et al., 1984). In Australia and New Zealand, deficiences of Co, Mo, S, and Zn are widespread, and the response of legumes to applications of one or all of these elements can be dramatic (Robson and Loneragan, 1978).

6. Microorganisms One ofthe unique featuresof legumes such as white clover is the formation of a symbiosis between the plant and soil bacteria of the genus Rhizobium which results in fixation of atmospheric nitrogen. Many factors influence infection of the root by the bacteria and the growth and functioning of a nodule but, in the absence ofrhizobia effective at forming nodules and fixing nitrogen, no symbiosis can take place. Rhizobia are only abundant in soil when associated with their host legume and they are strongly affected by adverse conditions such as heat, drought, and acidity. Thus, some soils, especially acid deep peats, contain no rhizobia and others, e.g., acid brown earths (ochrepts)may contain rhizobia, of which only a few are effective at forming functioning nodules (Holding and King, 1963). Methods to study the ecology of rhizobia in soils have developed considerably in recent years (Jones, 1983) but it is still relatively difficult and tedious to determine the number ofeffectiverhizobia in soilswhere it is proposed to sow white clover. Wood and Cooper (1985) demonstrated that some rhizobia are more adapted than others to tolerate acid conditions and in a recent survey of 192 sites in Northern Ireland, Wood et al. (1985) confirmed that clover rhizobia were generally absent from peat sites. However, the data from the same survey revealed large populations ( 106/gdry soil) of rhizobia in mineral soils but only 79% of the isolates were effective on the variety Grasslands Huia. These workers were able to correlate the number of clover rhizobia at each site with soil pH, exchangeable Ca, base saturation, and A1 saturation, but the effectiveness of the rhizobia was not correlated with any soil chemical property. The relevance of this information will become apparent in the section on inoculation (Section IV,C). Another microorganism which can infect the roots of white clover and

20

J. FRAME AND P. NEWBOULD

confer nutritional advantagesto the plant in return for photosynthatesis the vesicular arbuscular mycorrhizal (VAM)fungi (Hayman and Mosse, 1979). The significance of mycorrhizae to the nodulation of N-fixing plants was well described recently by Barea and Azcbn-Aguilar( 1983).This microorganism is not as easily studied as rhizobia since it cannot as yet be cultured in the absence of its host, nor is it easy to identify different strains. Small populations of VAM fungi capable of infecting white clover and scavenging soil P for the plants (Sanders and Tinker, 1971) are widely distributed in soils. Even the acid deep peat hill soils in the United Kingdom, shown not to contain rhizobia, contained a small population of mycorrhizal fungi (0.3 propagules/g soil). On a soil volume basis this population was 100times less than in a brown earth soil but the roots of white clover plants grown in it after the addition of lime had about 15%of their root length infected with mycorrhizal fungi (Rangeley et al., 1981). The ability of VAM fungi to transport soil P from soils where it is in short supply to the clover plant has important consequences. With a supply ofP, both nodules and plants can grow with the former being able to fix atmosphericN, so further helping plant growth. The stimulation of this double symbiosis by inoculation of the white clover seeds or seedlings with either or both rhizobia and VAM fungi is theoretically attractive but, as will be described later, has not yet become of general and predictable application.

IV. CULTURE A. VARIETIES

Van Bockstaele (1985) classified the white clover varieties in western Europe into (1) small-leaved wild white, which is prostate and has thin, much-branched stolons; (2) small-, medium-small-, and medium-largeleaved varieties from northern and western Europe, belonging mainly to the “hollandicum” group and with shorter, less branched stolons and larger petioles than the indigenous wild white type; and (3) large-leaved Ladino type with thick stolons and a robust root system, which is a short-day plant and more frost sensitive than the other types. Varieties are classified in the United Kingdom into four groups according to leaf size, as measured on spaced plants (Anonymous, 1985b):(1) small leaved; (2) medium leaved; (3) large leaved; (4) very large leaved. In the United States,a range of clover leaftypes, small to large, is available, including foreign varieties. Louisiana and Louisiana S- 1 are notable American varieties with intermediate leaf size. Ladino, a large-leaved type, is de-

AGRONOMY OF WHITE CLOVER

21

rived from an Italian ecotype introduced in the early 1900s. It is thus regarded as both a variety and type (Carlson et al., 1985; Gibson and Cope, 1985).Its use in the United States was reviewed by Ahlgren and Fuelleman ( 1950).The variety, Pilgrim, was developed from Ladino in the 1950s.Other varieties, developed from Ladino and new plant introductions, include Merit, Regal, and Tillman. In Europe, member countries of the European Economic Community are required by statute to publish National Lists (NL) of herbage varieties. Only varieties listed in a country can be traded commercially in that country, unless the varieties have subsequently been included in the EEC Common Catalogue,when they can be sold in any member country. To qualify for the Common Catalogue, a variety must be included on a National List for 2 years. Entry to a National List requires independent evaluation, which may vary slightly from one member nation to another. An outline of the testing procedures in the United Kingdom will serve as an example. The evaluation of white clover varieties released by plant breeders is an ongoing exercise. Botanical assessments are made at three centers throughout the United Kingdom to determine the distinctness, uniformity, and stability (DUS tests) of the new varieties. Simultaneously, the varieties undergo comprehensiveassessment of their value for cultivation and use (VCU trials)at 1 1 centers; one to six new varieties may be under test annually. Each variety is sown for 2 consecutive years, but production is measured for NL purposes in full harvest years 2 and 3, and not in the year followingestablishment. The varieties are sown with a perennial ryegrass companion (cv. Premo) and cut five to seven times per season at production levels of - 1.5 tons DM/ha per cut. Two fertilizer N regimes of 0 and 200 kg/ha per year have been used from the inception of the white clover NL trials in 1974, but from 1983 sowings only the high N regime is being applied. Further plots of the varieties also sown with Premo are cut over every 10- 14 days during the growing season to assess clover persistence under frequent defoliation. Varietal performance is compared with that of standard control varieties using the criteria of seasonal and annual DM production of total herbage and of clover persistence, winter hardiness, and resistance to pests and diseases. The principal purpose of NL testing is to report on each variety for NL acceptance, and resultsare published in due course in the Plant Varietiesand Seeds Gazette (Her Majesty’s Stationery Office, 1977 et seq.). However, advisory services also use the results to recommend varieties (Anonymous, 1985b,e)to grassland farmers for use in seed mixtures. These advisory publications are revised annually as information on new varieties, or the results of retests of older varieties become available. Ofthe 2 1 white clover varieties on the National List in September 1985 (Table 11) 12 are recommended in Scotland (Anonymous, 1985e)and 14 in England and Wales (Anonymous, 1985b).

22

J. FRAME AND P. NEWBOULD Table I1 White Clover Varieties on the United Kingdom National List, October 1985 ~

Small leaved

~

Medium leaved ~

A b e r y s w h S 1 84a.b Kent Wild WhiteRb Rivendel"

~bevstwyths 1 0 0 4 DonnaRb Grasslands HuiaQb Mennaanb Pajbjerg M i l k

Large leaved

Very large

~~

Aliceb Blancaa.b Grasslands Pitau Kersey Whiteb MilkanovaRb N e d Olwenb Retor" Ross Sabeda

Aran4,b

Sonja4sb Recommended in Scotland. Recommended in England and Wales.

A number of the varieties have been in commerce for many years. For example, Grasslands Huia was developed in New Zealand in the 1930s although improvements were incorporated up to 1960 (Barclay, 196 1). Prior to 1956 it was known as New Zealand white clover. The New Zealand variety Grasslands Pitau, released in 1975, was developed for better cool-season growth than Huia (Barclay, 1969); it also has better growth from midsummer to autumn (Brock, 197 1). Aberystwyth S 184 wild white clover was released in 1942. Some newly introduced varieties have shown marked production superiority to older varieties (Ingram and Aldrich, 1982; Davies, 1984; Frame, 1985a) but seed supplies have been scarce, particularly of the British and European releases. Of the 900- 1000 tons ofwhite clover seeds used annually in the United Kingdom only around 4% is home produced, whereasbetween 80 and 90% is imported from New Zealand (Davies, 1982, 1984). Some of the new releases were developed for lowland rotationally grazed swards receiving fertilizer N, but have also exhibited good productive ability without N (Davies, 1984; Rhodes, 1984; Connolly, 1985). However, following the energy crisis in the early 1970s and a heightened appreciation of the fossil fuel energy required in the manufacture of fertilizer nitrogen for modem high technology agriculture (Pimental et al., 1972), breeding has concentrated on white clover potential per se. Rhodes (1984, 1985) listed the current breeding objectives in the United Kingdom as (1) to breed varieties which are persistent and productive under continuous grazing and suitable

AGRONOMY OF WHITE CLOVER

23

for hill and upland conditions, (2) to improve predictability of yield in upland and lowland conditions through disease and pest resistance, grass/ clover compatibility, and better spring growth of white clover, (3) to ensure high seed yield potential, and (4) to improve Rhizobiumlclover symbiosis. Van Bockstaele (1985) and Gibson and Cope (1985) have listed the characters related to persistence and productivity which they considered of relevance and value in breeding programs in Europe and the United States, respectively. There is a dearth of information on clover varietal response to winter cold and frost stress (Davies, 1970). Hams et af.(1983) found varietal differences in which vigor of early clover growth in spring was related to the amount of stolon which overwintered satisfactorily.The low stature and “dwarf” morphological features of small-leaved varieties allow them to enter spring with more stolon and leaf than larger leaved varieties. The widely used variety Grassland Huia may sufferwinterkill or damage in severe winters albeit it has potential to recover; Hunt et af.(1 965) noted that the length and weight of stolon in Huia were very low in spring followingwinter frost damage. The Huia variety is not adapted to hill country and severe grazing in New Zealand (Lancashire, 1974; Suckling and Forde, 1978; Charlton, 1984), but the recently bred variety GrasslandsTahora (Williamset af.,1982; Charlton and Giddens, 1983) is likely to be better adapted to predominantly sheep-grazed hill country, especially under moist and wet conditions. Clover varietal winter hardiness needs to be examined further to identify the best varieties for upland or exposed areas and for colder latitudes generally (Copeman, 1979; McAdam, 1984). Because of the resources required for grazing work, clover varietiesare not routinely compared in terms of response to grazing, voluntary intake, or animal production. However, grazing experimentationis increasingly being conducted at research centers. Experiments involving cutting, rotational grazing with sheep, or continuous sheep stocking have revealed marked variety X defoliation system interactions (Evans, 1979; Evans and Williams, 1982, 1984; Connolly, 1985). The best varieties under cutting, usually large-leaved types, often performed less well or poorly under continuous stocking while conversely, small- or medium- leaved types were usually the highest producing under continuous stocking. The ranking order for varieties was similar under cutting and rotational grazing. Selective grazing of clover by sheep with consequent loss of stolon appeared to be a major factor contributingto a decreasein clover performance under continuous stocking (Evans and Williams, 1984). Since white clover is mainly a grazing species and emphasis in practice is on its use in the grazed sward, there is a need to expand varietal evaluation under appropriate grazing systems. However, the experimental techniques

24

J. FRAME AND P. NEWBOULD

used must be standardized so that results of different experiments can be adequately compared (Frame and Newbould, 1984). These authors also make a general observation that most agronomic and grazing work on the grass/white clover sward in the United Kingdom has been undertaken with clover varieties not alwaysreadily availablein practice; this implies a paucity of work with Grasslands Huia. B. LIMEA N D FERTILIZERS The quantity of lime and fertilizers needed to create the optimum soil conditions for the growth of white clover swards is normally based on soil analysis. However, the latter can be a poor guide, especially in acid, organic matter-rich hill soils in the United Kingdom (Pimplaskar et al., 1982). Sufficient lime should be used to reduce the quantity of soluble aluminum, where this is present, and to raise the soil pH to 5.5 but no higher than about 6.0. Account must be taken of cation exchange capacity and quantity of soil organic matter in determining the lime requirement (Logan et al., 1985).In Scotland, 5 - 7 tons of lime per hectare are usually required (Anonymous, 1983b)with the higher amount being applied to the deep peat (humist) soils in the wetter west. This amount is adequate to raise the pH of the top 5 -7.5 cm of soil so that white clover can establish successfully. Subsequently, maintenance amounts of lime, 2-3 tons/ha at 3- to 5-year intervals, is recommended to ensure that the conditions continue to favor growth of white clover. Present recommendations for the nutrients needed to establish grass/ white clover swards in Scotland (Anonymous, 1983b)are to use 50,40, or 25 kg P/ha for soils of low, moderate, and high status, respectively,and 100,75, and 50 kg K/ha for soils of similar relative status in available K. For very nutrient-deficient deep peat soils in Scotland, Floate et al. (1981) recommended 60 kg P and 80 kg K/ha to establish a perennial ryegrass/white clover sward. C. INOCULATION

The significance and application of rhizobial inoculation in agriculture have been reviewed recently by Peterson and Loynachan (1982), Newbould (1983),and Burton (1985).The latter authorgivesadetailed account ofother aspects of rhizobia relationships in addition to inoculation. Inoculation by transfer of soil in which legumes had been grown to fieldsabout to be used for legumes was practiced in 9000 BC. At the present time, clover seeds are

AGRONOMY OF WHITE CLOVER

25

treated with a layer of bacterial cells suspended in a mixture of finely ground peat and glue immediately prior to sowing. Widespread trials with this method for white clover to be grown in acid hill soils where no clover had been grown previously gave disappointing results (Newbould et al., 1982). Only in the deep peat and wet peaty podzol soils were there consistent and significantresponses to inoculation in shoot growth (Table 111). The practice of spraying solutions of rhizobia onto young white clover seedlings has been tested in Wales (Young and Mytton, 1983; Mytton and Hughes, 1984). These authors showed that the strain of rhizobia must be matched with the variety of white clover and that this method of inoculation was also unpredictable in its success. The causes for poor clover response to inoculation in many soils are not hard to find. The small numbers of relatively ineffective indigenous organisms are highly competitive to the introduced strains. The latter have usually been selected after screeningfor effectivenessin monoculture and on one variety of white clover. Recent work by Jebb (1984) has studied competition between indigenous strains of rhizobia and considerable differences were found. However, the highly competitive strains were often of only moderate effectiveness at fixing nitrogen. It is hoped that microbial genetics can transfer nitrogen fixing genes to these strains, to make elite (competitive/effective)strains for use in practical agronomy. Much work is needed by rhizobiologists and by plant breeders to achieve this goal but its realization could have a big impact on the culture of white clover in pastures. Early suggestions from Powell ( 1976, 1977, 1979), working in New Zealand, that the growth of white clover would be considerably stimulated by inoculation of white clover seeds or seedlingswith VAM fungi have not been fully realized. Rangeley et al. ( 1981) obtained large responses in white clover shoot growth to inoculation with VAM fungi under laboratory conditions Table 111 The Response in Herbage Production of White Clover (cv. Grasslands Huia) to Rhizobiurn Inoculation in Year of Sowing" Herbage production (kg DM/ha) ~~

Soil type

No Rhizobium

With Rhizobium

~

Brown earths (ochrepts) Dry peaty podzol (orthods and humods) Wet peaty podzol (aquepts and aquods) Deep peat (fibrists and hemists)

77 126 65 61

From Newbould ef al. (1982). Significantly different at the I % probability level.

SED ~~~

94 129

14

93

26 20

120

28b

26

J. FRAME AND P. NEWBOULD

but were unable to reproduce these responses in the field. Hayman and Mosse ( 1979),using preinoculated clover seedlings in the field in hill soils in Wales, were able to show a response but this method of inoculation is not a practical proposition. Tests of an inoculation pellet containing nutrients, rhizobia, VAM fungi, and white clover seeds are now in progress under field conditions at several sites in the United Kingdom (Hayman, 1984). The advantage of inoculation with both rhizobia and mycorrhizal fungi has been described (Newbould and Rangeley, 1984)for an acid peat soil in the laboratory. With this soil, shoot production, nodulation, and N fixation by white clover were increased by 160, 130, and 85%, respectively, followinginoculation with mycorrhizal fungi in the presence of effective rhizobia. Further study to devise practically applicable methods of inoculation with elite strains of both rhizobia and mycorrhizal fungi appearsjustified. At the present time in the United Kingdom, inoculation of clover seed or seedlings with rhizobia is recommended for use on all hill soils as an insurance,but it is essential on deep peat and wet peaty podzol soils.

D. ESTABLISHMENT There is a lack of suitable assessment techniques for judging success or failure in clover establishment and long-term survival (Haggar et al., 1985a); Haggar et al. suggested about 150plants/m23 months after sowing, translating to 30%ground cover 12 months later, as a suitable target.

1. Relative Clover:Grass Seed Rates A high clover or low grass seed rate can improve white clover plant establishment (Hemott and Wells, 1960;Cullen, 1964b;Young, 1984). However, due to the ability of clover to proliferate by stolons and possibly by late germination of hard seed (those in which the testa is intact), this initial effect ofclover :grass seed ratio is ovemdden in the first or second full harvest year. Chestnutt and Lowe (1970) concluded that a ratio of clover to grass seed of 3.5 kg/ha to 22 - 25 kg/ha was adequate for obtaining a good clover :grass balance in a sward. Laidlaw (1 978) confirmed the short-lived effect of clover :grass seed ratio when he examined combinations of clover seed rates ( 1 - 9 kg/ha) and grass seed rates (3- 14 kg/ha). A constant clover seed rate with varying grass seed rates also has no significant effect on white clover performance (Cullen, 1964b Frame, 1985a).It may be concluded that there is scope for considerable flexibility in the clover :grass seed rate ratio in seed mixtures, but nevertheless there has been a scarcity of work on the critical

AGRONOMY OF WHITE CLOVER

27

seed rate of white clover necessary to establish specific seedling populations. Meantime, it would seem prudent to sow 3-5 kg clover seed/ha in the mixture to ensure a satisfactory clover presence in the early life of a stand. If this presence is not achieved, considerable management skill and favorable conditions will be needed to encourage satisfactory clover spread.

2. Time of Sowing There is scant recent published information on this topic. The optimal time of sowing for white clover is primarily related to the avoidance of climatic conditions which militate against its establishment. Midsummer is often associated with soil moisture deficits. Late-autumn sowing leaves insufficient time for adequate plant development before the onset of low winter temperatures. Mortality of autumn-sown clover can be high due to attack by Pythium and other fungi which cause “damping off’ of seedlings. Spring is therefore the best time for sowing. Very early spring sowing could have low-temperature limitations, although white clover seeds germinate and seedlings emerge more rapidly than grass even under unfavorable soil conditions such as low soil temperatures (Stapledon and Wheeler, 1948). Winter cereal growing has expanded considerably in recent years in certain areas of the world. If harvested early there is opportunity for direct seeding of grass/clover mixtures, therefore avoiding the hazards from nurse crop competition with undersowing techniques. However, there is a danger in colder latitudes that the period after harvesting winter cereals is too short for satisfactory plant development before winter onset (Harris et al., 1983; Younie et al., 1984). Stress and damage to grassland plants in winter are caused by a number of interactive factors including low temperatures, fluctuating temperatures, snow cover, low light intensity, and wind (Copeman, 1979). In practice, several factors including the farming system and local weather patterns will influence the timing of sowing. In principle, direct seeding in spring offers the best chance of entering the first full harvest year with a balanced grass/clover sward since there is time for manipulation of grazing management, weed control, and other measures to encourage clover spread.

3. Sowing Depth Because of its small seed size and consequent limitations in food reserves, white clover seed should be sown no deeper than 13 mm (Cooper, 1977). Deeper sowing, while possibly ensuring a better moisture supply, delays

28

J. FRAME AND P. NEWBOULD

emergence, weakens seedlings, and reduces their competitiveability against companion grasses or unsown species. Companion grasses, depending on the species, can be smaller in seed size (e.g., timothy) or several times larger (e.g., tetraploid perennial ryegrass). Undoubtedly, sowing white clover too deeply is a major cause of poor establishment. Stapledon and Wheeler ( 1948)concluded that optimum establishment of herbage seeds required different fractions of a seed mixture to be sown at depths suited to the different seed sizes, a practice difficult to achieve with commercial sowing equipment. When white clover (and timothy) seed were broadcasted, and perennial ryegrass drilled, a 50% better establishment of white clover resulted than from either drilling or broadcasting the whole seed mixture (Hemott, 1970). The technique employed in Hemott’s work of using a seed box for clover seed mounted on the rear of a seed drill should be exploited; alternatively, Cooper ( 1977)suggested that a drill could be developed which provided simultaneous seeding of grasses and clovers in alternate rows at different depths. To obtain reasonably precise sowing depths, a fine, firm soil tilth with an even soil surface is required. Soil cover and seed/soil moisture contact are more readily obtained with a fine than a coarse soil tilth. The technique of smoothing the soil surface with a soil leveller is one which is often neglected in farming practice. Good consolidation, subsequent to seeding, but avoiding soil “capping,” will increase contact between soil and seed and, with autumn sowing, will reduce the chances of damage to young plants by frost heave (Anonymous, 1983b). 4. Cover Crop A direct seeded grass/white clover sward is not as productive in its sowing year as an established sward. Thus a spring cereal grain cover crop has been commonly used to augment productivity per unit area and to give an immediate cash return. However, because of competition from the cover crop, the chances of poor clover seedling establishment, or even of clover failure, are greater under a cover crop than with direct sowing (Cullen, 1964a;Spedding and Diekmahns, 1972; Younie et al., 1984). Winterkill of poorly developed clover plants is also likely. Poor clover establishment is likely to lead to low clover presence in the sward, at least in the early harvest years. It can thus be a contributory factor in the production variabilityassociated with grass/clover swards. An arable silage (cereal/forage pea) crop, with subsequent early removal, is an alternativeto a cereal grain crop (Whytock and Frame, 1985), and fundamentally, direct seeding is the best option for clover.

AGRONOMY OF WHITE CLOVER

29

E. COMPANION GRASS One of the major guidelines for the encouragement of a significant white clover proportion in grass/white clover swards is the choice of suitable companion grasses (Chestnutt and Lowe, 1979;Frame and Newbould, 1984). It is well documented that grasses differ in their competitivenessto clover, but a grass’s adaption to an area usually takes precedence over its suitability as a companion grass to clover. Within the perennial ryegrass species, the lower producing, less persistent varieties permit the best performance by white clover (Cowling and Lockyer, 1965; Green and Corrall, 1965; Wright and Faulkner, 1977; Camlin, 1981). Orchardgrass and tall fescue are highly competitive (Chestnutt and Lowe, 1970;Van Keuren and Hoveland, 1985). Differences in the relative within-season patterns of growth can aid the success of the grass/clover association (Turkington and Harper, 1979b; Haynes, 1980),although defoliation management can alter the normal seasonal production of the associated species (Harkess et al., 1970).The slower spring growth ofwhite clover, because of its inability to grow at low temperatures, renders it at a competitive disadvantage in mixture with grass but it should be possible to exploit the genetic variation in white clover and select for earlier spring growth (Ollerenshawand Baker, 1981;Ollerenshaw, 1983; Glendining et al., 1985). Summarizing a series of trials using modern high-yielding perennial ryegrass varieties, Frame (1985b) concluded that ear emergence date did not have a marked effect on white clover performance (Table IV). There are indications that white clover contribution and production are higher with a tetraploid ryegrass companion than with a diploid ryegrass (Frame, 1985b; Collins, 1985; Davies, 1985). Possibly the coadaptation concept whereby white clover and perennial ryegrass varieties are developed from already coexisting genotypes will lead to improved compatibility and performance of mixtures based on these varieties (Turkington, 1979; Turkington and Harper, 1979c; Burdon, 1983; Evans et al., 1983; Evans and Hill, 1984). Little compatibility work has been undertaken with mixtures of grasses, yet commercial seeds mixtures often contain several species of grass and sometimes more than one variety of a species. F. WEEDCONTROL Cultural methods of weed control have always been important in the sward establishment process. Preparation of a clean seedbed is an example of preemergence cultural control, and topping of tall annual weeds is a post-

30

J. FRAME AND P. NEWBOULD

Table IV Herbage Production from Perennial Ryegmss/White Clover Swards Cut under a Simulated Grazing Regimea DM (tons/ha per year)

Ear Experiment

Grassb

emergence type'

1

D D/T D and T D and T D T D D T

E E I L I and L I and L I I I

2 3

4 5 6

Total herbage

White clover

1.9

4.3 3.8 3.8 3.5 3.4 3.9 4.1 5.6 5.1

1.2

8.7 8.3 8.5 8.5 7.8 8.8 8.1

White clover

(%I 54

53 44 42 40 46 53 64 63

From Frame (1985b). D, Diploid or 2n; T, tetraploid on 4n. E, Early; I, intermediate; L, late.

emergence example. The sown clover is at its most vulnerable in the establishment phase when the open sward canopy can permit very rapid weed development. Apart from adversely affecting the establishment of sown species, weed ingress can adversely affect the subsequent yield potential of the sown sward (Haggar and Squires, 1979). Since grassland is not a crop with direct financial rewards from weed control, commercial development of herbicides has been slow and grassland farmers have been slow to integrate herbicide use into their management compared with arable farmers. The critical densities of weed species at various phases in the life of a sward have not been defined. Clover-safeselective herbicides such as MCPB and 2,4-DB have a long history of use for weed control in establishing or established grass/clover swards, but with limited efficacy; consequently, they have been boosted with 2,4-D or MCPA or have been superseded (Williams, 1984). Benazolin-, bentazone-, and linuron-based herbicides, effective against a wide range of speciesincluding the major weed, chickweed (Stellariamedia), were introduced recently into the United Kingdom for establishingor established grass/clover swards. Chickweed is a particular problem especially when it forms large smotheringclumps of up to 50 plants/m2(Haggar et al., 1982);dense infestation (up to 3000 plants/m2)of annual meadow grass (Poa annua) can also suppress sown species. The problem is exacerbated in mild wet autumns if the establishment of sown species is slow or poor. However, as efficiency against broad-leaved weeds is stepped up, the

AGRONOMY OF WHITE CLOVER

31

chances of damage to clover is also likely to increase. Timing of application becomes more critical, and the guidelines for application must be closely followed. Because clover seedlings do not always emerge uniformly, all the plants are not necessarily at the required growth stage (usually one to three trifoliate leaves depending on the herbicide) for tolerance to the herbicide, and a check to clover development or, indeed, plant death is not uncommon following the application of herbicides (Kirkham and Haggar, 1983; Kirkham el ul., 1984; Standell, 1985). If clovers are suffering from pest or disease attack, they can suffer a severe setback even when sprayed at a safe growth stage. There is not a great deal of published experimental evidence proving definitive clover safety of herbicides, and damage may go unnoticed simply because the grass/clover sward is a dynamic entity and the reasons for a changing balance in grass :clover ratio are not always recognized. Scorch, temporary suppression, and severe checking of clover are terms often mentioned on the manufacturers’ labels. Frame and Newbould (1984) suggested that incorrect use of herbicides was a major cause of lack of clover presence in sown grass/clover swards. Choice of herbicide will depend upon the weed spectrum present. Pernicious perennial weeds such as docks (Rumexspp.), thistles (Cirsiumspp.), or nettles (Urticu spp.) should be treated presowing. The undersown cereal crop poses a dilemma since the best herbicide for the cereal crop may not be the safest to the clover. Also, both cereal and clover may not reach a safe growth stage for tolerance to the herbicide simultaneously. Late application in relation to the cereal growth stage can result in reduced grain yield; overearly application results in death or retarded development of clover plants (Broughton et ul., 1982).In general, clover seedlingsare more susceptibleto herbicide damage than grass seedlings. Because of the practical difficultiesassociated with clover susceptibilityto herbicides when establishing a grass/clover sward, Haggar et u1. ( 1985a) proposed an “evasive” strategy. White clover would be established in monoculture in spring with or without a suitable cover crop. Then preemergence weeds would be controlled by EPTC and postemergence weeds by MCPB/ benazolin/bentazone mixtures, and clover would be well established by late summer and could then be slot seeded with its companion grass, such as perennial ryegrass. In the established grass/clover sward, invasion by perennial broad-leaved or grass weeds can lead to sward deterioration and low production from the sown species (Dibb and Haggar, 1979). Herbicide options to control certain problem weeds adequately have increased recently, but a penalty to clover of plant scorch, suppression, or even death has had to be accepted, e.g., ethofumesate for control of annual meadow grass, soft brome (Bromus mollis), or

32

J. FRAME AND P. NEWBOULD

chickweed, linuron for control of chickweed, 2,4-D for control of ragwort (Seneciojacobaea), and dicamba/mecoprop/MCPA,triclopyr, or triclopyrbased herbicides for the control of perennial broad-leaved weeds such as docks and thistles in established grassland. Comprehensive recommendations for weed control in grass/clover and clover swards have been listed by Fryer and Makepeace (1978), Anonymous (1983d), Williams (1984), and Lee ( 1985). It is important to note that after removal ofweedsby herbicide, a judicious management strategy is necessary to remove or ameliorate the conditions causing weed problems. Various individual factors or combinations have been identified;they include poor drainage, acidity, plant nutrient deficiencies, overgrazing, and undergrazing. G. DISEASES Investigations into clover diseases have been and still are limited in relation to other aspects of clover studied (Anonymous, 1977, 1983c; Lewis, 1984).However, it is becoming increasingly apparent that disease is a major cause of clover unpredictability and loss in swards (Chamblee et al., 1983; Gibson et al., 1983;Davies, 1984;Frame and Newbould, 1984).The various diseases affecting white clover have been listed for the United Kingdom by Speddingand Diekmahns ( 1972),Burdon ( 1983), and Williams ( 1984), for Ireland by O’Rourke (1976), for Canada by Turkington and Burdon (1983), and for the United States by Leath (1985) and Barnett and Diachun (1985). Clover rot (Sclerotinia trifoliorum) is a serious disease of white clover, especially in England and the United States, which adversely affectsproduction and persistency (Gibson and Hollowell, 1966; Aldrich and Doling, 1967; Aldrich, 1970a; Scott and Evans, 1980; Davies, 1982, 1984; Anonymous, 1985b; Carlson et al., 1985; Leath, 1985). Other synonyms for the disease are collar rot, black patch, Sclerotinia root and crown rot, Sclerotinia wilt, and clover canker. The fungus is soil- and seed-borne. Infection occurs mainly in autumn by wind-borne spores produced from sclerotia which form in the crown of the plants. Symptoms, mainly seen in early spring, include stolon and root rot, wilting, and plant death. The recommended list of clover varieties for England and Wales (Anonymous, 1985b)gives varietal production from Sclerotinia-infectedand Sclerotinia-freesites. Varietal resistance ratings, devised from the assessment of plants grown on naturally infected field plots, are given on a 1-9 scale (9 = good resistance). Varietal resistance ranges from 1 (Grasslands Huia) to 6 (Blancaand Sonja).In dense stands of clover in the south of the United States, another fungal root rot disease (Sclerotinia rolfssii) causes severe damage especially in humid conditions (Carlson et al., 1985).

AGRONOMY OF WHITE CLOVER

33

Clover root deterioration can also be caused by a range of soil-inhabiting fungi, either individually or in combination. The principal pathogenic fungi appear to be species of Fusarium, although other genera are implicated (Halpin et al., 1963; O’Rourke, 1970, 1976; Menzies, 1973a). The root rot complex has long been a recognized problem in the United States (Leath et al., 1971). The symptoms are progressive necrotic breakdown of tap and lateral roots. The Fusarium species do not appear to become active until the plants are exposed to stress, whether nutritional, climatic, managemental,or from pests or other diseases. Because of the complex nature of the problem, breeding for resistance is likely to be difficult (Leath et al., 1971; Menzies, 1973a; O’Rourke, 1976). A number of conspicuous foliar diseases are widespread in many temperate countries of the world, especiallywhere wet conditionsare common. The production and quality of the clover forage are adversely affected although little is known ofthe extent of the losses. Leafloss, lack ofvigor, stunting, and leaf yellowing can occur. The diseases, mainly leaf spots, and their causal pathogens include pepper spot (Leptosphaerulina trifolii), sooty or black blotch (Cymadothea trifolii), anthracnose (Colletotrichum trifolii), the leaf spots (Stemphylium sarcinaeforme, Pseudopeziza spp., and Curvularia trifolii), spring black stem (Aschochyta imperfecta), and summer blackstem (Cercospora zebrina) (Gibson and Hollowell, 1966; O’Rourke, 1976; Brougham et al., 1978; Carlson et al., 1985). It has been reported that sooty blotch can result in increased levels of coumestans (flavonoid estrogens) in clover forage which, following ingestion by livestock, can lead to reproductive disorders (Newton et al., 1970; Wong and Latch, 1971). Rusts (Uromyces spp.) can be serious in some countries, causing leaf loss, lowered forage quality, and impaired N fixation (Gibson and Hollowell, 1966; ORourke, 1970, 1976). Clover is sometimes affected adversely by powdery mildew (Erysiphe trvorii). In attempting to control seed-borne disease in clover seedlings, Lewis ( 1984) reported inconsistent benefits from routine fungicide use (e.g., benomyl, metalaxyl) at establishment. Many virus diseases, systemic in clover plants, and frequently insect transmitted (principally by aphids), have been recorded. The virus damage is often subclinical but the effect can also be debilitating and severe, causing reductions in clover production and persistency (Kreitlow et al., 1957; Fry, 1959; Gibson et al., 1981). Virus infection can also reduce flowering and seed yields (Barnett and Gibson, 1977). It was noted by Carr ( 1979) and Carlson et al. (1985) that white clover was commonly affected by multiple infections of three or four distinct viruses. Viruses affecting clover include white clover mosaic, clover yellow vein, red clover vein mosaic, red clover necrotic mosaic, alfalfa mosaic, arabis mosaic, pea mottle, aster yellow mosaic, and peanut stunt (Davies, 1964, 1970; Gibbs et al., 1966; O’Rourke,

34

J. FRAME AND P. NEWBOULD

1970; Barnett and Gibson, 1975; Brougham et al., 1978; Turkington and Burdon, 1983;Carlson et al., 1985).Rugose leaf curl caused severe effectson seedlings in Australia (Grylls and Day, 1966). Clover phyllody is a mycoplasma disease reported from several countries (Kilpatrick and Kreitlow, 1961;O’Rourke, 1970, 1976; Gibson and Hollowell, 1966;Carr, 1979;Turkington and Burdon, 1983).Infected plants show poor rhizobial nodulation (Joshi et al., 1967), reduced vegetative vigor, and increased winterkill compared with healthy plants. Infected plants usually fail to set seed so the disease can be a problem if present in breeding material (Carr and Large, 1963).English stolbur (clover red leaf) and clover witches’ broom are other mycoplasma diseases, transmitted by leafhoppers, which cause morphological abnormalities (Williams, 1984). It has been concluded that the most stable long-term solution to clover diseases generally is to produce varieties resistant to the commonest and most damaging pathogens; also the introduction of highly susceptiblegermplasm into plant breeding programs should be avoided (O’Rourke, 1970; Davies, 1974;Carr, 1979; Fisher and Hayes, 1982).However, because of the complexity of some of the diseases, progress in breeding programs may be slow (Davies, 1970; Leath et al., 1971). A greater effort is also required to quantify the effects of disease on clover production and persistence, and ascertain the best means of control. H. PESTS In grass/clover swards there is a large biomass of insectsand other invertebrates in and on the soil and on plants. Of this biomass only a small proportion may be regarded as pests, and of these veiy few are capable of damaging white clover. Damage can range from sporadic to frequent and from small patches to large areas. Complete destruction of the clover component in a sward is not common. Because of the often-covert nature of their activities, the pests and the damage they inflict are not always appreciated (Anonymous, 1977, 1983~; Burdon, 1983). Also, variability in clover production is clearly influenced by a complex of factors some of which, such as soil or climatic, are more obvious and have therefore received more study. The various pests affectingwhite clover in the United Kingdom have been tabulated by Spedding and Diekmahns (1972), Burdon (1983), and Williams (1984). Major pests of clover in the United States are listed by Gibson and Hollowell (1966), Carlson et al. (1983, and Manglitz (1 985). Cook and York (1979) referred to plant stunting, distortion, and drying out caused by stem eelworm (Ditylenchus dipsaci) in spaced white clover plants and speculatedthat such effectscould contribute to the unpredictabil-

AGRONOMY OF WHITE CLOVER

35

ity of white clover in grass/clover pastures. Williams and Barclay ( 1972) noted that stem eelworm infestation during sward establishment could inhibit clover and delay the development of a well-balancedgrass/clover sward in New Zealand. Varietal resistance to stem eelworm can vary. Williams ( 1972) ranked Ladino clover varieties as highly resistant, while Bingefors ( 197 1) also classed a number of Danish varieties as resistant. Aberystwyth S 184 was susceptible (Cook and York, 1979). The clover cyst nematode (Heterodera trifolii) is widespread in British agricultural soils (Cook and York, 1985). While its effects have not yet been quantified it was associated with the disappearance of white clover from a cutting trial and lack of clover vigor in a grazingtrial (Morrison, 198 1). It was also found at sites where clover production was low (Evans et a!., 1982). They recorded better clover establishment (three to six times) with nematicide (aldicarb)treatment relative to untreated on a site infected by stem (0. dipsaci)and cyst (H. trifolii)nematodes. Evans and Cook (1 983) obtained an improvement in herbage production of 2.5 times from aldicarb-treated plots. The adverse effect of clover cyst nematode on clover performance has been noted in the Netherlands (Ennik et al., 1965) and in New Zealand (Yeates et al., 1975). At sites in New Zealand with mixed populations of H. trifolii and the root knot nematode (Meloidogyne hapla), seedlings and established plants were damaged (Healy et al., 1972, 1973; Yeates et al., 1973). Damage to white clover by the root knot nematode is also widespread in the southern United States (Carlson et al., 1985). Free-living nematodes (Pratylenchus spp.) have been reported to delay clover growth and plant development in Canada and the United States through feeding on the roots and reducing root size (Minton, 1965; Willis and Thompson, 1969). In parts of New Zealand, the grass grub (Costelytrazealandica) is a major pest. The larvae feed on the roots of pasture plants and high infestations can cause reduced herbage production and the disappearance of white clover (Brougham et al., 1978; East et al., 1980). Grub populationsincrease to peak levels in reseeds and in permanent pastures and then, for unknown reasons, subsequently decline naturally to low levels (East and Willoughby, 1983). Knowledge of population dynamics can help in formulating a strategy of control. Wilson ( I 978) identified a number ofpotentially tolerant and resistant lines of white clover. The subterranean grass caterpillar, porina (Wiseana cervinata), is also a serious insect pest of New Zealand pastures (Pottinger, 1968; Harris, 1969), but quantitative measurements of its effects on sward productivity are scarce. Larval feedingcan destroy clover plants but there can be regeneration after defoliation by porina if there is a developed mat of clover stolons (Harris, 1969).

36

J. FRAME AND P. NEWBOULD

Sporadic reports of damage to white clover by slugs, particularly in autumn, have been made (Anonymous, 1982; 1985b). The extent of slug damage in commercial swards in the United Kingdom is unknown but swards are most vulnerable in the establishment phase. Deroceras reticulatum is the species of slug most implicated in the United Kingdom but Carlson et al. (1985) note L i m a spp. in the United States. Slugs are also a likely problem to seedlings in minimal cultivation techniques such as direct drilling (synonyms are slot seeding, sod seeding) into established swards (Edwards, 1975; Allen, 1981; Clements and Bentley, 1983). In a review of seed establishment in directly drilled sowings, Naylor et al. ( 1983)listed a set of guidelines for successwhich included the incorporation of crop protectant chemicals applied presowing or pre- or postemergence. The attractions of the clover varieties Sonja and Milkanova to slugs, and therefore their susceptibility to damage, has been noted (Shakeel and Mowat, 1984; Anonymous, 1985b). The chemical methiocarb is effective against slugs. Angseesing ( 1974)observed that slugs, snails, and small mammals preferred acyanogenic forms of clover. Leathejackets (Tipula spp.) feed on and damage clover, especially in spring (White and French, 1968). They can also be a problem on direct drilled land (Edwards, 1975). Effective means of predicting the onset of leatherjacket infestation and damage in swards are available (Newbold, 1981; Anonymous, 1985d). Several pesticides are effective, e.g., chlorpyrifos, triazophos, quinalphos, and y-HCH. Other pests of lesser importance generally, but which can be important locally in various countries, include weevils (Sitona spp.), clover leaf and alfalfa weevils (Hyperapunctata and H. postica, respectively),and the potato leafhopper (Empoasca fabae). Pests which affect seed crops in the United States include the lesser clover leaf and clover head weevils (Hypera nigriorostris and H. meles, respectively), clover seed weevil (Miccotrogus picirostris), Ladino clover seed midge (Dasineura gentneri), the lygus bugs (Lygus hesperus and L. elisus), and spider mites (Tetranyclues spp.) (Gibson and Hollowell, 1966;Carlson et al., 1985;Manglitz, 1985).In England, attack by the white clover seed weevil (Apion dichroum) can reduce seed production by one-quarter (Anonymous, 1979). I. SEED PRODUCTION Annual usage of white clover seed in the EEC is -3000 metric tons (Fritsen, 1985). Denmark is the major producer in the EEC but production has declined to a quarter (800tons) ofthat adecade ago. A similar pattern has

AGRONOMY OF WHITE CLOVER

37

occurred in the United Kingdom; annual production is now only 30-40 tons compared with 120- 160 tons formerly (Anonymous, 1983c). Italy produces a few tons of Ladino clover types, including the variety Expanso. The main reason for the decline in Denmark and the United Kingdom is the wide variation in seed production among individualcrops and years, leading to erratic economic returns for growers. Fritsen (1 985) quoted a “normal” mean production of 430 kg/ha k 30% but noted that production was only about 100 kg/ha in years with poor weather conditions. The average seed production in the United Kingdom of certain old-established varieties (S 184, S 100, Kersey) is only 100- 135 kg/ha (Anonymous, 1983~). Home-produced seed in the United Kingdom now consists of only 4% of the annual usage of 900- 1000 tons (Davies, 1982; Anonymous, 1983c). This reflects the climatic disadvantages of the United Kingdom for producing seed (Williams, 1970). Yet many varieties which are agronomically superior under United Kingdom conditions have been developed and are recommended (Anonymous, 1985b,e). In addition, breeders of these newer varieties have paid increasing attention to seed production potential (Evans and Davies, 1978; Davies, 1982). The problem of clover seed production for the United Kingdom is being approached from two angles. First, a consortium of commercial seed firms and the National Seed Development Organisation is seeking suitable areas abroad for seed multiplication, and seed is now being produced in Oregon and Idaho in the United States. Second, research has been stepped up to overcome the problem of low seed production under United Kingdom conditions. Hides et af.( 1984)have demonstrated that achieved seed production could be only 28% of the potential due to variation in flower ripeness at harvesting, low seed setting, and harvesting losses depending upon management. Haggar et d.(1963) achieved 25-75% potential in their trials. Vigorous stolon growth, which is encouraged by light penetration (Zaleski, 196I), is necessary during the seed harvest year since flowers arise principally from nodes developed that year (Thomas, 1981b). To encourage coincident stolon growth and floral development in a first-harvest-year sward, Roberts ( I 980) found that sowing clover in wide drills under a spring cereal crop in the establishment year was advantageous, while Hides et af. ( 1984)found thinning of an established clover sward beneficial; spring defoliation to remove the leaf canopy during floral developmentis also of benefit but timing depends on the variety and growing conditions. Haggar el al. ( 1963)noted that severedefoliation by continuous sheep grazing rather than rotational grazing or silage gave better clover seed production from the Kent Wild White variety, traditionally grown in perennial ryegrass/clover swards, because of better removal of the leaf canopy. Grazing these swards until late

38

J. FRAME AND P. NEWBOULD

May/early June to reduce grass competition gave better clover seed yields than earlier cessation of grazing (Evans and Knappet, 1985). Poor seed setting, which can result from reduced insect pollination and plant nectar release, can impair seed production (Hides et al., 1984); low temperatures and wet weather are adverse influences. Mechanical harvesting techniques need improvement (Anonymous, 1977),but an important factor is time of harvest, since clover has an extended flowering and ripening period and thus all the flowerheads do not ripen simultaneously.

V. NITROGEN FIXATION In addition to the high feed value and acceptability to stock of the herbage of white clover there is great interest in knowing how much N is fixed, what factors affect this, and how much of it is transferred to companion grasses. This knowledge is important so that agronomists can devise grazing strategies for pastures which will ensure optimum growth of herbage and N fixation, but also optimum intake and utilization by livestock.

A. AMOUNTS The literature is full of papers debating the precision of methods used to assess N fixation, and the subject is reviewed frequently. Three main methods, the difference method (Whitehead, 1970), acetylene reduction (Turner and Gibson, 1980), and isotopic dilution using I5N (Witty, 1983; Chalk, 1985), are used. Nutman ( 1971) published a summary table describing the amount of N fixed by forage legumes which included a top value of 682 kg N/ha per year from Sears et al. (1965) in New Zealand. The most recent ranges of figures are shown in Table V, from which it is seen that the top value is 350 kg N/ha per year. The wide ranges of values from all sources reflect large variations in the amount of white clover as well as the influence of a range of factors, such as Rhizobium strain effectiveness, amount of mineral N available,defoliation regime, and climatic influences. However, if a median value from all the sources shown in Table V is calculated, this would indicate fixation of 150 kg N/ha-year. Since only about 50%(range, 30- 80%)of fertilizer N added to pastures appears in the plants, the input of N equivalent to that fixed would require application of 300 kg N/ha.

-

39

AGRONOMY OF WHITE CLOVER Table V Amounts of Nitrogen Fixed by White Clover in Mixed Swards Country

Type of pasture

United Kingdom United Kingdom Netherlands New Zealand United States

Lowland Hill and upland Lowland various various

N fixed (kg/ha per yead

74-280

100- 150 65-200 85 - 265 50-350

Reference Cowling ( 1982) Newbould (1982) t’Mannetje (1985) Hoglund et al. (1979) Burton (1985)

B. FACTORS AFFECTING N FIXATION Assuming that effective rhizobia are present in sufficient numbers, the amount of N fixed depends primarily on photosynthates reaching the nodule, and thus on the amount of photosynthetically active leaf area in the sward. The amount of clover leaf is determined by the number of plants and/or branches with leaves that are present in full light in a sward. Climatic conditions, such as the availability of sunlight and the temperature of the leaves, affect the rate of photosynthesis as does the area of clover leaf which is affected by cutting or grazing. The conflict between keeping sufficient clover leaf for N fixation and yet providing sufficient feed for animals is apparent. There is much debate on the amount ofwhite clover that should be present in a grazed sward. Most animal nutritionists think an average of 30% or above of clover herbage over the season is a desirable target (Martin, 1960; Davies, 1974; Wright, 1975; Curll, 1982; Stewart, 1984). Attainment of this target would result in the amounts of fixed N shown in Table V. Low soil temperatures at the start and end of the growing season and midsummer drought, which all affect the appearance, growth, and functioning of leaves, also depress N fixation. In United Kingdom conditions, the peak nitrogen fixing activity occurs during the period of vigorous growth in late spring-early summer (Fig. 3; Marriott et al. 1984). Application of nitrogen reduces nodulation and N2fixation in pasture legumes, the response varying with species, cultivar, Rhizobium strain, form of N, amount of N, time and site of N application, age and size of host plant, and prevailing environmental conditions (Young, 1958; Sprent et al., 1983). For grass/white clover mixtures, applied N also enhances the growth of the grass component, and the resultant competition for light and nutrients may be more detrimental to the legume than to effects on nodule activity (Mulder et al., 1977). For perennial pasture legumes, mineral N application during

40

J. FRAME AND P. NEWBOULD

2

-50

I-

t c

-

-40 c

-

0

-30 L

3

f

-

-20

Temperaturec ---e 1 I

I

J

F

M

-.

c-c

* I

A

M

I

I

1

J

J

I

A

I

I

S

O

I

N

-

10 O

.L

0

"

D

FIG.3. Seasonal profile of (a) nitrogen fixing (acetylenereducing)activityand standing DM ofclover leaf and (b)soil moisture content and mean 100 mm soil temperature.(From Maniott and Rangeley, 1984.)

regrowth after defoliation can be particularly detrimental (Groat and Vance, 1981). Another effect of fertilizer N on fixation of N is that it reduces the proportion of white clover in the mixed sward (see Section VII).

C. NTRANSFER Atmospheric N fixed by white clover can be transferred to companion grasses via the grazing animal, via the atmosphere, or by death, decomposition, and mineralization of nodules, roots, and other plant parts (Haystead, 1983).

AGRONOMY OF WHITE CLOVER

41

I . Transfer via the Grazing Animal The consumption by livestock of clover shoots containing fixed N and the return of 80% of the N to the pasture as urine is the most rapid route for transfer, but it is also the route most subject to losses due to volatilization of ammonia (NH,), and possibly due to leaching too. Recent work by Ryden et al. ( 1984) and by Thomas et al. ( 1985) has examined aspects of this transfer mechanism.

2. Transfer via the Atmosphere The magnitude of transfer as atmospheric NH, is thought to be small (Denmead et al., 1976; Mamott and Rangeley, 1984), but recent work indicates it is possible and that care must be taken to allow for this route in both laboratory growth room and field-scale trials. 3. Transfer via Death, Decomposition, and Mineralization The route through decomposition is thought to be the most important for the buildup of long-term soil fertility, but until recently the amounts involved have been difficult to measure (Haystead and Marriott, 1978). Haystead and Marriott (1978) concluded that significant N transfer only occurred when the plants reached maturity or when the plant was subject to stress through shading or defoliation. They found significant transfer from clover to ryegrass ( 12 - 27% of grass N) only after the sward had been defoliated on four occasions during about 20 weeks of growth, and transfer was not detected using the I5N dilution technique until after the fourth harvest. The publication of more sophisticated techniques involvingthe direct labeling of legume foliage with 15Nis likely to lead to the accumulation of much more data on this important topic (Ledgard et al., 1985).

VI. QUALITY Increasing interest in the potential of white clover for animal production has been reflected in the number of recent reviews (Ulyatt, 1973; Thomson, 1979, 1982, 1984; Greenhalgh, 198 1). Thomson ( 1984) noted that in contrast to earlier studies which were conducted primarily with sheep, there is now more emphasis on cattle and dairy cows. A notable feature has been the comparative element with grass, principally perennial ryegrass.

42

J.

FRAME AND P. NEWBOULD

A. CHEMICAL COMPOSITION There is less information on the chemical composition of white clover than on grasses. A number of reviews on the general composition (Bland, 1968; Speddingand Diekmahns, 1972) and on mineral composition (Whitehead, 1966; Fleming, 1973; Jones and Moseley, 1984) are available for grassland forages including legumes. Essig ( 1985) recently discussed the beneficial and detrimental components of clovers, including white clover. It is well documented that the chemical composition of forage from grassland species can vary according to stage of growth, plant part sampled, season of year, soil pH, and soil nutrient status. Lime and fertilizer application can influence major element uptake more than the parent soil type, while trace element uptake is strongly influenced by soil pH (Mengel and Kirby, 1982). Mineral nutrition and its implications on animal health and production were reviewed recently (Reid and Horvath, 1980; Grace, 1983; Suttle et al., 1983). It is obviously important to be aware of potential mineral problems, especially where grassland forage is the major food for livestock production. Grazing strategy can have a major effect on chemical composition by controlling stage of growth of forage, by altering the botanical composition, particularly the content of white clover in mixed swards (see Section VIII,E), and by cycling of plant nutrients. The richness of protein, the high energy content, and high content of many minerals are major advantages of white clover forage. To illustrate typical chemical composition data from clover, ranges abstracted mainly from Spedding and Diekmahns (1972) are presented in Table VI. Most of the elements listed are necessary for plant nutrition, but some which are not (iodine, selenium) are essential for animal nutrition and are absorbed by the plant passively. There is little information on the content in clover of several other minor elements believed to be essential for animal nutrition. In relation to grasses, white clover is usually lower in cellulose, hemicellulose, water-soluble carbohydrates, lignin, sodium, manganese, and silicon contents. It is higher in water, pectin, total nitrogen compounds, organic acids, carotene, estrogeniccompounds, calcium, magnesium, iron, copper, cobalt, molybdenum, boron, and selenium. It is similar in lipids, phosphorus, potassium, sulfur, chlorine, zinc, and iodine. Because of a different chemical composition than grass, clover has been used in simulation and modeling work in animal nutrition (Black et al., 1976, 198 1). Many of the compositional differences between white clover and grasses, and indeed other forage legumes, are due to its stoloniferous habit of growth whereby the harvested portion is mainly youthful leaf and petiole, together with flowerheads and peduncles when flowering;stolon may be partially harvested particularly by sheep (Clark ef al., 1984a). In contrast, there is a decline in the leaf to stem ratio in the other foragesas they mature; this increasing maturity is accompa-

AGRONOMY OF WHITE CLOVER

43

Table VI Chemical Composition of White Clover" Constituent

Content range (% in DM)

Cellulose Hemicellulose Pectin Water-soluble carbohydrates Lignin Nitrogen compounds Lipids Organic acids Phosphorus Potassium Calcium Magnesium Sulfur Sodium Chlorine

(P) (K) (Ca)

(Mg)

(S) (Na) (Cl)

I .8 -26.6 3.6-12.0 3.5-7.7 5.2- 14.6 2.0-2.6 2.7-5.3 4.0-7.0 6.0-9.5 0.19-0.47 1.54- 3.80 1.20-2.31 0.15-0.29 0.24-0.36 0.05 -0.20 0.34- 1.56

(ppm in DM) Iron (Fe) Manganese (Mn) Zinc (Zn) Copper (CU) Cobalt (CO) (1) Iodine Molybdenum (Mo) Boron (B) Selenium (Se)

102-448 40-87 22 - 32 5.4-9.7 0.10-0.38 0.14-0.44 1.3-14.2 26 50 0.005-153

-

AFter Whitehead (1970); Spcdding and Diekmahns (1972); Osbourn (1980); Paynter (1985).

nied by an increase in structural carbohydrates and lignin and a decrease in nitrogen compounds and many minerals. The physical attributes of the chemical constituents in white clover may also be distinct from those in grasses (Van Soest, 1982).

B. INTAKEAND DIGESTIBILITY Thomson ( 1984) summarized the results from voluntary intake studies comparing white clover with perennial ryegrass. A range of forage types

J. FRAME A N D P. NEWBOULD

44

(fresh, dried, hay, silage) and animals (sheep, young cattle, lactating dairy cows) were used. Consistently, there was a higher voluntary intake of dry matter, 20%, of white clover compared with grass. The nutritive value of a forage to animals depends on the proportion of nutrients digested (apparent digestibility) and on the efficiency with which the digested nutrients are absorbed and utilized by the animals. The factors which affect the digestibility of temperate grassland specieswere reviewed by Raymond ( 1969). Digestibility of the organic matter (OMD) is a widely used expression in the United Kingdom. For many routine experimental purposes, it is usually derived by an in vitro digestion technique (Tilley and Terry, 1963; Alexander and McGowan, 1966). A more precise measure of energy value, the metabolizable energy (ME) of a forage, is used in animal nutrition work, and can be derived from the digestibility data by appropriate formulas (Osbourn, 1980). For most grassland species, digestibility is clearly related to stage of maturity. With advancing maturity, the ratio of stem to leaf increases, and the digestibility of the stem declines compared to that of the leaves (Harkess, 1963; Terry and Tilley, 1964; Aldrich and Dent, 1967; Harkess and Alexander, 1969). Unlike grasses and other legumes such as lucerne or red clover, white clover maintains a high digestibility even as it matures since there is a continual replacement of old leaves and petioles by new ones. This has two effects (Fig. 4); clover’s digestibility is maintained at a high level and the rate of decline is slow (Harkess, 1963, 1969; Davies et al., 1966; Harkess and Alexander, 1969). White clover regrowths during the season also maintain high digestibility relative to grass species because of clover’s habit of growth. Clearly the proportion ofwhite clover in a grass/clover sward can have a marked positive effect on the digestibility of the sward‘s forage. There has been little work carried out on the digestibility of clover plant fractions, but recently Gibb and Treacher (1983) found that the digestibilities of the flowers and flowering stems of white clover in a mixture of cvs. Blanca and Pronitro were low. It is not the purpose of this review to discuss animal production. Suffice it to say that many reviews have confirmed the superior feeding and nutritive value of white clover compared with grass for ruminant animal production (Ulyatt, 1973; Thomson, 1979, 1982, 1984; Greenhalgh, 1981; Stewart, 1984). The high voluntary intake characteristics,the high net supply of apparently absorbed amino acids per megajoule of metabolizable energy, and high mineral contents of white clover were major reasons given for its superiority.The main drawback ofwhite clover is its potential to cause bloat in grazing stock, especially cattle, but a number of preventative measures exist (Austin, 1982; Essig, 1985); cyanogenicglycosidesare not believed to be of importance in the grazing ruminant.

-

45

AGRONOMY OF WHITE CLOVER

0 .... . , ' o '......o.

\ \

\

...

'0

u,

1

2915

I

I

l2/6

I

1

26/6

I

I

10/7

0

I

I

I

24/7

C u t t i n g Date

FIG. 4. Changes in the percentage in vitro organic matter digestibility (96 OMD) with increasingmaturity. (0)Italian ryegrass;(0)white clover;(A) red clover. (From Harkess, 1969.)

VII. GRASS/WHlTE CLOVER DYNAMICS The establishment ofwhite clover plants in a mixed sward is relatively easy once the appropriate soil and microbial requirements have been met and climatic conditions are suitable. However, the attainment of a target proportion of white clover, and maintaining it over a period of time so that it provides a consistent and predictable contribution to the sward, remain very difficult tasks for the agronomist. Lack of such knowledge and the generally unpredictable behavior of white clover within and between years has not encouraged farmersto move from use of fertilizer N with grass swardsto sole use of mixed grass/clover swards (Frame and Newbould, 1984). The former are relatively easy to manage, and shortagesof herbage which are anticipated or arise within the growing season can often be overcome by use of fertilizer N.

46

J. FRAME AND P. NEWBOULD

l o90 o

t

a

Nil fertilizer N

nay

June

July

August

%?[ember

October

Growing season

FIG.5. Average daily growth rate of grass and white clover in grass/clover swards at two annual fertilizer N rates: (a) no fertilizer N, (b) 200 kg N/ha per year. Means of three clover varieties,Aberystwyth S 184, AberystwythS 100, and Kersey, over three harvest years and three Scottish National List centers during 1975- 1984; the companion grass was perennial ryegrass cv. Premo. (From M. Talbot, personal communication.)

Plants growing in mixtures compete above ground for space and light and below ground for space, water, and nutrients. When such mixtures are grazed, the type of animal, its treading and excretal patterns, and its preference or rejection of one or other partners can markedly influencethe balance of species (Section VII1,E). Man can influence the dynamics of grass/white clover swards by choice of grazing severity and pattern, and of lime and fertilizer (especiallynitrogen) additions. The situation is extremely complex and it is not surprising that there is no general agreement on the primary influences or on precise management guidelines for mixed swards containing clover. Competitive aspects of the grass/legume association were comprehensively reviewed by Haynes (1980) and the influence of nitrogen on

AGRONOMY OF WHITE CLOVER

47

100

90

80

-

b

-m

200 k g “/ha

per y e a r )

57c-60 n

m

2

I

m

r

j 5C’ m z

Z40 m

-

0 0

m

230>

a

2c-

1c-

d

I

I

nay

June

I July

1

I August

September

I October

Growing season

FIG.5b.

this by Vallis ( 1978) and Ennik ( 198 1). Aspects of the physiological basis of variation in production from grass/clover mixtures were described by Rhodes (198 I), and other factors affecting interactions between white clover and grasses were discussed by Snaydon and Baines ( 198 1). The ecology and management of white clover-based pastures in New Zealand were described by Brougham et al. (1978), in a discussion which covered many of the generally relevant aspects. There is general agreement that white clover is at a competitive disadvantage when grown with most pasture grasses. The latter are taller, have a greater mass of fine roots, and have less precise requirements of climate and soil nutrition for growth. Thus, unless management concentrateson providing a favorable environment for white clover, it is bound to be difficult to maintain a useful proportion of clover plants in a mixture with grasses. A further disadvantage of clover is that if plants die they are replaced by grasses or weeds but rarely by white clover (Wright, 1975).

48

J. FRAME AND P. NEWBOULD

Studies of plant demography in permanent pasture suggest that soil N levels and aggressiveness of grass species competing with white clover are dominant influences. Turkington and Harper ( 1979a)postulated a regeneration cycle for micrositesin the ecosystem which helps to explain the behavior of sown grass/clover swards. Initially, clover and perennial ryegrass coexist, mainly due to dissimilar growth cycles. As soil N builds up following inputs from clover N fixation, the grass increases its dominance; due to competition, clover declines and adopts dwarflike forms, and eventually disappears. The loss of fixed N inputs leads to the replacement of perennial ryegrass by short forms of Agrustis and other species, which then leaves the possibility that white clover can establish again if seeds are present at the site, so starting the cycle again. The growth cycles shown in Fig. 5 (M. Talbot, personal communication) were derived from the grass/clover swards used at three sites in Scotland during 1975- 1984 as standards in clover varietal evaluation for National Listing purposes (see Section IV,A). They are similar to those found in New Zealand (Brougham, 1959b; Haynes, 1980).Other examples of time course effects in competition between perennial ryegrass and white clover come from short-term box experimentsby Martin and Field (1984). They showed that perennial ryegrass was more competitivethan white clover throughout a 20-week experiment but its overall competitive ability increased with time; ryegrass roots dominated at first harvest, ryegrass roots and shoots dominated at second harvest, and ryegrass shoots dominated clover shoots at the third and fourth harvests. The applicationof fertilizerN increased the overall competitive ability of perennial ryegrass relative to white clover, due mainly to the increase of shoot competitive ability. The operation of long-term cycles of these types in experimental swards is often missed because experiments frequently last for the length of a research project (e.g., 3 years), so missing the clover decline phase. The occurrenceof unexpected “crashes” or declines in clover performance has been noted by Stewart et al. ( I970), Garwood and Tyson ( 1979),Davies ( 1982), and Stewart and Haycock (1984) (Fig. 6). Frame and Newbould (1984) gathered a collection of the causes given for clover inconsistency, and the wide extent and variability of the list (Table VII) illustrate the lack of precision of our knowledge. Support for the idea that compatible grasses and clovers can be found and must be used in mixtures comes from recent observations on coadaptability by Evans et al. (1983). The use of clover and grass selected from the same site of origin can result in higher annual production of total herbage (10.3 tons DM/ha) than if plants from different sites were used (7.4 tons DM/ha) without change in the percentage of clover which was 69% in their trial.

AGRONOMY OF WHITE CLOVER

1

2

3

4

5

6

49

8

7

Year

FIG.6. Example of variation and sudden “crashes” in white clover content (September data) in grazed grasslclover sward over an 8-year period, 1978- 1985. (From Stewart and Haycock, 1984; T. A. Stewart, personal communication.)

VIII. PRODUCTION AND MANAGEMENT There are many published production results from cutting experiments usually at research institutes and under conditions where many possible limiting factors are removed. The volume of data is much greater from grass/clover than clover swards. Traditionally, grass is included in seed mixtures with white clover since the production potential of the mixture is greater. Weed ingress is less of a problem in the mixed sward. The grass component also exploits the nitrogen fixed by the clover. Most data are derived from cutting regimes designed to simulate grazing, i.e., five to seven harvests per year. However, a limited amount of work has been done on the production from silage cutting systems or simulated grazing systems with silage cutting interposed at various times during the season. There is a relaTable VII

Major Causes of White Clover Inconsistencya Climate Soil Sward Animal Management

Radiation, temperature, rainfall Compaction, wet vs dry,acidity, nutrients Grass-toclover balance, clover longevity, pests and diseases, weeds Treading, excreta, selectiveness, species of animal Maintenance lime and fertilizer, fertilizer nitrogen, method of utilization, system of production ~

After Frame and Newbould ( 1984).

