scholarly journals ADDITIVE MAIN EFFECT AND MULTIPLICATIVE INTERACTION ANALYSIS FOR GRAIN YIELD IN BREAD WHEAT

2020 ◽  
Vol 30 (3) ◽  
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Interaction Analysis ◽  
Multiplicative Interaction ◽  
Main Effect

scholarly journals Additive Main effect and Multiplicative Interaction Analysis of Grain Yield of advanced Bread Wheat (Triticum aestivum L) Genotype in Ethiopia

2019 ◽  
Vol 2 (1) ◽  
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Interaction Analysis ◽  
Triticum Aestivum L ◽  
Yield Response ◽  
Similar Response ◽  
Wheat Genotypes ◽  
Main Effect ◽  
Ammi Analysis ◽  
Similar Yield

The present study was conducted to interpret Genotype main effect and GEI obtained by AMMI analysis and group the genotype having similar response pattern over all environments. Fifteen bread wheat genotypes were evaluated by RCBD using four replications at six locations in Ethiopia. The main effect differences among genotypes, environments, and the interaction effects were highly significant (P ≤ 0.001) of the total variance of grain yield. Results of AMMI analysis of mean grain yield for the six locations showed significant differences (P<0.001) among the genotypes, the environments and GEI. The environment had the greatest effect of the environmental sum of squares (35.28%) than the genotypes (33.46%) and GEI(31.45%) effect. The AMMI analysis for the IPCA1 captured 46.1% and the IPCA2 explained 28.6% the two IPC cumulatively captured 74.7% of the sum of square the GEI of bread wheat genotypes, when the IPCA1 was plotted against IPCA2. The genotype ETBW8075, ETBW8070 and ETBW9470 were unstable as they are located far apart from the other genotypes in the biplot when plotted on the IPCA1 and IPCA2 scores. The ETBW8078, ETBW8459, Hidase and ETBW8311 were genotype located near to the origin of the biplot which implying that it was stable bread wheat genotypes across environments. There is closer association between Lemu and ETBW8065 which indicate similar response of the genotypes to the environment. The best genotype with respect to location Kulumsa was ETBW9470, ETBW8075 was the best genotype for Dhera, ETBW8070 was the best genotype for Holeta while ETBW9466 was the best genotype for Arsi Robe. Arsi Robe and Kulumsa is the most favorable environment for all genotypes with nearly similar yield response for grain yield.

scholarly journals Additive Main Effect and Multiplicative Interaction Analysis for Grain Yield of Chickpea (Cicer arietinum L.) in Iran

ISRN Agronomy ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Sayyed Hossain Sabaghpour ◽  
Farhang Razavi ◽  
Seyyedeh Fatemeh Danyali ◽  
Davood Tobe ◽  
Asghar Ebadi
Keyword(s):  
Grain Yield ◽  
Cicer Arietinum ◽  
Interaction Analysis ◽  
Principal Component ◽  
High Rate ◽  
Ge Interaction ◽  
Environment Analysis ◽  
Multiplicative Interaction ◽  
Main Effect ◽  
Final Yield

Selection of chickpea (Cicer arietinum L.) cultivars with wide adaptability across diverse farming environments is important before recommending them to achieve a high rate of cultivar adoption. Multienvironment trials including 3 years and 5 locations for 17 genotypes of autumn chickpea were carried out in Iran. Additive main effect and multiplicative interaction (AMMI) were used to understand the GE interaction pattern. Analysis of variance of grain yield showed that 68.36% of the total sum of squares was attributable to environmental effects, only 15.9% to genotypic effects and 13.55% to GE interaction effects. Biplot of the first principal component and mean grain yields for genotypes and environments revealed that high yielding genotypes were not stable cultivars regarding final yield. The AMMI2 mega-environment analysis identified four chickpea megaenvironments in Iran. The first megaenvironment contained locations, Ghachsaran and Lorestan, where genotype Arman was the winner; the second megaenvironment contained locations Gorgan, where genotype FLIP 98-126C was superior. The tertiary megaenvironment contained locations in Ilam, where genotype FLIP 98-82C was superior and the location of Kermanshah made up the other megaenvironment, with FLIP 98-201C as superior.

