Application of univariate, multivariate, and mixed models to the stability analysis of Ethiopian tetraploid wheat cultivars under irrigation condition

Abstract The testing of durum wheat ( Triticum turgidum subsp. durum ) varieties in different irrigated environments is critical for determining the stability of their performance and adaptation. In this study, 12 popular and newly developed durum wheat varieties were examined in eight irrigated locations with the purpose of investigating genotype–environment interaction and their effect on Ethiopian tetraploid wheat yield stability across diverse environments. The field experiment has two replications with a randomized complete block design. Multivariate (analysis of variance, additive main effect and multiplicative interaction [AMMI], and genetics, genetics × environment [GGE] biplot) and univariate (b i [regression coefficient], S 2 d [deviation from regression], σ i 2 [Shukla's stability variance], W i 2 [Wricke's ecovalence], YS i [yield stability statistic], and CV i [coefficient of variance]) analysis methods were used to identify stable varieties. The AMMI analysis showed that the genetic × environmental interaction was highly significant ( p > 0.01), while the genotype and environment variation were not significant. The first two principal component axes (IPCA1 and IPCA2) were highly significant ( p > 0.01) and contributed 79% of the total GE interaction. Univariate statistical models indicate that Bulala is a stable, high‐yielding variety that can adapt to various environments. GGE biplot analysis revealed that the eight test environments were clustered into three mega‐environments, ranked Bulala as the most stable variety across diverse environments. The results of the combined mean analysis, multivariate and univariate models revealed that Bulala is a high yielder (3.46 tons ha −1 ) and stable variety across all test environments, while Mukiye variety has a high yield (3.43 tons ha −1 ) but is not as stable or adaptive to multiple locations. As a result, Bulala was recommended for further demonstration and popularization in test locations and places with similar agroecologies under irrigation.

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Publication Details

Journal
Agrosystems Geosciences & Environment
Published
2024-10-28
DOI
https://doi.org/10.1002/agg2.20574
Citations
3
Primary Topic
Genetics and Plant Breeding
Type
article
Field-Weighted Citation Impact
1.80
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article

Application of univariate, multivariate, and mixed models to the stability analysis of Ethiopian tetraploid wheat cultivars under irrigation condition

Girma Mengistu, Urgaya Balcha, Tilahun Bayisa, Geleta Gerema
3 citations
Agrosystems Geosciences & Environment
Genetics and Plant Breeding
1.80
article

Application of univariate, multivariate, and mixed models to the stability analysis of Ethiopian tetraploid wheat cultivars under irrigation condition

Girma Mengistu, Urgaya Balcha, Tilahun Bayisa, Geleta Gerema
article en
3 citations

Abstract

Abstract The testing of durum wheat ( Triticum turgidum subsp. durum ) varieties in different irrigated environments is critical for determining the stability of their performance and adaptation. In this study, 12 popular and newly developed durum wheat varieties were examined in eight irrigated locations with the purpose of investigating genotype–environment interaction and their effect on Ethiopian tetraploid wheat yield stability across diverse environments. The field experiment has two replications with a randomized complete block design. Multivariate (analysis of variance, additive main effect and multiplicative interaction [AMMI], and genetics, genetics × environment [GGE] biplot) and univariate (b i [regression coefficient], S 2 d [deviation from regression], σ i 2 [Shukla's stability variance], W i 2 [Wricke's ecovalence], YS i [yield stability statistic], and CV i [coefficient of variance]) analysis methods were used to identify stable varieties. The AMMI analysis showed that the genetic × environmental interaction was highly significant ( p > 0.01), while the genotype and environment variation were not significant. The first two principal component axes (IPCA1 and IPCA2) were highly significant ( p > 0.01) and contributed 79% of the total GE interaction. Univariate statistical models indicate that Bulala is a stable, high‐yielding variety that can adapt to various environments. GGE biplot analysis revealed that the eight test environments were clustered into three mega‐environments, ranked Bulala as the most stable variety across diverse environments. The results of the combined mean analysis, multivariate and univariate models revealed that Bulala is a high yielder (3.46 tons ha −1 ) and stable variety across all test environments, while Mukiye variety has a high yield (3.43 tons ha −1 ) but is not as stable or adaptive to multiple locations. As a result, Bulala was recommended for further demonstration and popularization in test locations and places with similar agroecologies under irrigation.

Agrosystems Geosciences & EnvironmentVol. 7(4)
Ethiopian Institute of Agricultural Research (ET), Adama Science and Technology University (ET)
Life in Land
Openalex Percentile: Top 13%
Genetics and Plant Breeding
1.80
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