Genomic selection (GS) is becoming an essential tool in breeding programs due to its role in
increasing genetic gain per unit time. The design of the training set (TRS) in GS is one of the …

Genetic progress of crop plants is required to face human population growth and guarantee
production stability in increasingly unstable environmental conditions. Breeding is …

Mixed cropping has been suggested as a resource-efficient approach to meet high produce
demands while maintaining biodiversity and minimizing environmental impact. Current …

Key message Training sets produced by maximizing the number of parent lines, each
involved in one cross, had the highest prediction accuracy for H0 hybrids, but lowest for H1 …

The present study is a transversal analysis of the interest in genomic selection for plant and
animal species. It focuses on the arguments that may convince breeders to switch to …

Key message Reciprocal recurrent selection sometimes increases genetic gain per unit cost
in clonal diploids with heterosis due to dominance, but it typically does not benefit …

Key message Model training on data from all selection cycles yielded the highest prediction
accuracy by attenuating specific effects of individual cycles. Expected reliability was a robust …

Key message Schemes that use genomic prediction outperform others, updating testers
increases hybrid genetic gain, and larger population sizes tend to have higher genetic gain …

Key message A reciprocal testcross design increases the relatedness among single crosses
and testcrosses, thereby increasing the effectiveness of genome-wide prediction in maize …

Key message Training population optimization algorithms are useful for efficiently training
genomic prediction models for single-cross performance, especially if the population is …