… Our study involved 9 multi-environment real data sets used in genomic selection of wheat
and maize breeding programs. The data sets comprise a large number of wheat and maize …

… multi-environment breeding trials in which not all genotypes of interest are grown in each
environment. Using genomic-enabled prediction … combinations can be predicted. Consequently…

… genomic prediction models to target a single trait at a time. An advantage of multivariate
prediction … of multi-trait and multi-environment prediction models to predict five key traits of …

… approach for genomic prediction, but also that the deep learning method is a practical
approach for predicting univariate and multivariate traits in the context of genomic selection. …

… Across-location prediction accuracies varied from 0.25–0.50, 0.28–0.48, to 0.31–0.56 for
uni-trait, multi-trait, and multi-trait multi-environment models, respectively, for seven traits …

… A suitable genomic prediction modeling strategy can potentially address this challenge
through ME genomic prediction models. In this study, we evaluated genomic prediction …

… Success in any genomic prediction platform is directly … on genomic prediction,
considering multi-trait multi-environment … -trait multi-environment trials and multi-trait multi-environment …

… The objectives of this study were to (i) confirm the value of multivariate genomic prediction
models in the context of METs with G\(\times\)E, (ii) present new CD criteria derived from those …

… for the prediction of phenotypes or breeding values of genotypes on unobserved individuals.
Most genomic prediction approaches predict … In this study, genomic prediction models were …

… Performances of single-environment and multi-environment genomic prediction models
were compared using kernel regression based methods (GBLUP and RKHS) under two cross …