Cereal crop breeders have achieved considerable genetic gain in genetically complex traits,
such as grain yield, while maintaining genetic diversity. However, focus on selection for yield …

Implementing genomic-based prediction models in genomic selection requires an
understanding of the measures for evaluating prediction accuracy from different models and …

Genomic prediction is a promising approach for accelerating the genetic gain of complex
traits in wheat breeding. However, increasing the prediction accuracy (PA) of genomic …

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

Genomic selection (GS) models have been validated for many quantitative traits in wheat
(Triticum aestivum L.) breeding. However, those models are mostly constrained within 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 …

Traits with a complex unknown genetic architecture are common in breeding programs.
However, they pose a challenge for selection due to a combination of complex …

Key message Early generation genomic selection is superior to conventional phenotypic
selection in line breeding and can be strongly improved by including additional information …

Genomic prediction of complex traits, say yield, benefits from including information on
correlated component traits. Statistical criteria to decide which yield components to consider …

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 …