Abstract

Climate change is one of the biggest problems for growing crops in a sustainable way around the world. At the cotton research station in Bahawalpur, th is experiment aimed to assess and classify cotton genotypes under conditions of heat stress. The study was done using RCBD with three replications. The distance between plants was 30 cm, and the distance between rows was kept at 75 cm. For key plant and fiber quality traits, data were taken from ten fully guarded plants and chosen randomly. Under conditions of heat stress, ANOVA showed that there were highly significant differences among the plant traits that were studied. The correlation coefficient analysis showed that seed cotton yield has a positive correlation with plant height (r = 0.46), plant population per hectare (r = 0.33), sympodial branches per plant (r = 0.27), number of bolls per plant (r = 0.27) and nodes per plant (r = 0.27) but a negative relationship with staple length (r = -0.35). The multivariate statistical methods of principal component and cluster analysis were used to describe cotton genotypes. Principal component analysis and cluster analysis showed that the most productive and heat-tolerant cotton genotypes were BH-200, BH-254, CIM-600, and BH-341. Also, BH-284 seemed more resistant to CLCuV than the other genotypes. So, rigorous, large-scale, and multilocation testing must be done on these cotton genotypes and plant traits to make cotton genotypes that can handle heat and CLCuV