Genomic Prediction and Genotype-by-Environment Interaction Analysis of Crown and Stem Rust in Ryegrasses in European Multi-Site Trials

Climate change calls for novel approaches to include environmental effects in future breeding programs forage crops. A set of ryegrasses (Lolium) varieties was evaluated multiple European environments crown rust (Puccinia coronata f. sp. lolii) and stem (P. graminis graminicola) resistance. Additive Main Effect Multiplicative Interaction (AMMI) analysis revealed significant genotype (G) environment (E) as well the interaction both factors (G × E). Genotypes plus Genotype-by-Environment (GGE) grouped tested mega-environments traits suggesting presence an effect on performances. The best performing given showed high resistance rust, overall, tetraploid performed better than diploid. Furthermore, we modeled G E using a marker x (M E) model predict performance some years but not others. Our results that despite limited number varieties, observations allowed us traits’ performances with accuracy. genomic prediction multi trials could enhance ryegrasses.