The objective of this study was to identify genotype high yielding and drought-tolerant, by understanding the interaction GY pattern for yield, yield components and physiological traits in 24 cotton genotypes over five years under drought stress conditions using AMMI analysis, genetic parameters and multivariate analysis. All assessed traits were significantly impacted by genotypes and GY interaction using the AMMI model, with the exception of chlorophyll b by GY interaction. Meanwhile, seed cotton yield/plant, number of open bolls/plant, lint percentage, lint cotton yield/plant, and number of fruiting branches/plant were significantly affected by the year's factor. High BSH coupled with high GAM% was observed for all studied traits, indicating the heritability due to additive type of gene action and, the importance of these genotypes and the possibility of effective selection for drought-tolerant genotype development. A statistically significant correlation was discovered between cotton yield and most investigated traits under drought stress conditions. Direct selection can be done through these traits based on genetic parameters and Pearson's correlations analyses, which will be effective for drought tolerance and enhancing cotton yield. The results of our study's Pearson's correlation analysis, PCA and cluster analysis could be relevant and appropriate for studying drought tolerance mechanisms and cotton yield improvement. According to PCA and cluster analysis, the genotypes G20 and G19 followed by G5, G4 and G21 genotypes showed the best performance in response to drought stress regarding the yield, yield components and physiological-related traits. The previous genotypes could be used in future cotton breeding efforts in Egypt to promote drought tolerance, improve cotton productivity, and sustainable production during drought stress conditions.

Drought impacts on cotton cultivation and production are expected to worsen as a result of global warming and water-deficit stress. Drought tolerance indices and PCA analysis were used to evaluate drought stress responses in eleven cotton genotypes and fifteen indices' ability to identify drought-tolerant genotypes under normal and drought circumstances. Seed cotton yield (Kentar feddan-1) was significantly affected by genotypes, years, and their interaction (p ≤ 0.05 or 0.01) under normal and water-deficit stress conditions, according to a combined ANOVA. Except for error variance, all genetic parameters studied for seed cotton yield were higher in normal irrigation conditions than in water-deficit stress conditions. According to PCA analysis, The STI, MP, GMP, HM, ATI, SSPI, and TOL are suitable indicators and were similar in their ability to screen, rank and detect tolerant genotypes, due to positive correlations among each other and also the highest association with seed cotton yield in both irrigation conditions. The genotypes G4, G9, and G10 (Group A) seemed to be the most drought-tolerant and cotton productive based on mean performance, GxY heatmap analysis, drought tolerance indices, and PCA analysis. The results of our study's drought tolerance indices and PCA could be useful and appropriate for studying drought tolerance mechanisms and cotton yield improvement in Egypt.