AMMI and GGE biplot analyses of root yield performance of cassava genotypes in forest and coastal ecologies.

Abstract

Multiple environment trials (MET) are generally carried out by plant breeders to select and recommend high yielding and stable genotypes for a set of environments. The analysis of MET data often results in genotype-byenvironment interactions which often causes difficulties in the interpretation of results and reduce efficiency in selecting the best genotypes. AMMI and GGE biplot analysis are two recent methods that are widely used to overcome these difficulties in MET data analysis. The objective of this study was to compare GGE biplot and AMMI analysis that determine the most efficient method for evaluating and describing genotype performance across environments. Ten (10) cassava (Manihot esculenta) genotypes including two local checks were evaluated across six (6) environments in Southern Ghana. The experimental layout was a randomized complete block design with three replications. The Additive Main Effects and Multiplicative Interaction (AMMI) analysis of variance identified highly significant effects for environment, genotype and genotype by environment interaction denoting different responses of genotypes across environments. The AMMI1 biplot identified AR14-10, CR42-4 and CR59-4 as the most stable genotypes but could not accurately display the performance of a given genotype in a given environment. However, the GGE biplot provided more information with regards to environments and genotype performance than the AMMI1 biplot analysis and was able to identify the environment PK08 as being the most representative and desirable of all.