Statistical Analysis of Genotype by Environment Interactions and Grain Yield Stability in Bread Wheat Using Anova and Ammi Models
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Date
2011-06
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Addis Abeba university
Abstract
In agricultural experimentation involving Genotype by Environment interactions, a large
number of genotypes are normally tested over a wide range of environments and the
underlying statistical and genetical theories used to model this system may be rather
complicated. The occurrence of the Genotype by Environment interaction further
complicates the selection of superior genotypes for a target population of environments.
In the absence of Genotype by Environment interaction, the superior genotype in one
environment may be regarded as the superior genotype in all, where as the presence of
the Genotype by Environment interaction confirms particular genotypes being superior in
particular environments. Therefore, Genotype by Environment interaction plays an
important role in identifying genotypes for high and stable yield. The goal of this study
were to analyze Genotype by Environment interaction and stability of the Ethiopian
wheat hybrids for grain yield across the target environments, and to observe the pattern of
grouping of the genotypes and the environments based on grain yield response of the
hybrids. This study was carried out on the yield performance of 20 bread wheat
genotypes across 8 environments in Ethiopia for two growing seasons. The experimental
layout was a randomized complete block design with four replications. The combined
ANOVA (AMMI ANOVA) showed that environments, genotypes and Genotype by
Environment interactions were highly significant (p<0.01) and they accounted for
80.91%, 3.37% and 4.6% of the total variation. The high percentage of the environment
is an indication that the major factor that influence yield performance of bread wheat in
Ethiopia is the environment. The best fit AMMI model for this multi-environment yield
trial data was AMMI-4. Out of the total interactions of principal component analysis
(IPCAs), the first four IPCA axes explained 82.63% of the Genotype by Environment
interaction sum of squares. However, the biplot (the first two IPCAs) captures 62.32% of
the interaction SS. The biplots showed G6, G4 and G9 were more stable genotypes while
G10, G20, G16, G18 and G3 were unstable varieties.
Key words: AMMI, Genotype by Environment interaction
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Keywords
AMMI, Genotype by Environment Interaction