scholarly journals Use of Parametric and Non-Parametric Methods for Genotype × Environment Interaction Analysis in Bread Wheat Genotypes

2018 ◽  
Vol 4 (2) ◽  
pp. 75-88
Author(s):  
Mohtasham Mohammadi ◽  
Rahmatollah Karimizadeh ◽  
Tahmaseb Hosseinpour ◽  
Hasan Ghojogh ◽  
Kamal Shahbazi ◽  
...  
Keyword(s):  
Bread Wheat ◽  
Interaction Analysis ◽  
Environment Interaction ◽  
Parametric Methods ◽  
Wheat Genotypes ◽  
Genotype Environment Interaction ◽  
Non Parametric

scholarly journals Analysis of genotype × environment interaction in rain-fed durum wheat of Iran using GGE-biplot and non-parametric methods

2012 ◽  
Vol 92 (4) ◽  
pp. 757-770 ◽  
Author(s):  
Reza Mohammadi ◽  
Ahmed Amri
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Environment Interaction ◽  
Parametric Methods ◽  
Gge Biplot ◽  
Ge Interaction ◽  
Yield Data ◽  
Stability Performance ◽  
Genotype Environment Interaction ◽  
Non Parametric

Mohammadi, R. and Amri, A. 2012. Analysis of genotype × environment interaction in rain-fed durum wheat of Iran using GGE-biplot and non-parametric methods. Can. J. Plant Sci. 92: 757–770. Multi-environment trials (MET) are conducted annually throughout the world in order to use the information contained in MET data for genotype evaluation and mega-environment identification. In this study, grain yield data of 13 durum and one bread wheat genotypes grown in 16 diversified environments (differing in winter temperatures and water regimes) were used to analyze genotype by environment (GE) interactions in rain-fed durum MET data in Iran. The main objectives were (i) to investigate the possibility of dividing the test locations representative for rain-fed durum production in Iran into mega-environments using the genotype main effect plus GE interaction (GGE) biplot model and (ii) to compare the effectiveness of the GGE-biplot and several non-parametric stability measures (NPSM), which are not well-documented, for evaluating the stability performance of genotypes tested and the possibility of recommending the best genotype(s) for commercial release in the rain-fed areas of Iran. The results indicate that the grain yield of different genotypes was significantly influenced by environmental effect. The greater GE interaction relative to genotype effect suggested significant environmental groups with different top-yielding genotypes. Warm environments differed from cold environments in the ranking of genotypes, while moderate environments were highly divergent and correlated with both cold and warm environments. Cold and warm environments were better than moderate environments in both discriminating and representativeness, suggesting the efficiency and accuracy of genotype selection would be greatly enhanced in such environments. According to the NPSM, genotypes tend to be classified into groups related to the static and dynamic concepts of stability. Both the GGE-biplot and NPSM methods were found to be useful, and generally gave similar results in identifying high-yielding and stable genotypes. In contrast to NPSM, the GGE-biplot analysis would serve as a better platform to analyze MET data, because it always explicitly indicates the average yield and stability of the genotypes and the discriminating ability and representativeness of the test environments.

scholarly journals Genotype environment interaction analysis for fruit yield in okra (Abelmoschus esculentus L.) under alkaline environments

2021 ◽  
Vol 81 (01) ◽  
pp. 101-110
Author(s):  
Satish Kumar Sanwal ◽  
Anita Mann ◽  
Hari Kesh ◽  
Gurpreet Kaur ◽  
Raj Kumar ◽  
...  
Keyword(s):  
Interaction Analysis ◽  
Stability Index ◽  
Genotype By Environment Interaction ◽  
Fruit Yield ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Alkaline Environments ◽  
Prone Area ◽  
Marketable Fruit ◽  
Ph Range

