Genotype x Environment Interaction and Repeatability of Traits

Abstract

Genotypes may differ considerably in the magnitude of performance in different environments. When genotypes perform differently in variable environments, genotype x environment interaction (G x E or GEI) has occurred. GEI poses a big challenge to maize breeders when developing varieties for release to farmers in a large geographical area, which is the case in West Africa (WA). Compulsorily, multi-locational environment trials (METs), involving the evaluation of a set of genotypes or varieties in many different environments within agroclimatic zones of WA, are used to identify stable, high-yielding genotypes for registration, release, and commercialization. The test locations used for the different types of Regional Uniform Variety Trials (RUVTs) since the time of WECAMAN (RUVT-early and RUVT extra-early) and now the DTMA/STMA trials for drought-tolerant varieties are not very representative and precisely discriminating. Therefore, there is a need to sample more testing sites in WA, using modern cultivars with high variation in mean performance; varieties developed during the last decade to identify sites which possess high representativeness, discriminating ability, and repeatability. In addition, because WA is large with several distinct agroclimatic zones that cut across the countries of the sub-region, there is a need to identify mega-environments for cultivar evaluation, release, and commercialization across WA. Such sites would be more appropriate for use in evaluating and selecting superior drought-tolerant genotypes as well as for serving as core testing sites within each agroclimatic zone, thereby minimizing human labor and research expenses. Several statistical tools are available for the analysis of data from METs. Among the most powerful tools are the additive main effects and multiplicative interaction (AMMI) and the GGE biplot. Many sets of data obtained during the last three decades were subjected to the statistical tools and the procedures used, results obtained, interpretation of the results, and possible application of the outcome to boost maize production in WA are presented in this Chapter.