Журнал генетики и селекции растений

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Multivariate Analysis among Advanced Breeding Lines of Rice (Oryza Sativa L.) Under Sub-Tropical Ecology of Jammu Region of J&K

Danish Mushtaq, Bupesh Kumar

Present study was aimed to determine the nature and extent of genetic divergence for agro-morphological and quality traits among twenty seven advanced breeding lines of rice utilizing multivariate techniques. Based on the calculated D2 values, breeding lines were grouped into six non overlapping clusters. Inter-cluster distances were found to be relatively greater than intra-cluster distances indicating presence of enormous amount of variation among the lines. Cluster I and Cluster II were found to be the largest clusters consisting of 14 and 9 genotypes respectively, while, remaining four clusters were monogenotypic consisting of single line only. Maximum inter-cluster distance was reported between cluster II and VI, while maximum intra-cluster distance was recorded for cluster II respectively [1]. Breeding lines present in cluster II were observed to have maximum cluster means for traits viz., plant height, and total number of tillers per plant, amylose content, grain yield per plant and grain yield per plot indicating its superiority over rest of the clusters. Traits including grain yield per plot, grain yield per plant, days to maturity, 1000 grain weight, and total number of tillers per plant and panicle length were observed to be major contributors to genetic divergence. Principal component analysis revealed presence of genetic variation through six principal components with first five components viz., PC-I to PC-IV having eigen scores greater than one suggesting that traits within these axis have potential effect on development of a phenotype. Further principal component analysis revealed that traits such as number of effective tillers per plant, grain yield per plot, plant height, panicle length and days to 50 per cent flowering contribute maximum towards genetic diversity [2].

Отказ от ответственности: Этот реферат был переведен с помощью инструментов искусственного интеллекта и еще не прошел проверку или верификацию.