Linking assimilate supply and seed developmental processes that determine soybean seed composition

The concentrations of protein and oil in soybean (Glycine max L.) seeds are important factors determining the quality of soybean meal and its competitiveness in international markets. Studies aimed at understanding genetic factors and/or environmental conditions that distinguish high levels of protein and oil accumulation from those that result in deficient levels typically analyze mature seeds. This approach inevitably confounds maternal, zygotic, and environmental effects on seed component accumulation. We have attempted to resolve these effects by manipulating assimilate supply per seed and quantifying the impact directly on the rate and duration of protein, oil, and residual (predominately carbohydrate) accumulation. Genotypes varying in final seed protein concentration were grown in the field and exposed to treatments to increase (depodding) or decrease (shading) assimilate supply per seed during seed filling. Depodding increased the rate of protein, oil, and residual accumulation. Protein accumulation was most responsive, resulting in a dramatic increase in final protein concentration, particularly in the low-protein genotypes. Shading decreased oil accumulation with less impact on protein and residual content, leading to a reduction in final oil concentration. Rates of protein accumulation explained most of the variation in final contents rather than duration. For each seed component, a single hyperbolic function described the relationship between assimilate supply per seed and the rate of component accumulation for all genotypes and treatments. These results underscore the importance of evaluating genetic and environmental effects directly on seed component accumulation, and confirm the predominant influence of assimilate supply per seed on soybean seed composition. Theoretical modeling showed that further increases in seed protein concentration cannot rely on more assimilates supply and that future increases will depend on increases in resource use efficiency and/or changes in partitioning.