Multivariate analysis for assessing the genetic diversity and association patterns of yield attributing traits in little millet (Panicum sumatrense)

DOI: 10.37992/2024.1501.016

  • R. Narasimhulu, C. Vijaya Kumar Reddy,
  • M. Jostna Kiranmayi, K. Hariprasanna,
  • K. Prabhakar and N. C. Venkateswarlu

Abstract

Little millet is an important small millet grown mostly in India. The availability of genetic variability is a critical requirement for crop improvement. Principal Component Analysis (PCA) and  correlation study was undertaken in a set of 28 little millet genotypes to estimate genetic diversity, association pattern among seven quantitative traits and to select suitable genotypes for crop improvement. In cluster analysis, the genotypes were classified into three distinct clusters, each with one or two subgroups. Cluster I had the major genotypes with comparable ancestry, followed by Cluster II. The total variance was split into seven major principal components, with the top two PCs with eigenvalues greater than one accounting for 82.57% of the overall variation. PC1, which explained a larger part of the variance (58.05%), was strongly influenced by days to 50% flowering, days to maturity, number of productive tillers per plant, 1000-grain weight, and grain yield. PC2 was primarily influenced by plant height and fodder yield. PCA and association analysis revealed a significant positive association between grain yield and the number of productive tillers per plant, 1000-grain weight, plant height. These traits would be useful for direct selection for little millet crop improvement. In both cluster analysis and PCA, the genotypes DHLM 14-5, IIMR LM-8004, NDL LM1, TNPSu 242, VS 33, WV 168, DPLN 1 and VS 38 displayed diversity, implying that these lines may be used in crossing programme to generate further genetic variability to select suitable transgressive segregants.

Keywords: Little millet, genetic diversity, correlation, principal component analysis, biplot

Published
02-04-2024
How to Cite
R. Narasimhulu, C. Vijaya Kumar Reddy, M. Jostna Kiranmayi, K. Hariprasanna, K. Prabhakar and N. C. Venkateswarlu

Multivariate analysis for assessing the genetic diversity and association patterns of yield attributing traits in little millet Panicum sumatrense

. 2024. Electronic Journal of Plant Breeding, 15 1, 178-184. Retrieved from https://www.ejplantbreeding.org/index.php/EJPB/article/view/4772
Issue
Vol 15 No 1 (2024): EJPB
Section
Research Note

It is certified that:

  • The corresponding author is fully responsible for any disputes arising due to the publication of his/her manuscript.
  • The article has been seen by all the authors who are satisfied with its form and content.
  • The sequence of names of authors in the by-line is as per their relative contribution to this experiment, giving due credit to all scientists who made notable contribution to it.
  • All the authors fully understand that inclusion of any other co-authors or exclusion of any co-authors is not possible once the article has been submitted to the journal.
  • The corresponding author takes full responsibility for this article.
  • The address of the organization where the research was conducted is given.
  • The article is exclusive for this journal, and the results reported here have not been sent (and will not be sent during its consideration by this journal) for publication in any other journal.
  • Authors agree to abide by the objective comments of referees and do agree to modify the article into a short note as per the recommendation, for publication in the Electronic Journal of Plant Breeding.
  • If published in Electronic Journal of Plant Breeding, the copyright of this article would vest with the Indian Society of Plant Breeders, who will have the right to enter into any agreement with any organization in India or abroad engaged in reprography, photocopying, storage and dissemination of information contained in it, and neither we nor our legal heirs will have any claims on royalty.