Crop Modeling to Predict Genetic Improvement and Genotype by Environment Interactions Under Climate Change.

Crop simulation models contain genotype-specific traits linked to processes affecting crop life cycle, photosynthetic capacity, determinancy, partitioning intensity, and seed-filling duration.  The crop models integrate the responses of these processes to weather, fertility, and management, and therefore predict growth dynamics of leaf area index, total dry matter, leaf, stem, pod, seed, single seed growth, seed number, final yield and yield components.  Genetic improvement in yield was simulated for different environments with the manipulation of single and multiple combinations of genotype-specific traits.  Yield improvements of 20 to 30% were possible with combinations of genetic traits, varied within a reasonable genetic range using the CSM-CROPGRO soybean, peanut, and chickpea models, as well as the CERES-sorghum model.  Simulated genotype by environment interactions were commonly found associated with environmental variation in temperature, CO₂, water (irrigated versus rainfed), and N fertilization.  Traits favorable in some environments were often neutral or negative in other environments.  Crop models can be valuable tools to study yield improvement and causes of genotype by environment interaction.