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.

scholarly journals THE USE OF AMMI MODEL FOR INTERPRETING GENOTYPE × ENVIRONMENT INTERACTION IN DURUM WHEAT

2017 ◽  
Vol 54 (5) ◽  
pp. 670-683 ◽  
Author(s):  
REZA MOHAMMADI ◽  
MOHAMMAD ARMION ◽  
ESMAEIL ZADHASAN ◽  
MALEK MASOUD AHMADI ◽  
AHMED AMRI
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Air Temperature ◽  
Heading Date ◽  
Principal Component ◽  
High Yield ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Breeding Lines ◽  
Ammi Model

SUMMARYDurum wheat (Triticum durum) is one of the most important cereal crops in the Mediterranean region; however, its cultivation suffers from low yield due to environmental constrains. The main objectives of this study were to (i) assess genotype × environment (GE) interaction for grain yield in rainfed durum wheat and to (ii) analyse the relationships of GE interaction with genotypic/meteorological variables by the additive main effects and multiplicative interaction (AMMI) model. Grain yield and some related traits were evaluated in 25 durum wheat genotypes (landrace, breeding line, old and new varieties) in 12 rainfed environments differing in winter air temperature. The AMMI analysis of variance indicated that the environment had highest contribution (84.3% of total variation) to the variation in grain yield. The first interaction principal component axis (IPCA1) explained 77.5% of GE interaction sum of squares (SS), and its effect was 5.5 times greater than the genotype effect, indicating that the IPCA1 contributed remarkably to the total GE interaction. Large GE interaction for grain yield was detected, indicating specific adaptation of genotypes. While the postdictive success method indicated AMMI-4 as the best model, the predictive success one suggested AMMI-1. The AMMI biplot analysis confirmed a rank change interaction among the locations, indicating the presence of strong and unpredictable rank-change location-by-year interactions for locations. In contrast to landraces and old varieties, the breeding lines with high yield performance had high phenotypic plasticity under varying environmental conditions. Results indicated that the GE interaction was associated with the interaction of heading date, plant height, rainfall, air temperature and freezing days.

scholarly journals Model selection in additive main effect and multiplicative interaction model in durum wheat

Genetika ◽  
2012 ◽  
Vol 44 (2) ◽  
pp. 325-339 ◽  
Author(s):  
Naser Sabaghnia ◽  
Rahmatollah Karimizadeh ◽  
Mohtasham Mohammadi
Keyword(s):  
Durum Wheat ◽  
Interaction Model ◽  
Principal Component ◽  
Wheat Genotype ◽  
Ge Interaction ◽  
Stability Parameters ◽  
Data Set ◽  
Group Iii ◽  
Main Effect ◽  
Ammi Model

The study included data set of 20 durum wheat genotype across 15 rain-fed environments. A combined analysis of variance showed that the genotypes differed significantly for seed yield and GE (year ? location) interaction. Cross validations procedure and four various F-tests including FGollob, FRatio, FGH1 and FGH2 are used for testing the GE interaction principal component analysis (IPCA) axes and indicated that two, four, six or seven axes could be significant. According to EV1, D1, AMGE1 and SIPC1 parameters, genotypes G3, G7 and G17 were the most stable genotypes while based on EV4, D4, SIPC4 and AMGE4 parameters, genotype G13 was the most stable genotype. The hierarchical clustering showed that the twenty one studied the AMMI stability parameters and mean yield could be divided into four distinct groups. Group III contains mean yield, SIPC4, SIPC6 and SIPC8 which were computed from four, six or eight IPCAs. In conclusion, G13 (DON-MD 81- 36) was found to be the most stable genotype as well as high mean yield performance (2592.45 kg ha-1) and so is recommended for commercial release in semi-arid areas of Iran. Also, the SIPC-based stability parameters of the AMMI model was found to be useful in detecting the yield stability of the genotypes studied.

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.

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 ANALISIS STABILITAS HASIL GENOTIPE JAGUNG MENGGUNAKAN METODE FIXED AMMI

2019 ◽  
Vol 8 (1) ◽  
pp. 9
Author(s):  
MODANA LOLITA ◽  
I KOMANG GDE SUKARSA ◽  
MADE SUSILAWATI
Keyword(s):  
Principal Component Analysis ◽  
Analysis Of Variance ◽  
Principal Component ◽  
Component Analysis ◽  
Yield Stability ◽  
Genotype Data ◽  
Multiplicative Interaction ◽  
Model Based ◽  
Main Effect ◽  
Total Diversity

Additive Main Effect and Multiplicative Interaction (AMMI) is a method that is used in research to study interaction between genotype and location. The aim of this research is to apply fixed AMMI in examining the production of corn genotype data and to explore yield stability of its based on biplot picture and AMMI Stability Value (ASV). This research uses six corn genotypes, eight trial locations, and three repetitions. The Interaction Principal Component Analysis (IPCA) that are significant to entered in the model based on analysis of variance fixed AMMI are IPCA1, IPCA2, and IPCA3 with total diversity interaction as much as 92,16%. The biplot picture and ASV should the stable genotype in all location are genotype KUI Carotenoid Syn FS. 17-3-2-B-B  T01 and genotype CML 305-B-B  T01. In addition, corns that are able to adapt only in certain location is: genotype KUI Carotenoid Syn FS. 5-1-5-B-B  T01, genotype KUI Carotenoid Syn FS. 25-3-2-B-B  T01, genotype KUI Carotenoid Syn FS. 17-3-1-B  T01, and genotype CML 130-B-B  T01.

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.

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