~~

50

J. FRAME AND P. NEWBOULD

tive paucity of data from grazing experiments and also of the performance of swards in farm practice. A. WHITECLOVERMONOCULTURES The highest recorded production from an imgated white clover monoculture in the United Kingdom was 11.80 metric tons DM/ha, but it included a grass weed component (Spedding and Diekmahns, 1972). On a white clover sward kept pure by carbetamide application in late winter, 10.25 tons DM/ha (100%white clover) was obtained without irrigation (Reid, 1983a). Under differing cutting regimes, Spedding and Diekmahns (1 972) cited ranges of 3.90 to 8.60 tons DM for unirrigated swards and 6.1 1 to 1 1.80 tons DM/ha for imgated swards while Davies (1969) cited 8.03 to 9.48 tons DM/ha for unirrigated swards. Suckling ( 1960)recorded 10.55 tons DM/ha from unirrigated swards in New Zealand, which is close to the 10 tons/ha forecast by Smetham (1973). From specific silage regimes, production levels of6.76 - 8.06 tons DM/ha with 75 - 78% white clover were reported by Castle et al. ( 1983)and Frame (1 985a), while under a range of cutting systems, i.e., 3- to 5-week intervals, D. Reid (personal communication) obtained 8-9 tons DM/ha. White clover swards are not responsive to fertilizer N application (Cowling, 196la; Armitage and Templeman, 1964). Recently, Hughes (1981) and Reid (1983a), using levels of N up to 750- 1000 kg/ha per year, obtained only small responses to N from pure white clover swards: 8.1 3 8.56 tons DM/ha with no N and means of 9.13 - 9.23 tons DM/ha over all the N application rates. B. GRASS/WHITE CLOVERMIXTURES

It is pertinent to examine production data from the 11 centers in the United Kingdom involved in evaluating white clover varieties for National Listing purposes (see Section IV,A). A total of 460 sets of data for perennial ryegrass cv. Premo/white clover swards exist for harvest years 1979- 1983 (Table VIII). The clover variety standards in the varietal evaluation work, mainly Aberystwyth S 184, Aberystwyth S 100, Kersey, and Milkanova, were sown annually during the period and herbage production measured for two successive harvest years (second and third after sowing). The highest recorded value in the United Kingdom of 15.53 tons DM/ha (with no applied N) obtained at Cambridge is noteworthy, although it is still only three-quarters of the theoretical potential (Frame and Newbould, 1984).The production ranges cited in Table VIII for both rates of fertilizer N

51

AGRONOMY OF WHITE CLOVER Table VIII Range of Annual DM Production and Clover Content of Grass/ Clover Swards from United Kingdom National List Trials, 1975-1983"

DM (tons/ha) Fertilizer N (kg/ha per year)

Total herbage

White clover

White clover

(96)

Highest Lowest Mean

0 0 0

15.53 2.03 8.31

12.12 0.49 4.16

24 50

Highest Lowest Mean

200 200 200

19.94 3.13 9.8 I

2.19 0.75 2.46

11 21 25

78

application (0 and 200 kg/ha per year) encompass achieved levels from many other types of cutting experiment involving grass/clover swards (Reid, 1970, 1972, 1983a; Spedding and Diekmahns, 1972; Morrison, 1981;Morrison et al., 1983;Frame, 1982a, 1985a;Frame and Newbould, 1984).However, most herbage production levelswithout applied N tend to be within the 6 - 10 tons DM/ha range. Very low levels have invariably been the result of pests and/or diseases (Aldrich, 1970a; Momson, 1981; Cook et al., 1984). Over nine sites scattered throughout New Zealand, and without fertilizer N, annual total herbage DM ranged from 6.7 1 to 14.92 tons/ha (Hoglund et al., 1979); the mean DM production was 8.40 tons/ha of which clover contributed 3.13 tons/ha (37%). Vartha ( 1972)cited a DM range of 10.031 1.94 tons/ha. From small paddock evaluations under grazing, Brougham (1977) listed highest production levels achieved over a range of environments at research stations as 12.0 tons DM/ha for hillsides, 16.2 tons/ha for nonirrigated dryland, and 22.8 tons/ha for a temperate site. The levels were about a third higher than the amounts of herbage utilized in farming system studies. Sward production, and indeed the clover component, is generally enhanced by infrequent defoliation compared with frequent defoliation and by close defoliation relative to lax (see Section VII1,D). Hill and upland areas often provide a harsh, variable, climatic environment for white clover growth (Munro and Davies, 1973; Francis, 1978; Newbould and Floate, 1979). In the United Kingdom the total herbage production of sown grass/clover swards rarely exceeds 5 -6 tons DM/ha in these situations and is often lower (Newbould, 1974, 1975, 1982).At a range

52

J. FRAME AND P. NEWBOULD

of Scottish sites, DM production levels from grass/clover swards given no applied N were 2.52-4.80 tons/ha (Burnham et al., 1970; Sandford, 1979a,b; Tiley, 198 1a; Newbould, 1982; Tiley and Frame, 1984). The establishment in the hills and uplands of grass/white clover swards is a desideratum since their production usually exceeds that of the indigenous swards (Frame et al., 1985) and the herbage is superior in feeding value (Thomson, 1984). The imposition of controlled grazing on indigenous grassy swards, allied to the use of sown grass/clover swards at key times in the grazing animal’s nutritional requirement cycle, led to the strategy of the “two-pasture” system of hill sheep farming (Eadie, 1970; Eadie et al., 1979; Armstrong et al., 1986). There is a lack of data from farm grass/clover swards, although Pflimlin ( 1984) reported that the use of grass/white clover swards on dairy farms in Brittany, France, was a viable alternative to high N use on grass swards. The variability of production on farm swards will be greater than that from experimental swards where more precise management control is exercised. Surveys have shown that the clover content in United Kingdom grassland is very low (Younie and Black, 1979; Forbes et al., 1980; Green, 1982; McAdam, 1983a,b; Swift et al., 1983), so total herbage production from these swards will be very low unless fertilizer N application rates are adequate. For example, in surveying450 farms, Forbes et al. ( 1980) recorded a mean of 2% clover ground cover on dairy farms; only 10% of the farms had enough to make an impact on production, compared with 25% on beef fatteningfarms and 30% on beef breeding farms. For these farm types in order, 50,30, and 25% of all swards had no sown legumes remaining, regardlessofage of sward. Corresponding mean fertilizer N rates applied per year were 154,65, and 42 kg/ha. Thus, either a vigorous clover content was not an objective, even on the beef farms with low N use, or else it was a failed objective, even though Doyle et al. ( 1984) have shown that a good economiccase exists for the use of grass/clover swards in sheep and beef enterprises with low fertilizer N usage. C. EFFECTOF FERTILIZER NITROGEN 1. Repetitive Application

Nitrogen is the main nutrient affecting herbage production from grassland. Accordingly, the production response of grass/clover swards to fertilizer N applied regularly throughout the season has been a subject of frequent study. Many response data (in kg DM/kg N applied) have accumulated. Variation in response is considerable from year to year, and from site to site.

53

AGRONOMY OF WHITE CLOVER

Chestnutt and Lowe ( 1970),summarizingthe responses obtained mainly in cutting experiments by experimenters, cited a range of 3.7 to 17.4 (mean, 8.8) from various annual N application rates up to 390 kg/ha; in six experiments where grass swards were included, the grass response range was 22.5 57.6 (mean, 32.4) for annual N rates up to 350 kg/ha. Perusal of more recent work (Bastiman, 1969; Reid, 1970, 1972, 1983a; Frame, 1973, 1982c; Orr and Laidlaw, 1978; Hood, 1982; Wilman and Asiegbu, 1982a; Boyd and Frame, 1983; Momson et al., 1983; McEwen and Johnston, 1985; Wilman and Hollington, 1985)together with the body of results from UK National List trials (see Section VIII,B) over the annual N application rates, 0 to 400 kg/ha, shows a somewhat wider response range, -6 to 20; however, the mean was - 8. The occasional negative responses occurred at low or moderate N rates (Cowling, 1961b; Frame, 1973; McEwen and Johnston, 1985). The size of response is related to the clover content of the sward and increases as the clover content decreases. The response also increases as cutting frequencydecreases. When cutting frequency is varied, the decline in response to N at higher N rates is less marked with frequent than infrequent harvesting (Holliday and Wilman, 1965; Cowling, 1966a; Frame, 1973). The effects of annual fertilizer N rates up to 900 kg/ha were examined on grass/clover and grass swards (Reid, 1970, 1972, 1983a). Production from grass/clover swards was superior to that from grass swards at N rates up to 300 to 350 kg/ha but not significantly different from grass at the higher N rates. Dobson and Beaty (1 977), using fewer N rates, obtained comparable production from grass/clover and grass fertilized with 336 kg N/ha per year in Georgia, United States. In Reid’s work the proportion of clover-fixed N transferred to the grass in the grass/clover sward decreased as N rate increased, a finding in agreement with Hemott and Wells (1 960), Reid and Castle (1 965), and Shaw et al. ( 1966). The use of large-leaved white clover cv. Blanca (Reid, 1983a)compared with a medium-leaved clover cv. Aberystwyth S 100 (Reid, 1970) resulted in better white clover performance, but in more recent work (D. Reid, personal communication), there was little difference in production between medium- and large-leaved clovers. In Reid’s swards, the amount of fertilizer N required annually on grass swards to produce the same total herbage DM as from the grass/clover without added N (the so-called fertilizer N equivalent of the gross effect of clover on production) was 165kg/ha for the grass/S 100sward and 265 kg/ha for the grass/Blanca sward when periods of 3 harvest years were compared. The grass/S 100 experiment was continued for a further 3 years and its nitrogen equivalent over the 6 years then averaged 140 kg/ha (Reid, 1972). In other recent work from 2 1 sites over 4 years (Morrison, 1981 ), fertilizerN equivalents of 180 and 200 kg/ha were obtained for perennial ryegrass/S 100

-

54

J. FRAME AND P. NEWBOULD

and ryegrass/Blanca swards, respectively (see Fig. 7). However, data for the United Kingdom summarized in Anonymous (1983d) suggest a wider N equivalent range, namely, experimental means of 124 - 275 kg/ha; the range of mean annual values was 28 - 302 kg N/ha. The decline in clover contribution of mixed swardswith increasing rates of fertilizer N is well documented. In Table IX, mean data from Frame ( 1985a), who used white clover varieties of differing leaf sizes, illustrate the effects. There has been an increase in the use of animal slurry (dilute mixture of urine plus dung) to fertilizeswardsin regionswhere winter housing of stock is practiced. Considerable savings in purchased fertilizers can be made if a rational program of manuring with slurry and fertilizers is instituted. However, there has not been a concomitant increase in research on the effects of slurry on swards. In comparison with fertilizer N, slurry and dilute urine application at equivalent N rates resulted in a greater content of white clover

-

12

-

S 23/Blanca S 23/S 100 c--..S 23

0 .

0

I

100

I

200

I

300

1

400

I

500

I

600

N (kg/ha per year) FIG.7. Mean total herbage production from grass(perennial ryegrass cv. Aberystwyth S 23) and grass (cv. S 23)/white clover (cv. Blanca or Aberystwyth S 100) swards; 2 1 sites X 4 years (Morrison, 198 I). Fertilizer

55

AGRONOMY OF WHITE CLOVER

Table IX Effect of Fertilizer Nitrogen Application Rates on White Clover Performance in Perennial Ryegmss/Clover Swards’

DM (tons/ha per year) Fertilizer N (kg/ha per year)

Total herbage

White clover

0 120 240 360

7.83 8.7 I 9.98 11.70

4.14 2.43 I .07 0.5 I

White clover (%) 53 28 I1 4

a Three-year means, two cutting heights, four white clover varieties. Afier Frame (1985a).

in grass/clover swards (Castle and Drysdale, 1962;Herriott and Wells, 1962; Drysdale, 1965).

2. Strategic Nitrogen Use The poor growth of white clover at low temperatures (springand autumn in the United Kingdom) is well documented. Thus, the use of fertilizer N to improve the grass/clover sward’s herbage production at these times has been advocated. Following spring application of N, white clover content and production were reduced, especially in midseason, and reductions were more marked as the rate of N application was increased (Cowling, 1966a; Heddle, 1966; Denehy and Morrison, 1979; Laidlaw, 1980, 1984; Laissus, 1983; Morrison et al., 1983; Frame, 1985a). Over differing rates of N application, but mainly in the range 0- 100 kg/ha, herbage DM responses vaned from 3 to 30 kg per kg N applied; responses were generally best at the low to moderate N rates (30 - 60 kg/ha) and where defoliation intervals were infrequent. Comparing first-harvest (May) responses at 15 sites from spring N rates of 0 and 67 kg/ha, Morrison et al. (1 983) obtained a mean response of 17 (range 6 - 35) kg DM/kg N. These trials were all conducted under cutting and white clover made up 35 - 65% of the total herbage in the treatments without N. Thus, even with reductions in clover caused by fertilizer N, clover contribution still remained at substantial levels. Laidlaw (1980) concluded that moderate spring N (up to 60 kg/ha) did not seriously reduce clover persistence, and later (Laidlaw, 1984) developed a method for predicting the effect of spring N on clover content. He found that medium-leaved and large-leaved

56

J. FRAME AND P. NEWBOULD

clover types responded similarly to spring N, but Aldrich ( 1970b)and Morrison et al. (1983) has suggested that large-leaved clovers are suppressed less than small- and medium-leaved types. There is a paucity ofwork on response to spring N ofgrass/clover swards in which white clover content is low, or on grazed swards (Brockman and Wolton, 1963; Wolton and Brockman, 1970) in which clover is under greater competitive pressure than in cut swards (see Section VII1,E). Frame (1985a) examined the effect of spring N only, autumn N only, or spring N and autumn N. He found that total herbage DM was increased by N in all systems, but white clover content and production were reduced. At equivalent N rates (25 - 75 kg/ha), autumn N suppressed clover less than spring N; similarly, with spring N plus autumn N combinations (up to 125 kg/ha per year) clover was most suppressed when a high proportion of N was applied in the spring. Annual herbage responses (in kg DM/kg N) were 1 1.5 for spring N increments, 7.2 for autumn N, 5.7 for spring N plus autumn N increments, and 7.1 over all N treatments. Armitage and Templeman ( 1964) obtained a herbage response of 7 kg DM/kg N applied from spring plus autumn N applications. Purvis and Younger (1984) noted that clover was able to make a greater contribution to total production when fertilizer N was applied in midseason compared to early or late season application. Clearly the value of increased herbage production must be weighed against the depressive effects of fertilizer N on clover performance. Clover is likely to persist if low to moderate N rates are used strategically and provided a grass/clover sward with a high clover content is used. However, it must be realized that all applied N is boosting the soil N pool, and must therefore be helping to tip the balance against clover in the successional cycle of the grass/clover sward (see Section VII). D. EFFECTOF CUTTINGDEFOLIATION 1. Frequency of Cutting

Many cutting studies have shown that total herbage production from grass/white clover swardsgenerally increases as the interval between defoliations is lengthened. This finding has been obtained as the fixed rest interval between defoliations was lengthened, or as the sward canopy height at cutting was increased. With annual N levels of 0-400 kg/ha, white clover production was increased, especially in early season, as the interval between defoliations lengthened (3- to 6-week intervals, or from the “simulated grazing” to the “silage” stage) but the proportion of white clover in the total herbage decreased (Holliday and Wilman, 1965; Frame, 1973; Orr and

AGRONOMY OF WHITE CLOVER

57

Laidlaw, 1978) or was little affected (Burger et al.,1958; Reid, 1959, 1962; Bland, 1967; Wolton et al., 1970; Brereton and Carton, 1985). However, Hollidayand Wilman ( 1965)noted that increasingthe defoliation interval to 14 weeks reduced both the amount and proportion of white clover in the total herbage. Using differingleaf-size clover types in association with perennial ryegrass, Wilman and Asiegbu ( 1982a)obtained enhanced white clover production with defoliation intervals of 3 to 12 weeks but the proportion of white clover was not markedly affected; their results supported the view of Spedding and Diekmahns ( 1972) that medium- to large-leaved varieties respond better to less frequent defoliation than smaller-leaved varieties. Tesar and Ahlgren (1950) and Chamblee et al. (1983) noted that Ladino clover benefited from infrequent compared with frequent cutting. The above results do not support the former, typically held view that frequent defoliation tends to offset the adverse effect of applied N on white clover by reducing the effects of shading by the grass (Chestnutt and Lowe, 1970; Whitehead, 1970). Increasing the defoliation interval can increase petiole length, leaf weight, stolon length, and stolon diameter (Wilman and Asiegbu, 1982b). Petiole elongation has also been noted by Wolton et al. ( 1970). Dennis and Woledge ( 1983)and Dennis et al. ( 1984) have observed that white clover can avoid the damaging effect of shade since petiole extension raises the developing lamina into bright light before its photosynthetic capacity is determined. Conversely to infrequent defoliation, severe and repeated defoliation, as with continuous and heavy sheep stocking, can result in reduced size of aboveground leaflets, petioles, and stolons (Briseiio de la Hoz and Wilman, 1981; Curll, 1982). It has been noted that relaxation of intense defoliation, for example, a silage cut in a grazing system (Wolton et al., 1970; Wilman and Asiegbu, 1982a;Curll and Wilkins, 1985) or a switch from high to low stockingdensity (Curll, 1982)or a change from continuous sheep stockingto rotational grazing (Marsh and Laidlaw, 1978; Laidlaw and McBratney, 1983; Newton et al., 1984), can result in increased aboveground parts of white clover and therefore an increase in vigor and production. Thus, while white clover is essentially a speciesfor grazing, it is more suited for conservation than previously thought. White clover has potential for greater persistence than the recognized “conservation” legumes, red clover and alfalfa. On account of its mode of growth (initiation of new petioles/ leaves), its primary growth and its regrowths have a higher level of digestibility than the “stemmier” conservation legumes (Harkess, 1963;Harkess and Alexander, 1969; Frame et al., 1983). Its disadvantage of a shorter growing season relative to grass is of less significance in a conservation context. If grass/white clover is to compete against grass plus fertilizer N systems in practice, it must be able to tolerate flexible grazing and cutting management.

58

J. FRAME AND P. NEWBOULD

In an era when rates of application of fertilizer N to grassland were much lower than now, Green and Cowling (1961) had suggested that the most effective exploitation of the N-fixing ability of white clover might be achieved by cut-forage feeding. Shaw et al. (1966) also concluded that the grass/white clover sward had considerable potential for cut-forage feeding and that there was little justification for the use of fertilizer N on grass/clover swards for cutting. Forage drying systems were suggested as a means of utilization by Lowe (1970). Pure-sown white clover gave satisfactory production and quality in specific silage cutting systems (Spedding and Diekmahns, 1972; Frame, 1982a, 1985a;Boyd and Frame, 1983;Castle and Watson, 1983; Frame et al., 1983) and with infrequent cutting regimes (Hughes, 1981; Reid, 1983a,b). Ingress of unsown weed species is a problem with pure-sown white clover swards, but weed grasses can be selectively suppressed by chemicals such as carbetamide (Wasmuth and Miles, 1972; Soper and Hutchinson, 1974; Reid, 1983a), propyzamide (Haggar and Bastion, 1980; Standell and Haggar, 1982), and paraquat (Blood, 1962). The potential ofgrass/white clover swards cut for silage has been shown in specific silage systems (Momson, 1981; Frame, 1982a, 1985a; Boyd and Frame, 1983; Frame et al., 1983) by the interposition of silage or hay into grazing or simulated grazing systems (Wolton et al., 1970; Chamblee et al., 1983; Curl1 and Wilkins, 1985; Frame, 1985a) and in fixed defoliation frequency work where infrequent cutting was among the treatments (Wolton et d.,1970;Frame, 1973;Orr and Laidlaw, 1978; Wilman and Asiegbu, 1982a). To ensure sustained white clover performance and adequate proportions in the harvested material, minimal fertilizer N should be applied (see Section VII1,C).

2. Closeness of Cutting Past work on grass/clover and grass swards generally showed that close cutting(- 25 - 50 mm from ground level) increased total herbage production considerably (up to 44%) compared with lax cutting (- 60 - 100 mm), provided adequate recovery periods were allowed between defoliations (Burger et al., 1958; Reid, 1959, 1962; Hunt and Wagner, 1963; Appadurai and Holmes, 1964; Frame, 1966a-c; Bryant and Blaser, 1968; Dobson et al., 1976).White clover production and proportion were either little affected by closeness or else were enhanced by close cutting. More recently, Boyd and Frame (1983) and Frame (1985a) obtained enhanced total herbage and clover performance from close (40 mm) relative to lax (80 mm) cutting from perennial ryegrass/white clover swards using white clover varieties with

AGRONOMY OF WHITE CLOVER

59

varying leaf sizes: the beneficial effect of close cutting on clover was most marked at high rates of applied N (240 and 360 kg/ha-year) and in later harvest years. Likewise, Brereton and Carton (1985) obtained improved total and clover production from a 50-mm cutting height compared with 75 mm. The stimulus to total herbage production from close cutting has been attributed largely to more efficient utilization, since a high proportion of a sward’s production is in the lower layers (Anslow, 1967). Close defoliation will also stimulate grass tillering and utilization of regrowth by removing floweringgrass shoots and by permitting better light conditions at the base of the sward. The stimulus to the clover production will include better utilization, while it may also benefit from reduced grass competitiveness. Better light conditions at the sward base will also encourage the number of clover growing points and promotion of photosynthetically efficient leaves (Woledge and Dennis, 1982).

E. EFFECTOF GRAZING The effects of grazing animals on pastures can be both harmful and beneficial. In addition to the defoliation, animals selectively graze, trample, and deposit dung and urine and their actions can distribute seeds (Watkin and Clements, 1978). The latter process, plus the marked heterogeneity arising from excretal return, helps to maintain species diversity in natural pastures but can make the management of sown grass/white clover pastures extremely difficult to regulate. Moreover, the species of animal can interact with one or several of the above processes, so adding to the complexity of studying the sward/animal interface. Few studies have tried to investigate the relative magnitude of the individual grazing effects on the proportion of white clover in a sward and on total herbage production. This follows because the effects occur simultaneously and are interdependent, and at any time one may be dominant; moreover, there are great practical difficulties in carrying out the type of research required under actual grazing conditions. Attempts to simulate some of the separate effects in cutting trials have not always been very successful. Many workers have shown that the proportion of white clover in a mixed sward is lowered by sheep grazing compared to cutting, especially when fertilizer N is applied (Table X).Cattle grazing depresses clover less than sheep grazing (Boswell, 1976; Briseiio de la Hoz and Wilman, I98 1), but more than cutting (Taylor et al., 1960; Bryant and Blaser, 1968;Garwood et al., 1982). In the assessment of existing clover varieties and potential varieties under

J. FRAME AND P. NEWBOULD

60

Table X Effect of Defoliation Method and Level of Nitrogen Fertilizer on Mean S e a ~ o White ~l Clover Content in Crass/White Clover Swards ~~

Clover content (%) ~~

N level

(kg N/ha per year)

Clover variety

0 I20

s 100

120 I20

S 100, Huia

0 68 I38 204

s 100

0 150 260 - 300

Huia, Blanca

Cutting

Sheep grazing

38 21

2I 5

24 11-19”

7 7

45 34 22 12

35 18

48 29 14

40 19 6

Reference Frame ( 1966a) Wolton et 01. (1970) Shaw et al. (1966)

LO 5

MacKenzie and Daly (1982)

Silage cut interposed once at various times in grazing regime.

a high fertilizer N regime, Evans (1 979) noted a mean 48% reduction of clover production in grass/clover swards with rotational sheep grazing compared with cutting. With a similar technique, but with no applied N, Evans and Williams (1982) found that clover growth rate in a grass/clover sward was reduced under grazing to the extent of a mean 50%reduction in annual clover DM. Since grass and clover respond differentially to defoliation, manipulation of grazing practices can effect botanical change markedly. 1. Treading

Edmond ( 1964)rated white clover as more susceptibleto treading damage than perennial or hybrid ryegrass but more resistant than timothy or cocksfoot. However, he also noted that clover was more tolerant of treading when grown in mixtures with grass than when grown in monoculture. Treading can directly damage plant parts, particularly under repeated treading in wet conditionswhich leads to poaching of the sward. Clover (and grass) can also be adversely affected by treading should it lead to soil compaction, soil puddling, lack of water infiltration, and reduced soil aeration (Brown and Evans, 1973). Curl1 (1980) assessed damage to marked plants in mixed ryegrass/white clover swards and recorded a 20% greater frequency of tread-

AGRONOMY OF WHITE CLOVER

61

ing on clover compared to grass. However, he also observed that defoliation occurred three times more frequently than treading. Curll and Wilkins (1983a,b), working with sheep set stocked at 25 and 50 wethers/ha on ryegrass/white clover swards, attempted to separate the effects of defoliation from defoliation and treading by use of “graze-through” cages. They observed that treading by sheep at 25 wethers/ha reduced the clover content of the sward only at the end of the grazing season, but the higher stocking rate had a greater depressive effect on clover. Curll (1982) concluded that the sensitivity of grass/clover pastures to treading by sheep was less than assessed for pastures by the short-term mob-stocked nongrazing methods used by Edmond (1964). Little information on the effects of treading by cattle on white clover has been reported. However, Monteath et al. (1 977) found that the top 7.6 cm of soil was more compacted under cattle than under sheep grazing; such treading effects may also indirectly affect the growth and persistence of white clover via effects on roots (F. X.de Montard, personal communication, 1985).

2. Selective Grazing Selectivity of grazing depends upon stocking density in relation to available herbage mass and sward growth rate. Sward species respond differentially to defoliation and have differing seasonal growth patterns. Type of animal influences selection and amount of utilization. Grazing management can thus effect botanical change by manipulation of frequency, intensity, and timing of grazing, and by changing the species of animal. White clover can survive selection during grazing by its plasticity, since it can develop a prostrate, small-leaved, short-petioled habit of growth (Curll, 1982). Animal species vary in their grazing behavior. Sheep graze more fastidiously than cattle and can readily select individual leaves and stems. Cattle tend to prehend bunches of foliage and will graze longer material. Sheep are said to graze white clover selectively in a grass/clover sward unless the stocking density is high enough to preclude selectiveness (e.g., Laidlaw and McBratney, 1983). Both Milne et al. ( 1982) and Curll et al. (1985) found that the proportion of clover in the diet consumed from a mixed grass/clover sward was higher than that in the total herbage on offer. However, Milne et al. ( 1982) and Woledge et al. (1984) noted that a higher proportion of clover than grass was found in the upper zones ofthe sward, the zone first grazed by sheep. Thus, a high proportion of clover in the diet may reflect the fact that grazing takes place mainly in the surface layers of the sward rather than active selection. If the depressive effect of sheep grazing on clover is not due

62

J. FRAME AND P. NEWBOULD

to selective grazing or clover’s accessibility, it follows that treading and pattern of excretal return must be implicated. There is much less information for cattle grazing than for sheep grazing. Briseiio de la Hoz and Wilman (198 1) studied the effects on clover of sheep grazing, cattle grazing, and cutting in a grass/clover sward by defoliation involving set stocking, frequent grazing, or cutting techniques aimed at keeping sward heights 40,60, or 80 mm above ground level. Sheep grazed clover preferentially and, relative to cattle grazing or cutting, the plant responded by reducing the amount of stolon, length of internodes, petioles, and leaflets; also stolons were thinner and closer to the ground. Increasing seventy of defoliation from 80 to 40 mm also reduced clover dimensions. The effect of cattle grazing on clover was similar to cutting. Following a respite from severe sheep grazing, the sizes of aboveground parts of white clover recovered to dimensions similar to those of clover which was cattlegrazed or cut; considerable phenotypic plasticity was thus exhibited. In farmlet studies in New Zealand (Monteath et al., 1977) clover comprised 13% of the sward under rotational sheep grazing and 16% under rotational beef cattle grazing. More recently, Morrison et al. (1986) compared the effects of continuous stocking by cattle over 2 years on swards maintained at 40,60, and 80 mm high. Clover survival was good in all treatments and there were only small effects on clover content. Purvis and Younger (1 984) obtained better clover performance under continuous stocking with young cattle than under monthly cutting over a range of fertilizer N rates from 0 to 300 kg/ha per year. Very few direct comparisons of the effects of sheep and cattle grazing have been carried out, but Calder ( 1970) noted that sheep grazed more severely than cattle and defoliated leaf portions of plants more than cattle. Sheep pastures produce more herbage dry matter than cattle pastures (Monteath et al., 1977). A recent study by Arosteguy et al. ( 1982)provided some explanation. Sheep and cattle grazed together gave tiller populations, rates of herbage growth, and net production values closer to swards grazed by sheep only than cattle only. Curl1( 1982)in a review of sheep grazing stated that changes in the grass and clover contents in response to grazing management relate to variation in the relative importance ofthe grazing processes and the ability of the clover or grass components to adapt their growth habit to survive these processes. The plasticity ofwhite clover grown in competition with perennial ryegrass has been demonstrated by Hill (1977) who found the expression of genotype, e g , petiole length, depended upon N source, the nature of the grass competitor, and, presumably, defoliation. Evidence has accumulated that continuous sheep stocking militates against white clover production and persistency in mixed swards compared

AGRONOMY OF WHITE CLOVER

63

with rotational grazing (Calder, 1970; Raguse er af., 1971; Laidlaw and McBratney, 1983; Newton et af.,1984; Curll et af., 1985). Removal of clover photosynthetic tissue is a factor at high stocking rates (Korte and Parsons, 1984) while selective defoliation (Leigh and Holgate, 1978;Stevens, 1978)and shading of stolon growing points by grass (Woledge and Dennis, 1982) may be factors at low stocking rates. Under rotational grazing, clover performance was better as the interval between grazings increased (Brock, 1971, 1974; Lancashire, 1974; Widdup and Turner, 1983), a finding which equates with cutting work (see Section VII1,D). Incorporating a rest interval from grazing and then taking a silage cut has been found to stimulate the clover component of swards continuously stocked or rotationally grazed by sheep (Wolton et al., 1970; Curll and Wilkins, 1985). In New Zealand, Hay and Baxter (1986) found that continuous stocking in spring increased the number of growing points compared with rotational grazing but the growth potential of those growing was realized better later in the season by rotational grazing rather than continuous stocking. Clearly, it is emerging that flexibility of grazing and cutting management, with the aim always offavoring the needs ofthe clover component, is the key to satisfactory clover performance in mixed swards. It has been shown recently (Batten, 1979; Clark et al., 1984b) that goats avoid white clover shoots when grazing and, ifgiven no alternative, prefer to eat white clover roots rather than shoots. Attempts to utilize this aversive grazing behavior as a way of removing the tall grasses and weeds from degraded, potentially clover-rich swards have been reported (Grant er al., 1984). It is worth noting that migrant wild geese preferentially select white clover (Owen, 1973;Owen er al., 1977).Preferential grazing, stolon removal, and scratching were given as possible reasons for white clover decline under poultry grazing (Cowlishaw, 1960).

3. Return of Excreta Excretal nutrient return vanes according to herbage intake and its composition. Excretal N operates against white clover in grass/clover swards by stimulating grass growth, thus increasing its competitiveness. Frame ( 1966a, 1976b) recorded increases in herbage production from rotational sheep grazing relative to cutting with equivalent defoliation regimes. The result was mainly attributed to recycled excreta N. White clover content and production were markedly reduced under grazing because of the boost to grass by excretal N and, to a lesser extent, because of the depressive effect of treading and selective defoliation on white clover. The results accord with

64

J. FRAME AND P. NEWBOULD

Shaw et al. ( 1966), Wolton et al. (1970), and MacKenzie and Daly (1 982) (see Table X). Laidlaw and McBratney ( 1 983) noted a reduction in clover leaf size from continuous high sheep stocking, but concluded that the effect could be partially alleviated by rotational grazing which would improve the ability of clover to compete with increased grass growth resulting from excretal N. Excreta can also influence the botanical composition of pasture by altering nutrient concentration in the soil, by “burning” plants, and by influencing grazing patterns. Urine and feces together and urine alone increase the proportion of grass in grass/clover swards (Ball ef al., 1979), while feces may give a boost to white clover (Weeda, 1967). The K in urine may also stimulate white clover (Scott, 1976). While the excretal return pattern from sheep grazing cannot be described as uniform, it is more evenly distributed than from cattle grazing (Monteath et al., 1977). Reduction in clover growth by excreta may not be simply due to N increasing the competitive ability ofgrass for light, moisture, and nutrients, but it may reflect the greater sensitivity of clover to urine bum, to the presence of free NH3 (Curll, 1982) and the temporarily increased pH of urine-affected soil (Thomas et al., 1985). To summarize, it appears that sheep grazing militates against clover whether by preferential grazing or by the net effect of trampling and excretal N, and this can lead to a reduction in the clover content of a sward. Cattle grazing is more equivalent to cutting than to sheep grazing. Clover is more susceptible to treading than grass. The return of excreta encourages grass growth which can cause suppression of clover. The composition of mixed grass/clover swards is sensitive to grazing management (Watkin and Clements, 1978) and to the ability of the particular grass or clover varieties to adapt their growth habits. There is a general consensus that rotational grazing encourages clover performance more than continuous stocking; it relieves clover from selective defoliation and allows the plant to elongate petioles and place leaves in the top of the canopy (Betts et al., 1978; Curll, 1982; Frame and Newbould, 1984; Newton et al., 1985).

F. RECOVERY MANAGEMENT Recent surveys of pastures in the United Kingdom (Forbes et al., 1980; Swift et al., 1983; McAdam, 1983a,b) confirm that, though sown originally with white clover, many now lack sufficient white clover to contribute significantly to herbage quality (see Section VI) or to fix N. Full reseeding is possible but expensive, and agronomists are often asked how the proportion of white clover can be restored by less expensive treatments. A range of methods including soil amelioration (lime and nutrients), change of defolia-

AGRONOMY OF WHITE CLOVER

65

tion practice, manipulation with herbicides, and slot seeding or oversowing is available.

I . Soil Amelioration The disappearance of white clover from pastures in many upland wetter regions of the United Kingdom is hastened by increases in soil acidity and a decline in the amount of available P and K. The ideal soil conditions described in Section III,B must be restored if white clover is to increase in the sward. In the United Kingdom this usually means applying 2 - 5 tons lime/ ha depending on the soil type and 20-40 kg P plus 40-80 kg K/ha (Newbould, 1986).Reduction in the total quantity of fertilizer N and/or alteration of the seasonal pattern of application may also help to reverse the decline in white clover content (see Section VII1,C).

2. Change of Defoliation Practice Relaxation of grazing pressure, change of animal species, the use of conservation cuts, and alternation of rest periods and grazing can often restore white clover to a sward (Frame and Newbould, 1984).The impact of change of animal species is shown by the use of goats, which eat tall grasses and weeds but ignore white clover (Clark et al., 1984b), so helping to restore white clover to a sward (see Section VII1,E). 3. Manipulation with Herbicide In the established grass/clover sward, invasion by perennial broad-leaved or grass weeds can lead to sward deterioration and low production from the sown species (Dibb and Haggar, 1979).Herbicide options to control certain problem weeds adequately have increased recently, but a penalty to clover of plant scorch/suppression or even death has had to be accepted (see Section IV,F). Haggar and Squires (1979) reviewed the history of manipulating the sown-species composition of grassland by herbicides. The important point was that the suppression of unwanted speciesset the stage for colonizationby existing sown species, but the success of this depended upon (1) an adequate presence and distribution of the species intended to be encouraged and (2) management, especially fertilizer use and stocking density to ensure the induced botanical change persisted. Stoloniferous white clover offers advantages as a colonizer if there is a

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sufficient nucleus of material and conditions are suitable. Hagger and Bastian ( 1980) evaluated a range of grass-suppressing herbicides (carbetamide, propyzamide, paraquat, asulam, glyphosate, and dalapon) to which clover is relatively tolerant. Their use in late winter led to a marked increase in white clover content subsequently. Initial loss of spring grass growth was high but there was compensation with extra growth in midsummer, so annual total production was unaffected. Standell and Haggar (1982) then assessed the effect of autumn application of carbetamide, paraquat, and propyzamide on a clover-depleted grass sward. All encouraged clover growth the following year without unduly reducing grass growth. Propyzamide was the best in terms of clover increase and avoidance of grass suppression. A method to increase clover content in mixed swards by spraying with mefluidide, a plant growth regulator which inhibits seed-head formation in temperate grasses (Glenn et al., 1980), is under investigation in New Zealand (Leonard et al., 1985) and the United Kingdom (Haggar et al., 1985b). The latter workers found that although the chemical caused a short-term check in the growth of white clover through a shortening of the stolons, it provided opportunity for increased colonization by “flattening” the seasonal growth peaks of the companion grass. Development work is required to find out how the use of grass suppressants can be integrated with animal production systems. Since some of the chemicals are expensive there is also a need to assess the costbenefit of these procedures against the cost of a full replacement by reseeding of both grass and clover. 4. Oversowing/Slot Seeding of White Clover In cases where few or no propagules of white clover are present but where good quality productive grasses still remain and where soil and climatic conditions are favorable to the growth of white clover, it is theoretically attractive to consider the introduction of white clover seeds. Various methods of minimal cultivation, with and without chemical suppression of grasses, have been devised to introduce clover into existing swards but consistent success has not been achieved (Tiley and Frame, 1980;Tiley, 1981b). The use of coated or pelleted seed has proved successful in New Zealand where grass swards are open and soils are low in organic matter (Lowther, 1978, 1980), but attempts to apply similar methods in the United Kingdom have not been successful. The presence of a very closed competitive sward, together with a spongy organic mat, and often the need for more lime than can be added in a thin coat or small pellet are thought to be reasons for the poor showing of these methods in the United Kingdom (Newbould, 1974, 1975).

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A number of machines have been devised to introduce white clover (and sometimesclover and grass) into existing grassy swards (Squireset al., 1979; Charles and Daniel, 1983; Sheppard et ul., 1985). In some cases (Charlesand Daniel, 1983) this has been successful, but in others only small percentages of clover have become established 2 or 3 years after drilling (Newbould, 1986). Problems arise due to the slowness of the clover in spreading from the slot; marked selection of the young clover plants takes place by sheep when grazing and from slugs and insects present in the existing sward (Naylor et al., 1983). In hill land with acid grassland (Agrostis/Festucu) where the introduction of white clover afier soil amelioration would be desirable, access and the presence of the organic mat limit the usefulness of the slot-seeding machines (Tiley, 198 1 b).

IX. POTENTIAL PRODUCTION It is of theoretical interest to consider the levels of production that might ideally be possible from either pure white clover or mixed grass/white clover swards. However, because of the many factors reviewed in this article, and variable individual farmer management, which influence the production and utilization of grazed swards, it is extremely unlikely that the attainment of any predicted potential set by climate will ever be approached in practice. Several workers have attempted to calculate the theoretical potential of grass production but few, with the possible exception of Frame and Newbould (1984), have tried to do the same for white clover. This is partly because the plant has to be grown in mixture with grass and partly because it is mainly used in the grazed sward with all the uncertaintiesthat can occur in this situation (see Sections VII and VII1,E). It is also because both the composition of mixed grass/clover swards and the performance of white clover are so markedly influenced by the supply of available N in the soil, whether from mineralization of organic matter, nitrogen fixation or from fertilizer N additions. Despite the uncertaintiesinherent in the calculationsit is relevant to consider what levels of production are theoretically possible in pure stands of white clover and in grass/white clover mixtures. A. WHITECLOVER MONOCULTURES As previously described,pure stands of white clover are not used in practical agriculture because of the difficulty of maintaining them weed free, the

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relatively low level of DM production, and practical difficulties in their utilization, especially by cattle (e.g., bloat). Calculations of the potential harvestable production from monoculture grass swards in Europe give values in the range of 20 - 30 metric tons DM/ha (Alberda, 197 1;Cooper and Breese, 197 1 ;Leafe, 1978); for monoculture white clover without added N, calculations suggest an annual herbage production of 16 tons DM/ha (Frame and Newbould, 1984). The highest recorded production from an irrigated monoculture white clover was 11.8 tons DM/ha (Spedding and Diekmahns, 1972).

B. GRASS/WHITE CLOVER MIXTURES For United Kingdom conditions, Frame and Newbould (1984) calculated that, given a 50 :50 mixture ofgrass and clover which each performed to half its theoretical monoculture potential, and with suitable utilization and fertilizer N regimes, total herbage of 18.5-22.5 tons DM/ha per year should be possible. Thus, a grass/clover sward with no applied N and with a soil-mineralizing 100 kg N (Hobson and Richards, 1978) would give 18 - 22 tons DM/ha per year. For New Zealand, where the growing season and soil conditions are said to be ideal for white clover, Smetham (1973) has described a production ceiling set by genotype and climate for a mixed perennial ryegrass/white clover sward at 22-28 compared with 10 tons DM/ha per year for white clover monocultures. However, calculations by Brougham ( 1959a) predicted annual herbage production from irrigated ryegrass/clover swards of 24.7 tons DM/ha; assumingmaximum white clover proportions in New Zealand pastures of 68% (Harrisand Thomas, 1973) the highest annual production of clover would be in the order of 16.8 tons/ha. This is surprisingly close to the calculated theoretical potential of white clover for the United Kingdom. The highest recorded production from a cut, perennial ryegrass (cv. Premo)/white clover (cv. Milkanova) sward for a season in the United Kingdom came from Cambridge,England, and was 15.53 tons DM/ha with white clover contributing 12.12 tons of the total herbage (i.e., 78%) (Table VIII, and Section VII1,B). Nitrogen was not applied and the sward was cut six times. With 200 kg N/ha the total production was 19.94 tons DM/ha per year but white clover contributed only 2.19 tons DM ( 1 1%) of the total. The highest annual pasture production levels achieved in New Zealand under grazing and with no applied N ranged from 16.2 to 22.8 tons DM/ha, depending upon site conditions (Brougham, 1977).

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X. MANAGEMENT GUIDELINES The preparation of a single blueprint for the exploitation of white clover applicable to all situations is not possible. White clover is grown in a wide variety of soils and climatic conditions, and is utilized for a range oflivestock enterprises. As is evident from the above, a host of interacting factors and relatimships can influence clover’s performance and persistence, and as yet they are not all fully understood. Nevertheless, not surprisingly, a number of authors have given sets of management guidelines on how best to exploit white clover in the mixed sward (Chestnutt and Lowe, 1970; Leffel and Gibson, 1973; Frame, 1982a; Anonymous, 1983b; Frame and Newbould, 1984; Tedstone, 1984; Stewart, 1985; Van Keuren and Hoveland, 1985). A single dominant guideline in any situation is to seek and remedy the limiting factor(s). However, the development of a well-distributed amount of white clover, inoculated with rhizobia in the stand‘s early life, clearly must be an essential target, implying attention to the initial stages of establishment and subsequent management. As a general rule, it can be stated that the use of fertilizer N on the grass/clover sward must be minimal. Any addition of N to the soil pool contributes to “loading the scales” against clover in the mixed sward. The key to utilization is flexibility of management system, so that periods of rest for clover to recover its vigor are integral parts of any system. In summary, at all stages in the management of the grass/clover stand, the needs of the white clover component should be paramount. Key guidelines are summarized in Table XI. Table XI Management Guidelines for White Clover Seeds Establishment

Production

Utilization

Choose compatible companion grasses Sow 3-4 kg clover seed/ha in seed mixture Use a blend of white clover leaf types Sow shallow (10- 15 mm) Soil pH a minimum of 5.5 Adequate basic soil fertility Preferable to sow directly in spring Make minimal strategic use of fertilizer N Maintain soil pH and P and K status Choose and use herbicides carefully Imgation is advantageous in dry areas Avoid continuous severe grazing Provide clover recovery periods, e.g., use rotational grazing, insert a silage cut in a grazing system Always favor the needs of white clover

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XI. CONCLUSIONS Most reviewers predict that sooner or later world agriculture will have to expand the use of legumes, and this applies particularly to forage legumes such as white clover in temperate regions ofthe world. A role for white clover is also foreseen in the subtropics and possibly the tropics, provided the necessary research is undertaken to widen its climaticand edaphic adaptability (Brougham et al., 1978).A major eulogistic reason for the above predictions was cited by Gladstones (1975): “Legumes make possible an ecologically sound nonexploitive and yet productive agricultural system, with which a hopefully stabilized (human) population can live in permanent balance or better.” Study of the relative role of legumes in the N economies of three temperate countries where grazing livestock are used indicates that they dominate in New Zealand, are little used in the Netherlands, and that low to moderate reliance is placed on them in the United Kingdom (Table XII). The types of livestock enterprise, suitability of the land for arable or forage cropping, and economic evaluations largely determine the national fertilizer N strategy. Taking the situation in the United Kingdom as an example, little reliance is placed on the use of white clover in lowland dairy systems;the main source of N is fertilizer N at annual rates up to 400 kg/ha. However, the average annual use of fertilizer N on United Kingdom grassland, excluding rough grazing, is now 105 kg/ha (Jollans, 1985);usage has risen steadily in recent years. In upland and marginal farming regions, both white clover and fertilizer N are used for beef cow and cross-bred sheep systems. The fertilizer N is used strategically mainly in spring and autumn and with annual amounts up to 150 kg/ha. In the more remote hill sheep farms where only small percentages of the total land area are upgraded to sown grass/white clover swards, economics determine that fertilizer N is used only in the establishment of

-

Table XI1 The Relative Sources of Nitrogen in the Agriculture of Three Contrasted Countries‘ New Zealand

Source Legumes Free living microorganisms Fertilizer Total N (million tons) in fertilizers (FAO, 1983)

United Kingdom

94 5 1

0.02

~

After Nutman (1971); Food and Agriculture Organization (1983).

25 2 73 1.4

Netherlands

5 1

94 0.5

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sown swards or in small amounts (20-40 kg/ha) to promote early growth in subsequent springs; white clover is regarded as the main source of N. As indicated previously the white clover content in pastures in the United Kingdom is usually low (e.g., Forbes et al., 1980),and this is despite the use of about 1000 tons of clover seed per year. The use of fertilizer N by British farmers undoubtedly hastens the demise of white clover in swards. In the summary of a recent symposium on forage legumes in the United Kingdom, Wilkinson (1984) gave good reasons why legumes were not exploited: “It is easier to grow grass than legumes and with grass/white clover swards the contribution made by clover can vary markedly from year to year. Bloat, oestrogens, diseases, lack of seedling vigour, combine to make legumes less flexible than other forage crops.” The role of pasture legumes may lie in the early history of pasture development (Greenhalgh, 1981; Newbould, 1982). Once a threshold quantity of organic matter has been built up which mineralizes sufficient nitrogen to support moderate levels ofgrass growth, it is extremely difficult to sustain the presence of white clover (Section VII). The farmer should then concentrate on the use of high-yielding grasses using additional fertilizer N, while this is available and its use is economically justified. This strategy might have to change should supplies of fertilizer N become limited and expensive because of shortage of fossil fuel energy. However, it is not outside the bounds of possibility that alternative energy sources to fossil fuel energy may be developed in the future which will ensure the continued manufacture of nitrogenous fertilizer. There is not a great deal of scope left to reduce further the amount of total energy required to manufacture fertilizer N (Jollans, 1985). Our review of the literature on white clover has caused us to question if white clover is the perfect pasture legume, if perennial ryegrass, and indeed other typically used cool-season perennial grasses (Van Keuren and Hoveland, 1985), are the ideal companions for it, and if the present agronomic practice ofgrowing and grazing mixed pastures ofgrass and clover is the most sensible (see summary in Table XIII). Ifthe attainment ofat least 30%white clover DM in total herbage for the growing season is a desideratum (Martin, 1960; Wright, 1975; Curll, 1982; Stewart, 1984), then most published evidence suggests that this clover content cannot be achieved or sustained consistently with the present varieties of clover and most of the typical companion grasses, and with present systems of grazing management. Plant demographic studies (Turkington and Harper, 1979a; Bradshaw et al., 1982)suggest that plants have preferred niches so that iftwo plants are to share the same space they must have complementary light, spatial, and nutrient requirements, or share these in a dynamically balanced temporal manner. The evidence reviewed briefly in Section VII indicates that on most of these grounds clover and its usual companion (perennial ryegrass) in the

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J. FRAME AND P. NEWBOULD Table XI11 Balance Sheet for and against White Clover Credit

Debit

Persistent under infrequent cutting

Not competitiveto perennial ryegrass(and many other grasses) Adversely affected by fertilizer N and urinary N Needs “good” climate: warmth, wetness Needs moderate soil fertility Within and between year variation in performance Bloat (mainly cattle)

Moderately persistent under grazing High nutritional value Fixes nitrogen Builds up soil fertility Enhanced animal performance Environmentally acceptable

United Kingdom and New Zealand are in direct competition. Moreover, if white clover is stressed by climatic (cold, drought), nutritional (pH, low P and K, high N), pest/disease, or management (sustained close grazing) factors, the likelihood is that it will be replaced by weed grasses or other weeds (Wright, 1975). Published literature includes examples of inexplicable and sudden white clover decline in both cutting and grazing trials in spite ofgood experimental technique and management (Garwood and Tyson, 1979; Davies, 1982; Stewart and Haycock, 1983, 1984; Frame and Boyd, 1984; Brereton and Carton, 1985). Clearly, marked production variability and clover inconsistency are even more likely in farming practice where a complex of factors, including soil, sward, animal, and management, many of them interactive, operate. Hence, in countries such as the Netherlands where fertilizer N is obtainable and its use is economically viable, farmers opt for animal production systems based on more easily and flexibly achieved herbage production from grass swards fertilized with mineral N. The management guidelines described in Section X stress that at all times agronomy and management of mixed grass/clover swards should favor white clover, but with few exceptions, the proportions of white clover found in farm pastures (Forbes et al., 1980; Swift et al., 1983;McAdam, 1983a)fall well short of the target needed to optimize its impact on animal nutrition or nitrogen fixation. Even in New Zealand, a country which relies almost entirely on white clover for its soil N supply, it is unusual to find in practice more than about 10-20% of the season’s total herbage production as white clover (D. A. Clark, personal communication). Indeed, Brougham ( 1977) stated that white clover made up 2 - 35% of the total annual herbage production, depending on the environment and region being assessed. Values of 20- 30% are typical in research station trials (Hoglund et al., 1979). In spite of the burgeoning volume of research on white clover in the last 50 years,

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Brougham et al. ( 1978) still concluded that more intensive research efforts are needed into all aspects of white clover’s use in temperate agriculture. To overcome all the uncertainties associated with the growth and utilization of white clover, increased research into its basic physiology, especially in association with grass, is required. There is inadequate information on growth analysis or on the seasonal behavior of the individual white clover plants; such information would help an understanding of its optimal growth requirements and management needs. While its potential role as a conservation legume should not be ignored, white clover is essentially a grazing legume; hence the greater proportion of experimentation should be under grazing conditions. Ideally, this should commence as early as the varietal evaluation stage. Thereafter, experiments, preferably long-term, should test varieties available in commerce rather than those for which little seed is available. Nitrogen from organic manures such as livestock slurry apparently inhibits white clover in mixed swards to a lesser degree than mineral N; this requires further investigation. Such studies also need extension to other forms of N, for example, slow-releaseN. Indeed, the total N cycle in grazed pastures requires study with long-needed emphasis on the N accumulation and release mechanisms in the soil. This knowledge is required particularly in countries such as those in southern Latin America which are almost totally reliant on a legume N economy (Frame, 1982b). Moreover, in his review on the flow of nitrogen in grassland, Ryden (1984) concluded that “It is important that the efficiency of the flow of N in fertilizer-based systems is compared with that in systems based on grass/clover swards.” Ryden also suggested “that the flow of N in grazed grass/clover swards is more precisely regulated than in ryegrass swards receiving fertilizer N.” If so, the grass/clover sward would be environmentally “safer” than the N-fertilized grass sward from which considerable N leaching can take place. In any further work on white clover and the N cycle there is a need to standardize methods of conducting grazing experiments among countries and among research groups within countries. There is also a need to define clearly what researchers mean by the proportion of white clover in a mixed sward; a wide range of methods, times of measurement, and methods of expression were evident in the literature. In our opinion, clover should be assessed in herbage production terms rather than ground cover estimates. Most importantly, all experimental work should be multidisciplinary (Le., a task force approach). All too often in the past, the single-disciplineexperiments performed have proved inadequate. More practical livestock systems work is needed and it should undergo simultaneous economic measurement and analysis. Ideally, seasonal target levels for clover contribution to differing animal production systems need quantification from both the viewpoints of animal

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nutrition and N fixation. Experimental work with white clover should be of sufficient duration to cover the inevitable grass/clover balance changes which occur insidiously, or suddenly. In the long term, other possibilities must be considered. Can white clovers be found with good growth in spring, an attribute not possessed by present varieties? Can more productive and persistent varieties of white clover or other pasture legume species be found or bred? Can low-fertility-tolerant varieties be developed?Admittedly, the history of breeding in forage legumes is short by comparison with the effort put into cereals. Can companion grass species be found that are as productive and nutritious as perennial ryegrass but are less aggressive to white clover? Somatic cell fusion techniques (Dale et al., 1984)might hasten the discovery of new legume plants which are easy to establish, high yielding, disease resistant (and therefore persistent), and bloat free. The use of coadaptation philosophies (Sections IV,E and VII) to match more closely legume and grass to give stable and productive mixed pastures with a high proportion of clover merits further high-priority research. The extension of this principle to encompass selection of appropriate microorganisms may also be advantageous. The use of farm systems with sole reliance on mixed grass/clover pastures warrants experimental consideration and evaluation, with complementary use of other legumes such as red clover or alfalfa (lucerne) where suitable. The use of some form of ‘buffer’ supplement (e.g., silage, hay, concentrates) at grazing, to even out feed supply at times when herbage production from grass/white clover is limited, merits investigation. Again various ways could be devised to use areas of monoculture white clover with areas of grass fertilized with mineral N. Both plants could then be grown in the manner that suits them best. The grazing of grass and red clover in separate but contiguous blocks by dairy cows was moderately successful (Greenhalgh, 1975). It is also possible that the principles of the two-pasture approach applied so successfullyto hill land in the United Kingdom (Eadie et al., 1979; Armstrong ef al., 1986) could be applied to lowland pastoral farms. One or two fields well suited to the growth of forage legumes could be scheduled for mixed swards while the remainder would be farmed conventionally with reliance on grass and the application of fertilizer N. However, little research has been instigated on this concept. Although the strategies just described might be described by some as pessimistic, it appears to us as eminently realistic. Efforts should also be turned to other “lateral thinking” strategies, some of which have been described by Greenhalgh (1982). Why not regard white clover rather than grass as the continuing element in a mixed sward and insert short-term grasses such as Italian ryegrass when required? If such a grass grows tall it can be mechanically harvested at a height which will enable the underlying

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clover-rich stubble to thrive and be available for utilization by grazing livestock. Clearly animal nutritionists should try to understand further why clover herbage is so nutritious to the ruminant. This knowledge could then be used to select and breed grasses so that they are digested and metabolized by livestock as efficiently as legumes. The growth of such grasses, possibly in rotation with white clover grown as a nitrogen-fixing monoculture, might avoid the complexities of trying to maintain clover in mixed swards on relatively fertile soils, a situation to which it is clearly not adapted. The technology of using pasture legumes should continue to be developed for use in improving existing grasslands, and for use in rotations on fertile arable land should fertilizer N become unavailable or too expensive. Such research would seem especially warranted in view of the fact that uniform land of good quality is of limited supply in the world and yet plays a crucial role in agriculture. Pasture legumes could also be used extensively as amenity plants to maintain land in reasonable fertility, and especially land which has to be taken out of agriculture because of surplus food production. Additionally, in many parts of the developing world, where land is at the earliest stage of plant succession, the role of legumes in improving soil fertility remains of vital importance. Despite the many difficulties outlined in this review, grass/white clover swards make an enormous contribution to temperate pastoral agriculture. They have the potential to produce large amounts ( 18 - 25 tons DM/ha per year) of high-quality feed for livestock and to fix up to 250 kg N/ha per year. Sadly, this potential is rarely approached. Challenging research is needed and is justified to solve the paradoxes of the agronomy of white clover.

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Westbrooks, F. E., and Tesar, M. B. 1955. Agron. J. 47,403-410. Wheeler, W. A. 1950. “Forage and Pasture Crops.” Van Nostrand-Reinhold, Princeton, New Jersey. White, J. H., and French, N. 1968. J. Br. Grassl. Soc. 23, 326-329. Whitehead, D. C. 1966. “Nutrient Minerals in Grassland Herbage.” Commonw. Bur. Pastures Field Crops, Hurley, England. Whitehead, D. C. 1970. “The Role of Nitrogen in Grassland Productivity.” Commonw. Bur. Pastures Field Crops, Hurley, England. Whitehead, D. C. 1982. J. Sci. FoodAgric. 33, 1227- 1235. Whytock, G. P., and Frame, J. 1985. Tech. Note- West Scotl. Agric. Coll. 245. Widdup, K. H., and Turner, J. D. 1983. N. Z. J. Exp. Agric. 11,27-31. Wilkinson, J. M. 1984. Occas. Symp. Br. Grassl. SOC.16,230-234. Williams, R. D. 1984. “Crop Protection Handbook-Grass and Clover Swards.” Br. Counc. Crop Prot., Croydon, England. Williams, W. 1970. Occas. Symp. Br. Grassl. SOC.6, 1-10. Williams, W. M. 1972. N. Z . J. Agric. Res. 15,363-370. Williams, W. M., and Barclay, P. C. 1972. N. Z. J. Agric. Res. 15, 356-362. Williams, W. M., and Hoglund, J. H. 1978. N. Z. J. Agric. Res. 21,491 -497. Williams, W. M., Lambert, M. G., and Caradus, J. R. 1982. Proc. N. Z. Grassl. Assoc. 43, 188- 195. Willis, C. B., and Thompson, L. S. 1969. Can. J. Plant Sci. 49,505-509. Wilman, D., and Asiegbu, J. E. 1982a. Grass Forage Sci. 37, 1 - 13. Wilman, D., and Asiegbu, J. E. 3982b. Grass Forage Sci. 37, 15-27. Wilman, D., and Hollington, P. A. 1985. J. Agric. Sci. 104,453-467. Wilson, E. R. L. 1978. N. Z. J. Agric. Res. 21,725-726. Witty, J. 1983. Soil Biol. Biochem. 15, 631 -639. Woledge, J. 1978. Ann. Bot. (London) [N.S.] 42, 1085- 1089. Woledge, J., and Dennis, W. D. 1982. Occas. Symp. Br. Grassl. Soc. 14, 3 1 1 - 3 12. Woledge, J., and Suarez, A. C. 1983. Ann. Bot. (London) [N.S.] 52,239-245. Woledge, J., Dennis, W. D., and Davidson, I. A. 1984. Adv. Photsynth. Res. 4, 149- 152. Wolton, K. M., and Brockman, J. S. 1970. J. Br. Grussl. SOC.25, 7- 19. Wolton, K. M., Brockman, J. S., and Shaw, P. G. 1970. J. Br. Grassl. SOC.25, 113- 118. Wong, E., and Latch, G. C. M. 1971. N. Z. J. Agric. Res. 14,633-638. Wood, M., and Cooper, J. E. 1985. Soil Use Manage. 1.66-69. Wood, M., Cooper, J. E., and Campbell, D. S . 1985. J. Soil Sci. 36,357-365. Wright, C. E. 1975. Rep. 1974-197s. Agric. Res. Inst. N. Ire., pp. 13-23. Wright, C. E., and Faulkner, J. S. 1977. Rec. Agric. Res. 25, 25 - 3 I . Yeates, G. W., Healy, W. B., and Widdowson, J. P. 1973. N. Z. J. Agric. Res. 15,81-86. Yeates, G. W., Crouchley, G. C., and Witchalls, J. T. 1975. N. Z. J. Agric. Rex 18, 149- 153. Young, D. J. B. 1958. J. Br. G r a d . Soc. 13, 106- 114. Young, N. R. 1984. Occas. Symp. Br. Grassl. Soc. 16,201-202. Young, N. R., and Mytton, L. R. 1983. GrassForageSci. 38, 13-19. Younie, D., and Black, J. S . 1979. North. Scotl. Coll. Agric., Bull. 16. Younie, D., Wilson, J. F., Carr, G., and Watt, C. W. 1984. Occas. Symp. Br. Grassl. SOC.16, 182- 183. Zaleski, A. I96 I. J. Agric. Sci. 57, 199 -2 12. Zohary, M. 1972. Bot. Not. 125,501-511.

ADVANCES IN AGRONOMY, VOL. 40

AGRONOMIC VALUE OF UNACIDULATED AND PARTIALLY ACIDULATED PHOSPHATE ROCKS INDIGENOUS TO THE TROPICS L. L. Hammond, S.H. Chien, and A. U. Mokwunye Agro-Economic Division, International Fertilizer Development Center Muscle Shoals, Alabama 35662

I. INTRODUCTION Considerable research has been conducted in recent years in search of alternative means of supplying phosphorus (P) for crop production in tropical soils. The motive for this effort has been not so much the agronomic ineffectivenessof the conventional high-solubility P fertilizers as the cost of these traditional commercial fertilizers. The primary component of the research has focused on the use oflow-cost indigenous material such as locally availablephosphate rock (PR) deposits, farmyard manure, or plant residues. The target groups for use of the alternative fertilizers are primarily the resource-poor farmers of subsistence and frontier-type agriculture. It is recognized that the greatest market for the conventional fertilizers is among the more modem commercial farmers who produce primarily cash crops such as sugar, cotton, soybeans, potatoes, coffee, fruits, or vegetables, and that the alternativesources may be most appropriate as complementsto the conventional sources to fill the needs of a specific user group with limited capital available for the purchase of production inputs. This review will focus on the use of indigenous PR deposits located in the tropics. Evaluation of these deposits was intensified around the 1974- 1975 period when the price ofphosphate fertilizers sharply increased on the world market and consumersin developing tropical countries began to realize that, although the PR essential for P fertilizer production was present in those countries, information was not available regarding means by which the resource could most appropriately be used to alleviate their dependence on foreign suppliers. The PR resources located in tropical regions had not been developed for a variety of reasons. Among the most important reasons is that many are considered “problem ores”: the chemical properties are not suit89 copyriebt 8 1986 by Academic h5.5, Inc.

AU rights of reproduction in any form m e n d .

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L. L. HAMMOND ET AL.

able for production of well-known fertilizer products using conventional process technology and many of the individual deposits are too small to warrant the investment required for conventional technology. The alternatives that have received the greatest attention include (1) use of the indigenous PR in a finely ground form for direct application to soil, (2) development of granulation techniques to improve the physical properties of unacidulated PR while minimizing a detrimental effect on agronomic performance, i.e., minigranulation, (3) mixing of finely ground PR with organic materials, sulfur, soluble P fertilizers, or other products capable of increasing the availability of P from the PR, (4) partial acidulation of the PR (PAPR) with available acids to increase the water and citrate solubility of the P in the PR while reducing the cost of the product relative to fully acidulated fertilizers, and (5) cogranulation of the PR with soluble P fertilizersto achieve a product similar to partially acidulated phosphate rock (PAPR) (i.e., extended superphosphate). Of the alternatives listed, the use of PR for direct application is one of the most appealing to developing countries because the low input of capital and energy required to prepare the product makes it one of the cheapest mineral P fertilizers possible. It is well known, however, that the agronomiceffectiveness of PR is highly variable and frequently lower than that of soluble P fertilizer. Several excellent reviews published earlier describethe factors that influence the agronomic effectiveness of PR (Lipman ef al., 1916; Rogers ef al., 1953; Russell, 1973; Khasawneh and Doll, 1978). These reviews have concentrated on the studies done in the temperate regions. It was generally concluded in each of these reviews that-paraphrasing both Russell (1973) and Khasawneh and Doll (1978)-PR is not suitable for use in intensive agricultural production because PR cannot maintain a sufficiently high concentration of P in the soil solution for high yields of crops with high P requirements but that finely ground PR may be a suitable source of P for many acid soils in tropical agricultural systemswhere very high yields are not sought and sulfur is not deficient, because it is the cheapest source of P that can be produced from PR. The purpose of this review is to evaluatethe degree to which PR and PAPR have, in fact, been observed to be suitable for use in tropical agriculture.

II. INDIGENOUS PHOSPHATE DEPOSITS IN THE TROPICS Phosphate rock is mined in many countries, but by far the greatest quantities available in the world market are produced in Morocco and the United States. The figures in Table I illustrate that 57.5% of the PR exports origi-

PHOSPHATE ROCKS IN THE TROPICS

91

Table I

Exports of Phosphate Rock by Country in 1983" Country of origin Morocco United States

U.S.S.R.

Jordan Togo Israel Nauru

s=d

Tunisia Christmas Island All others Total

Percentage of total exports 29.6 21.9 10.4 7.8 4.4 4.1 3.6 2.1

2.3 2.3 4.9 100.0

a From the Food and Agriculture Organization ( 1984).

nated from these two countries in 1983. Togo and Senegal, which lie within the region discussed in this review, accounted for 4.4 and 2.7%,respectively, of the PR exports. Other than those listed, all other countries combined accounted for only 4.9%of the exports. While the countries listed in Table I produce PR on a relatively large scale, the alternative P sources which are to be given attention in this review range from those that only show potential for commercial development to those that have only recently become available for internal use within the country of origin. Many of the deposits have not been exploited in the past because of their small size or inaccessibility; thus, their proximity to appropriate agricultural conditions an important factor. Some of these deposits located within the tropics are listed in Table 11. As will be shown in subsequent sections, these deposits exhibit a wide range in chemical composition, solubility, and, accordingly, potential for agronomic use. The economic potential of a deposit will depend on many factors, including market price or value, extent and grade of the deposit, location, cost of mining and beneficiation, quality and grade of the beneficiated product, and environmental factors [InternationalFertilizer Develop ment Center (IFDC), 19791. Also, when a deposit is to be mined for domestic use, the potential is related to the alternative of using imported ore or imported fertilizer. One country that has taken steps to reduce imports is Brazil.

92

L. L. HAMMOND ET AL. Table I1 Some Phosphate Rock Deposits Located in Countries with Agricultural Lands Lying within the Tropics"

~~

Country Africa Angola Burkina Faso Liberia Mali Mauritania Niger Senegal Tanzania Togo Uganda Zaire Zambia Asia Christmas Island India Paracel Island Philippines Sri Lanka Vietnam Latin America Aruba Bolivia Brazil

Colombia

Location Cabinda Kodjari Bomi Hills Tilemsi Valley Parc W Tahoua Taiba Thies Minjingu Hahotoe, Kpogame Sukulu Matadi Kaluwe. Nkomba Udaipur, Jaisalman Mussoorie Jhabua, Singhbhum, etc. Negros Island Eppawala Lao Cay

Total reserves and resources (mTX lo6)

I20 I500 1.5 20 5 100

-

1 100 2090 10 300 200 83 400

200 70 18 52 20 0.5

300 500

10

Capinota Anitapolis Araxa Catalao Ipanema Jacupiranga Olinda Patos de Minas Tapira Huila Pesca Sardinata Turmeque

-

320 500 370 I20 100

20 700 950 I38 600 80 10

Type deposit Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Igneous Sedimentary Igneous Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Igneous Igneous Sedimentary Sedimentary Sedimentary Igneous Igneous Igneous Igneous Igneous Sedimentary Sedimentary Igneous Sedimentary Sedimentary Sedimentary Sedimentary

PHOSPHATE ROCKS IN THE TROPICS

93

Table I1 (Continued)

Country Chile Curacao Ecuador Mexico Peru Venezuela

Location Mejillones Nape

Baja California Zacatecas Sechura (Bayovar) Lobatera Riecito

Total reserves and resources (mT X lo6) 4 10

-

lo00 140 6100

40

Type deposit Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary Sedimentary

a Adapted from the International Fertilizer Development Center (1979), Cathcart (1983), Harben (1983), Ricaldi and Escalera (1985), and PPCL (1 983).

Production of PR in Brazil has increased from 236,000 million tons in 1972 to 3,208,000million tons in 1983. As a result, imports of PR dropped from 1,156,000million tons in 1972 to zero in 1983 (Food and Agriculture Organization, 1984). Factors that must be considered in determination of the economic viability of developing a deposit for domesticconsumption must therefore include the value of savings on foreign exchange, the stability of price and supply of imported products, and the internal value of employment opportunities and infrastructure development. A prerequisite to all of these concerns is an understanding of the agronomic suitability of the alternative products that can be achieved with the ore.

