Additive Main Effect and Multiplicative Interaction Analysis of National Turfgrass Performance Trials: I. Interpretation of Genotype × Environment Interaction

Crop Science ◽  
2002 ◽  
Vol 42 (2) ◽  
pp. 489-496 ◽  
Author(s):  
J. S. Ebdon ◽  
H. G. Gauch
Keyword(s):  
Interaction Analysis ◽  
Environment Interaction ◽  
Multiplicative Interaction ◽  
Genotype Environment Interaction ◽  
Main Effect

scholarly journals Evaluation of maize hybrids and environmental stratification by the methods AMMI and GGE biplot

2010 ◽  
Vol 10 (3) ◽  
pp. 247-253 ◽  
Author(s):  
Rogério Lunezzo de Oliveira ◽  
Renzo Garcia Von Pinho ◽  
Márcio Balestre ◽  
Denys Vitor Ferreira
Keyword(s):  
Interaction Analysis ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Multiplicative Interaction ◽  
Maize Hybrids ◽  
Growing Seasons ◽  
Single Cross ◽  
Predictive Correlation ◽  
Environmental Stratification ◽  
Main Effects

The purpose of this study was to evaluate yield stability, adaptability and environmental stratification by the methods AMMI (Additive Main Effects and Multiplicative Interaction Analysis) and GGE (Genotype and Genotypes by Environment Interaction) biplot and to compare the efficiency of these methods. Data from the evaluation of 20 experimental single-cross and three commercial hybrids and 11 locations, in two growing seasons, 2005/2006 and 2006/2007 were used. Analyses of variance, adaptability, stability and environmental stratification were performed. A better combination of adaptability and stability was observed in the hybrids 10 and 16, according to the graphics of AMMI and GGE biplot methods, respectively. The number of locations could be reduced by 28% based on stratification. The predictive correlation of the AMMI and GGE methods was 0.88 and 0.86, respectively. The results showed that it is possible to reduce the number of evaluation sites; AMMI tended to be more accurate than GGE analysis.

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

scholarly journals Grouping genotypes and test environments by some cluster methods regarding genotype × environment interaction in multi-environment trials

Genetika ◽  
2012 ◽  
Vol 44 (3) ◽  
pp. 457-473 ◽  
Author(s):  
Naser Sabaghnia ◽  
Rahmatollah Karimizadeh ◽  
Mohtasham Mohammadi
Keyword(s):  
Lens Culinaris ◽  
Developed Countries ◽  
Environment Interaction ◽  
Stopping Criterion ◽  
Ge Interaction ◽  
Regression Methods ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Main Effect ◽  
Cluster Methods

Lentil (Lens culinaris Medik.) is an important source of protein and carbohydrate food for people of developing countries and is popular in some developed countries where they are perceived as a healthy component of the diet. Ten lentil genotypes were tested for grain yield in five different environmental conditions, over two consecutive years to classify thes genotypes for yield stability. Seed yield of lentil genotypes ranged from 989.3 to 1.367 kg ha-1 and the linear regression coefficient ranged from 0.75 to 1.18. The combined analysis of variance showed that the effect of environment (E) and genotype by environment (GE) interaction were highly significant while the main effect of genotype (G) was significant at 0.05 probability level. Four different cluster procedures were used for grouping genotypes and environments. According to dendograms of regression methods for lentil genotypes there were two different genotypic groups based on G plus GE or GE sources. Also, the dendograms of ANOVA methods indicated 5 groups based on G and GE sources and 4 groups based on GE sources. According to dendograms of regression methods for environments there were 5 different groups based on G plus GE sources while the dendograms of ANOVA methods indicated 9 groups based on G and GE sources and 3 groups based on GE sources. The mentioned groups were determined via F-test as an empirical stopping criterion for clustering. The most responsive genotypes with high mean yield genotypes are G2 (1145.3 kg ha-1), G8 (1200.2 kg ha-1) and G9 (1267.9 kg ha-1) and could be recommended as the most favorable genotypes for farmers.

