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

High-temperature stress is one of the hurdles to achieving self-sufficiency and sustainability in maize production globally. The current experimental study was executed to identify the best suitable maize hybrids for heat-prone areas based on their performance. During spring 2020 & 2021, hybrids were sown under two stress conditions (a) control sowing and (b) late sowing.  Kernel yield and related characteristics varied significantly among maize hybrids across both situations (P<0.05). Under High-temperature stress, correlation analysis uncovered a positive relationship between kernel yield and chlorophyll a (r = 0.77**, 0.54**), chlorophyll b (r = 0.72**, 0.66**), net photosynthetic rate (r = 0.71**, 0.67**), proline contents (r = 0.59*, 0.54**), hydrogen peroxide (r = 0.54*, 0.17NS), thousand kernel weight (r = 0.71*, 0.38*). Principal component and biplots analysis unveiled that the first four principal components accountable for 78.0% of the total variability among hybrids, with days to 50% silking, plant height, number of kernels per ear, kernel yield, net photosynthetic rate, hydrogen peroxide, malondialdehyde, and catalase as the primary sources of variation. Agglomerative Hierarchical Clustering (AHC) categorizes indigenous and multinational maize hybrids into three classes under stress treatments. The cluster analysis further revealed that indigenous hybrids, particularly YH-5395, YH-5482 and YH-5427 were the most heat tolerant and productive hybrids while YH-5404, P-1543 and JPL-1908 were among the most heat susceptible ones. Consequently, these hybrids are recommended for widespread cultivation, particularly in regions prone to high temperatures.