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Plant breeders spend considerable time, effort and expense in conceptualizing and selecting for improved plant types. Given the climatic variability and diverse management practices in different regions to which crops are exposed, different plant types may be needed For different agro-ecological zones. By capturing physiological understanding in a predictive framework, crop modelling offers the potential to interpret and predict the performance of individual genotypes in different environments, thus offering a possible decision support role in plant breeding. We propose that, when considering the adaptation of food legumes to the environments in which they are growing, the impact on the whole system should evaluated, including the N economy of the cropping system and impacts on the productivity of associated crops. We present some case studies of the use of static analytical models and simulation to evaluate traits in food legumes, from a cropping systems perspective. In one case study we show that the yield difference between determinate and indeterminate soybean types in this semi-arid environment will depend upon interactions between seasonal conditions, flowering date and starting soil water, which models can assist in analysing. Conducting analyses over the climatic record also allows any yield advantage to be assessed against the impact on the riskiness of production. In another study, we highlight the interaction between agronomic management (such as row spacing) and the performance of cowpea genotypes differing in height and leaf posture when grown as intercrops with maize. In a third case study we address the question of the impact of chickpea genotypes differing in potential N fixation on system performance of a chickpea-wheat rotation under dryland conditions. The results show the trade-off between the gains or losses in chickpea and wheat yields by introducing chickpea with different traits into the rotation.

In summary, the case studies are intended to demonstrate that breeding objectives often need to incorporate the impact of altered plant traits beyond the yield of the targeted crop and the interaction of management and climate on the differential performance of genotypes. This is particularly the case for food legume crops which are typically grown as important components of crop rotations.