Ill. AGRONOMIC POTENTIAL OF PHOSPHATE ROCK FOR DIRECT APPLICATION The term agronomicpotential as used in this review refers to the inherent capability of the P-containing rock to supply plant-available P under a specified set of conditions. It is determined primarily by the chemical solubility of the rock, and differsin meaning from the term agronomic eflectiveness in that the latter refers to the actual performance of a given PR source as influenced by both agronomic potential and external conditions under which it was used. The importance ofdefiningthe agronomicpotential ofthe PR source was not recognized for many years, thus leading to confusion in

94

L. L. HAMMOND ET AL.

interpreting the erratic results of agronomic trials with PRs. For decades, researchers failed to identify the source of PR used in the comparisonsunder the false assumption that all PRs would behave similarlywhen applied to the soil. It is now well recognized that this is not the case and that the observed effectiveness of PR relative to soluble P fertilizer will vary from source to source depending upon the mineralogy and chemistry of each rock as well as the influence of soil, crop, environment, and management factors. A. MINERALOGY AND CHEMISTRY OF PR SOURCES

Although a number of deposits of PR indigenous to countries within the tropics are characterized by high concentrations of iron and aluminum phosphate minerals [i.e., Phospal (Senegal),Christmas Island (C grade), and Maranhao (Brazil)],the P mineral of principal importance is apatite. Apatite varies widely in physical, chemical, and crystallographicproperties (Lehr et al., 1967). In general, the apatites are in the form of carbonate apatite (francolite)with varying degrees of isomorphicsubstitution of carbonate for phosphate. Precise identification of the apatite composition for a wide range of PRs located within the tropics has been accomplished during the past 20 years by the International Fertilizer Development Center (IFDC), the Tennessee Valley Authority (TVA), and other organizations using techniques including chemical analysis, X-ray powder diffraction, petrographic microscopy, infrared spectroscopy, and electron microscopy as described by McClellan ( 1979). Previous work has shown that the degree ofisomorphic substitution in the apatite structure is the key factor in determining the chemical reactivity of PR containing carbonate apatite (Lehr and McClellan, 1972). Thermodynamically, carbonate substitution for phosphate should increase the reactivity of the PR (Chien and Black, 1976; Chien, 1977). A plot of neutral ammonium citrate soluble P versus the mole ratio of C03 to PO4 of the apatites in 49 different PRs demonstrated that the solubility of those PRs increased as the carbonate substitution for phosphate in the apatite structure increased (Lehr and McClellan, 1972). These results agree with the earlier report by Car0 and Hill (1956) that the solubility increased as the “bound CO;’ in the apatitic minerals increased. Work done by Lehr and co-workers (Smith and Lehr, 1966; Lehr et al., 1967; McClellan and Lehr, 1969; Lehr and McClellan, 1972) has demonstrated that the unit cell a dimension of carbonate apatite can be measured by X-ray diffraction. The unit cell a dimension, in turn, is indicative of the degree of carbonate substitution for phosphate, decreasingas the mole ratio C03: PO4increases. This relationship, which is reviewed in greater detail by

95

PHOSPHATE ROCKS IN THE TROPICS

Khasawneh and Doll ( 1978), has been used to show that the composition of (sedimentary) apatites can be expressed by the following generalized formula: CaI0-a -dVaaM&(p04)6 -Ac03)22 +0.4x in which the u dimension = 9.374 - [0.204~/(6- x)]; u(Na) = 1.327(x)/ (6 - x); and b(Mg) = 0.5 15x/(6 - x). Table 111 shows the empirical formulae thus derived for the apatites of some representatives PRs from tropical regions in comparison with those of commercially developed phosphate rock deposits. B. CHEMICAL REACTIVITY OF THE PHOSPHATE ROCKS

Determination of the carbonate substitution for phosphate in the apatite structure as described above is theoretically the most appropriate means of characterizingthe chemical reactivity ofa PR sample, because it is a measure of the actual thermodynamicstability of the apatite structure. Its routine use, however, is limited by the requirement for sophisticated procedures and equipment not normally available in laboratories operating in developing countries. Instead, chemical reactivity is conventionally determined by measuring the solubility of the PR in extracting solutions. There are three commonly used chemical extractants for measuring the solubility of PR: neutral ammonium citrate (e.g., the United States), 2% Table I11 Unit Cell (I Dimension and the Empirical Formulas of Apatites in Some Representative Phosphate Rocks in Asia, Africa, Latin America, and the United States

Length of

Region Asia Africa Latin America United States

Rock sample

a axis (A)

El-Hassa, Jordan Mussoorie, India Kaiyang, China Gafsa, Tunisia Hahotoe, Togo Parc W, Niger Bayovar, Peru Pesca, Colombia Patos de Minas, Brazil North Carolina Central Florida Tennessee

9.339 9.3s2 9.372 9.328 9.35 9.365 9.337 9.346 9.370 9.322 9.345 9.357

Empirical formula C~.~N~.23M~.~(P04)5.12(C03)0.88F2.35

C~.~N~.14M~.06(P04)5.42(C03)0.~8F2.23 C~.9~N~.01M~.~l~P04~5.~~C03~0.06F2.02 C~.59N~.MM~.12(~4)4.90(C03)1.10F2.44

C ~ . ~ 9 N ~ . 1 5 M ~ . 0 6 ( P 0 4 ) 5 . 3 9 ( C 0 3 ) 0 , 6 1 F2.24 c~.93N~.05M~,02~p04~~.78~c03~0.22F2.~

C~.76Na.l,Mp0.0~P04)5,2a(C03)0.72F2.29 C~,~3N~.~M~.13(P04)4.77(C03)l.23F2.49

-35

N%.I I M h 4 ( P04)5.54(c03

)OM F2. I6

96

L. L. HAMMOND ET AL.

citric acid (e.g., Brazil until recently), and 2% formic acid (e.g., Europe). Other methods that have been found to be highly correlated with plant-available P include (1) absolute citrate solubility as proposed by Lehr and McClellan ( 1972),which is based on X-ray diffraction analysis of the apatite and (2) ammonium citrate, pH 3 (Chien and Hammond, 1978b). MacKay et af.( 1984)tried 5 and 15%citric acid and found that they were not suitable for measuring PR reactivity. Care must be taken in the interpretation of solubility measurements because of the presence of accessory minerals in the PR in association with the apatite. Free carbonates (calcite and dolomite), for example, are more soluble than apatite in neutral ammonium citrate solution (Silverman ez af., 1952)and tend to depress the extraction of citrate-soluble P during a single extraction. It has been shown, however, that if the first extract is discarded and the soluble P of the subsequent extract of the same sample is analyzed, a more accurate measure of agronomic potential can be obtained. This is most noticeable when measuring the relative potential of a number of PRs in which there is a wide spread in the content of free carbonates. In a study by Chien and Hammond (1 978b), for example, it was observed that in Huila PR from Columbia, which contains approximately 6% C02 in the form of free carbonates, the P extracted by neutral ammonium citrate increased from 0.4% by weight of the rock during the first extraction to 1.5% in the second extraction. Other PRs in the study contained negligible amounts of free carbonates, and the amounts of citrate-soluble P extracted during both the first and second extractions were the same. Thus, it is recommended that the second extraction by neutral ammonium citrate be employed for ranking of relative agronomic potential. Alternatively, sequential extractions as used by MacKay et af.( 1984)can be used to estimate the agronomic potential of PRs. Other accessory minerals can also influence the results of chemical solubility tests. Pesca PR from Colombia, for example, has siliceous minerals intermixed with the apatite in such a way that they render the apatite less accessible to attack by the chemical solvents. In this respect, the chemical solvents are in fact more indicative of the agronomic potential than is the absolute citrate solubility. Absolute citrate solubility, for example, shows that the C03:PO., ratios are the same for Pesca PR as for central Florida PR, whereas, in fact, the agronomic potential of Pesca is generally lower than that of central Florida PR because of the Si cementation (Chien and Hammond, 1978b). Differences in utilization of solubility tests for ranking the agronomic potential of PR are also encountered in the method of expressing the amount of P extracted by various methods. Lehr and McCellan ( 1972)pointed out that the conventional “apparent solubility,” as expressed by the amount of solubilized P as a percentage of total P in the material analyzed, can lead to

97

PHOSPHATE ROCKS IN THE TROPICS

an erroneous comparison of the PRs varying widely in grade. In Table IV it can be seen that the solubilities of the two low-grade PRs (Huila and Pesca) are apparently increased with respect to other rocks when the solubilitiesare expressed as percentage of total P rather than percentage of rock. Thus, expression of soluble Pas a percentage of rock, rather than as a percentage of total P, seems preferable where the PR sources vary widely in P content. Comparisons of chemical extractants have been made by various researchers. In early studies measuring the solubility of seven PRs, Car0 and Hill (1 956) reported that the method of 2% citric acid correlated better with the yield of alfalfa grown on three acid soils than did the method of neutral ammonium citrate. However, they did not provide the exact reason for this. Chien and Hammond (1 978b) compared various methods for predicting the agronomic potential of seven PRs (Table IV) for direct application. These measurements were evaluated by crop response data obtained from a greenhouse experiment with guinea grass and a field experiment with beans, both on acid Colombian soils. Among the five methods tested, neutral ammonium citrate (second extraction), 2% formic acid, and ammonium citrate, pH 3, were better correlated with the agronomic data than were the methods of neutral ammonium citrate (first extraction), 2% citric acid, and absolute citrate solubility. In a recent greenhouse study, MacKay et al. (1984) compared seven chemical extraction methods in terms of their ability to assess the agronomic effectiveness of five PRs using perennial ryegrass and white clover as testing crops. Of the conventional, single-extraction procedures Table IV Solubility of the Phosphate Rocks in Neutral Ammonium Citrate and Acid Ammonium Cltrate, pH 3" Soluble P (%) as expressed by Neutral ammonium citrate (second extraction)

Total P

Ammonium citrate, PH 3

Rock sample

(%)

Rock

Total P

Rock

Total P

Huila, Colombia Pesca, Colombia Bayovar, Peru Gafsa, Tunisia North Carolina Central Florida Tennessee

9.1 8.6 13.0 13.0 13.0 14.2 13.1

1.5 0.8 2.3 2.4 2.9 I .4 I .2

16.2 9.5 18.0

4.7 3.7 10.5 9.2 10.8 6. I 4.3

50.2 42.9 80.3 70.3 82.9 42.3 31.5

'

Data from Chien and Hammond (1978b).

18.6

22.4 9.7 8.9

98

L. L. HAMMOND ET AL.

evaluated, 2% formic acid appeared to be the most useful. Two 2% citric acid procedures (0.5- and 1-hr extraction time), neutral ammonium citrate, alkaline ammonium citrate, and two concentrations of citric acid ( 5 and 15%) at the first extraction were poor indicators of agronomic effectiveness. In the studies of Chien and Hammond ( 1978b)and MacKay et al. ( 1984), the poor correlations of the methods of neutral ammonium citrate (first extraction)and 2% citric acid with agronomic data were thought to be due to the depressed solubility caused by the presence of free carbonates in some PRs. Apparently, the associated free carbonatesdid not significantly depress the dissolution of apatites in the soils, and thus the two solubility measurements underestimated the agronomic effectivenessof these PRs. When the second extraction with neutral ammonium citrate was used, the solubilityof PRs then correlated well with crop data (Chien and Hammond, 1978b). It should be pointed out that the ability of chemical methods to predict the agronomic potential of PRs generally decreases as the residual effect of PRs progresses (Chien and Hammond, 1978b;Engelstad et al., 1974;MacKay et al., 1984). This is because of the influence of soil reactions with PR on the residual effect of PR, which is not measured by the initial chemical extractions. MacKay et al. ( 1984)proposed that a sequentialextraction procedure (sums of two to four extractions) be used to predict the long-term effect of PR. For example, the sum of two sequential extractionswith 2% formic acid method still correlated well with the yield of ryegrass at the fourth harvest, whereas the first extraction method failed to predict the residual effect of PRs. The motive for measurement of relative agronomic potential (RAP) has been threefold: First, it is recognized that the effectiveness of a P source measured under actual field conditionswill vary with changes in a number of climatic and agro-edaphic conditions. Solubility measurements, therefore, cannot be used to predict specific yield response, but they can serve as a means of predicting the relative performance of one source to another and thus assist in selection of the most appropriate source for a given set of conditions. Second, findings related to efficient use and management in studies with a given PR source can be expected to be relevant to other P sources with similar solubility.Third, for those countries with several undeveloped deposits of PR, measurements of RAP can serve as a guideline for selecting appropriate priorities for resource development. Studies reported by Hammond (1977), Le6n et al. ( 1986), and Nuiiez (1984) have attempted to rank a large number of PRs indigenous to countries within the tropics of Latin America. It was reported by Hammond (1977) that, on the basis of field trials in Colombia with beans (Phaseolus vulgaris) grown on a Typic Dystrandept and cassava (Manihot esculenta crantz) on a Tropeptic Haplustox as well as a greenhouse trial with Bra-

PHOSPHATE ROCKS IN THE TROPICS

99

chiaria decumbens on the same Oxisol, the seven distinct PRs studied could be ranked as having either high, medium, or low agronomic potential for direct application. It was found that RAP was correlated with the solubility of P in the PR when extracted with neutral ammonium citrate (second extraction). However, it was also concluded that due to the influence of the factors listed above which influence crop response, relative ranking of the source behavior represented the greatest degree of precision possible with solubility measurements. Of the Latin American sources included in that study, Bayovar PR from Peru was classified as having high RAP, Huila PR from Colombia as having medium RAP, and Pesca PR from Colombia as having low RAP relative to soluble P sources. This corresponded to category exhibited citrate solubility of the P in the range of 5.4 to 6.7% (high), 3.2 to 3.4% (medium), and 1.9 to 2.79/0(low). The three Latin American PR sources evaluated by Hammond (1977) were included with additional sources in a greenhouse evaluation reported by Lebn et al. (1986). In the later study, a total of 1 1 Latin American PRs (plus five additional sources) and triple superphosphate(TSP) were tested in a single experiment with guinea grass (Panicurn maximum) as the test crop grown in a Tropeptic Haplustox. The response curves obtained in that trial are illustrated in Fig. 1 and demonstrate the extreme differences among sources in their capability to supply plant-available P. 23

TSP North Carolina (USA)

21

Gaka (Tunisia) Bayovar (Peru)

19

Arad (Israel)

17

Huila (Colombia) Pesca (Colombia)

15

Lobaten (Venezuela) Sardinala (Colombia) Paloo de Mlnaa (Brazil)

13 11

Araxa (Brazil) Abaeti (Brazil)

9 7

Jacupiranga (Brazil)

5

Calalao (Brazil)

3

Taplra (Brazil)

1

50

ioo

2b0

400

Phosphorus Applled (mglpol)

FIG.I. Response by guineagrassto application ofphosphate rock.(FromL e h er al., 1986.)

100

L. L. HAMMOND ET AL.

With the inclusion of the additional sources, all of which were lower in solubility than those studied by Hammond (1 977), it was concluded by LeBn et al. (1986) that an additional RAP grouping (very low) should be recognized. The 16 PR sources (including the 11 from Latin America) were ranked into the four RAP groups by discriminant function analysis. The variables used in the discriminant function analysis included dry matter yield, P uptake, and P solubility in neutral ammonium citrate, 2% citric acid, 2% formic acid, and ammonium citrate, pH 3. Table V gives the average effectiveness and solubility measurements within each of the RAP groupings. In these evaluations, it was also concluded that solubility measurements with 2% citric acid, 2% formic acid, and ammonium citrate, pH 3, were effective, as was neutral ammonium citrate solution, in ranking the RAP of the PRs. This is in agreement with the findings of Chien and Hammond ( 1978b), who also found these methods highly correlated with initial crop response but not with residual P availability from the sources. In a review of studies conducted using Mexican PRs, Nuiiez (1984) reported the results obtained by Adan et al. (1980) with four PRs from Baja California and two from continental Mexico. It was observed in this review Table V Average Effectiveness and Solubility Measurements for Sources within Relative Potential Groupings' Relative agronomic potential (RAP)

Number of samples in the group Relative agronomic effectiveness (%) Mean Range Neutral ammonium citrate soluble P (%) Mean Range 2% Citric acid soluble P (%) Mean Range 2% Formic acid soluble P (%) Mean Range Ammonium citrate, pH 3, soluble P (%) Mean Range a

From LeBn et al. ( I 986).

High

Medium

Low

Verylow

4

4

5

3

94 85-99

16 74-19

55 42-67

21 12-28

2.6 2.4-2.9

I .2 0.8-1.5

0.5 0.2-0.8

0.2 0.1 -0.3

5.8 5.0-6.7

2.9 2.1-3.8

2.5 2.1-3.1

1.3 1.2- 1.3

9.1 7.6- 10.4

3.1 2.2-3.6

2.2 1.0-3.0

1.4 1.4-1.5

10.9 6.1 - 13.8

4.5 2.8-6.0

2.0 1.0-4.4

0.6 0.1-1.2

PHOSPHATE ROCKS IN THE TROPICS

101

that the PRs from Baja California were similar in reactivity to those from Morocco, Algeria, and Israel and were surpassed only by PRs such as those from North Carolina and Gafsa (Tunisia). The rocks from Zimapan and Saltillo, on the other hand, were found to be low enough in solubility that they were not recommended for direct application. It was also noted that plant response to direct application of these PRs on two soils in a greenhouse test with Italian ryegrass (Lolium multiflorum,cv. Westerwools)was closely correlated to the PR solubility in neutral ammonium citrate.

IV. PHYSICAL FACTORS INFLUENCING EXPRESSION OF AGRONOMIC POTENTIAL In the preceding section on agronomic potential of PR, it was pointed out that the degree to which the chemical reactivity of the source was expressed was measured as actual agronomic effectiveness. Although such external factors such as soil properties, crop type, and fertilizer management strongly influence agronomic effectiveness, the physical condition of the PR itself is also a critical factor. Since PR is water insoluble, the first step in utilization by the plant of the P applied to soil as PR is the partial dissolution of the rock. The physical form of the PR, therefore, influences both the rate of dissolution, because of the role of surface area contact in promoting the dissolution reaction, and the spatial availability of the P following dissolution. A. PARTICLE SIZEOF THE PHOSPHATE ROCK

In reviews of experiments with finely ground PR in the United States (Rogers el al., 1953; Khasawneh and Doll, 1978) and the United Kingdom (Cooke, 1956), it was concluded that increases in P availability were obtained by increasing fineness of grinding but that the degree of improvement rarely justified grinding to a size less than 100 mesh ( 150pm). It was additionally pointed out by Khasawneh and Doll (1978) that, because the concentration of P around the PR particle in the soil is low and the diffusion from the site is minimal, the availabilityof P from the PR is a function of the probability of plant roots intercepting zones in which PR is dissolving. This being the case, the influence ofparticle size is also interrelated with the rate of application, method of application, reactivity of the PR, and acidity of the soil. It can be predicted, for example, that the influence of fine grinding will diminish as the rate of application increases and as the distribution of particles in the soil is increased by more complete incorporation into the soil.

102

L. L. HAMMOND ET AL.

Data reported by Adan et af. (1980) support these contentions. In his greenhouseresearch using six PRs from Mexico, one from Morocco, and one from Florida, the P sources were applied at two rates of application on two soils with the PRs ground to two size ranges: minus 8O/plus 100 mesh and minus 17O/plus 230 mesh. Analysis of variance based on P uptake by L. muftiflorumduring a 177-day cropping period with four cuts showed that there was no statistically significant difference between the two particle size ranges when applied at the high rate. In Africa the first trials involving the use of Senegalese PR from Thies showed a delayed response of groundnut to the fertilizer (Bouyer, 1951, 1954). Poulain and Mara (1965) suggested that the coarse nature of the materials could have caused the poor initial response. It was subsequently found that for PR to be effective it must be finely ground (Bockelee-Morvan, 1966).Research continues on how finely ground the PR should be for direct application. The amount of soil moisture and the reactivity of the rock are important factors. Trials conducted with the moderately reactive Tilemsi PR seemed to confirm that rough grinding was beneficial and fine grinding added little to the agronomic efficiency of the rock (Thibout et af., 1980).

B. GRANULATION OF PHOSPHATE ROCK Based on the experiences with the particle size of ground PR, the general recommendation for its use has been to grind as fine as is economically feasible, but to grind fine enough so that at least 80%of the material will pass a 100-meshscreen. Several concerns, however, have been raised with respect to grinding to a powder state. For example, excessdustiness and consequent material loss are frequently encountered when finely ground PR is handled during transportation and application. Granulation of PR can eliminate objectionable dust, but it can also, as with increased particle size, lead to a reduction in the short-term P availability (Tennan et af.,1969;Engelstad et af.,1974; Chien and Hammond, 1978a). Granulation of PR to conventional fertilizer size ranges can be accomplished either by wet granulation (Cannon, 1979) or by dry compaction technology (Lupin and Le,1983).In either process, a small amount of binder (2 - 5%) is frequently added to improve the physical properties of the granulated products. When making compound NPK fertilizers, N and K fertilizers, e.g., urea and KC1, can also be used as binders. However, because any of these granulation processes reduce agronomic effectiveness, attempts have been made to produce smaller granules to reduce dust problems. The small-sized granules have been produced by a method called minigranufation, which was developed by IFDC (Peng and Hammond, 1979;Livingston,

103

PHOSPHATE ROCKS IN THE TROPICS

1979). This process uses a pin-type mixer and binders such as KC1, urea, H,S04, or H3P04. On the basis of results of greenhouse trials (Chien and Hammond, 1978a; Peng and Hammond, 1979; W. E. Fenster and L. A. Lebn, unpublished, 1980)a size range of minus 48/plus 150 mesh has been adopted by IFDC as defining a “minigranulated” PR. In the experiment conducted by W. E. Fenster and L. A. Lebn (unpublished, 1980), five PRs including Araxa (Brazil) and Pesca (Colombia) were tested in five different granule size ranges. Using corn as the test crop (three harvests), the researchers found that there were no significant differences between finely ground and minigranulated PR. There were, however, significant yield reductions when conventional size granules (minus 6/plus 14 mesh, 1.4-3.3 mm) were used. Minigranulation of PR is considered, therefore, as a potentially effective method to improve the handling characteristics of the PR for use in those tropical environments where unacidulated PR is found to be agronomically effective in a finely ground form. The adoption of this technology will depend to a large extent on the cost of production. It has been estimated that under current conditions the additional cost of the product due to the minigranulation process would be approximately $18 to $22 per mT (A. Roy, IFDC, personal communication). Conventional solubility measurements for finely ground PR are not suitable for measuring the agronomic potential of granulated PR because the granules disintegrate during the extraction with shaking. In order to eliminate this problem, Chien and Hammond ( 1978a) developed a simple, nonshaking method of evaluating the solubility of granulated PR by mixing Table VI Solubilities and Crop Yield Obtained with Two Granulated Phosphate Rocks“ Soluble P (% of rock) Conventional citrate method Granule size (mesh)

North Carolina

-6/+ 14 - 14/+28 -48/+ 100 - loo/+ 200

3.0 3.0 3.1 2.8

a

Proposed H-resin method

Bayovar

North Carolina

2.9

0.6

2.1

1.5 3.0 3.5

3.1 2.1

From Chien and Hammond (1978a). P rate = 200 mg P/kg soil. Control = 3.2 &pot.

Bayovar 0.8 2.0 3.3 3.1

Dry matter yield (&pot)’ North Carolina 5.1 14.1

26.0 34.4

Bayovar 5.6 16.6 27.0 31.8

L. L. HAMMOND ET AL.

104

H-resin and sand. The H-resin not only provides the sink for Caz+ionsin the solution but also provides H+ ions to dissolve PR. A similar approach was also developed by Gillon and Hagin ( 1979) except they provided an additional anion resin as a sink for the dissolved P. In the study of Chien and Hammond (1978a),there was little difference in conventional citrate solubilityof granulated PRs between samplesregardless of granule size, whereas the actual crop yield decreased with increasing granule size (Table VI). In contrast, the H-resin method more realistically measured a steady decrease in solubilitywith increasinggranule size. Consequently, no correlation was found between conventional citrate solubility and crop yield, whereas a significant linear relationship was found between crop yield and H-resin solubility.

V. SOIL FACTORS INFLUENCING EXPRESSION OF AGRONOMIC POTENTIAL The influence of the chemical and physical properties of the PR itself on the ability of the PR to provide plant-available P has already been discussed. In addition to those factors, it is well recognized that the properties ofthe soil and cropping system determine how well a water-insoluble P source will perform relative to conventional soluble fertilizers. Upon application of P to the soil, both the rate of dissolution and the fate of the P released are determined by the chemical reactions which occur in the soil and the pattern of P uptake by the crop. A. SOILpH, EXCHANGEABLE Ca, AND P RETENTION CAPACITY

Dissolution of PR in soil solution, using fluorapatite as an example, may be simply expressed as Ca,,(PO,),F,

+ 12H+

+

+

10Ca2+ 6HzP04 2F-

From the mass action law, it can be seen clearly that dissolution of PR in soil solution would be favored under the conditions that (1) soil pH, (2) soil exchangeable Ca, and (3) soil solution P concentration are low. For many tropical acid soils, both exchangeable Ca and soil solution P concentration are relatively low, thus providing favorable conditions for PR application. It can also be seen that liming the acid soils always results in a reduction of PR dissolution, due to the fact that both soil pH and exchangeableCa are raised upon liming. To separate the effect of soil pH from that of exchangeable Ca,

PHOSPHATE ROCKS IN THE TROPICS

105

Khasawneh and Doll (1978) compared the effect of CaCO, with that of S r C 0 3 on the agronomic effectiveness of North Carolina PR and found that S r C 0 3 depressed the plant yield less than CaC0, did at the same soil pH after liming. These topics have been reviewed in considerable detail (Khasawneh and Doll, 1978) and will not be developed further. The role of the P retention capacity of the soil, however, is less well understood. It has been theorized that, despite the fact that PRs are normally less efficient than soluble P sources even in acid soils, the relative agronomic efficiency of the PRs compared with superphosphatewill be higher in soils with high P retention capacity than in those with lower P retention capacity because the slow PR solubilization increases the opportunity of the plant roots to take up the P before it passes to unavailable forms (Nufiez, 1984). From the standpoint of the rate of dissolution of the PR in the soil, this theory has in fact been supported by a number of researchers. In an incubation study with acid soils from the Cerrado of Brazil, Smyth and Sanchez (1982) showed that the decomposition of PR increased with an increase of the P retention capacity of the soils (Fig. 2). A similar conclusion was also reached by Syers and MacKay (1986) in a study involving Bayovar PR and acid soils in New Zealand. Chu et al. (1962) reported that the increased

0

A Palos de Minas (Brazil) U as In 0

.n

E

0

60 -

'

0 0

u W

A0

0

W U

0

40

A

L

m

r m

A

0

0 In

E 20

-

A

A A

A 0

I

I

I

I

I

100

200

300

400

500

P Sorption Capacity (llglg soil)

FIG. 2. Decomposition of phosphate rocks in acid soils as influenced by soil P sorption capacity. (Data from Smyth and Sanchez, 1982.)

106

L. L. HAMMOND ET AL.

decomposition of PR may be due to the more effective removal of H2P0: ions from solution by Fe minerals in the high-Fe soils. They suggested that the rate-limiting reaction is that of PR breakdown and that A1 phosphates and/or Fe phosphates are formed almost immediately thereafter. Working with 16 acid soils including Oxisols, Ultisols, and Inceptisols from Colombia, Chien et al. (1980b) found that the amounts of water-extractable P in the soils treated with North Carolina PR decreased as P retention capacities increased. However, the relative amounts of water-extractable P from PR as compared with that from TSP increased as P retention capacities increased. Although PR dissolution increases as soil P retention capacity increases, it does not necessarily result in an increase in the amount of plant-available P in the soil. Smyth and Sanchez ( 1982)and Syers and MacKay ( 1986)found that extractable P (Olsen, resin, and Bray I) in the soils treated with PRs decreased as soil P retention capacity increased. Consequently, Syers and MacKay (1 986) found that plant yield obtained with PR, as well as with single superphosphate (SSP), decreased with increasing soil P retention capacity. However, they did not study the relative effectiveness of PR with respect to SSP as influenced by the P retention capacity. Crop response data collected by a number of researchers in Mexico (Adan et al., 1980; Marval, 1975; Alvarez et al., 1981; Guzman et al., 1980)were reviewed by Nuiiez (1984). It was observed in this review that the relative efficiency of the PRs tested in comparison with TSP was invariably higher in the high-P-retaining Andepts than in soils with lower P retention capacities. Although this trend was in fact observed, the influence of P retention capacity on the relative effectivenessof PR would not satisfactorily be determined on the basis of these comparisons because other soil properties also differed from soil to soil. In one case, for example, Marval(l975) found that PR was 78% as effective as TSP when applied to an Andept in which 90% of the soluble P applied was fixed. The three other soils included in the test ranged in relative effectiveness from only 25 to 48% despite the fact that the P retention ranged from only 1 1 to 6 1%. Although this would seem to verify that relative effectiveness increased with increasing P retention, it is important to note that the pH ofthe Andept was 5.5 and that ofthe other three soils from 6.3 to 7.8, which suggeststhat pH may have reduced the effectivenessof the PR to a greater extent than did P retention capacity. Examination of field data reported by Hammond and Lebn ( 1983),on the contrary, indicated that finely ground PRs applied to Latin American Oxisols and Ultisols were relatively more effective with respect to TSP than the same PR sources applied to Andepts which exhibited significantly higher P retention capacities than did the Oxisols and Ultisols. In this case, however, the Oxisols and Ultisols were more acidic than the Andepts and the indicator

107

PHOSPHATE ROCKS IN THE TROPICS

crops were not identical. In an attempt to clarify these conflicting observations, a greenhousestudy was conducted by Hammond et al. ( 1986) in which Bayovar PR from Peru was applied to a single soil which had previously been treated with varying levels of an amorphous iron gel to provide a range in P retention capacities while maintaining a uniform pH. These results showed that both TSP and the PR declined in effectivenessas the P retention capacity of the soil increased, but the PR tended to decline at a more rapid rate (Fig. 3). Results of greenhouseexperiments(IFDC, 1982) using the highly reactive Bayovar PR illustrate this effect by means of the preapplication approach. The soils were Mountview silt loam (Typic Paleudult)and Hartsells silty clay loam (Typic Hapludult). The Hartsells soil had a higher capacity to sorb added P. Incubating the Bayovar rock in the Mountview soil for 6 weeks before planting did not affect the yield of maize. Yields were generally lower in the Hartsellssoil, and incubation for 6 weeks significantlydepressed yield. From these results it would seem that PRs perform better in soils with reduced tendency to immobilize soluble phosphorus. This is in agreement with the findings of Hammond et al. (1986). Observations from the Philippines and Indonesia reported by Harris et al. (1984) also tend to support the finding that high P retention capacity can have a strong negative influence on the effectivenessof PR. In experiments conducted with corn on an Andept and an Ultisol, both with pH near 5.0, PR Bayovar PR

TSP

0

150

P Applied (mg P/kg)

300

0

150

300

P Applied (ms Wkg)

FIG.3. Influence of P retention capacity on maize response to P from TSP and Bayovar phosphate rock.C,, C, ,C,, and C, equal 0,0.33,0.66,and 1.0 MFegel applied, respectively. Vertical bars illustrate percent reduction in effectivenessas compared to Co. (From Hammond et al.. 1986.)

108

L. L. HAMMOND ET AL.

was found to be similar in effectivenessto TSP on the Ultisol but inferior on the Andept. It was concluded that low P-retention capacity contributed to the positive performance of PR on the Ultisol. Although the mechanisms involved have not yet been defined, one can speculatethat the reduced effectivenessof PR on soils with high P-retention capacity is related to reduced root development in the early stages of growth. Despite the fact that high P retention by the soil may promote a more rapid dissolution of the PR, concentrationof P in the soil solution will be limited to a low level controlled by the solubility product of the solid-phase apatite in the PR (Khasawneh and Doll, 1978).This P, of course, is just as susceptible to retention by the soil as is P derived from TSP. If development of the plant root system is depressed by the initial low concentrationsof P from the PR, it followsthat the probability for interception of immobile P concentrations in the soil by the roots will be reduced and the proportion of P left to react with the soil will increase. Quantification of these influences is still required in order to adequately predict which soils are most suited to effective use of PR.

B. SOILORGANIC MATTER Soil organic matter is known to enhance the dissolution of PR (Drake, 1964). Certain soil organic matter, upon hydrolysis, may supply some organic function groups or anions such as citrate and oxalate that can effectively chelate Ca2+ions and thus lower the Ca2+activity in soil solution. This in turn provides a driving force for further dissolution of PR. The mechanisms also may explain, at least in part, the beneficial effect of farmyard manures on increasing P availability from PR utilization (Guzman el al., 1980; Villarroel and Augstburger, 1984). Most researchers have assumed that the organic acids produced from the manures enhanced the PR dissolution. Direct evidence of chelating Ca2+ions by the hydrolyzed soil organic matter was recently demonstrated by Chien (1 979b). In this study, soil organic matter was extracted with water after urea had been added for 2 weeks. The extracted soil organic matter suspension was then used to dissolve PR. It was found that a significant amount of soluble P was liberated from PR, despite the fact that the pH of the extracted soil organic matter suspension was around 9.0. However, the amount of water-soluble free CaZ+ ions was very low as measured by a Ca ion-specificelectrode,suggestingthat Caz+ions were probably complexed by the soil organic matter. When the soil organic matter was flocculated by adding a few drops of acid followed by centrifugation, a significant amount of free Ca2+ions was found in the solution, indicating a liberation of chelated Ca2+into the solution after the Ca - organic matter complex was decomposed.

PHOSPHATE ROCKS IN THE TROPICS

109

C. SOILTESTMETHODOLOGY Three acid methods- Bray I, Bray 11, and North Carolina double acidhave been widely used to measure available P in acid tropical soils. These methods, however, were developed for fertilizerrecommendation for watersoluble P sources such as TSP or SSP. Both Bray I1 and double-acid methods use a relatively high concentration of HCl that can dissolve a substantial amount of the undecomposed PR during extraction and thus can overestimate the available P from PR in the soil as compared with that from TSP. The two methods also cannot distinguish the available P in the soil treated with different sources of PR (Barnes and Kamprath, 1975; Van Raij and Van Diest, 1980). Therefore, neither Bray I1 nor double-acid methods should be used for soil testing for available P from PR. Available P as extracted by Bray I in the soil has been shown to correlate well with chemical reactivity of PR (Chien, 1979a; Hammond, 1979) and with plant yield and P uptake (Barnes and Kamprath, 1975; Hammond, 1979; Syers and MacKay, 1986). However, the data obtained with the Bray I test should be interpreted with caution. In the past, Bray I solution was assumed to measure only the release of P from the reaction products of PR and not the undecomposed PR in the soil. To extract the undecomposed PR in the soil, Bray I1 was recommended (Bray and Kurtz, 1945). This assump tion may be valid if the soils are neutral or limed soils and the PRs used are relatively unreactive. As pointed out by Chien ( 1978), Bray I can still dissolve a significant amount of undecomposed PR in soils when the soils are very acid, such as in the tropics, and the PRs used are reactive, such as Bayovar PR (Peru). Barnes and Kamprath (1975) were probably the first to report that two distinct curves were obtained when the Bray I P level from two PRs and TSP was plotted against dry matter yield of corn. These curves indicate that corn yield obtained with a given Bray I P level with PR was higher than that with TSP. Subsequently,Hammond ( 1979) and Reinhorn and Hagin (1979) also observed similar results, as shown in Fig. 4. Chien (1978) suggestedthat Bray I solution can extract P from the reaction products of PR as well as from the undecomposed PR in the soil, and both sources can provide plant-available P. In the TSP-treated soil, only the reaction products of TSP are extracted by Bray I solution, and thus the Bray I curve of TSP differs from that of PR. It appears that the fertilizer P recommendation as based on water-soluble P sources cannot be applicable to PR because of different calibration curves. The Bray I P method can be used for PR for direct application; however, its calibration with plant response needs to include the influence of chemical reactivity of PR. More research is needed to develop a suitable soil test that enables us to make a recommendation of the rate of PR application in a given rock - soil - plant system. Tests on a new procedure developed with this

110 28

L. L. HAMMOND ET AL.

-

(a) Guinea G n u

't

14

24 -

I 0

Bny I-Extncbble

Bray I.Ertnctable P (ppm)

P (ppm)

FIG.4. Relationship between dry matter yield and Bray I-extractable P in soils treated with phosphate rocks and TSP. [Data from (a) Hammond, 1979, and (b) Reinhorn and Hagin, 1979.1

need in mind have recently been reported by Hammond et al. ( 1985).It was designated the Pi soil test because it utilizes an iron-impregnated paper strip as a sink for P during extraction rather than an extracting solution to dissolve P compounds in the soil. Early results indicate that calibration curves are neutral to P fertilizer source.

VI. CLIMATIC FACTORS INFLUENCING EXPRESSION OF AGRONOMIC POTENTIAL A. RAINFALL

The influence of rainfall on the effectiveness of PR has been an area of concern, particularly in Africa. As early as the 1950s,work done in Senegal (Bambey, 1957) showed that the fertilizer efficiency of PR increased with increasing rainfall. In a series of trials over a range of mean annual rainfall between 500 and 1300 mm, the yield increases of groundnuts over control showed a highly significant linear correlation with the mean annual rainfall for the first 2 years following basal fertilization. These early results are presented in Table VII. Similar results were obtained by Bockelee-Morvan (1966) in Senegal, Dupont de Dinechin (1967b) in Burkina Faso, and Pieri (unpublished, 1971) in Mali. Rainfall is important not only for annual fertilizationbut also for basal fertilization.In general, response to PR is more erratic under low-rainfall conditions. Increased solubility of PR in moist soils could result from the low-pH status of such soils. Soils in humid environments also have higher organic matter contents. Soil organic matter can complex Ca in apatite, thereby increasing the solubility of the apatite.

111

PHOSPHATE ROCKS IN THE TROPICS Table VII Rainfall and the Effectivenessof Basal Phosphate Rock Dressings"

Mean effective rainfall in fallow and groundnut years

Site of phosphate application

Year

Ferkessedougou Sefa Nioro Katibougou Sinthiou Boulel Nioro Saria Bambey Boulel Bambey Tama

1955 1954 1954 1954 1954 1954 1955 1955 1954 1955 1955 1955

Groundnut yield increase over control

(mm)

-

-

1296 108 1 924 896 884 876 83 I 785 736

+25 23 22 12 12 12 20 +8

I00 558

+ +

+ +

+ + + 10 -6 -6

Rainfall in cereal year

Cereal yield increase over control

(mm)

(%I

1833 I194 653 1088 1199 666

-

752 610 972 677 704

+ 17 +28

+ 10 +23 +28 +23 + 38 -3 +26 -11

+6

From Bambey (1957).

In Francophone West Africa, PR was not recommended either for annual or basal fertilization where the rainfall was below 700 mm.

B. TEMPERATURE Temperature has been found to have no significant effect on the dissolution of PR in soil (Fig. 5). This implies that P availability in tropical soils treated with PR may be much less affected by temperature as compared with that in water-soluble P fertilizers (Chien et al., 1980a). Thus, the influence of temperature on the agronomic effectiveness of finely ground PR is most likely an indirect result of the influence of temperature on the rate of physiological development of crop. Since the availability of P from PR for plant uptake is controlled by the rate of dissolution of the PR, P can continue to be released into the soil solution for a long period of time. The greatest utilization of that P can be expected, therefore, if the length of time during which the P is being extracted by the plant is extended. In Colombia, researchers from IFDC and the Colombian Institute of Agriculture (ICA) collaborated on investigations measuring the relative agronomic effectiveness (RAE) of local phosphates in farm-level trials in a number of agroclimatic zones (Le6n and Ashby, 1984). Field beans were

112

L. L. HAMMOND ET AL. TEMPERATURE 0 15°C 0 25°C A 35°C 45°C x 55°C

3.5 F

*

3.0

-

2.5

E

E

Q

-n

2.0

a2

-3 0

y

.2

1.5

L

0)

1.0

00

10

20

30

40

50

60

70

Time (hours)

FIG.5. Dissolution of North Carolina rock in Weston soil at differenttemperatures. (Data from Chien ef af.,1980a.)

grown on 14 sites near Pescador (Cauca) representing mid-altitude tropical conditions(a1titude 1000-2000 mad, mean temperature 17.5-23.0"C) and on 9 sites near Ipiales (Nariiio) representing highland tropical conditions (altitude 2000-3000 masl, mean temperature 12.0- 17.5"C). It was observed that finely ground Huila PR (Colombia) ranged from 15 to 87% as effective as TSP with a mean RAE of 6 1% in the Pescador region, whereas in the Ipiales trials there was no statistically significantdifference between the two P sources. Although some of the difference in performance between the two regionscould be attributed to other factors such as bean variety, management, and soil properties, the researchers also cited climate as a significant factor. Because of the colder climate in the highland region, where superior performance of the PR was observed, the growing season for beans spans 9 months; at the lower altitudes the beans were harvested within 3 months.

VII. PARTIAL ACIDULATION OF PHOSPHATE ROCK Partial acidulation of PR represents an alternative for use of indigenous PR deposits that are too low in reactivity for use as PR but may also be

PHOSPHATE ROCKS IN THE TROPICS

113

unsuited (for either technical or economic reasons) for the production of conventional fertilizer. Acidulation of PR with sulfuric acid to produce SSP or with phosphoric acid to produce TSP has been known since the 1800sto be an effective means of increasingthe solubility (and plant availability)of P from apatite. As opposed to these products in which a PR is treated with the theoretical (stoichiometric)quantity of acid required to fully convert insoluble phosphate minerals to water-soluble monocalcium phosphate monohydrate (MCP),PAPR utilizes only a portion of the quantity ofacid required to fully convert the apatite to MCP. The "% PAPR" nomenclature used in this review refers to the proportion of acid used to prepare the PAPR relative to the quantity of acid which would have been required to produce superphosphate from that particular PR. Thus, 50% sulfuric acid acidulation refers to the use of 50% of the H2SO4 required to produce SSP, and 50% H3P04 acidulation refers to 50% of the phosphoric acid required for TSP. Partially acidulating PR represents a technology that can improve the agronomic effectiveness of an indigenous PR at a lower cost than would be required to manufacture conventional fertilizers from that same rock. As will be shown in subsequent sections, there are numerous sets of conditions under which adequate yields cannot be obtained by using unacidulated PR as the sole source of P despite the low cost of the material. It has been reported that PAPR may be similar in cost to imported TSP (Sanchez and Salinas, I98 I), but if local policy has determined that it is in the national interest to develop technology so that these indigenous deposits can relieve some of the dependence of the country on foreign imports, PAPR is thought to offer the following advantages (IFDC, 1986): 1. In agronomic terms, it can provide a portion of the P in a readily plant-available form and the remainder in a form which should enhance residual value. 2. When H3P04is used, the PAPR increases the concentration of Pabove that of the unacidulated PR. 3. When H2S04is used, sulfur is included in quantities appropriate for many nutritional demands. 4. The amount of acid required is reduced. 5 . Production capacity of the manufacturer is increased. 6. Rocks that are unsuited chemically for the production of superphosphates can be used for PAPR.

A. PAPR CHARACTERISTICS

Since PAPR is the product of the acidulation of PR with less than the quantity of acid required for superphosphate,it contains variable quantities

114

L. L. HAMMOND ET AL.

of water-soluble, neutral ammonium citrate (NAC)-soluble, and NAC-insoluble fractions of P depending upon (1) the reactivity of the PR used, (2) the quantity of acid used, (3) the impurities in the rock, and (4) the process conditions used (IFDC, 1986). In H2S0,-based PAPR, therefore, the final product is essentially a mixture of monocalcium phosphate (MCP), unreacted PR, and CaSO,. The difficulty in predicting the exact composition of PAPR produced from a given PR is discussed by IFDC ( 1986)where the equation for the reaction of sulfuric acid to form SSP or PAPR is given as

+

Ca#O4)6Fz 7Y HZSO,

+ 3Y HZ0-

3YCa(HzPO4), . HZO 2Y HF

-k 7Y M O ,

+

+ (1 - Y ) Calo(PO4)6Fz

In this equation the Y term representsthe degree of acidulation;i.e., Y = 1.O for 100% acidulation (SSP) and Y = 0.5 for 50% PAPR. The equation, however, does not reflect the role of the nonfluorapatite components of the PR, which may significantly alter the reaction chemistry. Examples ofthe attributes of PAPR related to rock impuritiesare given by IFDC ( 1986).As one example, the Kodjari deposit in Burkina Faso is identified as a rock well suited to production of PAPR because it is very unreactive and contains relatively high levels of silica, iron, and aluminum. It is therefore difficult to fully acidulate and results in a pastelike material with poor physical properties when acidulation proceeds above 50%. Poor physical properties can also result from CaSO, cementation if PAPR is dried at an excessivetemperature (Hammond et al., 1980).It appearsthat dissolution of PAPR was inhibited by poor physical properties in early studies on these products (Sanchez and Uehara, 1979; Khasawneh and Doll, 1978), and the result was poor agronomic performance. Technology is now available to produce highly acceptable products (IFDC, 1986). B. REACTIONS OF PAPR IN SOIL

Studiesby McLean and co-workers(McLean and Wheeler, 1964;McLean et al., 1965;McLean and Balam, 1967; McLean and Logan, 1970)indicated that finely ground PAPR (10-20% acidulation with H3P04)was as good as or better than TSP for soils with high P retention capacity. On the other hand, Terman and co-workers ( 1964, 1970; Terman and Allen, 1967)and Hammond et al. ( 1980)reported that granulated PAPR was inferior to TSP in greenhouse studies and noted that the effectiveness of the various materials was rather closely related to their water solubility. Such differences in results apparently are related to the granule size, solubility of the PAPR materials (physical properties), and soil pH used. McLean and Wheeler ( 1964)suggested that dissolution of the MCP com-

115

PHOSPHATE ROCKS IN THE TROPICS

ponent of TSP would encouragethe formation ofthe less soluble aluminum phosphate and iron phosphate compounds because of MCP hydrolysis in soil, whereas part of the acidity produced by MCP hydrolysis would be neutralized by the unacidulated PR. Not only does this protect the water-soluble P of PAPR from reacting with substantial quantities of A1 and Fe but could also result in added P being released into the water-soluble P pool from the reaction of the acid with unacidulated PR. This hypothesis has been recently supported by Mokwunye and Chien (1980), who found that soil solution P concentrations obtained with PAPR and extended superphosphate relative to TSP (all in powdered form) increased with increasing P sorption capacity of three tropical soils (Fig. 6). Furthermore, powdered PAPR was more effective than powdered extended superphosphate in providing soil solution P concentration, suggesting a closer proximity for the interaction between MCP and unacidulated PR in the PAPR material. When both PAPR and extended superphosphatewere granulated and compacted, respectively, to the same granule size (minus 6/plus 14 mesh), the two P sources were found to be similar in supplying available P in the soil (Chien et al., 1986b). Other evidence to support the interaction between MCP and PR in the

aExtended superphosphate PAPR

Maiduguri

Jos P Sorption Capacity

Gaviotas c.

c

FIG. 6, Effect of P-fixing capacity on the relative water solubility of PAPR and extended phosphate in three soils. (Data from Mokwunye and Chien, 1980.)

116

L. L. HAMMOND ET AL.

materials of PAPR and extended superphosphate was presented by Logan and McLean ( 1977). They observed that diffusion of 32Pfrom labeled 100% acidulated PR was substantially increased when unlabeled PR was added to the matrix. Diffusion of TSP in soil without PR in the matrix was lower than diffusion of PAPR.

VIII. REGIONAL FINDINGS ON DIRECT APPLICATION OF PR AND PAPR A. LATINAMERICA

The agronomic effectiveness of directly applied Latin American PRs has been observed to be highly variable. This is not unexpected, because of the differencesin the chemical solubility of the PRs and the great diversity in soil and cropping systems in the region. A concerted effort has, therefore, been mounted by a number of national and international institutions in Latin America to identify specific sets ofconditions under which finely ground PR can be expected to be effective and, equally as important, to identify those sets of conditions under which the use of PR should not be recommended. The experimentalapproach has been to quantify the influence ofthe individual factors controlling agronomic effectiveness (chemical reactivity of the local sources, particle or granule size, soil properties, crop type, fertilizer management, residual effect, etc.), to evaluate the interactions between them, and to determine if PAPR is a suitable alternative in those cases where PR alone is not economically effective.

1. Influence of Agro-Edaphic Variables One of the primary target areas for the evaluation of unacidulated PR has been in the lowland tropics, where the soils are generally acid Oxisols and Ultisols which are highly infertile, especially with respect to P. According to Sanchez and Salinas ( 1 98 I), approximately 82% of the soils in the Latin American tropics (23"Nto 23"s)exhibit a deficiency of P for crop production and approximately822 X lo6ha (or 55% ofthe total distributionofsoils in the Latin American tropics) are classified in these two orders. Extensive frontier-type agriculture is typical on these soils and the use of fertilizer is minimal. The Llanos of Colombia and Venezuela, the Cerrado of Brazil and the Amazonjungle region are examples of extensive areas dominated by acid Oxisols and Ultisols.

PHOSPHATE ROCKS IN THE TROPICS

117

In Oxisols from the Colombian Llanos, a number of experiments have been conducted to compare P sources. In a review by Le6n et al. (1978), results of experiments conducted during the period 1969- 1971 are discussed in which Turmeque PR (Pesca-type PR) was compared with TSP, both at 200 kg P20,/ha, and with a mixture of PR and TSP. Corn was the indicator crop, and the soils were extremely acidic (pH 4.5-4.6, A1 saturation 65-72%). In these studies it was observed that the Colombian PR (low-medium reactivity)was relatively ineffectiveduring the first year at one site but was equally as effectiveas TSP during the next 2 years. At a second site, the PR was equally as effective as TSP during each year. The most effectivetreatment in both locations, however, was a basal application of PR at a rate of 200 kg P20,/ha plus 20 kg P20,/ha of TSP banded at planting. Also reviewed by Le6n et al. ( 1978) were experiments conducted during 1974 - 1975 with the same PR and with peanut as the indicator crop. In this case, the PR was only about one-half as effective as TSP or basic slag during the first cropping period but, as before, gave results similar to those with the more soluble sourcesduringthe second year ofcropping. It was also shown in this experiment that when the PR was banded the effectiveness during the first year was substantiallyreduced, but the residual availabilityof P was high during the second cropping period. On a similar Oxisol, Hammond and Le6n ( 1984) reported on a study with the use of Huila PR (Colombia) and with rain-fed rice as the indicator crop (Fig. 7). It was observed that there was no significant difference in effectiveness between Huila PR (medium reactivity) and TSP under the conditions tested, irrespective of the level of supplemental fertilizers supplied or the variety of rice utilized. Le6n et al. (1978) referred to studies by Howeler (1 974) who also studied the effect of various P sources on the production of irrigated rice in an acid Oxisol of the Colombian Llanos. It was reported that in that location TSP and North Carolina PR (a highly reactive PR) were the most effective sources and the less reactive Colombian PRs (Turmeque and Huila) were the least effective. This relationship between source effectivenessand chemical solubility of the PR was confirmed by Hammond (1977) in a series of studies with cassava, Brachiaria decumbens, and Panicum maximum grown on Oxisols with pH ranging from 4.2 to 4.5 (Fig. 8). In the field experiments with cassava and pasture, the highly reactive PRs (North Carolina and Bayovar) were nearly as effective as TSP up to 100 kg P20,/ha during the first crop. In the case of cassava, yields increased from only 7 tons/ha without added P to over 20 tons/ha with 100 kg P205/hafrom these sources. In addition, this site was replanted to cassava for 3 additional years without additional application of P. All sources showed high residual value at the initial rate of 400 kg

118

L. L. HAMMOND ET AL. 3600

-

3200

-

CICA-8

METICA-1

Huila PR With K. Mg. S, 8, Zn TSP

S, B, Zn

>yg,TSP

2800.

-=

f r

Huila PR

2400.

.-

6 rn

-L

2000-

,L; -‘‘*Huila

TSP Without

PR

I

Zn

II

I I

400 4

J’

I

0

L

20 40 60 P Applied (kglha)

0

20 40 60 P Applied (kglha)

FIG.7. Response of rain-fed rice to Huila phosphate rock. (From Hammond and LeBn, 1984.)

P,O,/ha and no significant differenceswere observed between sources (L. L. Hammond, unpublished). The experiment with B. decurnbens illustrated in Fig. 8 was also continued to study residual effect (Hammond et al., 1982). Figure 9 shows the average annual production of B. decumbens following a single application of either PR (mean of six different PR sources) or TSP during a 5-year period. Characterization work on the soil samples taken after 5 years revealed that the amounts of undecomposed PRs in the soil were less than 20%of that initially applied (Chien et al., 1986a). It was concluded that the initial differences between sourcesdue to solubilityof the sources persisted only during the first year and that there were no significant differences between sources when the accumulative production over the 5-year period was considered. The results described above were all obtained on Oxisols from the Colombian Llanos and are highly encouraging with regard to the possibility of substituting national PRs for the more expensive fertilizers in that region, especiallyin the case ofpasture production and possibly with a range of other

119

PHOSPHATE ROCKS IN THE TROPICS ilo,-

GUINEA GRASS (Greenhouse)

P

r

CASSAVA (Field)

-

a

BRACHIARIA (Field)

-

0

Medium Solubility

A Low Solubility 0 PzOs (kglha)

I

'

1bo I 200 3;o PZOS(kglha)

I

4iO

FIG.8. Relative agronomiceffectiveness of different phosphate sources.(From Hammond, 1979.)

crops if the value of the residual P is taken into consideration. Results have not been as encouraging, however, on other Latin American Oxisols. In the Cerrado of Brazil, for example, a number of researchers have reported that local Brazilian PRs exhibit low agronomic effectiveness (Goedert and Lobato, 1980; Van Raij and Van Diest, 1980;Cabala-Rosand and Wild, 1982; Smyth and Sanchez, 1982). In a review, Goedert (1983) cites an example in which the Patos, Araxa, and Catalao PRs were only 43, 36, and 20% as effective as TSP when measured over six annual crops. These differencescan be explained by a number of factors. First, the reactivities of the Brazilian

120

L. L. HAMMOND ET AL.

70

1

60

-

50

-

40

-

c

m

-s M c a al

5u

n al

30 c 0

W TSP-Annual Application UTSP-Residual (1 Application) A-A PR-Residual (1 Application) (mean of 6 sources)

20.4

10

I

0

,

11 22

1

I

176

44

Rate 01 P Applied (kg V h a )

FIG. 9. Average annual production of Brachiaria decumbens during five years. (From Hammond ef al.. 1982.)

PRs are substantiallylower than those ofthe sourcestested in the Colombian Llanos (Fig. 1). Second, the yield levels in the Brazilian Cerrado may have been higher (higher input agriculture places greater stress on P solubility), and third, the soils of the Cerrado exhibit higher P retention capacity. Results more similar to those observed on the Colombian Oxisols have been obtained on Ultisols of the Amazon basin. In Peru, experiments with Bayovar PR have been conducted in experiment stations both in Yurimaguas and Pucallpa. In Yurimaguas, a rotation of corn, soybean, and rice was grown to compare the effectivenessof the highly reactive Bayovar PR with soluble TSP (Bandy and Lebn, 1983).From these studies, it was concluded that the PR was equally as effective as TSP and offereda good substitute for imported fertilizer. Similar conclusions were drawn from studies in Pucallpa, Peru, using cassava, B. decumbens, and Stylosanthes capitata as the indicator crops. Although the extension of Oxisols and Ultisols dominates the lowland tropics, present agricultural production is generally centered in the highlands. Andepts and associated Inceptisols are typical soils in this region and represent approximately 16% (235 X lo6 ha) of the soils of tropical Latin

PHOSPHATE ROCKS IN THE TROPICS

121

America (Sanchez and Salinas, 198I). In contrast to the Oxisol and Ultisol region just discussed, the highlands region is dominated by intensive subsistence agriculture, steep slopes with severe erosion hazards, soils with generally higher pH and fertility levels, but also soils with volcanic ash influence and substantially higher P retention capacities. Numerous observations concerning the use of PR in cropping systems of the Latin American highlands have been reported from countries including Mexico (Montes et al., 1983),Costa Rica (Ramirez, I984), Colombia (Le6n and Hammond, 1984), and Peru (Davelouis et al., 1977). In a review by Montes ef al. ( I983), results from field studies conducted by Trinidad ef al. (1980) in eight locations in the Sierra Tarasca, Mexico, were discussed. In those locations, corn was grown on acid Andepts followingapplication of PR from San Hilario, Baja California. It was reported that a positive response was obtained with the PR relative to the check where no P was applied but the response to P from SSP was consistently superior. For example, it was observed that in the four experiments conducted in 1980with an application rate of 120 kg P,Os/ha the RAE of the PR averaged 87% when compared with the SSP. An additional treatment included at that rate of application in which supplemental S was applied verified that the response to SSP was not influenced by the S content of the fertilizer. In experiments conducted with field beans on an Andept from Colombia (Chien and Hammond, I978b), positive initial response to PR to the degree reported in Mexico was observed only with highly reactive sources.Gafsa PR (Tunisia),for example, was 87%as effective as TSP during the first cropping period; Huila PR (Colombia), however, was reduced to 66% as effective as TSP, and Pesca PR (Colombia)was only 7% as effective as TSP. Cropping was continued in this experiment without additional applications of P to observe the difference in residual P availabilitybetween sources. In Fig. 10,it can be seen that the highly reactive PRs (Gafsa and North Carolina) were equal to or better than TSP in providing residually available P in each of the three subsequent crops. The medium-reactivity PRs (central Florida and Huila) tended to increase in effectiveness until they became equal to residual TSP in the third crop. The PR with the lowest reactivity in the trial (Pesca) increased sharply in effectiveness through the first three crops as compared with TSP, increasing from only 7% in the first crop to 27 and 82%as effective as TSP in the second and third crops, respectively. Yields were substantially improved, however, by repeated application of TSP prior to each crop. Focusing on Bayovar PR from Peru (a highly reactive PR), a number of studies have now been completed in the highlands as well as in the lowlands of Peru. Lopez ( 1985)has reviewed the results of 25 of these investigations. Numerous examples are cited confirming the positive response of a wide range of crops to finely ground Bayovar PR. Again, it is pointed out that in

L. L. HAMMOND ET AL.

122 300 -

P

TSP Repeated (352 kg Plha total)

v)

I r .-W>

p

180 -

E

w

.-E

U

L U

-.-1B

140-

100 -

02

eE

/*7""

C. Florida

i

2

3

4

Crop Number

FIG.10. Relative agronomic effectiveness of five phosphate rock sources as compared to residual and fresh TSP at 88 kg P/ha during four consecutive crops of beans (Los Guacas, Popayhn, Colombia). (From Hammond and L e h , 1983.)

many of the cases, especially in the highlands where potatoes and wheat are grown on high-P-retaining soils, yield response is usually lower than that observed with soluble sources. Villagarcia er al. ( I978), for example, found the Bayovar PR to be approximately 70%as effective as soluble sourceswhen growing potatoes over a 4-year period. Mixtures of the Bayovar PR with other soluble fertilizers (TSP, SSP, DAP, manure, etc.) were also evaluated, and were found to be similar in effectiveness to the soluble sources alone. In a seriesof 13 field experimentsin which PR from Bolivia was compared with TSP and other fertilizer for potato production on soils ranging from pH 4.6 to 6.5, it was observed that the average 9.5% improved response to I20 kg P205/hafrom the PR was not statistically superior to the check where no P had been applied (Villarroel and Augstburger, 1984). However, the yield response to TSP was low and TSP was statisticallysuperior to the PR in only 3 ofthe 13sites. In all cases, yieldswere extremelylow ( 10.9 tons/ha average), indicating either that 120 kg P205 was not sufficient to overcome the P

PHOSPHATE ROCKS IN THE TROPICS

123

deficiency or that factors other than P were limiting production. Both problems are suspected since other fertilizers, including organic manures (with additional N, K, micronutrients, etc.) resulted in significantly higher yields than did TSP alone but still averaged only around 15 tons of potatoes/ha. In additional experiments with a rotation of potatoes-corn- wheat or potatoes-corn-barley using the PR from Boliva, it was again concluded that the PR was ineffective, but review of the data reveals that, of the 19 fertilizer treatments tested, only 2 treatments (TSP at 120 kg P205/haand organic compost with N :P205:K 2 0 levels of 1 12 :240 :68 kg/ha) were significantly superior to the absolute check. From these experiments, therefore, it is difficult to determine the actual potential to supply the P requirements per se followingcorrection of the other limiting factors. Solubility measurements as well as greenhouse experiments conducted by Rodriguez et al. ( 1981), which compared the Bolivian PR to Colombian sources on acid Colombian soils, indicatethat the Bolivian PR is low to medium in reactivity and would be expected to perform similarly to the Pesca PR from Colombia. In experiments conducted on high-P-fixingAndepts in Tulcan and Canar, Ecuador, it was observed that response to freshly applied P by both potatoes and forage grass increased as the amount of water-soluble P in the fertilizer increased (INIAP/IFDC, unpublished, 1981). In the case of potatoes, yields resulting from the use of central Florida PR acidulated with 40% of the H2S04required for SSP was similar to those obtained with TSP, but it was not known whether part of the response may have been due to the S supplied by the PAPR. The unacidulated PR was almost completely ineffective in those trials, even when residual effect was measured by a subsequent planting of forage grass. It was concluded that PAPR was the most appropriate alternative under these conditions and that banding of the PAPR was more effective than broadcasting and incorporating. As a result, studies are now being initiated by the National Research Institute in Agriculture and Livestock (INIAP) and IFDC on the partial acidulation of the locally available Nap0 PR. Greenhouse trials have also been conducted to evaluate partial acidulation of PRs from Colombia (Sardinata, Pesca, Huila, Media Luna), Peru (Bayovar), Bolivia (Capinota), and Venezuela (Lobatera and Riecieto) as part of a program organized by IFDC.From those trials, it was concluded that 40- 50%acidulation with H2S04would be required to achieve desired agronomic response. As shown by Hammond et al. (1980) in Fig. 1 1, this is equivalent to 15- 18%acidulation with phosphoric acid in the case of Pesca PR. Extensive farm-level testing of PAPR was subsequently initiated by IFDC in 1982 using 40% Pesca PAPR and 50% Huila PAPR in varied cropping systems and agroclimatic zones of Colombia. Multiple-sitetrials were estab-

124

L. L. HAMMOND ET AL.

Degree of Acidulation with HJPO~(oh) FIG. 11. Relationship between effective levels of acidulation with H,SO, and H,PO, on Pesca phosphate rock. (From Hammond et al., 1980.)

lished where test crops included both potatoes and intercropped maize and beans grown on Andepts of the high-altitude region in Narifio, cassava and beans grown on Oxic Inceptisols of the mid-altitude region in Cauca, and rice (both rain-fed and flooded)on Oxisols in the low-altitude region in Meta (IFDC, 1984). In all, the evaluation included over 60 on-farm experiments. While considerable farm-to-farm variation was observed, it was concluded that there was no statistically significant differencebetween the effectiveness of TSP and that of the PAPR products irrespective of the crop/soil combination. Sulfur was not identified as a limiting factor. This was not the case with unacidulated PR, which was found to be significantly lower in effectiveness than the fertilizers containing soluble P in the majority of the cases.

2. Observations on Source Management The importance of maximizing the surface area contact between unacidulated PR and soil has already been discussed in reference to the particle or granule size of the PR, but it is also reflected in performanceas a function of method of application. Research in Colombia, for example, has verified that optimum response to PR application is generally obtained when the PR is broadcast and incorporated into the soil (Le6n and Hammond, 1984).

PHOSPHATE ROCKS IN THE TROPICS

125

When Huila PR (Colombia)was banded into an acid Andept, response to P by field beans was only 40% as high as that observed if the PR was broadcast and incorporated (Fig. 12). It is important to note, however, that this influence may not be long-lasting-it can be seen in Fig. 12 that when the fertilizer treatments were reapplied for a second cropping period, the difference between the two methods of application in the response of beans to P was greatly diminished. It has been speculated that disturbance of the P initially applied in the band due to tillage before the second band application resulted in an improved distribution of the PR for utilization of the residual P. The influence of method of application has also been shown to vary depending on the crop to which the PR is applied. In a greenhouse experiment, Peng and Hammond (1979)reported that surface application ofboth TSP and Bayovar PR (Peru) significantly reduced dry matter production of corn whereas only a slight influence was noted when guinea grass was used as the indicator crop.

1300

1000Second Crop

m

Y,

t

800

-

600

-

Rate of Application (kg P/ha)

Fic. 12. Response of beans to Huila phosphate rock in Popayln, Colombia, as influenced by method of application. (From LeBn and Hammond, 1984.)

126

L. L. HAMMOND ET AL

Recommendationson method of application vary when PR is compared with PAPR. For example, Nufiez (1984) recommended that unacidulated PR should be broadcast and incorporated into the soil 15 days prior to planting. He also presented data by Arroyave et al. (1979) obtained in an experiment with corn on an Andept from Sierra Tarasca, Mexico, which illustrates the beneficial effect of band application with 25,50,75, and 100% acidulation of the PR (Fig. 13). In this case, with low-reactivity PR from ZimapBn, Mexico, broadcast application was superior only with unacidulated PR and the effect of acidulation was reflected only when band applied. Mean maximum yield was again obtained with 50% acidulation.

B. SUB-SAHARAN AFRICA Agronomists in FrancophoneWest Africa were in the forefront in research assessing the agronomic potential of phosphate rock (Dupont de Dinechin, 1967a; Beye, 1973; Jenny, 1973; Charoy, 1980; Thibout el al., 1980). Much of this work was in direct response to the changing systems of agriculture in West Africa, and most of the work was camed out in farming systems that were (1) nonitinerant or completely settled or (2) semiintensive. 1. Evaluation of Ground Phosphate Rock

Poulain and Mara ( 1965) summarized the results of two trials conducted at Bambey, Senegal, between 1962 and 1964. Single superphosphate and

1800 1600

Band Applied at Planting

r

-

=-----A,--

Broadcast in Advance -,4,,,,,,, of Planting

A

0

25 50 15 Degree of Acidulation (Vo)

100

FIG. 13. Corn yield from application of Zimaphn phosphate rock with five degrees of acidulation and two forms of application. (From Arroyave et al., 1979.)

PHOSPHATE ROCKS IN THE TROPICS

127

dicalcium phosphate were compared with PR sources from Taiba and Thies. There was no difference between Psources although only SSP yielded significantly higher than the control, which received both N and K (Table VIII). Further evaluation of the deposits at Thies and Taiba has led agronomiststo conclude that these sources are not suitable as annual fertilizers, especially for cereals (L. Cisse, personal communication). The recent discovery of a medium- to high-grade ore (28.7% P,O,) with 4.5% neutral ammonium citrate solubility near Matam in eastern Senegal has revived agronomic activities on the use of PR as an alternative source of P fertilizer in Senegal and in The Gambia. Use of PR for annual maintenance fertilization after initial basal dressings of rock was investigated in experiments at Saria and Farako Ba in Burkina Faso (Dupont de Dinechin, 1967b).Yields of sorghum, cotton, and groundnut were improved with fertilizer addition. However, TSP was superior to PR in the first year of application. At Saria, this advantage disappeared during the second year. Phosphate rocks from Senegal were used in these experiments. Results of greenhouse trials at IFDC using Kodjari PRYa low-grade ore (25% P,O,) found in Burkina Faso, showed that the relative agronomic effectiveness(ascompared with SSP)was between 4 and 7%,which indicated the unsuitability of this rock as an annual fertilizer source. Results obtained by scientists from the Institut Voltaique Recherches Agronomiques et ZooTable VIIl

Use of Phosphate Rock as Annual Fertilizer at Bambey, Sen@ Yield* (kgba) Phosphate fertilizer source

Groundnuts

Millet

Single superphosphate Dicalcium phosphate Phospal Slimes Control ( N and K)

(1962) 1829 a 1689 ab 1645 ab 1591 ab 1481 b

( 1963) 1079 a 990 ab 897 ab 917 ab 777 b

Dicalcium phosphate Phospal Taiba phosphate rock Control ( N and K)

(1963) 1769 a 1675 a 1660 a 1431 a

( 1964) 1048 a 904 a 942 a 699 b

a

From Jones ( 1 973). Figures in the same column followed by the same letter are not significantly different.

