Paper SD15 Statistical Analysis of Genotype X Environment Interaction in Agricultural Research
نویسنده
چکیده
In agricultural experimentation, a large number of genotypes are normally tested over a wide range of environments (locations, years, growing seasons, etc.) and the underlying statistical and genetical theories used to model this system may be rather complicated. The occurrence of the genotype (G) X environment (E) interaction effect further complicates the selection of superior genotypes for a target population of environments. In the absence of G X E interaction, the superior genotype in one environment may be regarded as the superior genotype in all, whereas the presence of the G X E interaction confirms particular genotypes being superior in particular environments. A variety of statistical procedures are available to analyze the results of multi-environment trials. One of the most common methods in a G X E interaction study is to compute the simple averages across replications for a genotype in an environment and then analyzing the means. An alternative method of analyzing the data in a two-way table of means is the Additive Main Effects and Multiplicative Interaction (AMMI) model which combines the conventional analyses of variance for additive main effects with the principal components analysis (PCA) for the non-additive residuals. AMMI is frequently applied in yield trials in agricultural research when both main effects and interaction are important. Other methods (e.g., the regression of genotype means on the environment means) and selected SAS codes will be presented.
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