scholarly journals Additive main effects and multiplicative interaction and yield stability index for genotype by environment analysis and wider adaptability in Barley

2018 ◽  
Vol 46 (2) ◽  
pp. 365-375 ◽  
Author(s):  
V. Kumar ◽  
A.S. Kharub ◽  
G.P. Singh
Keyword(s):  
Stability Index ◽  
Yield Stability ◽  
Environment Analysis ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Main Effects

Rectification of modified AMMI stability value (MASV)

2020 ◽  
Vol 79 (04) ◽  
Author(s):  
B. C. Ajay ◽  
J. Aravind ◽  
R. Abdul Fiyaz ◽  
Narendra Kumar ◽  
Chuni Lal ◽  
...  
Keyword(s):  
Principal Components ◽  
Stability Index ◽  
Correct Version ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Ammi Analysis ◽  
Correct Formula ◽  
Ammi Model ◽  
Main Effects ◽  
Original Formula

Additive main effects and multiplicative interaction (AMMI) analysis is widely used for analyzing data of multi-environment trials (METs) to model the genotype-by-environment interactions (GEIs). However, AMMI model do not rank genotypes which is required for aiding selection. In order to overcome these lacunae a stability index titled AMMI stability value (ASV) was proposed by Purchase et al. (1997) using first two interaction principal components (IPCA) from the results of AMMI analysis. Later, Zali et al. (2012) modified it and proposed Modified ASV (MASV) which used all significant IPCAs. However, Zali et al. (2012) read the original formula of ASV incorrectly while proposing MASV thus rendering it erroneous. Use of this erroneous MASV impacted genotype ranking significantly. Corrected version of MASV, i.e. MASV2 showed significant correlation with other stability models. Hence, we propose MASV2 as a correct formula for modified AMMI stability Value (MASV) and this correct version of MASV may be used instead of earlier formula proposed by Zali et al. (2012).

scholarly journals Genotype by environment interaction for physiological traits in sugar beet (Beta vulgaris L.) parents and hybrids using additive main effects and multiplicative interaction model

2021 ◽  
Author(s):  
Zahra Abbasi ◽  
Jan Bocianowski
Keyword(s):  
Sugar Beet ◽  
Beta Vulgaris ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Physiological Traits ◽  
Environment Interaction ◽  
Extraction Coefficient ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Main Effects

AbstractThe objective of this study was to assess genotype by environment interaction for 21 physiological traits in sugar beet (Beta vulgaris L.) parents and hybrids grown in Rodasht Agricultural Research Station in Iran by the additive main effects and multiplicative interaction model. The study comprised of 51 sugar beet genotypes [10 multigerm pollen parents, four monogerm seed parents and 36 F1 hybrids], evaluated at four environments in a randomized complete block design, with three replicates. The additive main effects and multiplicative interaction analyses revealed significant environment main effects with respect to all observed traits, except extraction coefficient of sugar. The additive main effects and multiplicative interaction stability values ranged from 0.009 (G17 for leaf Ca2+) to 9.698 (G09 for extraction coefficient of sugar). The parental forms 2 7233-P.29 (G38) and C CMS (G49) as well as hybrids 2(6)*C (G27) and 5*C (G33) are recommended for further inclusion in the breeding programs because of their stability and good average values of observed traits.

scholarly journals Genotype by environment interaction for seeds yield in pea (Pisum sativum L.) using additive main effects and multiplicative interaction model

Euphytica ◽  
2019 ◽  
Vol 215 (11) ◽  
Author(s):  
Jan Bocianowski ◽  
Jerzy Księżak ◽  
Kamila Nowosad
Keyword(s):  
Pisum Sativum ◽  
Block Design ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Randomized Complete Block Design ◽  
Main Effects

Abstract The objective of this study was to evaluate the genotype by environment interaction using the additive main effects and multiplicative interaction model for seeds yield of pea cultivars grown in Poland. Twelve pea (Pisum sativum L.) cultivars: Bohun, Boruta, Cysterski, Ezop, Kavalir, Lasso, Medal, Santana, Tarchalska, Terno, Wenus and Zekon were evaluated in 20 environments (ten locations in 2 years). The experiment was laid out as randomized complete block design with three replicates. Seeds yield ranged from 26.10 dt ha−1 (for Wenus in Radostowo 2011) to 79.73 dt ha−1 (for Lasso in Słupia 2010), with an average of 50.70 dt ha−1. AMMI analyses revealed significant genotype and environmental effects as well as genotype-by-environment interaction with respect to seeds yield. In the analysis of variance, 89.19% of the total seeds yield variation was explained by environment, 1.65% by differences between genotypes, and 8.33% by GE interaction. The cultivar Terno is the highest stability. The cultivar Tarchalska is recommended for further inclusion in the breeding program because its stability and the highest averages of seeds yield.

