Plant science applied: a case study on cotton

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Brian Hearn

CSIRO, Division of Plant Industry, Narrabri

Origins and domestication


Cotton harvest in progress at Narrabri, New South Wales (July 1995). (Photograph courtesy P.E. Kriedemann)

Worldwide, the genus Gossypium consists of over 40 species of perennial xerophytic shrubs (including domesticated cotton, G. hirsutum). They are frost-sensitive short-day plants found along banks and beds of dry streams. Though the genus is pan-tropical, individual species have limited distribution and are of relic status with little genetic diversity, suggesting a declining genus. All species except two are diploid. The diploid species are divided into five genomes, each of which is largely confined to one continent. Australia has a rich flora of wild species, some very rare, but none has contributed to commercial varieties so far.

Cotton lint consists of seed hairs that collapse in cross-section and form convoluted ribbons when mature allowing them to be spun into yarn. Apart from G. herbaceum the other wild species have stiff seed hairs that cannot be spun. Traits appropriate to spinning were selected after domestication and cotton was then grown in temperate regions. Further varieties were selected for longer and finer fibre and heavier yield. Domestication did not involve loss of sensitivity to daylength as a trigger for reproductive development. Moreover, adoption of an inherent annual habit was not required because termination of a cropping cycle can be imposed by withholding irrigation in combination with defoliation.

Water relations

Cotton is grown in the Yemen in a way that offers invaluable insight into the ecology of cotton’s wild ancestors, and helps explain the behaviour of modern crops. Erratic floods in the Yemen are impounded in order to store the water in their deep alluvial soil. Cotton is then grown entirely on this stored water. Such conditions are remarkably similar to the natural environment of wild ancestors of cotton, and strikingly illustrated by the occurrence of an indigenous wild species as a weed in cultivated crops. Common adaptive traits are seen in both wild and cultivated cotton. The root system explores the soil to the depth wetted, and an indeterminate shoot develops at a rate unaffected by the amount of stored water, until approximately three-quarters of the water is exhausted, whereupon morphological development and vegetative growth stop abruptly, and the crop matures. Plant size and fruit number thus depend on duration of development, which in turn depends on how long it takes for soil water to run out.

This pattern of development is well adapted for survival in arid and semi-arid environments where the water supply from rainfall or floods is erratic and can vary greatly from one season to the next. An indeterminate habit allows plants to make full use of variable water supplies by growing large or small according to water supply. Cotton plants appear to recognise a signal indicating that soil water supply is running out. They then stop development, shed young fruit and mature the fruit that are already set. Passioura et al. (1993) have accumulated evidence from several sources that plants react to drying soil in response to signals from their roots. In irrigated crops, a succession of drying cycles replaces a single prolonged cycle in rainfed crops, presumably generating a different pattern of signals.

There appears to be another signal at the wet end of the range that triggers the rank growth syndrome. Most bolls are shed, unable to assert their priority for assimilates, while vegetative growth is excessive indicating no shortage of resources. This is presumably a latent response from wild progenitors to maximise vegetative growth and delay setting fruit when conditions allow. Both signals are keys to managing cotton crops.

Cotton in Australia

Cotton had been grown in Australia experimentally from time to time in the first half of the nineteenth century, but it took reverberating events in the USA to induce large-scale production in Australia. A world shortage of cotton during the American Civil War and later depredations of the boll weevil, exacerbated by shortage of foreign exchange after World War I, stimulated production of rainfed cotton in Queensland. Additionally, in the early 1960s restrictive US Farms Bills persuaded Californian growers to bring their methods of intensive (irrigated) production to Australia. So began the modern Australian industry. Over the next 30 years the industry expanded dramatically and in the course of 15 years Australia swung from being an importer of cotton to being the world’s fourth largest exporter. Cotton ranks third in Australia in value as an export crop.

Visitors to the Ord Valley in 1970 witnessed an ecological disaster when Heliothis armigera (genus subsequently renamed Helicoverpa) became resistant to DDT. Cotton research resumed on the Ord with new technology and a lot of hard-won wisdom. Intensive cotton production in the tropics is a great challenge, being afflicted by an interaction between pests and rank growth and is rarely successful. Synthetic growth substances and transgenic varieties now offer hope of success.

Narrabri sustains temperate climate production in irrigated valleys between the 22nd and 32nd parallels in eastern Australia. The crop has brought much prosperity and wealth to those valleys, to their towns and to individuals who live there, and even to the nation as a whole. Such are the economic realities. But when we consider the ecological realities, cotton is a disruptive crop. Production on the vertisol plains is intensive, highly mechanised, with heavy inputs of nitrogen (up to 200 kg ha–1), irrigation water (up to 9 ML ha–1), and pesticide (one or two herbicide and 8 to 10 insecticide sprays). Given such requirements, is cotton production sustainable?

Cotton management models

Cotton was threatening to become an ecological pariah in the 1970s. Heavy use of pesticides and irrigation water for cotton growing was of great concern. We needed a simulation model to explore options for pest and irrigation management at tactical and strategic levels. At a tactical level we wanted to use fruit counts to evaluate the potential for pest damage during the season. At a strategic level we wanted to identify the ‘best bet’ strategy for using limited irrigation water supplies in the face of uncertain rainfall. We needed to extrapolate the results of our experiments in a few years and locations to any year and any location in the cotton growing regions. OZCOT evolved as a simulation model for management of cotton crops.

