Phenotypic modelling of crop adaptation

Plant breeders base many of the selection decisions on phenotype predictions obtained from multi-environment models fitted to field trial data. The quality of these predictions is affected by the within trial variation and by the heterogeneity of genotypic rankings across environments (genotype by environment interaction, G×E). Using an experimental design that allows to account for spatial variation within the trial is an essential step to obtain reliable estimates for the within-environment performance. This course will discuss about the principles of experimental design and illustrate them by means of commonly used designs as RCBD, lattice designs, alpha designs and row-column designs. Students will also be asked to design their own field trials. Issues related to the estimation of heritability, BLUPs and adjusted means will also be addressed. Phenotypes across multiple environments will be modelled focusing on G×E, and strategies to characterize the target population of environments (TPE) will be discussed. Environment classes will be used in mixed model framework to model phenotypes across the whole TPE. The course will consist of lectures, followed by computer exercises for each of the topics. Students will be invited to apply the models discussed during the lectures to plant breeding data.