scholarly journals Genotype by environment interaction and stability analysis for rice genotypes under Boro condition

Genetika ◽  
2014 ◽  
Vol 46 (2) ◽  
pp. 521-528 ◽  
Author(s):  
Lotan Bose ◽  
Nitiprasad Jambhulkar ◽  
Kanailal Pande
Keyword(s):  
Interaction Analysis ◽  
Block Design ◽  
Principal Component ◽  
Stability Index ◽  
Yield Stability ◽  
Environment Interaction ◽  
Multiplicative Interaction ◽  
Genotype Effect ◽  
Rice Genotypes ◽  
Stability Statistics

Genotype (G)?Environment (E) interaction of nine rice genotypes possessing cold tolerance at seedling stage tested over four environments was analyzed to identify stable high yielding genotypes suitable for boro environments. The genotypes were grown in a randomized complete block design with three replications. The genotype ? environment (G?E) interaction was studied using different stability statistics viz. Additive Main effects and Multiplicative Interaction (AMMI), AMMI stability value (ASV), rank-sum (RS) and yield stability index (YSI). Combined analysis of variance shows that genotype, environment and G?E interaction are highly significant. This indicates possibility of selection of stable genotypes across the environments. The results of AMMI (additive main effect and multiplicative interaction) analysis indicated that the first two principal components (PC1-PC2) were highly significant (P<0.05). The partitioning of TSS (total sum of squares) exhibited that the genotype effect was a predominant source of variation followed by G?E interaction and environment. The genotype effect was nine times higher than that of the G?E interaction, suggesting the possible existence of different environment groups. The first two interaction principal component axes (IPCA) cumulatively explained 92 % of the total interaction effects. The study revealed that genotypes GEN6 and GEN4 were found to be stable based on all stability statistics. Grain yield (GY) is positively and significantly correlated with rank-sum (RS) and yield stability index (YSI). The above mentioned stability statistics could be useful for identification of stable high yielding genotypes and facilitates visual comparisons of high yielding genotype across the multi-environments.

scholarly journals Evaluation of Yield Stability of Bread wheat (Triticum aestivum L.) Genotypes using Additive Main Effects and Multiplicative Interaction (AMMI)

2018 ◽  
Vol 10 (25) ◽  
pp. 73-80
Author(s):  
Saeed Omrani ◽  
Amir Mohammad Naji ◽  
Mohsen Esmaeil Zadeh Moghadam ◽  
◽  
◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Bread Wheat ◽  
Triticum Aestivum L ◽  
Yield Stability ◽  
Multiplicative Interaction ◽  
Main Effects

Analyzing genotype by environment interaction in potato using yield-stability index

2002 ◽  
Vol 79 (3) ◽  
pp. 211-218 ◽  
Author(s):  
José M. Cotes ◽  
Carlos E. Ñustez ◽  
Ricardo Martinez ◽  
Nelson Estrada
Keyword(s):  
Stability Index ◽  
Genotype By Environment Interaction ◽  
Yield Stability ◽  
Environment Interaction ◽  
Genotype By Environment

scholarly journals Genotype-by-environment interaction for seed glucosinolate content in winter oilseed rape (Brassica napus L.) using an additive main effects and multiplicative interaction model

2018 ◽  
Vol 55 (1) ◽  
pp. 85-96 ◽  
Author(s):  
Jan Bocianowski ◽  
Kamila Nowosad ◽  
Alina Liersch ◽  
Wiesława Popławska ◽  
Agnieszka Łącka
Keyword(s):  
Block Design ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Glucosinolate Content ◽  
Environment Interaction ◽  
Brassica Napus L ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Winter Rapeseed ◽  
Main Effects

Summary The objective of this study was to assess genotype-by-environment interaction for seed glucosinolate content in winter rapeseed cultivars grown in western Poland using the additive main effects and multiplicative interaction model. The study concerned 25 winter rapeseed genotypes (15 F1 CMS ogura hybrids, parental lines and two European cultivars: open pollinated Californium and F1 hybrid Hercules), evaluated at five locations in a randomized complete block design with four replicates. The seed glucosinolate content of the tested genotypes ranged from 5.53 to 16.80 μmol∙g-1 of seeds, with an average of 10.26 μmol∙g-1. In the AMMI analyses, 48.67% of the seed glucosinolate content variation was explained by environment, 13.07% by differences between genotypes, and 17.56% by genotype-by-environment interaction. The hybrid PN66×PN07 is recommended for further inclusion in the breeding program due to its low average seed glucosinolate content; the restorer line PN18, CMS ogura line PN66 and hybrids PN66×PN18 and PN66×PN21 are recommended because of their stability and low seed glucosinolate content.

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