Abstract
The objectives of this work were to evaluate the genotype x environment (GxE) interaction for popcorn and to compare two multivariate analyses methods. Nine popcorn cultivars were sown on four dates one month apart during each of the agricultural years 1998/1999 and 1999/2000. The experiments were carried out using randomized block designs, with four replicates. The cv. Zélia contributed the least to the GxE interaction. The cv. Viçosa performed similarly to cv. Rosa-claro. Optimization of GxE was obtained for cv. CMS 42 for a favorable mega-environment, and for cv. CMS 43 for an unfavorable environment. Multivariate analysis supported the results from the method of Eberhart & Russell. The graphic analysis of the Additive Main effects and Multiplicative Interaction (AMMI) model was simple, allowing conclusions to be made about stability, genotypic performance, genetic divergence between cultivars, and the environments that optimize cultivar performance. The graphic analysis of the Genotype main effects and Genotype x Environment interaction (GGE) method added to AMMI information on environmental stratification, defining mega-environments and the cultivars that optimized performance in those mega-environments. Both methods are adequate to explain the genotype x environment interactions.
Highlights
Additive Main effects and Multiplicative Interaction analysis (AMMI) allows for a large set of technical interpretations (Duarte & Vencovsky, 1999) and uses a principal component to interpret cultivar performance. Yan et al (2000) proposed Genotype main effects and Genotype x Environment interaction (GGE) Biplot analysis for graphic interpretation of the genotype x environment interactions
Interaction, the GGE Biplot analysis considers that only the G and genotype x environment (GxE) effects are relevant and that they need to be considered simultaneously when evaluating cultivars
Yan & Rajcan (2002) described the results of two multivariate analysis techniques (GGE Biplot and Genotype-Trait (GT) Biplot) by means of graphics, to describe the GxE interaction and genotypes for several soybean traits. They concluded that the analyses identified the GxE interaction and a single megaenvironment
Summary
Additive Main effects and Multiplicative Interaction analysis (AMMI) allows for a large set of technical interpretations (Duarte & Vencovsky, 1999) and uses a principal component (autovector) to interpret cultivar performance. Yan et al (2000) proposed Genotype main effects and Genotype x Environment interaction (GGE) Biplot analysis for graphic interpretation of the genotype x environment interactions. Additive Main effects and Multiplicative Interaction analysis (AMMI) allows for a large set of technical interpretations (Duarte & Vencovsky, 1999) and uses a principal component (autovector) to interpret cultivar performance. Yan et al (2000) proposed Genotype main effects and Genotype x Environment interaction (GGE) Biplot analysis for graphic interpretation of the genotype x environment interactions. Interaction, the GGE Biplot analysis considers that only the G and GxE effects are relevant and that they need to be considered simultaneously when evaluating cultivars. The graphic axes take the environment as fixed effect. This analysis identifies which cultivars are superior and identifies mega-environments, i.e., environmental groupings having the same cultivar as superior in the trait under evaluation
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