Simulation of soybean growth and yield in near-optimal growth conditions

SoySim is a new soybean (Glycine max, L. Merr) simulation model that combines existing approaches for the simulation of photosynthesis, biomass accumulation and partitioning with several new components: (i) flowering based on floral induction and post-induction processes, (ii) leaf area index based on logistic expansion and senescence functions, (iii) integration of canopy photosynthesis using a beta function, and (iv) yield simulation based on assimilate supply and seed number. Simulation of above ground dry matter (ADM) and seed yield by SoySim were validated against data from field studies at Lincoln (NE), Mead (NE), Whiting (IA), and West Lafayette (IN) that included 147 site-year-cultivar-planting date-plant-plant population combinations. In each of the four field studies, agronomic management other than planting date and plant population was optimized to achieve growth with minimal limitation from pests, nutrients, or other controllable factors. SoySim requires just two genotype-specific and two crop management-specific input parameters and yet provides reasonable accuracy in simulating growth and yield under optimum growth conditions across a wide range of sowing dates, plant population, and yield (2.5–6.4 Mg ha−1) in the North-Central U.S. Corn Belt. Simulated seed yield had a RMSE of 0.46 Mg ha−1. Few cultivar-specific parameter input requirements, lack of requirements for specification of key developmental stages, and mechanistic treatment of phenological development, canopy photosynthesis, and seed dry matter accumulation give several advantages to SoySim for use in research and for use as a decision-support tool to evaluate the impact of crop management options on yield potential in favorable environments.