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AMMI and GGE Biplot Analysis of Linseed (Linum usitatissimum L) Genotypes in Central and South-Eastern Highlands of Ethiopia
Author(s) -
Adane C. Chobe,
Abebe Delesa Ararsa
Publication year - 2018
Publication title -
journal of plant breeding and genetics/journal of plant breeding and genetics
Language(s) - English
Resource type - Journals
eISSN - 2308-121X
pISSN - 2305-297X
DOI - 10.33687/pbg.006.03.2785
Subject(s) - ammi , biplot , main effect , gene–environment interaction , interaction , principal component analysis , biology , genotype , randomized block design , yield (engineering) , agronomy , statistics , mathematics , genetics , materials science , gene , metallurgy
Twelve linseed genotypes were evaluated in 13 environments during the main cropping season in central highlands of Ethiopia. The objective of the study was to determine the magnitude and pattern of G × E interaction and yield stability in linseed genotypes. The study was conducted using randomized complete block design with 3 replications. Genotype × environment interaction and yield stability were estimated using the additive main effects and multiplicative interaction and site regression genotype plus genotype × environment interaction biplot. Pooled analysis of variance for seed yield showed significant (p ≤ 0.001) differences among the genotypes, environments and 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 effect was responsible for the greatest part of the variation, followed by G × E interaction and genotype effects, indicating spatial and temporal replications of linseed yield trials. The first three multiplicative component terms of AMMI were found to be significant. The first two multiplicative component terms sum of squares, with their cumulative degrees of freedom of 44, explained 62.9% of the interaction sum of squares. No single variety showed superior performance in all environments but CI-1525 demonstrated top ranking at six of the thirteen environments. The application of AMMI and GGE biplots facilitated the visual comparison and identification of superior genotypes, thereby supporting decisions on variety selection and recommendation in different environments

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