Title : Cotton improvement for heat tolerance using multiple stress tolerance indices and multivariate analyses
Abstract:
In current abrupt climate change scenarios, yield under stressful and normal conditions is a principal indicator for identifying stress-resilient genotypes. Different studies have suggested that various yield indices determine stress-tolerant genotypes. With the help of stress indices as an appropriate criterion to select desirable genotypes across heat-prone areas, the response of 23 cotton genotypes was evaluated under normal and heat stress conditions. Nine stress tolerance indices were used for seed cotton yield under both conditions to identify the overall index precisely. The correlation and principal component analysis results revealed that mean productivity (MP), Geometric Mean Productivity (GMP), Harmonic Mean (HM), Stress Tolerance Index (STI), and Yield Index (YI) was positively associated with seed cotton yield under both conditions. These stress indices revealed that the five are the most heat tolerant genotypes, while the three are the most heat sensitive ones. The hierarchical clustering and ranking based on stress indices revealed that the genotypes G15 and G7 were the most heat tolerant genotypes as they revealed the best mean rank and almost low standard deviation of rank. The correlation of GMP of physiological traits was strongly related to STI, YI, and AR also validates our ranking based on yield indices.
Keywords: Heat Tolerance, Cotton, Stress Tolerance Indices, Multivariate Analysis
