Al Doherty

Crop design for specific adaptation in variable dryland production environments

Abstract. Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.

Reliability of production of quick to medium maturity maize in areas of variable rainfall in north-east Australia

Maize may assume a more significant role in grain crop production systems in north-east Australia if the probability of producing low yields associated with given amounts of available water can be reduced. Growing hybrids with very early maturity provides a possible way to achieve this. Simulation studies of dryland maize production in areas of highly variable rainfall in north-east Australia were undertaken using long-term weather data input to the APSIM model configured for quick to medium maturity maize. The studies focussed on sowing time options, population density, cultivars, and water availability at sowing. Simulation outputs included predicted mean and median yield, measures of yield variability, and the probability of producing low to very low yield (< 2 t/ha). The study showed that optimum sowing date varied with location, and that low populations gave more reliable production, despite some potential yield losses in favourable years. The results of the simulation study provide estimates of yield and thus economic viability of maize production that are interpreted in terms of seasonal variability. They indicate that maize is a viable dryland cropping option provided that cultivar, sowing time and starting water conditions are optimised. Non-optimal conditions of water supply at sowing should be avoided, as greater variability in yield and reduced viability are predicted.

Analysis and modelling of the effects of water stress on maize growth and yield in dryland conditions

Abstract It is essential to provide experimental evidence and reliable predictions of the effects of water stress on crop production in the drier, less predictable environments. A field experiment undertaken in southeast Queensland, Australia with three water regimes (fully irrigated, rainfed and irrigated until late canopy expansion followed by rainfed) was used to compare effects of water stress on crop production in two maize (Zea mays L.) cultivars (Pioneer 34N43 and Pioneer 31H50). Water stress affected growth and yield more in Pioneer 34N43 than in Pioneer 31H50. A crop model APSIM-Maize, after having been calibrated for the two cultivars, was used to simulate maize growth and development under water stress. The predictions on leaf area index (LAI) dynamics, biomass growth and grain yield under rainfed and irrigated followed by rainfed treatments was reasonable, indicating that stress indices used by APSIM-Maize produced appropriate adjustments to crop growth and development in response to water stress. This study shows that Pioneer 31H50 is less sensitive to water stress and thus a preferred cultivar in dryland conditions, and that it is feasible to provide sound predictions and risk assessment for crop production in drier, more variable conditions using the APSIM-Maize model.

Quantification of wheat water-use efficiency at the shire-level in Australia

In eastern Australia, latitudinal gradients in vapour pressure deficit (VPD), mean temperature (T), photosynthetically active radiation (PAR), and fraction of diffuse radiation (FDR) around the critical stage for yield formation affect wheat yield and crop water-use efficiency (WUE = yield per unit evapotranspiration). In this paper we combine our current understanding of these climate factors aggregated in a normalised phototermal coefficient, NPq = (PAR· FDR)/(T · VPD), with a shire-level dynamic model of crop yield and water use to quantify WUE of wheat in 245 shires across Australia. Three measures of WUE were compared: WUE, the ratio of measured yield and modelled evapotranspiration; WUEVPD, i.e. WUE corrected by VPD; and WUENPq, i.e. WUE corrected by NPq. Our aim is to test the hypothesis that WUENPq suits regional comparisons better than WUE or WUEVPD. Actual median yield at the shire level (1975–2000) varied from 0.5 to 2.8 t/ha and the coefficient of variation ranged from 18 to 92%. Modelled median evapotranspiration varied from 106 to 620 mm and it accounted for 42% of the variation in yield among regions. The relationship was non-linear, and yield stabilised at ~2 t/ha for evapotranspiration above 343 mm. There were no associations between WUE and rainfall. The associations were weak (R2 = 0.09) but in the expected direction for WUEVPD, i.e. inverse with seasonal rainfall and direct with off-season rainfall, and strongest for WUENPq (R2 = 0.40).We suggest that the effects of VPD, PAR, FDR, and T, can be integrated to improve the regional quantification of WUE defined in terms of grain yield and seasonal water use.

Simulating daily field crop canopy photosynthesis: an integrated software package

Photosynthetic manipulation is seen as a promising avenue for advancing field crop productivity. However, progress is constrained by the lack of connection between leaf-level photosynthetic manipulation and crop performance. Here we report on the development of a model of diurnal canopy photosynthesis for well watered conditions by using biochemical models of C3 and C4 photosynthesis upscaled to the canopy level using the simple and robust sun-shade leaves representation of the canopy. The canopy model was integrated over the time course of the day for diurnal canopy photosynthesis simulation. Rationality analysis of the model showed that it simulated the expected responses in diurnal canopy photosynthesis and daily biomass accumulation to key environmental factors (i.e. radiation, temperature and CO2), canopy attributes (e.g. leaf area index and leaf angle) and canopy nitrogen status (i.e. specific leaf nitrogen and its profile through the canopy). This Diurnal Canopy Photosynthesis Simulator (DCaPS) was developed into a web-based application to enhance usability of the model. Applications of the DCaPS package for assessing likely canopy-level consequences of changes in photosynthetic properties and its implications for connecting photosynthesis with crop growth and development modelling are discussed.