Crop improvement for tropical and subtropical Australia: Designing plants for difficult climates

Field Crops Research, 26 ( 1991 ) 113-139 Elsevier Science Publishers B.V., Amsterdam

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Crop improvement for tropical and subtropical Australia: Designing plants for difficult climates R.J. Lawn and B.C. Imrie CSIRO Division of Tropical Crops and Pastures, The Cunningham Laboratory, 306 Carmody Road, St Lucia, Qld 4067, Australia

ABSTRACT Lawn, R.J. and Imrie, B.C., 1991. Crop improvement for tropical and subtropical Australia: Designing plants for difficult climates. Field Crops Res., 26:113-139. The use of physiological understanding in crop breeding in northern Australia is discussed, and is illustrated with examples from several summer grain crops including soybean (Glycine max - - an oilseed ), mungbean ( Vigna radiata/V, m u n g o - a grain legume) and sorghum (Sorghum bicolora cereal). These, and most of the summer grain crops being developed in the region, are relatively recent additions to Australian agriculture, and in some cases to the tropics, or to mechanized agriculture in the tropics. Most are strongly sensitive to photoperiod and temperature. A primary aim, therefore, has necessarily been to improve their adaptation to tropical and subtropical environments characterized by generally warm temperatures and relatively short photoperiods. At the same time, constraints imposed by stressful temperature extremes, and frequent water-deficits as a result of limited and highly variable seasonal rainfall, have had to be addressed. The latter constraint has been compounded by soils that often have limited water-storage capacity. Genetic improvement has been confounded by large and often nonsystematic genotype X environment (gX e) interaction, which increases the testing necessary as a basis for selection. The most valuable contribution of physiological understanding has been to assist interpretation of g × e interaction in terms of biological, as opposed to statistical, models. Physiological interpretations have been both qualitative and quantitative in nature, and 'models' range from simple to complex, but nonetheless enable predictive inference to be drawn of the performance of particular genotypes in specific environments. Physiological research is thus being used to identify the key physiological and climatic constraints to productivity confronting crop improvement, to establish strategies for agronomic and breeding research, and to formulate 'dynamic' ideotypes to assist the breeder to match crop life-cycles to the resources and constraints of target environments. Physiological understanding also offers the potential to exploit traits conferring resistance to specific stresses but, to date that potential remains largely unrealized.

INTRODUCTION

Crop improvement, in its broadest sense, involves the manipulation of both the crop germplasm and the production environment. The aim is to increase, through plant breeding, the genetic potential for performance (generally and in specific environments) and, through agronomy, to aid the realization of that potential. While the record shows that agronomic and breeding advance 0378-4290/91/$03.50

© 1991 - - Elsevier Science Publishers B.V.

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TABLE 1 Summer grain crops grown in tropical and subtropical Australia and the status of local improvement activity Crop

Species

Vigna angularis (Willd.) Ohwi and Ohashi Black gram mungbean V. mungo (L.) Hepper Cowpea V. unguiculata (L.) Walp. Greengram mungbean V. radiata (L.) Wilczek Groundnut Arachis hypogaea L. Guar Cyamopsis tetragonoloba ( L. ) Taub. Maize Zea mays L. Millet Pennisetum americanum ( L. ) Leeke Dry/culinary bean Phaseolus vulgaris L. Pigeonpea Cajanus cajan (L.) Millsp. Rice Oryza sativa L. Sesame Sesamum indicum L. Sorghum Sorghum bicolor (L.) Moench Soybean Glycinemax (L.) Merrill Sunflower Helianthus annuus L.

Improvement activity

Adzuki bean

Introduction and evaluation Introduction and evaluation

) ~ Hybridization and selection Introduction and evaluation Hybrid development Introduction and evaluation ] Hybridization and selection Introduction and evaluation Hybrid development Hybridization and selection Hybrid and OP development

ics are also outlined. Throughout, examples are drawn primarily from those grain crops widely recognized as being 'tropically adapted' or 'summer grown', and for which there has been some local improvement effort (Table 1 ). The general production of summer crops in northern Australia has been reviewed by Wood and Fukai (1982). Special emphasis here is placed on soybean ( Glycine max, an oilseed ), mungbean ( Vigna radiata/V, mungo, a grain legume ) and sorghum (Sorghum bicolor, a cereal). Temperate crops such as the winter cereals, although widely grown as far north as the Queensland Central Highlands, are considered by Richards ( 1991, this volume). EXPLOITING PHYSIOLOGY IN CROP IMPROVEMENT

The rationale for exploiting physiological understanding in crop improvement in the tropics has been widely canvassed (e.g. various authors in Byth and Mungomery, 1981; and Shorter et al., 1991 ). Briefly, the efficiency of crop improvement can be enhanced through the elimination in advance of many of the 'errors' in 'trial-and-error' methodology. To this end, plant breeders have developed a range of useful analyses which enable responses to be described, and predictive inference to be drawn, from data on the comparative performance of breeding lines across environments. Most usually, these involve the statistical partitioning of the phenotypic performance (P) of in-

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dividual entries or 'genotypes' in a specific environment, into genotypic (g), environmental (e) and g × e interaction components:

P=g+e+ ( g x e )

( 1)