128

L. L. HAMMOND ET AL.

technique (IVRAZ) for 2 years ( 1983 and 1984) at Zaria on both sorghum and millet confirm the poor performance of the Kodjari rock. Togo phosphate rock applied at the rate of 37 kg P,05/ha at four sites in northern Togo was somewhat less effective than dicalcium phosphate, although the yield differences were not significant (Research Institute for Tropical Agriculture-Niger, unpublished). In Nigeria, Juo and Kang (1978) evaluated the initial response of North Carolina PR and Morocco PR in greenhouse trials using an Alfisol and an Ultisol. Under similar pH conditions, both phosphate rocks performed better in the Alfisol than in the Ultisol. It was also concluded that to obtain 80% of maximum yield, the rates of P required were 80, 100, and 200 ppm P for TSP, North Carolina PR, and Morocco PR, respectively, in one of the Alfisols. Considerably higher quantities of PR were needed for the Ultisol. In another experiment in the Nigerian savanna environment, Mokwunye (1979) reported that Togo PR was 63%as effective as SSP in the first year of application.Continued applicationsof PR for 2 additional years raised the P fertility level and by the third year, the mean yield ofthe phosphate rock plots was 96% of that of the SSP treatments which were also reapplied (Table IX). More recently, IFDC scientists and their collaborators have evaluated Togo PR as an annual fertilizer in several trials in Togo, Nigeria, Sierra Leone, and Kenya. In general, SSP was superior to Togo PR at every location. Truong et al. (1 978) summarized the results of several experiments comparing some of the West African phosphate rocks [Togo, Kodjari, Tahoua (Niger), and Tilemsi (Mali)]. The conclusion was that only Tahoua and Tilemsi were suitable for direct application. These results were confirmed by experiments conducted at three sites in Mali by Thibout et al. (1980), in which Tilemsi PR and Taiba PR from Senegal were compared. The concluTable IX

Maize Response to Togo Phosphate Rock at Samaru, Nigeria" Phosphate rock ( W h a grain)

P,O, added (kg/ha) 1974

0 50 100 150 200

Single superphosphate (kg/ha grain)

1975

1976

1974

1975

1976

1974

1975

1976

0 25 50 75

0 25 50 75

558 2087 2134 2381

696 3410 3599 3670

605 3435 5189 4172

558 2939 3603 4370

696 4202 5079 5779

605 3668 4831 4692

3214

3705

4392

3847

100

1

Mean

From Mokwunye (1979).

0

2119

0

~

3021

~

129

PHOSPHATE ROCKS IN THE TROPICS

sion was that Tilemsi PR was reactive enough to be used for direct application. Tilemsi PR was also evaluated in Trials at Sapu in The Gambia, using maize and groundnut. Although 1984 was a very dry year, finely ground Tilemsi PR was 74 and 92% as efficient as SSP for maize and groundnut, respectively. The adoption of fixed rotation within a settled, nonitinerant agricultural system has encouraged the idea of fertilizer as a long-term investment and the policy of fertilizing not just a crop but the whole rotation. This policy nurtured the practice of basal fertilization which aims, by means of a large dressing once per rotation, to raise soil fertility to a level at which crop production is maximized. The level of fertilizer to be applied as a basal dose was determined by existing nutrient content of the soil. In West Africa, where P is the most limiting nutrient in the subhumid and semiarid savannas, the use of PR as basal fertilizer was particularly attractive. The fact that the colloidal systems in soils of most parts of sub-Saharan Africa are derived from coarse materials and thus have small tendencies to immobilize added P also encouraged the practice of basal fertilization. Thus, the beneficial effect of a single large dose of P fertilizer, especially PR, on the yields of certain crops grown in rotation has been documented by several workers (Schilling, 1965; Jenny, 1965; Lienart and Nabos, 1967; Tourte er al., 1967; Poulain and Amvets, 1971). It can be observed from the results obtained by Bockelee-Morvan ( I 966) at Darou in Senegal (Table X) that the residual value of Phospal extended for a number of years at high rates of application. More recently Parc W PR applied at three times the annual rate produced as much millet over 3 years as that quantity applied as an annual fertilization treatment (IFDC, unpublished data). Dupont de Dinechin (1967a) camed out some trials at Saria and Farako

Table X Effect of Phospal on Yields of Groundnuts in Continuous GroundnutsMillet Rotation at Darou, Senegal" P,O, in year of application ( 1 953) Wha)

1953

1955

1957

1959

Control I00 200 400 800 I600

1950 1920 2140 2020 1980 2000

1610 1750 2420 2390 2740 2580

I250 1410 1920 21 10 2080 2180

1530 1750 I750 2070 2220 2340

From Jones (1973).

Groundnuts yield (kg/ha)

130

L. L. HAMMOND ET AL.

Ba in Burkina Faso in which he investigated the effect of Taiba PR applied either when the field was plowed at the end of the previous cropping season or as a sidedressing to sorghum. Mixtures of PR and TSP were also compared. The results obtained encouraged Dupont de Dinechin (1967a) to recommend the application of PR as an annual fertilizer only when it was applied at the end of the previous season and then plowed in. Phosphate rock should be broadcast, and he concluded that application of insoluble PR as a sidedressing to growing crops even where rainfall is not limiting was not likely to be effective. It would seem that the degree of improvements in both seedling growth and agronomic effectiveness of PR applied for some time before cropping would depend on the characteristicsof both the rock and the soil. Observations identifying the influence of P-retention capacity were described previously. Although work done in temperate regions has emphasized the influence of soil pH on P availability from PRYlittle work has been done in the strongly acid soils of the forest zones of tropical Africa. In one case where observations have been reported, Juo and Kang ( 1979)studied the effect of liming on the agronomic effectiveness of North Carolina PRYMorocco PR, and Togo PR in two Ultisols from Nigeria. Liming the soils to pH 5.5 reduced the dry matter yield of maize as well as P uptake where PR was applied. Liming the soils to near pH 5.5 also lowered the levels of Bray P from soils treated with phosphate rock. As discussed previously, liming of acid soils leads to a reduction of PR dissolution because of the resulting increase in both pH and exchangeable Ca levels. There is definitely a need to find ways to utilize PR in acid aluminous soils since these soils have a tendency to immobilize large quantities of expensive soluble P fertilizers. 2. Evaluation of PAPR

Although phosphate rock appears to be the cheapest alternative form of P fertilizerfor food crops in the P-deficient soilsoftropical Africa, the chemical nature of the rocks, soil conditions, and the characteristicsof the crops affect the performance of phosphate rock. Tropical African agronomists are in general agreement that phosphate rock can increase yields in the year of application but its effect is generally less than that of the more soluble commercial fertilizers.One of the attempts at improving the initial effectiveness of PR involved mixing the rocks with other fertilizers (Ollagnier and Prevot, 1958; Poulain and Mara, 1965;Bockelee-Morvan, 1966; Dupont de Dinechin, 1967b). Work carried out by the Research Institute for Tropical Agriculture (IRAT) at Sango in Togo comparing mixtures of Togo PR and

PHOSPHATE ROCKS IN THE TROPICS

131

dicalcium phosphate showed that sorghum yield decreased significantly when the PR component exceeded 75%. In general, the poor performance of the West African phosphate rocks in the first year of application is due to the unreactive nature of the rocks. One way to overcome the problem of low reactivity, as shown by the example above, is to use a product in which at least a portion of the P is more readily plant available. IFJX has pioneered the production and field testing of PAPR made from various African ores. PAPR has been produced (using sulfuric acid) from Tilemsi PR, Kodjari PR, Togo PR, Parc W PR, Sukulu (Uganda) PR, and Dorowa (Zimbabwe)PR. The resultsofactivitiesofIFDC and its collaborators from 1982 through 1984 are summarized in a report to the International Fund for Agricultural Development (IFAD) (IFDC, 1985). The results presented in Fig. 14 for maize in Ultisols and in Fig. 15 for sorghum in Alfisolsin West Africa are representative of the improvementsin the performance of PR as a result of partial acidulation. For example, the 50% Togo PAPR in both regions of West Africa was equal in agronomic effectiveness to SSP, whereas finely ground PR was inferior. C. ASIA Extensive research on the use of phosphate rock has been conducted in a number of countries in Asia. In India, for example, a bulletin was prepared by Pyrites, Phosphates, and Chemicals, Ltd. (PPCL) in 1983 which contains 2200

2000 1800 I0

f

I

1600

s

1400 1200

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L. L. HAMMOND ET AL. 2400

I

I

I

I

I

I

15

30

45

60

75

90

2300 2200 2100 2000 P

m .->

1900 1800

1700 1600

1500

0

PtOs Rate (kglha) FIG.15. Sorghum yield response to phosphorus sources in an Alfisol in West Africa. (From the International Fertilizer Development Center, 1985.)

abstracts or extended summaries of 54 published papers on phosphate rock research. In the same year, the proceedings of a symposium on phosphate rock held at Marathwada Agricultural University, Parbhani (Maharashtra) were published and included 19 papers on phosphate rock (IndianJournal of Agricultural Chemistry, 1983). Considerable interest in the use of phosphate rock has also been shown in Sri Lanka, Thailand, Malaysia, Indonesia, the Philippines, and other Asian countries. In many places the traditional interest in PR utilization has been for plantation crops (rubber, tea, cocoa, oil palm, etc.), which were expectedto more fully benefit from the residual value of PR, however, this review (as those from India cited above) will highlight only the findingsrelated to food crop production, and flooded rice in particular, since the results reported under upland conditions are consistent with those obtained in Latin America and Africa. In 1977, the International Network on Soil Fertility and Fertilizer Evaluation for Rice (INSFFER), a collaborative network among national institutions, the International Rice Research Institute (IRRI), and IFDC, established a series of internationaltrials on sourcesof phosphorus in flooded rice (IRRI, 1982). During the period 1977- 198 1, 84 experiments were conducted in 24 sites and in 10 countries. Asian countries participating in the network included Bangladesh, India, Indonesia, Philippines, Sri Lanka, Thailand, and Vietnam. In each of the locations, 10 treatments were tested which included a check, three positive rates of superphosphate, a highly reactive PR, and a less reactive PR. The fertilizers were reapplied before each crop. Of the 84 trials, P response was reported in only 58, and in those, all P

PHOSPHATE ROCKS IN THE TROPICS

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sources were reported to have behaved similarly (IRRI, 1982). In an earlier report on the same network (IRRI, 1980),at the time when only 54 of the trials had been completed, it was reported that 65% of the trials exhibited a positive response to P and that of these, the highly reactive PR showed no significant difference in yield from superphosphate at the same rate. The low-reactivity PR was also equally as effective as superphosphate in about 80% of the cases-but when applied at double the rate of application. The excellent response to finely ground PR in the INSFFER network trials is consistent with the conclusions generally reported by Indian scientists (PPCL, 1983; Indian Journal of Agricultural Chemistry, 1983). However, greater differences related to source solubility would have been predicted, based on the observation of Engelstad et al. (1974) in Thailand. The highly encouraging results with the use of PR in flooded soils can be related to the differences in the chemical reactions of P in those soils as opposed to the reactions which occur in unflooded soils. In general, the P-supplying capacity of flooded soils is superior to that of nonflooded soils, and it has been observed that soils which do not exhibit a deficiency of P for flooded rice often do require applications of fertilizer P for the subsequent upland crops in the same location (De Datta, 1981). These reactions tend to reduce the differences between the agronomic effectiveness of unacidulated PR and that of soluble P and thus suggest high potential for the use of PR in flooded cropping systems. Nevertheless, it can be noted from the INSFFER network results that double the rate of application of P was still required to achieve the yields obtained with soluble forms when low-reactivity PRs were applied. This is a significant observation because the PR indigenous to Asian countries, such as India and Sri Lanka, are of this type. PPCL (1983), for example, showed that the Indian PRs from Udaipur, Jhamarkotra, Purulia, and Meghanagar are fluorapatites with negligible amounts of substitution of C 0 3 for PO4; Mussoorie, Duramala, and Maldeota apatites are francolites with a small degree of substitution; and Andra Pradesh and Kasipatiram rock has fluorochloraapatitecomposition. The decision whether to use low-reactive indigenous PRs, therefore, becomes an economic question since similar yields may require higher rates of application. The relationship between relative agronomic effectiveness of the PR source as compared with TSP and the ratio of the price of TSP to the price of PR illustrated in Fig. 16 have been proposed as an index for source selection on the basis of relative economic effectiveness. Again, because of the low reactivity of the indigenous PRs a number of modifications have been evaluated to determine the possibilities of improving the agronomic effectiveness of the rock. Of those modifications, the provision of approximately 50%of the total Pin water-soluble form has been found to consistently result in yields comparable to those of completely

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01 1.0

I

1.5

1

2.0

I

25

I

3.0

I

3.5

1

4.0

I

4.5

PTSP’PPR

FIG. 16. Relationship between the price ratios of TSP and phosphate rock and relative agronomic effectiveness values (RAE). RAE can be used in making a choice between these sources.(Adapted from Engelstad ef al., 1974.)

soluble P fertilizer. The references are too numerous to cite, but the data shown in Table XI illustrate the effectiveness of Mussoorie PR and PAPR from India when used for flooded rice.

IX. SUMMARY AND CONCLUSIONS Information gained from the research conducted in the tropics on the use of indigenous phosphates (of which only a part was described in this review) can be combined with knowledge concerning the mechanisms of PR dissolution, P reaction in soil, and uptake by crops, to provide a basis for general conclusions regarding the most appropriate means of utilizing these deposits. First, it must be kept in mind that, while each deposit does differ in mineralogy, P content, and chemical reactivity, all natural deposits indigenous to tropical regions share certain properties with those well-known rocks used for production of commercial P fertilizers-the most important of which is that the P is contained in a form which is not readily plant available when applied to the soil but which will convert to plant-available forms at

135

PHOSPHATE ROCKS IN THE TROPICS Table XI Response of Rice to P from Mussoorie PR Products in Kanpur" Grain yield (kg/ha) for different rates of application (kg P,O,/ha) 0 Check TSP 50%H,PO, PAPR 50%H,SO, PAPR Unacidulated PR Mean

4330

-

30

60

90

Meanb 4330 b 4997 a 4806 a 5012 a -0a, b 475 I

-

-

-

4663 4553 4167

5024 4838 5078

5303 5026 5 192 4819 5085

-

4442

4569

4330

4606

4811

Data from K. N. Tiwari and C. B. Azad, University of Agriculture and Technology,Kanpur, India (unpublished, 1985). Means with the same letter are not significantly different as determined by Duncan's multiple range test ( p = 0.05); CV = 7.9%.

varying rates with time. It was observed decades ago in temperate climates that this rate of liberation of P usually was not sufficient to support the level of crop production desired and that directly applied PR was erratic in its performance. These problems were overcome by acidulation to convert the P in the PR to a form that was readily plant available. To place the role of direct application of PR in the tropics in proper perspective, is important to acknowledge the followingdeduction: in agronomic terms, it is unlikely that finely ground PR alone can be as consistent as processed PR in satisfyingthe P requirements for high levels ofcrop production across the wide range of agroclimatic and edaphic conditions encountered in the tropics. In the majority of the cases where finely ground PR has been observed to be as effective as soluble P, it has been due to one of the following circumstances: 1. The rock has been one of the highly reactive PRs. 2. Factors other than P availability limited crop growth, and thus response to the soluble P applied was limited (e.g., nutrient deficiencies,aluminum toxicity, moisture stress, nonresponsive varieties). 3. Response was measured long after application (residual effect studies), resulting, to a large degree, in the measure of the reaction products in the soil rather than or in addition to the availability of P from the fertilizer.

Even if it is accepted that the insoluble P of natural PR is inherently less effective than soluble fertilizers,the situation as it existstoday with respect to tropical agriculture is that the last two circumstances described above are

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L. L. HAMMOND ET ,415.

often found at the farm level (i.e., the farmers cannot afford the inputs required to relieve all nutritional deficiencies or toxicities, the climate is often a constraint, and P fertilizers often are not purchased on a regular basis). The directly applied PR in the tropics, therefore, can be considered not as a replacement for processed fertilizers in the whole of the agricultural sector, but rather as a supplemental low-cost fertilizer targeted for those segments where the above conditions exist. In this respect, finely ground PR conforms to the goals of minimum inputs-not because of quantity required but rather because of low cost and reduced risk of loss in the face of production constraints. Its appropriateness, however, is also a function of the soil properties and cropping systems-suggesting that PR will find its greatest utility in the acid soil regions where pH and soil P retention are relatively low. Cropping systems that include pastures, other long-term crops, or flooded rice represent other situations conducive to the use of PR. On the other hand, it should not be assumed that the cheapest product (i.e., PR) should always be the product of choice under conditions with high constraints. Careful selection is required, especially where the PR is low in reactivity, the soil is not highly acid, the P retention capacity of the soil is high, or the early P requirement by the crop is high. Utilization of PR under inappropriateconditionsor with poor management can result in an unfavorable cost - benefit relationship relative to soluble sources even in areas with severe constraints to crop production. An important observation from research on PR in the tropics is related to the role of plant-available P in the very early stages of plant development. One of the major limitations of finely ground PR is its inability to satisfy this early requirement because ofits slow rate ofdissolution. To overcomethis, it is often recommended that the PR be applied several weeks or months prior to planting so that a greater portion of the PR is dissolved by the time of planting. This approach is effective, however, only when the P retention capacity of the soil is low so that the dissolved P remains availableto the plant throughout the incubation period, or when practiced in flooded systems which can increase the availabilityof P in the reaction products. One practice that has been observed to effectively increase the utilization of unacidulated PR is supplying the early requirements of the crop with soluble P and to rely on the unacidulated PR in the soil to provide for the subsequent P requirements. This has been accomplished in a number of ways, including 1. Basal applications of PR as a soil amendment followed by use of a starter fertilizer at the time of planting. 2. Mixtures of finely ground PR with substances containing soluble P (superphosphates, commercial multinutrient fertilizers, animal manure, etc.) applied at the time of planting. 3. Partial acidulation of the PR.

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Although research on the mechanisms responsible for these observations is incomplete, it can be hypothesized that, just as maximization of surface area contact between the PR and soil is required to promote adequate dissolution of the PR, maximization of contact between the root surface and the PR is required to promote adequate uptake of the P by the plant. The presence of soluble P fertilizers during the initial growth stages, even in relatively small concentrations, may augment root development to a sufficient degree that during the course of the growing season the crop can benefit not only from the soluble P provided but also from the unacidulated PR to a much greater degree than would otherwise have occurred. Therefore, the use of PR combined with soluble forms of P, such as PAPR, represents a highly efficient means of utilizing indigenous PR resources. The research on these combinations throughout Latin America, Africa, and Asia has consistently shown that the response curves for products with only 40 - 50% of the P applied in a water-soluble form are similar to those ofhighly soluble P fertilizers, thus suggesting that both the soluble and insoluble fractions contribute to the plant response. This approach offers expanded opportunities for utilizing indigenous resources that possess properties unsuited to production of fully acidulated products and for use with soils and crops where PR alone is unreliable. This is especially the case in soils characterized by high P retention capacity, where the soluble fraction of the fertilizer treatment is relied upon only for the early stages of growth and the unacidulated fraction continues to dissolve during the longer term.

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ADVANCES IN AGRONOMY. VOL. 40

CROP SIMULATION MODELS IN AGRONOMIC SYSTEMS F. D. Whisler,’ B. Acock,2 D. N. Baker,2 R. E. Fye,2 H. F. Hodges,’ J. R. Lambert,3 H. E. Lemmon,2 J. M. McKinion,2and V. R. Reddy3 ’Department of Agronomy, Mississippi State, Mississippi 39762 WSDA- ARS, Crop Simulation Research Unit, Mississippi State University Mississippi State, Mississippi 39762 3Departmentof Agricultural Engineering, Clemson University, Clemson, South Carolina 29631

I. NEED FOR CROP SIMULATION MODELS AND TYPES OF MODELS There are probably as many answers to the question “Why build crop models?’ as there are modelers. We might, however, catalog the reasons into three broad categories: (1) as aids in interpreting experimental results, (2) as agronomic research tools, or (3) as agronomic grower tools. Many crop models or parts of crop models have been built to help the researcher and/or his graduate students understand the operation of some part of an agronomic cropping system, e.g., soil water flow, stomata1control, or fertilizer nutrient movement. These are attempts by the modeler to understand, and perhaps quantify, these processes. Such models will strongly reflect the interests and strengths of the modeler, and will often be weak to nonexistent in those areas where he has little interest or knowledge. The multidisciplinary and often multiagency team approach helps to eliminate some of these shortcomings. Other crop models are built to be research tools. In addition to understanding various parts of some agronomic systems, the modelers want to see what can be expected to happen if some change is made in that system. Field tests are very expensive, especially as the numbers of variables and/or treatments increase and years of results are needed. A proven model ofthe system would help to evaluate these treatments and indicate which ones could be expected to give the desired results. These could then be field tested to verify the predictions. Note we do not suggest that models will eliminate field tests, but they should sharpen their use and lower the overall costs of such tests. 141 Copyright 0 1986 by Academic Ress, Inc. All rights of reproduction in any form reserved.

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Some other crop models are being built with the ultimate goal of grower usage. This presents the exciting possibility of allowing precise, laboratory, growth chamber and/or field data to be used by the grower. If these models are comprehensiveand mechanistic, as we believe they should be, then they will allow the grower to use management “what if” games to check on the profitability of many options. Every modeler must consider the level of detail at which a given model should be developed. Models may range from the strictly empirical model which uses only daily average temperature to predict wheat yield in an imgated system, to the very complex, biochemical detail of guard cell control of stomata. The level of detail is also linked to the objectives of the model, as discussed earlier. Another determinant is the data availability needed to build and run the model. For example, in our work on crop simulation, we know how to build very detailed models of infiltration depending upon rainfall intensities, amounts, and soil properties. However, if only daily total rainfall values are generally available, and we want these models to be widely used by growers in all regions, then we are generally limited to a mass water balance approach to soil water storage recharge rather than a more detailed numerical analysis technique. In Fig. 1, we have arranged in a hierarchy the various levels at which models can be built. With these levels are shown the usual time frames (i.e., time steps used in running the models) and the usual data bases for building the models. Generally, models low in the hierarchy use a small time frame LEVEL OF HIERARCHY

I Biome

I Ecosystem I

Crop

I

USUAL

TIME FRAHE

I I I I

Years Months

Plant

Days

I I Cell

Hours

Organ

I Organelle I Holecule

I I

1

Seconds

USUAL DATA BASE

Field experiments

I

control 1 eaenvi ronment experiments

e- level o f prediction

1

range o f mechanism level of empiricism

I

Laboratoy experiments

I

I FIG.1. A hierarchical classification scheme for models based on levels of resolution.

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and require data from detailed experiments performed in closely defined conditions. Models low in the hierarchy also tend to be models of individual processes. These can be aggregated to form models at higher levels in the hierarchy, but there are limits on the extent to which this is feasible. The current conventional wisdom is that it is not desirable to build a model at more than one, or at most two, levels of hierarchy below the one at which predictions are to be made. This is because ( 1) activities at lower levels run in a shorter time frame and, to simulate the activity, it is necessary to use shorter time steps in the model, which increases the running time; (2) there is usually insufficientinformation to allow the whole model to be built at the same level of detail; and (3) with the introduction of extra detail it becomes increasingly difficult to find the source of any problems in the model. With crop simulation models we are interested in making predictions at the crop level. Therefore, we can incorporate process models from the plant and organ levels into our crop models. For reasons to be discussed later, these should be mechanistic models if possible. Processes at the cell and finer levels of resolution will be treated empirically, if at all. Empirical (or correlative)models describe relationshipsbetween variables without referring to any underlying biological or physical structure that may exist between the variables, as has been discussed by Reynolds and Acock (1985). For this reason, empirical modeling becomes more prevalent with decreasingresolution as our understanding of causalitydecreases. Mechanistic (or explanatory) models, on the other hand, attempt to explicitly represent causality between variables. In a mechanistic model, mathematical functions represent the known or hypothesized mechanism that relates the variables and explains their observed behavior. For this reason, mechanistic modeling becomes feasible as our understanding of causality increaseswith increasing resolution. Although the distinction between empirical and mechanistic models is useful, many crop models in fact contain a mixture of empiricism and mechanism. All models become empirical at some level. For example, a mechanistic crop model would be considered empirical by a modeler working at the cellular level. Nevertheless,the amount of mechanism in a model is an important determinant of its utility. Although mechanism cannot be measured quantitatively, in Fig. 2 we present a framework for qualitatively classifying crop models. On the left of the diagram, we place models that are entirely empirical. With increasing amounts of mechanism incorporated in them, models are placed successively further to the right on the diagram. Comprehensiveness should perhaps be a third dimension but, in general, the comprehensiveness of the model increases as the amount of mechanism in it increases. The capabilities of the various models in this spectrum are also shown in

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Types of models

Cornprenenslveness

Ernplricism Mechanism

Capabi 11ties

--SM-IP--R+EP

IN -

FIG. 2. Types of crop models and some of their capabilities. SM, Summarizing data; IP, interpolative prediction (i.e., predicting behavior within the range of the data base); RM, research management (i.e., identifyinggaps in our knowledge base); EP, extrapolative prediction (i.e., predicting behavior outside the range of the data base); IN, interpretation of experimental results.

Fig. 2. For summarizing data (SM) and maybe even for interpolative prediction (IP), completely empirical (e.g., multiple regression) models may suffice. For extrapolative prediction (EP) and research management (RM), the models must be mechanistic, and for interpretation (IN) they must be mechanistic and comprehensive. As the amount of mechanism in a model increases so does the requirement for detailed experimental data. Such data are often currently unavailable and may be difficult to obtain experimentally. Finally, because the introduction of more mechanism generally implies the use of a smaller time frame, the time required to run the model increases. This article is about crop simulation models. Simulation means that the model acts like a real crop by gradually growing leaves, stems, roots, etc., during the season. It does not just predict some final state such as biomass or yield. Simulation models, therefore, all contain some mechanism, but there is still a wide range in their capabilities. In our opinion, it is desirable to build crop simulation models that are both highly mechanistic and comprehensive. The primary reason for this is that such models can be applied to solving a wide range of problems. Many of the applications that will be discussed in Section IV involved interpretation which can only be done with models of this type. Computers are now sufficiently powerful to run such models through a full simulated growing season in a few minutes. We have also developed techniques and apparatus for obtaining the required experimental data and these will be described later. In addition to the types of models already described, some further definitions are needed. We will be describing dynamic simulation crop models. These models predict changes in crop status with time as a function of exogenousparameters. For example, models that predict the changing numbers of bolls on a cotton plant throughout the growing season, or the changing soil water content or temperature at a certain depth throughout the season, are dynamic simulation models.

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Phenological models are a broad class of models that predict crop development from one growth stage to another. These predictions are generally based upon accumulated heat units, with development being delayed by various stresses. These models may or may not be based upon mechanistic concepts. Stochastic simulation models are those that are based upon the probability of occurrence of some event or exogenous variable. They may have mechanistic submodels or subroutines. Weather variables are often treated in a stochastic manner or probability of occurrence and as such may be combined with a mechanistic crop model. The same might also be done with insects, diseases, and weeds. Physiologically, physically based simulation models are those mechanistic models whose plant or soil processes can be physiologically, physically, or chemically described. For example, nitrogen may be taken up from the soil by root systems based upon the soil nitrogen content and the rate of solution flow to the root. Thus the physical placement of the fertilizer with regard to the plant root system is important as well as soil and plant nitrogen transformations. Surrogate variables are those variables that are calculated by the model and used to estimate the value of another quantity that the model does not directly (or mechanistically) calculate. For example, some modelers calculate dry matter production rate from the estimated transpiration rate, citing Tanner’s ( 1974) observation of “an impressive linearity between transpiration and yield.” There are a number of theoretical reasons why we would not expect a constant relationship between photosynthesis and transpiration. For several years prior to the appearance of these models, we (Baker and Musgrave, 1964) had been making 15-min measurements of gas exchange rates in crop canopies. The data in Fig. 3 are typical. Although curvature is observed under some circumstances, as the data in Fig. 3 show, the idea works fairly well in cotton (probably because it is a xerophyte). Obviously, there is an impressive curvilinearity in the relationship for corn. The remainder of this article deals with crop simulation models. There are 20-25 teams in the United States and in other parts of the world who are building crop simulation models. Among the crops which have been modeled are citrus, peanuts, sugar beets, corn, sorghum, wheat, rice, barley, white potato, cotton, soybean, and alfalfa. Several models, developed by different groups, exist for some of these species. Most of them are materials balances. They vary widely in terms of the array of processes treated and the ways they are treated. They also vary greatly in their developmental status and in the level of consultative support available to the potential user. A list of some published modeling efforts is contained in Table I. This table is not all inclusive for it seems that, almost monthly, we learn of new efforts under way

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F. D. WHISLER ET AL. 1.8 1.6 1.4

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N

E 1.0

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0 " 0.8

u

0,

E

0.6

0.4

0. 2 0

0

1

2

3

4

5

6 7 8 9 mm H20/day

1

0

1

1

FIG.3. Crop canopy photosynthesis versus transpiration in corn (0)and cotton (0).

to model other crops. Since we have no first-hand experience with many of the models listed in Table I, we will not give any further evaluation.

II. MODEL BUILDING

In building a crop simulation model it is necessary to divide the cropping system into its constituent parts so that the various processes involved can be modeled separately. As we have discussed already, the current conventional wisdom is that simulation models should only treat processes one or two hierarchical levels below the level at which predictions are to be made. Thus, for a crop model, we treat explicitlyprocesses at the plant and organ level but not at the organelle and lower levels of hierarchy. These processes can be conveniently divided at the soil surface into aerial processes, which are mostly concerned with crop physiology and morphology, and soil processes. The division is not a perfect one and, in the following text, evapotranspiration and root growth are described under the heading of soil processes. For many of the processes discussed below we have little understanding of the mechanisms involved. In these circumstances it is common to find several models of the process extant. These models and their relative merits are discussed below from the point of view of the crop modeler. Many of the process models referenced have never actually been incorporated in crop

Table I Some Process-Level Crop Simulation Efforts Research group

Institutions

USDA-ARS, Mississippi State U., Acock, B., V. R. Reddy, F. D. Whisler, D. N. Baker, J. M. and U. of Florida McKinion, H. F. Hodges, and K. J. Boote Allen, J., and J. H. Stamper u. of Florida Angus, J. F., and H.G. Zandstra CSIRO (Australia) and Internationat Rice Research Institute Arkin, G. F., J. T. Ritchie, and Texas A&M U., USDA/SEA, and Kansas State U. R. L. Vanderlip USDA/SEA (Mississippi)and Baker, D. N., J. R. Lambert, Clemson U. and J. M. McKinion Baker, D. N., D. E. Smika, USDA/SEA (Mississippi, A. L. Black, W. 0. Willis, Colorado, and North Dakota) and A. Bauer Brown, L.G., J. D. Hesketh, Mississippi State U. J. W. Jones, and F. D. Whisler

Model name

Species

Processes treated

GLYCIM

Soybean

Photosynthesis, respiration, transpiration, growth, and morphogenesis. Incorporates RHIZOS

CITRUSIM IRRIMOD

Citrus

SORG

Sorghum bicolar Cotton

Photosynthesis Growth, phasic development, soil water flow, soil nitrogen, transpiration, and evaporation Photosynthesis, respiration, transpiration, and evaporation Photosynthesis, respiration, growth, and morphogenesis. Incorporates RHIZOS Photosynthesis, respiration, transpiration, growth, and morphogenesis. Incorporates RHIZOS Photosynthesis, respiration, transpiration, runoff, drainage, nitrogen u p take, denitdication, leaching, organogenesis, partitioning, and growth Photosynthesis, respiration, transpiration, growth, soil evaporation, and soil water flows Photosynthesis, respiration, translocation, and evaporation Photosynthesis, processes involved in setting seed number and seed size

GOSSYM

Rice

WINTER WHEAT

wheat

COTCROP

Cotton

Unnamed

Corn

Childs, S. W., J. R. Gilley, and W. E. Splinter

U. of Nebraska

Curry, R. B., G. E. Meyer, J. G. Streeter, and H. L. Mederski Duncan, W. G.

Ohio Agriculture Research and SOYMOD Development Center OARDC U. of Florida and U. of Kentucky SIMAIZ

Soybean Corn

(continued)

Table I (Continued) Research group

Institutions

Modelname

Species

Processes treated

Duncan, W. G.

U. of Florida and U. of Kentucky MIMSOYZ

soybean

Duncan, W. G.

U. of Florida and U. of Kentucky PEANUTZ

Peanuts

Fick, G. W.

Cornell University

ALSIM

Alfalfa

Holt, D. A., G. E. Miles, R. J. Bula, M. M. Schreiber, D. T. Doughtery, and R. M. Peart Jones, C. A., and R. T. Ritchie

Purdue University and USDA/ SEA

SIMED

Alfalfa

USDA/SEA (Texas) and IFDC, Alabama

CERES MAIZE

Corn

Kercher, J. R.

Lawrence Livermore Laboratory

GROW1

General

van Keulen, H.

Netherlands Agricultural U. (Wageningen) Netherlands Agricultural U. (Wageningen)

GRORYZA

Rice

ARIDCROP

Lambert, J. L., D. N. Baker, and J. M. McKinion

Clemson U. and USDA/SEA (Mississippi)

RHIZOS

Loomis, R. S., and E. Ng

U. of California-Davis

POTATO

Photosynthesis, respiration, transpiraNatural vegetation tion, and water uptake in semiarid regions soil Infiltration, uptake, capillary redistribution, ET, nitrogen transformation, N fertilizer applications Potato Photosynthesis, respiration, transpiration, water uptake, growth, develop ment, and senescence

van Keulen, H.

Photosynthesis, nitrogen hation, assimilate redistribution, processes for setting seed number and seed size Photosynthesis, nitrogen hation, processes for setting seed number and seed Size Photosynthesis defined as crop growth rate, and partitioning Photosynthesis, respiration, growth, translocation, and soil moisture u p take Phasic development, morphogenesis, growth, biomass accumulation and partitioning, soil water balance and plant - soil nitrogen status Photosynthesis, transpiration translocation Gross assimilation and respiration

Loomis, R. S., J. L. Wilson, D. W. Rains, and D. W. Grimes

U. of California- Davis

COTGRO

Cotton

Loomis, R. S., G. W. Fick, W. A. Williams, W. H. Hunt, and E. Ng Marani, A.

U. of California-Davis

SUBGRO

Sugar beet

The Hebrew U. of Jerusalem

ELCOMOD

Cotton (Ada)

McMennamy, J. A., and J. C. OToole Orwick, P. L., M. M. Schreiber, and D. A. Holt Ritchie, J. T., and S. Otter

International Rice Research Institute Purdue University

RICEMOD

Rice

SETSIM

Setaria

USDA/Sea (Texas)

CERES WHEAT

wheat

Grassland Research Institute (Hurley, Berkshire, England)

Unnamed

Uniculum barley

Rothamsted Experimental Station, Letcombe Laboratory, U. of Bristol Netherlands Agricultural U. (Wageningen)

ARCWHEAT I

wheat

PHOTON and BACROS

Any crop

u. of Florida

SOYGRO

Soybean

Ryle, G. J. A., N. R. Brockington, C. E. Powell, and B. Cross Weir, A. H., P. L. Bragg, J. R. Porter, and J. H. Rayner de Wit, C. T., et al. Wilkerson, G. G., J. W. Jones, K. J. Boote, K. T. Ingram, and J. W. Mishoe

Photosynthesis, respiration, transpiration, water uptake, growth, develop ment, flowering, fruit development, senescence, and heat flux Photosynthesis, respiration, transpiration, water uptake, growth, plant development, and senescence Photosynthesis, respiration, growth, morphogenesis, ET, nitrogen uptake, and gravitational soil wetting Photosynthesis, respiration, growth Carbon flow, photosynthesis, respiration, growth, and translocation Phasic development, morphogenesis, growth biomass accumulation and partitioning, soil water balance, plant nitrogen status Photosynthesis, assimilate distribution, and synthetic and maintenance respiration Photosynthesis, phenology, respiration, and dry matter partitioning Photosynthesis, respiration, transpiration, reserve utilization, water uptake, and stomatal control Photosynthesis, respiration, growth, senescence, phenology, infiltration, drainage, transpiration

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models but the ideas embodied in them have. In general,the more mechanistic process models discussed under each topic are the ones we have incorporated in our own models: GOSSYM, GLYCIM, and WINTER WHEAT (Table I). AND MORPHOLOGY A. CROPPHYSIOLOGY

I . Primary Processes Involved In order to grow, a crop must take up carbon dioxide, water, and various nutrient ions in the correct proportions. These materials are all essential to the plant, but the processes involved in acquiring them are not given equal prominence in most crop models. Carbon fixation is the process given most attention, partly because it is the one most often limiting crop growth and partly because it has been thoroughly researched and is therefore quite well understood, but mainly because a mass balance is essential for yield estimates. Water uptake receives almost as much attention. It frequently limits crop growth but ironically we know less about water uptake when soil water is limiting than when it is plentiful. Our understanding of the processes involved in water uptake are at best semiempirical,mostly because they involve roots which are inaccessibleand difficult to study in situ. Even less is known about the processes of nutrient ion uptake and many models omit them all together. This omission is not a problem when modeling crops that are heavily fertilized. However, it will limit the utility of crop models as the need for more economical use of fertilizer increases. Also, models that omit ion uptake cannot be used to make predictions about crops such as cotton in which a restricted nutrient supply is used to limit vegetative growth. a. Light Interception. Light or, more exactly, photosynthetically active radiation suppliesplants with the energy for COzfixation. It is fairly obvious that the amount of light intercepted depends on the leaf area of the crop, and this is usually expressed as leaf area index (leaf area per unit land area). However, it is also obvious that leaves on a crop and even on a single plant shade each other, and light interception cannot be directly proportional to leaf area index. In 1953, Monsi and Saeki showed that the decrease in light flux density with depth in the canopy approximately follows Beer’s law. In fact, light flux density decreases exponentially as the light travels through successive layers of leaves. Beer’s law strictly applies to light interception by small particles that are uniformly distributed, as for example in a fog or muddy water. While leaves in a crop canopy do not meet these criteria, the equation works quite

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well so long as the canopy is closed; i.e., the leaves of plants in adjacent rows are touching. The equation even works quite well for some canopies before they have closed but, in general, the equation is less reliable when the leaves of the crop are not uniformly distributed over the field. In the early stages of growth, crops consist of separate plants or rows of plants; i.e., the leaves of adjacent plants or rows do not overlap. Indeed, this may be true throughout the life of some crops. In these circumstances some of the light reaching the field falls on the ground without ever passing through the crop canopy. There have been several attempts to model this situation by defining the outline of the crop canopy and applying Beer’s law only to those rays oflight which pass through it. Some authors have then used numerical integration to calculate overall crop light interception (CharlesEdwards and Thornley, 1973;Allen, 1974),but this is expensivein computer time and probably unnecessary since there are approximate, analytical solutions for the same conceptual model (Palmer, 1977; Jackson and Palmer, 1979;Mann et al., 1980;Acock et al., 1985).Most ofthese interpretations of the model contain equations to deal with both direct and diffise radiation. For many purposes an even simpler approach to the calculation of light interception may be perfectly adequate. Baker et al. (1978) found that the proportion of light captured by the canopy each day was directly proportional to the height of the plants divided by the row spacing. This simple relationship holds during the period of canopy development but naturally fails during canopy defoliation at the end of the growing season (Kharche, 1984). b. Carbon Dioxide Fixation. It has often been observed that crop dry weight gain is approximately proportional to total canopy light interception (Baker and Meyer, 1966; Hesketh and Baker, 1967; Shibles and Weber, 1965). This relationship is used in some models (e.g., SORG in Table I) to predict dry weight gain but suffers from the probelm that the parameter values need to be vaned from one year to the next (Shiblesand Weber, 1966). Because of this problem, most crop models deal mechanistically with the processes involved in C02fixation. The relationship between C02 fixation and light interception has been measured many times on leaves, plants, and canopies of various crops as both an instantaneous rate and a daily integral. In nearly all cases, C02 fixation showsa hyperbolic dependence on light interception and the rectangular hyperbola is often used to describe the relationship (Acock et al., 1971). Most crop simulation models use one of these empirical relationships as the basis for the calculation of C02 fixed. In some models there is an attempt to separate one or more types of respiration from net photosynthesis and calculate those and some form of gross photosynthesis separately. Although the idea had been around for

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some time, McCree (1970) is largely responsible for formalizing the notion that a certain amount of respiration takes place to maintain plant tissue and that this maintenance respiration rate is a function of biomass rather than gross photosynthetic rate. His interpretation certainly fits the data for some crops (e.g., Baker et al., 1972) but not for all of them (Acock et al., 1979). Therefore, it may not be necessary to deal separately with maintenance respiration for all crops. Also, the idea of a fixed maintenance requirement for the crop gives rise to the possibility that maintenance respiration may exceed the amount of substrate available to support it. To avoid this situation, Thornley ( 1977) has proposed a model in which structural material that is degraded becomes part of the supply of substrate available for growth. When this substrate is used for growth the resynthesis is accompanied by the usual growth respiration. Growth respiration is associated with the synthesis of protein, oil, and other plant biochemicals. It is closely related to the amount of substrate available for growth and hence to the net C02 fixation rate. When growth respiration is modeled separately, it is normally made a function of the compounds being synthesized by the plant at that time, using the estimates of Penning de Vries ( 1975). Carbon dioxide is fixed by one of three cyclic pathways in plants. Apart from maize and sorghum, most crops of agronomic importance employ the C3pathway. These C3crops simultaneouslyrespire and fix CO, in the light. This respiration is called photorespiration or light respiration, and its rate is approximately proportional to the rate of gross photosynthesis. The ratio of photorespiration rate to gross photosynthetic rate is actually a function of temperature and the concentrations of oxygen and CO, at the site of carboxylation (Ehleringer and Bjorkman, 1977). Since oxygen and C02concentrations have the greatest influence on the ratio and these are virtually constant for field crops, most models implicitly treat the ratio as a constant. In GOSSYM it is treated as a function of temperature. Ifthe crop model is to be used to analyze or predict growth in various C02concentrations, it is necessary to model the dependence of photorespiration on temperature and oxygen and C02concentrations. This has been done by Charles-Edwards (1978, 198 1) and the result has been incorporated in GLYCIM. The rates of the various types of respiration and the gross photosynthetic rate are all influenced by temperature. Growth and maintenance respiration rates increase continuously with temperature over the range 15 - 50°C for many species, but for gross photosynthetic rate and photorespiration rate, temperature acts as one of several limiting factors (Hofstra and Hesketh, 1969). In the absence of limitations other than temperature, gross photosynthetic rate is zero at some low temperature between 0 and 10°Cand increases linearly with temperature up to approximately 35°C. It then decreases lin-

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early to reach zero again at approximately 50°C. The shape of this relationship is only seen in high light and in the absence of oxygen (Hofstra and Hesketh, 1969; Ludwig and Withers, 1978). At normal oxygen concentrations gross photosynthesisis limited by light and/or COzconcentration over much of this temperature range. Temperature therefore only affects gross photosynthetic rate when the former is very high or very low. This difference in the temperature responses of respiration and photosynthesis may in itself be sufficient argument for modeling the processes separately. As already implied, gross photosynthesis is a function of C02concentration. Most crop models treat COzconcentration as a constant, but since it is presently increasing by 2 ppm (by volume) each year (Keeling et al., 1982) and is expected to increase more rapidly in the future, it may be time to put COz concentration into our models as a variable. The equations to do this have already been developed (Charles-Edwards, 1981; Acock et al., 1985). Photosynthetic rate may also be limited by leaf nitrogen concentration (Boote el al., 1978) and by low leaf water potentials (Boyer, 1970). These limitationsare dealt with empirically in most models if they are dealt with at all. The reduction in photosynthetic rate that occurs as leaves age (e.g., Woodward, 1976) must also be modeled empirically at the moment. However, the effect of leaf age on photosynthesisis only important in crops where dry matter accumulation in the harvested plant continues until canopy senescence reduces leaf area index below 3.0. c. Partitioning. We are profoundly ignorant of the processes involved in partitioning carbon to the various organs on the plant. Some modelers use empirical partitioning factors which they vary from stage to stage in the plants’ development e.g., Wilkerson et al., 198 1). Other modelers partition carbon according to the potential of the various organs on the plant for growth (e.g., Baker et al., 1983). This approach is often linked to a system of priorities for various organs, so that, for example, seeds may have first call on the carbon available. It is also common for the growth potential of various organs to be reduced by shortages of water, nitrogen, etc. It seems logical to suppose that natural selection over the millennia will have ensured that present-day plants have survival and reproduction as their highest priorities. On the basis of such considerations, Acock and Allen (1 985) have suggested that plants have the following order of Priorities for carbon use: (1) survival, (2) reproduction, (3) growth of existing organs, (4) increase in number of organs (mostlyby branching), and ( 5 ) storageof excess carbon for future use. When the higher priorities for carbon use are being met, or cannot be met because of environmental limitations, the next priority will be addressed. Some plants stop fixing COzwhen all possible uses for carbon have been met. It is not always easy to translate these general priorities into specific priori-

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ties for organs on the plant. Annual plants, of course, give priority to seed production because this is the only part that survives to the next growing season, but plants that are perennials in their native habitat will often have conflicting interests in both survival and reproduction. This explanation of the partitioning of carbon is teleological rather than mechanistic of course, but teleology can serve the modeler if it results in good predictive capability. Another useful teleological explanation of carbon partitioning that is widely accepted among crop physiologists is that plants act to maintain a functional balance (Szaniawski, 1983). This means that when some material essential to plant growth is in short supply, the organs nearest the source of that material, i.e. those responsible for acquiring the material, will have proportionately more carbon partitioned to them. For example if some nutrient ion is limiting growth, root growth will be increased at the expense of shoot growth. That plants maintain a functionalbalance has been demonstrated repeatedly (e.g., Brouwer and de Wit, 1969; Sanders and Brown, 1976).

Models of root/shoot partitioning which maintain a functional balance between the carbon supply from the shoot and nitrogen supply from the root have been described by Brouwer and deWit (1969), Thornley (1 972), and Charles-Edwards(1976). Similarly, Acock efal. (1985) have incorporated in GLYCIM a model of root/shoot partitioning which maintains a functional balance between carbon from the shoot and water from the root. The rationale is that when water uptake by the root is insufficient to maintain shoot turgor, carbon that would otherwise have been used by the shoot is diverted to grow the root. However, when the shoot is turgid, it has priority for use of the carbon merely because of its proximity to the source. Thus, in this instance, we can suggest a plausible mechanism by which the plant can maintain a functional balance. In GOSSYM and many other models a functional balance is effectively maintained by modifiying the potential growth rates of various organs (and hence the carbon partitioned to them) according to the stresses experienced by the plant. d. Tissue Expansion. Very few crop models deal with tissue expansion explicitly. In many of the models that do, only leaf tissue expansion is important. Usually, the increment of dry matter partitioned to leaves is multiplied by specific leaf area (SLA = leaf area divided by leaf dry weight) to give the increment of increase in leaf area. Specific leaf area is often taken as a constant, but in fact we know that it vanes greatly with the environmental conditions in which the leaf expands (Acock, 1980) and may also vary with its point of insertion on the plant (Koller, 1972). A more mechanistic approach is to calculate potential tissue expansion as a function of temperature and to calculate the amount of carbon and nitro-

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gen available to support that expansion. Temperature and carbon and nitrogen availability can all limit tissue expansion individually. For a given species, leaf tissue alwayscontains a certain minimum ofdry matter (maximum SLA) and nitrogen. Presumably if these are not available, expansion cannot take place. Similarlyat the other end of the scale, it is often possible to discern maxima of structural dry matter and nitrogen per unit area of leaf tissue. Unfortunately, very few determinations of structural dry matter (total dry matter minus starch and sugars) are ever made; as this will be maximum under high light and high COZY the observation is a fairly simple one. Another factor which limits tissue expansion is water availability. Most models deal with this empirically if they deal with it at all, but the mechanisms are known and can be modeled. On most days, as the solar radiation flux density increases, transpiration rate increases and leaf water potential decreases in order to increase the water potential gradient and hence the water uptake rate by the roots. (This process will be examined in more detail in Section II,B,2 under the heading “Evapotranspiration.”) As leaf water potential decreases, so does leaf turgor pressure and this immediately decreases leaf expansion rate. Green et al. (1 97 1) have shown that the organ expansion rate is proportional to turgor pressure (P) minus a turgor pressure threshold (P’). They have also demonstrated that when P changes, P’ changes in the same direction. If P decreases faster than P’can adjust, leaf expansion is inhibited. An empirical model of the rate at which P’ changes has been developed from data (Acock et al., 1985) which fits field observations of soybean leaf expansion rates made by Wenkert et al. (1978). During late afternoon and evening, transpiration rate decreases and leaf water potential and turgor pressure increase again. This increases the value of P - P’ and causes a period of very rapid tissue expansion until P’ has adjusted to nearly equal P. In this way the potential tissue expansion lost during the middle of the day is recovered during the evening in crops with adequate water. In crops experiencingwater stress similar changesoccur, but for part of the day, P falls below the minimum level to which P’ can adjust. For that part of the day the loss of potential expansion is not recoverable. In the work of Green et al. (1 97 1) with Nitella, the minimum value ofP’ was 0.2 MPa (2 bars). Obviously the use of this mechanism in a crop model necessitates the use of several time steps for each day simulated, and this has been done in GLYCIM. The expansion of stems and petioles is often ignored in crop models, but it must be calculated if the light interception model being used requires an estimate of the volume occupied by the canopy. Expansion of these tissues can be modeled in exactly the same way as for leaf laminae. However, it is important to remember that these tissues do not have a uniform dry matter

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content down their entire lengths. They are narrower at the distal end than they are at the proximal end and each increment of linear growth requires more dry matter than the previous increment. e. Morphology. Crop morphology is the resultant of two independent processes: organ initiation and organ abortion. Clearly these are distinctly different processes responding to different plant and environmentalfactors, and hence, they must be modeled separately (Baker et al., 1973). For most plants, the rate of appearance of new nodes on any axis is a function of temperature. In some species the rate is limited by the availability ofcarbon, water, nitrogen, etc., but in other species the rate is influenced very little by these factors unless they are in very short supply. For species in the latter category, if some material such as water is in short supply, the expansion of leaves, petioles, and stem internodeswill all be inhibited but new leaves will continue to appear at a rate dependent only on temperature (e.g., Mayaki et al., 1976). The number of branches or tillers on crop plants varies with plant density; more form on plants in widely spaced rows than in narrowly spaced rows (e.g., Enyi, 1973). Consequently,some modelers calculatebranch number as an empirical function of plant density. The major problem, however, is that the relationship varies with solar radiation and C02 concentration. The situation can be modeled mechanistically by assumingthat it takes a certain increment of dry matter in excessof that required for the growth of the rest of the plant to start a new axis (Charles-Edwards, 1984; Acock et al., 1985). Nitrogen availability is also known to affect branching (Aspinall, 196 1 ; Phillips, 1968) and, presumably, the same is true of other nutrient ions. Unfortunately, we do not know how much of each of these materials is necessary before a branch can be formed. We can, however, try various amounts in our models and see which give us the right answers. In some species the number of branches that can be formed may be limited by the number of sites available or there may be a limited time during which branches can form because the plant passes on to the next stage of development. Very little experimentalwork has been done on organ abscission,and crop models are correspondinglydeficient in this area. In many models, leaves are abscised after a fixed number of days and for some speciesthis givestolerably good results. However, we know that leaf life can be reduced by certain conditions such as water stress (Sionit and Kramer, 1977) and low light (Ludwig et al., 1965). It may be that these conditions have independent effects on leaf longevity but there is at least one common element; both of them affect leaf photosynthetic rate. Several decades ago it was popular to suppose that the lower leaves on a plant were parasitic, that is, that they imported more carbon than they

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exported to the rest of the plant (Davidson and Philip, 1958). However, experimentsdesigned to determine optimum canopy leaf area soon revealed that leaves were abscised as soon as they became parasitic (Ludwig et al., 1965). Provided we accurately model the photosynthetic characteristics,the light environment, and other critical factors for leaves at the bottom of the canopy, we can determine if they are self-sufficient for carbon or should be abscised. Parasitism cannot be used as the only criterion for leaf abscission. Even fully exposed leaves that are well supplied with water and nutrients eventually become senescent. However, the reduction in photosynthetic activity in these leaves occursat a much slower rate than the reduction in leaves that are being buried progressively deeper in the canopy. Sinclair and de Wit ( 1976) have tried to link it to the transfer of nitrogen from the leaves to the seeds in soybean. Their assumption was that remobilization of this nitrogen resulted in leaf deterioration. However, Nooden (1984) has shown in a series of experiments that (1) pod development and foliar senescencecan both occur in soybeans without nitrogen being extracted from the leaves and (2) leaf senescence shows no direct relationship to pod load; leaving a few pods on a plant is sufficient to cause nitrogen to be extracted from the leaves even though the pods are not a very large sink for nitrogen. This experimental evidence effectively invalidates the Sinclair and de Wit hypothesis. Instead, Nooden’s results suggest that terminal leaf senescence may be triggered by the first few seeds that reach their full size. Of the many criteria that we have tested so far in our soybean model, this one has given the best results. It may be that similar criteria will be found appropriate for other species. Presumably the effect of the seeds on the leaves is mediated by some hormone. The timing of the developmentof reproductive structures will be discussed in the next section, but the number of such structuresis correctly considered here under morphology. In some species, vegetative and reproductive development occur simultaneously, whereas in others there is a distinct and abrupt transition between the two stages. In the former case, it is necessary to predict the rate at which the flowers appear. In the latter case, flowering is treated as a phenological event. The rate of flower appearance is usually modeled as a function of temperature with appropriate reductions in the rate to allow for delays caused by stress. Stress is defined here as any combination of conditions, including shortages of metabolites which interfere with growth (Baker et al., 1983). Most agronomic models treat flowers merely as the sites for potential fruits. Flowers themselves take an insignificant amount of energy to produce and since they are not a big drain on resources. Most plants produce two to four times as many flowers as they can ever turn into fruits (Hansen and Shibles, 1978). Whether the flowers appear singly or in large numbers at the same

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time on a plant, the crop model must be able to predict how many (and in some cases which) of these flowers will become fruit. In the same way as for branches, the number of fruit set seems to depend on carbon and nutrient source - sink imbalances. The relationships between fruit sinks and sourcesink imbalances are not well understood, but Baker and Acock (1986) have proposed a conceptual model of stress physiology in cotton including the hormones that are possibly involved. 1: Phenology. Because of early successeswith heat units in predicting the timing of growth stages in maize, modelers have tended to assume that the heat unit concept is universally applicable. The theoretical basis for the technique is that, of the processes involved in crop development, all are sensitive to temperature and one will be limiting. The temperature response of the limiting process will be the temperature response of overall crop development. It is further assumed that the rate of that process is proportional to temperature between certain limits. If that assumption is incorrect, or different processes limit at different times, the technique will not work. Clearly, we should not expect to accumulate the same number of heat units between successive growth stages throughout the life of the plant. Experiments in controlled-environment chambers are necessary to determine if heat units are a suitable predictor of crop development. The practice of assuming applicability and determining the equation parameters from field data is common but can give unreliable results. Certainly temperature is the main driver of progress through the vegetative stages of plant growth and for many species those stages can be linked to a certain number of accumulated heat units. As discussed under morphology, this is true for some crops regardless of stressesencountered new nodes appear on the main stem and branches as a function of temperature only except in extremely stressful conditions. For other species, mild stresses delay development. It should also be remembered that there are both lower and upper limits to the temperature response of plants, and for many crops both limits are encountered during their growing season. Plant development through the reproductive stages may also be wholly or partly a function of temperature but for many species photoperiod is important too. It is not appropriate here to discuss all that is known about the mechanism connecting photoperiod and the flowering of plants; we would not wish to put that much detail in a crop model. However, the understanding developed by physiologists should not be ignored either. This is effectively what happens in the majority of agronomic studies which seek an empirical relationship between temperature, photoperiod, and the interval between planting and flowering(e.g., Major et al., 1975).Our models should acknowledgethat a plant must acquire its first true leaves before it becomes

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sensitive to photoperiod, that photoperiod has its greatest effect on the time taken to induce the initiation of floral primordia in the apex, and that the subsequent development must be largely a function of temperature because existing leaf primordia must be expanded before the flowers can appear. Recognizing these stages of development and modeling progress between them separately should improve the predictive capability of our models. A fairly common misapprehension about the photoperiodic response is that plants flower when they are exposed to a critical photoperiod. Although this is true of some species, most crop plants make progress toward flowering in any photoperiod, although the rate depends greatly on that photoperiod. Moreover it is possible, at least in some plants, for flowers to be initiated and then if the photoperiod changes, for the plant to revert to vegetative growth (Borthwick and Parker, 1938; Battey and Lyndon, 1984). There is also evidence that soybeans are sensitiveto the direction of change in day length so that they initiate flowers more rapidly when photoperiod is decreasing over the same range (Gamer and Allard, 1930). Another problem not generally recognized is that photoperiod is not the same as calculated astronomical day length. Astronomical day length is defined as the period between sunset and sunrise. The latter occur when the upper edge of the sun’s disk appears to be on the horizon, with an unobstructed horizon and normal atmospheric refraction. At sunset and sunrise on clear days, light flux density on a horizontal surface is about 1 W/mz PAR. Takimoto and Ikeda (196 1) have shown that several species are photoperiodically sensitive to light levels of less than 1 W/m2 PAR, and furthermore, that the threshold of sensitivity is lower at dawn than at dusk. Francis (1970) has explored the relationship between astronomicalday length and photoperiod measured at these light intensities and has found that photoperiod can exceed day length by up to an hour. With the photoperiodicresponses being triggered at such low light intensities a sequence ofcloudy days could have an appreciable impact on the timing of flowering. We know enough about all these phenomena in soybeans to model them mechanistically, but few models recognize this complexity. Finally, it is known that the photoperiodic processes leading to floral induction are influenced by temperature. Hadley et al. (1984) have represented this temperature- photoperiod interaction as a three-dimensional response surface. They found for soybean that the surface consisted of a number of intersecting planes. Unfortunately such data are not available for most crops. Even the data of Hadley el al. are only for plants grown in a constant photoperiod and they therefore do not include the effect of the direction of change in day length on time to flowering. Ultimately,the ability to predict the flowering response of crops seems likely to come from under-

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standing the separate effects of temperature and photoperiod on the size of the apical dome (Homdge and Cockshull, 1979; Charles-Edwards et al., 1979).

2. Limits and Stresses Crop modelers find all too frequentlythat the equations they have written to describe some process, under certain combinations of circumstances, allow the rate of that process to increase without limit (run away). Similarly, the equation may predict rates for the process that are too low or even negative. The most common reaction to either of these situations is to place artificial limits on the range of values that the process rate can take. This use of limits isjustifiable if we wish to restrict the variable under consideration to taking values of a particular sign or values between zero and one. For instance, the ratio of carbon supply to carbon demand can theoretically take values between zero and infinity. If the ratio has a value less than one, carbon supply will limit certain plant activities but if it is greater than one, carbon supply is greater than demand and does not limit any activities. Therefore, by restricting the ratio to values between zero and one, we can use it as a multiplier for the relevant plant activities. This is just a mathematically convenient way of achieving a certain result. However, the use of limits with numerical values usually indicates ignorance or an unwillingness to model the system mechanistically. For all processes that we understand fully, the rates are limited either by the levels of environmental factors or by substrate availability. Even when the ranges of values that may be taken by various process rates have been correctly defined, it is still necessary to deal with the effects of various stresses. The dictionary definition of stress is a “constraining or impelling force.” In the agronomic context, we use the term to mean any condition that reduces the rate of a physiological process. Thus, shortages of light, water, and nutrients are all stresses. Very few crops grow to their full potential, and thus crop modeling is basically an exercise in correctly predicting crop response to stress. There are three methods in common use for dealing with stress effects. These treat stresses as additive, multiplicative,or limiting. The additive method equates a given level of stress with a certain reduction in the rate of a process. The method is seldom used in simulation models but is implicit in the use of linear multiple regression equations. The multiplicative method equates a given stress with a percentage reduction in the rate of a process. Its use is widespread. The limiting method equates a given stress with a certain limiting rate of the process, i.e., a rate that cannot be exceeded.

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These methods can all give similar results if we consider only a single stress, but the differencebetween them becomes obvious if we look at interacting stresses. Consider, for example, leaf dry weight gain. Suppose that a crop grown in a low-light environment has a rate ofphotosynthesissuch that the rate of leaf growth (dry weight gain) is halved. Another crop, grown in high light, experiences a nitrogen stress which halves its rate of leaf growth. What will the various models predict as the leaf growth rate for a crop grown under a combination of these two stresses? The additive model will predict zero growth rate (1 - 0.5 - 0.5 = 0). The multiplicative model will predict 0.25 of normal rate (1 X 0.5 X 0.5 = 0.25). The limiting model will predict 0.50 of normal rate because the factors are considered to act independently in imposing an upper limit on the rate of leaf growth. Which of these predictions is correct? We have already stated that for all processes that we understand fully, the rates are limited by some level of environmental factor or by substrate availability.In other words, the limiting model is usually the most appropriate. In our example, unit leafarea must contain certain minimum amounts of carbon and nitrogen. Low light will limit carbon supply and hence leaf growth. But if the nitrogen requirement is halved, the nitrogen stress will impose no further limitation. Considerationofthe physiology involved leads to the use of the limiting method. Blackman’s law of limiting factors (Blackman, 1905)does not completelydescribe the interaction between stressesbut it is still the best model available. In our models, for each process considered, we calculate a potential rate as a function of the prevailing temperature, test to see which stress most limits that rate, and from that calculate an actual rate. Occasionally, where we know the relative effect of some factor but not the absolute effect, we use the multiplicative model because that is the least objectionable alternative. B. SOILPROCESSES We now consider the below-ground processes. Figure 4 is a schematic diagram of the soil matrix and plants. The natural soil horizons are imposed upon this grid so that there may be from 1 to 20 layers per horizon. The soil processes are described in a model called RHIZOS (Lambert ei a/., 1976). 1. Water Movement As was mentioned earlier, in the present form of our models we use daily total rainfall. However, we are planning to change this to hourly or more

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1

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

N K C O L U M N

FIG.4. Spatial configuration of RHIZOS.

frequent measurements for on-farm versions of the model. With the advent of portable, solar-powered weather stations, we can collect data with this frequency. However, historic data will have to be handled as before, or else some statistical distribution of rainfall throughout the day for that location and time of year could be used. Therefore, water enters the surface soil and fills the profile, layer by layer, until that horizon’s “field capacity water content” is reached. Excess rainfall is counted as deep seepage or runoff.

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The lower layer of soil is considered to be a time-dependent, water content boundary. Therefore,drainage out of or into that layer will depend upon the hydraulic gradient associated with the water content. In our models this lower boundary is usually 1 or 2 m deep and therefore the water content does not change rapidly, especially under irrigated conditions. The water content - matric potential (pressure head) relationship and water content -diffusivity relationship are taken from Brooks and Corey (1 964) and Gardner and Mayhugh (1958), respectively. They are (0, - er)/(es - or) = ( V / B / V ~ ) ~ ' - ~ ~ ' ~

ei= e,

Wi

WB

(la)

fi

WB

(1b)

and

o(4)= Do ~ X BP (4 - 8 0 )

(2) where 0, is the volumetric water content at the matric potential, wi; 6, is the saturated (including entrapped air for field values) water content; 8, is the residual water content; yBis the air entry value for desorption relationships; q is a soil characteristicparameter; Do is the soil water diffusivityat the water content 8;, and pis another soil characteristic parameter. The methods for estimating the soil characteristic parameters are given in Whisler (1976). More recently we have changed the form of the relationship between 0, and tyi [ Eq. ( la)] to

where a,m,and n are constants for each soil horizon. This form has been found by Otto Baumer (personal communication, USDA-SCS National Soils Laboratory, Lincoln, Nebraska) to fit measured desorption relationships for several hundred soil samples. The fit is generally better than Eq. (la). The hydraulic soil properties are used in the capillary flow and water uptake subroutines. In these calculations, fluxes between soil cells are calculated using the diffusivity form of Darcy's law. Soluble ions, such as nitrate, are assumed to move with the water. 2. Evapotranspiration The dilemma facing anyone who models evapotranspiration is that the most mechanistic models require information not readily available, while the empirical models do not have good predictive ability. The most mechanistic models deal with energy fluxes in the crop and the turbulent transfer of

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C02 and water vapor between the soil, plant, and bulk atmosphere (e.g., Stewart and Lemon, 1969). These models enjoyed a brief period of popularity during the early 1970s when it was thought that they could be used to

estimate the photosynthetic rate of field crops without confining the plants. Unfortunately, they never fulfilled their early promise because measurement errors severely limited the accuracy of the prediction. This alone would not preclude their use in simulation models, but they also require information about stomatal aperture, leaf water potential, and wind turbulence, as well as relationships between these and other environmental factors. These relationships are difficult to model. The normal solution is to use empirical relationships between, for example, solar radiation and stomatal resistance and treat them as though they were fixed relationships. Often, as in the above example, there is no mechanistic relationship between the variables so an empirical relationship is unreliable. Ultimately, the results obtained with such models do not justify the effort of determining the value of parameters (Heilman and Kanemasu, 1976). A simpler alternative and the one used by most crop modelers is the venerable Penman equation (Penman, 1963). This equation is mechanistic to the extent that it models evaporation from a free water surface. However, it deals empirically with crop roughness and the resultant effect on wind turbulence. It also only applies to a crop that is freely evaporating, i.e., not experiencing water stress. Thus the equation is most useful for calculating potential evapotranspiration and additional models are needed to predict how this will be limited in order to calculate actual evapotranspiration. The Penman equation requires a knowledge of solar radiation, wind speed, temperature, air humidity, and the albedo of the soil and crop. Because this information is not always readily available, some modelers use simple empirical equations derived from the Penman equation by Procrustean approximation (e.g., Tanner and Jury, 1976). Albedo is another variable in the Penman equation that is not commonly available. Most values ofcrop albedo range from 0.2 to 0.25 (Fritschen 1967; Linacre, 1968, 1969; Ritchie 197 1) and we are probably safe in assuming a constant value of 0.23 in our models. The albedo of bare soil varies greatly with soil color and water content. Idso et al. (1 975) have shown for one soil that albedo is inversely proportional to water content at the surface. Our reading of similar data scattered through the literatureleads us to believe that a single relationship may hold over a wide range of soil types. This is possible because the light-colored soils are sandy and have low water-holding capacity while the darker soils are heavier and generally have higher water contents. Of course the relevant soil water content is that of the surface soil crust, rather than the bulk soil. The surface dries out very rapidly following rain.

