The current experiments were carried out in alpha lattice design at the Seed Breeding Farm, Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, Madhya Pradesh state, India, during 2019−20 and 2020−21 crop seasons, using 236 RILs population. The aim of current experiment is to assessment of genetic diversity and identification of promising recombinant inbred lines for irrigated and restricted irrigated conditions through PCA and cluster analysis. The drought selection indices viz. Relative drought index, yield stability index, drought resistance index, mean productivity, stress tolerance index and yield index were performed from two year grain yield pooled data. The principal component analysis and cluster analysis were performed through drought selection indices. Drought selection indices viz. relative drought index, yield stability index, yield index were confirm strong positively associated with grain yield under restricted irrigated conditions while mean productivity, stress tolerance index and yield index were strong positively associated with grain yield under irrigated conditions. Moreover, high cluster mean, for grain yield under restricted irrigated condition with associated selection indices was confirmed by 77 inbred lines from cluster I. similarly 128 superior inbred lines were found for irrigated condition. The highest inter cluster distance was observed between cluster I and cluster III therefore the inbred line occupy by cluster I and cluster III were considered as most diverse lines and could be used in farther breeding program to achieve more recombination for drought tolerance.

The purpose of this study was to ascertain the genotype by environment interaction (GEI) of heat tolerance wheat genotypes. The objective was to inspect the stable wheat genotype for timely and late sown planting condition in central zone of India. For that total of 20 wheat genotypes, including two parents and three commercial checks, were tested across 6 (timely sown) + 4 (late sown) environments at Jabalpur, Narmadapuram, and Sagar district of Madhya Pradesh state of India in 2019-20 and 2021-21. The per plant yield and grain filling rate data were considered to perform univariate and multivariate stability analysis. Our result revealed that environment, genotype, and GEI effects were significant (P < 0.001) across all the environments and individual environmental conditions. The greater performing along with high stability for grain yield JW3288, L8 and L13 while for grain filling rate L11, L13 and L11 genotypes were identified in timely sown, late sown and across all the environments, respectively. In order to find stable and high-performing genotypes, the GEI accompanied by several models but AMMI and GGE models were further effective and accurate than the linear regression model. In conclusion according to univariate and multivariate stability analysis L13 was the utmost genotype across all the environments therefore, it might be used in future breeding programs although, Jabalpur was recognized as the most discriminating and representative environments across all the environments.