Research Project

The KSU crop team, in partnership with the United Soybean Board and a network of US universities, is committed to increasing competitiveness, sustainability, and marketability for US soybean production. In this context, the KSU crop team hosts several projects aiming to improve seed composition quality throughout crop management and plant nutrition.

One of the primary reasons for soybean importance for the livestock industry is because of the relatively high protein concentration and amino acid profile of its seed. Protein and amino acids are carbon-based molecules with at least one nitrogen (N) functional group. Their accumulation into the seeds results from a complex interplay between environmental conditions and genotype, but markedly depends on crop N nutritional status. Soybean is a N fixing crop which commonly receives less N-fertilizer input (mineral and organic) than the crop requirements. Most N is supplied thru endosymbiosis between the plant and α-proteobacteria rhizobia group. The N provided by rhizobia will serve as building blocks for the whole plant protein systems such as photosynthesis apparatus and ultimately to the seed contained protein. Therefore, improving protein concentration and the quality of the amino acid profile is achievable by using comprehensive multi-factor crop management and environmental framework.

Recently our research showed not all amino acids have been decreasing at the same rate of protein in US historical genotypes. The bulk N reserve amino acids such as glutamine followed a similar trend of protein, but some essential amino acids increased when compared to the protein. This evidence unleashed potential opportunities to investigate other than genotype aspects undertaking influence in seed amino acid profile. Our ongoing projects include: i) The effect of N and S mineral fertilizer management in the seed composition and interactions to plant C and N acquisition process; ii) How the activity of biological activity along the growing season affects seed composition; iii) Prediction of protein concentration based on environmental and agronomic variables.

For more information and the current state of the project, please reach us.