Random effects models, BLUPs and redundancy analyses for grain legume crops in semi-arid environments

Grain legume crops play a strategic role in cropping systems around the world, but their acceptance in European agriculture is rather low, because of low yield stability. We used a dataset comprising five to eleven genotypes for each of four legume crops (field pea, lentil, faba bean and chickpea) in four dry environments (two locations by two years). We focused on 'genotype by environment' interactions, by using several statistical techniques, such as random models, BLUPs and redundancy analysis. The main aim was to show how these techniques and the concomitant use of yield and other phenological/morphological traits as well as environmental data can help understand which species/genotypes are most adapted to dry environments and address the possible reasons for yield instability. Our results confirmed large environmental effects on the expression of phenology and productive traits, even though a shorter duration of the vegetative phase was associated to higher yields in most species and genotypes. The use of BLUPs gave information on the most suitable genotypes for each of the studied species, targeting the traits and environmental variables which are mostly related to yield level and stability. Baccara in field pea, Pantelleria in lentil, Gemini in faba bean and PA34 in chickpea showed high correlation between yield and precocity of the flowering stage. BLUPs for genotype means across environments emphasize that the reported genotypes where characterized by a low value of stability variance that implies the ability to keep an additive relationship between genotypic and environmental effects. This could represent a strategic issue for genotype selection.