AMMI analysis to comprehend genotype-by-environment (G × E) interactions in rainfed grown soybean [<i>Glycine max</i>. (L)Merrill]

Birla, Dilip; Ramgiry, S. R.

doi:10.5958/0976-058x.2015.00005.0

Cited by 3 publications

(3 citation statements)

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“…Genotype×environment interactions have been defined as a failure of genotypes to achieve the same relative performance in different environments (Baker, 1988). Analysis of genotype×environment interactions on grain yield and estimation of phenotypic stability in barley and other crops has been widely studied (Voltas, et al 1999;Mohammadi and Mahmodi, 2008;Rodriguez, et al 2008;Ahmadi, et al 2012;Mladenov et al 2012;Mohammadi et al 2013;Mortazavian, et al 2014;Sarkar, et al 2014;Karimzadeh et al 2016;Birla and Ramgiry, 2015;Vir and Sultan, 2012;Sahay and Sarma, 2005). There are two major approaches to studying genotype×environment interactions and determining the adaptation of genotypes (Huen, 1996).…”

Section: Introductionmentioning

confidence: 99%

Grain yield stability of barley genotypes in uniform regional yield trails in warm and semi warm dry land area

Khanzadeh

Vaezi

Mohammadi

et al. 2017

IJARe

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The aim of this study was to assess the effect of GEI on grain yield of barley advanced lines and exploit the positive GEI effect using AMMI and SREG GGE biplot analysis. Therefore, 18 lines were evaluated at five research station s (Ghachsaran, Mogan, Lorestan, Gonbad and Ilam) of Dryland Agricultural Research Institute (DARI), in the semi-warm regions in Iran, in 2012, 2013 and 2014 cropping seasons under rain-fed conditions. Analysis of variance showed that grain yield variation due to the environments, genotypes and GE interaction were highly significant (p<0.01), which accounted for 68.9%, 9.3% and 22.7% of the treatment combination sum of squares, respectively. To determine the effects of GEI on yields, the data were subjected to AMMI and GGE biplot analysis. The first five AMMI model terms were highly significant (p<0.01) and the first two terms explained 59.56% of the GEI. There were two mega-environments according to the SREG GGE model. The best genotype in one location was not always the best in other test locations. According to AMMI1 biplot, G2, G4, G5 and G6 were better than all other genotypes across environments. G2 was the ideal genotype to plant in Gachsaran. It seems that Ghachsaran is the stable environment between the environments studied and next in rank was Gonbad. In finally, the ATC method indicated that G1, G3, G4 and G6 were more stable as well as high yielding.

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Section: Introductionmentioning

confidence: 99%

Grain yield stability of barley genotypes in uniform regional yield trails in warm and semi warm dry land area

Khanzadeh

Vaezi

Mohammadi

et al. 2017

IJARe

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“…They also advocated that they may be extended to other linear-bilinear models by fixing certain conditions. Birla and Ramgiry (2015) used AMMI analysis to comprehend genotype by environment (G × E) interaction in rain fed grown soybean [Glycine max (L.) Merrill]. Bhushan and Samnotra (2017) studies the stability for yield and quality trails in brinjal (Solanum melongena L).…”

Section: Introductionmentioning

confidence: 99%

Stability Variance and its Bayesian Estimation for Genotype × Environment Interaction in m × m Gracro-latin Square Layout

Datt

Chetan

2022

ASD

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Background: In agricultural, the field experimenters have been bona fide way of verifying the test result when researchers have developed new cultivating method in order to improve the overall crop production. To meet this requirement experimenters have continuously be measured in thinking the new and/or modified techniques and methodologies. Methods: To estimate stability variance with two treatments through Graceo-latin square layout apart from prevailing Latin square layout with one treatment. The maximal data information prior and asymptotically locally invariant prior are also studied for the obtained stability variance in such layout. Result: The Graceo-latin square design layout with two different treatments has been proposed to study genotype × environment (G × E) interaction. Statistical model for the design and ANOVA is also developed and simultaneous methods are proposed to diagrammatize the respective stability variance.

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“…The measured value of each cultivar in a test environment is the cumulative effect of genotype main effect (G), environment main effect (E) and the GE interaction (Yan and Kang, 2003). Birla and Ramgiry (2015)…”

Section: Introductionmentioning

confidence: 99%

A new index for evaluation of G×E interaction in pearl millet using AMMI and GGE biplot analyses

Mamata

Hooda

2019

IJARe

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Performance of a genotype is the result of its genetic constitution and the environment in which it has been grown. In practice, a particular variety may not exhibit the same phenotypic performance under different environments. Also, different varieties may respond differently to a specific environment. Additive Main effects and Multiplicative Interaction (AMMI) and GGE biplot analyses are the most frequently used models to explain G×E interaction of multi-environment cultivar trials. Based on climatic conditions, the pearl millet cultivation in India is divided in 3 major zones A1, A and B for effective evaluation of the pearl millet breeding material. In the present study, the G×E interaction in pearl millet genotypes from zone-A of India has been evaluated using the techniques of AMMI and GGE biplot analyses. A new Weighted Stability Index (WSI) has been proposed for determining the high yielding and stable genotypes based on the normalized indices for grain yield and ASV indices. The three interaction principal component axes (IPCA1, IPCA2 and IPCA3) have been found to be significant for this zone. AMMI Stability Value (ASV) and Stability Index have been used to find the most stable genotypes while indices YSI and WSI have been used to find both the most stable and high yielding genotypes. On the basis of ASV, genotypes MH 2120, MH 2109 and MH 2116 have been found to be the most stable for this Zone. The Spearman’s rank correlation coefficient between YSI and WSI was found to be significant at 1% level of significance indicating that the two indices have almost similar performance in determining high yielding stable genotypes.

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AMMI analysis to comprehend genotype-by-environment (G × E) interactions in rainfed grown soybean [Glycine max. (L)Merrill]

Cited by 3 publications

References 0 publications

Grain yield stability of barley genotypes in uniform regional yield trails in warm and semi warm dry land area

Grain yield stability of barley genotypes in uniform regional yield trails in warm and semi warm dry land area

Stability Variance and its Bayesian Estimation for Genotype × Environment Interaction in m × m Gracro-latin Square Layout

A new index for evaluation of G×E interaction in pearl millet using AMMI and GGE biplot analyses

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