Selecting Increased Seed Density to Increase Indirectly Soybean Seed Protein Concentration

Because soybean [ Glycine max (L.) Merr.] is the world's most important source of high quality vegetable protein, development of high yielding genotypes with increased seed protein concentration is a major soybean breeding objective. A major impediment to this objective is the often observed negative correlation between yield and protein. Seed density is a component of grain yield that is correlated positively with seed protein concentration. If genotypic correlations between seed density and yield are low, selection for increased density could provide an efficient way to improve protein concentration without affecting seed yield. The objective of this study was to investigate direct and correlated responses to selection on density of seeds sampled from male‐sterile plants in three different random‐mating populations. Seed density was determined for 192 male‐sterile plants in each population. In each population, 15 plants with the highest and 15 plants with lowest seed density were selected. Seeds of each selection were increased in the winter and tested the following summer at three locations in North Carolina with two replications per location. In those tests, the previously selected high and low density groups were not significantly different in seed density, seed weight, yield, or concentrations of protein and oil. Thus, single plant selection for seed density was ineffective for increasing seed density or seed protein concentration. An alternative selection method is proposed in which the selection unit is a selfed half‐sib or S 1 family. Desired gains selection indices for increased density and seed weight may increase both protein and yield in all three populations. This selection system has appeal because measurement of seed density and seed weight is relatively inexpensive, requiring less economic and land resources than actual measurement of yield and protein. It is recommended as a low‐cost way to improve initially unadapted populations.