The g and e components are derived, respectively, from the performance of that genotype in other environments, and of other genotypes in that environment. Much can be inferred from g and e, particularly where each can be divided into subcomponents which would enable untested genotypes or environments to be assigned pro tempore to specific response types. For example, environments might be subdivided on the basis of any climatic, edaphic or biotic factors identified as being associated, whether casually or causally, with specific responses. Analogously, genotypes can be classified on phenotypic attributes correlated with specific responses. To be useful to the plant breeder, it is not necessary that the basis of associations between performance and environmental and/or phenotypic factors be physiologically understood. Rather, the main concern is that they be strong. Where some physiological understanding is established, however, these relationships provide a more useful tool for plant improvement. The relative importance of environmental as opposed to genetic constraints can be more readily established, and the most appropriate improvement strategy (i.e. agronomy a n d / o r breeding) adopted. In turn, breeding objectives and selection criteria can be more directly defined in terms of the specific traits or processes required; that is, in Donald's (1968) terms, an 'ideotype' can be formulated of the desired phenotype. Genotypes known to possess the desired responses can be included as parents in the crossing program, thus ensuring genetic variability within the breeding population. Given explicitly defined selection criteria, the choice of test locations to discriminate effectively between genotypes is made easier and, in many instances, efficient artificial screening techniques can be developed. The 'ideotype' is thus only one of several ways in which physiology can contribute to crop improvement. Attempts to exploit 'ideotypes' have not of course been universally successful. In part, problems have arisen because the understanding on which some ideotypic concepts were founded later proved to be less complete than originally recognized, and breeders were directed into 'blind-alley' breeding. The ideotype is also less effective in instances where homeostatic mechanisms of one form or another exist, and the same outcome may be achieved via several alternative ideotypes. However, probably the most serious criticism which can be made of ideotypes is that they are frequently 'static', and do not take into account g × e interaction. As such, they deny the breeder the opportunity to exploit specific adaptation. Stated another way, different ideotypes may provide optimal solutions in different environments. It is possible, however, to use physiological understanding to help interpret g × e interaction, and so assist the breeder to address the most difficult task of

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plant improvement: predicting the phenotypic performance of particular genotypes in specific environments. The g × e interaction term in equation ( 1 ) is in effect the deviation of the individual entry in a specific environment from expectation based on knowledge o f g and e. As such, it is extremely difficult to interpret and, more importantly, to predict. In a few situations, mainly where environmental effects are due to variation in a single limiting factor, g×e can be systematic, and amenable to prediction using regression approaches such as those of Finlay and Wilkinson (1963) and Eberhart and Russell (1966). To enable an a-priori prediction of g × e, some understanding is obviously required not only of the key environmental factors conditioning adaptation to the target environment (s), and the physiological processes or traits influenced by those factors, but also the nature and extent of differential genotypic response to those factors. In its most sophisticated form, this understanding may be formalized into mathematical models, directly relating physiological response to variation in environmental factors, and with genotypic differences manifested as parameter constants. Thus, phenotypic performance (P) is now expressed as some direct function ofg and one (or more) environmental factors, ei: P = (g, ei)

(2)

Ideally, knowledge of the genetic basis and heritability of the variation reflected in the parameters of differing genotypes can assist the development of more effective breeding strategies. The ability to predict the performance of individual genotypes in specific environments opens up the potential to exploit specific adaptation, and is thus useful in programs targeting a range of diverse environments. It is especially relevant in the development phase where crops are being extended into new production environments, as is the case for many crops in northern Australia. It also provides the opportunity for developing 'dynamic' crop plant ideotypes, which implicitly recognize that optimal solutions may differ between environments. Clearly, however, the validity of dynamic ideotypes still depends as much on the quality of the understanding on which they are founded as does that of earlier 'static' ideotypes. To what extent, then, is physiological knowledge contributing to genetic improvement of grain crops in the tropics? In order to address this question, it is useful to examine the key climatic features and constraints to crop performance in the tropics and subtropics. MAIN CLIMATIC FEATURES

Detailed climatic descriptions of the tropics and subtropics of northern Australia are available in surveys published by the Australian Bureau of Meteorology. Sample comparisons of the climatic statistics at specific sites within

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TABLE2 Estimated times to emergence of summer grain crops at mean temperatures of 16 ° C, 18 ° C and 25 ° C, based on experimental estimates of base temperatures (Tb) and thermal time to emergence of Angus etal. (1981) Crop

Sunflower Cowpea Sorghum Millet Mungbean Dry/culinary bean Maize Adzuki bean Soybean Pigeonpea Guar Groundnut Sesame Wheat

Days to emergence at: 16oc

18°C

25°C

8.3 8.6 8.9 9.4 9.5 9.6 9.8 11.5 11.6 18.2 24.9 28.3 -5.8

6.6 6.1 6.5 6.4 6.9 7.0 7.4 8.6 8.7 11.2 9.8 16.2 10.1 5.0

3.9 3.1 3.3 3.0 3.5 3.6 4.0 4.6 3.6 4.8 3.1 6.5 2.3 3.5

Tb (°C)

Thermal time ( ° C d > Tb)

7.9 11.0 10.6 11.8 10.8 1.06 9.8 9.9 9.9 12.8 14.7 13.3 15.9 2.6

66.9 43.0 47.9 39.5 49.6 52.1 60.8 69.9 70.5 58.2 32.4 76.3 21.3 77.9

decreases and the frequency and severity of frost increases from north to south, and with elevation. Rainfall is predominantly of summer incidence throughout the region. However, the pattern changes from distinctly summer occurrence (mid-November-mid-April) in the tropics, to one with an increasing component of winter rainfall at higher latitudes. In southern Queensland, some 30-35% of the average annual rainfall occurs during the period April-September. In the eastern tropics and subtropics, summer rainfall isohyets decrease rapidly from > 2000 mm on the northeast tropical coast to < 100 mm in southwest Queensland, while winter rainfall isohyets decline rapidly from > 400 m m on the southeast coast to < 20 m m in northwest Queensland. The combined effect of these patterns is that average annual rainfall decreases with distance inland from the coast. In coastal and subcoastal regions, however, there is large variation in annual rainfall, reflecting the local configuration of mountain ranges. In the tropical northwest, average annual rainfall decreases sharply north/south, from > 1600 m m around Darwin (12°27'S) to <600 m m at Daly Waters ( 16 ° 16' S ). Throughout the region, rainfall is highly variable, in terms of annual totals and regional and temporal distribution, with variability generally increasing as the average annual total decreases. Much of the summer rainfall occurs during storms, so that intensity can be high and, particularly in the tropics, cyclonic influences can result in a significant proportion of the average an-