scholarly journals Genotype × Environment Interaction for Resistance to Spider Mites in Fragaria

1999 ◽  
Vol 124 (4) ◽  
pp. 353-357 ◽  
Author(s):  
José López Medina ◽  
Patrick P. Moore ◽  
Carl H. Shanks ◽  
Fernando Flores Gil ◽  
Craig K. Chandler
Keyword(s):  
Spider Mite ◽  
The United States ◽  
Spider Mites ◽  
Environment Interaction ◽  
Interaction Patterns ◽  
First Order ◽  
Genotype Environment Interaction ◽  
Main Effect ◽  
Ammi Analysis ◽  
Main Effects

Genotype × environment interaction for resistance to the twospotted spider mite (Tetranychus urticae Koch) of eleven clones of Fragaria L. sp. (strawberries) grown in six environments throughout the United States was examined using two multivariate analysis techniques, principal coordinate analysis (PCA) and additive main effect and multiplicative interaction (AMMI). Both techniques provided useful and interesting ways of investigating genotype × environment interaction. PCA analysis indicated that clones X-11 and E-15 were stable across both low and high environments for the number of spider mites per leaflet. The initial AMMI analysis showed that the main effects of genotype, environment, and their first-order interaction were highly significant, with genotype × environment interaction due mainly to cultivar `Totem' and environment FL94. A second AMMI analysis, which excluded `Totem' and FL94, showed that the main effects of the remaining genotypes, environments, and genotype × environment interaction were also highly significant. AMMI biplot analysis revealed that FL93 and GH93 were unstable environments, but with opposite interaction patterns; and GCL-8 and WSU2198 were unstable genotypes with similar interactions that were opposite those of WSU 2202.

Analysis of Indian post-rainy sorghum multi-location trial data reveals complexity of genotype × environment interaction

2016 ◽  
Vol 155 (1) ◽  
pp. 44-59 ◽  
Author(s):  
S. RAKSHIT ◽  
K. N. GANAPATHY ◽  
S. S. GOMASHE ◽  
A. DHANDAPANI ◽  
M. SWAPNA ◽  
...  
Keyword(s):  
Trial Data ◽  
Conservation Practices ◽  
Environment Interaction ◽  
Improvement Project ◽  
Genotype Environment Interaction ◽  
Main Effect ◽  
Highly Correlated ◽  
Main Effects ◽  
Major Emphasis ◽  
New Cultivars

SUMMARYSorghum [Sorghum bicolor (L.) Moench] grown in India is of two adaptive types: rainy and post-rainy. The post-rainy sorghum is predominantly consumed by humans. While releasing new cultivars through multi-location testing, major emphasis is given to the superiority of new cultivars over existing cultivars, with very little emphasis on the genotype × environment interaction (GEI). To understand the complexity of GEI in post-rainy sorghum testing location trials, the multi-location evaluation data of two post-rainy seasons (2009/10 and 2010/11) under the All India Coordinated Sorghum Improvement Project were analysed. In both years, location explained the highest proportion of total sum of squares followed by the GEI effect and main effect of genotype. Additive main effects and multiplicative interaction (AMMI), stability values (ASV) and genotype + genotype × environment interaction (GGE) instability values recorded high correlation resulting in identification of the best performing cultivars. However, the rank correlations were lower, though still significant. A mixture of crossover and non-crossover GEI was a common occurrence in both years. ‘Which-won-where’ analysis suggested the existence of four possible mega-environments (ME) among post-rainy testing locations, with a few non-informative locations within ME. Mega-environments are characterized by soil type, rainfall pattern and moisture conservation practices. The present study indicated the possibility of reducing the number of test locations by eliminating non-representative highly correlated locations and suggested the need to breed for location-specific genotypes rather than genotypes with wider adaptability.

Sign in / Sign up

Export Citation Format

Share Document