Trying to build my own model I agreed with Conway (1977) that simulation models at that time were of little value in tactical pest and crop management (Hearn and Room 1979). We used a non-dynamic trajectory of yield development consisting of the number of fruit needed at any time in the season to achieve a specified yield by a specified date. Actual numbers were compared with the trajectory to determine how much pest damage could be tolerated.

The fruit model SIRATAC pest-management system was then built in a succession of steps (Hearn and da Rosa 1985):

  1. The number of counted fruit that would survive and contribute to harvest was estimated. The degree-days requirement for fruit development was used to build an age profile of the fruit counted. The proportion of young fruit shed was estimated as a function of fruit load (number of older fruit).
  2. Production of flower buds was estimated as an empirical function of the cumulative number of flower buds and the fruit load. The former provided positive feedback and the latter negative feedback. The form of the function took account of branching structure geometry.
  3. The model crystallised round the concept of carrying capacity, which is the fruit load that reduces the rate of bud production and rate of fruit survival to zero. The concept implicitly incorporates the carbon economy of the crop; the ratio of fruit load to carrying capacity is a surrogate for the carbon demand:supply ratio for fruit.

A simulation model results that is simple and elegant, and which captures the dynamics of cotton fruiting when water and nitrogen are not limiting. This model saw more than 10 years’ service in the SIRATAC pest-management system.

We had asked 20 years earlier, ‘Why does the crop close its doors, and why do some bolls drop out?’ In these models we recognise that older bolls compete against other sinks for limited assimilate supply, and are successful. Twenty years previously we could not predict when the crop would stop producing flower buds and how many fruit would shed, or whether the crop would compensate for pest damage. Now we could. We had no more data than when these questions were asked; instead we had more relevant understanding. We did not need data on assimilate supply and demand. What we needed were concepts of competition among sinks for limited supply of assimilates, and the priority of the older fruit over other sinks including young fruit and buds generating more fruit.

The OZCOT and hydroLOGIC models were developed from the SIRATAC fruit model by linking it to the Ritchie (1972) water balance model for use in situations where water and nitrogen are limiting. Ritchie’s model had already been used with a stress-day yield function to analyse strategies with limited water supplies (Hearn and Constable 1984). A leaf area generator, a boll growth model and a rudimentary soil nitrogen model were added, and photosynthesis included explicitly. OZCOT and hydroLOGIC have been widely used as manage-ment tools (Hearn 1994).

A new model, CERCOT, has been built by linking OZCOT with the soil water and nitrogen models from the CERES family of models, in order to simulate soil and plant nitrogen dynamics more realistically. Light interception and conversion to dry matter are done in the way pioneered by Monteith and followed in CERES, and partitioning is linked to the fruiting dynamics. CERCOT is currently in the final stages of validation.

Our modelling has thus gone a full circle. We started by turning our backs on simulation models and using a static model. A simple dynamic model was then built which has been made progressively more complex over the years. At no stage was it more complex than it needed to be to solve the problems being addressed.

Concluding remarks

Cotton is always fascinating and sometimes maligned, a crop that has shaped the history of many countries. Cotton is grown in a remarkable range of environments and economic circumstanccs from tropical to temperate, and from small-scale subsistence holdings to large and intensive corporate farms. There has been a dark side to cotton — slavery, colonial exploitation and alleged environmental vandalism. It is a crop that our media and environmentalists love to hate, a crop alleged to exhaust soil and require excessive amounts of insecticides and water; and yet this crop clothes humanity in natural fibre!

Equally for plant science, empiricism in cotton growing has given way to process-based models of growth and reproductive development as an aid to management on a huge scale. Such application of basic principles from crop physiology takes on added significance for a species that natural selection honed as a perennial, but which farming practice now manages as an annual. Moreover, genotype × environment interactions are still at work on Gossypium hirsutum, but this time human selection for inherent earliness with wide adaptability to photoperiod will help shape future genotypes.

Further reading

Brown, K.J. (1968). ‘Translocation of carbohydrate in cotton: movement to fruiting bodies’, Annals of Botany, 32, 703–713.

Constable, G.A. and Hearn, A.B. (1981). ‘Irrigation of crops in a subhumid climate, 6: effects of irrigation and nitrogen fertiliser on growth, yield and quality of cotton’, Irrigation Science, 2, 17–28.

Hearn, A.B. and Fitt, G.P. (1992). ‘Cotton cropping systems’, in Field Crop Ecosystems, ed. C.J. Pearson, 85–142, in Ecosystems of the World, series ed. C. Goodall, Elsevier: Amsterdam.

Passioura, J.B. (1996). ‘Simulation models: science, snake oil, education, or engineering?’, Agronomy Journal, 88, 690–694.

Turner, N.C., Hearn, A.B., Begg, J.E. and Constable, G.A. (1986). ‘Cotton (Gossypium hirsutum L.): physiological and morphological responses to water deficits and their relationship to yield’, Field Crops Research, 14, 153–170.

Trolinder, N.L., McMichael, B.L. and Upchurch, D.R. (1993). ‘Water relations of cotton flower petals and fruit’, Plant, Cell and Environment, 16, 755–760.

Van Iersel, M.W., Oosterhuis, D.M. and Harris, W.M. (1994). ‘Apoplastic water flow to cotton leaves and fruits during development’, Journal of Experimental Botany, 45, 163–169.