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nual rainfall occurring within a few days. Intermittent droughts are therefore common during crop growth, and effects on productivity, depending on soil water balance, are potentially severe. Indeed, with the exception of small areas where irrigation is available, water deficit provides the major climatic constraint to summer cropping. Effective crop establishment depends on the timely occurrence of adequate, but not excessive, sowing rains and is thus a particularly vulnerable period. At maturity, seed quality of some crops is adversely affected by humid, wet conditions during maturation. Evaporative demand is high throughout the year in the tropics, and during the summer in the subtropics, generally reflecting the patterns of seasonal and regional variation in temperature. Accordingly, Wood and Fukai ( 1982 ) suggest the lower rainfall limits for annual rainfed cropping are the 500-mm isohyet in southern and central Queensland, the 600-mm in northern Queensland, and the 700-mm in northwest Queensland, the Northern Territory and northern Western Australia (see Fig. 1 ). To summarize, climatic conditions in the tropics are broadly favourable for irrigated cropping of'summer' crops during most of the year. However, rainfed cropping can be contemplated only during the summer season. Even then, productivity is likely to be substantially limited by intermittent droughts and, occasionally, by excessive rainfall. In the subtropics, temperature constrains the favourable period to the summer 6-8 months, when again periods of intermittent drought pose a serious constraint to the productivity of rainfed crops. The problems of water-deficit are compounded over much of the area by soils with low water-storage capacity (Williams et al., 1985 ). DEFINING SPECIFICCONSTRAINTS A historical feature of crop improvement in tropical Australia is that many of the summer grain crops were relatively new to Australian agriculture. Indeed some, such as mungbean and pigeonpea, were relatively new to mechanized agriculture, while others such as soybean and sorghum were relatively new to mechanized agriculture in the tropics. Thus knowledge was limited, compared with, say, the temperate cereals, as were opportunities for translating experience from overseas. Further, many of the tropical crop species are relatively more sensitive to photoperiod and temperature, and are therefore more specific in their adaptation (Roberts and Summerfield, 1987 ). The sensitivity of the summer crops, combined with the large climatic variability across years and regions, confronted crop improvement with large and often non-systematic g × e interaction (e.g. Byth and Mungomery, 1981; Imrie and Butler, 1982 ). A general priority with most summer grain crops has therefore been to develop better understanding of the factors affecting, and limits to, the adaptation of each crop, and to identify the key constraints to productiv-

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ity in particular environments. The aim has been both to extend adaptation into new areas and to improve productivity in existing ones. The experience in adapting soybeans to the lower latitudes illustrates the specific constraints faced with many species, and also the role of physiological research in identifying them. Initial attempts to grow soybeans in southern Queensland, using cultivars and agronomic strategies from the southern U.S.A. for sowing date, plant populations and row spacings, were largely unsuccessful (Gray, 1955 ). Yields were generally low, and variable across locations and sowing dates, and it was generally concluded that the introduced cultivars were 'unadapted' to the subtropics. Analysis of the growth and development of a range of soybean genotypes across locations and sowing dates established that the temperate cultivars flowered too rapidly. Growth was thus inadequate to ensure canopy closure and maximum radiation interception during reproductive growth (Lawn and Byth, 1974). The main problem was that, at 27-28 °S, mid-summer photoperiods were somewhat shorter than the latitudes for which the U.S. cultivars were bred (32-36 °N). Several environmental and management factors exacerbated this problem. Like the U.S. crop, the local soybean crop was largely rainfed. However, the greater unreliability of adequate sowing rains meant that sowing was rarely possible before late November, and was often delayed beyond late December (summer) whereas the U.S. crop was generally sown in April-May (spring). The local crop thus encountered inductive conditions, and flowered sooner. Even where irrigation was available, as in the Namoi Valley in northwestern New South Wales, early-sown crops were likely to encounter heatwaves during flowering, so that December sowings were preferable (Constable, 1977 ). The effect of a shorter growth period was exacerbated by the initial use, as in the U.S., of wide (75-100 cm (30-40 in)) row spacings (Lawn et al., 1977). Indeed, the use of narrow rows (50 cm or less), and higher plant populations, particularly when sowing was delayed beyond midDecember, proved adequate to compensate for the reduced vegetative development. Thus, whereas cultivars specifically bred for local conditions now predominate, the Australian soybean industry was founded, and depended for many years, on marginally adapted U.S. cultivars. The soybean research in the subtropics established several general principles which simplified later improvement strategies in the tropics (Garside et al., 1985). Controlled-environment (Byth, 1968 ) and field (Lawn and Byth, 1973 ) studies showed that photoperiodic effects are largely responsible for differences in time to flowering of genotypes of tropical vs temperate origin. In the subtropics, tropical lines develop slowly and flower later, because prevailing daylengths exceed their critical photoperiods (Pc); Pc is shortest, and photoperiod sensitivity generally greatest, in the 'most tropical' lines. Generally, the rank order for time to flowering among genotypes remains consistent over sowing dates. However, the dispersion between genotypes is greatest for

