Abstract
This study involved examining 32 advanced wheat breeding lines sourced from BISA, Ludhiana and NBPGR, New Delhi. Executed at Lovely Professional University’s Experimental farm for Plant Breeding and Genetics in Phagwara, Punjab, India, within the span of 2021-2022, this experiment utilized a meticulous randomized block layout replicated three times. The research focused on studying ten different characteristics. Genotypic variance significance was evident in all traits, reflecting genetic diversity. Phenotypic coefficient of variation (PCV) exceeded genotypic coefficient (GCV), likely due to genotype-environment interactions. Plant height and grain yield displayed moderate PCV and GCV, while days to flowering, days to maturity, spike length, 1000-seed weight, biological yield, and harvest index showed lower values. Effective tillers and grains per spike had higher PCV and GCV, indicating limited enhancement potential. Traits like effective tillers, plant height, grains per spike, and grain yield showed high heritability and genetic advance. Moderate genetic advance was noted in spike length, weight of a thousand seeds, overall biological productivity, and the index of harvesting efficiency. In contrast, flowering and maturity had low genetic advance. Eight of ten traits positively impacted yield of harvested grain, including time taken to reach maturity, height of plant, grain count per spike, seed weight per thousand, total biological output and harvest efficiency. Clustering analysis revealed the highest intra-cluster distance in cluster IV, followed by I and II. Clusters III and V lacked intra-cluster relations. Inter-cluster distances were highest between V and II, followed by other pairs. Plant height drove divergence, followed by grain yield, effective tillers and harvest index. This study suggests leveraging diverse genotypes for hybridization, supported by predictive statistical distances, for broad variations in wheat improvement strategies.
doi: 10.17756/jfcn.2023-s1-005
Citation: Kaur SJ, Talekar N, Delvadiya I, Singh SK, Raut A. 2023. Genetic Profiling of Bread Wheat (Triticum aestivum L.): Analyzing Variation, Associations, Path Analysis, and Diversity to Revolutionize Crop Enhancement. J Food Chem Nanotechnol 9(S1): S21-S27.
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