Assessment of genetic variability in bread Wheat (Triticum aestivum) under heat stress

• Published in: The Indian journal of agricultural sciences 2022-05, Vol.92 (4), p.511-505
• Main Authors: SAMITA, KUMAR, MUKESH, SINGH, VIKRAM, YADAV, SUNAINA, YADAV, SURESH, KAVITA, KUMAR, DEEPAK, CHOUDHARY, RAJU RAM
• Format: Article
• Language: English
• Subjects: Diversity, Grain yield, Heat stress, Wheat
• ISSN: 0019-5022; 2394-3319
• DOI: 10.56093/ijas.v92i4.124005

The present study was carried out during rabi 2017–18, at wheat research farm, Department of genetics and plant breeding, CCS Haryana Agricultural University, Hisar, Haryana to assess the genetic diversity of 64 genotypes of bread wheat (Triticum aestivum L.) under late sown conditions based on the morpho-physiological traits. Analysis of variance depicted significant differences for all morpho-physiological traits under heat stress. Mean sum of squares due to genotypes were found significant for all the traits, indicating the presence of sufficient genetic variability among the genotypes. High estimates of phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV) and high heritability coupled with high genetic advance were observed for traits, viz. spike weight, relative stress injury, chlorophyll stability index and GGR28 indicating additive gene action in expression of the traits and simple selection will be effective for the improvement of these traits. Correlation coefficient analysis revealed that increased grain yield under heat stress conditions was significantly contributed by spike weight (0.699), spike length (0.646), harvest index (0.616), spikelets per spike (0.445), number of productive tillers (0.393), grains per spike (0.390), 1000-grain weight (0.364), biological yield (0.360), GGR14 (0.332) and chlorophyll stability index (0.330). Among the traits studied, biological yield per plot (0.8421) and harvest index (0.9686)recorded for highest positive direct effect on grain yield in late sown conditions. The grain yield is indirectly contributedby spike length, spike weight, spikelets per spike, CSI, GGR14 through harvest index and number of productive tillers permeter, spike weight, thousand grain weight, GGR14 through biological yield.