Heat tolerance indices and their role in selection of heat stress tolerant chickpea (Cicer arietinum) genotypes

未知. Given the current scenario of global climate change, high temperature stress is appearing as a major challengelimiting crop productivity including chickpea (Cicer arietinum L.). Evidences of significant yield loss in chickpea due to high temperature stress encountering during reproductive stage has been recorded. Therefore, to sustain chickpea productivity, identification of heat stress (HS) tolerant chickpea via recruiting ‘breeder’s friendly’ selection criteriabased on yield traits under field condition is urgently needed. In our current study, we evaluated 78 chickpea genotypes(including 3 checks) in 5 blocks in augmented design under normal and late sown condition during 2015-16. VariousHS tolerance indices, viz. mean productivity (MP), geometric mean productivity (GMP), yield index (YI), toleranceindex (TOL), stress susceptibility index (SSI) and superiority measure (SM) were employed for identifying chickpeagenotype based on grain yield under normal and HS conditions. Based on the important selection indices, viz. YI,MP, GMP and SSI the following genotypes RVG 203, RSG 888, JAKI 9218, GNG 469, IPC 06-11 showed higherto moderate heat tolerance. Positive and high significant correlation of Yp with Ys, MP, YI, GMP, SSI and TOL wasrecorded. Likewise, Ys showed positive and high significant correlation with MP and GMP. While, YI indicatedsignificant and high positive correlation with MP and GMP, but it showed negative correlation with SSI. Importantly,MP and GMP both showed high and positive correlation with SSI and TOL, respectively. Importantly, principalcomponent analysis lowered all the six indices into 2 components PC1 explaining 61.9% and PC2 explaining 37.1%of total variation. While, 3-D scatter plot analysis grouped all the genotypes into four groups. Likewise, consideringcluster analysis, four distinct clusters were generated based on above-mentioned various indices. Towards this end,correlation analysis, 3-D scatter plot and cluster analysis explained that the most effective and efficient selectionindices for identifying heat tolerant genotype are MP, YI, GMP and SSI.