Genomic predictive ability for foliar nutritive traits in perennial ryegrass

Forage nutritive value impacts animal nutrition, which underpins livestock’s productivity, reproduction and health. Improving nutritive value in perennial ryegrass will enhance animal nutrition and thus on-farm value to farmers. The aim of the present study was to investigate genotypic and environmental variation for a range of nutritive traits to support the design of future breeding strategies, including genomic selection (GS). A multi-population (n = 5) GS training set comprising 517 half-sib families was evaluated in two distinct New Zealand environments. Harvested samples were analysed for 18 nutritive quality traits associated with fibre, protein, energy and minerals. Phenotypic analysis was performed for the complete training set, as well as on the five individual populations, using linear mixed model. Significant (P<0.05) genotypic variation was detected for all nutritive traits and repeatability (R) was moderate to high (0.26 to 0.75). Narrow-sense heritability (h2n) for the same trait varied in individual populations and was due to differences in additive variation in each population. These results indicate that nutritive traits can be improved through selective breeding and opportunities exist to implement GS. Genotype-by-environment (G x E) interactions were significant and particularly large for soluble sugars, fat, crude protein and phosphorus. For traits with large G x E interactions, multi-trait selection approaches may be explored, utilising genotypic correlation amongst traits reported in this study.