GENETIC DIVERSITY PATTERNS IN NORTH-AMERICAN PUBLIC SOYBEAN CULTIVARSBASED ON COEFFICIENT OF PARENTAGE

The genetic relatedness of North American soybean [Glycine max (L.) (M err.)] may threaten long-term breeding progress. To alleviate this pro blem, we propose that breeders diversify applied programs by capitaliz ing upon genetic patterns that may exist in cultivated germplasm. To d ate, only one diversity pattern, the well-known North-South distinctio n, is explained in applied breeding. Our objective was to identify and quantify additional factors influencing diversity in 258 cultivars re leased by public agencies during 1945 to 1988. We theorized that matur ity group effects (MG, as a hybridization restriction factor), locatio n of breeding programs (BP, as a selection factor), and breeder intuit ion and success factors beyond MG and BP may all influence the soybean cultivar diversity patterns. The patterns of diversity associated wit h the first two factors, MG and BP, were examined by quantifying avera ge coefficient of parentage (r) within and between MG and BP. Multidim ensional scaling (MDS) was applied to the r matrix to produce coordina tes for pictorial depiction of MG and BP. To examine the third factor, breeder intuition and success, the MDS coordinates were also subjecte d to a nonhierarchical cluster analysis that revealed nine major clust ers of soybean cultivars. A regression analysis was employed to determ ine the relative importance of North-South, MG, BP, and cluster patter ns in explaining variation in the r matrix. The South-North distinctio n accounted for only 21% of variability in cultivar relations indicati ng the presence of other major patterns of diversity. The MG, BP, and clusters independently explained 32, 42, and 57% of the total variatio n in the cultivar pedigrees. Clusters most efficiently revealed patter ns of diversity, and we propose the use of these clusters in the furth er study and management of soybean diversity. Multidimensional sealing coupled with nonhierarchical cluster analysis was a highly promising approach to the study of diversity.