Search

Variation in crop performance is directly affected by the environment in which the plant grows. Analyses and estimation of genotype x environment interactions (GxE) have the potential to provide information about the characteristics of genotypes, identify elite genotypes and suitable environmental conditions, establish breeding objectives, and make recommendations for crop management practices. For the past half century, a variety of statistical models have been used for estimating GxE in plant breeding field experiments to facilitate the allocation of superior genotypes to the target population of environments. The most commonly used models are described in this review starting with linear regression and ANOVA models. We then describe modifications in the form of multiplicative models, models that can accommodate external variables, and mixed effect models. Quantification of differential effects of segments of a genome across environments is shown by exploiting marker x environment (MxE) interac-tions. We close with a brief overview of some nonparametric concepts that aim to understand genotypic stability. [ABSTRACT FROM AUTHOR]