scholarly journals STATISTICAL ANALYSIS OF GENOTYPE-BY-ENVIRONMENT INTERACTION USING THE AMMI MODEL AND STABILITY ESTIMATES

Author(s):  
Bahman Shafii ◽  
William J. Price
2021 ◽  
Vol 50 (2) ◽  
pp. 343-350
Author(s):  
Meijin Ye ◽  
Zhaoyang Chen ◽  
Bingbing Liu ◽  
Haiwang Yue

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)


2016 ◽  
Vol 67 (7) ◽  
pp. 792
Author(s):  
M. R. Dehghani ◽  
M. M. Majidi ◽  
A. Mirlohi ◽  
G. Saeidi

Development of forage grass genotypes which maintain a high level of performance over a wide range of environments is a goal of most breeding programs. In this study the additive main effects and multiplicative interactions (AMMI) model analysis was used to understand the complexity of genotype by environment interaction and to evaluate the adaptability and yield stability of some tall fescue genotypes and their selected polycross progenies. Replicated forage yield data of 72 genotypes (24 parental, 24 early flowering and 24 late flowering progenies) from six main cropping seasons (2008–14) at two locations and under two levels of irrigation were used for this purpose. The AMMI-1 analysis results accounted for 47.6% of the genotype by environment interaction. Interaction patterns revealed by AMMI-1 biplots indicated that most of the tall fescue genotypes were narrowly adapted and among all evaluated genotypes, only four genotypes (G22, G50, G62 and G65) with yield performance above the average were considered broadly adapted. The AMMI-1 mega-environment analysis indicated that all the environments in Lavark were grouped in one mega-environment, except for E1 and E2. For this mega-environment the winning genotypes were the genotypes G9, G48 and G72. The environments in Isfahan location, except for E13, were grouped in another mega-environment. The genotypes G23, G8 and G15 were the winners in this mega-environment.


2018 ◽  
Vol 6 (3) ◽  
pp. 75-85 ◽  
Author(s):  
Girma Fana ◽  
Diriba Tadese ◽  
Hiwot Sebsibe ◽  
Ramesh P.S. Verma

Food barley released varieties were tested in 2012 for performance across major environments in Ethiopia consisting of 12 varieties Diribe, Tilla, Abbay, Biftu, Defo, Dinsho, Mulu, Setegn, Misiratch, Basso, Mezezo and local checks over six locations Gergera, Estayish, Shambu, Arjo, Robe and Sinana. The objective was to determine genotype by environment interaction using AMMI and GGE biplot, compare the two models for identifying the adaptable and stable genotypes. Sinana was identified as the high yielding environment and MULU the high yielding variety with mean yields of 3466.31 and 3137.67 kg/ha, respectively. The mean yield at Estayish was lower (1535 kg/ha) than other environments whereas lower yield (2212.16 kg/ha) was also obtained from the variety DINSHO. The AMMI analysis of Variance indicated that 47% of the total sum of squares is attributed to the Environmental effect, 8% to the genotypic effect and 25% to the interaction. The first three principal components of the GEI explained 81% of the variation. Genotypes Basso, Biftu and Setegn were the most stable whereas Diribe was unstable. Variety Mulu was identified as the winner genotype by AMMI model whereas Diribe was identified as the winner by the GGE model. GGE model better explains the which-won-where scenario and hence preferred to AMMI model. The discriminating and representative view of the GGE biplot depicted that Sinana and Shambu are discriminating environments whereas Sinana, Estayish and Gergera are representative environments. Therefore, Sinana is the ideal environment for discriminating genotypes and representing other environments for selecting ideal genotypes.


Genetika ◽  
2009 ◽  
Vol 41 (2) ◽  
pp. 169-177 ◽  
Author(s):  
Miodrag Dimitrijevic ◽  
Sofija Petrovic ◽  
Novica Mladenov ◽  
Milivoj Belic ◽  
Nikola Hristov ◽  
...  

Phenotypic variation of nine wheat varieties under different growing conditions was followed. Trials were conducted on solonetz, humoglay and black soil. The yield, as well as, the plant height, spike length and harvest index were studied. The effect of different environments on varietals phenotypic variability, with the emphasis on genotype by environment interaction, was analyzed using AMMI model.


Sign in / Sign up

Export Citation Format

Share Document