Principal component analysis of yield and quality traits in Zinc rich landraces of rice (Oryza sativa L.)

DOI: 10.37992/2022.1304.169

  • T. Venkata Ratnam, B.N.V.S.R. Ravi Kumar,
  • L. V. Subba Rao,
  • T. Srinivas and A.D.V.S.L.P. Anand Kumar

Abstract

Principal Component Analysis (PCA) was carried out to find the genetic divergence among 35 zinc-rich landraces of rice along with two checks for yield and quality traits. Three principal components with Eigenvalue more than one, explained maximum variation witha total contribution of 78.33 percent of the total variability.Principal Component 1(PC 1) contributed a maximum of 51.71 percent, while PC 2 contributed to 18.71 percent and PC 3 contributed to 7.96 percent towards the total variability. Yield and quality traits such asdays to 50 percent flowering, number of productive tillers plant-1, grain yield plant-1, head rice recoverypercent, iron content and volume expansion ratio explained maximum variance in PC 1. The results of the 2D scatter diagramrevealed GM-120 and GM-173 landraces to be most diverse. These genotypes were identified to be high yielding and nutritionally rich, compared to BPT 5204. Hybridization of these genotypes is expected to result in desirable transgressive segregants for yield, quality and nutritional traits.

Keywords: Principal component analysis, Yield components, Quality traits,Zn ,Fe.

Published
11-01-2023
How to Cite
T. Venkata Ratnam, B.N.V.S.R. Ravi Kumar, L. V. Subba Rao, T. Srinivas and A.D.V.S.L.P. Anand Kumar

Principal component analysis of yield and quality traits in Zinc rich landraces of rice Oryza sativa L.

. 2023. Electronic Journal of Plant Breeding, 13 4, 1162-1169. Retrieved from https://ejplantbreeding.org/index.php/EJPB/article/view/4389
Issue
Vol 13 No 4 (2022): EJPB
Section
Research Article

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