Soybean breeding programs are successful in increasing yield potential but progress in breeding for optimizing seed quality composition such as protein, oil, fatty acids, amino acids has not received similar attention. There is a need to develop a simple, robust and high-throughput platform for quantifying quality parameters and the seed compositional changes in response to a range of environmental conditions. Objectives of this project include developing and standardizing a high-throughput approach to quantify genetic diversity in soybean protein, amino acids, oil, oleic acid from germplasm; estimating the spatial and temporal impact of Kansas climatic variability on soybean quality; and integrating the technology into the Kansas soybean breeding program.

Key Benefactors:
farmers, breeders, scientists, biologists