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Increasingly, however, crops are planted in soil that is still covered with litter from the previous crop. Albedo vanes greatly with state of decomposition of the litter and is very hard to predict. The NTRM (nitrogen tillage residue management) model treats this problem in detail (Shaffer and Larson, 1982). Soil water evaporation and transpiration are limited by different mechanisms and fall below their potential rates at different times after a heavy rain. It is therefore desirableto model them separately. Water evaporatesfrom the soil surface at the potential rate only as long as the surface is saturated: a condition that persists for 3 or 4 days at most. Thereafter, evaporation rate falls continuously as a surface mulch of dry soil develops. Ritchie ( 1972) has developed empirical equations for several soilswhich relate evaporation rate to time after rain and these are still widely used. However, the equations do not allow for the effect of plant roots drying the lower layers of soil and rapidly reducing the movement of water to the soil surface. A more mechanistic approach has been pioneered by Rowse ( 1979, who calculates the rate at which water moves toward the soil surface depending on the hydraulic diffusivity and soil water potential for the top soil layer. If this rate of water movement to the surface is less than the potential evaporation rate, then it is taken as the value for the actual evaporation rate. Hydraulic conductivity and water potential in various layers of soil are readily calculated. However, there is a very steep gradient in water potential near the surface of a drying soil and the only way to correctly simulate this, using the present numerical methods, is to treat the top soil as if it were composed of a large number of thin layers of soil with different water contents. This is possible but computationallyexpensive, and no desirableanalytical solution is yet available. Crop transpiration rate occurs at the potential rate (dictated by climatic variables) until the roots can no longer take up water at that rate and the stomata begin to close. This condition is more likely to occur in the middle of the day than at any other time and normally persists for only a few hours. Furthermore, water uptake rate depends on the length and age of plant roots, soil water potential in the vicinity of those roots, and the previous stress history of the plant. The relationships are very complex and almost impossible to model empirically, although that is what most crop modelers attempt to do. A mechanistic approach requires the use of several time steps during each simulated day because of the ephemeral nature of the phenomenon. Mechanistically, the maximum water uptake rate can be calculated by dividing the soil profile into a number of layers and columns (Fig. 4) and looking at the behavior of the roots in each of the cells so formed. Water uptake rate from a given cell will equal the water potential gradient between

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the soil in that cell and the leaves, divided by the sum of resistances in the pathway between the soil and the leaves. This model is analogous to Ohm’s law. Summing over all the soil cells that contain roots enables us to calculate maximum water uptake rate for the average plant in the crop. It has been shown repeatedly that water uptake rate is not proportional to the water potential gradient between soil and leaf (Hailey et al., 1973) or to the total length of plant roots (Eavisand Taylor, 1979).These findingswould appear to invalidate the use of the Ohm’s law analog proposed above. However, studies of these relationships have all ignored variation in root radial resistance with root age and effects of high transpiration rate on root growth. In fact young roots have a much lower radial root resistance than old roots (Brouwer, 1965;Graham et al., 1974,cited by Scott Russel, 1977).Also, it is highly likely that a high transpiration rate enhances root growth. This is because a high transpiration rate tends to cause a loss of tissue turgor in the shoot which stops shoot expansion. It seems plausible that under these conditions the carbon that was being used for shoot growth would be made available to the root. In support of this, our own observations show more root growth during the day than the night. Therefore, under conditions of high transpiration, root growth will be more rapid, it will produce more root with a low radial resistance, and the water uptake rate will be higher than would otherwise be expected. This is the sort of relationship frequently observed. Thus a realistic, mechanistic model must deal separately with young and old roots in each soil cell and allow for the amount of root growth occumng during the course of the day.

3. Soil Temperature Most crop models ignore soil temperatureand any effect that it might have on the crop. However, in crops such as the cereals and peanuts, a lot of important activity occurs near the surface of the soil and the surface temperature cannot be ignored. Essentially, predicting soil temperature is a matter of modeling the fluxes of heat to and from the soil surface and between different parts of the soil. Again it is convenient to divide the soil into either layers or layers and columns. The latter is preferable because heat flux between the crop rows is markedly differentfrom heat flux under the rows. a. Heat Fluxes at the Soil Surface. At the soil surface, heat is gained from solar radiation and lost by reradiation, evaporation, and convection to the atmosphere and by conduction to lower layers of soil. The equationsgoverning these energy transfers are well-known but their forms are inconvenient. For instance, the equation for reradiation includes the fourth power of the

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soil surface temperature. We would like to exclude soil surface temperature from our calculations, if possible, because it is difficult to predict and even more difficultto measure accurately. Fortunately, Linacre (1968)has shown that all of these heat transfer equations may be approximatedby equations in which the heat flux is proportional to the difference between air and soil surface temperatures.Similarly,the equation for heat transfer by conduction into the soil has heat flux as a function of the difference between soil surface temperature and deep soil temperature. All of these equations can be solved simultaneously to eliminate soil surface temperature and directly calculate downward heat flux into the soil. Of course, soil moisture content at the surface is an important variable in these equations for its effect on both albedo and soil thermal diffusivity. Litter on the soil surface has a profound effect on these heat fluxesjust as it does on soil water evaporation. This effect of litter on heat flux is usually ignored or dealt with empirically; no one has yet proposed a mechanistic approach. b. Heat Fluxes within the Soil. An excellent, and perhaps the only, source of ideas about the mechanisms governing heat transfer in soils is DeVries ( 1966).He has developed equations to calculate soil thermal diffusivity from soil texture, organic matter content, water content, and total pore space. The equations treat soil as a system of randomly oriented particles in a continuous medium of water or, when the soil is fairly dry, in a continuous medium of air. Air-filled pores are also considered as inclusions in the first instance and water-filled pores as inclusions in the second instance. In the air-filled pores, heat moves through the air both by conduction and by the evaporation of water at one end and its condensation at the other, as in a heat pipe. Having predicted the thermal diffusivity of the soil in each cell, we can calculate the geometrical mean thermal diffusivity for each adjacent pair of cells and apply this figure to the transfer of heat between these cells. However, it is necessary to move the heat in small increments. This is because the heat capacity of soil is small and thus moving heat too rapidly between adjacent soil cells can result in the temperature gradient being reversed and sometimes even exaggerated. This problem can be partly overcome by integrating the instantaneous flux rate equation over time in such a way that heat transfer between adjacent cells tends to bring them to the same temperature. Even with such an equation, it is still necessary to choose a time step such that the temperature change in a given cell during a single step is always less than 0.25 of the difference in temperature between that cell and its neighbor. This is because most cells in the soil profile have four adjacent cells and if they all remove heat from the given cell, instability can result. As a result, the time step through the soil temperature subroutine has to be much smaller than for other modules in a crop simulation model.

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4. Soil Mechanical Impedance The effectsof soil mechanical impedanceare calculated in the root impedance and root growth subroutines. A relationship between soil penetration resistance and root growth was published by Taylor and Gardner ( 1963).It is RG = 104.6 - 3.53PR

(4)

where RG is the percentage root growth compared to nonimpeded growth and PR is penetration resistance in dynes per square centimeter. The relationship was found to hold for cotton over a wide range of soil types. The relationship between penetration resistance, soil bulk density, and soil water content for Norfolk sandy loam soil published by Campbell et al. (1974)is used in these simulations as a table look-up procedure. If the relationship were known for other soils, then it could be used. These calculations require the input of the bulk density for each soil horizon to be used in the simulation.

5. Soil Oxygen Content

The soil oxygen subroutine relies mainly on work reported by the Auburn Rhizotron Group (Melhuish et al., 1974;Eavis et al., 1971).The oxygen concentration is calculated for the soil profile using apparent diffusion coefficients and root-soil oxygen consumption rates as functions of the calculated soil water content, temperature, and root densities (Melhuish et al., 1974).Root elongation rates are then reduced, as indicated by Eavis et al. (197I),when the oxygen concentration falls below 10% of 0.10atm. Thus, cultivation and wheel traffic will affect the soil aeration as well as normal water flow. The mass flow of oxygen into the soil due to water depletion is taken into account.

6. Nitrogen Transformations and Movement

The nitrogen transformations in these models use a subroutine published by Kafkafi et al. in 1978. It accounts for the changes from organic to ammonium to nitrate forms of nitrogen. As was stated earlier, the nitrate ion is assumed to move with the water. The organic and ammonium forms of N are assumed to be immobile. Other subroutinescould be inserted in place of this one, as long as the input data needs could be met.

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7. Other Chemicals As these models are used increasingly as on-farm management tools, the effects of various chemicals such as fertilizer nutrients, herbicides, and pesticides will have to be simulated.Also the effectsof pH and aluminum toxicity will have to be modeled. This is part of a never-ending process of upgrading crop simulation models in order to make availablebasic research to growers. C. PESTS Simulations of insect, weed, and nematode populationsand epidemiology of plant pathogens are premised on a detailed understanding of biological, ecological, and behavioral responses and damage capability of each species in relation to biotic and abiotic factors in the environment. Although complex, simulations of pests can be synthesized in steps of increasingcomplexity leading to a final usable simulation model. Some crop simulation models have been designed to interface with pest models for the purpose of pest management decision making. This implies sufficiently detailed descriptions of the plant to identify the site and nature of the attack or damage. The population dynamics data required for insects and nematodes are very similar. The relationship of individual development to temperature, nutrition, and other pertinent factors is required to provide an age stratification of populations at all times. Age stratification provides a basis for determining when the various events in the population dynamics of insects and nematodes will occur. Reproductivepotential and mortality due to climatic, biological control, pesticides, and cultural practices are essential to determine numbers of pests to be expected. Fecundity and interactionsof mortality factors are difficult to determine and require well-developed experimental designs. If damage is to be considered in the simulation, individual potential damage to the crop, preferably with the effects of other factors on the damage rate, must be included. Early insect models (e.g., Hartstack, 1982; Hartstack et al., 1976, 1981; Ives et al., 1984; Curry et al., 1980; Gutierrez and Wang, 1979; Gutierrez et al., 1975) have related to specific pests. However, the current demand for insect control simulations for onfarm use demands that models be expanded to multispecies status so farmers can make proper insect control decisions. A comprehensiveseries of models ofthe nematode/grapevine system have been developed for California wine grapes (Ferris, 1976, 1978, 1980; Ferris et al., 1978; Duncan and Ferris, 1983). The series provides an excellent demonstration of both procedural and mathematical methods for the devel-

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opment of a nematode population dynamics model. The accumulation of nematode data is a laborious, time-consuming activity requiring perseverance and ingenuity. Weed simulations will require that various weed species be modeled in a manner similar to the crop species, as described for plants in this discussion. However, the modeling of the plant configuration is compounded by the capability of some species to vary their geometry in response to competition with other weeds and crop plants. Early model research has been directed toward determining the configurations of specific weeds under various row spacings of crops and as individual plants. The determination of potential weed populationsin crop fields is complicated by the longevity ofseedsin the soil, which may exceed 20 years in some species. Therefore, early models are concerned with competitive growth of weed populations, that may be estimated from field data, growing simultaneously with the crop. Future models should encompass the reproductive physiology of the weeds, the detailed interaction of applied herbicides with plant growth and improved understanding of impact of weed growth competing with crop growth. Disease models currently in use are simplistic epidemiology models of plant pathogens designed to aid the timing of pesticides applied for control. However, simulations have played only minor roles in understanding epidemics or as a means of managing epidemics. Appreciable research must be directed to the factors affecting epidemiologyof pathogens to permit proper couplingofthe pathogen simulationwith simulation ofgrowthto the host, to mobility and transport of pathogens, and to variability of pathogens during a growing season. Therefore, future basic research should be directed into the area of epidemiology and relationships with the host. Early models of the crop pests have been developed but few give sufficiently precise estimates to provide reliable research for farm management tools. A major deficiency is the lack of data of high quality for modeling purposes. Improving technology and an awareness of the potential of pest simulations to contribute to modem farm management should overcome these deficiencies in the near future. D. DATAACQUISITION

I . Data Needed to Run Crop Simulation Models All crop simulation models require as input, data on the management of the crop, as well as the macro- and microenvironmental parameters associated with the weather and the soil. Management data consist of the latitude of the site, row spacing, plant population, amount and timing of fertilizer

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applications, and similar information. The relevance of this data is readily apparent to experimentalagronomists.However, when modelers ask experimentalists to collect detailed data about the weather and soil, the significance of the request is not always understood. a. Daily Weather Data. There is little disagreement among modelers about the weather data required to drive a crop simulation model. These data are total solar radiation incident on the top of the crop canopy, maximum and minimum air temperature above the crop, rainfall, and irrigation. In addition, some models can make use ofwind run and some measure of the water vapor content of the air. These data are all available from a class A weather station, except for the essential addition of solar radiation. Most crop models make use of daily data because they are readily available and therefore many of them use a daily time step. However, some models can also make use of regular (hourly) measurements of the following variables: solar radiation flux density, photosynthetic photon flux density, air temperature, leaf temperature, rainfall, wind flow rate, and water vapor content of the air. b. Soil Data. There is tremendous variation in the amount of soil data required for different crop simulation models. Many models deal with below-ground processes very crudely and as such may only require information about the rooting depth of the soil and its water holding capacity. At the other extreme the most comprehensive models require (1) depths of the major soil horizons, (2) for each horizon, the particle size analysis, bulk density, water release curve, and saturated hydraulic conductivity, (3) residual fertilizer content at the start of the season, (4) organic matter content of the soil at planting, and ( 5 ) deep soil temperature (1 m or deeper). This more detailed information is generally only available for soils on experimental farms. However, it can be obtained by coring any site, and the cost of doing this for each field on a farm can easily be justified by the improved returns from using a crop simulation model as a farm management tool. Even so, there is a great attraction to making use of existing soil data sets such as those developed by the Soil Conservation Service. This option is just being explored by modelers (see Section II,B,l). 2. Data Needed to Develop Crop Simulation Models

The data needed to develop a model will depend on the species under consideration and the type of model to be constructed. Essentially, all simulation models require informationabout the initiation,growth, and abortion of organs on the plant as affected by the relevant environmental and physiological variables. This in turn implies the use of controlled environmentsfor

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gathering the data so that the environmental factors can be varied independently. In the field, environmental factors are often highly correlated and their effects cannot be separated. This remains true despite the use of multiple regression analysis;even the protagonistsof that technique have to admit that sometimes the parameters derived from the analyses make nonsense agronomically (Waggoner, 1983). a. Experiments. In most models, temperature is the primary driving factor, and other environmental factors are thought of as limiting the crops’ response to temperature. In some models, however, all environmental factors are envisaged as reducingcrop response from some theoretical potential level. With both approaches the first experiment is usually to grow crops in a range of temperatures with other factors nonlimiting: high light flux density, high COz concentration, ample water and nutrients, and a deep porous rooting medium. In subsequent experiments, other factors that limit growth may be examined by growing the crop at various levels of those factors over the range of interest. Normally, soil water and nutrient availability are the first factors to be considered in these subsequent experiments. Since most crop models deal mechanistically with COz uptake and water loss, it is desirable to measure light interception, photosynthesis, respiration, and transpiration of the whole crop canopy. Essentially the same observations are made in all the experiments: (1) canopy CO, exchange and average light flux density every few minutes, (2) water transpired by the canopy and average air humidity every few minutes, (3) timing of progress from one growth stage to another, (4) rates of appearance of branches, leaves, flowers, and h i t s , ( 5 ) rates of expansion and dry weight gain of stems, leaves, fruits, and roots, and (6) timing of senescence and abscission of leaves and fruits. When soil water availability is a variable under study, soil water content is usually measured at several depths in the profde and leaf water potential is measured to the extent that destruction of the canopy can be tolerated. b. Controlled-EnvironmentEquipment. We have already stated that field data cannot be used to develop crop simulation models because it is impossible to separate the crop responses to the various environmental factors. The same is true of greenhouse data, in which temperature is the only environmental factor that can be varied independently of the others. This leaves the choice of using either artificially lit or sunlit controlled-environment chambers, both of which have problems of their own. In artificallylit chambers, the quantity of light available is usually too low, and its spectral composition differs from that of sunlight and often leads to abnormal plant growth and development. Xenon lamps could overcome these objections to light quantity and quality but they pose other problems

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and are rarely used. On the other hand, light flux density cannot be controlled in sunlit chambers. However, a curve of photosynthetic rate vs light flux density can be obtained for every day of the growing season and from this it is easy to model the limitations imposed by light. Chambers that are airtight, or nearly so, improve the accuracy of the gas and vapor exchange measurements. Therefore, in our opinion, the best data for the development of crop models are obtained from sunlit, airtight, controlled-environment plant growth chambers. Our own sunlit, airtight chambers are called SPAR (Soil-PlantAtmosphere Research) units (Phene et al., 1978). Each of them contains a physical (or similitude)model ofthe field crop consisting ofa slice across two or more rows of crop. The soil bin measures 2 X 0.5 X 1 m high and has a glass face on which roots can be observed and measured. The acrylic plastic top measures 2 X 0.5 X 1.5 m high and one face is hinged to provide access to the plants. Each SPAR top is surrounded to plant height with graded shades to eliminate the need for border plants. A dedicated computer continuously monitors important environmental and plant variables and controls C02concentration (& 15 ppm), temperature (*0.S0C), and imgation in the chambers. The SPAR tops transmit 98% of the light and have leakage rates of about one air change per hour. In all controlled-environment experiments, sampling for dry weight is a problem because it results in loss of the canopy. Extra rows of plants can be grown during the seedling stage without affecting the “permanent” plants and dry weight can be measured at final harvest. These meager data must be supplemented with field data for intermediate stages of plant growth. However, organ sizes can usually be measured nondestructively. For example, leaf area is often highly correlated with leaf length. Another problem with controlled-environment chambers, even sunlit chambers, is that plants grown in them do not react always exactly like plants grown in the field. For example, with soybeans the temperature responses of stem extension and leaf expansion differ in growth chambers and the field. Equations developed from plants grown in a chamber do not fit field observations and the parameters have to be adjusted during the early stages of model validation. The reason this is necessary is not known, but it is possible that the quality of light falling on the plants in the chambers is altered by its passage through the plastic or glass enclosure. As already mentioned, light quality is a significant problem in interpretingthe results from plants grown in artificially lit chambers. Overall then, to develop crop simulation models a judicious blend of data from both controlled-environmentsand field is needed. Controlled environment data reveal the effects of individual factors on crop growth and the

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shape of the relationship between the levels of those factors and various physiological responses. Field data enable us to adjust the parameter values in the equations developed from controlled environment data, to measure light interception, and to obtain more data that require destructive harvesting. c. Data Interpretation and Analysis. It is part of the crop modeler’s creed that basically plants are uncomplicated organisms. They have a few simple responses to environmental variables and their apparent sophistication is merely the result of these responses interacting. This belief may just reflect the limited ability of crop modelers or their desire to apply Occam’s razor but it is a potent driving force in the interpretation of data. Simple explanations of processes are more intellectually satisfying and we have good reason to suppose that they will have more predictive power. As a result of this philosophy, crop modelers always attempt to interpret data in terms of simple responses and their interactions. The quest is for an understanding of what is happening and no part of any hypothesized explanation may contradict any known physical or chemical laws or observed plant behavior. Statistical curve fitting has no part to play in this process unless we have found a consistent relationship between two variables and merely wish to summarize that relationship. d. Model Calibration. It frequently happens that crop models, as first developed, fail to simulate some aspect of the growth of the field crop. To make the model work correctly, some of the parameters in the equationsand even some of the relationships have to be adjusted. This process is called calibration. An example that we have discussed already is the adjustment of parameters in the equations governing stem extension and leaf expansion. When these equationsare developed from controlled environment data and then used to make predictions about field crops, calibration is essential. However, a note ofcaution is necessary. While calibration is a legitimate part of model development,it can easily be abused. Most crop simulation models contain a very large number of parameters and as a result almost any desired answer can be obtained by adjustment of these parameters. This is especially true if very few plant variables are being used to test the validity of the model. It is less likely to occur if a large number of plant variables are being checked. Sometimes it is necessary to recalibrate a model when a different soil type, cultivar, etc., is to be simulated. For example, in soybeans, much of the variation between cultivars can be explained by maturity group number but there are additional important differences between cultivars in their tissue expansion rates. The existence of parameters that have to be altered alerts us to the fact that our model is not as universally applicable as we might have supposed. Either there is a problem with some mechanism or we need

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additional input data. Even when simulation models have to be recalibrated for different situations, they can still be useful so long as the recalibration procedure is simple. If, during calibration, a model turns out to be very sensitiveto one particular parameter, almost certainly the mechanism in that part of the model is wrong. As far as we are aware, plants do not have any finely tuned mechanisms (with the possible exception of the flowering response to photoperiod in some species). If a model misbehaves in a given situation, most modelers will attempt to correct the fault with calibration. However, providingenough plant variables are checked, it soon becomes obvious if the fundamental problem requires a mechanism to be changed.

Ill. MODEL TESTING Model building is an enjoyable if arduous task whereas model testing can be heartbreaking. Perhaps this is why so many crop models are published without being tested. Testing takes two main forms: validation in which model predictions are compared with field observations, and sensitivity and uncertainty analyses which test how responsive the model is to changes in certain variables and parameters. A. VALIDATION

1. Dejnitions

Lemon (1977) has defined validation as a “comparison of a verified model to the real world and determination if it is suitable for its intended purpose.” A verified model is one in which the equations have been tested to ensure that they perform as intended by the developer. This does not, of course, mean that a verified model will correctly simulate a crop. There are two problems with this definition of validation. First, it fails to mention that the real world data set used for validation should not have previously been used for calibrating the model. Second, it fails to acknowledge the activity that all modelers engage in when some aspect of their model is found to be invalid, namely, the identification and correction of errors. A better definition therefore might be a “Comparison of the predictions of a verified model with experimental observations other than those used to build and calibrate the model, and identification and correction of errors in

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the model until it is suitable for its intended purpose.” This definition acknowledges the fact that most data sets collected for validation are subsequently used for model development and calibration. This is because there are so few good data sets available for developing models, and researchers cannot afford to waste them. However, the definition also warns that once a data set has been used for calibration, it can no longer be used for validation. 2. Data Needed for Validation An essential part of any validation data set is a complete record of the soil and aerial environment in which the plants grew. The data essential to characterizethis environmentare listed in Section II,D, 1. Without these soil and weather data, there is no validation data set. In addition, the models require information on crop management such as date of emergence, row spacing, plant population after emergence, and latitude of the site. Given these essentials, almost any other data on plant performance can be useful for validation. The most useful plant data are ( 1) timing of the various stages of growth, (2) dry weights of the major classes of organs on the plants at various times throughout the growing season, (3) final yield and an analysis of components of yield, (4) number of branches, leaves, fruits, and other organs, and ( 5 ) main stem and branch heights. For water and nutrient stress experiments, it is helpful to record the distribution of roots and water in the soil profile during the course of the growing season. Leaf water potential and evapotranspiration rate are also useful. Many models are developed using data from single-factor experiments, but the validation data most likely to expose weaknesses will come from multifactor experiments.

3. Levels of Validation Crop simulation models can be validated at the level of the predictions using field data or at the level of assumptions using controlled-environment data. Both types of validationbuild our confidence in the predictive ability of our model. However, a model can make correct predictions for the wrong reason so our confidence in the model increasesmore rapidly with validation at the level of assumptions than with validation at the level of predictions. Actually, validation of a crop model is never completelyaccomplished. Crop models are just working hypotheses, and it is never possible to prove a hypothesis absolutely correct in science. However, by testing a model under diverse conditions, ample opportunity is provided to identify its areas of weakness. Also, validation against data covering all aspects of a crop’s growth and development enables us to determine at what stages and in what aspects the model incorrectly predicts crop behavior.

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4. Example of Validation The soybean crop model GLYCIM has been validated for irrigated and rain-fed conditions, on three soil types, and for several maturity groups (Hernandez, 1984; Trent, 1984; Gertsis, 1985). Each study has emphasized the validation of a differentpart of the model. In a recent experiment (Hernandez, 1984),varieties representing maturity groups IV through VIII were planted at Mississippi State University on various dates from May 2 to July 25, 1983. The model correctly simulated the vegetative growth stages of maturity groups IV to VII for plantings during May and early June (the normal range of planting dates). However, the vegetative development of plants in group VIII progressed more rapidly than the model predicted. The model also stopped main stem node production too early in maturity group IV when the crop was planted after midJune. Neither maturity group IV nor VIII varieties are normally grown at Mississippi State University but the model should be able to handle them. Using the data obtained in the validation experiments, it was possible to calibrate the relevant equations in the model. Further validation of the model, with data for a range of maturity groups grown at another site, is needed to indicate if this recalibration is adequate, or if some mechanism in the model needs to be changed. The history of the validation work with GOSSYM involves many locations, soils, and management operations. Fye ef al. (1984) attempted to simulate cotton crops grown in Arizona at two planting densities with the model GOSSYM, which until then had only been used in a small number of Mississippi crops. They made a number of changes in the model until accurate simulations of numbers of main stem nodes, plant height, numbers of fruiting sites, numbers of flower buds, and numbers of bolls in both of the Arizona data sets were obtained. Then (unnecessary)changes were removed one at a time and the model was run against the Mississippi data sets. Site specific forms of equations for soil and canopy air temperature were identified. Three site specificphysiological rate functions pertaining to water stress were found, i.e., the Arizona crops appeared to have much higher potential root growth rates and greater sensitivityto water stress in leafarea expansion and stem elongation. Reddy et al. 1985)developed and incorporated into GOSSYM new equations for estimating canopy temperatures under very hot dry Mississippi conditions. This model provided very good simulations of seasonal time coursesof numbers of flower buds, bolls, main stem nodes, and fruitingsites. It also provided good simulationsof leaf, stem, and boll dry weightsas well as leaf area index and plant height. The revised model was then used to obtain good simulations of three other cultivars at another location in Mississippi, after adjustments for insect damage were made. Perhaps the most extensive crop simulation model validation effort to

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date is that of Marani and Baker ( 1981). They made severalimprovementsin GOSSYM in describing the shape of water release curves in soils and in the priorities for dry matter partitioning to fruit. The latter change was also incorporated in the model validated by Reddy et al. (1985). Marani and Baker (1981) also changed a number of organ growth rate parameters to simulate the Acala type of cotton (as opposed to the Delta types used previously). With these changes, they were able to obtain good simulations of seasonal time courses of numbers of flower buds, bolls, and main stem nodes as well as weights of stems, leaves, and bolls in 57 validation data sets. These data sets spanned three growing seasons and 19 locations (in Israel) with widely varying climate and soil conditions. The very feasibility of developing generally valid crop simulation models has been questioned, in some quarters, until recently. These validation efforts have done much to establish the feasibility of process level models and to pave the way toward a variety of applications.

B. SENSITIVITY ANALYSES In Section I1 we have seen that many input variables are needed for comprehensive,mechanistic models such as GOSSYM or GLYCIM. In this section we have also seen that various tests are used to validate the model. If one takes an individual input variable and changes it, holding all others constant, this is called sensitivitytesting. We have done this for the weather and soil variables of GOSSYM and reported the results at various meetings (Whisler et al.. 1979a,b). The results of changing the values of the weather variables are given in Table 11. The model is most sensitiveto changes in air temperature (either maxima or minima), next most sensitive to changes in solar radiation, and least sensitive to changes in rainfall. (The latter test might not be the best since some imgation was used in all cases.) To be more specific a 1% change in temperature changed the predicted yield as much or more than a 10% change in solar radiation or rainfall. In general if the changes were made systematically, i.e., either all higher or lower than the actual readings, such as a faulty instrument might give, the results were worse than if the errors were random, such as a poor chart reader might give. As with validation more than yield needs to be checked, but it illustratesthe type of results obtained from sensitivity analysis. The senior author has also tested rice models (RICEMOD, IRRIMOD) in much the same way (Whisler, 1983a-d). It was pointed out in those studies that one can group the changes in variables and simulatechanges in location, i.e., moving to higher or lower latitudes; changes in soils, i.e., increasing or decreasingcompaction or texture;changes in crop management procedures,

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Table I1

Yield of Lint Cotton as Mected by Weather Variables Percentage change from standard

Yield (kg/ha)

Actual Standard simulation Radiation

+ 10% - 10%

Random"

+60% -60%

Random Rainfall

+ 10% - 10%

Random

+60% - 60%

Random Temperature 1% - 1% Random

+

+ 10%

- 10%

Random

High irrigation

Low irrigation

High irrigation

Low irrigation

1690 1580

1312 I450

-

+7

- 10 -

1650 1480 I570 1880 730 1480

1310 1550 1970 1150 630 1 I30

+4 -7 -1 19 - 54 -7

- 10

+7 -6 -21 - 56 - 23

1530 1640 1560 1550 I790 I600

1430 1440 I400 1510 610 800

-3 +4

-2 -1

1660 I520 I600 2000 610 1630

1480 1310 1380 1450 550 1680

+

-1 -2

+ 13 +1

+5 -4 +1 26 -62 +3

+

-3 +4 - 58 -45 +2

- 10 -5 0 - 62 15

+

The percentage change was applied randomly, either plus or minus, to the data variable.

i.e., timing of irrigation; and changes in crop cultivars. Thus, such analyses are not just academic exercisesbut can serve as indicators of environmental, crop, and managementeffectson crop growth for other agronomicscientists. In general, crop simulation models such as GOSSYM, RICEMOD, and even IRRIMOD are most sensitive to changes in crop and weather variables. This is to be expected since they involve the direct plant growth processes or temperatures at which the processes take place. The next most sensitive variables are soil parameters and least sensitive are management variables. The soil indirectly affects plant growth through stresses such as water and nitrogen deficits. The management parameters which were available to test in the rice models mainly change the timing at which crops are planted, harvested, etc.

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IV. MODEL APPLICATIONS A. BREEDING Physiological process models are capable of being used as tools in establishing breeding objectives by building gene analogs into the model. These gene analogs take the form of rate coefficients or other system constants. This has not been a specificobjective of any simulation models, of which we are aware to date; i.e., dynamic simulation models with complete arrays of gene analogs in system constants have yet to be assembled. Nevertheless, some major physiological processes are represented by model characters, which may or may not be simply inherited, and some effortshave been made to use these models in evaluating particular plant characters. Baker et al. ( 1973) used SIMCOT I1 (McKinion et al., 1975)to perform an analysis of the relation between photosynthetic efficiency and yield in cotton. Their procedure was to validate the model, in terms of seasonal time courses of plant development, fruiting, and yield, and then make various assumptions about photosynthetic efficiency and plant population to predict yield responses. This type of analysis might be useful to a breeder considering trade-offs involved with genotypes of lower photosynthetic efficiency, or in considering the potential benefits of selecting for increased efficiency. As outlined earlier in this article, SIMCOT I1 and GOSSYM calculate canopy photosynthesis on a ground area basis, rather than on a leaf area basis. Growth, however, is treated on an organ by organ basis, at the single (average)plant level, and so, in a low plant population, a given increment of photosynthate results in proportionately larger plants, and (typically) plants with less metabolic stress and organ abortion. The Baker et al. ( 1973) simulated seasonal time courses in fruiting are presented in Fig. 5 , where photosynthetic efficiency was increased and decreased 50%. In most fruiting plants, and in SIMCOT I1 and GOSSYM, carbohydrate stresses become acute during fruiting, and the plant balances supply and demand by aborting fruit to produce at least some viable seed. In indeterminate cotton, flower bud initiation and abortion occur simultaneously.As the boll load accumulates (Fig. 5), initiation rates decrease and abortion increases, resulting in a peak number of flower buds (“squares”). This peak occurs earlier than normal in crops with lower photosynthetic efficiency and later in those with high efficiency. Final predicted boll numbers were smaller in the crop with lower photosynthetic efficiency and higher in the case of higher efficiency. The associated yield response to increasing and decreasing photosynthetic efficiency (Baker et al., 1973), for two plant populations, is presented in Fig.

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a

m

r

0

2k 60 -

b

3

2

50

-

40

-

30

-

40

50

60

70

80

90

100

m

m

110

120

130

140

Days of Emergence

FIG.5. Seasonal time course of fruiting for real cotton crop with normal photosynthetic efficiency(representedby the solid curves) and simulated crops at 1.5 (a) and 0.5 (b) normal photosynthetic efficiency. The realcrop dataare representedwith open symbols; simulated data with closed symbols. (09) Bolls; @,W) flower buds. (From Baker et al., 1973.)

6. The relationshipis nonlinear and suggeststhat a point existsat which, even with complete insect control and nonlimiting soil water and fertility, other factors will limit yield. Landivar et al. (1983b)used GOSSYM in further feasibility studies to evaluate the yield responses to increasing photosynthetic efficiency, specific leaf weight, and longevity of leaves in cotton. The

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a

I

1

I

0.5

1.0

1.5

2.0

Relative

P

FIG. 6. Yield versus relative photosynthetic efficiency, P, for two plant populations of cotton; (0)20,498 plants/ha; (0)4 1,OOO plants/ha. One bale/acre equals 88 kg/ha.

-

analysis, with a 30% increase in leaf photosynthetic efficiency, resulted in a predicted increase in lint yield of 54% if water and nitrogen supplies were abundant. This yield response is very reminiscent of the yield responses to elevated atmospheric CO, reported by Mauney et al. (1978). Again, higher than normal applications of water and fertilizer might be helpful in the breeding and management of new cultivars. Landivar et al. (1983b) concluded that if genetically enhanced photosynthetic efficiency were associated with increased specific leaf weight, much of the additional carbohydrate would be partitioned into leaf growth rather than into lint. Thus breeders should be cautious in selecting for high photosynthetic efficiency on the basis of high specific leaf weight observations. Crop leaves often become senescent and abscise rapidly during the fruit

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growth period. If LA1 in cotton falls below 2.9 (Ludwig et al., 1965),canopy light capture is impaired, and photosynthesis declines. This can decrease yields. Rate of leaf abscission is most likely to exceed leaf growth during the period of rapid fruit growth (cf. Fig. 4 from Landivar et al., 1983b). The analyses of Landivar et al. (1983b) predicted a linear yield response to increasing the age of leaf abscission up to 70 days. Breeding work to increase cotton yields either by increasing leaf photosynthetic efficiency or by delaying leaf senescence has not, as yet, been undertaken as a major objective. Jenkins et al. (1973) used SIMCOT I1 in an attempt to determine the mechanism of delayed fruiting in frego bract cotton. Frego bract is a mutant cotton strain in which flower buds are associated with bracts which are rolled and twisted. This character conveysresistance to boll weevil damage, but it is associated with delayed fruiting. Jenkins et al. (1973) tested the following three hypotheses in their analysis: (a) that frego squares are more sensitive to bum by solar radiation, (b) that the frego character is linked to other characters causing slower plant development (fruit initiation), (c) that the frego bract fruit, while resistant to boll weevil, are more susceptibleto damage by tarnished plant bug. This was done by modifying fruit abscission rates in the model in cases (a) and (c) and by changing the equation for fruiting site initiation in the case of (b). Two plant bug damage scenarios were tried in the analysis, a short-term, highlevel damage- simulated by removal of three modeled squares over a 5-day period -and a longer term, low-level damage-simulated by abscission of three modeled squares over an 1 l-day period. Of all the hypotheses tested, the long-term, low-level plant bug damage scenario simulated field observations best. This analysis was confirmed in subsequent field experiments by Parrot et al. (1985) and McCarty et al. (1983). Baker et al. (1979) demonstrated a variety of applications, including breeding, for process-level crop simulation models. Levitt (1 972) had shown how stomatal behavior might affect a plant’s water use efficiency under semiarid conditions. He associated high water use efficiency with plants that avoid drought and described two types of drought avoiders, “water savers” and “water spenders.” Water savers avoid drought by closing their stomata during the day even though soil water supplies may be adequate. They achieve high water use efficiency through efficient seasonal control of the total water supply. Water spenders avoid drought by extracting larger quantities of water from the soil per unit time and leaf surface. As a result, water spenders keep their stomata open more throughout the day, assimilate more C02,and therefore have a more rapid growth than water savers. Most cottons would be considered to be water spenders. Roark and Quisenbeny ( 1977)reported a heritable component of leaf-diffisive resistance in cotton, and they proposed to develop water saving cultivars. Baker et al. (1979) used GOSSYM and made analyses which were de-

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signed to estimate yield responses to the kind of breeding effort suggested by Roark and Quisenberry (1977). Since GOSSYM does not have a detailed description of the various resistances affecting gas exchange in the plant, Baker et al. first had to estimate the effect of changes in stomatal resistance on transpiration and photosynthesis. Values for various resistances were obtained from the literature. They were stomatal resistance ( R E0.9 , cm/sec), mesophyll resistance (R,, 2.5 cm/sec), and boundary layer resistance (R,, 0.5 cm/sec). Photosynthesis(P)and transpiration (T) under typical midday conditions in Mississippi were calculated as follows: P=

[C02air] - [C02mesophyll]

R, iR E +R , [H 2 0 cell] - [H 2 0 air] T= 0.6(R, R , )

+

where 0.6 is the ratio ofthe diffusioncoefficientsof C02in air to that ofwater vapor in air. Then by doubling the stomatal resistance (for example) while keeping R , and R , constant, and solving for P and T, Baker et al. (1979) estimated that the transpiration should be reduced approximately twice as much as photosynthesis(39 vs 19%,respectively). Runs were made with no changes and with these changes in transpiration and photosynthesis rates whenever soil water potential in the root zone fell below -0.08 MPa using high, medium, and low water input treatments. The low water input treatment consisted of 95 mm total irrigation,which is approximatelyequivalent to typical summer rainfall on the Texas High Plains. The soil was a deep clay loam with the entire profile at field capacity at emergence. Results of the Baker et al. (1979) analysis are presented in Table 111. The high and medium water regimes resulted in very little effect on seasonal transpiration or photosynthesistotals. There was some delay in maturity of the crop with increased R, in the medium water treatment due to peculiarities in the seasonal weather pattern, i.e., in the seasonal distortion of water stress conditions and associated delays in fruiting. This resulted in a slight decreasein yield which would have been overcome via harvest aid chemicals in a real-world situation. The driest treatment, however, resulted in a seasonal increase in photosynthate production in the crop with an increased stomatal resistance as compared with the normal crop. The seasonal average water potential in the root zone was higher in the crop with the modified stomates,and a higher lint yield was predicted. Thus, the analysesof Baker et al. (1979) tend to confirm the importance of the breeding work proposed by Roark and Quisenberry (1977). Quisenberry et al. (1985) followed up their lead by developing cotton lines with modified stomatal mechanisms which, in fact, exhibit about 25% higher yields in the Texas High Plains.

CROP SIMULATION MODELS

185

Table I11 The Simulated Effects of Increasing Stomata1 Resistance in Cotton by Partially Closing the Stomataa

Total water applied

275 mm

Total T(mm) Normal Increased R, Total P (gm) Normal Increased R, Average soil y~ (MPa) Normal Increased R, Boll count Normal Increased R, Seed cotton yield (kg/ha) Normal Increased R,

186 mm

95 mm

373 367

21 1 204

118 I22

183 184

121 121

79 97

0.045 0.045 (Open Green) 17.4 1.1 19.2 I .O

0.058 0.053 (Open Green) 13.1 1.3 11.6 4.8

0.090 0.076 (Open Green) 14.9 3.4 14.7 4.5

1636 1609

I408 1325

948 1219

From Baker ef ul. ( 1 979). T,Transpiration;P,photosynthate; (v, soil water potential.

Landivar et al. ( 1983a)used GOSSYM to analyze the differences in yield between okra-leaf (deeply lobate) and normal-leafed cottons in several imgation and nitrogen fertility scenarios. Okra-leaf cottons typically produce more fruiting sites than normal-leaf types. Without any changes in the morphogenesis logic, but with an appropriate change in leaf area growth and canopy light interception, GOSSYM simulated that observation. The simulated difference in number of fruiting sites produced by the okra- and normal-leaf types was of the same order of magnitude as found in the literature (Kerby and Buxton, 1976). The model output suggested that cotton genotypes with reduced leaf area would invest the carbohydrate not used in leaf area increase for the production of roots, stems, and flowers. The redistribution of carbohydratesoccumng in okra-leafcotton led to the production of a higher fruit load. As the season progressed, carbohydratestresses developed due to increased demand as the fruit load increased. The model balanced the supply and demand for materials by aborting fruit. The abortion of fruit was higher in the okra than in normal-leaf cotton because the okra-leaf had developed a higher fruit load. This result agreed with the general observation that okra-leaf genotypes abscise more fruit than normal-leaf types, but the

186

F. D. WHISLER ET AL.

differencein numbers of aborted fruit between okra- and normal-leaf cotton was less than reported in the literature. In analyzing yield responses at various treatment levels, Landivar et al. (1983a) predicted that as growing conditions improve (i.e., at higher water and nitrogen application rates), the okra-leaf cotton will produce higher lint yields than the normal-leaf types, whereas unfavorable conditions will favor normal-leaf cotton. Under favorable conditions, simulated growth of normal and okra-leaf cotton produced a leaf canopy sufficient to intercept most incoming solar radiation. Adverse growingconditions affected the simulated LA1 of both leaf types, but because okra-leaf had a smaller area/leaf, it produced a lower LAI. As the leaves senesced, LA1 dropped below 2.9 (the point at which light begins to penetrate the leaf canopy to ground) earlier in the boll-fill period, resulting in a lower yield in the okra-leaf cotton. This is shown by the GOSSYM output in Fig. 7. Under favorable growing conditions, the simulated okra-leaf crop produced and maintained adequate LA1 to intercept most of the incoming radiation without being wasteful. Because okra-leaf invested less carbohydratein leaves, it could invest relatively more in the production of fruit, and final yield was higher. Further analyses of this type were conducted by Landivar et al. (1983b) in which they determined that an intermediate-leaf type (subokra) should be superior to either normal- or okra-leaf cotton under a variety of dryland conditions. Intermediate leaf was simulated by reducing leaf growth 15% compared to normal-leaf (okra-leaf was reduced by 30%). The predicted yields are shown in Table IV. The symbols AAA, ABB, and ADD represent Bruce and Romkens’ (1965) irrigation inputs. The AAA treatment was maintained at field capacity throughout the season. Under that treatment, vegetative development was greatly enhanced in all three genotypes, reaching maximum LAIs of 5.8,5.0, and 4.2 for normal, intermediate, and okraleaf, respectively. Under AAA conditions, predicted yield was negatively correlated with leaf biomass. The ABB treatment was somewhat drier; it was maintained at field capacity from planting to first bloom, then was irrigated whenever root zone tensiometer readings were below -0.06 MPa. This treatment represented a more typical year in the cotton-producingareas of Mississippi than AAA. The simulated LA1 in the ABB treatment was reduced considerably in all three genotypes, flecting light interception primarily in the okra-leaf cotton, which reached a maximum LA1 of 2.8. This resulted in reduced yield in the simulated okra-leaf crop, but increased yield in the normal and intermediate-leaf types with maximum LAIs of 3.9 and 3.3, respectively. Those levels were apparently adequate for intercepting most of the incoming solar radiation, but the more efficient distribution of carbohydrates in the intermediate-leaf type predicted a lint yield increase of 166 kg/ha over normal-leaf cotton. Simulated LAIs were reduced further in the ADD treatment. This treat-

187

CROP SIMULATION MODELS 4.0 X

w 3.0 0

-

0

YIELD Okra leaf 1021 k / h a

X

Normal leaf 1211 k/ha

z

CI

5E

2.0

-

4

lL

*

W

1.0 -

-I

b

513

t

d

I

1844 k/ha Normal lecf 1469 k/ha

n

'

60

80

100

120

1LO

DAYS FROM EMERGENCE

FIG.7. The simulated leaf area index at two water levels and high application of N (224 kg/ha) in okra- and normal-leafcotton.(a) 186 m m water; (b) 375 m m water. (From Laodivar et al., 1983a).

ment was irrigated to field capacity at planting and maintained at that level to first bloom. It was then irrigated whenever soil water potential was below -0.23 MPa. The LAIs were considerably reduced in all genotypes, reaching a maximum of 2.7,2.2,and 2.0, respectively, for normal, intermediate, and okra-leaf. In this situation, normal-leaf was predicted to be, by far, the best type.

188

F. D. WHISLER ET AL. Table IV Effects of Irrigation Level and Leaf Type on Cotton Lint Yield

Lint yield (kg/ha) by irrigation level" Leaf type

AAA

ABB

ADD

Mean

Okra Intermediate Normal

1769 1583 1468

1429 1885 1719

958 99 I 1210

1385 1486 1465

a The symbols AAA, ABB, and ADD indicate irrigationregimes described in the text.

Analyzing the mean lint yields over the three environments, the model predicted that the intermediate-leaf type should outyield okra-leaf by approximately 100 kg lint/ha. Considering the ABB treatment, the intermediate-leaf was predicted to outyield normal-leaf by 10%.In 1982 Meredith ( 1984)compared several subokra populations with normal populations on three soil types at three planting dates in the Mississippi Delta. Growing conditions were conducive to high yields in that area in 1982.He found that the intermediate-leaf type cottons significantly outyielded normal-leaf cottons by an average of 4.8%, confirming the findings of Landivar et al. (1 983b). In summary, physiological process-oriented crop simulation models are capable of breeding feasibilitystudies, although models with completearrays of gene analogs in system constants have yet to be assembled. These models are useful in breeding programs in an explanatory sense, explaining the nature of yield responses, and in identifying the environmental conditions under which yield increases will be expressed. The use of physical/physiological process-oriented crop simulation models in crop system design, including breeding, is still in its infancy. Nevertheless, we have cited one instance of such a model aiding in explaining the nature of delays in fruiting in a particular breeding program, and we have identified two instances where these models have helped to anticipate yield increases from particular breeding programs. GOSSYM correctly predicted increased cotton yields with increased stornatal sensitivity under dryland conditions, and it correctly suggested a yield advantage to an intermediate-leaftype in unirrigated conditions in the Mississippi Delta. B. SOILEROSION Comprehensive, mechanistic crop models such as GOSSYM and GLYCIM can be used to test the effects of different soil management strategies

189

CROP SIMULATION MODELS

( Whisler et a!., 1982)and/or natural Occurrencessuch as erosion. To test the response of GOSSYM to erosion, several runs were made, and the results are shown in Table V. There are several scenarios that one might use in such tests. The soil that we used for this test had a traffic pan between 17 and 24 cm. In the 100-cm profile tests we assumed that 5 to 10 cm of soil had eroded uniformly from the surface horizon and that the primary tillage operations had not broken up the pan (that is, disk, harrow only). Simulated decreases in yields due to erosion would, as expected, be greater in a dry year such as 1980 than a wet year such as 1982. Since the same amounts of water and fertilizer were applied in all simulations, the indicated responses were due to root growth, water movement and uptake, and nutrient movement and uptake. In the 30-cm profiles, which are common in the MississippiAlabama Blackbelt soils, it was assumed that the primary tillage operation disrupted the previous year’s traffic pan but reformed it at the same depth relative to the soil surface. The results indicated a major decrease in yield when profile depth went from 100 to 30 cm, and reductions in yield generally continued with increased erosion.

C. PHYSIOLOGICAL PROBE We cannot obtain by direct measurement all of the information about plants we would like. For example, the turgor pressure in leafcellsis the main driver of leaf expansion, but it cannot be measured directly. It can only be inferred from other measurements using a model to relate these measurements to turgor pressure. Again, we would like to know what controls canopy senescence in monocarpic plants at the end of the growing season, but at Table V

Simulated Cotton Lint Yield as Affected by Soil Erosion

30-cmProfile

100-cm Profile

Dry year, 1980 Noneroded 5-cm erosion 10-cm erosion Wet year, 1982 Noneroded 5-cm erosion 10-cm erosion

Yield (kdha)

Percent change

Yield (ke/ha)

Percent change

1580 1460 1280

-9 - 19

1070 760 1010

- 32 - 52 - 36

-

1470

+2 -2

I154

- 14 - 33 - 55

1710 1750 1690

780

190

F. D. WHISLER ET AL.

present we do not know what the controlling agent may be, or when or where to look for it. In these and many similar instances, there are hypotheses or models describing the relationships involved. If our crop models are sufficiently comprehensive and mechanistic, the various candidate models for a process can be tested to see which of them, if any, gives realistic results. Unrealistic behavior may enable us to eliminatesome hypothesesfrom further consideration but realistic behavior does not necessarily mean that we have correctly identified the mechanism. Exercising the model may, however, suggest further experimentationto test a successful hypothesis. In this way, crop simulation models can be used to probe the physiology ofthe plant even when the processes are not experimentally accessible. Using models in this way is probably more realistic than waiting for improvements in experimental techniques. Modeling and experimentation can be mutually supportive in developing our understanding of crop physiology,just as they have been in developing our understanding of particle physics. Simulation modelers generally recognize the importance of avoiding the use of time as a variable in rate equations; i.e., elaborate model structures including appropriate feedbacksare often used to simulate(mathematically) complex seasonal patterns of growth and development, although time may be used as a discrete event marker. For example, the seasonaltime courses of plant development, in Fig. 8, and fruiting, depicted in Fig. 9, from Baker et al. (1973) were obtained purely as a result of model structure, including a mathematical definition of stress. No plant character which changes in time was needed or included among the inputs to this model. In the model of Baker et al. (1973), SIMCOT 11, stress was defined as the carbohydrate supply-demand ratio. The model itself was used as a physiological probe to identify the demand component represented by stem growth. Early season, exponential growth was described for a well-irrigated, heavily fertilized crop by the empirically derived expression DW = 0.2

+ 0.06(STMWT)

where DW is the change in stem dry weight (STMWT)in grams per day. The simulation of the transition from exponentialto linear growth, in this woody stemmed perennial, was obtained by modifying the above form as follows: DW = 0.2

+ 0.06(STMWT - 124)

where 124 is the incremental gain in stem weight marked 24 days earlier. In other words the simple hypothesis was implemented that stem dry matter becomes woody and incapable of further growth after about 24 days. The 24-day figure was obtained by making many runs with the model, using numerous I values. A rather sudden and dramatic improvement in the simulations shown in Fig. 9 were observed with the 24-day value.

191

CROP SIMULATION MODELS

0

2

0)

V

30

z E

4 20 .-c

a

-

t

-

v)

10-

0' 40

I

50

I

60

I

70

I

80

I

90

I

100

I

I

110

120

1

130

a

I

120 130

140

i

a 1

a

a

1

a

a

u40

50

60

70

80

90

I f

100

110

I I L

120

130

140

Days from Emergence

FIG.8. A season's time course of main stem node and total fruiting site per plant develop ment. Open circles and lines trace the real cotton crop. Upper, middle, and lower sets of solid circles represent model predictions for 50,600, 101,200 and 197,500 plants per hectare, respectively. (From Baker ef al., 1973.)

Developmental and abortion rates are both functions of the total plant carbohydrate supply - demand ratio. The same physiological probe techniques and the same definition of carbohydrate stress enabled Baker et al. ( 1983)to develop the strress functions for developmental delay (Fig. 10)and fruit loss (Fig. 11) in the GOSSYM model. The delays in Fig. 10 are expressed as days to be added to the temperature functions describing plastochrons and fruiting intervals in cotton (Hesketh et al., 1972). The fruit loss

F. D. WHISLER ET AL.

60

I

a

Days from Emergence

FIG.9. Seasonal time course of fruiting per plant for real and simulated cotton crops at 50,600 plants/ha under (a) “normal” and (b) all “clear” skies. Open symbols, real crop data; (09) bolls; (0J) flower buds. (From Baker er al., 1973.)

in Fig. 1 1 is expressed in terms of numbers of flower buds and young bolls to be aborted per day as functions of carbohydrate source- sink imbalance in cotton. FSTRES is defined in Fig. 10 as a product of C-stress and N-stress. The physiological probe has permitted the development and use of model structures which are generally valid, but contain components which are

CROP SIMULATION MODELS

193

FSTRES

FIG. 10. Morphogenetic delays expressed as an increase in number of days between the appearance of successive (0)leaves (CDLAW) or (X) fruits (CDLAYF)versus the FSTRES parameter. FSTRES is the product of the carbon supply-demand ratio and the nitrogen supply-demand ratio. (From Baker et al., 1983.)

completely inaccessible to direct observation. Frequently these functions have genetic analogs in plants. For example the FLOSS function vanes greatly in cotton, with Pima cottons (Gossypium barbadense) retaining many more fruit than upland cottons (Gossypium hirsutum). Artificial intelligence techniques, as discussed later, promise to greatly enhance the speed with which such comprehensiveprocess-oriented models can be used as physiological probes. D. HERBICIDE INJURY

Herbicides, especially dinitroaniline herbicides, do not require rainfall or imgation to be activated, but they must be incorporated into the soil for maximum effectiveness. The rate of application, depth of incorporation, and the organic matter content of the soil influence the behavior of these herbicides. The toxicity of a herbicide is a measure of its effectiveness in reducing

194

F. D. WHISLER ET AL. 3

.o

2.0 m m

0 -I

LL

1.o

0

0.2

0.4

0.6

0.8

1.0

FSTRES

FIG.11. Numbers of fruit lost per day (FLOSS)versus FSTRES for plants with fruit total plant dry weight ratios (FRATIO),(X) above and (0)below 0.1 FSTRES(see Fig. 10). (From Baker ef al., 1983.)

plant growth. Toxicity is dependent on four factors: (1) the chemical and physical nature of the herbicide, (2) the availability of the herbicide to the plant, (3) the availability of nutrients to the plant, and (4) the nature of the plant species, including varieties within a species. Of these four factors, the influencesof the first three are likely to be affected by environmental factors such as soil characteristics and weather (Adams and Pritchard, 1977). To attain productive top growth,a plant must have a healthy root system,in that the roots are responsible for uptake of water and nutrients. The depth of herbicide incorporation affects the number and length of roots, especially the lateral ones (Anderson et al., 1967;Oliver and Frans, 1968). The formation of lateral roots, deeper in the profile, may cause a reduction in root surface area in the upper soil zones, thereby resulting in less nutrient and moisture uptake by the plant (Gordon et al., 1979). A large reduction in phosphorusuptake was observed when trifluralin and phosphorus were applied in the same soil layer (Cathey and Sabbe, 1972). This reduction in uptake could be due to root inhibition or reduced root permeability or both. Pavlista (1980) reported that trifluralin at 2.24 kg/ha inhibited top growth, length ofprimary roots, developmentof lateral roots in the incorporated zone, and the emergence of cotton seedlings. Moody et al. ( 1970)observed an increase in uptake of herbicides by soybean plants with an increasein temperature from 5 to 30"C. They also reported that trifluralin activity increased as soil organic matter decreased (Segraves, 1973;Weber et al., 1974a,b). Ketchersid et al. ( 1969)reported both acropetal and basipetal movement of trifluralin in peanut seedlings. We have demonstrated that a computerized crop simulation model such

CROP SIMULATION MODELS

195

as GOSSYM can be used in analyzing the response of cotton crops to herbicide damage. In an effortto identify causes ofdeclining cotton yields, a series of simulations was conducted to study the effect of root inhibition and reduction in the permeability of roots to water and nutrient uptake on growth, development, and lint yield of cotton under different rainfall and temperature patterns under Mississippi soil conditions. Modifications were made in GOSSYM to simulate a crop with reduced root growth and with reduced uptake of water and nitrogen. Inhibition levels assumed in this computer experiment were 30,20, 10,0%; 50,40,30,20%; 70,60,50,40%; and 90,80,70,60% at depths of 5,10,15, and 20 cm, respectively (Fig. 12) at the beginning of the season. These inhibiting factors were decreased exponentially to one-half by the end of the season to simulate the degradation of these herbicides. Simulationswere made using 1983 weather (Kharche, 1984) and Leeper clay loam soil conditions. Additional simulations were made by adding 2°C to the 1983 day and night average temperatures, and for cool/wet condition we subtracted 2°C from day and night average temperatures and added 1.3 cm water whenever the simulated soil water potential fell below -0.05 MPa. The predicted root weights decreased with increased depth or intensity of root inhibition, except that at 5 cm a slight increase in root weight was predicted with increased inhibition. This was due to the fact that the simulated plant compensated with root growth in the deeper layers (Table VI). Also, the model plant utilized the carbon saved by restricted root growth in the top 5 cm of soil in the production of taller and bigger plants which intercepted more light and produced more photosynthate early in the season. Total root weight consistently decreased with an increase in herbicide depth or percentage of root and permeability reduction. The predicted decrease in root weight was much greater when root growth and permeability were both reduced than with root reduction alone. The effect was much larger under cool/wet conditions than normal weather or hot/dry condiPERCENT ROOT AND PERMEABILITY REDUCTION SOIL DEPTH (crn) 0

5 10 15

20

FIG.12. A diagramaticrepresentationofroot inhibitionor permeability reduction percentages at depths ranging from 0 to 20 cm in the soil.

196

F. D. WHISLER ET AL.

Table VI Maximum Root Weight as a Function of Increasing Depth and/or Root Permeability Reduction in Cotton Root weight (dplant) by treatmenta ~~

Root weight

9 1 0 1 1

121314

15

16

22 22 22 22 22 22 19 13 23 20 18

12 22 20

15

13

1

2

3 ~

Under different root reduction levels Underdifferentrootand permeability reduction levels Underdifferentrootand permeability reduction levels and under hot/dry weather Underdifferent rootand permeability reduction levels and under cool/wet weather a

~~

4

5

6

7

8

~~

19 19 18 18 18 17 17

9 18 17 13

26 22 21 21 26 22 17 14 22 21

3

3

3

3

3

3

2

1

3

2

13

7 17 15

10 < 1

8 21 16

13

1 <1

2

1 <1

Treatments refer to treatments in Fig. 12.

tions, because of interacting effects of cold temperature on plant growth and reduction of root growth due to permeability of roots. Root inhibition reduced predicted root mass in the top 20 cm where nitrogen was applied, reducing predicted nitrogen uptake as the depth of inhibition increased. The uptake of nitrogen followed the same pattern of root growth both under root reduction and permeability reduction under all weather patterns we studied. Due to reductions in root permeability and resulting nitrogen shortages, the simulated plant accumulated its unsynthesized excess carbon in woody tissue. This was more apparent in the later part of the season due to greater demand for nitrogen for bolls and seeds. The simulated lint yields showed a slight increase in response to root inhibition at 5 cm (Fig. 13A). This increase in yield occurred because the carbon saved was utilized in the production of shoots in the early part of the season. Better establishment of the canopy early in the season resulted in taller plants, more light interception, and higher yields. Root inhibition at 5 cm did not cause any shortagesofwater or nitrogen becausethe top 5 cm of soil normally stays dry. Also, under moderate inhibitingconditions the crop matured slightly earlier than with no inhibition because the crop retained more early-produced bolls. Similar results were observed in both earliness as a response to root restriction and higher yields by Ben Porath (1985) under restricted root volume conditions. However, as the intensity and depth of

3


197

CROP SIMULATION MODELS

-

30,2OJO,O

5.0

10.0

15.0

20.0

10.0

15.0

20.0

DEPTH OF ROOT REDUCTION

FIG.13. Cotton lint yield as a function ofincreasingdepth ofroot reduction (A) with change in root reduction levels under normal Mississippi weather conditions, (B) with change in root reduction and permeability levels under normal Mississippi weather conditions, (C) with change in root reduction and permeability levels under 2°C wanner weather conditions, (D) with change in root reduction and permeability levels under 2°C cooler and wet weather conditions.

inhibition increased severe nitrogen and water shortages occurred during the season and lint yield declined as much as 40% (Fig. 13A). A similar trend was observed in numbers of squares, bolls, and fruiting sites. In the case of root permeability reduction the decreased yields were much larger than with root inhibition only (Fig. 13B). Here the decrease in predicted yield was not only due to water and nutritional shortages but also due to delayed maturity. Such events occur under Mississippi weather conditions where temperature is often the limiting environmental factor for boll opening in the later part of the season. The latematuring bolls did not open, causing greater yield reductions than the nutrient and water shortage can

198

F. D. WHISLER ET AL.

account for under higher levels of restricted root and permeability conditions. Under hot/dry weather conditions, the yields were generally low (Fig. 13C). The high temperatures caused excessive water stress and reduced photosynthesis. The predicted yields under extreme root inhibiting conditions were higher than yields of normal weather conditions, because with higher root inhibition and permeability conditions, the warmer temperatures caused increased root growth due to warmer soil temperatures. This in turn partially compensated for reduced uptake of water and nitrogen. Also, the warmer temperatures helped boll opening at the end of the season, thereby producing up to 500 kg lint/ha even under extreme root-inhibiting conditions. Under cold/wet weather, the yields were much lower (Fig. 13D) than under normal weather or hot-dry conditions. The cooler temperatures caused slow vegetative growth, delayed canopy closure, reduced light interception during the early part of the season,and slowed boll growth as well. At the end of the season, more unopened bolls were left which could not be counted toward yield.

E. INSECTDAMAGE Certain types of insect damage in crops often are localized to particular classes of organs. A model which simulatesthe development of the plant on an organ by organ basis is useful in the assessmentof this type of damage. For example,GOSSYM has been used in the analysis of the impact of Lygus spp. on the growth and yield of cotton (Baker et al., 1986). This study began as a model validation effort with field data of Jenkins and Parrott (Boll Weevil Research Laboratory, Mississippi State, MS, personal communication). Initially, the model predicted not only more unpollinated flower buds, but also more fruiting sites than were counted in the field. The model prediction of the final plant structure and fruiting is presented in the lefthand side of Fig. 14. The yield associated with that simulation was 1040 kg/ha. The observed yield for the crop was approximately 730 kg/ha. Parrott et al. (1982) had recorded a population of up to 2570 lygus/ha in the crop during the season. The model plant in the righthand side of Fig. 14 shows the lygus damage in a simulation predicting the correct numbers of mainstem nodes, fruitingsites, bolls, and yield. This result was obtained by assuming that the lygus infestation lasted 44 days (approximately two generations) during the fruiting period. It was assumed that during that time each lygus bug damaged three unpollinated flower buds and removed two fruiting branch terminals per day. The observation that lygus may terminate two fruitingbranchesper day was made by Milam ( 1981). The assumption of a flower bud damage rate of 3

CROP SIMULATION MODELS normal

199

lygus

1-0 *-I

I-*

&*-I I-*-0 &$-I I-$-* *-$-I I-$-*a &*-$-I I-$-$-*

*-$-$-I

0-1 1-0 0-1 1-0 0-0-1 1-04 0-0-1 1-0-0 &$-I

I-$ $-I

I-$-O-O

-$-I

I-$-$-*-(I I I

I

I-$-$-04

I I I

FIG. 14. Simulated end-season plant maps for Scott’s (1979) crop with and without lygus damage. The model prediction of the final plant structure and fruiting is presented on the lefthand side. The righthand side shows the lygus damage in a simulationpredicting the correct numbers of mainstem nodes, fruiting sites, bolls, and yield.

per day per insect represents a compromise between estimatesof Mauney et al. ( 1979)and Gutierrez et al. (1979). The analysis of Baker et al. (1986)was later extended to include variable infestation dates and numbers of insects. They predicted delays in plant maturity in some cases and “typical” yield losses of the order of 25%. This type of analysis indicates the possibility of providing farmers with a method of estimating (what are in reality) dynamic economic thresholds, i.e., insect control thresholds which vary with the development of the crop.

F. ON-FARM The cotton grower makes management decisions in two general time frames: annually and daily. On an annual basis he decides, for example, on the area to plant, selects varieties, and purchases machinery. On a daily basis he decides whether to irrigate, apply a herbicide or insecticide, fertilize, use a growth regulator or a boll opener, cultivate, defoliate, or possibly replant. Several quantitative tools have been developed to aid in annual decisions, e.g., linear and dynamic programming. Considerable research has been conducted on techniquesand procedures for making annual decisions. But daily decisionsare usually based on the following: (1) rule ofthumb, e.g., irrigate at 50% available soil water, (2) custom, e.g., cultivate every 2 weeks until boll set, or (3) an abstract feeling, e.g., replanting because the stand “looks” too thin to produce a reasonable crop.

