Pattern analysis of multi-environment trials in common bean genotypes

Agenor Martinho Correa,Paulo Eduardo Teodoro,Manoel Carlos Gonçalves

doi:10.14393/bj-v32n2a2016-29572

Abstract

The aim of this study was to use the patterns analysis technique to investigate the grain yield of 13 common bean genotypes evaluated in 12 environments in the State of Mato Grosso do Sul, under presence of genotype x environment interaction (G x E). The trials were conducted between the years 2000-2006 at Universidade Estadual de Mato Grosso do Sul, Unit of Aquidauana, and at Faculdade de Ciencias Agrarias da Universidade Federal da Grande Dourados. Have been identified nine groups of genotypes and environments. It were submitted the grain yield data to individual and joint variance analysis. Subsequently, it was performed the pattern analysis, which was made the cluster of genotypes and environments with similar patterns and its means grouping by Scott-Knott’s test. The first two principal components of ordination analysis explained 56.6% of the total variation of G x E interaction data. Pattern analysis proved to be efficient in identifying groups of environments that discriminate similarly genotypes, genotypes with similar performance in all environments, and in the description of the genotypes stability patterns.

Highlights

In the common bean breeding programs, it is tested a large number of genotypes annually in different environments before its final recommendation and multiplication (CORRÊA et al, 2015)
The aim of this study was to use the patterns analysis technique to investigate the grain yield of 13 common bean genotypes evaluated in 12 environments in the State of Mato Grosso do Sul, under presence of genotype x environment interaction (G x E)
We evaluated grain yield (YIE) considering the production of the harvested area in the plot transformed into kg ha-1 of grains

Summary

Introduction

In the common bean breeding programs, it is tested a large number of genotypes annually in different environments before its final recommendation and multiplication (CORRÊA et al, 2015). In most cases, these environments are distinct, and there is an interaction between the genotype and environment (G x E), which affects the gain with selection and makes necessary to estimate the magnitude and the nature of this interaction. These estimates allow assessing the real impact of selection and ensure high reliability in the genotype recommendation for a specific place or environment groups (ROSADO et al, 2012). It is necessary to realize adaptability and phenotypic stability analysis, in which the identification of genotypes with predictable behavior is possible, that are responsive to environmental variations in specific or broad conditions (CRUZ et al, 2014)

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