Prinicipal Component Analysis and Traits Association in Blackgram (Vigna mungo (L.) Hepper)

Kumar, Bheeram Vinod and Lal, Gaibriyal M. and Reddy, Yeruva Venkata Subba and Kumar, E. Shashi and Bhupal, Golla (2022) Prinicipal Component Analysis and Traits Association in Blackgram (Vigna mungo (L.) Hepper). International Journal of Plant & Soil Science, 34 (23). pp. 37-48. ISSN 2320-7035

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Abstract

The present investigation was carried out to assess the genetic variability parameters, correlation and path analysis in the 23 genotypes of Blackgram during Zaid-2021 at the research field, Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj. LBG-645 is identified as high seed yielding per plant at Prayagraj agro-climatic condition. The analysis of variance for all the characters revealed that genotypes were highly significant except harvest index (%). Genotypes were highly significant at 5%, 1% level for all the characters, indicating presence of considerable amount of genetic variability in the parental material tested. The characters with high range estimates of GCV and PCV number of clusters per plant, number of pods per plant. Heritability and genetic advance as % of mean values were high for number of pods per plant. The seed yield per plant exhibited positive significant and correlation with number of pods per plant at genotypic and phenotypic level. At genotypic and phenotypic path coefficient analysis revealed that number of pods per plant had greatest positive direct effect on seed yield per plant. Principal component (PC1) contributed maximum towards variability 22.808% was correlated with Seed Index followed by, plant height and number of seeds per pod. The second principal component (PC2) accounted 21.410% per cent of total variance and it reflected positive loading of days to 50% pod initiation, days to 50% flowering, and pod length whereas; the third principal component (PC3) accounted 15.642% per cent of total variance and positive loading of harvest Index followed by seed Index. Fourth principal component (PC4) contributed 11.325% of variability reflected loadings of days to maturity followed by seed yield per plant. The fifth principal component (PC5) contributed 9.489% variability of seed yield per plant, followed by days to 50% flowering.

Item Type: Article
Subjects: STM Article > Agricultural and Food Science
Depositing User: Unnamed user with email support@stmarticle.org
Date Deposited: 24 Jan 2023 06:41
Last Modified: 07 May 2024 04:53
URI: http://publish.journalgazett.co.in/id/eprint/232

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