200

F. D. WHISLER ET AL.

Most risk management decisions consider economics quite heavily. The predominant question is, or should be, “Would I make money by followinga proposed course of action instead of some alternative?’ Another way of asking the same question is “How much increase in net return would result if I irrigated today?’ or “. . . if I cultivated today?’ Maybe the question is not “How much?’ but rather “Will my net return increase?’ if a particular action is taken. A major problem in answering the question, “How much increase in net return would result if I acted a certain way?’, is that the answser depends on several factors, including the following. (1) The status of the crop when the question is asked influences the result of a particular treatment, e.g., irrigation, and therefore influences the net return. (2) The future weather has a tremendous influence on the net result of applying, for example, a growth regulator. If the next month is hot and dry, the net economic result will be quite different than if the next month is cool and wet. (3) Future treatments will also influence the result of any particular action “today.” For example, the benefit of applying foliar nitrogen “today” depends on any irrigation during the next few weeks. Conceptually, a cotton crop grows from emergence until “today” under whatever weather nature provides, i.e., the previous or historic weather. Now the question is “Under the future weather, whatever that may be, how will the crop progress in physiological, morphological, and physical attributes until the end of the season, or harvest?” If the hypothesized or proposed action is not taken, the crop will follow one course. If the action is taken, it will follow a differentcourse. The differencein net crop value at harvest is the benefit which may be attributed to the proposed action or treatment, whether it be insecticide application, cultivation, or use of a boll opener. The overall goal of an on-farm pilot project in 1984 and 1985 was to initiate the transfer of crop simulation technology to the cotton producer, and to evaluate the feasibility of on-farm use of personal computers and simulation software for aiding in production management decisions. The research version of the model was input -output oriented to serve the needs of the researcher, who must build master input files and decipher voluminous output data about detailed physiologicalvariables. During the course of this project, a user-oriented interface has been designed in consultation with cotton extension specialists,county agents, and cotton growers. The goal was to allow the user (grower or extension worker) to easily input data into the model (GOSSYM) and simplify the output to includeonly data of interestto the grower. The interface and simulation have been implemented on a personal computer (PC). In 1984 two grower- cooperatorswere selected: one in Mississippi and the other in South Carolina. Soil cores were taken from each horizon in the soil

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20 1

profile to a depth of 1 m at five locations within a single field and single, mapped soil type on each farm. Samples from each horizon were analyzed for nitrogen and organic matter. Saturated hydraulic conductivity and the moisture characteristic curve were determined on these soil cores. These data were then used as input into the GOSSYM model. After we had determined soil characteristics,installed a weather station on each farm, and built the user interfaceto GOSSYM, we helped the farmersand extension personnel to run the crop model on the farms to aid production management decisions. We also observed the crop about once a week. Daily solar radiation, maximum and minimum air temperatures, rainfall or irrigation amounts, and wind runs were recorded in 1984 and 1985 at each of the cooperating farms using automated weather stations. We got a late start on this project in 1984. Development of the user interface took significantly more time than we anticipated;therefore, we did not make as many decision-making computer runs as we had hoped to make. Rainfall distribution precluded significant irrigation needs after delivery of the on-farm program in 1984 but irrigation was used in 1985. We cannot yet interactively simulate insect damage to the crop or the effects of growth regulators or boll openers. An enlightening and meaningful incident regarding fertilization on the South Carolina farm occurred in early August, 1984. GOSSYM indicated that the crop would soon “cut out,” or run out of nitrogen, causing photosynthesis to decrease and therefore causing the crop to accumulate less dry matter. The grower decided to evaluate the “What if?’ conditions of applying foliar nitrogen. For hypothesized additions of 1 1.2 and 22.4 kg N/ha, he found by running the computer program that yield increases of 0.137 and 0.223 kg/ha were predicted. He came to the conclusion that nitrogen should be applied to increase his net income. In spite of getting the hardware and software package delivered to the farms late in 1984, both growers were generally positive in their reaction to the experiencesof the first year. They were both willing to participate in the program in 1985 and made more timely use of the model. Both also felt that the model needed to be modified to account for insects, growth regulators, defoliants, and boll openers. We wholeheartedly agree. From the researcher’s viewpoint, the effort had several positive results. First, the initial discussions with the growers pertaining to the choices of available information to be included in the output were useful. The discussions focused the growers’ attention on the yield-determining attributes of the crop system. Second, the on-site discussionsindicated that when considering the benefits of a particular proposed action, emphasis should be placed on differences in growth and yield caused by cultural treatments rather than on absolute yield per se. As long as a reasonable yield is predicted, the

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absolute yield per se is not so important in making a decision about irrigation, fertilization, etc., as is the difference in yields with and without the hypothesized treatment. This point must be well understood by all users. Third, the transfer of this comprehensive, mechanistic model of the cotton crop-soil system serves as a medium to update the grower on new basic research findings about all parts of the cotton system. This transfer could be transparent to the grower, obviating any need for reeducation. The grower would only notice that the model seemed to be doing a better job of predicting his crop performance. G. ARTIFICIALINTELLIGENCE/EXPERT SYSTEMS An expert system is a computer system which is capable of performing at the level of a human expert. The objective is to allow an unavailable human expert to be replaced with a computer. Under certain circumstances, it has been possible to create expert systems which perform better than human experts. This is not because the computer knows more than the human expert, in fact it knows considerably less, but because it applies what it does know in a relentlessly thorough manner. The Agriculture Research Service of the USDA has developed the Crop Management Expert System (COMAX), which for cotton is called COMAX/GOSSYM, and which advises cotton growers regarding the application of nitrogen, imgation, and growth regulators (McKinion and Lemmon, 1985). (At present this is the only model using the COMAX concept. As it is expanded we anticipate COMAX/GLYCIM, etc.) COMAX, like most expert systems, consists of a knowledge base and an inference engine. The knowledge base is composed of a set of facts and a set of if- then rules. The third component to COMAX is the cotton plant model, GOSSYM. The method by which COMAX operates is as follows. The inference engine examines the rules, one at a time, and in no particular order. If all the conditions on the “if” side are met, then the inference engine will perform the actions specified on the “then” side of the rule. A simple rule might be, “IF the cotton plant is in nitrogen stress on day X,THEN hypothesize an application of 45 kg/ha of nitrogen 10 days before X,and run this hypothesis on the GOSSYM model to determine the impact on the cotton yield.” The power of a rule-based expert system is founded in two very important concepts. First, it is easy to write the rules, easy to understand them, and easy to change them if they do not work out. It is not necessary to call in a programmer to change or remove rules and facts. While the rule quoted above is not precisely the way it is entered into COMAX, it is very close, and experts have no difficulty in learning how to compose rules or in understanding existing rules.

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The second important concept in rule-based systems is that the order in which the rules are entered is irrelevant. It is the function of the inference engine to examine the rules continuously and when the conditions on the if side are all true, the inference engine performs the actions specified on the then side. In classical computer programming, the order in which things are to be performed is integral to the program, and the difficulty of specifying components in the proper order under all circumstances is a major source of programming bugs. In a rule-based system the order in which functions are to be performed is not specified. Instead, the situation in which rules are to be used is specified. The designer concerns himself with the circumstances which dictate what things are to be performed, and not with the order. He asks himself, “Under what circumstances do I want this rule to be used?” He then specifies those circumstances on the if side of the rule, and writes the actions to be taken when these circumstances are true, on the then side of the rule. COMAX works in a mode of hypothesizing and testing. It hypothesizesa scenario for fertilizing and irrigating, and then tests the impact of the scenario by running GOSSYM with the hypothesized values. A set of rules is used to determine an approximately good scenario for fertilization and irrigation. Another set of rules is used to improve on the first approximations by optimizing them, using the optimization methods of operations research. Finally, it is important for the grower to know when his cotton has matured. This is particularly important in some locations such as the Mississippi Delta where there is a threat of early rains which can physically damage the crop, create conditions conducive to boll rot, and cause the soil to become plastic so that cotton pickers cannot operate. COMAX informs the grower when the crop is mature. The grower can then harvest his cotton at the earliest possible date, when he knows that delaying the harvest will not increase the yield. COMAX was developed on a high-speed, LISP language computer used for the development of artificial intelligence systems (expert systems is a subfield of artificial intelligence). However, COMAX was designed to run at the farm site on a PC-type computer. It begins the season by hypothesizinga management strategy for the grower. As the season goes on, the hypothesized weather, rainfall, irrigation, and fertilization are replaced with the actual values. Each day COMAX recomputes the optimum management strategy based on this new knowledge. For example, on Monday COMAX may have advised the grower that based on the expected weather it will be necessary to imgate on Friday. But if Monday’s and Tuesday’s weather were colder or wetter than expected, then COMAX will change its recommendation correspondingly.And of course if the Monday and Tuesday weather were hotter and drier than expected it will change its recommendation in the other direction. The point is that

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COMAX is an expert system that very much operates in the real world, changing its recommendationsas circumstanceschange,just as in the case of a human expert.

V. SUMMARY We have reviewed the building of crop simulation models and some of the terminology used to describe certain aspects of modeling, and listed some of the current models. We have built physiologically,physically based, mechanistic, process-level crop simulation models for cotton, soybeans, and wheat. This effort has identified numerous knowledge gaps. Naturally lit, controlled-environment facilities have been developed and operated specifically to fill the gaps in the model data bases. The cotton model, GOSSYM, has been widely validated and the soybean and wheat model less so. These models have been used as tools in predicting breeding feasibility, soil erosion impact, insect damage, and herbicide injury. They have also been used to test physiological theories. In the last 2 years, GOSSYM has been used in a user-friendly form on a PC microcomputer as a tool for on-farm management decisions pertaining to nitrogen fertilizer applications, irrigation scheduling, and timing of harvest-aid chemicals. By combining GOSSYM with an expert system program, COMAX, the on-farm management decisions have been run in several combinations to give the user an optimal plan for fertilizer and irrigation scheduling. REFERENCES Acock, B. 1980. In “Opportunities for Increasing Crop Yields” (R. G. Hurd, P. V. Biscoe, and C. Dennis, eds.), pp. 131 - 148. Pitman, London. Acock, B., and Allen, L. H., Jr. 1985. In “Direct Effects ofCO, on Vegetation,” Chapter 4. U.S. Dept. Energy, Washington, D.C. Acock, B., Thornley, J. H. M., and Warren Wilson, J. 1971. In “Potential Crop Production’’ (P. F. Wareing and J. P. Cooper, eds.),pp. 43-75. Heinemann, London. Acock, B., Charles-Edwards,D., and Sawyer, S. 1979. Ann. Bot. (London) [N.S.] 44,289- 300. Acock, B., Reddy, V. R., Whisler, F. D., Baker, D. N., McKinion, J. M., Hodges, H. F., and Boote, K. J. 1985. “The Soybean Crop Simulator GLYCIM: Model Documentation 1982,” PB85 171 163/AS. U.S. Dept. Agric., Washington, D.C. (available from NTIS, Springfield,Virginia). Adams, R. S., Jr., and Pritchard, D. J. 1977. Agron. J. 69,820-824. Allen, L. H., Jr. 1974. Agron. J. 66,41-47. Anderson, W. P., Richards, A. B., and Whitworth, J. W. 1967. Weeds 15,224-227. Aspinall, D. 1961. Ausf. J. Eiol. Sci. 14,493-505. Baker, D. N., and Acock, B. 1986. In “Cotton Physiology: A Treatise” (J. Mauney and M. Stewart, eds.) (in press).

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Baker, D. N., and Meyer, R. E. 1966.Crop Sci. 6, 15- 19. Baker, D. N.,and Musgrave, R. B. 1964. Crop Sci. 4, 127- 13 I. Baker, D. N., Hesketh, J. D., and Duncan, W. G. 1972.Crop Sci. 12,431 -435. Baker, D. N., Bruce, R. R., and McKinion, J. M.1973.Proc. BeltwideCottonProd. Res. ConJ, pp. 110- 114. Baker, D. N., Hesketh, J. D., and Weaver, R. E. C. 1978.In “Crop Physiology” (U. S. Gupta, ed.), pp. 110- 135.Oxford and IBH Publishing Co., New Delhi, Bombay, and Calcutta. Baker, D. N., Landivar, J. A., Whisler, F. D., and Reddy, V. R. 1979. “Plant Responses to Environmental Conditions and Modeling Plant Development,” Proc. Weather Agric. Symp. (W. L. Decker, ed.),pp. 69- 109. Baker, D. N.,Lambert, J. R., and McKinion, J. M. 1983. Tech Bull.-S. C.Agric. Exp. Stn.

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Fems, H., Du Vernay, H. S., and Small, R. H. 1978. J. Nematol. 10,39-42. Francis, C. A. 1970. Agron. J. 62,790-792. Fritschen, L. J. 1967. Agric. Meteorol. 4,55-62. Fye, R. E., Reddy, V. R., and Baker, D. N. 1984. Agric. Syst. 14, 1-21. Gardner, W. R., and Mayhugh, M. S. 1958. Soil Sci. Soc. Am. Proc. 22, 197-201. Gamer, W. W., and Allard, H. A. 1930, J. Agric. Res. (Washington, D.C.) 41,719-735. Gertsis, A. C. 1985. M.S.Thesis, Mississippi State University, Mississippi State. Gordon, E. C., Frans, R. E.,Talbert, R. E., and Waddle, B. A. 1979. Bull.-Arkansas, Agric. Exp. Stn. 836. Graham, J. P., Clarkson, D. T., and Sanderson, J. 1974. Annu. Rep.-Agric. Res. Counc., Letcombe Lab., pp. 9 - 12. Green, P. B., Erickson, R. O., and Buggy, J. 197 I. Plant Physiol. 47,423-430. Gutierrez, A. P., and Wan& Y. 1979. Can. Entomol. 111,41-54. Gutierrez, A. P., Falcon, L. A., Loew, W., Leipzig, P. A., and van den Bosch, R. 1975. Environ. Entomol. 4, I25 - 136 Gutierrez, A. P., Wang, Y.,and Regev, U. 1979. Can. Entomol. 111,41-54. Hadley, P., Roberts, E. H., Summerfield, R. J., and Minchin, F. R. 1984. Ann. Bot. (London) [N.S.] 53,669-681. Hailey, J. L., Hiler, E. A., Jordan, W. R., andvan Bavel, C. H. M. 1973. CropSci. 13,264-267. Hansen, W. R., and Shibles, R. 1978. Agron. J. 70,47-50. Hartstack, A. W. 1982. Proc. Int. Workshop Heliothis Manage., pp. 51-60. Hartstack, A. W., Witz, J. A., Hollingsworth, J. P., Ridgway, R. L., and Lopez, J. D. 1976. “MOTHZV-2: A Computer Simulation of Heliothis zea and Heliothis virescens Population Dynamics,” ARS-S-127. U.S. Dept. Agric., Agric. Res. Serv.,Washington, D.C. Hartstack,A. W., Witz,J. A.,andLopez, J.D. 1981. “PredictingtheTimingandPotentialofthe Spring Emergence of Overwintered Populations of Heliothis spp.,” NASA Grant T-4629H. Nat. Tech. Inf. Serv., Washington, D.C. Heilman, J. L., and Kanemasu, E. T. 1976. Agron. J. 68,607-61 1. Hernandez, M. 0. 1984. M.S. Thesis, Mississippi State University, Mississippi State. Hesketh, J. D., and Baker, D. N. 1967. Crop Sci. 7,285-293. Hesketh, J. D., Baker, D. N., and Duncan, W. G. 1972. Crop Sci. 12,435-439. Hofstra, G., and Hesketh, J. D. 1969. PIanta 85,228-237. Honidge, J. S., and Cockshull, K. E., 1979. Ann. Bot. (London) [N.S.] 44, 547-556. Idso, S. B., Jackson, R. D., Reginato, R. J., Kimball, B. A., and Nakayama, F. S. 1975. J. Appl. Meterol. 14, 109 - 1 1 3. Ives, P. M., Wilson, L. T., Cull, P. O., Palmer, W. A., Haywood, C., Thompson, N. J., Hearn, A. B., and Wilson, A. G. L. 1984. Prof.Ecol. 6, 1-21. Jackson, J. W., and Palmer, J. W. 1979. Ann. Bot. (London) [N.S.] 44,381 -383. Jenkins, J. N., Baker, D. N., McKinion, J. M., and Pamott, W. L. 1973. In “Symposium Proceedings: The Application of Systems Methods to Crop Production” (Baker, Creech, and Maxwell, eds.),pp. 49-90. College of Agriculture, Mississippi State University, Mississippi State. Kafkafi, U., Bar-Yosef, B., and Ha&, A. 1978. Soil Sci. 125,261 -268. Keeling, C. D., Bacastow, R. B., and Whorf, T. P. 1982. In “Carbon Dioxide Review: 1982” (W. C. Clark, ed.), pp. 377-385. Oxford Univ. Press, London and New York. Kerby, T. A., and Buxton, D. R. 1976. Proc. Beltwide Cotton Prod. Res. Conf, 67-70. Ketchersid, M. L., Boswell, T. E., and Merkle, M. G. 1969. Agron. J. 61, 185- 187. Kharche, S. G. 1984. Ph.D. Dissertation, Mississippi State University, Mississippi State. Koller, H. R. 1972. Crop Sci. 12, 180- 183. Lambert, J. R., Baker, D. N., and Phene, C. J. 1976. In “Computers Applied to the Management

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ADVANCES M1 AGRONOMY. VOL. 40

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY IN SOIL W. D. Gould,’ C. Hagedorn,* and R. G. L. McCreadyl

’ Biotechnology Section, CANMET, Energy Mines and Resources Ottawa, Ontario, Canada K1A OG1 Allied Corporation, Syracuse Research Laboratory, Solvay, New York 13209

I. INTRODUCTION A. PREVIOUS REVIEWS CONCERNING UREAAND ITS USE

Although a number of review articles have dealt with the environmental, chemical, and physical factors affecting the hydrolysis of urea in soil (Bremner and Mulvaney, 1978; Kiss el a/., 1975; Ladd, 1978;Skujins, 1967, 1976), to date, none have discussed urea transformation in the field. Most of the studies relating to urease activity in soil have been conducted in the laboratory where a urea solution, with or without a buffer, has been added to a soil sample. These types of studies have improved our understandingof soil urease activity, but they do not simulate field conditions, and in order to improve the efficiency and use of urea as a fertilizer, it is necessary to understand the soil interactionsof urea under field conditions.The environmental and soil factors affecting ammonia losses from fertilizer urea have been discussed by Terman ( 1979), Nelson ( 1982), and Gasser ( 1964a).Urease inhibitors and methods of controlling urea transformations in soil were thoroughly reviewed by Sahrawat (1980) and by Mulvaney and Bremner ( 1981). A number of papers have recently been published concerning a new class ofurease inhibitors,the phosphorodiamidatesand phosphorotriamides which are the most effective inhibitors presently known for soil urease (Martens and Bremner, 1984b). The objectives of this review are to discuss (1) environmental, chemical, and physical soil conditions which must be considered in regard to controlling urea transformationsin the field; (2) studiesthat have directly measured urea transformations in the field or under simulated field conditions;and (3) new classes of urease inhibitors that may improve the efficiency of urea under field conditions. 209 CopvriehlO 1986 by Aadcmic Resq Inc. AU rights of reproduction in any forin mewed.

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W. D. GOULD ET AL.

B. AGRONOMICIMPORTANCE OF UREA Although urea was first used as a fertilizer in 1935 it was not used extensively until the 1960s. A number of problems concerningthe physical properties and the low nitrogen efficiency of urea prevented its rapid acceptance as a fertilizer. Many of these problems have been overcome by new technology and proper management procedures. The production of urea has increased more rapidly than any of the other nitrogenous fertilizers. During 1980- 1981, urea accounted for 12%of the 12.7 X lo6 metric tons of fertilizer utilized in North America and accounted for 70%of the nitrogen fertilizer utilized in Asia. Due to its high N content, ease of handling, and recent technological improvements, urea is predicted to gain an even greater percentage of the total N fertilizer sales in the future (Beaton, 1978).Presently, only anhydrous ammonia is a less expensive nitrogen source than urea.

c. FACTORS AFFECTINGTHE EFFICIENCYOF UREA AS A FERTILIZER I. BeneJits The manufacture of urea uses inexpensive starting materials, carbon dioxide and ammonia, the former a by-product, and the latter the final product of anhydrous ammonia manufacture. The chemical synthesis of urea has a higher yield efficiency than that achieved in the manufacture of ammonium nitrate (Beaton, 1978). Urea has less tendency to coalesce and compact than ammonium nitrate, is less corrosive than other nitrogen fertilizers, and is suitable as a camer for a number of herbicides. Much ofthe urea in the United States is applied as urea ammonium nitrate solution prepared by combination of urea with ammonium nitrate, resulting in a solution of 28-32% N (Englestad and Hauck, 1974; Pesek et al., 1971), since their combination increases the solubility of both fertilizers (Hardesty, 1955). 2. Problems Although urea is frequently equivalent to other nitrogenous fertilizers (Smith and Chalk, 1980c; Van Lierop and Tran, 1980) poor crop responses to urea have frequently been observed (Beaton, 1978).The rapid hydrolysis of urea in the soil can result in high soil pH values and high ammonium ion concentrations which are conducive to the accumulation of ammonia. The major problems observed in urea fertilization are the loss of volatile ammonia gas and ammonia toxicity to germinating seedlings (Court et al., 1964a).

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY

211

Also, the accumulation of nitrite in the soil following the hydrolysis of urea can result in toxicity and nitrogen losses. Biuret, which is found in low concentrations in urea, is phytotoxic under certain conditions. The low density and small size of prilled urea makes it unsuitable for broadcasting and blending with other fertilizers. Prilled urea is also friable and tends to produce fines during handling. The disadvantages of prilled urea are eliminated by use of granular urea.

II. PROBLEMS ASSOCIATED WITH UREA FERTILIZERS A. BIURET

The dimer of urea, biuret, is formed by the thermal decomposition of urea during the preparation of prilled and granular urea (Court et af., 1964a; Reynolds and Trimarke, 1964). Biuret is known to interfere with protein synthesis in plants ( Webster et al., 1957),and phytotoxic effectsare generally observed when the biuret content of urea is greater than 1% (Low and Piper, 1961; Smika and Smith, 1957; Wilkinson and Ohlrogge, 1960). There are some crops (i.e., citrus fruit, pineapple, and coffee)that are very sensitive to biuret; and urea containing more than 0.25%biuret cannot be used on these crops (Church, 1964). High concentrations (1 - 10%)of biuret in urea has been shown to inhibit nitrification of the urea in soil (Sahrawat, 1977). Foliarly applied urea containing 4% biuret has been shown to have no deleterious effects on soybeans (Poole ef al., 1983). However, the biuret content of most urea fertilizers currently being produced is less than 1% (Church, 1964; Reynolds and Trimarke, 1964); thus biuret contamination of urea is no longer considered a problem.

B. ACCUMULATION OF NITRITEIN SOIL The accumulation of nitrite in the soil may be toxic to the plants and may result in losses of gaseous nitrogen by chemical denitrification. The alkaline pH and high ammonium ion concentrations resulting from urea hydrolysis in soils do not appreciably affect the oxidation of ammonia to nitrite by Nitrosomonas sp., but does inhibit the oxidation of nitrite to nitrate by Nitrobacter sp. (Chapman and Liebig, 1952; Hauck and Stephenson, 1965; Wetselaar ef al., 1972).Bezdicek ef af.(1 97 1) compared the behavior ofurea, diammonium phosphate, and ammonium sulfate in an alkaline soil. They

212

W. D. GOULD ET AL.

found that the highest accumulation of nitrite (260 ppm) occurred in the soil to which urea had been added. In contrast to the biological reactions, three chemical reactions for the loss of nitrite are known. 1. The decomposition of nitrous acid (Allison, 1963; Nelson and Bremner, 1970b; Van Cleemput and Baert, 1976): 2HN0,

-

NOT

+ NO,f + H,O

In the soil, both the nitric oxide and nitrogen dioxide produced by this process may undergo further reactions in the soil (Nelson, 1982). 2. The Van Slyke reaction between the nitrite ion and a-amino acids (Christianson and Cho, 1983; Sabbe and Reed, 1964; Smith and Chalk, 1980b): NH, 0

I

I1

R-CH-C-OH

OH 0

+ HNO,

I

II

R-CH-C-OH

+

-+

+ H,O + NZf

3. The decomposition of ammonium nitrite (Allison, 1963) NH,NO,

N,

2H,O

Volatile nitrogen losses by the decomposition of ammonium nitrite are unlikely since studies utilizing "N have shown that all of the nitrogen gas evolved from nitrite was a result of a Van Slyke type of reaction (Christianson and Cho, 1983;Smith and Chalk, 1980b). Wullstein and Gilmour (1 964, 1966) have suggested that metal cations enhance nitrite decomposition in soil, but others have not confirmed this hypothesis (Moraghan and Buresh, 1977;Nelson and Bremner, 1970a).The reactions involved in the volatilization of nitrogen from nitrite are enhanced by low pH (Allison, 1963; Sabbe and Reed, 1964),but these conditionsare not favorable for the accumulation of nitrite. However, appreciable chemical denitrification has been observed at alkaline pH values (Smith and Chalk, 1980a). Toxicity to plants from nitrite accumulation has been observed subsequent to the addition of urea fertilizer (Court et al., 1962, 1964b).

C. LEACHING As urea is a nonionic compound, it is susceptibleto leaching in soil, but at a slower rate than the nitrate ion; it can be weakly adsorbed by soil and is simultaneously hydrolyzed to ammonium bicarbonate by soil urease (Broadbent et al., 1958). Urea is retained within soil due to salt formation between urea and the carboxyl groups of soil organic matter. At acid pH

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY

2 13

values urea can be protonated and behave as a cation (Broadbent and Lewis, 1964; Chin and Kroontje, 1962).Urea can also complex with clay minerals (Farmer and Ahlrichs, 1969; Mitsui and Takatoh, 1963; Mortland, 1966). Leaching losses of urea may occur by two processes: ( 1) urea is leached per se from the soil, and (2) urea migrate below the rooting zone, is hydrolyzed, nitrified, and then leached as nitrate (Bauder and Montgomery, 1980). Split applications of urea have been shown to result in large losses of nitrate by leaching (Bauderand Schneider, 1979).Leachinglosses of nitrogen from the application of urea to forest soils have been found to be quite low (Overrein, 1968, 1969). TOXICITY D. Loss OF AMMONIAAND AMMONIA Ammonia toxicity and the loss of nitrogen as volatile ammonia are the major problems encountered with fertilizer urea. An equilibrium between ammonium ions and ammonia gas occurs in aqueous solutions of ammonium salts. At pH values below 7, the ammonium ion predominates, whereas above pH 8.5 free ammonia is the predominant form (Bates and Pinching, 1950). Although the ammonium ion is relatively nontoxic, ammonia gas is extremely toxic (Warren, 1962). In studieson excised beet root disks and beet root mitochondria, ammonia was found to interfere with the NADH oxidase system, an integral part of the electron transport system (Vines and Wedding, 1960).The hydrolysis of urea with subsequentproduction of ammonia inhibits the germination of corn (Liege1 and Walsh, 1975a,b). The alkaline hydrolysis products of urea (ammonium bicarbonate and ammonium hydroxide) can increase the pH of soil microenvironments, resulting in the loss of soil ammonium by volatilization (Ernst and Massey, 1960; Terman, 1979). The greatest ammonia losses have generally been observed in soils where urea has been broadcast. The loss of ammonia from flooded rice soils that have been fertilized with urea has recently been recognized as a severe problem (Fillery ef al., 1984; Vlek and Craswell, 1981). However, when urea is applied to rice at an earlier stage of growth biological denitrification is the major mechanism of nitrogen loss (Simpson et al., 1984). The loss of nitrogen from urea by ammonia volatilization is favored by a high initial soil pH (Overrein and Moe, 1967), low soil buffer capacity (Ferguson etal., 1984;MartinandChapman, 195l;Nelsonetal., 1980),and high temperatures (Lippold et al., 1975; Watkins et a]., 1972). Ammonia losses from agricultural soils vary from 0.4 to 80% of the applied urea nitrogen (Fernando and Roberts, 1975; Gasser, 1964b; Hargrove and Kissel,

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W. D. GOULD ET AL.

1979;Kresge and Satchell, 1960; Simpson, 1969; Torello et al., 1983; Volk, 1959), and from 3.5 to 24.9% in forest soils (Nommik, 1973a; Overrein, 1968). Volatilization loss measurements are dependent on experimental technique (Kissel et al., 1977; Watkins et al., 1972), but even though the absolute magnitude of nitrogen loss may be difficult to predict, comparative studies are still valid. In order to simulate field conditions Boumeester et al. (1985) measured ammonia losses from urea broadcast on soil placed in a wind tunnel. They measured a loss of 40% of the urea nitrogen when a simulated rainfall event of 1 cm was applied 7 days subsequent to fertilization. The ammonia loss was reduced to 13%of the added urea nitrogen when a simulated rainfall event of 4 cm was applied subsequent to fertilization. A urease inhibitor could have some use in maintaining the fertilizer as urea until sufficient rainfall occurred to wash it into the soil. Hanawalt ( 1969) and Mahendrappa and Ogden ( 1973) have suggested that volatile ammonia lost from urea-fertilized soil may be reabsorbed by adjacent soils.

E. IMMOBILIZATION Immobilization of urea nitrogen has been shown to be a problem particularly in some forest soils and under reduced tillage. Appreciable amounts of the urea applied to forest soils are rapidly immobilized in a nonexchangeable form which is not available to the trees (Momson and Foster, 1977; Nommik, 1970; Overrein, 1970;Worsnop and Will, 1980). Several explanations have been advanced for the rapid incorporation of urea into the organic fraction of forest litter: ( 1) microbial immobilization of nitrogen (Overrein, 1970), (2) a chemical reaction between humus and urea (Ogner, 1972), and (3) a chemical reaction between ammonia and soil organic matter (Burge and Broadbent, 1961). Foster et al. (1985) added I5N-labeledurea to sterile and nonsterile forest soils and concluded that the immobilization of urea occurs via the chemical reaction of ammonia with soil organic matter at elevated pH values. Both elevated pH and high concentrations of gaseous ammonia would be present in the vicinity of a urea granule and likely make urea more prone to such reactions than other nitrogen fertilizers. Heilman et al. ( 1982a,b)reported that most of the fertilizer nitrogen was assimilated by Douglas fir within 168 days of fertilization and thus immobilized nitrogen would probably not be utilized. Also, the high C/N ratio ofthe surface mulch that accumulateson no-till soilsis conducive to microbial immobilizationof nitrogen (Allison, 1966; Frederickson et al., 1982; Rice and Smith, 1984).

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY

2 15

F. EFFECTOF MANAGEMENT ON UREARESPONSE

Intensive fertilization of grasses and forage crops is practiced in western Europe (Craven and Kilkenny, 1974),and nitrogen applications vary from 125 to 500 kg/ha (Widdowson et af.,1973). Although increased yields have been obtained by fertilization of fescue grassland in southern Alberta, fertilization of pastures is not considered economically feasible in western Canada (Smith et al., 1968).The current agronomic practices for nitrogen fertilization of forages and grasses are: (1) to broadcast solid fertilizer (Hill and Tucker, 1968; Penny et af., 1977; Widdowson et af., 1973), (2) surface banding of fertilizer solutions (Mengel, 1985), and (3) injection of anhydrous ammonia or fertilizersolutions(Penny et af.,1977;Widdowson et af., 1973).However, anhydrous ammonia may temporarily kill grasses adjacent to the zone of injection (Hill and Tucker, 1968; Widdowson et al., 1973). Urea has not been as effectiveas other nitrogenous fertilizers when broadcast on grasses (Simpson, 1968; Power, 1974; Westerman et af.,1983). Ammonia volatilization from urea broadcast on grasses has been well documented (Gasser, 1964a; McGarity and Hoult, 1971; Simpson, 1969; Simpson and Melsted, 1962; Volk, 1959)and can be attributed to the high urease activity of the surface thatch layer (Torello and Wehner, 1983)and a low absorbtive capacity for ammonia (Nelson et af.,1980).Surface application of urea is equivalent to other fertilizersif it is incorporated into the soil by mixing or washed in by rainfall subsequent to application (Ansorge et af., 1973; Ernst and Massey, 1960). Urea has several advantages as a nitrogen source for aerial application on forests; it is relatively nontoxic, has a high N analysis, and may be directly absorbed by the foliage (Volk, 1970). Urea is generally equivalent to other nitrogenous fertilizers used in forests (Fisher and Pritchett, 1982;Weetman and Fournier, 1984),but in some studies has been shown to be an inferior N source (Brix, 1981;Pang, 1985). The major problems observed in the urea fertilization of forests are ammonia volatilization (Acquaye and Cunningham, 1965;Craig and Wollum, 1982; Marshall and De Bell, 1980)and immobilization (Nommik, 1970). Management systems employing zero and minimal tillage have become more popular, and by the year 2000,45%ofthe cropland in the United States could be under reduced tillage (Phillips et al., 1980). The presence of the surface residues on no-till soils increases soil moisture, affects biological activity in soil, and changes soil nitrogen transformations (Aulakh et af., 1984; Doran, 1980a,b; Rice and Smith, 1982, 1983). The current nitrogen fertilization practices in reduced tillage cultivation are broadcasting, injection of anhydrous ammonia and liquid fertilizers,

216

W. D. GOULD ET AL.

spray application of urea- ammonium nitrate (UAN) solutions, and surface banding of UAN solutions (Mengel, 1985; Richey et al., 1977; Touchton and Hargrove, 1982). Broadcast urea has been shown to be less effective than ammonium nitrate or injected N sources on no-till soils (Bandel et al., 1980; Fox and Hoffman, 198 1; Touchton and Hargrove, 1982), primarily due to volalitization of ammonia (Fox and Hoffman, 198 1 ;Mengel, 1985).

Ill. UREA TRANSFORMATIONS A. HYDROLYSIS 1. Laboratory Studies

The enzyme urease (urea amidohydrolase, EC 3.5.1.5) which catalyzesthe hydrolysis of urea was first crystallized from the jack bean (Cunavaliu ensiformis) by Sumner ( 1926). Urease is found in some higher plants and in most species of bacteria, yeast, and fungi (Sumner, 1953). The ability to hydrolyze urea was found to vary from 17 to 7 1% for soil bacteria and from 78 to 98% for soil fungi (Lloyd and Sheaffe, 1973; Roberge and Knowles, 1967). Although soil urease is considered to be of microbial origin (Skujins, 1976) there is evidence that some soil urease activity may be derived from plants (Frankenbergerand Tabatabai, 1982). However, there is no direct evidence for the production of urease by plant roots (Estermann and McLaren, 196 1). Paulson and Kurtz (1969) altered soil urease activity by adding various amendments, and calculated, with regression analysis, that 79 - 89% of soil urease activity was extracellularand complexed by soil colloids. A significant amount of soil urease can be extracted as an organo-urease complex (Bums et al., 1972a,b; Ceccanti et al., 1978; McLaren et al., 1975; Nannipieri et al., 1974,1978). This extracted organo-ureasecomplex was found to be resistant to digestion by pronase (Bums et al., 1972a). Soil urease and organo-urease complexes extracted from soil are more stable than jack bean urease under comparable conditions (O'Toole and Morgan, 1984; Pettit et al., 1976). Zantua and Bremner (1976) found that a number of Iowa soils had a stable level of urease activity that depended on the propertiesof the individual soil. Although varying results have been obtained when urease activity has been compared with soil properties, the soil organic carbon content has been shown to correlate quite well with urease activity (Beri and Brar, 1978;Dalal, 1975a; Speir, 1977; Zantua et al., 1977). Urease activity is usually highest in the surface horizons of forest soils (Roberge and Knowles, 1966, 1968) and

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY

2 17

lowest in alkaline and saline soils (Kumar and Wagenet, 1985; Skujins and McLaren, 1968). Very high urease activities have been observed in some tropical soils (Dalal, 1975a)while weak urease activity has been observed in the lower mineral horizons of a number of soils (Gould et al., 1973; Myers and McGarity, 1968). A large number of studies have examined the effect of temperature, pH, water level, and urea concentration on the rate of urea hydrolysis in soil. Many of these measurements have been made with different assay techniques and comparisonsbetween soils using data from the literature must be made with caution. The hydrolysis of urea in soil generally follows Michaelis- Menten kinetics; that is, the hydrolysis rate increases with increasing substrateconcentration until the enzyme is saturated (Dalal, 1975a; Tabatabai, 1973; Tabatabai and Bremner, 1972). At very high urea concentrations the hydrolysis rate decreases, probably due to substrate inhibition of the enzyme ( Rachhpal-Singh and Nye, 1984a).The hydrolysis of urea in soil increases with increasing temperature according to the Arrhenius equation (Dalal, 1975a; Gould et al., 1973) up to 60 to 70°C and then decreases rapidly above that temperature range (Pettit et al., 1976; Sahrawat, 1984; Zantua and Bremner, 1977).A pH optimum for soil urease of 6.5 -7.0 was found by Pettit et al. (1976) and pH optima of 8.8-9.0 have been found by others (May and Douglas, 1976; Tabatabai and Bremner, 1972). Differing results for the effect of water content on the rate of urea hydrolysis in soil have been found. In most studies urease activity was not appreciably affected by the soil water content (Delaune and Patrick, 1970;Gould et al., 1973; Skujins and McLaren, 1967, 1968, 1969), but others have found the hydrolysis rate to increase (Kumar and Wagenet, 1984; Rachinskiy and Pel’tser, 1965)or decrease (Dalal, 1975a;Simpson and Melsted, 1963)with increasing water content. Sahrawat (1984) found the urease activity to be unaffected by the water contents above 20% (w/w) but to decrease rapidly below that level. Vlek and Carter (1983) found that urea hydrolysis rates decreased below the permanent wilting point. 2. Field and Simulated Field Studies

There have been very few studies in which the hydrolysis rate of urea has been determined in the field. In the soil surrounding a urea prill, granule, or band, gradients of pH, urea, and ammonium ion concentrations develop ( Rachhpal-Singh and Nye, 1984b). Malhi and Nyborg ( 1979)measured the hydrolysis rate of urea under field conditions and simulated field conditions. They found that the equivalent of 200 pg urea N/g of soil added as pellets to soil in the laboratory was completely hydrolyzed in 160 hr. The same con-

W. D.GOULD ET AL.

218

centration of urea added as a solution to the same soil in the laboratory hydrolyzed in 20 hr (Gould et al., 1973). However, prilled urea added to field plots required 192 hr to completely hydrolyze (Malhi and Nyborg, 1979). Mohammed et al. (1 984) applied 100 kg urea nitrogen/ha to the soil surface and determined that 86% of the urea was hydrolyzed after 1 week. Aulakh and Rennie (1984) added lSN-labeledurea at a rate of 100 kg N/ha to field microplots during the fall and estimated that only 60% of the urea hydrolyzed in 3 weeks. They attributed the reduced hydrolysis rate to the low soil temperatures at that time of the year. Campbell et al. ( 1984) added urea to soil columnsin order to simulate field conditions and found urea hydrolysis to depend on the application method and soil moisture content. Urea incorporated in the soil hydrolyzed more rapidly than banded urea. The differencein hydrolysis rate between banded and incorporated urea was greater in the dry soil, probably due to less water contact with the banded urea which would limit dissolution and hydrolysis (Campbell et al., 1984). Savant and De Datta (1979) measured the amount of urea remaining at placement sites when urea was placed at lower depths in a wetland rice field. However they only recovered a portion of the urea, and thus an accurate hydrolysis rate could not be calculated. A number of simulation models have been developed in order to understand some of the processes involved in urea transformationsin soil (Ardakani et al., 1975; McLaren, 1970; Parton et al., 1981; Scotter et al., 1984; Wagenet et al., 1977). The effectsof a number of environmentalvariables on the spatial and temporal distributions of the various nitrogenous intermediates can be easily simulated by various computer models.

B. SUBSEQUENT REACTIONS OF UREAIN THE SOIL Urea is rapidly hydrolyzed under favorable conditions to ammonium bicarbonate, which is subsequentlynitrified (Fig. 1). Nitrite and nitrate ions 0 H,N

II

;tc

-

-N H ~

NH~-NO;-

I

N 2 0-1

NO;

I

NO;

N2 f

FIG.1. Possible reactions of urea in the soil.

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY

2 19

and urea can readily diffuse through the soil or be leached. However, ammonium ions are much less mobile. Nitrification is favored by neutral pH, adequate aeration and higher temperatures (Ayanabaand Kang, 1976;Pang et al., 1977). The nitrification of band-applied urea has been shown to be dependent on the diffusion of ammonium away from the band (Pang et al., 1973). Pang et al. (1 975a) studied the nitrification of band-applied urea in soil columns and found rapid nitrification in high pH soils and a very slow rate of nitrification in low pH soils. Liming the low pH soils decreased the rate of nitrification of urea-derived ammonium. In order to obtain rapid nitrification in the low pH soil it was necessary to both lime to neutral pH and either add an inoculum of the active soil or a pure culture of Nitrosornonas to the soil (Pang et al., 1975a). No nitrite was observed in a soil column when urea was applied at a rate equivalent to 100 kg N/ha, but significant quantities of nitrite accumulatedwhen 200 and 800 kg urea N/ha were added to the soil columns (Pang et al., 1975b). Very high concentrations of banded urea could produce nitrite sufficient to cause gaseous losses of N2 and N20 (Christianson et al., 1979). In the immediate vicinity of a band, the high pH values and high ammonium ion concentrations are conducive to the accumulation of nitrite (see Section 11,B). After 6 weeks, the distribution of inorganic nitrogen was symmetrical around the band of urea under isothermal conditions (Pang et al., 1977). However, when a temperature gradient (8.5 to 23 "C) was establishedin a soil column, a higher proportion of the added nitrogen was found at the warm end of the column after a 6-week incubation (Table I). Vaporizationofwater Table I

Effect of Temperature Gradient on Distribution of Inorganic Nitrogen around a Band of

Temperature conditions Isothermal Temperature gradient

Nitrogen concentration (Pg N/g soil) Above urea

Below urea

600 1032

74 1 329

From Pang ef al. (1977). bDistribution determined after 6 weeks above and below banded urea under a temperature gradient of 8.5 to 23°C and under isothermal conditions. a

220

W. D. GOULD ET AL.

at the warm end and condensation at the cold end would result in return liquid flow to the warm end, thus resulting in transport of nitrogen to the warm end. Since similar temperature gradients are observed in field soils during the spring, it is very likely that this phenomenon occurs in the field (Pang et al., 1977).

IV. METHODS TO ALTER THE EFFICIENCY OF UREA A. UREASE INHIBITORS

I . Introduction In recent years a number of approaches have been considered to prevent the accumulation of high concentrations of ammonium and the loss of ammonia by volatilization from soils when urea has been applied to the surface of the soil. The rapid biological hydrolysis of urea can be reduced by the use of urease inhibitors. In the past, many of the commonly used inhibitors were selected by a trial and error process. However, by understanding the reaction mechanism of the urease-catalyzed hydrolysis of urea and the chemistry of the active site of urease, it should be possible to choose potential urease inhibitors on a more rational basis. The currently accepted reaction mechanism for the enzymatic hydrolysis of urea is the enzymatic cleavage of urea to ammonia and carbamic acid (Fig. 2), followed by the chemical hydrolysis of carbamic acid to ammonia and carbon dioxide (Blakeley et al., 1969, 1982; Gorin, 1959). The presence of sulihydryl groups within the urease structure was first

FIG.2. Mechanism of the urease-catalyzedhydrolysis of urea.

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY

22 1

demonstrated by Sumner and Poland (1933), and their essential role in the catalytic activity of urease is now well documented (Andrews and Reithel, 1970; Gorin and Chin, 1965, Gorin et al., 1962; Riddles et al., 1983). Recent findings indicate that urease is a metalloenzyme and that it contains nine atoms of nickel per urease molecule (Dixon et al., 1975, 1980). Barth and Michel ( 1972) suggested that the imidazole group of histidine was involved in the enzymatic hydrolysis of urea by urease. X-Ray fluorescence studies indicate that each nickel atom may be bound to one or more histidine residues (Hasnain and Piggott, 1983). The ideal urease inhibitor (1) must be inhibitory at low concentrationsin order to be an economically feasible additive in fertilizer formulations, (2) must have minimal detrimental effects on plants and soil microorganisms (May and Douglas, 1975), and (3) must not be inactivated by soil constituents. As Mulvaney and Bremner (198 1) published a comprehensive review of urease inhibitors in 1981, only representative compounds of the major classes of urease inhibitors and new inhibitor formulationswill be discussed here. 2. Suljhydryl Reagents Any organic or inorganic compound which will react with sulfhydryl (mercapto) groups will inhibit urease to various degrees. Metal ions inhibit urease by reacting with the sulfhydryl groups (Shaw and Raval, 1961b) and the observed inhibition is inversely proportional to the solubility product of the metal-sulfide complex (Hughes et al., 1969; Shaw, 1954; Toren and Burger, 1968). pChloromercuribenzoate (Moe, 1967), dihydric phenols, aminocresols (Rodgers, 1984), and benzoquinones have also been used to inhibit soil urease (Fig. 3A) (Bremner and Douglas, 197 la; Mishra and Flaig, 1979; Mulvaney and Bremner, 1978; Tomar and MacKenzie, 1984). The dihydric phenols only inhibit urease when they are in the quinone form (Quastel, 1933). Thiol or sulfhydryl groups form addition products with some quinones (Cecil and McPhee, 1959), and they inhibit urease activity by blocking the essential group@)at the active site. Until recently, the quinone class of compounds were the most effective inhibitors of soil urease. Several heterocyclic sulfur compounds are known to be inhibitors of both jack bean urease and soil urease (Gould et al., 1978). Gould et al. (1978) postulated that the mechanism of inhibition was via a thiol-disulfide exchange reaction between a heterocyclic disulfide and the sulfhydryl group at the urease active site.

W. D. GOULD ET AL.

222

A OH

II

0

OH

HYDRoQUINONE

CATECHOL

183 4 - T H I A D I A Z O L E -2, ~-DITHIOL

p-BENZOQUINONE

5;AMINO-1 3 4 -THIADIAZOLE-2-THIOL

B

II

C H 3 C-NHOH

ACETOHY DROXAMIC ACID

0

H2N- 8 - N HOH

HYDROXYUREA

C H 3 ( CH2 Is-

51C -

NHOH

C APRY LOHY DROXAMI C ACID

FIG.3. Various compounds that have been evaluated as urease inhibitors. (A) Sulfhydryl reagents; (B) hydroxamates.

3. Hydroxamates The hydroxamic acids are the most thoroughly studied of the urease inhibitors. The hydroxamates are specific, noncompetitive inhibitorsof urease (Gale and Atkins, 1969; Kobashi et al., 1962). The most potent hydroxamate type of inhibitor identified to date is caprylohydroxamicacid (Fig. 3B) (Hase and Kobashi, 1967). Inhibition of urease by hydroxamates is believed due to a complex formation with one of the nickel atoms at the active site of urease (Dixon et al., 1975). Acetohydroxamicacid has been shown to be less effective in soil than many of the other urease inhibitors (Bremner and

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY

223

Douglas, 197la; Gould et al., 1978). This inhibitor reduces the rate of ammonia volatilization with a urea-fertilized soil; however the total amount of ammonia volatilized over an extended period of time is not reduced by this compound (Moe, 1967; Pugh and Waid, 1969a,b). 4. Structural Analogs of Urea and Related Compounds

Compounds that have structural similarities to urea inhibit urease by competing for the same active site on the enzyme. Thiourea, methylurea (Kistiakowskyand Shaw, 1953;Shaw and Raval, 196la), and the substituted phenylureas (Cervelli et al., 1975, 1976) are known inhibitors of jack bean urease (Fig. 4A). Ashworth et al. ( 1980)have measured urea hydrolysis and nitrification inhibition in soil by a number of xanthates. Neither the substituted ureas nor the xanthates provide sufficient inhibition of soil urease to be of practical agricultural value. Recently, a new class of urease inhibitors, the phosphorodiamidates (Heber et al., 1979; Matzel and Heber, 1979; Matzel et al., 1978, 1979; Muller and Forster, 1980), the phosphorotriamides (Millner et al., 1982), and the thiophosphoric acids (Liao and Raines, 1985) have been reported (Fig. 4B). Some of these compounds appear to meet all of the criteria for agronomically acceptible urease inhibitors. They are extremely effective inhibitors of soil urease activity at very low concentrations; e.g., phenylphosphorodiamidate(PPD) has been found to inhibit soil urease activity at concentrations as low as 0.2 pg/g of soil (Martens and Bremner, 1984b). Martens and Bremner (1984a) measured the inhibition of soil urease by PPD, phosphorodiamidinic acid, and 10 phosphorotriamides. They found that all but two of these compounds are better inhibitors of soil urease activity than hydroquinone, which had been reported to be the most effective inhibitor of soil urease prior to 1976. PPD, co-applied with urea pellets to flooded rice at a concentration of 1% w/w, delays urea hydrolysis, reduces volatile nitrogen loss, and increases the assimilation of nitrogen (Byrnes et al., 1983; Vlek et al., 1980b). Martens and Bremner (1984b) studied the effect of a number of environmental and soil factors on the ability of PPD to inhibit soil urease activity, and found that PPD was ineffective at higher temperatures. Inhibitors added to surface-applied urea solutions did not improve nitrogen recovery, but trichloroethylphosphorodiamidate and diethylphosphorotriamidateimproved nitrogen efficiency when coated on broadcast urea (Broadbent et al., 1985). Since only a few of the phosphoroamide class of compounds have been examined as potential urease inhibitors it is likely that compounds superior to PPD will be discovered.

W. D. GOULD ET AL.

224

A

THIOUREA PHENYLUREA

B

PHENYLPHOSPHORODIAMIDATE

PHENYLPHOSPHOROTRIAMIDATE

on THIOPHOSPHORY L TRIAMIDE

THIOPHOSPHORYL DIAMIDATE

FIG. 4. Various compounds that have been evaluated as urease inhibitors. (A) Substrate analogs; (B) phosphoroamides.

B. COATINGS OR MIXTURES

1. Sulfur-Coated Urea

Urea has been coated with resin (Brown et al., 1966), plastic (Mahendrappa and Salonius, 1974; Beaton et al., 1967), shellac (Reddy and Prasad,

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1979, silica (Savant et al., 1983), and sulfur (Rindt et al., 1968; Savant and De Datta, 1979) and impregnated with petroleum wax (Skogley and King, 1968) in order to retard the dissolution of urea in the soil. Sulfur-coated urea (SCU) is prepared by spraying molten sulfur onto heated urea pellets, which in turn are sprayed with molten wax containing a biocide, and the pellets are subsequently coated with a conditioner which is added to prevent caking of the fertilizer (Blouin et ul., 197 1). Both the wax and the sulfur are necessary to produce a retardant coating; a biocide may be included in the wax coating to prevent degradation of this layer by soil microorganisms (Allen et ul., 197 1;Blouin et al., 197 1). However, the cost effectiveness of the biocide in delaying the release of urea from SCU has been questioned, and its use has been discontinued (Shirley and Meline, 1975). The release of urea from SCU has been postulated to occur by three mechanisms: ( 1) the wax sealant is microbially degraded and absorbed by the adjacent soil; (2) the conversion of polymeric amorphous sulfur to a crystalline structure results in cracks or fissures in the sulfur shell (McClellan and Scheib, 1975), thereby opening channels through the sulfur coat which allow the release of urea (Lunt, 1968); and (3) the biodegradation of both the wax sealant and the sulfur coating releases urea from SCU (Jarrell and Boersma, 1979,1980). Temperaturehas the most pronounced effect on the dissolution of SCU (Hashimoto and Mullins, 1979; Jarrell and Boersma, 1979, 1980). Hashimoto and Mullins ( 1979) observed a two- to threefold increase in the dissolution rate of various SCU preparations when the temperature was increased from 8 to 35°C. The dissolution of SCU has been shown to be more rapid when incorporated in soil, compared to either in solution (Lunt, 1969) or on the soil surface (Prasad, 1976b). The increased dissolution rate of SCU in soil is consistent with the postulated role of microorganisms in breaking down the external coat of SCU. Giordano and Mortvedt (1970) found that SCU released urea very slowly in flooded soil. They attributed the slow release of urea to the formation of a FeS coating around the granules. However, this phenomenon has not been observed by other investigators. The accepted method of determiningthe release characteristicsof commercial SCU products is to measure the amount of urea released from SCU granules into water at 37.8"Cafter 7 days immersion (Hashimoto and Mullins, 1979). SCU has a number of advantages over soluble fertilizers. (1) By releasing urea slowly into the soil solution, leaching and volatilization losses are reduced. (2) In contrast to ammonium salt fertilizers, SCU does not result in high rates of N assimilation by the plants following fertilizer application and a subsequent N deficiency in the soil for the later stages of plant growth; rather it results in the gradual release of N throughout the plant growth cycle (Lunt, 1971). The disadvantages of SCU are (1) higher cost than soluble

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nitrogen fertilizers, and (2) soil acidification due to the formation of H,SO4 resulting from the metabolism of sulfur by the sulfur-oxidizing organisms. SCU has been shown to be an effective nitrogen source when applied to turfgrass and forage grass(Dunavin, 1975;Hummel and Waddington, 1984; Mays and Terman, 1969; Volk and Horn, 1975).As fertilizers are generally surface applied in such systems the potential for volatile nitrogen losses are much greater than the losses observed when fertilizers can be incorporated into the soil (Terman, 1979). In laboratory studies, lower ammonia losses from SCU placed on the soil surface (0 to 7% of applied N) have been measured compared to ammonium sulfate (6.6 to 16.7%)and urea (8.4 to 20%) (Prasad, 1976a). SCU was superior to a single ammonium nitrate application, and was equivalent to three split ammonium nitrate applications for forage grasses (Dunavin, 1975; Mays and Terman, 1969). Single applications of SCU have been used in place of three split applications of other nitrogen fertilizers for corn (Dalal, 1974, 1975b; Lunt, 1969), sugarcane (Dalal and Prasad, 1975), and citrus trees (Puchades et al., 1984). Sanchez et al. (1973) found SCU to be superior to urea and ammonium nitrate for fertilization of rice. They assumed the major nitrogen losses with urea and NH4N03resulted from leaching and denitrification. Flinn et al. ( 1984) compared the responses of irrigated rice in the tropics at 17 sites to prilled urea, urea supergranules, and SCU. They found urea supergranules and SCU to be economically viable alternatives to prilled urea. Addiscott and Cox (1976) found SCU and urea to be inferior to ammonium sulfate when they were applied during the fall, and Sander and Moline (1980) found SCU to be inferior to urea for imgated corn on a sandy soil. Other workers have found SCU to be equivalent to other nitrogen sources for forage production (Lamond et al., 1979 Ludwick et al., 1978). In a greenhouse experiment Oertli (1975) determined nitrogen uptake for sunflowers and tomatoes in sand under conditions of intense leaching, and found that 50% of the nitrogen in SCU was assimilated by the plants. Under comparable conditions only 1-4% of the nitrogen in prilled urea was taken up by the plants. 2. Urea-Aldehyde Polymers Another slow-releaseurea fertilizer is produced by polymerizationor condensation of urea with an aldehyde. Crotonylidenediurea and isobutylidenediurea are two slow-releasenitrogen sources produced by the condensation of two urea molecules and two aldehyde molecules (Fig. 5). The most common aldehyde used to produce this class of slow-release fertilizer is formaldehyde, which is polymerized with urea to form ureaformaldehyde. Com-

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227

( H2N-C-NH-CH2-NH-C-NH2), !? f? UREAFORMALDEHYDE POLYMER

CROTONYLIDENEDIUREA

0

0

ISOBUTY L I DENEDIUREA

FIG.5. Urea-aldehyde condensationproducts that have been used as slow-releasenitrogen fertilizers.

mercial ureaformaldehydes consist of a mixture of polymers and can be classified into three fractions based on their solubility in water (Hays and Hayden, 1966; Kaempffeand Lunt, 1967). Fraction I is cold-water-soluble nitrogen which is a mixture of urea, methylenediurea, and dimethylenetriurea. Fraction I1 is hot-water-solublenitrogen (excluding the cold-watersoluble nitrogen) and is a mixture of trimethylenetetraureaand tetramethylenepentaurea. Fraction 111is composed of the water-insoluble nitrogen and is a mixture of pentamethylenehexaurea and other long-chain polymers. An activity index has been proposed as a measure of the amount of slow-release nitrogen in ureaformaldehyde products (Hays et al., 1965; Kaempffe and Lunt, 1967. The activity index (AI) is defined by the following relationship: A1 =

Cold-water-insoluble N - Hot-water-insoluble N Cold-water-insolubleN

x

100

Plant assimilation of nitrogen has correlated well with the activity indexes of various ureaformaldehyde preparations (Hagin and Cohen, 1976). The decomposition of ureaformaldehyde in soil is a first-order reaction, and the rate increases with an increase of temperature up to 24°C (Hadas and Kafiafi, 1974). The low temperature limit for the decomposition of ureaformaldehyde in soil is 15 "C (Basaraba, 1964). Katz and Fassbender ( 1966) measured the biodegradation of ureaformaldehyde by a mixed cul-

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ture of microorganisms in a Warburg respirometer and found an inverse relationship between polymer length and the degradation rate. Hadas et a/. (1975) found the degradation rate of ureaformaldehyde in the field to be 10-fold higher than the degradation rate measured in the laboratory. The major advantages of ureaformaldehyde are (1) uniform release of nitrogen during the growing season, and (2) residual soil nitrogen remaining for the following year (Balba and Sheta, 1973; Waddington et al., 1976). Combinations of ureaformaldehyde and occluded herbicide have been formulated to produce a slow-release herbicide and nitrogen source (Hewson and Hays, 1972). Beaton et al. (1967) compared a number of slow-release nitrogen sources for orchard grass and found plastic (dicyclopentadiene copolymer)-coatedurea to be the most effectiveand ureaformaldehydeto be the least effective. Ammonium and nitrate sources of fertilizer nitrogen have been shown to be superior to ureaformaldehyde for small-grain production in semiarid regions (Alessi and Power, 1973). Isobutylidenediurea(IBDU) is an effective slow-release fertilizer for turfgrass (Volk and Horn, 1975)and has reduced nitrogen losses under alternating wet and dry soil conditions(Prasad and Rajale, 1972). Mazur and White (1983) found IBDU to be superior to sulfur-coated urea in field studies. Mechanical breakage of SCU was the major factor adversely affecting its slow-releasecharacteristics(Mazur and White, 1983). Initially,the release of nitrogen from IBDU is very slow, followed by a period of very rapid release of nitrogen (Volk and Horn, 1975). Crotonylidenediurea (CDU) has been successfullyused for the fertilizationof peach trees (Uchiyama, 1973).However, ryegrass grown in pots took up more nitrogen in a 16-weekperiod from ammonium sulfatethan from CDU during a 50-week period (Gasser, 1970). The initial decomposition products of CDU are urea and 2-0x04-methyl-6hydroxyhexahydropyrimidine (Ishibashi et al., 1969).The decomposition of CDU occurs both by chemical and microbiological means. 3. Mixtures of Urea with Other Chemicals

In order to reduce the volatilization of ammonia, urea has been mixed with other chemicals such as ammonium polyphosphate (Murdock and Frye, 1985) and phosphoric (Bremner and Douglas, 1971b), boric (Nommik, 1973a), and nitric (Gasser and Penny, 1967) acids. Nommik (1973a) reported that the incorporationof 5% H3B03in large pellets ofurea reduced ammonia losses using surface-applied urea due to the inhibition of urease by the borate anion (Mulvaney and Bremner, 198l), as well as by the reduction of soil pH. Gasser and Penny (1967) found urea phosphate to be superior to urea nitrate or ammonium nitrate as nitrogen sources for grass and barley.

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229

However, Stumpe et al. (1984) found urea phosphate to be ineffective in reducing ammonia losses on calcareous soils due to the precipitation of the phosphate anions by indigenous soil calcium, thereby increasing the soil pH and resulting in increased loss of NH4 by volatilization. Urea- thiourea mixtures (Urea :thiourea 2 : 1 w/w) placed in either bands or pellets have been used to retard the transformations of urea in the soil (Malhi and Nyborg, 1979, 1984).Thiourea is both a weak urease and nitrification inhibitor; alone it has been utilized as a slowly availablesourceof both sulfur and nitrogen. Another approach has been to coapply calcium or magnesium salts with urea in order to decrease ammonia losses (Fenn and Kissel, 1973). The precipitation of calcium carbonate alters the equilibrium between ammonium carbonate, and ammonia and carbon dioxide thus retard ammonia losses (Fig. 6). Fenn et al. ( 198la,b, 1982b) found a range of 0.25 to 1.O for the ratio Ca2+eq to N to be satisfactory for the reduction of ammonia losses from surface-applied urea. On calcareous soils potassium or sodium salts have yielded comparable results (Fenn et al., 1982a;Rappaport and Axley, 1984).The potassium or sodium ions apparently displace calcium ions from the cation exchange complex, thereby producing a net effect similar to the addition of calcium salts. C. FERTILIZER PLACEMENT

I . Banding The placement of urea in a band results in a region ofhigh pH and high salt concentration within the soil which inhibits nitrification (Wetselaar et al., 1972).Banded urea is in contact with less soil than broadcast or incorporated urea, and thus N immobilization is reduced (Tomar and Soper, 1981). Banded urea was found to be superior to incorporated urea for barley when the fertilizers were applied during the fall (Mahli and Nyborg, 1985). Fall application of banded urea resulted in lower losses of nitrogen due to deni-

FIG. 6. Effect of calcium salts on ammonium evolution. (1) Hydrolysis of ammonium carbonate to produce volatile ammonia. (2) Reaction of calcium chloride with ammonium carbonate to suppress ammonia volatilization.

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W. D. GOULD ET AL.

trification; this can probably be attributed to a reduced rate of nitrification because of the inhibitory effect of the urea. In contrast, no difference in N loss between incorporatedand banded urea was observed when the fertilizers were applied in the spring (Mahli and Nyborg, 1985).Banded urea was equal to or better than urea applied by other placement techniques for rice (Cao et al., 1984b; Rao et al., 1985). Urea banded twice (2 and 16 days postemergence) was superior to incorporated, single-banded, and surface-applied urea for dryland sorghum (Moraghan et al., 1984). One of the major disadvantagesof banding is the inhibition of root growth in the region surrounding the band (Creamer and Fox, 1980). Both side banding and seed application of urea -ammonium phosphate fertilizer caused delayed germination and a reduced stand of corn seedlings (Liegel and Walsh, 1975a). The same effect was not observed with fertilizers not containing urea (Liegel and Walsh, 1975a).Liegel and Walsh ( 1975b)measured high ammonium ion concentrations and high pH values in the soil surroundingthe banded urea - ammonium phosphate and suggested that the presence of free ammonia was responsible for the observed plant toxicity.

2. Large Pellets Incorporation of urea in large pellets or granulesis an alternativemeans of retarding nitrogen transformations,by concentrating urea in the soil (Nommik, 1973b). Pellets have an additional advantage in that they can easily be formulated as mixtures of urea with other chemicals (Nommik, 1973a). Large urea pellets (2.0 to 2.2 g) had lower initial volatile nitrogen losses than smaller pellets or prilled urea when these fertilizers were applied to the surface of a forest soil, but cumulative ammonia losses after 20 to 30 days were equivalent for all particle sizes (Nommik, 1976). Nyborg and Malhi ( 1979) found fall-applied pelleted urea to be equivalent to spring-applied urea, and to be superior to fall-applied banded urea for barley. However, Watkins et al. (1972) found that pelleted urea was equivalent to prilled urea. Deep placement of urea supergranuleshas shown promise for the fertilization of flooded rice (Craswell et al., 1981, 1985; Prasad et al., 1984). Deep placement of large urea pellets resulted in higher recoveries (50- 6 1%) of the applied nitrogen by rice than when urea was applied in split treatments (25-34% recovery) (Savant et al., 1982). The advantages ofthe deep placement of urea pellets with rice are (1) reduced diffusion of urea into the floodwater, thereby reducing the potential for ammonia loss and denitrification (Cao et al., 1984a; Eriksen et al., 1985); and (2) proliferation of roots through the zone of high ammonium ion concentrations at a later stage of growth when nitrogen requirementsare higher (Savant and De Datta, 1980).

UREA TRANSFORMATIONS AND FERTILIZER EFFICIENCY

23 1

However, in permeable soils with high leaching rates, the deep placement of large urea granules resulted in higher leaching losses of nitrogen than was observed with other methods of application (Vlek et al., 1980a).

V. SUMMARY A. FUTURE TRENDS IN THE USE OF UREA FERTILIZERS

Although the use of nitrogen fertilizers has steadily increased during the past 20 years, the greatest percentage increase has been in the use of urea. Urea utilization is expected to increase, particularly in the developingcountries. Urea currently constitutes 80% of the nitrogenousfertilizer that is used on rice (Vlek and Craswell, 1981). High nitrogen losses have restricted the use of urea on some crops but this may change as new technologiesdevelop. Slow-release urea preparations may find widespread acceptance for the fertilization of forages, grasslands, and forests. B. FUTURE DEVELOPMENTS IN IMPROVING THE EFFICIENCY OF UREAFERTILIZER

Under most conditions urea is equivalent to other nitrogenous fertilizers, but under certain conditions conventional practices must be modified for urea to be used successfully. Coating urea with sulfur or adding urease inhibitors to retard the hydrolysis rate of urea appear to be the most effective means of preventing ammonia losses. On soils where extensive leaching occurs, sulfur-coated urea might be more effective than urea containing a urease inhibitor, due to the high mobility of urea. Fall application of nitrogenous fertilizers can result in immobilization,leaching, and denitrification. Placement (i.e., banding or large granules of urea) may be appropriate for fall fertilization and also for flooded rice crops. The recently discovered class of urease inhibitors, the phosphoroamides, are the first group of inhibitors that are sufficientlyactive at low concentrations to be agronomically feasible for field application. One can anticipate that more effective compounds in this class of inhibitors will be developed in the future. Further research with respect to urea fertilizers is required in the following aspects: (1) the measurement of urea transformations in the field under agronomically realistic conditions, (2) improved understanding of urea transformations in no-till or minimum till soils, (3) the effect of placement and time of application on mobility and uptake of nitrogen from urea, and (4) the development of improved urease inhibitors.

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W. D. GOULD ET AL. ACKNOWLEDGMENTS

The authors express gratitude to Mr. G. H. Bishop of the Canadian Fertilizer Institute and Mr. G. M.Gould of Shemtt Gordon Mines for data concerning world consumption of nitrogenous fertilizers. A critical review of the manuscript by Dr. L. L. Hendrickson is also appreciated.

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Broadbent, F. E.,Nakashima, T., and Chang, G. Y . 1985. SoilSci. Soc. Am. J. 49,348-351. Brown, M. J., Luebs, R. E., and Pratt, P. F. 1966. Agron. J. 58, 175- 178. Burge, W. D., and Broadbent, F. E. 1961. Soil Sci. Soc. Am. Proc. 25, 199-204. Bums, R. G., El-Sayed, M. H., and McLaren, A. D. 1972a. Soil Biol. Biochem. 4, 107- 108. Bums, R. G., Pukite, A. H., and McLaren, A. D. 1972b. SoilSci. Soc.Am. Proc. 36,308-3 1 1. Bymes, B. H., Savant, N. K., and Craswell, E. T. 1983. SoilSci. Soc.Am. J. 47,270-274. Campbell, C. A., Meyers, R. J. K., Catchpoole, V. R., Vallis, I., and Weier, K. L. 1984.Allsf.J. Soil Res. 22, 433-441. Cao, Z.-H., De Datta, S. K., and Fillery, I. R. P. 1984a. Soil Sci. Soc. Am. J. 48, 196-203. Cao, Z.-H., De Datta, S. K., and Fillery, I. R. P. 1984b. Soil Sci. Soc. Am. J. 48,203-208. Ceccanti, B., Nannipieri, P., Cervelli, S., and Sequi, P. 1978. Soil Biol. Biochem. 10, 39-45. Cecil, R., and McPhee, J. R. 1959. Adv. Profein Chem. 14,255-389. Cerevelli, S., Nannipieri, P., Giovannini, G., and Pema, A. 1975. Pestic. Biochem. Physiol. 5, 221 -225. Cervelli, S., Nannipieri, P., Giovannini G., and Perna, A. 1976. WeedRes. 16, 365-368. Chapman, H. D., and Liebig, G. F. 1952. SoilSci. Soc.Am. Proc. 16,276-282. Chin, W. T., and Kroontje, W.1962. SoilSci. Soc. Am. Proc. 26,479-481. Christianson, C. B., and Cho, C. M. 1983. SoilSci. Soc. Am. J. 41,38-42. Christianson, C. B.,Hedlin, R. A., and Cho, C. M. 1979. Can. J. Soil Sci. 59, 147- 154. Church, R. J. 1964. In “Fertilizer Nitrogen. ItsChemistry and Technology” (V. Sauchelli,ed.), ACS Monogr. Ser., pp. 247-279. Van Nostrand-Reinhold, Rinceton, New Jersey. Court, M. N., Stephen, R. C., and Waid, J. S. 1962. Nufure(London) 194, 1263-1265. Court, M. N., Stephen, R. C., and Waid, J. S. 1964a. J. SoilSci. 15,42-48. Court, M. N., Stephen, R. C., and Waid, J. S. 1964b. J. SoilSci. 15,49-65. Craig, J. R., and Wollum, A. G., 11. 1982. SoilSci. Soc.Am. J. 46,409-414. Craswell, E. T., De Datta, S. K., Obcemea, W. N., and Hartantyo, M. 1981. Fen. Res. 2, 247 - 259. Craswell,E. T., De Datta, S. K., Weeraratne, C. S., and Vlek, P. L. G. 1985. Ferl. Res. 6,49-63. Craven, J. A., and Kilkenny, J. B. 1974. Proc.-Fert. Soc. 142,39-56. Creamer, F. L., and Fox, R. H. 1980. Soil Sci. Soc.Am. J. 44,296-300. Dalal, R. C. 1974. SoilSci. Soc.Am. Proc.38,970-974. Dalal, R. C. 1975a. Soil Biol. Biochem. 7,5-8. Dalal, R. C. 1975b. SoilSci. Soc.Am. Proc. 39, 1004-1005. Dalal, R. C., and Prasad, M. 1975. J. Agric. Sci. 85,427-433. Delaune, R. D., and Patrick, W. H., Jr. 1970. SoilSci. Soc. Am. Proc. 34,603-607. Dixon, N. E., Gazzola, C., Blakeley, R. L.,and Zemer, B. 1975. J. Am. Chem. Soc.97, 41 3 1-4133. Dixon, N. E., Blakeley, R. L., and Zemer, B. 1980. Can. J. Biochem. 58,469-473. Doran, J. W. 1980a. Soil Sci. Soc. Am. J. 44,518-524. Doran, J. W. 198Ob. SoilSci. Soc. Am. J. 44,765-771. Dunavin, L. S . 1975. Agron. J. 67,415-417. Englestad, 0. P., and Hauck, R. D. 1974. Crops Soils 26, No. 7, I I - 14. Eriksen, A. B., Kjeldby, M., andNilsen, S. 1985. Phnf Soil&l,387-401. Emst, J. W., and Massey, H. F. 1960. Soil Sci. Soc. Am. Proc. 24,87-90. Estermann, E. F., and McLaren, A. D. 1961. Plunf Soil 15,243-260. Farmer, W. J., and Ahlnchs, J. L. 1969. SoilSci. Soc.Am. Proc. 33,254-258. Fenn, L. B., and Kissel, D. E. 1973. SoilSci. Soc. Am. Proc. 37,855-859. Fenn, L. B., Matocha, J. E., and Wu, E. 1981a. SoilSci. Soc.Am. J. 45,883-886. Fenn, L. B., Matocha, J. E., and Wu, E. 198I b. Soil Sci. Soc. Am. J. 45, 1 128- 1 131. Fenn, L. B., Matocha, J. E.,and Wu, E. 1982a. SoilSci. Soc. Am. J. 46,78-81.

