Sites Regression GGE Biplot Analysis of Haricot Bean <i>(Phaseolus vulgaris </i>L.<i>)</i> Genotypes in three Contrasting Environments

Abstract

Fourteen haricot bean genotypes were evaluated at three contrasting environments in Ethiopia during 2007-2009 main cropping seasons. The objective of the study was to determine the magnitude and pattern of G × E interaction and yield stability, and to determine the best performing varieties for selection environments. The study was conducted using a randomized complete block design with 4 replications. G × E interaction and yield stability were estimated using the sites regression genotype plus G × E interaction biplot. Pooled analysis of variance for grain yield showed significant (p ≤ 0.001) differences among the genotypes, environments and for G × E interaction effects. This indicated that the genotypes differentially responded to the changes in the test environments or the test environments differentially discriminated the genotypes or both. Environment accounted for 50.2% of the total yield variation, genotype for 29.1% and G × E interaction for 18.3%, indicating the necessity for testing haricot bean varieties at multi-locations and over years. The first two multiplicative component terms sum of squares of the GGE biplot explained 85.76% of the interaction sum of squares. There were no single genotypes that showed generally superior performance across all the test environments but genotype 213-FOT-15 followed by other three better performing genotypes including 551-SEQ-1024, BAYOMADERO-75 and ZEBRA, were ranked first in 78% and 67% of the nine test environments, respectively and identified as stable based on GGE analysis. Generally, the application of sites regression GGE biplots facilitated the visual comparison and identification of superior genotypes, thereby supporting decisions on haricot bean variety selection and recommendation in different environments.