Stability Analysis of Greengram [Vigna radiata (L.) Wilczek] Genotypes for Seed Yield in Telangana using Regression, AMMI, GGE and WAAS Biplot Models

Abstract

Background: To increase area and production of greengram, breeders must develop high yielding, stable and adaptable varieties. This study aims to identify such superior greengram genotypes that perform consistently well across different locations. Methods: The experiment was carried out during Kharif, 2023 in six locations at different Agricultural Research Stations of Telangana state. A total of 15 genotypes were evaluated in RBD with three replications. The data on seed yield was subjected to statistical analysis. The G×E interaction was studied as per Eberhart and Russel model, AMMI, GGE biplot and WAAS model analysis. Result: Regression analysis revealed that genotypes MGG-385 and MGG-573 considered as stable. AMMI analysis of variance indicated that genotypes contributed 13.1% followed by environment (55.4%) and G×E interaction (20.48%). With further examination of GGE using AMMI analysis, two significant principal components were separated explaining 69.7% of variance interaction (PCI-42% and PC2-27.7%). The results of AMMI 1 and 2 biplot analysis, the genotypes MGG-385 and MGG-295 were considered as stable with high mean seed yield and recorded nearly zero IPCA1 score. The environments of Madhira and Tandur had recorded the lowest IPCA1 scores had less interaction effects. AMMI stability value and stability indexes were indicated MGG-385 was more stable. Y×WAAS graph revealed the genotypes VBN-4, MGG-570, MGG-571 were unstable had high seed yield, while the environments Palem, Tornala and Warangal provided high seed yield and presented good discrimination ability as had recorded high WAAS values. The genotypes MGG-573, MGG-556, MGG-385 and MGG-564 were broadly adopted. Based on all the stability models, the genotype MGG-385 was considered as stable with high mean seed yield across locations.