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ADVANCES IN AGRONOMY, VOL. 40

LUPIN CROP AS AN ALTERNATIVE SOURCE OF PROTEIN L. Lopez-Betlido and M. Fuentes Departamento de Cultivos Herbeceos Universidad de Cbrdoba, Cbrdoba, Spain

I. INTRODUCTION A. THEROLEOF LEGUMES IN PROTEIN PRODUCTION

The deficiency of protein in the world is one of the major factors in the present-day food crisis. It is also the most outstanding feature in nutritional differences throughout the world. The average protein intake in Europe is 65 g/person-day, while in the poorer countries it is less than 10 g/person-day. In the last few years different theories have arisen over the utilization of plant resources and whether these should be made available directly to humans or channeled through animal production. The extent of human consumption of foods of animal origin is still considered an index of the living standard. Although the biological value of animal protein is clearly superior to that of plant protein, their ratio in human nutrition does not appear to be going to change for the moment. Nevertheless, some scientists warn that in the not too distant future, the populationsin certain parts ofthe world, especially within arid climates, will have to turn even more to plant protein due to the expense and difficulty in obtaining animal protein. The prolonged food concern has acquired a marked structural character, and the growing demand for food has necessitated an increase in food production using all the means and resources possible. Under these circumstances great interest in the large group of cultivated legumes has been revived, and in several countries studies and investigationsto obtain higher yield and better nutritional quality cultivars of legumes have already begun. With the agricultural technical developments of the last decades many of the legume crops cultivated since ancient times have suffered a setback because of low yields and mechanization difficulties.This reduction in cultivated areas has left great tracts of land unused in many areas, or these areas have been turned over to single-crop farming with all the problems this presents. Such cultivation systems also deprive the legumes of one of their 239 Copyight 6 1986 by Academic F'm& lac.

Au IighIa of rcproduetion in any form rcavsd

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most important roles, that of soil improvement. Also, the technical changes brought about by the use of fossil energy has made agriculture in the developed countries highly specialized, and at the same time separated it from nature and made it wasteful of primary products and energy. These agricultural production systems are little adapted to countrieswhich are still developing and may even lead them into a cul-de-sac within the near future. Legumes are a source of cheap proteins which may be used integrally with other foods or alone. Their amino acid composition is rich in lysine but poor in sulfur, which makes them the perfect complement for cereals. Lupin is considered one of the legumes With the greatest future potential because of its high protein content, even in a wild state, and because of its adaptation to poor soils and dry climates. It has been called “the new soya” and in the last few years research to promote its cultivation and to improve its nutritive qualities has increased in Europe, South America, and Australia. This work attempts to present a comprehensivereview ofthis plant and its productive potential.

B. THEORIGIN AND HISTORY OF LUPIN The Lupinusgenus is included among the world‘s prehistoriccrops. Lupin is referred to in the earliest Mediterranean and Andean civilizations. Both the Greeks and Romans have written about its ability to grow in poor soils and to improve them (Gladstones, 1970) The first species cultivated in the old World was L. albus and in pre-Columbian civilizations L. mutabilis. Gross (1982a) pointed out the parallels between these species in that they were used in the same way for the same ends. All wild species of the Lupinus genus contain toxic substances, alkaloids. These were a defense against herbaceous predators but this quality became a defect when lupin was domesticated for consumption. For this reason humans since ancient times have been using debitteringprocesses, i.e, cooking the seed and washing them in water to eliminate the bitter taste of their alkaloids. Belteky et al. (1983), for Old World lupins, and Antunes de Mayolo (1980), for L. mutabilis, have reviewed the history of the crop and human utilization of it down through the centuries. Lupin grain, belonging to the species L. digitatus (L. consentinii),was found by Schweinfurth in an Egyptian grave from the year 2000 BC.Some authors situate the origin of the crop in Egypt even though others believe that it was introduced there in the Greco-Roman period (330 BC). The Greeks called it thermes and in Egypt it was called ternos The Latin name of Lupinus, derived from lupus meaning “wolf,” became generalized in the European languages and was used by Linnaeus in his classification of the group.

LUPIN AS ALTERNATIVE PROTEIN SOURCE

24 1

The earliest referencesto cultivated lupin are found in Hippocrates (430 377 BC)who remarked on its use in human nutrition noting its easy digestibility and nonflatulentqualities. Numerous Roman writers mention lupin in their works: Teofrasto, Cato, Varro, and Columela. Cat0 (234- 149 BC)in his De agricultura liber cited lupin’s important role as a forage plant and Varro (1 16-27 BC) in his work Dere rustica libri mentions it as a green manure plant to improve soils. The doctor Galeno (200 - 130 BC) described methods used by the Romans to debitter lupin: the grain was cooked and left soaking for some time in water. A special container which Cat0 called labrum lupiniarum was used, confirming that the Romans were well aware of the toxic properties in bitter lupins used for human and animal consump tion. Lupin spread out from Egypt and the Roman Empire as far as the southern zones of the Caucasus. It was introduced in France and Spain by the Romans who used it as green manure for vineyards. The Spaniard Alonso de Herrera in his work Agricultura General ( 15 13) described in detail lupin in Spain, where it was used mainly as green manure. The author referred to a series of crop practices which are curious because of their actuality; among these practices he mentions the convenienceof early sowings, soil preparation, the preference of the plant for loose sandy soils, and the advantages of shallow sowing. He also referred to the plant’s medicinal uses, to debittering by means of soaking in warm water, and even to the insecticide role of the water used for debittering. In the New World, especially Peru, the references to L. mutubilis are also very old. “Tarwi” seeds have been found in Nazca as offeringsfor the dead in tombs over 2000 years old. Las Relaciones Geograjcas de las Indias cited the consumption, in pre-Columbian times, of lupin in the form of tender grain, which after being boiled and dried was called kirku. Possibly the steps followed may have been the actual process of boiling and washing in water to eliminate alkaloids. No data exist which establishes the origin of the L. mutabilis crop in South America due to the absence of writing in pre-Columbian cultures. However, there does exist archeological information, folklore, and custom. The Andean peoples have always recognised the basic nutritional and medicinal properties of “tarwi” (Andean lupin), associating its consumption with religious rites and festivals. There are references to its fertility properties and the curative role of its alkaloids in cardiac diseases, rheumatism, malaria, and infections of intestinal parasites and livestock parasites. With the Spanish domination, the indigenouspopulation adopted Spanish food and habits, as the conquistadores disdained and disregarded the Inca dietetics simply because they could not understand them. This resulted in the endemic malnutrition which has lasted practically up to the present day. In Europe in 1783, on the orders ofFrederick I1 o f h s s i a , lupin was sown

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L. LOPEZ-BELLIDO AND M. FWENTES

in numerous regions of Germany. However, the long-cycle lupins imported from Italy could not mature easily, and were used only as green manure for the poor sandy soil of East Germany as well as for sheep forage. Borchard in 188 1 carried out trials on L. luteus to select shorter cycle cultivars, obtaining excellent results in grain production. Within a short time the success of L. luteus resulted in its displacingL. albus, and based on these first experiments it quickly spread all over Europe. By the end of the nineteenth century interest in lupin had diminished,due, without doubt, to the toxic action of its alkaloids which made the utilization of its grain difficult. However, cultivation as a green manure crop continued. With the First World War, interest revived. Research work on selection began in Holland, Sweden, Poland, South Africa, the United States, Australia, New Zealand, and Germany. It was in Germany where, for the first time, a nonshattering line of L. luteus was found and later a mutant with low alkaloid content. At present lupin is cultivated in most parts of the world. The three species from the Mediterranean - African area L. albus, L. angustifolius, and L. luteus) and the one from South America (L. mutabilis) have reached full crop status, while L. consentinii,which also has necessary requirements to be considered a crop plant, is just in its beginnings.

II. BOTANY AND ECOLOGY OF LUPIN A. GEOGRAPHIC DISTRIBUTION OF LUPINSPECIES

The wild speciesof Lupinus are distributed in two large areas: the Mediterranean and the Western Hemisphere. The Mediterranean zone ranges from southern Europe to the highlands in northern and eastern Africa. The range in the Americas includes the western part of North and South America and excludes the tropical lowlands and the Amazonian basin (Hackbarth, 196 1b). According to Gladstones (1984) and Plitmann and Heyn ( 1984) only 12 species are acknowledged as native to the Old World, among which are the cultivated species of L. albus, L. luteus, and L. Angustifolius (Table I). The rest are native to the New World. Although the numbers are not precise there are calculated to be between 300 and 400 species (Dunn, 1955; Bruecher, 1968, 1970; Planchuelo, 1982). Planchuelo (1984) stated that the South American species are distributed in two separate geographical regions, the Atlantic and Andean. In the Atlantic region (eastern Brazil, Uruguay, Paraguay, central and eastern Argentina) the perennial species with simple or compound leaves which grow in open areas, mountainsides, and riverbanks

LUPIN AS ALTERNATIVE PROTEIN SOURCE

243

Table I

Taxonomy and Natural Distribution of Old World Lupins‘ Section Albus Angustifolius Luteus

Micranthus Rough-seeded

Chromosomes (2n)

Taxa L. albus var. albus var. graecus L. angustfolius L. luteus

Natural distribution

50 40 52

Cultivated S. Balkans, W. Turkey Pan-Mediterranean

SSQ. /UteUS

W. Mediterranean

SSQ.orientalis

E. Mediterranean

L. hispanicus SSQ. hispanicus SSQ.bicolor L. micranthus L. pilosus L. palaestinus L. consentinii L. atlanticus L. digitatus L. princei L. somaliensis

52 42 42 32 38 36 ? ?

Pan-Mediterranean E. Mediterranean S.E. Mediterranean W. Mediterranean S. Morocco Egypt, C. and W. Sahara E. Africa N. Somalia

From Gladstones ( 1984).

are found in abundance. The Andean region covers the mountains and mountainsides of the Andes from Venezuela, Colombia, Ecuador, Peru, Bolivia, Chile, and northwest Argentina to the plains of Patagonia. These species include perennial and annual shrubs, the latter forming a heterogeneous group. Many of these species are still under study. Lupinus mutabilis is the only cultivated species. Some species, according to Planchuelo( 1984), have been cited as native to South America, but were actually first introduced as cultivated crops and later “rediscovered” as wild. Such is the case of L. polyphyllus and L. Arboreus, North American species which were introduced in southwestern Argentina. B. TAXONOMY

Tournefort in 1694 used the name Lupinus for the genus (Planchuelo, 1982). Later in 1753 Linnaeus included it as the name of the genus in his book Species plantarum, and described six species (L. perennis, L. albus, L.

varius, L. hirsutus, L. angustijolius, and L. luteus).

244

L. LOPEZBELLIDO AND M. FUENTES

The number of known specieswas rapidly increasedduring the eighteenth and nineteenth centuries by new finds in North, Center, and South America (Planchuelo, 1982). 1. The Old World Lupins The Old World species have been separated into five groups or sections (Albus, Angustifolius, Luteus, Micranthus, and Rough-seeded)by Nowacki and Prus-Glowacki ( 197 1) on a basis of serological grounds, morphological characters, and crossability (Table I). Plitmann and Heyn (1984) classified the species according to the seed coat texture into two distinct subgeneric groups: Section Lupinus and Section Scabrispermaesect. nov., which correspond to the rough-seeded group. For Plitmann and Heyn ( 1984) the principal taxonomic groupings should be biological species isolated from one another by different chromosome numbers and biological species with a low genetic polymorphism in general. However, several characters, particularly vegetative ones, display continuous variability within species and populations. This is due to polygeniccharacters,phenotypic plasticity, or disruptive differentiation, which may be used in breeding. Gladstones ( 1984) has completely revised the actual state of taxonomy of Old World lupins starting from the five native sections in the Mediterranean/African region (Table I). The albus section comprises strictly only one species; the described species L. graecus, L.jugoslavicus, and L. vavilovi are wild ancestors of L. albus. Crossing experiments by Kazimierski (1960, 196 1,1963,1964) showed a complete lack of genetic barriers between these and L. albus, and also showed that the main differences which have arisen from domestication are governed by only a few genes. Such differences do not indicate speciation or even subspeciationin the true genetic or botanical sense; therefore the wild forms have been integrated as var. graecus. An Angustifolius section also only contains one species although a number of synonyms in both old and recent literature have given rise to taxonomic confusion. However, Gladstones ( 1984) affirmed after exhaustive research and observation that neither the lack of genetic barriers nor any of the morphological and physiological differences forms a sufficient basis for taxonomic distinctions. The Luteus section contains two species, L. luteus and L. hispanicus, which both have an equal number of chromosomes. Their main center of distribution is the Iberian Peninsula. Kazimierski ( 1980), contrary to Gladstones (1984), maintained that L. rothmaleri is a species distinct from L. hispanicus. The species L. luteus, rare in a wild state, is confined to highrainfall areas of Portugal and northwest Spain and to a separate population in coastal Israel. The latter population differs morphologically, biochemi-

LUPIN AS ALTERNATIVE PROTEIN SOURCE

245

cally, and cytologically from those of the western Mediterranean, producing partial sterility on crossing (Kazimierski and Kazimierska, 1975; Kazimierski, 1980). Thus, the Israeli form is described as a separate subspecies, ssp. orientalis instead of ssp. luteus. The species L. hispanicus is very common in western Spain and northern Portugal but its infraspecifictaxonomy is more controversial. Gladstones ( 1984) maintained that the two distinct forms of this species which occur in the Iberian Peninsula are two separate subspecies: ssp. hispanicusand ssp. bicolor. Although difficult, L. luteus does cross with ssp. bicolor and there is enough fertility to allow artificial introgression of genes from one species to another. The same occurs with ssp. hispanicus. Recently, Swiecicki (1985) has obtained a fertile hybrid of L. hispanicus ssp. hispanicus X L. luteus named Lupinus eurohybridus Swiec. The Micranthus section is little known and comprises only one species, L. micranthus, whose chromosome number after much uncertainty has been established as 2n = 52 (Pazy et al., 1977). This chromosome number, together with growth habit and seed form, suggests a possible affinity with L. luteus; however, the serological evidence shows that it should continue to be regarded as distinct. Further research is needed. The Rough-seeded section consists of a wide group, collected together based on serological and morphological characteristics despite diversity in chromosome numbers. Among these is the new species, L. atlanticus, found in the High Atlas foothills and Anti-Atlas region of southern Morocco (Gladstones, 1974). It appears to be both cytologically and morphologically an intermediate species between L. consentinii and L. pilosus, and therefore could be used as a genetic bridge between them. The other species of the group worth mentioning because of its interesting agriculture potential is L. consentinii, which appears in older literature under misnomers such as L. varius and L. digitatus. Although morphological differences exist due to distinct habitats (Iberian Peninsula and Morocco) the species is essentially homogeneous, which implies that both populations have been genetically isolated for some time (Gladstones, 1974). In summary,limited information on the better studied rough-seeded lupins along with their morphological similarities indicates a close relationship among them. According to Gladstones ( 1984) their characteristics and distributions suggest that they are relics of a possibly much larger speciesgroup,centered in North Africa, when the climate was much wetter than now. 2. The New World Lupins The first complete review of the New World lupins was carried out by C. P. Smith in his series Species lupinorurn published in 1938- 1945 (Planchuelo, 1984). In his work Smith described hundreds of new species based only on superficial morphological characteristics, and many of his taxons are now

246

L. LOPEZ-BELLIDO AND M. FUENTES

considered as synonyms. More recently Dunn and collaborators, using the more accurate criteria of biosystematic, chemotaxonomic, and cytogenetic studies, have revised many of the American species, partially resolving the chaotic nomenclature state of the genus (Dunn, 1955, 1956, 1971; Schaller, 1977; Planchuelo, 1978; Dunn and Planchuelo, 1980; Planchuelo and Dunn, 1980; Planchuelo, 1984). The number of chromosomes of the American lupins, distributed from the Andes to the Arctic, is 24, 36,48, and 96, constituting an allopolyploid series of multiple levels, triploid, tetraploid, and octoploid, with a basic number X = 6 (Bruecher, 1975; Dunn, 1984). This has given rise, from an ecological standpoint, to a wide genetic flexibility that has enabled these species to inhabit not only the high Andes and the mountains of western America but also coastal and desert regions. According to Nowacki and Prus-Glowacki ( 1971) the American lupin species have a closer cytogenetic relationshipand are more similar to one another than to the species from the Old World. Lupinus mutabilis or Andean lupin (2n = 48) is practically the only cultivated species in the New World, domesticated in the pre-Columbian age. The first description was made by Sweet in 1825, but at present, confusion exists with respect to its exact taxonomic definition (Gross, 1982a). One of the causes of this confusion is that until now no wild form of the species has been found, although Blanco (1984) cited finds of wild material in Peru (the area bordering Ecuador and Bolivia),where the largest variabilitiesare found and where he situates the center of domestication. According to Gross (1982a) there are two subspecies of L. mutabilis in Peru, separated geographically along the 10.5 latitude south. In the north of Peru the species presents a greater vegetativedevelopment and late maturity, the leaves are narrower, and the seed is almost round. In the south the plants are smaller and mature early, the leaves are wider, and the seeds are flatter and more oval with a greater variety of color. Curiously, the genetic difference of the two subspecies corresponds to a linguistic difference, namely “chocho” in the north and “tarhui” in the south. There exist different hypotheses over the nomenclature ofL. mutabilis due to the enormous genetic variety of the species, suggesting a need for a more precise taxonomic definition of this plant (Gross, 1982a). O

C. GROWTH AND PHYSIOLOGY 1. Growth Pattern

The growth pattern of lupin can be divided into three stages: sowing to beginning flowering, flowering, and final flowering to maturing. The first stage includesemergence and floral initiation, the second includes flowering

LUPIN AS ALTERNATIVE PROTEIN SOURCE

247

on the main stem and branches (ramificationorders), and the third includes pod growth and seed filling. There is wide variability in the duration of these phases depending on the ecotype and climatic environment; this variability has been used as a basis for plant selection. The duration of the sowing-emergence period is correlated inversely with temperature (Famngton, 1974; Reeves et al., 1977; Garside, 1979) and varies little among the cultivated species, although according to Famngton 1974), Garside (1979), and Fuentes (1985) L. luteus generally presents a slower germination. The influence of vernalization and photoperiod on floral initiation in various cultivated species has been known for some time (Hackbarth, 1936; Plarre and Vettel, 1958; Hill, 1965; Kubok, 1965). Lupin is a plant which needs vernalization and is sensitive to photoperiod (long day), but there are important inter- and intraspecific differences. Gladstones and Hill ( 1969) and Rahman and Gladstones (1 972, 1974) have studied both these factors along with the influence of temperature superior to that of vernalization in four cultivated lupin species: L. angustifolius, L. albus, L. luteus, and L. consentinii. In L. angustifolius floral initiation is controlled mainly by vernalization, photoperiod having little influence, whereas the species L. consentinii needs less cold but is more sensitive to photoperiod. In both species there are isogenic lines with and without vernalization requirements. The species most sensitive to photoperiod is L. luteus. According to Goldstein (1984) there is a wide range of vernalization necessities in the distinct types of L. albus, from winter types with high needs, to those of spring dwarftypes with little sensitivity. There have been few studies carried out on L. mutabilis in this respect; Gross (1982a) stated that there is no clear answer whether vernalization or photoperiod affects this species. Gladstones ( 1970, 1984), Perry and Poole ( 1973, Reeves et al. (1977), Sylvester-Bradley (1980), and Williams ( 1982)have underlined the agronomic inconveniencesof susceptibility of lupin to vernalization, which makes flowering dates erratic and influences duration of flowering. To create cultivars which are less sensitive to vernalization is a principal breeding objective. Once vernalization has occurred for those cultivars which are sensitiveto it, the higher temperatures (within an optimum range) accelerate floral initiation (Perry and Poole, 1975; Reeves et al., 1977). The duration of floral initiation depends fundamentally on temperature, not on vernalization or photoperiod (Rahman and Gladstones, 1973; Perry and Poole, 1975; Reeves et al., 1977). After flowering on the main stem the successive ramification orders begin to flower until the last inflorescence is formed. Flowering on the main axis is long-lasting but it becomes progressively shorter on the successive branching orders, possibly due to higher temperatures(Greenwood et al., 1975).This growth pattern makes the dura-

248

L. LOPEZBELLIDO AND M. FUENTES

tion of flowering very variable depending on the cultivar and environmental conditions. In autumn and winter sowings Perry and Poole (1975) have obtained a longer floweringperiod, which increasesgrain yield due to greater pod setting. Various factors have been cited for flower finishing, such as temperature (Garside, 1979), greater radiation (Perry and Poole, 1975), and photoperiod (Reeves et al., 1977), but it appears that moisture stress may have the greatest influence (Greenwood et al., 1975;Perry and Poole, 1975; Famngton, 1976; Fuentes, 1985). A practical form of extending flowering may be earlier sowing and the utilization of cultivars whose vernalization requirements are low or nonexistent. In temperate zones with sufficient rainfall, flowering tends to continue too long, preventing maturation (Garside, 1979; Shutov, 1980; Williams, 1982; Bromberek et al., 1984b; Gladstones, 1984; Mikolajczyk et al., 1984a; Vavilov and Gataulina, 1984). Early-flowering cultivars with little lateral branching must be obtained for these areas. Greenwood et al. ( 1975),Perry and Poole ( 1973, and Famngton ( 1976) have confirmed that the end of flowering is followed by a rapid and progressive leaf drop and plant senescence, simultaneously producing seed filling and later seed maturity.

2. Dry Matter Accumulation and dry matter distributionhave been studied in Australia, New Zealand, the USSR and Spain, mostly in L. albus and L. angustifolius and to a lesser degree in L.luteusand L. mutabilis.These four species follow a similar growth pattern although L. mutabilis, which was studied in Spain and not in its native region, differs from the other species in its behavior from floweringto maturation. The growth rate in lupin is slow from the beginning of the vegetative stage until week 7 - 13depending on whether it is a spring or autumn sowing (Greenwood et al., 1975; Perry, 1975; Herbert, 1977a; Fuentes, 1985). Perry (1975) suggested that this is due to low temperatures and Greenwood et al. ( 1975)also attributed this low growth rate to a lack of nitrogen fixation. According to Perry (1975) and Fuentes (1985) less than 50% of total dry weight is accumulated during this period. Simultaneously with inflorescence on the main axis, growth rate increases and successive ramification orders develop. Greenwood et al. (1975) confirmed that in L. angustifuliusthe emergence of inflorescence in each branching order coincides with flowering on the order anterior. During this period pod growth is still very slow. After leaf drop there is a stabilization and even a decrease in dry matter in both stems and branches; 2 or 3 weeks before, the pod increases its growth rate and reaches maximum dry weight simultaneously with the stems. This moment generally coincideswith the maximum dry weight total

LUPIN AS ALTERNATIVE PROTEIN SOURCE

249

of the plant some 4 - 6 weeks before maturation. From this point seed growth is increased simultaneously in all ramification orders (Greenwood et al., 1975; Perry, 1975; Famngton, 1976; Lemaire and Poulain, 1984; Fuentes, 1985). Total dry weight production can obtain a wide range of values depending on environmentalconditions (Table 11).There are no clear differences in dry weight production among the species; however, according to Farrington ( 1974) and Vavilov and Gataulina ( 1984))long-cycle cultivars have greater potential for dry matter production. Among the factors affecting dry matter accumulation are planting time, plant density, and water stress. Famngton (1974), Perry (1979, Withers et al. ( 1976),Hill et al. ( 1977),and Fuentes ( 1985)all agreed that early autumn and spring sowings produce a greater dry weight accumulation as well as increased ramification and pod formation. Withers (1975, 1984), Herbert (1977a), Herbert and Hill (1978), and Fuentes (1985) have proved that increased plant density, while causing less lateral branching, increases total dry weight per unit area up to a determined density, after which there are no differences.This initial density depends on the species and lessens according to more favorable growing conditions. Investigations by Withers (1979b)in L. albus have shown that water stress during the beginning of flowering reduces stem and leaf growth and total plant weight. If, however, this stressis corrected, normal growth rate is recovered in young leaves but the reaction is much slower in the stems. Water stress also diminishes the number of flowers and pods on lateral orders and subsequent orders, while at the same time stimulating the growth of the already formed pods, which resume normal growth once the water deficit disappears. There is little information on lupin growth indices. The leaf area index ( LAI) has been the most frequently determined, reaching maximum average Table I1

Dry Matter Production in Cultivated Lupin Dry matter (13/m2)

References

L. albus

565 - I865

L. angustqolius

249- 1625

L. luteus L. rnufabilis

348- 1900 252-544

Herbert (1977a); Hill et al. (1977); Vavilov and Gataulina (1982, 1984); Goldstein (1984); Fuentes (1985) Farrington (1974, 1976); Greenwood ef al. (1975); Perry (1975); Hill ef al.(1977); Herbert and Hill (1978); Bishop ef al. ( 1984) Farrington ( 1974); Fuentes ( 1985) Hill ef al. (1977); Fuentes (1985)

Species

250

L. LOPEZ-BELLIDO AND M. FUENTES

values of 3.5 -4.5. These maximum valuesgenerallycoincidewith the end of flowering. Maximum absolute values of 7 in L. angustifoliusand 7.5 in L. albus have also been cited (Greenwood et al., 1975; Herbert, 1977a; Herbert and Hill, 1978; Vavilov and Gataulina, 1982; Fuentes, 1985). The leaf area duration index (LAD)in L. albus has been estimated at between 186-208 in the USSR by Vavilov and Gataulina ( 1982) and in Spain by Fuentes ( 1985). Crop growth index (C) has also been determined by Vavilov and Gataulina (1982) in L. albus and by Fuentes (1985) in L. albus, L. angustijolius, L. luteus, and L. mutabilis for different sowingtimes and plant densities. Other indices such as relative growth rate (RGR), net assimilation rate (NAR),and leaf area ratio (LAR) have been studied in L. albus by Herbert (1977a) in New Zealand in distinct plant densities, and by Fuentes (1985) in Spain for different sowing times and distinct plant densities in the four cultivated species (Table 111). Accordingto both Greenwood ef al. (1975) and Perry ( 1975) the development pattern in lupin causes great competition between each inflorescence and sequential lateral orders for photosynthesis products. This may be the cause of the low percentage of pod setting, frequently 25 - 30% of the total flowers, and also their slow initial development (Greenwood et al., 1975; Famngton, 1976; Garside, 1979; Porter, 1980; Shutov, 1980). Rapid seed filling is effected at the expense of photosynthesis products in the remaining leaves, translocation from branches and senescent leaves, and the weak photosynthetic activity of the pods (Greenwood et al., 1975) has suggested that part of the weight loss in the vegetative organs corresponds to the translocation of substancesto the seed. This coincides with findings of Farrington (1976), who detected a decrease of nitrogen concentration in the stems and branches parallel to the increase found in the seeds. Hocking and Pate (1978) studied the absorption and distribution of minerals in L. albus and L. angustifolius.Mineral accumulation is closely synchronized with dry matter accumulation. During fruiting, vegetative parts

L. albus L. angustifolius L. luteus L. mutabilis a

0.3- 10 0.1-4.7 0.2-6.8 0.2-8.9

2.8-71.4 2.4-88.7 5.5-93.4 0.2-58.0

From Herbert (1977a) and Fuentes (1985).

1.9- 10.2 2.1 - 15.7 2.2-1 1.7 0.3-8.6

0.3-1.3 0.2 - I .o 0.3- 1.2 0.3- 1.2

LUPIN AS ALTERNATIVE PROTEIN SOURCE

25 1

showed losses of 10- 80% of their phosphorus and potassium, 20 - 50% of their magnesium, iron, zinc, manganese, and copper, and loss of less than 15% of their calcium and sodium. Simultaneously there was a mobilization of these minerals toward the fruits, whose intake of phosphorus, potassium, magnesium, and manganese was 23-5996 and was 10-25% for zinc, calcium, and iron. Leaves showed a higher translocation efficiency than stems and petioles,just as in L. albus, whose mobilization efficiencyis greater than L. angustifolius. However, Lemaire and Poulain (1984) suggested that in spring-sown L. albus translocation from pods to seed is not very efficient because of the high dry weight pod values at harvest. Investigationsto modify the lupin growth pattern by sprayingwith growth regulators or by hand pruning the inflorescences on the main stem were camed out by Porter (1980), but the results were not satisfactory.However, Shutov (1980) has had some success in diminishing floral abortivity by spraying during flowering of the main stem with solutions of macro- and micronutrients, especially ammonium nitrate and some growth regulators. This suggests (Shutov, 1980) that these nutrients have a regulating effect on the plant.

3. Nitrogen Fixation Rhizobium lupini belongs to the slow-growinggroup of rhizobial bacteria. This bacteria forms nodules in the genera Lupinus, Omithopus, Cystisus, Ulex, and on other tropical legumes (Withers et al., 1976; Temprano et al., 1982). An effective symbiosisin lupin, according to Pate (1984), produces a growth ratio similar to plants grown with an optimum nitrogen level in the soil. However, nitrogen-fixing plants have less photosynthetic efficiency due to the greater energy spent on fixation (69% of net photosynthesiscompared to nonsymbiotic fixing plants). Nodulation and nitrogen fixation have been studied in autumn-sown L. angustifoliusin Australia (Farrington, 1974; Farrington et al., 1977). Nodules appeared 4 - 6 weeks after sowing and fixation began 15 days later. The fixation ratio reached its maximum at the beginning of flowering on the main stem and remained constant until the beginning of seed filling when it decreased, coinciding with water stress. Trinick et al. ( 1976) also found that fixation continues until the death of the plant unless there is water stress. Comprehensive studies on nitrogen metabolism in the plant have been camed out by Pate ( 1984) using I5N and I4C. In the species L. albus and L. angustifolius only a small proportion (less than 15%) of total nitrogen absorbed or fixed is taken up before flowering. Maximum ratio is reached during fruiting and the nodulated root competesefficientlywith the develop-

252

L. LOPEZ-BELLIDO AND M. FUENTES

ing fruits and other plant parts for the carbohydrates. The root continues using half the net photosynthesis and is able to carry out fixation until seed maturity and even up to leaf drop, which suggests carbohydrate reserves in the root. Research by Pate ( 1984) also confirmed the high lupin efficiency in nitrogen mobilization to the fruit during seed filling. Studies of nitrogen balance in L. albus showed that the net loss of nitrogen from leaflets, stem, petioles, and nodulated root after floweringprovides 57% of the fruits’ net demand for nitrogen. The remainder comes from N fixation or uptake of inorganic nitrogen from the soil during fruiting. The harvest index of nitrogen in some L. albus cultivars reaches 0.84, and 0.79 in some L. angustfolius cultivars. According to Greenwood et al. (1975), there is a close relationship between nitrogen fixation and dry matter production, with the former at times a limiting factor at the beginning of growth. Duthion and Amerger (1984), also using 15N,have found, up to 40 days after flowering, a close relationship between nitrogen accumulation and the number of seeds per unit area which determines yield. Nitrogen assimilation during the followingphase depends on N fixation, which influences the nitrogen percentage found in the seeds. The total capacity of N fixation by lupin has been estimated by various authors to vary between 102 and 252 kg N/ha (Hemdge, 1982; Duthion and Amerger, 1984). Wells and Forbes (1980) showed that L. hispanicus spp. bicolor is able to fix 140 kg N/ha. Various factors such as waterlogging, level of soil nitrogen, or type of fertilizer may influence nodulation and nitrogen fixing. According to Farrington ( 1974), Trinick et al. ( 1976), and Farrington et al. ( 1977), low temperatures at the beginning of the vegetative stage delay nodulation. Waterlogging diminishesnitrogen fixation and even may kill the nodules, but once this is corrected the plant forms new nodules which carry out fixation (Farrington et al., 1977). The level of nitrogen in the soil notably influences nitrogen fixation in the plant (Hemdge, 1982). In France, Duthion and Amerger ( 1984) used various application of nitrogen fertilizer to inoculated and noninoculated lupin in a soil containing less than one rhizobium per gram of soil; the amounts of nitrogen fixed were less in relation to the greater amounts of nitrogen fertilizer applied. The number and dry weight of nodules per plant also diminish with increasing nitrogen levels in the soil (Fuentes and Lopez-Bellido, 1984). Finally, the type of nitrogen fertilizer used has an influence; ammonium has more effect than nitrate (Paradinas et

al., 1982). Gladstoneset al. ( 1977)and Chatel et al. ( 1978)found that applyingcobalt to soils poor in trace elements in western Australia, had a positive effect on nitrogen fixation, which suggests that this element is related to cell division in the rhizobial bacteria.

LUPIN AS ALTERNATIVE PROTEIN SOURCE

253

According to Withers et al. (1976) nodulation is spontaneous in soils where lupin has traditionally been cultivated or where there are wild plants able to associate with Rhizobium lupini. In France, Amerger et al. (1984) has verified that the presence of R. lupini in the soil is closely related to the pH value. If the pH is below 6 there is enough inoculum for good nodulation . (more than 100 bacteria per gram soil); in soils with a pH value of 6 to 7 the number of rhizobial bacteria is variable; but probably there is a deficiency of bacteria if pH values are above 6.5. Inoculation is recommended by numerous researchers, especially if the soil pH is above 6.5 and lupin has not been sown for 4 - 7 years, as the rhizobial bacteria survive about 6 years (Rhodes, 1976; Withers et al., 1976; Girard and Lenoble, 1979; Duthion and Amerger, 1982;Gross, 1982a;Amerger et al., 1984).According to Chatel et al. (1978), with inoculation most of the nodules are found on the main root, whereas with spontaneous nodulation the nodules are distributed on all the plant roots. Numerous inoculation trials have been carried out in combination with nitrogen fertilizer.The results have been variable accordingto the conditions of each trial. Sometimes no conclusive answer has been found (Fuentes and Lopez-Bellido, 1984). Other times there have been certain initial results, such as an increase in nodulation, a greener plant, or a greater reduction in acetylene, but without having increased production (Tayler and SylvesterBradley, 1978).On the other hand there have been clearer answers when no rhizobial bacteria exist in the soil (Rhodes, 1976; Duthion and Amerger, 1982, 1984;Plancquaert, 1982). A clear increase in lupin yield due to nitrogen fertilizer exists only when there is no rhizobia in the soil and no inoculation has been carried out (Rhodes, 1976; Withers ef al., 1976; Tayler and Sylvester-Bradley, 1978). Various studies on the selection of Rhizobium lupini strains and their evaluation have shown differences in their effectiveness, and also interactions between strains and lupin species, and to a lesser degree between cultivars (Temprano et al., 1982; Lagacherie et al., 1983; Amerger et al., 1984). 4. Grain Yield and Components

The particular branching structure oflupin makes the branches the physiological unit of the plant, contrary to other legumes whose physiological unit is the inflorescent axillar (Withers, 1984). Some researchers divide yield according to the different ramification orders and in some cases the number of branches per plant are considered as a yield component. Many studies have been carried out on the factors which influence harvest index (HI), yield distribution in the distinct ramification orders, and yield components;

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L. LOPEZBELLIDO AND M. FUENTES

most studies have been made in Australia, New Zealand, France, Great Britain, and Spain. a. Harvest Index. The lupin harvest index is low compared to other legumes such as peas and soya (Farrington, 1976). Even though the index is variable due to environmental conditions, its value depends on the species and the intensity ofbreedingprograms carried out on them (Hill et al., 1977; Fuentes, 1985) (Table IV). In general, the harvest index is higher in early cultivars; it is the same for L. albus (Goldstein, 1984; Vavilov and Gataulina, 1984)as for L. angustifolius (Bishop et al., 1984). The influence of sowing date and plant density on the HI is not very clear. Goldstein (1984) registered higher HI in early spring sowingsthan in later sowingswith L. albus (cv. Lublanc), but Fuentes(1985) in southern Spain did not find a clear influence of sowing time in autumn winter sowings. Plant density does not appear to affect HI in L. albus or L. angusfifolius(Herbert, 1977a; Herbert and Hill, 1978; Fuentes, 1985)even though Tayler and Sylvester-Bradley(1979) obtained a lower HI with lower densities. b. Yield Distribution. Although lupin is able to produce many lateral branching orders, the total harvest is almost always formed on the main stem and fmt and second lateral orders. Frequently, 90- 100% of the grain is situated on the main axis and primary orders (Greenwood et al., 1975; Fuentes, 1985). This contribution is normally greater in L. albus and L. luteus than in L. angustifolius (Farrington, 1974; Herbert, 1977b; Tayler and Sylvester-Bradley, 1979; Fuentes, 1985). The distribution of total yield in the distinct inflorescent orders is a direct consequence of the higher or lower grade of plant ramification. As the lateral branch orders increase the number of flowers and pods per inflorescencedecreases(Perry, 1975;Farrington, 1976)whereas the percentage of pot set increases (Greenwood et al., 1975; Garside, 1979). The low Table IV Harvest Index of Lupin Species Species

L. albus

Harvest index, HI (range) 6.9-51.1

L. angust$olius

10.4-48.8

L. luteus L. mutabilis

12.3-39.7 3.9-25

References Herbert (1977a); Hill et al. (1977); Goldstein (1984); Fuentes (1985) Hill et al. (1977); Herbert and Hill (1978); Bishop et al. (1984); Fuentes (1985) Fuentes (1985) Hill et al. (1977); Fuentes (1985)

LUPIN AS ALTERNATIVE PROTEIN SOURCE

255

percentage of pod setting on the lower inflorescencesis generally associated with plants with higher order branches (Withers, 1984) and may be due to any of the following factors: shading (Greenwood et al., 1975),competition between the lower and higher lateral orders for photosynthetic products (Greenwood et a/., 1975; Perry, 1975), or cooler temperatures (Withers, 1984). c. Yield Components. The number of pods per plant is the most variable yield component and depends on environmental conditions, as demonstrated by many researchers. This number decreases under water stress conditions (Perry and Poole, 1975; Withers, 1979b)and the shortening of the growing season (Farrington, 1974; Perry, 1975; Walton, 1976; Garside, 1979: Withers, 1979a, 1984; Fuentes, 1985). The increase in plant density also reduces the number of pods per plant (Withers, 1975;Herbert, 1977a,b; Herbert and Hill, 1978; Fuentes, 1983, while imgation from initial flowering increases the number (Stoker, 1975). The factors already mentioned have little influence over the pod numbers on the inflorescence of the main axis but has a decisive effect on the amount of plant ramification and therefore the number of pods on the branches (Farrington, 1974; Perry, 1975; Stoker, 1975; Garside, 1979; Fuentes, 1985). Although the rate and amount of branching varies between species (Herbert, 1977b), under similar conditions the number of pods per plant tends to be the same for all the species (Herbert, 1977b; Hill et al., 1977; Herbert and Hill, 1978; Withers, 1979a); in this case, other yield components are responsible for the production differences between the species (Withers, 1984). Plant density together with the number of pods per plant determine the number of pods per unit area, which is the main factor to be optimized in crop management (Withers, 1984). The optimum value of plant density is variable, as it is influenced by the species, sowing date, location, duration of growing season, management, etc. Very different results have been found accordingto the conditionsof the distinct trials. Optimum populations tend to be lower when growth conditions are more favorable (Withers, 1984). In the species L. albus yield is stabilized at 70 - 75 plants/m2,but in some cases there has not been a productive answer even when this number has been modified to very low densities. In L. angus&ifoliusthe yield is stabilized at lower densities than L. albus, normally between 25 and 75 plants/m2 (Herbert, 1977b;Tayler and Sylvester-Bradley, 1978, 1979;Girard and Lenoble, 1979;Fuentes, 1985).The distance between planting rowsdoes not appear to influence yield (Herbert and Hill, 1978;Girard and Lenoble, 1979;Fuentes, 1985). Seed number per pod also seems to have little influence on yield determination (Withers, 1984; Herbert, 1977b). Within each plant the number of seeds per pod decreases notably with the increase of higher lateral branching

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L. LOPEZ-BELLIDO AND M. FUENTES

orders (Perry, 1975; Herbert, 1977b;Herbert and Hill, 1978;Garside, 1979; Fuentes, 1985).Therefore, the average number of seeds per pod will be less as the pod number on subsequent branch order increases (Withers, 1984). Withers (1 979b) stated that the lack of water at the end of flowering reduces the number of seeds per pod. Irrigation at the beginning of flowering appears to have positive effect on seed number (Stoker, 1975) although Withers ( 1979a) found no such positive relationship. Herbert ( 1978) has obtained various effects: a negative effect on the main stem, no influence on the first and second lateral orders, and a positive effect on the third and fourth orders. Weight per seed, as measured by 1000-seed weight, may be the cause of notable differences in yield, even though other components are similar (Withers, 1984).The 1000-seed weight depends fundamentally on the species: for L. albus it is 245 -600 g, L. mutabilis 123- 344 g, L. angustifolius 128-202 g, and L. luteus 8 1 - 180 g (Villax, 1963). Within each species the distinct cultivars may have different 1000-seed weights, which also produce yield differences (Perry, 1975). For each determined cultivar the variability of 1000-seed weight is small compared to the variability of pods per plant or pods per unit area and slightly higher than the number of seeds per pod (Withers, 1984).The variability of seed weight isgreater in specieswithlarger seed size, such as L. albus and L. mutabilis, than in species with small seed size (Fuentes, 1985). Generally, seed weight is higher in the main stem and decreases in the subsequent lateral orders (Perry, 1975; Herbert, 1977a; Herbert and Hill, 1978; Garside, 1979; Fuentes, 1985), although L. angustifolius varies less in this respect (Herbert, 1977a; Fuentes, 1985).There may be at times a negative relationship between total yield and 1000-seedweight due to the development of subsequent branching orders which lower the mean average of seed weight (Withers, 1984). If rainfall is not scarce, irrigation from the beginning of flowering does not have a clear effect on seed weight (Stoker, 1975; Withers, 1979a). Withers (1984) made a clear distinction between relatively stable yield (seeds per pod and 1000-seedweight) and the variable components (plants per square meter and pods per plant). The main objective in crop management is to improve this latter group of components. However, due to the numerous factors which influence development and the interactions which exist among them, it is not easy to find optimum solutions. In general, early sowings are advisable to prolong the growing season and to increase pod numbers, though this often causes greater competition between vegetative development and productive development, and thus affects the harvest index. It appears clear that higher plant densities are favorable, especially at the end of the growing cycle in water stress years; using cultivars with a low branching tendency may also be favorable, but this means greater seed quantity which may not be compensated by greater yield.

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257

The highest yields found in the literature are of L. albus (cv. Ultra) (6050 kg/ha) and L. angustifolius (cv. Unicrop) (5660 kg/ha), both spring sowings in New Zealand (Herbert, 1977b). The species L. angustifolius and L. albus are the most productive in Australia and New Zealand (Hill et al., 1977; Stoker, 1978;Withers, 1978;Garside, 1979)and L. albus in western Europe (Lenobleand Picard, 1980;Fuentes et al., 1982,1983;Fuentes, 1985).Great differences have been recorded in the yield reached by L. mutabilis in South America versus Europe, where this speciesproduces few pods per plant and a low-weight grain even though the number of seeds per pod is similar in both continents (Gross, 1982a). Table V shows the average lupin grain yield in different cultivation areas around the world (Lopez-Bellido, 1984).

Table V Average Grain Yield in Cultivated Lupin" Country

Species

Africa South Africa

L. albus L. albus (irrigation) L. angustifolius

North America United States South America Bolivia Brazil Chile Ecuador Peru Europe Spain France

IdY Portugal Poland Oceania Australia New Zealand USSR ~

~~

~

(Yield/ha)

1000 3000 750

L. albus

1700-3900

L. mutabilis Without specification L. albus L. luteus L. mutabilis L. mutabilis

I200 1200-2000 2000-5000 1600-2600 600-700 300-2000

L. albus L. albus (spring) L. albus (winter) L. albus L. albus L. luteus L. albus L. angustifolius L. IUleUS

500-1500 2500-4000 3500-5000 1480 1200-1500 800 2000- 3500 1500-2500 1200-2000

L. angustifolius L. angustifolius L. albus

500-2500 3000-4000 2000-4000

~~

From Lopez-Bellido (1984).

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L. LOPEZ-BELLIDO AND M. FUENTES

D. CLIMATE AND SOIL Cultivated lupin is a moderate-climate plant which has variable thermic requirements according to the species and cultivar (Table VI). The cultivated species tolerate temperatures between -6 to -9 'C even though their resistance to cold varies during growth and is different between the species from the Old and New Worlds. The Mediterranean species tolerate frost better during the beginning of the vegetative stage, i.e., three or four leaves, but are more suceptible to low temperatures during flowering and pod setting (Gladstones, 1970;Nelson et al., 1983).Lupinus mutabilis,cultivated in the high Andes, is susceptible to cold during the young plant stage but frost resistant during maturation (Gross, 1982a). For this reason it is difficult to grow L. mutabilis under winter conditions. In contrast, for L. albus and L. angustifoliusautumn sowing in the Mediterranean Basin suits their climatic requirements perfectly (Villax, 1963; Fuentes, 1985). Optimum growth takes place with average temperatures between 15 and 25°C (Gladstones, 1970). Higher temperatures can affect growth especially during flowering and pod setting and especially if accompanied by water stress (Withers and Edge, 1979; Nelson et al., 1983). Lupin is cultivated in areas of very diverse rainfall. It has been estimated that precipitation levels above 350 mm are necessary during the growth cycle in order to obtain adequate yields (Nelson et al., 1983; Gross, 1982a). Although drought resistant due to a deep root system which can cover a large volume of soil, lupin in general requires water. This need varies among the distinct species and according to the different growth stages. It appears that L. luteus needs less water, growing adequately in Hungary on 250 mm (Belteky et al., 1983). Lupin also tends to require more water during flowering and pod setting, and thus water stress during this period notably affects yield (Gross and von Baer, 1981). Deep, fertile and well-drained soils with an acid to neutral pH are the most adequate for obtaining high yields from lupin (Nelson et al., 1983). According to Gross (1982a) lupin prefers, if there is sufficient humidity, sand or sandy loam soils to fine-textured or clayey soils, which can cause excessive vegetative growth or growing difficultiesdue to lack of drainage or aeration. These conditions inhibit Rhizobium development, making the plant more susceptible to certain diseases, mainly Fusarium sp. Gladstones (1970) has established the differences among the principal cultivated species according to soil type and nutritive requirements (Table VI). Chlorosis, another characteristic phenomenon in lupin, may have different origins but is usually associated with high levels of lime in the soil, i.e., with alkaline and calcareoussoils (Gross, 1982a). Different hypotheses exist over the causes of chlorosis, e.g., deficiencies of Fe, Mn, and Mg or alter-

Table VI Reqoirements of Cnltivated Lupin Species"

sod type

SpeCieS

L. luteus L. angustifolius

L. albus

L. consentinii

Sand and sandy loam; mediumhigh acid content. Slightly tolerant to waterl-g Sand and loam; moderateneutral acid content. Nonresistant to waterlogging Loamy sand and loam; moderately acidic; slightly calcareous. Nonresistant to waterlogging Sand and loam; moderately acidic to slightly c a l m u s . Nonresistant to waterlogging

Specific nutritive

Nutritive requirements

requirements

Low

Very Susceptible to deficiencies of Fe and Mn in neutral

Low - moderate

Susceptible to deficiency of Co. Requirements of P,K,and probably other elements higher than in L.luteus Not well known but generally higher than L. angustifolius

Moderate

LOW

calcareoussoils

Susceptible to deficiency of Mo. Tolerant to deficiencies of other elements. Similar to L. lUtt?US

a

From Gladstones ( 1970).

Climate Requires moderate temperature at vegetative stage. Oniy slightly resistant to frost Requires cold- moderate temperature at vegetative stage. Frost resistant Requires cold to moderately warm temperatures at vegetative stage. Frost resistant Requires moderately warm temperatures at vegetative stage. Highly susceptible to frost

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L. LOPEZ-BELLIDO AND M. FUENTES

ations in absortion or metabolism of nitrogen in the plants in relation to Rhizobium. The deficiency of Fe characteristicin calcareoussoils is the most accepted theory. Hutchenson ( 1968) suggested that calcium carbonate hinders the absorption, translocation, or activity of the Fe but Furgal ( 1974) showed that the level of chlorosis depends originally on the concentration of CaCO, in the soil, not the pH value. However, as the pH value is influenced by the lime content in the soil, the pH value is a useful parameter to determine adequate soils for lupin cultivation (Gross, 1982a). Due to the chemical nature of the soil in direct contact with the roots, physiological differences may appear in the reaction of lupin to chlorosis (Beltekyet al., 1983). The various species differ in their susceptibilityto lime. According to Furgal (1 974) the order in a diminishing scale is as follows: L. luteus, L. angustifolius,L. mutabilis, and L. albus. The reaction of cultivars within the same speciesto lime may present important differenceswhich can change the ordering of susceptibility (Koch, 1968; Belteky et al., 1983). This variability may be used in breeding programs to obtain a more lime-resistant lupin, which would increase the crop’s yield potential.

Ill. PLANT BREEDING A. AGRONOMIC POTENTIAL

Gladstones ( 1984) has made a comprehensive review of genetic sources and agronomic potentials of the cultivated Old World species of lupin and Blanco (1984) of L. mutabilis. The references used here are from both these authors. The species L. albus has only moderate natural genetic resources which have been profitably supplemented by artificially induced variation. The wild forms of L. albus have only recently been reexploited for breeding, but as their natural distribution is in the Balkan-Aegean area, their potential may be fairly limited. Considerable secondary variation has arisen within var. albus during its spread throughout the Mediterranean region and up the Nile to Ethiopia. However, its requirements for relatively fertile soils limits its possibilities for use on poor soils. The species L. luteus is limited both genetically and environmentally. Even so, it has shown good adaptability to spring-summer sowings in high latitudes and cool-temperate environments. This herbaceous plant form seems more appropriate for forage than for seed production; the high seed protein content may be due not so much to efficient nitrogen metabolism as

LUPIN AS ALTERNATIVE PROTEIN SOURCE

26 1

to inefficiency in seed carbohydrateaccumulation. The principal advantage of L. luteus is its tolerance to waterlogging. Introgression of genes to or from L. hispanicus may intensifythis advantage. For the dry Mediterranean climates, on the other hand, L. luteus lacks drought tolerance. Derivativesof L. hispanicus may have a special role in some areas due to their high frost resistance. The species L. angustifolius is by far the most common and most widespread of the species in its natural or near-natural state in the Mediterranean area. It can be cultivated under a wide range of climatic environments from sea level to 1200 m or more, tolerating moderately acid sands to quite heavy and mildly alkaline soils. The wild and partly domesticated populations form a diverse genetic pool in which there are few genetic barriers. The speciesadapts more naturally to winter growing seasonsthan to the summers of cool - temperate climates because of its susceptibilityto vernalization and frost resistance. However, poor adaptation to high temperaturesparticularly at flowering suggests that as a spring-summer seed crop the species may be confined to the cool-temperate climates or to areas where early spring sowing is possible. It has shown itself to be more drought resistant than L. albus and much more so than L. luteus, and grows well on a much wider range of soilsthan L. albus, especiallypoorer sandy soils which have recently been brought under cultivation. Finally, the erect habit of L. angustifolius seems ideally suited to cropping and yield improvement due to its strong main stems and fine leaves, permitting good light penetration into the canopy. In summary, Gladstones ( 1984) stated that L. angustifoliushasgreat potential, and in the long term will make a highly valuable addition to the world leguminous crop plants, particularly on soils which in the past have often been marginal for agriculture. All the rough-seeded species have quite limited natural distribution, causing a narrow range of genetic variability. Although this group of species has not yet been improved sufficiently for inclusion in modern agricultural systems (except marginally L. consentinii),they have considerablelong-term potential. Most of the speciesalready have large to very large seeds, which are low in alkaloid content for wild plants. It is speculated that they might have been a food source for preagricultural man and that their seed characteristics could have resulted from long selection and spreading by primitive humans. The species L. pilosus, L. atlanticus, and L. consentinii present an excellent yield potential even though the first has a very thick seed coat which constitutes about one-third of its total weight. Other rough-seeded species have been studied less but probably possess similar yield potentials in suitable environments. Their soil preferences, where documented, range from the neutral to slightly alkaline. Some species such as L. pilosus and L.

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L. LOPEZBELLIDO AND M. FUENTES

atlanticus grow on quite heavy soils, but L. consentinii is a sandy soil species which tolerates acidity although it is a native of neutral to calcareous sands and tolerates free calcium in the soil. Although information on drought resistance in this group of species is limited, the natural growing sites of many of them are dry zones, which indicates their adaptation to arid climates. The fluctuations of aridity in North Africa, throughout the years, must have subjected the group as a whole to a strong selection favoring drought resistance. In summary the rough-seeded Mediterranean-African lupins offer interesting prospects for future domestication and cultivation. The ecological ranges could be markedly different from those of existing domesticated lupins. The species L. mutabilis is distributed among cultivated forms, which are the most abundant, and among wild and semiwild forms. The Andean lupin has a wide genetic variability due to natural selection, caused by the diverse Andean environment. There are three main types: Highland plants, which develop under conditions of little rainfall and low temperaturesgenerally above altitudesof 3500 m. They are small plants less than 60 cm high without branching orders, the main stem prominent, and ending in one inflorescence. The vegetative cycle is short. The most representative of this group is found in Potosi, Bolivia. Plants with prolific branching system which reach 1.5 m high, and in which the main stem contributes more than 50% of yield. The vegetative cycle is of medium length. They are found in the inter-Andean valleys of meridional Peru and Bolivia. Temperate climate plants which grow in areas without frost, such as the north of Peru and Ecuador. The branching orders are abundant and the main stem contributes little to yield. These plants grow to a height of more than 1.8 m and their cycle is long. There exist intermediate forms among these three types due to the microclimate. There are also morphological variations such as the color, forms, and size of seeds as well as flower color. Protein content, oil, and alkaloids and susceptibility to disease (especially anthracnose)also vary. There are no crossing barriers between wild and cultivated types. Gladstones concludes in his report that for climatically suitable areas, most lupin species have the plant structure and potential yieldingcapacity to become successful and valuable crop legumes. Their contribution to world agriculturecan be exceptionalnot only because they can be used for producing nutritious and directly usable foodstuffs but much more importantly because they can serve as a basis for developing ecologically sound permanent farm rotations for some of the world’s poorer soils.

LUPIN AS ALTERNATIVE PROTEIN SOURCE

263

B. RESULTS AND AIMS OF BREEDING Gladstones ( 1975,1984)has reported on the actual breeding state of lupin in the Old World, claiming that they had been overlooked in the recent past largely because of their intractablebitterness and the fact that their adaptive range lays outside the fertile valleys and similar locations where primitive agriculture evolved. Lupins breeding began simultaneouslywith its domestication by means of selection carried out by the same farmers. The species L. albus has been the most improved due to its longer cultivation. According to Gladstones (1984) even in ancient times it already had white flowers and seeds, a permeable seed coat, rapid homogeneous germination, and nonshattering pods. Modem breeding began in Germany in 1928 with the search for alkaloidfree plants by von Sengbusch; sweet plants of L. luteus and L. angustifolius were found in 1928 and 1929, and of L. albus at the beginning of the 1930s (von Sengbusch, 1942). Since then 10 recessive mutant genes which cause sweet characteristics have been found in these three species (Harrison and Williams, 1982, 1983). The alkaloids are not completely eliminated in the mutants but the levels are very low (0.02-0.05%). The mutant genes alter the original relative proportion of the distinct alkaloids and their efficiency. In comparison the breeding of L. mutabilis for low alkaloid content has been much slower. Although von Sengbusch ( 1942)and Hackbarth ( 1961a) obtained lines with low alkaloid content, they were not developed because of their slow maturation. Other researchers such as Bruecher (1971) and Pakendorf ( 1974)have released low-alkaloid lines but these have not resulted in commercial varieties. More recently, von Baer and Gross ( 1977), von Baer (1980), Blanco (1980), and Blanco and Jimenez (1982) have carried out selection work, and have found low-alkaloid-content lines (0.1%) which have a polygenic determination in contrast to the Mediterranean species. Williams et al. (1984) discovered another allele-recessive mutant which reduces alkaloid content to 0.2-0.3%. The improvement of both protein and oil content has been studied using soya as the model. Williams and Looker (1978, 1979) and Gross et al. (1 983a) have determined the genetic and environmental influence on protein and oil content. According to Gross et al. (1983a) the heritability in L. mutabilis is 90% for protein content and 66% for oil, which favors the breeding of rich protein cultivars instead of those with high oil content. Even though there exists a negative correlation between protein and oil content (Gross et al., 1983a;Fuentes, 1985),selection for oil content without altering that of protein content should be possible but it would mean a diminishing of a-galactoside content (Lenoble, 1979).

264

L. LOPEZ-BELLIDO AND M. FUENTES

Gladstones (1984)questionedthe usefulness of oil content selection in L. albus, which has initially a low content. He believed that the energy is more efficient in carbohydrate form which is also valid for nitrogen fixing and protein production. Besides, in this form storage qualities are better and the seed can be used directly for animal consumption.

I . White Lupin Private firms in Germany have obtained semidwarf, high-yield sweet lines of L. albus with early flowering and maturing, adapted to the northern European climate: Ultra, Blanca, Gela, Plugs-Gela, Astra, Multolupa, etc. (Gladstones, 1975, 1984).From Poland come Kali and Kalina (Mikolajczyk et al., 1984a); from the USSR, Kievski; from France, Lublanc and Lucky (Lenoble and Picard, 1980) among others. The species L. albus is still the lupin crop grown under the most diverse conditions, which makes breeding aims different for each case. For the northern zones it is still necessary to shorten the cycle, first to reduce susceptibility to vernalization, and second, to shorten the duration of pod maturity (Williams, 1982; Gladstones, 1984; Mikolajczyk et al., 1984a; Vavilov and Gataulina, 1984). In Poland recently, the “epigonal” mutation has been used to increase pod setting on the main stem and to shorten the plant cycle (Mikolajczyk et al., 1984a) and in the USSR a very early-floweringcultivar with little branching has been obtained (Vavilov and Gataulina, 1984). In general, the European cultivars may be apt for winter sowing in warm areas, especially Multolupa and Lucky which can be considered winter/spring alternatives (von Baer, 1980; Lenoble and Picard, 1980). However, winter sowing in colder zones is more of a problem. Wells and Forbes ( 1980)have obtained lines such as Tiftwhite, which resists freezing and can be grown under the winter conditions of Georgia (United States). Similar lines is a breeding aim for other European areas such as France and Spain (Lenoble, 1980;Jambrina, 1982). Lenoble (1980, 1982) set out other breeding objectives for L. albus, namely obtaining a smaller grain, which will lower seed cost, and also a reduced pod weight, which will facilitate earlier maturation but also will increase the proportion of testa, consequently diminishingseed quality. 2. Yellow Lupin Also in Germany, von Sengbusch and later Hackbarth and Troll have obtained mutants of L. Luteus with nonshatteringpods and permeable white seed coats, distinguishing them from traditional lines. Combining these

LUPIN AS ALTERNATIVE PROTEIN SOURCE

265

characterswith the lack of alkaloids, they released in 1943 cultivar Weiko I1 and in 1951 Weiko 111 (Gladstones, 1975). The other breeding aim was disease resistance, especiallyto Fusarium spp. (Gladstones, 1984). Selection work has continued mainly in Europe (Germany, Poland, USSR, and Holland) where cultivars such as Sulfa, Gyulatanyai, Cyt, Afus, Tomix, Puissant, Aga, Reda, etc. have been obtained (Jambrina, 1980; Mikolajczyk et af.,I 984b). The lack of early flowering and low pod setting, aspects which are characteristic of this species in spring sowing in temperate areas, has motivated selection programs to find early cultivars (Shutov, 1980; Mikolajczyk et al., 1984b).The cv. Zytomirski, coming from the Soviet collection, carries the “epigonal” mutation, which is characterized by intense primary pod setting and little branching. This mutation has been incorporated into other early flowering cultivars in Poland with excellent results (Mikolajczyk et af., 1984b).

3. Narrow-Leafed Lupin In L. angustifoliusless genetic progress was made until the 1960s, when German and Swedish breeders attained the sweet and permeable seed coat lines of the cultivars Muncheberger Blaue Susslupine (1944) and Borre ( 1946)(both lines are pod shatteringand have the blue flowersand grey seeds of their bitter ancestors). Later, Polish and Russian researchers obtained early flowering lines with a short growing cycle, making their cultivation in Northern zones possible, but the pod still shattered. Finally in the 1960s Gladstones in Australia found individual mutant genes which produced early flowering plants with white flowers and seed and nonshattering pods. Combining these characters he released Uniwhite (1967), Uniharvest (1971), and Unicrop (1973). The cultivar Fest (1973), bitter, with blue flowersand grey seeds, and nonshattering,was commercialized as green manure. The cultivation of bitter L. angustifoliusas a cover and green manure crop began in southeastern United States in the 1930sbut since 1948 sweet lines have been utilized. The main problems were lack of winter hardiness, diseases, and the rapid contamination of sweet cultivars which could not be distinguished from the bitter ones (Gladstones, 1975). Wells and Forbes ( 1980)brought out the cultivars Blanco (1960) with white flowers and seeds and Rancher ( 1965) which is resistant to anthracnosis and grey leaf spot. A program of collaboration between Gladstones and Wells was established resulting in the cultivars Mam (1976), Illyame (1979), Yandee (1980), and Chittick (1982) in Australia and Tiftblue (1978) in the United States, all of them resistant to grey leaf spot and anthracnose (Wells and Forbes, 1980;

266

L. LOPEZBELLIDO AND M. FUENTES

Gladstones, 1984).The most immediate breeding objectives for this species are early flowering cultivars, thermoneutral, with less branching and more intense primary pod setting (Bishop et al., 1984; Brombereck et al., 1984a,b).

4. Andean Lupin Plant breeding in L. mutabilis has been much slower than in the other three species. The long tradition of cultivation in the Andes has given rise to numerous ecotypes with large white seeds and nonshattering pods. These ecotypes are adapted to the diverse ecological environment. Programs of germplasm evaluation and breeding are being carried out to obtain sweet, early flowering, and disease-resistant cultivars. The wide genetic variability may permit rapid breeding advances in this species (Blanco, 1980; Gross, 1982a; Wells, 1984). 5. Actual Objectives Wells ( 1984) reviewed plant breeding publications between 1978 and 1983 (1 14 papers) and summarized the principal breeding aims for lupin: A total absence of alkaloids is desired. The alkaloid problem is a major factor in maintaining cultivar integrity, especially in areas where wild types have grown. Protein content is heritable and will continue to be an aim in breeding. Genetic resources for a better balance of amino acids is uncertain in the genus. If, through intergenericgene transfer, this balance is improved, lupin will be a better food and feed source. Because of the negative correlation between protein and oil content in L. mutabilis, the breeders will have to decide between one objective or the other. Disease resistance (Fusarium spp., leaf spots, anthracnose, viruses etc.) continues to be a breeding aim even though there are some cultivarsresistant to some diseases. Growth rate and maturity should be better adapted to cooler climateswith a short growing season for spring sowings. Yield dependabilityis also an important breeding objective. This depends on a number of adaptation factors such as disease and pest damage, water stress, frost resistance, lack of vernalization or floral initiation during some seasons, consistent yields, etc. It is advisable to use a cultivar with less yield potential but more dependability. Individual breeding programs adapted to the crops utilization.

LUPIN AS ALTERNATIVE PROTEIN SOURCE

267

Table VII Distribution of Cultivated Lupin throughout the Worlda Country Africa South Africa North America United States

SpeCieS

L. angustifolius(90%) Steb; Stevens Ultra; Kiev; Buttercup L. albus ( 10%) L. albus L. angustifolius

South America Bolivia Brazil Chile Ecuador Peru Europe Spain France Italy Portugal Poland

L. albus (50%) L. luteus (50%) L. albus L. albus L. albus L. luteus L. luteus (89,5%)

L.albus (0.5%)

New Zealand USSR

0

Ultra; Kievski, Nyirsegi; Nutresweet 4601, 4602,4603; Tiftwhite Tiblue

L. mutabilis L. albus (90%) L. angustifolius(8%) L. luteus (2%) L. albus (90%) L. angustifolius(8%) L. luteus (2%) L. mutabilis L. mutabilis

L. angustifolius (10%) Oceania Australia

cultivar

L. angustifolius L. consentinii L. angustifolius L. albus L. arboreus L. luteus L. albus L. angustifolius L. polyphyllus

From Lopez-Bellido (1984).

