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Genetic Variability and Multivariate Analysis in Mungbean (Vigna radiata L.)

EasyChair Preprint no. 10092

19 pagesDate: May 12, 2023


In order to analyse and find a diverse line to future hybridizing programmes for genetic improvements, address variability and genetic diversity. This research focused on multivariate analysis using indirect and direct traits attributing to seed yield for developing a superior cultivar from existing cultivars and the coefficient of correlation using PCV and GCV with high heritability. Twenty four genotypes with thirteen quantitative characters were used and found significant through analysis of variance. High heritability and genetic advances are observed through which the highest index and biological yield per plant are observed in all the phenotypic traits and two genotypic traits: pod length and biological yield per plant. High-contribution divergence genotypes are ranked highly to seed weight and the highest intra-cluster distance. Highest seed weight and intra cluster distance were observed in clusters IV and VII, indicating that genotypes Guarat 4, MH 88, Tilak, and SML 688 were expected to have better performance and were therefore proposed for the hybridizing programme.

Keyphrases: genetic diversity, Genetic variability, multivariate analysis, path analysis

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Kanakkumar Patel and Satya Prakash and Adesh Kumar},
  title = {Genetic Variability and Multivariate Analysis in Mungbean (Vigna radiata L.)},
  howpublished = {EasyChair Preprint no. 10092},

  year = {EasyChair, 2023}}
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