The availability of dense molecular markers has made possible the use of genomic selection in plant and animal breeding. However, models for genomic selection pose several computational and statistical challenges and require ...

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The ...

Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this ...

Genomic selection (GS) has been implemented in animal and plant species, and is regarded as a useful tool for accelerating genetic gains. Varying levels of genomic prediction accuracy have been obtained in plants, depending ...

The marker ´ environment interaction (M´E) genomic model can be used to generate predictions for untested individuals and identify genomic regions in which effects are stable across environments and others that show ...

Today, breeders perform genomic-assisted breeding to improve more than one trait. However, frequently there are several traits under study at one time, and the implementation of current genomic multiple-trait and ...