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Background: The research focused on investigating the impact of genotype-environment interaction on the yield stability and performance of eight chickpea genotypes across three different locations (Bhatapara, Kawardha and Raipur). Methods: The study employed a randomized block design with two replications in each environment in Rabi season during 2021-22. Analysis of variance (ANOVA) revealed significant variations between environments and genotype-environment interaction (G x E) based on AMMI and GGE biplot. Result: To visualize the genotype-environment relationship, a two-dimensional GGE biplot was created using the first two principal components, which accounted for 87.8% and 11.5% of the interaction's variation. The GGE biplot indicated that genotype g4 (ICCX 161100-B-B-B-B) in environment e2 (Kawardha) and g8 (JG-24) in environment e1 (Bhatapara) exhibited high yield. Genotype g3 (ICCV 201112) in environment e3 (Raipur) also showed high yield, while genotype g5 (JG 2020-10) demonstrated stability across all three environments. Furthermore, the AMMI analysis identified genotype g2 (ICCV 201103) as a superior performer in terms of yield stability across environments. By employing the GGE biplot and AMMI analysis, the study categorized the genotypes into three groups, facilitating simplified visual evaluations. The GGE biplot highlighted that genotype g8 (JG-24) exhibited better seed index in environment e3 (Raipur), while genotype g1 (ICCV 201210) performed well in environment e1 (Bhatapara). Genotype g2 (ICCV 201103) demonstrated a good seed index in all three environments. The AMMI analysis indicated that genotype g3 (ICCV 201112) had a slightly lower seed index but maintained stability across all environments. Overall, the findings of this investigation, as represented by the GGE and AMMI biplots, visually illustrated the relationship between genotypes and environments. The identified genotypes hold potential for improving yield production and further research and breeding efforts can be based on these findings. [ABSTRACT FROM AUTHOR]

Background: Pigeonpea is second most important pulse crop of India after chickpea and it is necessary to identify its high yielding and stable genotypes to feed the increasing population of country. Methods: The present study was laid down in a randomized block design with three replications during kharif season of 2016-2019 at GBPUAT, Pantnagar using twenty genotypes of pigeonpea with an aim to identify the high yielding and stable genotypes. The hierarchical cluster analysis (HCA) based on mean seed yield and Average of Sum of Ranks (ASR) of all measures (Parametric and nonparametric) was used in present study. Result: The pooled ANOVA revealed the presence of significant differences among genotypes, environments and G x E interaction effects. The results of hierarchical cluster analysis indicated the genotypes PA 622 (yield=1774.85 kg/ha, ASR=2.00), PA 620 (yield= 1579.92 kg/ha, ASR=2.18), UPAS 120 (yield=1268.57 kg/ha, ASR=2.87), PA 626 (yield=1571.40 kg/ha, ASR=5.56), PUSA 992 (yield= 1331.17 kg/ha, ASR=5.68) and PA 628 (yield= 1271.50 kg/ha, ASR=7.06) as most stable and high yielding and hence these genotypes can be recommended for pigeonpea improvement programmes. [ABSTRACT FROM AUTHOR]

Background: Chickpea is an important nutrient rich food legume cultivated mainly as rainfed crop in arid and semiarid regions of India. Due to changed climatic conditions incidence of frequent drought stress events are causing significant yield losses. Methods: In order to identify superior and locally adaptable genotypes under rainfed conditions multi-environment chickpea evaluation trial was conducted in five environments with 50 genotypes during Rabi, 2021-2022 stability analysis for grain yield was performed by deploying the AMMI (Additive Main Effects and Multiplicative Interaction) model and GGE (Genotype and Genotype by Environment) biplot method with an aim to identify the high yielding stable chickpea genotypes. Result: The AMMI analysis of variance for grain yield (kg ha-1) of 50 chickpea genotypes revealed significant genotype, environment and G x E interaction indicating the presence of variability among the genotypes and environments. The mean grain yield of 50 genotypes over environments ranged from 1296 kg/ha (G39) to 2222 kg/ha (G8). The genotype G24 exhibited high grain yield than mean yield with specific adaptability for the environment E2 (Palem). The results indicated that, environment E5 (Warangal) was identified as the best suited for potential expression of grain yield. Results of stability analysis revealed that genotype G17 exhibited high grain yield along with high stability across the locations with desirable mean performance. [ABSTRACT FROM AUTHOR]