Additive Main Effect and Multiplicative Interaction analysis for grain yield of early maturing sorghum [Sorghum bicolor (L.) Moench] varieties in drought prone areas of Central Tigray, Northern Ethiopia

2020 ◽  
Author(s):  
Fantaye Belay ◽  
Hintsa Meresa ◽  
Shambel Syum
Keyword(s):  
Grain Yield ◽  
Analysis Of Variance ◽  
Interaction Analysis ◽  
Block Design ◽  
Northern Ethiopia ◽  
Environment Interaction ◽  
Multiplicative Interaction ◽  
Tigray Region ◽  
Early Maturing ◽  
Testing Environments

Abstract Shortage of widely adapted and high yielding variety is one of the major bottlenecks for production and productivity of sorghum in dry lowlands of Tigray region, northern Ethiopia. A field experiment was conducted during the main seasons of 2017and 2019 at four locations using randomized complete block design with three replications to evaluate the performance of ten early maturing sorghum genotypes for grain yield using AMMI (Additive Main Effects and Multiplicative Interaction) model. The combined analysis of variance revealed highly significant (P≤0.01) genotype (G), environment (E) and genotype × environment interaction (GEI). The significant genotype by environment interaction effects were further partitioned in to two significant interaction principal components by using AMMI model. The AMMI analysis of variance showed that the genotype, environment and interaction sum squares contributed 41.55 %, 28.67 % and 29.78 % to the treatment sum squares for grain yield respectively. In addition the first two IPCAs and interaction residual were significant. The first two IPCAs accounted for a total of 82.20 % of the interaction sum square. The results revealed that the observed yield variation among genotypes were due to genetic potential of genotypes and interaction rather than location differences. The highest yield was obtained from ESH-1 (3276 kg ha-1), while the lowest was from Grana-1 (2094 kg ha-1) and the average grain yield of genotypes was 2462 kg ha-1. Therefore, ESH-1 is selected as the best stable hybrid with consistent yielding performance across the testing environments in dry lowland areas of Abergelle and similar agro-ecologies in Tigray region, northern Ethiopia.

scholarly journals Genotype X Environment Interaction and Yield Stability of Bread Wheat Genotypes in central Ethiopia

2019 ◽  
Vol 7 (2) ◽  
pp. 87-94
Author(s):  
Gadisa A. Wardofa ◽  
Hussein Mohammed ◽  
Dawit Asnake ◽  
Tesfahun Alemu
Keyword(s):  
Grain Yield ◽  
Bread Wheat ◽  
Response Pattern ◽  
Yield Response ◽  
Similar Response ◽  
Environment Interaction ◽  
Wheat Genotypes ◽  
Main Effect ◽  
Ammi Analysis ◽  
Similar Yield

The present study was conducted to interpret Genotype main effect and GEI obtained by AMMI analysis and group the genotype having similar response pattern over all environments. Fifteen bread wheat genotypes were evaluated by RCBD using four replications at six locations in Ethiopia. The main effect differences among genotypes, environments, and the interaction effects were highly significant (P ≤ 0.001) for the total variance of grain yield. Results of AMMI analysis of mean grain yield for the six locations showed significant differences (P0.001) among the genotypes, environments and GEI. The environment had the greatest effect with the environmental sum of squares (35.28%) than the genotypes (33.46%) and GEI (31.45%) effect. The AMMI analysis for the IPCA1 captured 46.1% and the IPCA2 explained 28.6%. The two IPC cumulatively captured 74.7% of the sum of square the GEI of bread wheat genotypes, when the IPCA1 was plotted against IPCA2. The genotype ETBW8075, ETBW8070 and ETBW9470 were unstable as they are located far apart from the other genotypes in the biplot when plotted on the IPCA1 and IPCA2 scores. The ETBW8078, ETBW8459, Hidase and ETBW8311 were genotype located near to the origin of the biplot which implying that it was stable bread wheat genotypes across environments. There is closer association between Lemu and ETBW8065 which indicate similar response of the genotypes to the environment. The best genotype with respect to location Kulumsa was ETBW9470, ETBW8075 was the best genotype for Dhera, ETBW8070 was the best genotype for Holeta while ETBW9466 was the best genotype for Arsi Robe. Arsi Robe and Kulumsa is the most favorable environment for all genotypes with nearly similar yield response for grain yield.

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