Genomic prediction of optimal cross combinations to accelerate genetic improvement of soybean (Glycine max).

ABSTRACT: Improving yield is a primary soybean breeding goal, as yield is the main determinant of soybean's profitability. Within the breeding process, selection of cross combinations is one of most important elements. Cross prediction will assist soybean breeders in identifying the best cross combinations among parental genotypes prior to crossing, increasing genetic gain and breeding efficiency. In this study optimal cross selection methods were created and applied in soybean and validated using historical data from the University of Georgia soybean breeding program, under multiple training set compositions and marker densities utilizing multiple genomic selection models for marker evaluation. Plant materials consisted of 702 advanced breeding lines evaluated in multiple environments and genotyped

SUBMITTER: Miller MJ 

PROVIDER: S-EPMC10206060 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature