Key message The optimization of training populations and the use of diagnostic markers as
fixed effects increase the predictive ability of genomic prediction models in a cooperative …

Key message Genomic predictions across environments and within populations resulted in
moderate to high accuracies but across-population genomic prediction should not be …

Genomic selection (GS) offers breeders the possibility of using historic data and unbalanced
breeding trials to form training populations for predicting the performance of new lines …

Genomic prediction (GP) is now routinely performed in crop plants to predict unobserved
phenotypes. The use of predicted phenotypes to make selections is an active area of …

Incorporating secondary correlated traits collected from high-throughput phenotyping in
genomic selection (GS) models for complex traits has been demonstrated to improve …

Genomic selection applied to plant breeding enables earlier estimates of a line's
performance and significant reductions in generation interval. Several factors affecting …

Background Genomic selection has the potential to increase genetic gains by using
molecular markers as predictors of breeding values of individuals. This study evaluated the …

Genomic selection (GS) is a promising tool for plant and animal breeding that uses genome‐
wide molecular marker data to capture small and large effect quantitative trait loci and …

Genomic selection (GS) uses genome‐wide molecular marker data to predict the genetic
value of selection candidates in breeding programs. In plant breeding, the ability to produce …

Genomic selection (GS) is a breeding tool that estimates breeding values (GEBVs) of
individuals based solely on marker data by using a model built using phenotypic and marker …