Simulation of environmental and genetic effects on grain protein concentration in wheat

The performance of the APSIM-Nwheat model for the simulation of grain protein levels has previously been tested across a number of environments, but the influence of management, environment and genotype on protein levels has not been fully investigated. A number of simulation exercises were carried out to analyse the sensitivity of the APSIM-Nwheat grain protein routine to environmental and genetic factors. The model initialises grain protein at 17% at the beginning of the linear phase of grain filling if sufficient N is available in the crop. Grain protein concentration is then simulated as a consequence of daily grain N and grain weight accumulation as two independent temperature functions that are constrained at their extremes. An upper boundary of daily protein accumulation in the grain is set at 23%. The lower boundary of grain protein daily accumulation is set to 7%. The simulated responses were consistent with published trends. An increased temperature during grain filling accelerated grain N accumulation more than grain weight accumulation and resulted in a higher grain protein concentration at crop maturity. Increased water shortage due to reduced rainfall had a negative effect on grain numbers per unit area, grain size and grain N accumulation, resulting in an increased grain protein concentration. Water shortage which started after grain numbers had been set at the beginning of grain filling had a small positive impact, or sometimes no impact, on grain protein concentration. Simulating crop growth with more than 100 years of historical weather records showed that initial grain protein concentration, grain protein dynamics and final grain protein concentration varied substantially between seasons. In addition, N supply affected grain protein, but the magnitude of the effect depended on the specific season. Location also affected grain protein via seasonal rainfall and temperature, so that grain protein declined linearly with a seasonal rainfall/temperature index. When the potential rate for grain dry matter accumulation was increased in the model to reflect an increase in the genetic yield potential, grain protein concentration declined linearly with increasing yield under optimal water and N supply. Increasing temperatures and water shortage or sub-optimal N supply shifted the line but the linear relationship was maintained. All these model responses to environmental and genetic effects were similar to expectations based on field or greenhouse studies. The close linear negative relationship between grain protein concentration and grain yield highlights the genetic limitation to increases in grain protein, which agrees well with experimental findings elsewhere. However, under combined water and N limitations, the model suggested that this negative linear relationship can become non-linear in some situations, which needs to be verified under controlled environment and field conditions.