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sowings made before the summer solstice, and least for late-summer sowings. These generalized effects are modulated by variations in temperature. In general, warmer temperatures speed development (although later research (Mayers, 1989) has shown that mean daily maximum temperatures > 30°C may be supra-optimal and delay flowering). Photoperiod and, to a lesser extent, temperature also vary in a regular pattern with latitude, with predictable effects on genotype responses. The pattern described above persists (Fig. 2), but the absolute time to flower and the degree of dispersion between genotypes varies. When moved to higher temperate latitudes where midsummer photoperiods are longer, and temperatures, if anything, are cooler, all lines will flower later, and genotypic differences tend to be exaggerated. Conversely, all lines become earlier-flowering in the tropics, with genotypic differences compressed. Although there are some genotypic differences in the duration of the postflowering phase in soybean, total duration is highly correlated with time to flowering. Further, among genotypes at any one location, total biomass production is largely a function of total duration (Lawn and Byth, 1974). However, harvest index (HI) is greatest in early genotypes and decreases with longer duration, a response observed in several photoperiod-sensitivespecies. Thus, optimal genotype duration in terms of seed yield (and in the absence of water deficits), represented a compromise between high HI, and a phenological potential adequate to ensure closed canopies at 'moderate' densities (Lawn et Days to flowering 140

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Date of sowing Fig. 2. Effect of latitude and sowing date on time to flowering of two soybean genotypes, Gilbert (tropical, squares) and Semstar (subtropical, circles) sown at two-weekly intervals from midOctober to early February at latitudes 31°39'S (Perth, dotted lines) and 27°37'S (Redland Bay, broken lines), and at various intervals between early December and late March at latitude 15 ° 39'S (Kimberley Research Station, solid lines). (Perth data courtesy P. Farrington; KRS data courtesy D.F. Beech; Redland Bay data from Lawn and Byth, 1973 ).

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al., 1977 ). Not surprisingly, optimal sowing density tended to be greater for earlier cultivars, and greatest yield potential was achieved from dense sowings of moderately early genotypes. Under rainfed conditions, however, optimal crop duration depends more on the availability of adequate soil water, and thus may be shorter than under irrigated conditions (Fig. 3 ). These generalized relationships also apply when soybean is grown as a dryseason crop (Mayers, 1989), but with some additional complications. During the dry, the seasonal profile of photoperiod and temperature change is the reverse of that encountered during the summer or wet season. Crops sown in May flower in July-August, the coolest time of the year, and mature in September-October, when photoperiods are > 12 h and lengthening. Temperature rather than photoperiod is the main environmental factor affecting rate of development toward flowering, because days are shorter than Pc for all but the most 'tropical' genotypes. Flowering is therefore induced rapidly in warmer years, and HI is maximal. However, the yield of all but the latest genotypes is constrained by low biomass, even at sowing densities approaching 1 X 106 plants ha -1. The constraint imposed by rapid development is illustrated through the experimental use of artifical lighting to extend daylength and increase phenological potential and yields (Fig. 4 ). In contrast, minimum temperatures in cooler years can be low enough to delay flowering by as much as a month, but not to slow crop growth rates. Thus, the duration of vegetative growth is extended and seed yield potentials in cooler years approach those of wet-season crops. An additional constraint is that dry-season crops maturing after 21 September encounter photoperiods longer than those experienced S e e d yield (t h a -1) (a) Y - 0.31 ÷ 0.026 D

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Fig. 3. Seed yield (Y) as a function of total crop duration (days) for ten soybean genotypes grown during the wet season of the Australian tropics (a) under irrigation in the Ord Irrigation Area ( 15 ° 39'S) and (b) as a rainfed crop in the Douglas Daly region of the Northern Territory (13°48'S). (After Lawn et al., 1985).

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Fig. 4. Relationship between total dry-matter production (Y) and total crop duration (D), for six soybean genotypes grown during the dry season in the Ord Irrigation Area with ( + ) and without ( O ) extension of the diurnal photoperiod to 14 h for 28 days post-emergence, using 100-W incandescent lights. (Data courtesy J.D. Mayers).

by summer-grown crops at any latitude. The consequences are delayed and uneven maturity of pods, and reduced HI (Mayers, 1989 ). The general experience with soybean provided a model for improvement of other legume crops such as pigeonpea and mungbean. Indeed, research on both these new crops has shown much analogy with soybean, particularly in terms of the interrelation between photothermal sensitivity and adaptation (Byth et al., 1981; Imrie and Butler, 1982). Unlike soybean however, pigeonpea and mungbean were also novel to mechanized agriculture, and there was no large body of published experience elsewhere to guide their development. The situation with sorghum also has many analogies with that of soybean. Again, early development of the industry in Australia relied heavily on germplasm and experience from warm temperate areas in the U.S.A.; and again, sensitivity to photoperiod and temperature has been of major importance in conditioning the adaptation ofgenotypes across seasons and latitudes (Done, 1986; Myers et al., 1986a, b; Hammer et al., 1989 ). Thus, introduced temperate hybrids have exhibited poorer adaptation as they have been moved further into the tropics (Millington et al., 1977; Done, 1986). Myers et al. (1986b) believe that manipulating maturity through photoperiod sensitivity provides the 'major resource' available for plant breeders in adapting sorghum to new environments. In general, sorghum has proved less sensitive to photoperiod than soybean and the grain legumes, and many U.S. hybrids have proved reasonably adapted over a range of warm-temperature to subtropical latitudes. Many of these temperate hybrids appear to be essentially photoperiod-insensitive in the

