Multivariate Genetic Analyses Unveil the Complexity of Grain Yield and Attributing Traits Diversity in Oryza sativa L. Landraces from North-Eastern India

Anjan Roy Anjan Roy; Sanghamitra Rout Sanghamitra Rout; Lakshmi Hijam Lakshmi Hijam; Supratim Sadhu Supratim Sadhu; Pavithra S Pavithra S; Abir Ghosh Abir Ghosh; Moumita Chakraborty Moumita Chakraborty; Nandita Sahana Nandita Sahana; Saurav Singla Saurav Singla; Suddhasuchi Das Suddhasuchi Das

doi:10.14719/pst.2500

Authors

Anjan Roy Anjan Roy Department of Genetics and Plant Breeding, Uttar Banga Krishi Viswavidyalaya, Pundibari, Cooch Behar, West Bengal- 736165, India; Department of Genetics and Plant Breeding, MS Swaminathan School of Agriculture, Centurion University of Technology and Management, Paralakhemundi, Odisha- 761211, India https://orcid.org/0000-0002-4354-7861
Sanghamitra Rout Sanghamitra Rout Department of Genetics and Plant Breeding, MS Swaminathan School of Agriculture, Centurion University of Technology and Management, Paralakhemundi, Odisha- 761211, India https://orcid.org/0000-0003-4910-687X
Lakshmi Hijam Lakshmi Hijam Department of Genetics and Plant Breeding, Uttar Banga Krishi Viswavidyalaya, Pundibari, Cooch Behar, West Bengal- 736165, India https://orcid.org/0000-0002-8312-920X
Supratim Sadhu Supratim Sadhu School of Agriculture Science, JIS University, Kolkata, West Bengal, India https://orcid.org/0000-0001-9661-4223
Pavithra S Pavithra S Department of Genetics and Plant Breeding, Uttar Banga Krishi Viswavidyalaya, Pundibari, Cooch Behar, West Bengal- 736165, India https://orcid.org/0000-0001-9348-5569
Abir Ghosh Abir Ghosh College of Forestry, Sam Higginbottom University of Agriculture, Technology and Sciences, Allahabad, Uttar Pradesh- 211007, India https://orcid.org/0009-0000-6834-7332
Moumita Chakraborty Moumita Chakraborty Department of Genetics and Plant Breeding, Uttar Banga Krishi Viswavidyalaya, Pundibari, Cooch Behar, West Bengal- 736165, India https://orcid.org/0000-0002-7832-8159
Nandita Sahana Nandita Sahana Department of Agriculture Biochemistry, Uttar Banga Krishi Viswavidyalaya, Pundibari, Cooch Behar, West Bengal- 736165, India https://orcid.org/0000-0003-4959-173X
Saurav Singla Saurav Singla School of Chemical Engineering and Physical Science, Lovely Professional University, Phagwara, Punjab- 144401, India https://orcid.org/0000-0001-9780-4010
Suddhasuchi Das Suddhasuchi Das Krishi Vigyan Kendra, Malda, Uttar Banga Krishi Viswavidyalaya, West Bengal- 732205, India https://orcid.org/0009-0004-0397-2259

DOI:

https://doi.org/10.14719/pst.2500

Keywords:

Genetic diversity, grain yield, landraces, multivariate analysis, Rice

Abstract

In the North-Eastern region of India, rice stands as the predominant staple, with diverse cultivars evolving over the past six decades. This study systematically evaluated 20 rice landraces, analyzing eleven variables related to yield and its attributing traits. The aim was to identify promising genotypes for potential breeding programs and to ascertain the minimum number of components essential for explaining the total diversity. Among the eleven principal components (PCs) examined, four PCs exhibited eigenvalues surpassing 1.0, collectively contributing to 80.45% of the total variability in the traits. PC1, which explained 31.19% of the overall variance, was associated with plant height, days to 50% flowering, panicle length, grain breadth, and grain length-to-breadth ratio. Utilizing cluster analysis, the 20 rice landraces were categorized into seven distinct clusters. Maximum inter-cluster divergence was observed between clusters VI and I, as well as clusters VI and V, indicating greater genetic distinctiveness among genotypes in these clusters compared to others. Notably, rice landraces such as Borosolpana, Phougak, Satyaranjan, Kakcheng Phou, Moniram, Kanaklata, and Bahadur were identified as genetically divergent. These genotypes hold promise for generating segregating populations, serving as valuable source materials for targeted yield improvement through meticulous selection, as indicated by inter-cluster distances.

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