Vol.8 : Number 13
Estimation of genetic divergence of bread wheat (Triticum aestivum L.) under normal sown condition

Author(s): Navodeeta Raaj, SK Singh


Present study was conducted using twenty four wheat genotypes under normal environment in Randomized Block Design with three replications at Wheat Breeding section of Dr. RPCAU, Pusa, Samastipur, Bihar during RABI 2016-17 for the evaluation of bread wheat (Triticum aestivum L.) genotypes under normal sown condition. Observations were recorded on sixteen characters. All the genotypes were taken for genetic divergence study under timely sown condition differed significantly with regard to the characters studied, displayed marked divergence and grouped into five clusters by Tocher’s method cluster II contain maximum nine genotypes whereas cluster I contain minimum three genotypes. For 14 characters considerable differences were observed on the basis of cluster means. cluster I recorded maximum mean values for number of tillers per plant, flag leaf area, relative water content, number of grains per spike, spike fertility, chlorophyll content, thousand grain weight, harvest index and grain yield. Cluster I also exhibited minimum mean value for plant height, days to fifty per cent flowering and spike length. Maximum intra cluster distance (D2 ) was observed by cluster IV (120.146) whereas minimum intra cluster distance was observed by cluster I (20.68). The highest inter cluster distance (D2 ) was observed between cluster I and V (445.23) whereas lowest inter cluster distance was recorded between cluster II and III (132.33). On the basis of contribution percentages of traits under studied towards total divergence under timely sown condition highest contribution in the manifestation of genetic divergence was exhibited by days to fifty per cent flowering (40.58) whereas negligible contribution (0.00) was exhibited by plant height, flag leaf area, relative water content, spike fertility. For the improvement of wheat genotypes, divergence suitable parents were selected based on genetic distance (cluster mean) and per se performance for different traits. 


Country: India