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tropics and subtropics, although some analyses (e.g. Keefer, 1986a; Myers et al., 1986a) suggest they may not be entirely so. As with soybean, the main effect of photothermal regime is to alter phenological potential through effects on the timing of anthesis (Myers et al., 1986a). Warmer temperatures tend to favour rapid development, although again, temperatures > 30 °C may be supra-optimal (Muchow and Coates, 1986). Warmer temperatures also tend to reduce tillering (Myers et al., 1986a). In photoperiod-sensitive lines, photoperiods greater than Pc delay initiation, and increase the accumulated thermal time (day-degrees, °C d) and therefore vegetative growth potential, prior to anthesis. Total duration is highly correlated with time to flowering, and in turn, total biomass production is closely related to growth duration (Myers et al., 1986b). Thus, as temperate lines are moved into the tropics, the combination of shorter days and warm temperatures favours rapid initiation and reduced vegetative growth (Muchow and Carberry, 1990). This cannot be offset entirely by increased sowing density (Done, 1986). Likewise, when crops in the subtropics are sown in January rather than late October, more rapid development reduces phenological potential and optimal sowing densities may be higher (Herbert et al., 1986 ). There is evidence, also, of photoperiodic effects on HI in sorghum. For example, there is frequently a negative correlation between HI and time to flowering (e.g. Henzell et al., 1984), while in the tropics, HI is greater in the dry season (Done, 1986). IMPROVING

CLIMATIC ADAPTATION

Improvement programs with the summer grain crops have embraced one (sometimes both) of two strategies for improving adaptation to the highly variable and frequently stressful climates of the tropics: matching the crop to the resources and constraints of the environment; or breeding for tolerance of, or resistance to, stressful extremes. Matching the crop to the environment

The strategy here is to optimize productivity by matching the ontogeny of the crop to the climatic resources of the environment, and, where less favourable conditions are unavoidable, by minimizing the risk of their coincidence with more vulnerable stages. Perhaps not surprisingly, given that the main constraints to date have been due to poor phenological adaptation of crop cultivars in the Australian subtropics and tropics, this strategy is being widely exploited. It is most effective where the distribution of favourable (or, more accurately, of distinctly unfavourable) conditions is generally seasonal, or at least reasonably predictable. In most species, phenology is modulated by photoperiod and temperature, through effects on rate of development toward flowering analogous to those

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discussed above for soybean and sorghum, although effects can occur during other stages of ontogeny. Further, like soybean and sorghum, most summer grain crops are quantitative short-day plants (Roberts and Summerfield, 1987 ), although in most, insensitive or day-neutral genotypes also exist or have been bred (e.g. Stephens et al., 1967). Adequate understanding now exists for the formulation of empirical models of varying complexity and robustness to enable photoperiod and temperature responses to be accommodated, with varying levels of sophistication, in crop improvement (Hammer et al., 1982, 1989; Lawn et al., 1985; Keefer, 1986a; Myers et al., 1986a). Flowering responses of photoperiod-sensitive genotypes in many species can be described by relatively simple linear models of the general form:

1/f=a2 + bET+CEP

(3)

where f i s the time from sowing to flowering, P is mean daily photoperiod, T is mean daily temperature and a2, bE, ¢2 are genotype-specificparameter constants (Roberts and Summerfield, 1987 ). For non-photoperiodic genotypes, or for sensitive genotypes grown in environments where P
1/f=al +blT

(4)

whence the base temperature for rate of developmenttoward flowering is given by -a~/bl. At the critical photoperiod, i.e. when P=Pc, equation (3) =equation (4), whence Pc = [ ( a l - a 2 ) + (bl-b2)T]/c2. These relationship have been shown to apply with a range of both long- and short-day species, at least for environments excluding stressful temperature extremes. Where temperatures routinely exceed the optimum, however, the inclusion of parameters for optimum and maximum temperatures may also be necessary. Genotypic differences are manifest in the models as differing parameter estimates for Pc, base temperature, minimum juvenile period, and sensitivities to both temperature and photoperiod. In the grain legumes, and soybean (Summerfield et al., 1989), genotypic differences in time to flowering are manifest primarily as differences in sensitivity to photoperiod and Pc. Application of the same model to published data for sorghum (Table 3, Fig. 5 ) suggests genotypic differences in photoperiod sensitivity, and to a lesser extent, in Pc, in that species also. The temperate line Texas 610 was insensitive to the daylengths tested while, as might be expected, sensitivity was greater in later (tropical) genotypes. On the other hand, Hammer et al., (1989) reported no variation in either parameter for some 12 hybrids of temperate to tropical adaptation, so that further examination of the response in sorghum is warranted. Models describing the flowering response of several mungbean genotypes and their F~ progeny suggest that there is a genetic basis to the various parameters (Imrie and Lawn, 1990), with perhaps several alleles governing each. If confirmed, these results imply

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TABLE3 Photoperiodic parameter estimates for several sorghum genotypes, derived from application of the model of Roberts and Summerfield ( 1987, and see text), using least squares minimisation, to field data of Myers et al. (1986a), wherein crops were grown at three sowing dates at each three latitudes, 15 ° 39', the Tropic, and 27°34'S (data courtesy R.J.K. Myers) Genotype