Multolupa; bitter local ecotypes “Tremosilla” Lublanc; Kalina; Lucky Local varieties

-

Topaz; Palucki, Afw; Ventus; Iryd; Orbit; Aga (sweet) Ignis; Emir, Kazan (sweet); Turkus; Mirela (bitter) Wat; Kalina (sweet)

Uniharvest; Unicrop; Illyarrie; Yandee; Chittick (sweet) Chapman (bitter) Uniharvest;Unicrop Ultra

-

Bistrorastuchy 4; Academichesky I (sweet) Kievsky mutant; Horisont Start (sweet) Nemchinovsky 846

-

268

L. LOPEZ-BELLIDO AND M. FUENTES

The most important cultivars of the cultivated four species has been tabulated by Lopez-Bellido ( 1984) (Table VII).

IV. PLANT PRODUCTION A. CROPPING SYSTEMS Cultivated lupins appear in agricultural production in diverse forms and for very different purposes: grain production and forage in crop rotation, green manure, soil conservation, agroforestry, and also as a permanent pasture for livestock (Lopez-Bellido, 1984). Although lupin grain production has been a long-established practice in the Mediterranean, Central Europe, the USSR, and the highlands of South America, its use in rotation has diminished because of the increased use of mineral nitrogen fertilizers (Lopez-Bellido, 1984). Recently, however, Reeves (1984) reported that in Australia grain lupin production has increased from a few hundred hectares at the end of the 1960s to around 500,000 ha in 1983- 1984, due to the benefits it contributes to subsequent crops, especiallycereals. Grain lupin is used in rotation with a wide range of crops but is nearly always present with winter and/or spring cereals. They are rotated with potatoes, maize, and native plants such as quinoa (Chenopodium quinoa) in the Andean area, temporal pasture in Australia, and sugar beets and potatoes in the USSR and Central Europe ( Lopez-Bellido, 1984). Gross ( 1982a)and Belteky et al. (1983)cited the positive effect of intercropping lupin with cereals and other plants on subsequentyields. Investigations in Russia have shown that there is greater nutrient absorption in mixed cropping compared to single cropping (Kanrov, 1967). Lupins not cultivated for grain are usually ploughed in as green manure (bitter lines ofL. albus, L. mutabilis, L. luteus, and L. angustifolius)or used alone or mixed with cereals or grasses as fodder (sweet lines of the aforementioned species). According to Lopez-Bellido( 1984)and Reeves ( 1984)there is a wide range of situationswhere lupin is used in these roles, and succeeding crops can be other fodder crops, cereals, vegetables, or even trees. Lupin is used as green manure in Brazil, some regions of the United States, Central America, and the Andean area, and as forage in the USSR, Central Europe, Australia and the southwest part of the Iberian Peninsula. Lupin also plays a role in the fight against erosion in soil establishment and afforestation in numerous areas of the world. In Parana (Brazil) L. albus is recommended for soil conservation, as it is known to improve the structure and biology of the soil and increase water infiltration (Gross, 1982a;Toma-

LUPIN AS ALTERNATIVE PROTEIN SOURCE

269

sini and Lhamby, 1982).Gross (1 982a) reported good results obtained with L. mutabilis in Peru on afforestation of highlands suffering from erosion, while in New Zealand L. arboreus has been used for some time to control erosion in high areas to stabilize sand dunes in coastal areas which are later planted with forestal species (Restall, 1964; Berg and Smithies, 1973; Wendelken, 1974).There are numerous references to the role of lupin species in agroforestry. Their positive effect on tree growing is primarily due to the accumulation and transference of nutrients, especially nitrogen: L. mutabilis with Pinus radiata and Eucalyptus globosus in Peru (Gross, 1982a),L. arboreus with Pinus radiata in New Zealand (Gadgil, 197la,b,c, 1976;Mead and Gadgil, 1978;Sprent and Sylvester, 1973),and L. polyphylluswith Picea abies in West Germany (Melzer and Lucke, 1984).

B. LUPININ CROPROTATION Reeves (1984) has made a complete review of research and results obtained on lupin in crop rotation. Although the role of lupin in soil improvement has been known since ancient times, very little work on lupin in crop rotation and even less on lupin harvested for grain has been reported. Reeves ( 1984) asserted that lupin has inestimable value in crop rotation as a cash crop, soil fertilitybuilder, and break crop for cereal diseases(assuming that it is effectively nodulated with Rhizobium lupini). To these advantages the production of a highly nutritious grain and stubble for farm livestock can also be added.

I. Lupin for Green Manure or Grazing Even though the wide practice of using lupin as green manure shows positive results, the magnitude of the soil improvement has rarely been reported (Reeves, 1984). Preliminary results obtained by Hamblin (cited by Reeves, 1984)in Western Australia indicate that mid-post fill in L. angustifolius is the best time to apply green manure treatment and that cutting and removing the crop or harvesting it for grain considerablyreduces the residual value of lupin (Table VIII). In Parana (Brazil)Tomasini and Lhamby ( 1982) found the ploughing in of L. albus at flowering, before maize cropping, was equivalent to 80 kg N/ha, and Muzilli et al. (1983) using this practice obtained a 26% yield increase in maize compared to plots without nitrogen fertilizer. Reeves ( 1984) also mentioned investigations which reflect the positive effect of lupin as green manure on potato yield and quality and on wheat yield.

270

L. LOPEZBELLIDO A N D M. FUENTES Table VIII Influence of Different Utllhtion of Lupin on Subsequent Wheat Crop Grain Yield" Treatment of prior lupin crop

Grain yield of subsequent wheat crop (tons/ha)

Cut and removed Ploughed in Cut and left Harvested

0.76 1.01 1.02 0.72

From Reeves (1984).

The effect of grazing lupin on soil fertility has been studied by McKenzie and Hill (1 984) using annual ryegrass (Lolium multiforum),two densitiesof L. angustifolius (cv. Uniharvest), and barley and fallow as controls. The results confirmed that lupin is beneficial to the succeeding crop. The difference in ryegrass growth between grazed and harvested lupin shows the better effect of grazing (Table IX),although harvested lupin also improved soil structure compared to fdow. Hamblin and Nelson (1984) compared the residual value of lupin (L. angustifoliusand L. consentinii) with other legume species (Pisum sativum, Vicia benghalensis, Trifoliumhirtum, T. subterraneum.Medicago polymorpha, M. truncatula, M. tornata, M. littoralis, M. scutella, and Ornithopus compressus) in crop rotation with wheat, native pasture, and fallow in both high and low rainfall zones in western Australia on nitrogendeficient soil Table M

Nitrogen Fertilizer Vnlw of Grpzed Lupin, Barley, and Followa Treatment

N fertilizer value

Lupin (low population) Grazed early Grazed late HarVeSted Lupin (high population) Grazed early G d late HarVested

Barley Fallow From McKenzie and Hill (1984).

53 86 0 73 79 7 -115 0

27 I

LUPIN AS ALTERNATIVE PROTEIN SOURCE

where wheat yield with no applied N averaged 0.15 tons/ha. Growth and yield correlated well to the estimate of nitrogen fixed, particularly at the dry site, where the residual value of lupin appeared qualitatively different from other legumes. Wheat yield following lupin was higher than following any other legumes. In all cases the harvest index of wheat was greater following a legume than when cropped continuously, a practice which probably leads to root disease; these results thus demonstrate the marked disease-cleaning effect of legumes. 2. Grain Lupin Significant yield responses following grain lupin have been obtained from a range of crops and under widely varying environmental conditions. In the last few years there have been reports from Australia, USSR, Poland, Germany, France, England, Italy, Kenya, New Zealand, Peru, and elsewhere. Although there are published results of effects of grain lupin on other crops, most of the investigations have been carried out on cereals, mainly winter cereal and grain lupin in rotation. One of the most comprehensive investigations is that of Reeves (1984) carried out in Australia (northeast Victoria) between 1974 and 1979 using L. angustifolius cv. Uniharvest (Table X).Grain yield increases resulted when Table X

Mean Grain Yield and Nitrogen Content of Wheat and Luph Crown h Rotation4* Year 2 Year 1 W 2.89 L 1.90

tonslha WW3.16~ LW 3 . 9 0 ~ WL 1.89a LL 1.27 b

Year 3 %N 2.53~ 2.75 x 5.58 a 5.57 a

tonsha WWw2.58~ LWW 3 . 0 0 ~ WLW 3.34 x LLW 3.41 x WWL 1.46 a LWL 1.36 a WLL 0.55 b LLL 0.66 b

%N 2.31 z 2.51 y 2.65 x 2.73 x 5.68 a 5.66 a 5.7 1 a 5.67 a

From Reeves ( 1984).

* Lupin species,L.angusfifolius.Nitrogen content given as percentage of dry matter. Each value representsmean of three sites. Postscript letters refer to differences between values in the same column (x, y, z for wheat; a, b for lupins). Values with common letters do not differ ( p < 0.05).

272

L. LOPEZ-BELLIDO AND M. FUENTES

these crops were rotated. Wheat grown after one lupin crop yielded on average 750 kg/ha more than a second successive wheat crop, and a second wheat crop after lupins yielded 420 kg/ha more than a third successive wheat crop. After 9 years of continuous wheat, the last year yield was only 2.87 tons/ha compared to 4.05 tons/ha with successive wheat/lupin rotation. Rotation also benefited lupin yield, which was higher than when lupin was cropped successively. Grain nitrogen content of wheat was significantly increased following lupin while the nitrogen content of lupin grain was unaffected. Reeves ( 1984) concluded from trials camed out in Australia and the USSR that in general, cereal grain yield increases from 30 to over 100% when cereals are grown after lupin compared to successive cereals. The role of grain legumes in improving soil fertility has never been completely clear. As legumes they should increase soil nitrogen but due to the removal of the grain which is high in nitrogen, it has often been thought that the net effect on soil may be minimal. As has been mentioned earlier, harvested lupin supplies less toward soil fertility than if the crop is greenmanured. Herridge (1982) has reported the effects of L. angustifolius in wheat rotation on sandy soils at two sites in New South Wales (Australia) where he studied the nitrogen flow through the lupin/soil/cereal system. The net input of N in the soil, after lupin harvesting, was 49 and 166 kg/ha, even though the following year, because of reduced rainfall, the lupin benefit to wheat rotation was only equivalent to 40 and 80 kg of nitrogen fertilizer/ha respectively. The availability of nitrogen from lupin residues is affected by environmental conditions such as temperature and especially the frequency and intensity of rainfall, which influence the rates of mineralization and losses due to leaching and denitrification. The research by Reeves (1984) showed soil mineral nitrogen was significantly greater after lupin crops than after wheat; the overall mean increase of mineral nitrogen under lupin was 4 1 kg/ha-year. Residual effects of lupin were also evident, with nitrogen levels reaching an average of 23 kg/ha after 2 years. Increasedsoil nitrogen was accompanied by increased nitrogen uptake by wheat. Yield responses of two successivewheat crops grown after a range of legumesand other crops (Table XI) show that wheat yields increased after all the legumes but only increased significantly after lupin in the second year compared to a third successive wheat crop. Last, the effectof lupin rotations on plant diseases must be considered. It is well known that some determined crops “break” disease cycles as in the case of some temporal pastures. According to references, lupin plays a significant role as a “disease breaker” although this influence differs from place to place depending on soil fertility and the specific disease. Reeves (1984) has shown that a lupin/wheat rotation mutually benefits both crops for disease control (diseases of wheat: Gaeumannomycesgraminis, Fusarium spp., Pseudocer-

273

LUPIN AS ALTERNATIVE PROTEIN SOURCE Table XI Yields of Two Successive Wheat Crops following Various Winter Crops"

Yield of subsequent wheat crops (tons/ha) Initial crop, 1978

Crop yield, 1978 (tons/ha)

Wheat Rapeseed Sub. clover Lupin cv. Uniharvest Lupin cv. Hamburg Fava bean Field peas Chickpea Lathyrus sativus

3.98 1.95

2.47 4.22 0.27 1.82 0.10 1.47

I979

1980

3.94 4.61 4.70 5.36 4.92 4.26 4.83 4.54 4.89

3.90 4.07 3.60 4.67 4.4 1 3.95 3.43 4.07 4.28

From Reeves (1984).

cospore1la herpotrichoides;diseases of lupin: Pleiochaeta setosa, Fusarium spp.). According to Moore et al. (1982) a single crop of lupin, L. angustifolius, reduced the level of common root rot in a subsequent wheat crop by approximately half compared with a wheat/wheat rotation; grain yield was 1912 and 793 kg/ha, respectively. C. CROPPING PRACTICES

1. Sowing

The soil iks normally prepared by a turnover plow or subsoiler (von Baer, 1982; Lopez-Bellido, 1984). Because of lupin's deep tap root, von Baer ( 1982) recommended a subsoiler which improves soil water accumulation and makes the plant more frost resistant. In France, minimum ploughing is suggested to avoid soil compactness (Anonymous, 1983). In both Australia and the Andean zone direct sowing into cereal stubble is frequent to avoid erosion and problems of sandblasting damage (Gross, 1982a; Nelson et al., 1983). The applicationof preemergence herbicides necessitatescomplementary soil preparation which leaves the soil finely prepared (Anonymous, 1983). In warm zones (Mediterranean area, South America, South Africa, Australia, and New Zealand) sowing is most often in autumn, before or just after the first rains, but in the temperate-cool zones (Europe, USSR United

274

L. LOPEZ-BELLIDO AND M. FUENTES

States) sowing is carried out in early spring (Lopez-Bellido, 1984). Numerous authors recommend early sowing whether in spring or in autumn, not later than March (or its equivalent in the Southern Hemisphere) for spring sowings, and October or November (or equivalent in Southern Hemisphere) for autumn sowings; December sowing is not recommended (Girard and Lenoble, 1979; von Baer, 1982; Anonymous, 1983; Nelson et al., 1983; Fuentes, 1985). All researchers recommend shallow planting, 1-5 cm deep because of epigeal germination; anything deeper makes emergence difficult(Girard and Lenoble, 1979; Jambrina, 1980; Lenoble and Picard, 1980; von Baer, 1982; Gross, 1982a; Postiglione, 1984). Numerous trials on plant density have been camed out with variable results, as has been mentioned in other sections; therefore it is advisable to carry out trials in each planting zone to establish the adequate population density for each particular area. In general, the suggested plant density for L. angustifoh is between 40 and 50 plants/m2 (Herbert and Hill, 1978; Nelson et al., 1983), 50-80 plants/m2 for L. albus (Girard and Lenoble, 1979; Tayler and Sylvester-Bradley, 1979; Lenoble and Picard, 1980; Anonymous, 1983), and 20-40 plants/m2 for L. mutabilis (Gross, 1982a). Higher densities increase seed price considerably. Seeding rate depends on seed size and germination percentage. It is important to check the viable germination percentage because seeds which appear normal may have fractured embryos caused by mechanical damage during harvesting and grading (Nelson et al., 1983). Seeding rates in different countries and species are tabulated in Table XI1 (Lopez-Bellido, 1984). Seed distribution is usually in rows using a seed drill or spacing drill and the distance between rows varies between 15 and 70 cm (Girard and Lenoble, 1979; Lenoble and Picard, 1980; Anonymous, 1983; Lopez-Bellido, 1984; Postiglione, 1984). In the Andean area, Spain, and Portugal a seed broadcaster is frequently employed (Lopez-Bellido, 1984).

2. Herbicides Lupin has a poor capacity to compete with weeds during the initial growth phase, especially at low temperatures; under these conditions weeds are one of the principal limiting factors in crop yield (von Baer, 1982; Nelson, 1984). Furthermore, weeds make harvesting more difficult, contaminate the harvested grain, and increase weed seed buildup in the following crop (Nelson, 1984). For these reasons weed control plays an important part in cropping practices. Some natural means ofweed control such as higher plant densities,

275

LUPIN AS ALTERNATIVE PROTEIN SOURCE Table XI1 Lupin Seeding Rate Utilized throughout the World"

Species L. albus

L. luteus

Wha

Country

100- 120 80- 170 160- 170 70- 140 160-180 200 160- 180 120-150 (0.5-0.8 X 106)b (1.1 x 106) 220-250 (0.4-0.6 X lo6 to 106)b

Brazil Chile USA Spain France IdY Portugal South Africa USSR Poland Portugal USSR

80- 100

-

Australia New Zealand

60-80 60- 100 40-50 120-150

South Africa Bolivia Ecuador Peru

Comments

60- 70 cm row distance 50 plants/m2

-

45-50 to 15 cm row distance

-

13-15 cm row distance for forage; 45 - 50 cm row

distance for grain L. angustgolius

-

15 cm row distance; 70

plants/m2

-

50-60 cm row distance

-

From Lopez-Bellido ( 1984).

* Number of seed per hectare. earlier autumn sowings, and rotation with cereals which control broadleaf weeds are used (Nelson, 1984), but the utilization of herbicides is advisable in lupin cultivation. Many active materials have been tried in different parts of the world, generally with favorable results (Table XIII). Preemergence treatments control weeds well but their effect is irregular on dry soils if not followed by precipitation. Presowing products are more efficient but their range of activity is more reduced. Postemergenceproducts, in contrast, have little effect against broadleafweeds (Anonymous, 1983). Among all the tried products simazine is the most outstanding and is used extensively in Australia. Its application has increased from 30% area in 1980 to 95% area in 1983. In order to increase its effectiveness, it may be applied before sowing and incorporated into the soil, which also permits a reduction in dosage. Negative aspects of simazine may be its phytotoxicity in sandy soils, even in low amounts, and also its high persistence which may affect subsequent crops, especially if there has been an overlap (Nelson, 1984; Nelson et al., 1984).

276

L. LOPEZ-BELLIDO AND M. FUENTES Table XI11 Herbicides Utilized on Lupin throughout the World Dosage (a.i.) (Wha)

Herbicide Presowing Triallate

References

1.4

Cuthbertson ( 1976); Lopez Ruiz ef al. ( 1982); Anonymous (1983); Plancquaert (1984); Postiglione

1.26 1.15

Anonymous (1983); Plancquaert (1984) Allen (1977); Sylvester-Bradley (1979); Lopez RuizCalero ef al. ( 1982); Lopez-Bellido ( 1984); Postiglione (1984)

0.5- 1.50

Sylvester-Bradley (1979); Anonymous (1983); von Baer (1984); Lopez-Bellido (1984); Lopez RuizCalero ef al. (1984); Nelson ef al. (1984); Plancquaert ( 1984); Postiglione ( 1984) Girard and Lenoble (1979); Lenoble and Picard (1980); Lopez Ruiz-Calero ef al. (1 982); Anonymous (1983); Plancquaert (1984) Girard and Lenoble (1979); Lenoble and Picard (1980); Anonymous (1 983); Plancquaert (1 984) Sylvester-Bradley ( 1979) Girard and Lenoble (1979); Anonymous (1983); Plancquaert (1984) Lenoble and Picard (1980); Anonymous (1983); Plancquaert ( 1984) Anonymous ( 1983); Plancquaert ( 1984)

(1984)

Benfluraline Trifuraline Preemergence Simazine

Methabenzthiazuron

2.8

Neburon

+ nitrofen

2.3

+ 1.75

Nitrofen Nitrofen

+ linuron

1.8

+ 0.55

Chlortoluron

2.5

+

Tnfluralin linuron Pendimethalin neburon Terbutryn neburon Metribuzin linuron Atrazine Pronamide Prometxyne Alachlor

+ 0.6 0.4 + 1.84 1.2

+

+ +

1

+ 1.5

1.1 0.8-1.6 1.1-2.2 0.5

Fluometuron

1-2

+

Anonymous ( 1983); Plancquaert ( 1984) LopeZ-Bellido (1984)

Metribuzin

Terbutryn tetbuthylazine

Anonymous ( 1983); Plancquaert ( 1984)

Rhodes ( 1976); Lopez-Bellido ( 1984) Cuthbertson (1976) Sylvester-Bradley( 1979); Lopez-Bellido( 1984) Cuthbertson ( 1976); Allen (1 977); LopezRuiz-Calero ef al. ( 1982); Postiglione (1984) von Baer (1980); Lopez Ruiz-Calero et af. (1982); Postiglione ( 1984) Cuthbertson ( 1976); Lopez Ruiz-Calero et al. ( 1982); Postiglione ( 1984) Sylvester-Bradley ( 1979)

277

LUPIN AS ALTERNATIVE PROTEIN SOURCE

Table XI11 (Continued) Dosage (a.i.) (ke/ha)

Herbicide

-

Propyzamide Diuron Postemergence Diclofopmethyl

0.4-2.4 0.9 0.75

Alloxydine sodium

1.5-3

Carbetamide

Simazine Flampropisopropyl Propazine

0.5 0.6 0.75- 1.5

References Sylvester-Bradley(1979) Allen (1977); Lopez Ruiz-Calero el al. (1982)

Lopez Ruiz-Calero et a/. (1 982); Anonymous ( 1983); von Baer ( 1984); Plancquaert ( 1984) Girard and Lenoble (1979); Anonymous (1983); Plancquaert ( 1984) Cuthberston (1976); Girard and Lenoble (1979); Sylvester-Bradley ( 1979); Lopez Ruiz-Calero et al. (1982); Anonymous (1983); Plancquaert (1984); Postiglione ( 1984) Anonymous ( 1983); Plancquaert (1984) Anonymous (1983); Plancquaert (1984) Cuthbertson (1976)

3. Fertilizers There is not much information on fertilizing in lupin as it is a little used practice ( Lopez-Bellido, 1984). The nutrient extractions in L. angustifolius according to Nelson et al. (1983)are shown in Table XIV. Nearly all authors agree that lupin does not need nitrogen fertilizer or at the most only 20-30 kg/ha at the beginning of growth, before nitrogen fixation starts. A larger quantity may favor weed development (Girard and Lenoble, 1979; Anonymous, 1983; Postiglione, 1984). According to Gross (1982a)L. mutabilis roots are able to free and take up blocked soil phosphorus. Nelson et al. (1 983) points out that, in general, Table XIV Lupin Uptake of Nutrientsab Nutrients N

P K

Stem/leaves (3000 kg)

Pods (2615)

seeds (2000 kg)

Total plant (7615 kg)

30 2 25

22 2 21

110 7 16

162 11

62

From Nelson ef a/. (1983). Nutrient amounts shown in kilograms per noted volume of plant parts. Taken from a crop producing a grain yield of 2000 kg/ha.

278

L. LOPEZ-BELLIDO A N D M. FUENTES

lupin needs twice as much phosphate as wheat on new land but its requirement is less than wheat on old land. High rates of superphosphate drilled with the seed can affect seedling emergence as lupin seeds are sensitive to concentrations of salts; also, high rates of superphosphates make potassium and manganese uptake more difficult for the plant. The global dosage must be established accordingto the history of phosphate in the soil and declining steadily as the fertilizer history increases, reaching levels similar to wheat. Recommended applications range between 60 and 120 kg P205/ha(Girard and Lenoble, 1979; Gross, 1982a; Anonymous, 1983; Postiglione, 1984). Lopez-Bellido (1984) noted an utilization range of 30- 100 kg/ha in superphosphate form. Cox (1978) has studied potassium nutrition in lupin in Australia, confirming that the plant is sensitive to potassium deficiency and less able to extract it from the soil than cereals. Potassium deficiency results in fewer number of pods per plant and, to a lesser degree, in less seeds per pod and smaller 1000-seed weight, although it has no effect on the protein content of the seed. Morphological symptoms specific to the deficiency (different depending on the species) may occur, especially in the older leaves; plants with potassium deficiency are more susceptible to Pleiochueta setosu. It is possible that this deficiency exists without showing external symptomsbut it can be determined by analyzing the plant and comparing the results with the critical levelsset by Cox ( 1978). However, this author noted little response by lupin to applied potash if soil potash levels are above 40 ppm. The normal application on the crop is between 50 and 120 kg of K20/ha (Lopez-Bellido, 1984). Potash may be leached in sandy soils by high rainfall. Cox (1978) concludes that in these soils the optimum application time is 4 weeks after germination, which coincides with root development. Germination may be reduced if potash is drilled with the seed due to an excess of salt, especially in humid soils which later have to suffer a dry period. The fertilizer potassium chloride does not affect lupin (Cox, 1978). Walton and Francis ( 1975) stated that the species L. angustifoliusis sensitive to manganese deficiency, producing a split seed disorder with seed coat rupture and a yield reduction. According to these authors splitting is associated to the genes “incundus” (low alkaloid content) and “tardus” (nonshattering pods) although both act distinctly and independently; the “tardus” gene only enhances this disorder. Bitter L. angustijioliusis almost splitting resistant. Walton (1 978) found that in manganese-free soil the concentration of the element in the seed was less than 10 ppm, and manganese deficiencies were found in the sweet lines. However, no phenotypes of L. consentinii showed any split seed symptoms. Walton (1978) suggested that the variationsamong the species is probably due to differencesin their ability to take up manganese and transport it from the vegetative parts to the seed,

LUPIN AS ALTERNATIVE PROTEIN SOURCE

279

which in L. angustifoh appears to be associated with the biochemical process of alkaloid synthesis. These problems can be overcome by the application of manganese sulfate ( 15 - 30 kg/ha). Early sowings with high plant densities and early flowering cultivars reduce the splitting disorder. The levels of copper, zinc, and molybdenum necessary for lupin are similar to those for wheat (Nelson el al., (1983). According to von Baer (1982) and Gross ( 1982a), lupin responds well to sulfur fertilizer such as magnesium sulfate, calcium sulfate, potassium sulfate, or superphosphate.

4. Irrigation Although lupin is a drought-resistant plant, it is sensitive to water stress at the beginning of vegetation before the development of the tap root (Girard and Lenoble, 1979). In irrigation trials it has been proved that watering before flowering does not influence yield but that later watering might, producing increases in branching and number of seeds per pod (Stoker, 1975). Girard and Lenoble (1979) and Plancquaert ( 1982) recommend 30 50 mm of water during flowering on the first lateral orders, which increases fruiting. Lemaire and Poulain (1 984) in France, with a good welldistributed rainfall, have obtained little benefit from irrigation and only in some years. Water at the end of flowering decreased yield while increasing seed final humidity, factors which are negatively correlated, and also makes the plant more susceptible to Fusarium ssp. and Botrytis spp. 5. Harvesting The morphology of the lupin plant with its rigid stem and high nonshattering pods makes for easy mechanical harvestingwith a conventional cereal harvester (Lenoble and Picard, 1980; Fuentes, 1985). Lodging is not frequent except in very humid region or in very good growing years (Shutov, 1980; Fuentes, 1985). In the USSR,plant growth regulators have been used satisfactorilyto avoid this problem (Shutov, 1980). Harvestingtakes place at the beginning ofsummer for the autumn -winter sowings, and at the end of summer or the beginning of autumn for spring sowing. Different problems emerge depending on sowing time. In the autumn sowings there may be shatteringso it is advisable to harvest as soon as the crop is ripe even though the base of the stem is still green. Harvesting in the cool of the mornings and evening reduces shattering and seed cracking (Nelson, et al., 1983; Postiglione, 1984). Frequently, spring sowings lead to maturation difficulties, especially in L. angustijXus it may be necessary to

280

L. LOPEZ-BELLIDO AND M. FUENTES

use drying or defoliant products such as diquat or paraquat (Withers, 1979c; Shutov, 1980). As the harvester may damage lupin seed, threshing must be very gentle so as not to crack the seed coat. The lowest drum speed and widest concave setting possible should be used (Withers, 1979c; von Baer, 1982; Nelson et al., 1983). D. PESTSAND DISEASES Although there are relatively few comprehensive and systematic studies on the distribution and importance of pest and diseases in lupin throughout the world, the recent works by Frey and Yabar (1983) and Plancquaert (1984) and information collected by Lopez-Bellido ( 1984) from a world questionnaire are referred to here. Most of the rest of the available information is on a specific pest or disease. Lupin is susceptibleto a wide range of parasities due to ecological diversity of the areas in which it is grown. The importance of these parasities depends on the purpose for which the lupin is cultivated. Pests and diseases, especially the latter, differ according to species of lupin and in some cases parasitic damage may be a limiting factor for the crop. Many of the parasites that damage lupin are not specific to it-they also attack other legumes and plants, creating continuous potential of infection under favorable conditions. Plancquaert ( 1984)has summarized the existing information on the different pests and diseases attacking four cultivated lupin species and the control methods in actual use (Tables XV and XVI). Lopez-Bellido( 1984) pointed out that frequently problems of identifyingthe parasite and the lack of knowledge of its biological characteristics lead to confusion about its species type and the methods to be used in its control. 1. Pests According to Lopez-Bellido ( 1984)aphids are found on sweet lupin lines in Australia, Brazil, Spain, and New Zealand and often transmit various virus diseases. Diverse species of Heliothis ssp. are found in Western Australia and South Africa where they cause important damage to buds, flowers and pods. Also found in numerous zones are soil insects which attack the seedlings, cut worms and mining insects which live on stems, leaves, and pods, and vertebrates such as birds and rodents which cause damage at the emergence and vegetative stage. In Spain larvae of Sitona ssp. cause severe damage in the Rhizobium lupini nodules.

28 1

LUPIN AS ALTERNATIVE PROTEIN SOURCE

Table XV Principal Pests in Lupin Speciesab Pests Sowing-emergence (soil insects) Lepidoptera: Agrotis sp. Feltia sp. Copitarsia turbata Diptera: Phorbia platura Tipula sp. Coleoptera: Adioristus sp. Agriotes spp. Astylus spp. Collembola: Sminthurus viridis Mollusca: Agriolimax agrestis Acari: Halotydeus destructor Vegetative period Lepidoptera: Ciampa arietaria Copitarsia turbata Heliothis punctigera Heliothis armigera Plusia chilensis Diptera: Liriomyza sp. Melangromyza sp. Ophiomyia sp. Phytomyza horticola Coleoptera: Epicauta sp. Sitona griseus Homoptera: Acrytosiphonpisum Acrytosiphon kondoi Aphis craccivora Myzus persicae Flowering harvest Lepidoptera: Heliothis punctigera Heliothis armigera Helicoverpa titicacae Leptotes callangae Peridroma saucia Etiella behrii Heteroptera: Calocoris norvegicus Adelphmoris lineolatus Lygus rugulipenuis Thysanoptera: Frankliniella spp. From Plancquaert ( 1984). X, Present in species.

L. albus

L. angustifolius

L. luteus

L. mutabilis

X X X X X X

X

X

X X

X

X X

X X X X X

X X X

X

X

X X X X X

X X

X

X

282

L. LOPEZ-BELLIDO AND M. FUENTES

Table XVI

Principal Diseases in Lupin SpeCiesab DiSeaSeS

Sowing-emergence Pythium sp. Rhizoctonia sp. Thielaviopsis basicola Vegetative period Ascochyta caulicola Ascochyta gossypii Ascochyta pisi Botrytis cinerea Colletotrichum gloeosporioides Erysiphe polygoni or pisi Pleiochaeta setosa Winter Spring Sclerotinia sp. Virus Bean yellow mosaic Cucumber mosaic Flowering harvest Fusarium oxysporum Fusarium japonicum Fusarium anguioides Phomopsis leptostromiformis Stemphilium vesicarum Uromyces sp.

L. albus

L. angustifolius

L. luteus

X X X

X X

-

X X X

X

-

-

X

-

-

X

X X

-

-

xx

xxx xxx

X

xxx X X

X X X

-

X X X ~~

X

xx

X X

xx

-

xxx

X

~

X

X X

xx xx xxx

L. mutabilis

X

X

X

X

~~~

From Plancquaert (1984).

* XXX,High susceptibility; XX,medium susceptibility; X,exists in species;-,

no existing

information.

Systematic treatments are not often used because the economics have not been evaluated satisfactorily; other methods employed are determined by crop techniques limiting populations. Yabar and Baca ( 1982) and Nelson et al. (1983) cited the biological control of Heliothis ssp. and other moths by using natural predators and parasites. In Western Australia Heliothis spp. are also controlled by spraying with DDT, carbaryl, endosulphan, permethrin, and fenvalerate, according to the size and number of caterpillars per square meter (Nelson er al., 1983). Plancquaert (1 984) warned about the dangers of carrying out certain chemical soil and seed treatments if the soil has been inoculated, citing the risk of affectingRhizobium lupini such as has occurred with omethoate.

LUPIN AS ALTERNATIVE PROTEIN SOURCE

283

2. Diseases The most widespread and severe lupin diseases are Pleiochaeta setosa (brown leaf spot) and Colletotrichumgloeosporioides(anthracnose). Brown leaf spot, which is found in Western Australia, France, and Brazil (Tomasini and Lhamby, 1982; Nelson et al.. 1983; Gondran, 1984), is most damaging in the preflowering period when it can cause severe defoliation. Chemical treatment of the seed accompanied by early spraying is the most efficient control method (Gondran, 1984). Anthracnose in Bolivia, Chile, Ecuador, Peru and Spain is considered by Frey and Yabar (1 983) and Lopez-Bellido (1 984) as the most frequent and damaging disease found in L. mutabilis. According to Frey (1 982) the fungus appears to be especiallyadapted to this lupin, as it did not infect other legumes during trials developingmore intensively at lower altitudes in the Andes. Therefore this author recommends seed production at altitudes above 3500 m and seed disinfection with triurame or captane and crop spraying. The investigations by Forbes and Wells .(196 1) found a genetic resistance to anthracnose in L. angustifolius;therefore it can be hoped that resistant lines exist within other species. Root rot (Fusarium,Pythium, Rhizoctonia complex) is also found in most of the lupin-growing countries: Australia, Andean region, Brazil, Hungary, United States, France, Poland, New Zealand, and the USSR (Frey, 1982; Tomasini and Lhamby, 1982; Belteky et al., 1983; Nelson et al., 1983; Lopez-Bellido, 1984). Although the severity of damage varies, in some cases it is a limiting factor for the crop. Russian authors have cultivars that are Fusarium ssp. resistant but until now the main method ofdiseasecontrol has been rotation (Lopez-Bellido, 1984). Other diseasesattackinglupin are Stemphylium vesicarium(grey leaf spot) found in Western Australia and where resistant cultivars are used (Nelson et a/., 1983);Erysiphessp. in South Africa, Peru, and Spain; rust in France and the Andes; Sclerotinia ssp. in Western Australia and Peru; and diverse virus diseases in Brazil, Poland, Australia, and New Zealand (Lopez-Bellido, 1984). Frey ( 1982) has found the presence of mycoplasmas (MLO) in Peru, which present symptomsof abnormal growth in the plant and a “greening of flowers.” A special mention must be made of the causal agent of lupinosis, Phomosis leptostromiformis,which is not significant as a parasitic fungus, but as a saprophyte. It grows on dead stubble and can cause problems by producing a mycotoxin that kills sheep (Nelson et al., 1983). The only satisfactory method to date of lupinosis control is stock management. Nelson et al. (1 983) reported that the principal disease control method is rotation, separating the two successive crops in the same soil as much as possible. The recommended year gap between lupin crops is as follows: 2

284

L. LOPEZ-BELLIDO A N D M. FUENTES

years in grey leaf spot, 2 -4 years in root rots and brown leaf spot, and 4 years in scelerotinia. Despite these recommendations some farmers have successfully grown lupin/wheat/lupin rotations for three to four cycles without suffering severe epidemics. However, as the lupin area increases, so will the risks as the fungal inoculum builds up. Further research is being conducted to determine if such tight rotation will provide sufficient disease break in the long term. This is an important research objective for the future.

V. CHEMICAL COMPOSITION AND USE OF LUPIN SEED A. CHEMICAL COMPOSITION

I . Protein Content Protein content varies among the distinct species, being approximately 30-50% of dry matter (Gross, 1982a). Among the cultivated species L. luteus and L. mutabilis have the highest values and L. angustifolius the lowest (Table XVII). Protein content is determined by multiplying total nitrogen by 6.25, but the result obtained maybe overvalued (especially when the alkaloid content in the seed is high) since the content of no-protein nitrogen in lupins is considerable (Hill, 1977; Gross, 1980). Lupin proteins are poor in sulfur-containing amino acids, which is characteristic of all legumes (Hill, 1977); the species L. albus may also be deficient in lysine (Gross, 1982b). Gross (1982b) has reported that the biological quality of protein in L. albus and L. mutabilis in relation to the protein efficiencyratio Table XVII Gross Composition of Lupin Seed" Percentage of dry matter Crude protein

Ether extract

Crude

Species

fiber

Ash

L. albus L. angustijolius L. consentinii L. luteus L. mutabilis

34.3-44.9 28.0-37.9 28.2-40.1 36.0-47.6 31.7-45.9

9.9- 14.5 5.3-6.6 3.3-4.4 4.0-7.1 13.1 -23.1

3.3- 10.0 13.0- 16.8 18.5-22.4 14.6- 17.6 7.4- 1 1.3

2.9-4.7 2.4- 3.9 2.4-3.8 4.0-5.2 3.0-4.5

~

~~

From Hill (1977).

LUPIN AS ALTERNATIVE PROTEIN SOURCE

285

(PER) is low, but can be improved by the addition of methionine (Savage et af., 1982, 1984b). Technical processing may cause considerable modifications in protein quality because the alkaline treatment to produce isolates destroys sulfur amino acids (mainly methionine), thereby greatly reducing PER values (Gross, 1982b).Cooking barely improves the protein quality as lupin has few antinutritive thennolabile substances. However, mixing with other foods can notably improve the protein quality, which may almost reach that of casein (Gross, 1982b). Research on the structure, composition, and biochemistry of lupin proteins have been carried out by Blagrove and Gillespie ( 1980), Cerletti et al. (1980), Caldwell et al. (1982), Casero et al. (1982), Duranti and Cerletti (1 982), Millan and Vioque (1 982), and Riccardi and Cerletti (1 982).

2. Oil Content The species L. albus and L. mutabilis have potential as oleaginous plants (the other speciesbarely reach 5% lipids in their composition).The speciesL. albus has an average of 1 1% lipids and L. mutabilis averages 19% lipids, making it viable for industrial extraction (Gross, 1982b). The most studied species in relation to oil content is L. mutabilis, which has a fatty acids composition intermediate between that of peanut oil and soya, with the typical characteristics of seed oil plants. It has a higher tocopherol content than sunflower oil, soya, and corn germ (Gross, 1982b).Hatzold et al. (1983) has reported on the chemical characteristics of refined L. mutabilis oil: Iodine index: 1 14 Saponification index: 188 Unsaponifiable (%): 1.04 Refraction index (40°C): 14,670 a - Tocopherol (ppm): 20 y - Tocopherol (ppm): 5 10 The coefficient P/S (polyunsaturated/saturated) is above the recommended 1.8 value. Hill ( 1977)review composition and nutritive value in lupin seed and Gross ( 1982a)and Feldheim (1 982) have studied the lipid composition.

3. Alkaloids and Other Toxic Substances There are numerous antinutritive substances in legume seeds which considerably diminish their nutritive value. In lupin, both seed and plant, the main obstacle to its use in food consumption are quinolizidine alkaloids

286

L. LOPEZ-BELLIDO AND M. FUENTES

which are bitter and toxic. These alkaloids belong to the lupininas group. The most important are lupinine, lupanine, sparteine,and hydroxylupanine (Gross, 1982b). Sparteineand lupanine are the most toxic. Although there is a diversity of information on the level of their toxicidity, the lethal dose is cited at between 1 1 and 46 mg/kg human weight (Gordon and Henderson, 195 I ; Hudson er al., 1976). The hemagglutinins have very little importance in lupin, showing a minimum hemagglutinin activity, 10 times less than soya and 1000 times less than bean. After thermal treatment there is no hemagglutinin activity as the lectins are destroyed (Contrerasand Tagle, 1974; Schoeneberger et al., 1980; Muzquiz el al., 1984). Studiesby Hudson (1979) and Hove and King ( 1979) have shown that trypsin inhibitors in lupin are not as important as in other legumes. Trypsin activity in L. murabilis is 1.16 U.I.T./ml (U.I.T., trypsin inhibitor unit) as compared to 30.1 U.I.T./ml in soya. Schoeneberger er al., ( 1980) also mentioned the presence of small quantities of cyanogenic glucosides (0.53-2.89 mg/100 g seed). This concentration is similar to soya and well below the permitted maximum quantity of 20 mg CHN/ 100 g (Montgomery, 1965). Work on saponins, sapogenins,and tanins have been carried out by Muzquiz et al. (1984) and Cassinello and Martinez (1982). 4. Other Components

Hill (1977), Cerletti and Duranti (1984), and Savage er al. (1984a) have determined the composition of carbohydrate, minerals, and vitamins in lupin. Carbohydratecontent varies between 20 and 30%,the principal component being cellulose which may surpass 10%of seed weight in small lupin seeds because of the high proportion of seed coat. One of the main breeding objectives is the reduction of the seed coat, which hinders transformation techniques and nutrition quality. Lupin seed may contain maximum averages of0.3%calcium, 0.27%magnesium, 0.6%phosphorus, 1.1% potassium, 1% sodium, and trace elements such as aluminum, boron, cobalt, copper, iron, manganese, molybdenum, and zinc; these contents vary, according to the distinct species (Hill, 1977; Burgano et al., 1982). Significant quantities of vitamin A @-carotene),niacin, thiamine, riboflavin, and especially choline are also present in lupin grain (Hill, 1977).

B. ANIMALNUTRITION The first physiological and nutritional trials on the use of sweet lupin in animal diets were carried out on 1930 (Mangold, 1950). At present there are

LUPIN AS ALTERNATIVE PROTEIN SOURCE

287

still aspects which are not clear in animal nutrition, such as the role of carbohydrates, presence of antinutritive substances, or the availability of vitamins (Hill, 1982). Guillaume (1980) has reviewed the current use of lupin in animal nutrition. To compensate for the deficiency of sulfur in the amino acids, lupin is mixed with other fodders. The most usual practice is to use lupin as a protein provider in the fodder ration at a level of 10- 20% of the total diet, depending on the type of the animal. The role differs according to whether lupin is used for ruminants or monogastrics, for which the main problems are still methionine deficiency and the high proportion of testa which is rich in fiber. Lupin may be used for ruminants as green forage, in grain, or as standing stubble for sheep. The situation is more complex in monogastrics in that lupin is limited by the methionine deficiency and the low nutritional quality of its carbohydrates. These carbohydrates, for unknown reasons, are practically undigestiblein birds. Teratogenic effects have been found when administered over long periods. Numerous alimentation trials have been carried out on weening piglets, swine, young calves, milking cows, lambs, rabbits, broiler and egg-laying hens, and even fish (carp and trout) to observe its advantagesand disadvantageswhen used to replace corn and soya (Herrera et al., 1980; Bogdanov et al., 1982; Cazes et al., 1982; Cubillos et al., 1982a,b; Lacassagne, 1982; Castaing and Seroux, 1984; Erickson and Elliott, 1984; Fekete, 1984; Huguet and Hoden, 1984; Raymond and Seroux, 1984; Vallade and Seroux, 1984).

C. HUMAN NUTRITION Utilization of lupin in human consumption is very complex because the first transformation products (Flours, oils, oil cakes, concentrates, and isolates) must later be elaborated to obtain products which respond to nutritional necessitiesand quality requirements(Pompei, 1984). Metabolic studies on human alimentation have been camed out in the last few years, mainly in South America, showing that the nutritional characteristics of lupin are similar to those of other legumes used in human food (Godomar and Reyes, 1984; Lopez de Romafia, 1984; Reina and Wittung, 1984). The nutritional protein value of lupin is significantly increased when supplemented by synthetic methionine at a level of 2% of total protein, but digestibility is decreased due to the poor action of proteolitic enzymes on the globulins (Lopez de Romafia, 1982). Diverse investigationshave shown that lupin, which is a low cost source of protein, is best used in combination with other foods. Lupin flour has been used in bread making, subsidizing 10- 20% of wheat flour ( Reyes et al., 1980; Zacarias et al., 1982; Gross et al., 1983b; Beirao da

288

L. LOPEZ-BELLIDO AND M. FUENTES

Costa, 1984; Godomar and Reyes, 1984). The bread obtained had a good volume and texture, pleasant color, high protein content, improved amino acid composition, and a pleasant aspect from the consumer point of view. Lupin is also employed in biscuit and cake making (Reynoso et al., 1982; Villegas et al., 1982) pastas (Ballini 1983; Lucisano and Pompei, 1984), lactic substitutes (Ivanovic et af., 1982), precooked foods, snacks, hamburgers, etc., and even incorporated into the production of baby foods (Lehmann and Moeller, 1982; Pompei, 1984). The oil of L. mutabilis has good nutritive qualities with a composition similar to that of other vegetable oils. Trials by Lopez de Romaiia (1982) demonstrated that it is more digestible than mixtures of soya and cotton oil.

VI. PERSPECTIVES The surface area of cultivated lupin in the world is approximately 2 million ha (Table XVIII) 50%in grain production and 50%in fodder and green manure. The countries with most area under cultivation are the USSR (53.3%), Australia (26.6%), and Poland (1 5.2%), which together represent 95.1% of the world's total. Australia is the first, in grain production and the USSR in fodder (Lopez-Bellido, 1984). The speciesL. luteus occupiesthe largest cultivated area, principally in the USSR and Poland with sweet cultivars. The species L. angustiJolius is the most widespread; it is sown in Australia, the USSR, Poland, South Africa, the United States, Brazil, Chile, and the countries in the Mediterraneanarea, mostly with sweet cultivars. The speciesL. albus is sown in lesser proportion in Europe, the USSR, South Africa, the United States, Brazil, and Chile using sweet cultivars, and also bitter ecotypes in their native region. Lupinus mutabilis is only cultivated in the Andes, its natural habitat; its adaptation to other areas has not been successful as yet (Lopez-Bellido, 1984). Although lupin has not received much attention in agricultural policies until now, many institutions both national and international have recently begun to show an interest in the crop. This interest is due to its potential as a low-cost protein source and as a soil improver in cultivation systemsin areas with poor soil and low rainfall. The Food and Agriculture Organization (FAO) is carrying out work through the International Board for Plant Genetic Resources on programs of collection, conservation, and evaluating germplasm in the Mediterranean and Andean zones. The German Agency for Technical Cooperation (GTZ) is sponsoring various investigations and

289

LUPIN AS ALTERNATIVE PROTEIN SOURCE

Table XVIII Surface Area of Lupin under Cultivation (ha)”

Country Africa South Africa North America United States South America Bolivia Brazil Chile Ecuador Peru Europe Germany, F.R. Spain France IMY Portugal Poland Oceania Australia New Zealand USSR Total a

Total area 3,500

Grain

Use as forage and green manure

3,500 3,700

9,700

-

700 52,500 4,480 953 5,500

700 12,000 3,940 953 5,500

100 3,000 2,000 4,654 5,000 285,000

100 1,800 1,950 4,654 4,700 135,000

I50,OOO

500,000 100 1,000,000 1,877,187

450,000

50,000

333,000 963,797

667,000 9 13,290

-

40,500 540

-

1,200 50

-

300

-

From Lopez-Bellido ( 1984).

development programs in South America, and recently, the European Economic Community (EEC) has incorporated lupin grain into its protection policy for protein plants, subsidizing its production and utilization for animal feed. In 1980, the International Lupin Association was founded in order to promote international cooperation and research in all aspects of the lupin plant. Scientists and technicians from 20 countries contribute to these objectives. Three internationalconferences have taken place in Peru in 1980, in Spain in 1982, and in France in 1984. ACKNOWLEDGMENTS We would like to thank Dorothyann Milne for her kind help in the translation of this article.

290

L. LOPEZ-BELLIDO AND M. FUENTES REFERENCES

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Contreras, S., and Tagle, M. A. 1974.Arch. Latinoam. Nutr. 24, 191 - 199. Cox, W. J. 1978.J. Agric. West. Aust. 19,27-31. Cubillos,A., Caceres,O., de Beer, C., Mora, S., and Mege, R. 1982a.Prm. Int. Lupin Conf, 2nd, Pp. 271 -275. Cubillos, A., Norambuena, L., Henriquez, O., von Baer, E., Gutierrez, J. A., and Sigmund, I. 1982b.Proc. Int. Lupin Con$, 2nd. pp. 276-280. Cuthbertson, E. G. 1976.Aust. J. Exp. Agric. Anim. Hub. 16,394-401. Dunn, D. B. 1955.Aliso 3, 135- 172. Dunn, D. B. 1956.Am. Midl. Nut. 55,443-472. Dunn, D. B. 1971. Trans. Mo. Acad. Sci. 5,26-38. Dunn, D. B. 1984.Proc. Int. Lupin Conf, 3rd, pp. 67-86.

LUPIN AS ALTERNATIVE PROTEIN SOURCE

29 1

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Index soil exchangeable,agronomic potential of phosphate rocks and, 104- 108

A

Acetohydroxamic acid, urease inhibition,

Caprylohydroxamic acid, urease inhibition,

Acidulation, partial, see Partial acidulation Africa, sub-Saharan, direct application of phosphate rocks in, 126- 131 Aldehyde-urea polymers, 226-228 Alkaloids, in lupin seed, 285-286 5-Amino- 1,3,4-thiadiazole-2-thiol, urease inhibition, 222 Aminocresols, urease inhibition, 221 Ammonia loss and toxicity, urea fertilizer and, 213-214 Ammonium bicarbonate, urea hydrolysis,

Carbohydrates, lupin seed,286 Carbon partitioning, crop simulation models and, 153- 154 Carbon dioxide fixation, crop simulation models and, 15 1 - 153 Catechol, urease inhibition, 222 Cercospora zebrina, 33 Chemistry phosphate rock guinea grass response to application, 99 reactivity, 95- 101 solubility in neutral and acid ammonium citrate, 97 sources, 94- 95 white clover, composition, 42-43 pChloromercuribenzoate, urease inhibition, 221 Climate lupin requirements, 258-260 white clover drought, 13-14 light, 1 1 temperature, 1 1 - 13 wind, 14-15 Clover, white, see White clover Clover canker, see Clover rot Clover cyst nematode, 35 Clover rot, 32 Collar rot, see Clover rot Collectotrichumgloeosporioides, 283 COMAX, see Crop Management Expert System Costelytra zealandica, 35 Cover crop, white clover, 28 Crop Management Expert System, 202-204 Crop morphology, simulation models and,

222

222

2 18-220

Ammonium citrate, neutral and acid, solubility of phosphate rocks, 97 Ammonium polyphosphate-urea mixtures,

228 Anthracnose lupin, 283 white clover, 33 Aschochyta imperfects. 33 Asia, direct application of phosphate rocks in, 131-134 Atmosphere, white clover nitrogen transfer and, 41 B

Banding, urea, 229-230 Benzoquinones, urease inhibition, 22 I 222 Biuret formation, urea and, 2 1 1 Black blotch, white clover damage, 33 Black patch, see Clover rot Boric acid-urea mixtures, 228 Breeding, crop simulation models and,

-

180-188

Brown leaf spot, lupin damage by, 283

156-158

C

Calcium

salts, urea and, 229

Cropping systems, lupin, 268- 269 Crop rotation, lupin for grain, 27 1 -273 for green manure or grazing, 269 - 27 1

297

298

INDEX

Crop simulation models applications artificial intelligence/expert systems, 202 - 204 breeding, 180- 188 herbicide injury, 193- 198 insect damage, 198- I99 on-farm, 199- 202 physiologicalprobe, I 89- 193 soil erosion, 188- 189 data acquisition controlledenvironment equipment, 172- 174 daily weather data, 171 experiments, 172 interpretation and analysis, 174 soildata, 171 hierarchical classification, 142 limits and stresses, 160- 16 1 model calibration, 174- 175 morphology, 156- 158 need for, 141- I46 pe~ts,169-170 phenology, 158- 160 physiology carbon dioxide fixation, 15 I - 153 light interception, 150- 151 partitioning, 153- 154 tissue expansion, 154- 156 process-level, table, 147- 149 sensitivity analyses, I78 - I79 soil processes effects of other chemicals, 169 evapotranspiration, 163- 166 heat fluxes soil surface, 166- 167 within soil, 167 mechanical impedance, I68 nitrogen transformation and movement, 168 oxygen content, 168 water movement, 161- 163 t w OF, 141- 146 validation data, 176 definitions, 175- 176 example, 177- 178 levels, 176 Crop yield, with two granulated phosphate rocks, 103

Crown rot, see Clover rot Curvularia trifolii, 33 Cymadothea trifolli, 33 D

2,4-D, white clover and, 30 2,4-DB, white clover and, 30 Decomposition, white clover nitrogen transfer via, 4 1 Defoliation change, white clover recovery and, 65 cutting, white clover and, 56 - 59 Deroceras reticulaturn, 36 Digestibility, and intake of white clover, 43-45 Dihydric phenols, urease inhibition, 22 1

Diseases

lupin, 280,283-284 virus, see Virus diseases white clover, 32-34 Distribution lupin, 242-243 white clover, 2 -4 Ditylenchus dipsaci, 34- 35 Drappa, urea coating with, 224-226 Drought effects on white clover, 13 - 14 resistance, lupin, 262 Dry matter accumulation, lupin, 248-25 I

E Eelwonn, stem, 34-35 Erysiphe ssp., 283 Erysiphe trifolii. 33 Evapotranspiration, in crop simulation models, 163-166 Excreta nutrient return, white clover and, 63-64 Expert systems, crop simulation models and, 202-204 F

Fertilizers lupin, 277-279 nodulation and nitrogen fixing, 252 urea banding, 229 - 230

299

INDEX efficiency improvement, 23 1 future trends in, 231 large pellets, 230-231 problems with ammonia loss and toxicity, 2 13- 2 14 biuret formation, 2 I 1 immobilization, 2 14 leaching, 2 12-2 13 management effects, 215-216 nitrite accumulation in soil,21 1-2 12 white clover, 24 nitrogen effect, 52 - 56 Fusarium ssp., white clover and, 33 0

GLYCIM model partitioning in, 154 sensitivity analyses, 178 soil erosion, 188- 189 tissue expansion in, 155 validation, 177 GOSSYM model breeding, 180-185, 188 and COMAX, 202 herbicide injury, 195 insect damage, 198- 199 on-farm decision making and, 20 I physiological probe, I9 I sensitivity analyses, 178- 179 soil erosion, 188- 189 validation, 177- I78 Grain, lupin for, 27 1 -273 Grass companion, for white clover, 29 guinea, response to phosphate rock application, 99 and white clover dynamics, 45-49 mixtures, 50-52,68 potential production, 68 Grass grub, white clover damage by, 35 Grass seed rates, white clover, 26-27 Grazing lupin, 269-271 white clover effects of, 59 - 60 excretal nutrient return, 63 - 64 nitrogen transfer via, 4 1 treading damage, 60

Green manure, lupin for, 269-271 Grey leafspot, lupin damage by, 283 Growth, lupin, 246 -248 Guinea grass, response to phosphate rock application, 99

H Harvest index, lupin, 254 Harvesting, lupin, 279-280 Heliothis ssp., 280,282 Herbicides injury, crop simulation models and, 193- 198 lupin and, 274-277 white clover recovery and, 65 -66 Heterodera trgolii, 35 Hydrolysis, urea, 2 16 - 2 17 Hydroquinone, urease inhibition, 222 Hydroxamates, urease inhibition, 222 -223 I

Immobilization, urea nitrogen, 214 Impedance, soil, mechanical, 168 Inflorescences lupin, 250 white clover, 9- 10 Inoculation lupin, 253 white clover, 24-26 Insect damage, crop simulation models and, 198- 199 Intake, and digestibility of white clover, 43-45 Irrigation, lupin, 279 IRRIMOD, sensitivity analyses, 178- 179 L

Latin America, direct application of phosphate rocks, 116- 126 Leaching, urea and, 2 12- 2 13 Leaf area index, lupin, 249-250 Leafspots, white clover damage by, 33 Leathejackets, white clover damage by, 36 Leaves, white clover, 5 -7 Legumes, role in protein production, 239-240

300

INDEX

Leptosphaerulina trifolii, 33 Light effects on white clover, 11 interception, crop simulation models and, 150-151 L i m a ssp., 36 Lime, white clover and, 24 Lupin agronomic potential, 260-262 breeding, 263-268 Andean, 266 narrow-leafed, 265 -266 objectives of, 266-268 white, 264 yellow, 264-265 climatic and soil requirements, 258-260 cropping practices fertilizers, 277-279 harvesting, 219-280 herbicides, 214-277 imgation, 219 sowing, 213 - 274 cropping systems, 268 -269 in crop rotation grain lupin, 27 1- 273 green manure and grazing, 269-27 I cultivated distribution, table, 267 world surface area, table, 289 diseases, 281,283-284 dry matter, 248-251 geographic distribution, 242- 243 grain yield components, 255-257 distribution, 254-255 harvest index, 254 growth pattern, 246-248 New World species, 245-246 nitrogen fixation, 251 -253 Old World species, 244-245 origin and history, 240- 242 pests, 280-282 seed

alkaloids and other toxic substances, 285 - 286 in animal nutrition, 286-287 in human nutrition, 287 -288 oil content, 285 protein content, 284-285

seeding rate throughout the world, 275 taxonomy, 243-244 Lupinosis, 283 M

Magnesium salts, urea and, 229 Management guidelines for white clover, table, 69 Management systems, urea response, 215-216 MCPA, white clover and, 30 MCPB, white clover and, 30 Methylurea, urease inhibition, 223 Microorganisms, white clover and, 19-20 Mineralization, white clover nitrogen transfer via, 4 1 Mineralogy, phosphate rock sources, 94 - 95 Minerals, lupin absorption and distribution, 250-25 I seed, 286 Models, crop simulation, see Crop simulation models Morphology, crop, simulation models and, 156-158 Mycoplasmas lupin, 283 white clover, 34 N

Nematodes, clover cyst, 35 Nitric acid-urea mixtures, 228 Nitrite accumulation, urea and, 2 1 1 - 2 12 Nitrogen excretal return, and white clover, 63-64 transformation and movement in crop simulation models, 168 white clover and, I8 repetitive application, 52- 55 strategic use, 52 - 55 Nitrogen fixation lupin, 251 -253 white clover amounts, 38 - 39 factors affecting, 39-40 transfer, 40-41 Nitrogen transfer, white clover, 40-4 I Nodulation, lupin, 251 -253

INDEX Nutrition, lupin seed animal, 286-287 human, 287-288 0

Oil content, lupin seed,285 Organic matter, soil, agronomic potential of phosphate rocks and, 108 Origins lupin, 240-242 white clover, 2 Oversowing, white clover, 66 - 67 Oxygen, soil, in crop simulation models, 168 P

Partial acidulation of phosphate rocks, 112-116 characteristics, I I3 - I 14 direct application inAsia, 131-134 in Latin America, 1 16 - 126 in Sub-Saharan Africa, 126- 131 reactions in soil, 114- I16 Pellets, urea, 230-23 1 Pepper spot, white clover damage by, 33 Pests in crop simulation models, 169- I70 lupin, 280-282 white clover, 34-36 Petroleum wax, urea coating with, 224-226 pH, soil agronomic potential of phosphate rocks and, 104- 108 effect on urea concentration and hydrolysis, 2 I7 white clover and, I6 Phenology, crop simulation models and, 158-160 Phenylureas, urease inhibition, 223 Phomosis leptostromi/ormis, 283 Phosphate rocks agronomic potential, factors affecting granulation, 102- 104 particle size, 10 1 - 102 rainfall, 1 10- 1 1 1 relative potential, 100 soil

30 1

organic matter, 108 pH, exchangeable calcium, and phosphorus retention capacity, 104- 108 test methodology, 109- 110 temperature, 1 1 1 - 1 12 chemical reactivity, 95- 101 direct application inAsia, 131-134 in Latin America, 116- 126 in sub-Saharan Africa, 126- 13 1 indigenous deposits in the tropics, 90-93 mineralogy and chemistry, 94-95 partial acidulation, 112-1 16 characteristics, 1 13- 1 14 reactions in soil, 114- I16 Phosphoric acid-urea mixtures, 228 Phosphorodiamidates, urease inhibition, 223 Phosphorodiamidinic acid, urease inhibition, 223 Phosphorotriamides, urease inhibition, 233 Phosphorus soil retention, agronomic potential of phosphate rocks and, 104- 108 white clover and, 16- 18 Plant density, lupin dry matter accumulation and, 249 Planting time, lupin dry matter accumulation and, 249 Plastic, urea coating with, 224-226 Pleiochaeta setosa, 283 Porina, white clover and, 35 Potassium, white clover and, 16- 18 Powdery mildew, white clover damage by, 33 Production potential of white clover and grass mixtures, 68 monocultures, 67 -68 Proteins content, lupin seed, 284-285 production, role of legumes, 239-240 Pseudopeziza ssp., 33 R

Rainfall, agronomic potential of phosphate rock and, 110- 1 1 1 Relative agronomic potential, phosphate rocks, 98- 100 Resin, urea coating with, 224-226

302

INDEX

Rhizobium lupini, 25 1 RHIZOS model, soil processes, 161 - I69 RICEMOD model, sensitivity analyses,

178-179

Root rot, lupin damage by, 283 Roots,white clover, 4- 5 Rusts lupin, 283 white clover, 33 S salonius, urea coating with, 224- 226 Sclerotinia root/wilt, see Clover rot Sclerotinia ssp., 283 Sclerotinia trifoliorum. 32 Seed production, white clover, 36-38 Seeding rate, lupin, 275 slot, white clover, 66-67 Sensitivity analyses, crop simulation models, 178- 179 Silica, urea coating with, 224- 226 SIMCOT I1 model breeding, 180, 183 physiological probe, 190 Simulation models, crop, see Crop simulation models Sitona ssp., 280 Slugs,white clover damage by, 36 Soil agronomic potential of phosphate rocks and organic matter, 108 pH, exchangeable calcium, and phosphorus retention capacity,

104- 108

temperature, in crop simulation models surface heat fluxes, 166- 167 within-soil heat fluxes, 167 white clover and microorganisms, 19- 20 nitrogen, 18 PH, 16 phosphorus and potassium availability,

16- 18

physical, 15-16 trace elements, 18- 19 Solubility and crop yield with two granulated phosphate rocks, 103 phosphate rocks in neutral and acid ammonium citrate, 97 Sooty blotch, white clover damage by, 33 Sowing lupin, 273-274 white clover depth, 27-28 oversowinghlot seeding, 66- 67 time of, 27 Spring black stem, white clover, 33 Stemphylium sarcinaejbrme, 33 Stemphyhm vesicarium, 283 Stolons, white clover, 7 - 9 Sub-SaharanAfrica, direct application phosphate rocks in, 126- 1 3 1 Sulfhydryl reagents, urease inhibition,

221 -222 Sulfur, urea coating with, 224- 226

Summer blackstem, white clover, 33 T

test methodology, 109- 110 Taxonomy, lupin, 243-244 amelioration, white clover recoveryand, 65 Temperature data, in crop simulation models, I7 1 effect on erosion, crop simulation models and, 188urea concentration and hydrolysis, 217 189 white clover, 1 1 - I3 lupin requirements, 258- 260 lupin floral initiation and, 247-248 mechanical impedance, 168 phosphate rock agronomic potential and, nitrite accumulation, urea and, 2I 1 - 212 I 11-1 12 nitrogen, lupin nodulation and nitrogen soil,in crop sirnulation models fixing, 252 surface heat fluxes, 166- 167 oxygen content, 168 within-soil heat fluxes, 167 reactions of partially acidulated phosphate I ,3,4-Thiadiazole-2,5dithioI, urease rocks in, 114-1 16 inhibition, 222

lNDEX Thiophosphonc acids, urease inhibition, 223 Thiourea-urea mixtures, 229 Thiourea, urease inhibition, 223 Tipula ssp., 36 Tissue expansion, crop simulation models and, 154-156 Toxic substances, in lupin seed, 285-286 Trace elements, white clover and, 18- I9 Trifolium repens L., see White clover Tropics direct application of phosphate rocks Asia, 131-134 Latin America, 1 16- 121 sub-Saharan Africa, I26 - I3 1 indigenous phosphate rock deposits, 90-93

303 V

Validation of crop simulation models data needed for, 176 definitions, 175 - 176 example, I 77- 178 levels, 176 Vernalization, effect on lupin floral initiation, 247 Vesicular arbuscular mycorrhizal fungi, white clover and, 20, 25-26 Virus diseases lupin, 283-284 white clover, 33-34 Vitamin content, lupin seed, 286 W

U

Urea agronomic importance, 2 10 efficiency alteration banding, 229 - 230 hydroxamates, 222 -223 large pellets, 230-231 mixtures with other chemicals,228 -229 structural analogs and related compounds, 223 -224 sulfhydryl reagents, 22 I -222 sulfurcoating, 224 -226 urea-aldehyde polymers, 226-228 efficiency as fertilizer benefits, 2 10 future improvements, 23 1 problems, 210-21 1 fertilizers, problems with ammonia loss and toxicity, 2 I 3 - 2 14 biuret formation, 2 11 immobilization, 2 14 leaching, 212-213 management effects, 2 15 -2 16 nitrite accumulation in soil, 2 I 1-2 12 hydrolysis, 2 16 - 2 I 7 reactions in soil, 218-220 Urea-aldehyde polymers, 226-228 Urea amidohydrolase, see Urease UreaSe field and simulated studies, 2 17-2 I 8 laboratory studies, 216-217 Uromyces ssp., 33

Water level, effect on urea concentration and hydrolysis, 2 I7 movement, in crop simulation models, 161-163 stress, lupin dry matter accumulation and, 249 Weather data,in crop simulation models, 171 Weed control, white clover and, 29 - 32 White clover balance sheet for and against, table, 72 chemical composition, 42-43 climate, 10- 15 drought, 13-14 light, I I temperature, I 1- 13 wind, 14-15 companion grass, 29 cover crop, 28 cutting defoliation effects closeness of, 58-59 frequency, 56-58 d i m , 32-34 fertilizer nitrogen effect repetitive application, 52-55 StrategicW, 55 - 56 and grass dynamics, 45 -49 mixtures, 50-52 grass seed rates, 26-27 grazing, 59-60 excretal nutrient return, 63-64

304 selective, 61 -63 treading damage, 60-6 1 inconsistency, major causes, table, 49 inflorescences,9 - 10 inoculation, 24-26 intake and digestibility, 43-45 leaves, 5 - 7 lime and fertilizers, 24 management guidelines, table, 69 monocultures, 50, 67-68 nitrogen fixation amounts, 38-39 factors affecting, 39 -40 transfer of, 40- 4 1 origins, 2 pests, 34-36 potential production grass mixtures, 68 monocultures, 67-68 present use, 2-4 recovery management defoliation practice, 65

INDEX herbicides and, 65 -66 oversowing/slot seeding, 66-67 soil amelioration, 65 roots, 4 - 5 seed production, 36 - 38 soil factors affecting microorganisms, I 9 - 20 nitrogen, 18 PH, 16 phosphorus and potassium availability, 16-18 physical, 15 - 16 trace elements, 18- I9 sources of seed supply, table, 4 sowing depth, 27-28 time of, 27 stolons, 7-9 varieties, 20 - 24 weed control, 29 - 32 Wind, effects on white clover, 14- I5 Wiseana cervinata, 35