Mungbean (Vigna radiata (L.) Wilczek) in Australia has been transformed from a niche opportunistic crop into a major summer cropping option for dryland growers in the summer-dominant rainfall regions of Queensland and New South Wales. This transformation followed stepwise genetic improvements in both grain yields and disease resistance. For example, more recent cultivars such as ‘Crystal’, ‘Satin II’, and ‘Jade-AU‘ have provided up to a 20% yield advantage over initial introductions. Improved agronomic management to enable mechanised management and cultivation in narrow (<50 cm) rows has further promised to increase yields. Nevertheless, average yields achieved by growers for their mungbean crops remain less than 1 t/ha, and are much more variable than other broad acre crops. Further increases in yield and crop resilience in mungbean are vital. In this review, opportunities to improve mungbean productivity have been analysed at four key levels including phenology, leaf area development, dry matter accumulation, and its partitioning into grain yield. Improving the prediction of phenology in mungbean may provide further scope for genetic improvements that better match crop duration to the characteristics of target environments. There is also scope to improve grain yields by increasing dry matter production through the development of more efficient leaf canopies. This may introduce additional production risks as dry matter production depends on the amount of available water, which varies considerably within and across growing regions in Australia. Improving crop yields by exploiting G × E × M interactions related to cultivar photo-thermal sensitivities and make better use of available water in these variable environments is likely to be a less risky strategy. Improved characterisation of growing environments using modelling approaches could also better define and identify the risks of major abiotic constraints. This would assist in optimising breeding and management strategies to increase grain yield and crop resilience in mungbean for the benefit of growers and the industry.

Matching crop phenology to environment is essential to improve yield and reduce risk of losses due to extreme temperatures, hence the importance of accurate prediction of flowering time. Empirical evidence suggests that soil water can influence flowering time in chickpea and wheat, but simulation models rarely account for this effect. Adjusting daily thermal time accumulation with fractional available soil water in the 0–60 cm soil layer improved the prediction of flowering time for both chickpea and wheat in comparison to the model simulating flowering time with only temperature and photoperiod. The number of post-flowering frost events accounted for 24% of the variation in observed chickpea yield using a temperature-photoperiod model, and 66% of the variation in yield with a model accounting for top-soil water content. Integrating the effect of soil water content in crop simulation models could improve prediction of flowering time and abiotic stress risk assessment.

Post-flowering frosts cause appreciable losses to the Australian chickpea industry. The Northern Grains Region (NGR) of Australia, which accounts for nearly 95% of chickpea production in Australia, is frequently subjected to such events. The objective of this study was to map frost risk in chickpea in the NGR and develop strategies to minimise the impacts of such risk. The Agricultural Production System Simulator (APSIM) modelling framework was used to determine spatial and temporal trends in post-flowering frost risk. The NGR could be divided into six broad sub-regions, each delineating locations with similar frost risk. The risk was nearly two to three times greater in the Southern Downs and Darling Downs sub-regions as compared to the Central Queensland Highlands, Dawson Callide, New South Wales, and Northern New South Wales–Western Downs sub-regions. There was an increasing trend in the frequency of frost events in the Southern Downs and New South Wales sub-regions, and a decreasing trend in the Central Queensland Highlands and Dawson Callide sub-regions, consistent with the changing climate of the NGR. In each sub-region, frost risk declined with delayed sowings, but such sowings resulted in simulation of reduced water limited yield potential (unfrosted) as well. The model output was also used to compute 10, 30, 50, and 70% probabilities of the last day of experiencing −3 to 2 °C minimum temperatures and identify the earliest possible sowings that would avoid such temperatures after flowering. Choosing the earliest sowing times with a 30% frost risk could help increase overall yields in environments with high frost risk. Simulations involving genotype x environment x management interactions suggested additional opportunities to minimise frost losses through the adoption of particular cultivars of differing phenology and the use of different agronomy in various environments of the NGR. The study indicates that there is considerable variation in frost risk across the NGR and that manipulating flowering times either through time of sowing or cultivar choice could assist in minimising yield losses in chickpea due to frost.

Phenological development is critical for crop adaptation. Phenology models are typically driven by temperature and photoperiod, but chickpea phenology is also modulated by soil water, which is not captured in these models. This study is aimed at evaluating the hypotheses that accounting for soil water improves (i) the prediction of flowering, pod-set, and flowering-to-pod-set interval in chickpea and (ii) the computation of yield-reducing frost and heat events after flowering. To test these hypotheses, we compared three variants of the Agricultural Production System Simulator (APSIM): (i) APSIMc, which models development with no temperature threshold for pod-set; (ii) APSIMx, which sets a threshold of 15 °C for pod-set; and (iii) APSIMw, derived from APSIMc with an algorithm to moderate the developmental rate as a function of soil water, in addition to temperature and photoperiod common to all three models. Comparison of modelled and actual flowering and pod-set of a common cheque cultivar PBA Boundary^A in 54 diverse environments showed that accuracy and precision were superior for APSIMw. Because of improved prediction of flowering and pod-set timing, APSIMw improved the computation of the frequency of post-flowering frosts compared to APSIMc and APSIMx. The number of heat events was similar for all three models. We conclude that accounting for water effects on plant development can allow better matching between phenology and environment.

There is interest in growing pigeonpea [Cajanus cajan (L.) Millsp.], a tropical grain legume crop, in temperate regions. A few extra‐short‐duration lines were developed in Minnesota (∼45° N), USA, to improve the crop's adaptation to temperate regions. We investigated whether photoperiod responses of the Minnesota lines (MN #) differed with lines (ICPL #) bred in the tropics. Five ICPL lines and three MN lines were grown under artificially extended daylength (ED) simulating 45° N and normal daylength (ND) at Patancheru, India, (17° N) during the 1995 and 1996 rainy seasons. Six ICPL and two MN lines were also tested at Suwon (37° N), Korea, in 1998. At Patancheru, the line × photoperiod interactions were highly significant for grain yield, total dry matter (TDM), harvest index (HI), days to flowering (DF), and maturity (DM). Under ND, yield was significantly more for ICPL lines and correlated with TDM (r = 0.892 and 0.902, n = 8), DF, and DM, but not with HI. Under ED, yield was more for MN lines and correlated positively with HI and negatively with DF and DM (in 1996), but not with TDM. The additive main effects and multiplicative interaction (AMMI) analysis suggested a distinct interaction pattern for MN lines. Yield was correlated negatively with DF and DM in Korea also where a MN line gave the highest yield. The results suggest that there has been a selection for a high HI potential and early flowering in MN lines for better adaptation to longer days and a high TDM production potential in ICPL lines to shorter days.