Mean days to anthesis

Photoperiod sensitivity

Pc at 25 °C

R 2,

Ryer Milo Texas 610 PX-10 Meloland X- 1169 Q8028 Q7844

51.4 65.0 68.2 74.6 84.6 90.8 161.4

- 0.00075 n.p. -0.00107 - 0.00078 - 0.00249 -0.00522 -0.00448

15.2 n.p. 11.2 8.6 10.9 12.1 11.5

0.71 ** 0.58** 6.69** 0.87** 0.56** 0.89** 0.74**

a Degrees of freedom corrected. n.p., Non-photoperiod-sensitive (see Fig. 5 ).

that there is large scope for manipulating phenology in mungbean, and presumably other species, through the construction of novel combinations of alleles designed to match the constraints of target environments. In the shorter term, emphasis will continue to be placed on manipulating time to flowering. In the longer term, however, greater emphasis will need to be placed on the optimal duration of other phases (e.g. grain-filling) in specific environments. There are both genotypic and environmental (primarily photoperiodic) effects on post-flowering development in most species (e.g. Lawn and Byth, 1973; Myers et al., 1986a) and differences in productivity are often ascribed to differences in the duration of grain-filling (e.g. Done, 1986 ). Two traits of particular relevance to manipulating phenology in many of the non-cereal crops are indeterminatenessand phenological plasticity. Both traits can offer substantial homeostasis in stress-prone environments through the ability of the plant either to resume reproductive activity after, or to 'postpone' activity until, the relief of stress. In a few instances, the heritability and genetic basis of phenological response are already known. For example, a series of'maturity' genes has been identified within soybeans (McBlain et al., 1987). Further, several 'juvenile' genes, which confer reduced photoperiod sensitivity, have been identified and exploited to broaden the adaptation of tropical soybeans across latitudes and seasons (Hinson, 1989; Kiihl and Garcia, 1989 ). Likewise, at least four genes control maturity in sorghum (Quinby, 1967), with the recessive alleles tending to confer lateness or tropical adaptation. Three genes affecting flowering have been identified in pigeonpea (Byth et al., 1983 ). In addition to matching the crop to the climatic resources of the environment, phenology can be manipulated, usually in conjunction with judicious

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TABLE 4 Effect of sowing date and genotype maturity on weather damage (expressed as percentage seeds damaged) of mungbean grown at Douglas Daly Research Station, Northern Territory (data courtesy S.J. Yeates) Genotype

Cv. Satin Cv. King LMM 1590 LMM 1179

Maturity class

Early Early-medium Medium-Late Late

Sowing date 15/1/88

2/2/88

16/2/88

100.0 22.5 11.5 1.5

3.1 7.5 1.1 0.0

0.0 0.0 0.0 0.0

choice of sowing date, to avoid coincidence of vulnerable stages with periods of likely stress. For example, the strongly seasonal nature of the monsoonal wet season provides an opportunity for avoiding crop maturation during hot, humid conditions favourable to grain weathering. Thus Done (1986) suggests that breeding strategies for sorghum, as well as selecting for open heads which are less susceptible to moulds might well include the incorporation of lateness to ensure that the crop matures after the most probable end of the wet season. An analogous strategy has been adopted to overcome weathering damage in mungbean in the Northern Territory (Imrie et al., 1988), where studies have shown weather damage can be avoided either by the use of later sowings, or later-maturing genotypes (Table 4). In rainfed crops, however, the strategy may increase the risk of terminal water stress, particularly in those seasons where the wet season ends earlier than expected. The optimal balance between risk of weather damage and water stress thus depends in large part on probable rainfall distribution, and soil water-storage capacity.

Improving tolerance of specific constraints The second strategy for improving climatic adaptation is breeding for traits conferring resistance to, or at least tolerance of, specific stresses. In general, much progress has been made in identifying putative traits that might contribute to improved tolerance of stresses, and for some, in establishing the extent of genotypic variation. For several, the genetic basis and inheritance have been established. As yet, however, in the tropical crops, few traits have had their practical value unequivocally demonstrated through intentional use in commercial cultivars. In the Australian tropics, strongest research emphasis has been placed on three goals: resistance to drought, to temperature extremes, and to weather damage of grain. Strategies for exploiting physiological and morphological traits in breeding for adaptation to drought-prone environments are discussed by Blum (1984).

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Suffice it to say here that the relevance of particular breeding strategies, and of individual traits, depends on the likely seasonal pattern of water availability, and the timing and severity of water deficits. As indicated earlier, intermittent drought is a risk of rainfed cropping in most areas of northern Australia, while in the tropics there is the additional risk of terminal drought. Given the difficulty of escaping intermittent drought by manipulating phenology, the most promising strategies should be those based on resistance or tolerance, particularly those exploiting mechanisms which favour recovery following stress (Lawn, 1988 ). Various physiological mechanisms contributing to drought resistance have been identified in summer grain crops (Table 5 ), and for several, information is available on genotypic variation and heritability. Each of the mechanisms contributing to desiccation avoidance, through reduced water loss during drought periods, leads to some extent to reduced productivity. Those relating to stomatal and epidermal conductance and leaf movement, howTABLE 5 Physiological mechanisms potentially contributing to drought tolerance in various summer crop species Strategy and mechanism

Example of occurrence

I. Reduced or more efficient water use

Low stomatal conductance

Lower epidermal conductance

Leaf area adjustment Paraheliotropic leaf movement and leaf rolling Higher transpiration efficiency Higher leaf reflectance

Variation between grain legumes (Lawn, ! 982); No genotypic variation within sorghum (Santamaria et al., 1986). Variation between grain legumes (Sinclair and Ludlow, 1986); conductance genotypic variation within soybean (Paje et al., 1988) and sorghum (Jordan and Sullivan, 1982; Muchow and Sinclair, 1989). Variation between grain legumes (Lawn, 1982) and within sorghum (Henzell et al., 1984; Santamaria et al., 1986). Variation between grain legumes (Lawn, 1982) and within sorghum (Santamaria et al., 1986). Variation within groundnut (Hubick et al., 1986). Genotypic variation in sorghum (Jordan and Sullivan, 1982)

11. Improved water uptake

Improved root function (e.g. density and depth)

Variation between grain legumes (Lawn, 1982) and within groundnut (Williams et al., 1986 ).

