In this paper multiplicative mixed models have been used for the analysis of multi-
environment trial (MET) data for canola oil and grain yield. Information on pedigrees has …

The performance of hybrids can be predicted with gene expression data from their parental
inbred lines. Implementing such prediction approaches in breeding programs promises to …

With the improvement of high-throughput technologies in recent years, large multi-
dimensional plant omics data have been produced, and big-data-driven yield prediction …

Key message Integration of multi-omics data improved prediction accuracies of oat
agronomic and seed nutritional traits in multi-environment trials and distantly related …

Breeding for dry matter yield and persistence in alfalfa (Medicago sativa L.) can take several
years as these traits must be evaluated under multiple harvests. Therefore, genotype‐by …

Predicting single‐cross performance is of high importance to improve the efficiency of
sunflower (H elianthus annuus L.) hybrid breeding programmes. We used experimental data …

Abstract mRNA transcription profiles are an alternative to DNA markers for predicting hybrid
performance. Our objective was to investigate their prediction accuracy in an unbalanced …

Genomic selection (GS) is a powerful tool for improving genetic gain in maize breeding.
However, its routine application in large-scale breeding pipelines is limited by the high cost …

Key message Complementing genomic data with other “omics” predictors can increase the
probability of success for predicting the best hybrid combinations using complex agronomic …

Exploring and exploiting variety by environment (V× E) interaction is one of the major
challenges facing plant breeders. In paper I of this series, we presented an approach to …