Asymptotic Confidence Regions for Biadditive Models: Interpreting Genotype--Environment Interactions.

An understanding of how genotypes of an agricultural crop interact with the environment in which they are grown is important for assessing plant production. A breeding trial for 21 genotypes of rye-grass grown at seven locations is used to illustrate the interpretation of genotype-environment interactions. Statisticians have proposed many ways of modelling these interactions, but a subclass of bilinear models, that we term biadditive, fits especially well. We emphasize assessing and interpreting the interaction parameters of biadditive models by constructing confidence regions in biplot representations. When a biadditive model is valid, this new development underpins better informed decisions on variety recommendation and genotype selection. [ABSTRACT FROM AUTHOR]