I l l . Desiccation tolerance

Osmotic adjustment Low lethal water status

Variation within sorghum (Wright et al., 1983; Santamaria et al., 1986), soybean (Ludlow and Muchow, 1989) and pigeonpea (Hower and Ludlow, 1987) Variation between grain legumes (Sinclair and Ludlow, 1986 ); genotypic variation in sorghum (Jordan and Sullivan, 1982; Santamaria et al., 1986) and pigeonpea (Hower and Ludlow, 1987 ).

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ever, are more conducive to recovery following the relief of drought. Increased rooting depth and rooting density may contribute to sustained water uptake during drought, provided that water remains available at depth. Mechanisms which contribute to desiccation tolerance include osmotic adjustment and lower lethal water contents. Ludlow and Muchow (1989) provide a critical evaluation of the range of physiological mechanisms and traits of potential value in improving crop yields in drought-prone environments, with emphasis on sorghum and cowpea. They argue that, apart from manipulating phenology, the most valuable traits in both intermittent and terminal droughts, and for both species, would be greater osmotic adjustment and greater rooting depth and density. Among the tropical grain crops, genotypic variation in osmotic adjustment has been reported in sorghum (Wright et al., 1983), soybean (James et al., 1990 ) and pigeonpea (Flower and Ludlow, 1987 ). Within the grain legumes, differences between species in the survival of leaves during drought have been attributed to differences in the lethal water content and epidermal conductance of leaves (Sinclair and Ludlow, 1986 ). Genotypic variation for epidermal conductance has been established in soybean (Paje et al., 1988) and sorghum (Muchow and Sinclair, 1989 ), although it is not known if the variation is sufficient to have any serious effect. Genotypic variation has been reported for transpiration efficiency, as measured by carbon isotope discrimination, in several species including Arachis (groundnut) genotypes (Hubick et al., 1986). Frequently, there is strong interrelationship between stress-response mechanisms, and several may operate in concert, perhaps causally, to give rise to strategies of response (Ludlow and Muchow, 1989 ). For example, in sorghum there are genotypic correlations between osmotic adjustment, the 'stay-green' or delayed senescence trait, and leaf-rolling (Santamaria et al., 1986). Relatively few examples exist where breeding programs for the summer grain crops in Australia have improved drought resistance through the active incorporation of physiological traits. One possible exception has been the successful selection for resistance to drought-induced stem lodging in sorghum (Henzell et al., 1984), using empirical selection for the 'stay-green' trait. Susceptibility to lodging was associated with a shortage of carbohydrates and the death of the lower stem tissues during grain-filling, and tended to be greater in earlier-maturing genotypes with greater HI. Even here, the extent to which physiological knowledge contributed to the solution is questionable. Nonetheless, knowledge of the basis of susceptibility assisted breeders to balance the conflicts between resistance, earliness and high ul, and also to select appropriate test environments. The exploitation of osmotic adjustment in sorghum is also well advanced. Beneficial effects of osmotic adjustment have been demonstrated for HI and seed yield in drought environments (Ludlow et al., 1989b) and studies ofheritability of the trait are underway.

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Genotypic variation has been shown in sorghum for ability to emerge at high soil temperatures, and heat-stress sensitivity of growth rates and seed yield (Jordan and Sullivan, 1982). Genotypic differences also exist in the ability to 'harden' in response to high temperatures. Done (1986) reported genotypic differences in leaf discoloration and necrosis in response to the combined effects of excessive heat and radiation in field tests in the Ord. Jordan and Sullivan ( 1982 ) argue that the relatively consistent performance of some parents in hybrid combination implies that the development of heat tolerance is an attainable goal in sorghum breeding. However, to our knowledge, no widespread screening for heat tolerance has been undertaken in Australia. Soman et al. (1986) report the development at ICRISAT of screening techniques for selecting types able to emerge from soil with high surface temperature. While soybeans are acutely sensitive to water-deficit in tropical environments, there is little evidence that heat stress is of itself a major constraint to productivity. Where adequate water has been available, as in the saturatedsoil-culture system, high yields have been obtained both in south-east Queensland and in the Ord (Troedson et al., 1985 ). As with many crops, the main problem is likely to arise from the combined effects of heat stress and water-deficits. Genotypic variation has been demonstrated between soybean lines of tropical and temperate origin in the sensitivity of pollen formation to cool minimum temperatures during the dry season in the tropics (Lawn and Hume, 1985 ). Parental lines have been selected to ensure that genes for tolerance are included in breeding populations targeting the dry season (Imrie, unpublished data, 1983 ), but no specific screening for cool-temperature tolerance has been seen as necessary. Genotypic variation has been found for sensitivity to cool autumn temperatures in mungbeans grown in the subtropics (Lawn, 1979), with sensitivity negatively correlated with latitude of origin. One of the few sustained efforts to develop resistance to a climatic stress in northern Australia has been the attempt to breed weathering resistant mungbeans (Imrie et al., 1988 ). Detailed studies were undertaken to describe the physiology of weathering in relation to environmental factors such as humidity, temperature and rainfall (Williams, 1989). This research provided the basis for a controlled-environment screen in which intact racemes and their pods are exposed to cycles of wetting and drying, with humidity and temperature regulated. The screen was used to establish the sensitivity to weathering damage of some 324 genotypes and, from some 24 pod and seed traits investigated using pattern analysis and regression techniques, two traits, hardseededness and greater pod-wall density, were identified as being associated with greater resistance to damage (Imrie et al., 1988). The inheritance of hardseededness has been established for several crosses, and hardseeded lines are now being developed to determine the efficacy of the trait and of methods of breaking hardseededness. Further research is also being undertaken into pod-

