The multi-environment trial, in which a number of genotypes is evaluated over a range of environmental conditions, is a standard experiment in plant breeding in general, and variety testing in particular. Useful statistical models for the analysis of multi-environment trials, with emphasis on the analysis of genotype by environment interaction, can be found in the classes of linear and bilinear models. Statistical properties of the most important representatives of these model classes are shortly reviewed. Structural differences between the models stem from: (1) the inclusion of random model terms in addition to fixed model terms; (2) the representation of the interaction by additive or multiplicative parameters; (3) the incorporation of concomitant variables on the levels of the environmental factor. For models with bilinear multiplicative structure for the interaction it is described how the interaction can be visualized by biplots. An illustration of the application of the models and biplots is given in a companion paper.
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van Eeuwijk, F.A. Linear and bilinear models for the analysis of multi-environment trials: I. An inventory of models. Euphytica 84, 1–7 (1995). https://doi.org/10.1007/BF01677551
- best linear unbiassed prediction
- factorial regression
- genotype by environment interaction
- multiplicative interaction
- reduced rank regression
- two-way table
- variance components
- variety trials