Prediction of breeding values and variance in (Lolium perenne L.) breeding populations

Perennial ryegrass (Lolium perenne L.) is the most important forage crop in temperate grassland agriculture, but acceleration of the rate of improvement of genetic gain is desirable. Genomic selection (GS) has the potential to achieve this, but prediction accuracies need to be sufficiently high to compete with phenotypic selection. Here we report the results of the performance of GS in the breeding programme at the Institute of Biological, Environmental and Rural Sciences (IBERS) using data from more generations than previously possible. Cross validation analysis showed that the highest prediction accuracies were obtained for dry matter digestibility (0.84) and water soluble carbohydrates (0.82). The accuracies for yield related traits ranged from 0.3 to 0.55. All accuracies represent an improvement on previous results. We also used the data to obtain predictions of the breeding values and their variance of all pairwise crosses of the population. Such data are likely to be helpful in deciding selections for variety generation and the population improvement cycle. The available variance is more important to preserve for the improvement cycle, while the highest possible combination of breeding values is needed for variety generatio