The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and Evaluation

Perennial ryegrass (Lolium perenne L.) is a cornerstone forage species in temperate dairy systems worldwide, valued for its high yield potential, nutritive quality, and grazing recovery. However, current regional evaluation systems face challenges in accurately assessing complex traits like seasonal dry matter yield due to polygenic nature, environmental variability, and lengthy evaluation cycles. This review examines the evolution of perennial ryegrass evaluation systems, from regional frameworks—like Australia’s Forage Value Index (AU-FVI), New Zealand’s Forage Value Index (NZ-FVI), and Ireland’s Pasture Profit Index (PPI)—to advanced genomic prediction (GP) approaches. We discuss prominent breeding frameworks—F2 family, Half-sib family, and Synthetic Population—and their integration with high-throughput genotyping technologies. Statistical models for GP are compared, including marker-based, kernel-based, and non-parametric approaches, highlighting their strengths in capturing genetic complexity. Key research efforts include representative genotyping approaches for heterozygous populations, disentangling endophyte–host interactions, extending prediction to additional economically important traits, and modeling genotype-by-environment (G × E) interactions. The integration of multi-omics data, advanced phenotyping technologies, and environmental modeling offers promising avenues for enhancing prediction accuracy under changing environmental conditions. By discussing the combination of regional evaluation systems with GP, this review provides comprehensive insights for enhancing perennial ryegrass breeding and evaluation programs, ultimately supporting sustainable productivity of the dairy industry in the face of climate challenges.