Modelling expectation and variance for genotype by environment data

An integration of two types of models for the analysis of genotype by environment interaction is presented. On the one hand, the expectation of G × E interaction is frequently modelled by regression models; on the other hand, for deviations from these regressions, either separate stability parameters are defined or extra components of variance are introduced. A class of mixed models is described that contains facilities for modelling expectation by regression and, in addition, has extensive possibilities for dealing with heteroscedasticity. Practical aspects of the use of these mixed models are illustrated on a data set involving sugar yield in beet.

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