Asymptotic Confidence Regions for Biadditive Models: Interpreting Genotype‐Environment Interactions

Jean‐Baptiste Denis and John C. Gower

Journal of the Royal Statistical Society Series C, 1996, vol. 45, issue 4, 479-493

Abstract: 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.

Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:45:y:1996:i:4:p:479-493

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