scholarly journals EVALUATION OF GENOTYPE BY ENVIRONMENT INTERACTION FOR GRAIN YIELD IN DURUM WHEAT USING NON-PARAMETRIC STABILITY STATISTICS

2016 ◽  
Vol 21 (1) ◽  
pp. 50 ◽  
Author(s):  
Yüksel KAYA ◽  
Musa TURKOZ
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Parametric Stability ◽  
Genotype By Environment ◽  
Stability Statistics ◽  
Non Parametric

Pattern analysis of genotype-by-environment interaction for grain yield in durum wheat

2009 ◽  
Vol 147 (5) ◽  
pp. 537-545 ◽  
Author(s):  
R. MOHAMMADI ◽  
A. AMRI ◽  
R. HAGHPARAST ◽  
D. SADEGHZADEH ◽  
M. ARMION ◽  
...  
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Pattern Analysis ◽  
Genotype By Environment Interaction ◽  
Interaction Matrix ◽  
Environment Interaction ◽  
Yield Data ◽  
Breeding Lines ◽  
Cold Environments ◽  
Genotype By Environment

SUMMARYPattern analysis, cluster and ordination techniques, was applied to grain yield data of 20 durum wheat genotypes grown in 19 diversified environments during 2005–07 to identify patterns of genotype (G), environment (E) and genotype-by-environment (G×E) interaction in durum multi-environment trials (METs). Main effects due to E, G and G×E interaction were highly significant, and 0·85 of the total sum of squares (SS) was accounted for by E. Of the remaining SS, the G×E interaction was almost 12 times the contribution of G alone. The knowledge of environmental and genotype classification helped to reveal several patterns of G×E interaction. This was verified by ordination analysis of the G×E interaction matrix. Grouping of environments, based on genotype performance, resulted in the separation of different types of environments. Pattern analysis confirmed the cold and warm mega-environments, and allowed the discrimination and characterization of adaptation of genotypes. However, several patterns of G×E interaction in Iran's regional durum yield trials were further discerned within these mega-environments. The warm environments tended to be closer to one another, suggesting that they discriminate among durum genotypes similarly, whereas cold environments tended to diverge more. The dwarf and early maturing breeding lines from ICARDA with low to medium yields and high contribution to G×E interaction were highly adapted to warm environments, whereas the tall and later maturing genotypes with low to high yields were highly adapted to the cold environments of Iran.

Using AMMI approach to delineate genotype by environment interaction and stability of barley (Hordeum vulgare L.) genotypes under northern Indian shivalik hill conditions

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Om Prakash Yadav ◽  
A. K. Razdan ◽  
Bupesh Kumar ◽  
Praveen Singh ◽  
Anjani K. Singh
Keyword(s):  
Hordeum Vulgare ◽  
Grain Yield ◽  
Principal Component ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Hordeum Vulgare L ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Principal Component Axis ◽  
Ammi Analysis

Genotype by environment interaction (GEI) of 18 barley varieties was assessed during two successive rabi crop seasons so as to identify high yielding and stable barley varieties. AMMI analysis showed that genotypes (G), environment (E) and GEI accounted for 1672.35, 78.25 and 20.51 of total variance, respectively. Partitioning of sum of squares due to GEI revealed significance of interaction principal component axis IPCA1 only On the basis of AMMI biplot analysis DWRB 137 (41.03qha–1), RD 2715 (32.54qha–1), BH 902 (37.53qha–1) and RD 2907 (33.29qha–1) exhibited grain yield superiority of 64.45, 30.42, 50.42 and 33.42 per cent, respectively over farmers’ recycled variety (24.43qha–1).

Stability Analysis of Agronomic Traits for Maize (Zea Mays L.) Genotypes Based on Ammi Model

2021 ◽  
Vol 50 (2) ◽  
pp. 343-350
Author(s):  
Meijin Ye ◽  
Zhaoyang Chen ◽  
Bingbing Liu ◽  
Haiwang Yue
Keyword(s):  
Grain Yield ◽  
Agronomic Traits ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Kernel Weight ◽  
Environment Interaction ◽  
Maize Hybrids ◽  
Genotype By Environment ◽  
Ammi Model ◽  
The Ideal

Stability and adaptability of promising maize hybrids in terms of three agronomic traits (grain yield, ear weight and 100-kernel weight) in multi-environments trials were evaluated. The analysis of AMMI model indicated that the all three agronomic traits showed highly significant differences (p < 0.01) on genotype, environment and genotype by environment interaction. Results showed that genotypes Hengyu321 (G9), Yufeng303 (G10) and Huanong138 (G3) were of higher stability on grain yield, ear weight and 100-kernel weight, respectively. Genotypes Hengyu1587 (G8) and Hengyu321 (G9) showed good performance in terms of grain yield, whereas Longping208 (G2) and Weike966 (G12) showed broad adaptability for ear weight. It was also found that the genotypes with better adaptability in terms of 100-kernel weight were Zhengdan958 (G5) and Weike966 (G12). The genotype and environment interaction model based on AMMI analysis indicated that Hengyu1587 and Hengyu321 were the ideal genotypes, due to extensive adaptability and high grain yield under both testing sites. Bangladesh J. Bot. 50(2): 343-350, 2021 (June)

scholarly journals Grain yield, stability and bacterial brown spot disease of dark red kidney dry bean (Phaseolus vulgaris L.) genotypes across six environments in South Africa

2020 ◽  
pp. 1433-1442
Author(s):  
Venâncio Salegua ◽  
Rob Melis ◽  
Deidré Fourie ◽  
Julia Sibiya ◽  
Cousin Musvosvi
Keyword(s):  
South Africa ◽  
Disease Resistance ◽  
Grain Yield ◽  
Genotype By Environment Interaction ◽  
Brown Spot ◽  
Environment Interaction ◽  
Phaseolus Vulgaris L ◽  
Dry Bean ◽  
Genotype By Environment ◽  
Bacterial Brown Spot

Dry bean (Phaseolus vulgaris L.) is grown under an extensive range of agro-climatic conditions and is an essential source of protein and income globally. This study aimed to evaluate yield performance, stability, and bacterial brown spot (BBS) disease resistance of fourteen dark red kidney genotypes across environments in South Africa namely Carolina, Clarens, Cedara, Middelburg, Potchefstroom, and Warden. Analysis of variance (ANOVA), additive main effects and multiplicative interaction (AMMI) and the genotype plus genotype by environment interaction (GGE-biplot) analysis were used to evaluate grain yield performance, stability, and BBS disease resistance. The AMMI ANOVA revealed that mean squares for grain yield and BBS severity for the environment, genotype, and genotype by environment interaction were highly significant (P<0.001). Four interaction principal components (IPCA1 - 4) for grain yield and IPCA1 for BBS severity were highly significant (P<0.001, P<0.01). Genotype G12 showed broad adaptation for both high grain yield and low BBS severity across the six environments, while genotypes G08, G06, G03, G02, G05, and G04 had specific adaption for high grain yield and low BBS severity. These genotypes recorded grain yield above the grand mean and the best check cultivar, both with 1.43 t ha-1 , and BBS severity below the grand mean (31.90%) and the best check (48.89%). The genotypes identified with either broad or specific adaptation can be released in the environments they are adapted to, or used as parents in breeding programmes aiming to improve grain yield and BBS disease resistance of dry bean for farmers in South Africa.

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