Denis, Jean-Baptise and Gower, John C.
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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 recom- mendation and genotype selection.
|Item Type:||Journal Article|
|Copyright Holders:||1996 Royal Statisical Society|
|Keywords:||asymptotic variances and covariances; biadditive models; biplot; confidence regions; genotype-by-environment interactions; Tukey non-additivity; two-way tables|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Depositing User:||Sarah Frain|
|Date Deposited:||11 May 2011 09:55|
|Last Modified:||04 Oct 2016 10:47|
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