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wall density and other pod and seed traits. Meanwhile, an advanced breeding line, soft-seeded but identified as having some resistance to weathering, has been released. Wild germplasm is also being investigated as a source of resistance to weather damage (Lawn et al., 1988). In crosses between cultivated mungbean, and Australian genotypes of the wild form ( V. radiata spp. sublobata), hardseededness is conditioned by a major gene, with perhaps several minor genes. The trait has been backcrossed into the weather-susceptible cultivar Berken, preparatory to tests of its efficacy in reducing weathering susceptibility. The wild material is also being explored for tolerance to other environmental stresses, including cool temperature, drought stress, and calcareous and saline soils. In each case, the emphasis is on populations collected from locations where the respective stresses are common. The reasoning is that longterm selection pressures in such environments are likely to have favoured the accumulation of traits favouring tolerance, or perhaps avoidance, of the stress. There appear to be several reasons why specific traits for tolerance to environmental stresses have not been more widely exploited in crop improvement in the Australian tropics and subtropics. Probably the main reason is that emphasis has necessarily been on improving phenological adaptation, where the potential for rapid improvement has been greatest. Thus, as pools of reasonably well-adapted germplasm are developed, increasing focus can be expected on 'fine-tuning' adaptation through developing tolerance to specific stresses. Additionally however, plant breeders must also address a suite of non-climatic problems, and are understandably reluctant to invest effort pursuing often unproven physiological traits. The observation of Ludlow and Muchow ( 1989 ) is relevant here: "There is much information about various traits, but less knowledge and even less understanding of their real worth... Unless they make a contribution .... there is little use breeding for them." The problem is compounded by the difficulty of measuring and screening for some traits. In this context, new genetic techniques such as RFLP (restriction fragment length polymorphism ) mapping may greatly improve the ease with which quantitative physiological traits can be manipulated by breeders (e.g. Beckman and Soller, 1986 ). Thus, as the value of putative traits is established, and new techniques for handling them developed, we may expect greater effort to be invested in exploiting them. RETROSPECT AND PROSPECT

Various approaches have been adopted in studies to define physiological and environmental constraints to growth and adaptation of the summer grain crops. Analyses have frequently sampled a very limited array of genotypes and environments, particularly where the focus was chiefly on improving productivity in existing environments and/or on improving agronomic manage-

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ment. In the extreme, examples can be found in the literature of genotypeand/or environment-specificstudies. (Indeed, the focus on detailed analyses of one - - albeit high-yielding and widely adapted - - sorghum genotype led some plant breeders to complain of a 'Texas 6 l0 syndrome'). Over time, however, there has been increasing awareness that, to be relevant to genetic improvement, analyses need to consider at least several genotypes and environments. Another frequent perception is the need for 'holistic' or 'crop-level' physiological analysis (Charles-Edwards, 1982; Shorter et al., 1991 ). Undoubtedly the most significant (continuing) development has been the transition from qualitative to quantitative physiological analysis and, in particular, the integration of physiological understanding of crop growth and development into models to predict, quantitatively, crop performance in particular environmental conditions. Thus the task of optimizing phenology in specific environments, particularly where competing risks have to be balanced, has been greatly facilitated by the use of various agroclimatic models to integrate and interpret historical weather data in terms of suitability for crop growth (Shorter et al., 1991 ). Some of the approaches to the use and interpretation of probability data for various climatic events, such as heatwaves, frost, timing of planting rains etc. in assessing climatic limitations, are discussed by Hammer (1983). Relatively simple growth indices and waterbalance models can be used to indicate the timing and duration of conditions favourable to growth, and examples of their use are available for the grain legumes (Nix et al., 1977) and sorghum (Hammer and Wade, 1986; Wade and Hammer, 1986). Rather more complex simulation models aim to use weather data to predict crop growth and yields (e.g. Keefer, 1986b; Sinclair et al., 1987; Carberry et al., 1989; Hammer and Vanderlip, 1989; Muchow et al., 1990). Depending on their nature and structure, such models provide potentially powerful tools for formulating the 'dynamic' ideotypes mooted earlier. For example, simulation models can provide insight into the impact of specific traits on crop performance under hypothetical conditions. Thus Ludlow et al. (1989a) have explored the possible effects of root signals on growth of soybean and maize under terminal vs intermittent droughts. Alternatively, the information on environmental variability 'frozen' in historical weather records can be exploited to evaluate the probable long-term performance of 'novel' genotypes in target environments. We believe the stage is therefore set for a sustained and broadly-based contribution by quantitative physiological analysis to crop improvement in the tropics. Inevitably, however, the value of physiological models depends on the quality of the information encapsulated in them, and as ever, the field remains the final arbiter of plant response. ACKNOWLEDGEMENTS

The authors acknowledge the assistance of Mr. A.R. Watkinson and Ms. L.M. Abberton in the preparation of the Figures, and the provision ofunpub-

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lished data by several colleagues, as indicated in the relevant Tables and Figures.

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