Simulating the impact of source-sink manipulations in wheat

Grain yields in wheat can be limited by the assimilate supply (source) or by the carbohydrate demand of the grains (sink). Recently, there have been questions regarding the capability of crop models to simulate the physiology of source-sink interactions in crops; however, crop models have never been tested with source-sink manipulated data. We tested the Nwheat model with detailed measured field experimental data with treatments of manipulated source (i.e., assimilate supply), sink (i.e., kernel number), and their combinations. In general, the model could reproduce observed effects of shading before and after anthesis as well as the additional impact of halving the spikes. A 90% shading during grain filling reduced individual grain weights drastically, with the remaining yield mostly determined by carbohydrate remobilisation, which the model reproduced. The model also reproduced the decline of biomass accumulation due to shading, but was not sensitive enough to simulate the observed reduction of kernels per m² from a 90% reduction in solar radiation between booting and the beginning of grain filling, resulting in an overestimated grain yield. The model reproduced the positive impact of a 7% genetically increased radiation use efficiency (RUE) on growth and yield. A sensitivity analysis indicated that the yield response to increased RUE can vary among environments. The yield impact can be positive in many environments, but negative in terminal drought environments. In these environments, stimulated early growth from higher RUE can cause accelerated water deficit during grain filling and reduced yields. The model adequately simulated source-sink interactions of most of the treatments, but there were obvious shortcomings in simulating kernel set and final grain size. Improving these will be critical for estimating crop-environmental interactions that affect assimilate supply, including breeding, industrialisation-induced or geo-engineered solar dimming, genetically and atmospheric CO₂-related increased RUE, and source manipulations, such as pest and disease impacts.