Twenty four Okra genotypes were evaluated for marketable fruit yield and its related traits for genotype environment interaction during 2015-16 and 2016-17. The genotypes were exposed to alkaline environment with a pH range of 8.0±0.2, 8.5±0.2, 9.0±0.2 and 9.5±0.2. A significant level of deviation in expression of different traits was observed in all the genotypes with increasing pH. Based on Additive Main Effects and Multiplicative Interaction (AMMI), Genotype and Genotype Environment Interaction (GGE) biplot, Wrick’s ecovalence (Wi2 ), AMMI Stability Value (ASV) and Yield Stability Index (YSi) stable genotypes with high fruit yield were identified over the eight environments. The combined AMMI analysis of variance indicated that genotype main effect, environment and genotype-by-environment interaction effects showed variation of 19.83%, 63.07% and 17.10%, respectively for fruit yield. On the basis of different stability measures, VRO-112, VRO-110, Kashi Kranti, VROB178, AE-70 and VRO-108 were differentiated as high yielding and stable genotypes over the tested environments. This study will be helpful for selecting alkali tolerant okra parents for further breeding programme and recommending the suitable genotypes for alkalinity prone area

Evaluation of genotype × environment interaction and stability of corn hybrids and relationship among univariate parametric methods

2014 ◽  
pp. 140519061247009
Author(s):  
Mahdi Changizi ◽  
Rajab Choukan ◽  
Eslam Majidi Heravan ◽  
Mohammad Reza Bihamta ◽  
Farrokh Darvish
Keyword(s):  
Environment Interaction ◽  
Parametric Methods ◽  
Corn Hybrids ◽  
Genotype Environment Interaction

scholarly journals Genotype x environment interaction of wheat genotypes under salinity environments

2017 ◽  
Vol 3 (1) ◽  
pp. 38-43
Author(s):  
Md Saleh Uddin ◽  
Md Sultan Alam ◽  
Nasrin Jahan ◽  
Kazi Md Wayaz Hossain ◽  
Md Ali Newaz
Keyword(s):  
Grain Yield ◽  
Grain Weight ◽  
Environment Interaction ◽  
Stability Parameters ◽  
Wheat Genotypes ◽  
Genotype X Environment ◽  
Genotype Environment Interaction ◽  
Days To Heading ◽  
Salinity Levels ◽  
1000 Grain Weight

Genotypes x environment interaction as well as stability of performance were determined for grain yield and yield contributes of 12 wheat genotypes under four salinity levels of environments (control, 8, 12, 16 dS/m). Significant genotype-environment interaction (linear) for days to heading, plant height, number of spikes per plant and grains per spikes, 1000-grain weight and grain yield per plant at 1% level of probability when tested against pooled deviation. Both the environment (linear) and genotype x environment (linear) components of variation for stability were also significant indicating that prediction of the genotypes on the environment appeared feasible for all the characters. The variance due to pooled deviation was significant for only days to heading. Considering all the three stability parameter, genotype G11 was found most stable among all the genotypes for grain weight of wheat. Among the genotypes G11, G22, G24, G33 and G40 were most desirable for yield per plant. The genotype G32 showed more responsiveness to changing environment and was suited only for highly favorable environments. Based on three stability parameters, G11, G22 and G37 were the most stable and desirable genotypes with reasonable good yield among the all.Asian J. Med. Biol. Res. March 2017, 3(1): 38-43

Modeling Genotype × Environment Interaction Using Additive Genetic Covariances of Relatives for Predicting Breeding Values of Wheat Genotypes

Crop Science ◽  
2006 ◽  
Vol 46 (4) ◽  
pp. 1722-1733 ◽  
Author(s):  
Jose Crossa ◽  
Juan Burgueño ◽  
Paul L. Cornelius ◽  
Graham McLaren ◽  
Richard Trethowan ◽  
...  
Keyword(s):  
Environment Interaction ◽  
Breeding Values ◽  
Wheat Genotypes ◽  
Genotype Environment Interaction ◽  
Genetic Covariances
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