In agricultural experimentation, a large number of genotypes are normally evaluated over a wide range of environments for delineating stable genotypes. In this study, fifteen dwarf field pea genotypes were evaluated at six diverse locations under three Agro-climatic zones viz., Central zone, North West peninsular zone and North east peninsular zone for the purpose of identifying stable genotypes through deploying the additive main effects and multiplicative interaction (AMMI) model. The uniqueness of AMMI biplot is to provide comprehensive solution regarding multi-environment evaluation of genotype. In addition to identification of stable genotypes, this approach facilitates effective selection of test environment and allows optimum resource allocation in future testing programme. In the present study from the AMMI biplot and the ASV AMMI stability value (ASV), it was detected that genotypes 6 (Pant-P-345), 12 (KPF-14-50) and 4 (KPMR-940) were the stable genotypes amid the tested genotypes. These identified genotypes with wide adaptation would be valuable treasure troves for the breeder for utilizing as a parent in field pea breeding programme of India. [ABSTRACT FROM AUTHOR]

Multi-environmental trials have generally significant genotype main effects and genotype x environment interaction (GEI) effect and, therefore different univariate and multivariate stability methods have been used to study the GEI. Among the multivariate methods, the additive main effects and multiplicative interaction (AMMI) analysis is widely used for GEI investigation. This method has been effective because it captures a large portion of the GEI sum of squares; it clearly separates main and interaction effects and often provides meaningful interpretation of data to support a breeding program such as genotypic stability. Based on the AMMI model, a stability index has been used to rank the genotypes. This index is the weightage of stability and yield component and higher the index value better is the genotypes. The index of 40 promising chickpea genotypes were calculated with two different weight of yield (50% and 75%) and stability component (50% and 25%). These genotypes were evaluated at seven locations viz. Hiriyur, Nandyal, Coimbtore, Dharwad, Lam, Bijapur and Gulbarga representing the south zone of All India Coordinated Research Project on Chickpea program during 2015-16. Ranking of genotypes are done based on two different weight of stability and yield component. [ABSTRACT FROM AUTHOR]

Stability analysis helps to identify superior genotypes suited to specific agro-ecological zones. The objective of the study was to determine stability and adaptability of fifteen soybean genotypes for seed yield, protein and oil contents by additive main effects and multiplicative interaction (AMMI) analysis. The research was conducted at Eldoret, Lanet, Nakuru West and Njoro. AMMI analysis identified genotypes DPSB 8 and SBH 7/1/1 as most stable for seed yield with means above the trial mean of 1267 kg ha-1. Genotypes SBH 4/4/4, SBH 7/1/1, SBH 1/12/19 and Gazelle were stable for seed yield and oil content. Genotype DPSB 19 had high and stable protein content (402.8 g kg-1) with low seed yield. Genotypes SBH 4/4/4 and EAI 3600 were stable for pods plant-1 and 100-seed weight. Either GGE or AMMI analysis maybe employed to identify stable soybean genotypes for production across environments and adaptable genotypes for specific environments. [ABSTRACT FROM AUTHOR]

Ajwain is the second most important seed spice crop in Andhra Pradesh, India. It is grown as rainfed crop in vertisols. The crop is sown usually during July to September as a rainfed crop. There is a need for identifying suitable high yielding genotypes adaptable to rainfed vertisols. In view of this, fourteen genotypes were evaluated for their performance in rainfed vertisols for four years. The uniqueness of the rainfed environment which varies with year to year was taken as advantage and Additive Main Effect and Multiplicative Interaction (AMMI) analysis was used to understand the complex genotype x environment (GE) interactions. Further AMMI Stability Values and Genotype Selection Index (GSI) were worked out for the genotypes. Stability when assessed should be reliable. Genotype Selection Index (GSI) due to its nature of combining the estimated the stability measure and yield data, gave more useful information for selection and recommendation. The most desirable genotypes for selection of both stability and high grain yield were genotype 3 (LTa-26) followed by genotype 2 (LTa-25). [ABSTRACT FROM AUTHOR]

Five elite chickpea genotypes along with three check varieties were grown in eight environments during rabi 2011-12 season at Pulses Improvement Project, Mahatma Phule Agricultural University, Rahuri to check their stability. The genotypes were grown in randomized block design with three replications. The AMMI analysis of variance for seed yield clearly indicates that the mean sum of square for genotypes is significant, suggesting broad range of diversity among genotypes. The environmental variances are highly significant for all the characters. G x E mean sum of square was significant for seed yield which indicates that the performance of genotypes was differential over the environments. The proportion of sum of square for G x E for seed yield kg/plot was 26.04 %. Three genotypes viz., Phule G-07102, Phule G-09103 and Digvijay exhibited stable performance over all environment (non-interacting)for seed yield kg/plot. The environments E3 (sowing date 1/11/ 2011), E4 (sowing date 16/11/2011) and E5 (sowing date 1/12/2011) had good conditions for most of the genotypes while at the same time, the PCA score for these three environments were nearly zero indicating all genotypes produced fairly stable seed yield. [ABSTRACT FROM AUTHOR]