Multivariate analysis of morphological descriptors for identification of Sesbania Scop. accessions

Authors

  • SC Chanda Laboratory of Plant Systematics, Department of Crop Botany, Bangladesh Agricultural University, Mymensingh, Bangladesh
  • Md A Razzak Laboratory of Plant Systematics, Department of Crop Botany, Bangladesh Agricultural University, Mymensingh, Bangladesh
  • Md E Haque Department of Agriculture Extension, Sirajganj, Bangladesh
  • AKM Golam Sarwar Laboratory of Plant Systematics, Department of Crop Botany, Bangladesh Agricultural University, Mymensingh, Bangladesh

DOI:

https://doi.org/10.3329/bjsir.v55i3.49395

Keywords:

Sesbania Scop.; Numerical data; Agglomerative hierarchical clustering; Principal component analysis; Dissimilarities distance

Abstract

Based on the 36 quantitative morphological descriptors, agglomerative hierarchical clustering (AHC) and principal component analyses (PCA) were conducted to identify 106 diverse Sesbania accessions. The AHC analysis identified three major clusters with 11 sub-clusters. In PCA, the first and second PCs explain 72.48% and 12.72% of total variations with high Eigen value 9.1 and 1.7, respectively. Sesbania accessions occupied four distinct positions in the PCA graph. Based on multivariate analyses and qualitative descriptors, Sesbania accessions have been identified as S. bispinosa (90 accessions), S. cannabina (9 accessions), S. sesban (6 accessions) and the known S. rostrata. The AHC dendrogram has detected the close similarities between S. rostrata and S. cannabina. However, the PCA has emerged to be better than the AHC as a species identification tool. Among these four species, the highest discriminating distance (23.69%) was observed between S. sesban and S. bispinosa, and the lowest (10.52%) was in S. bispinosa and S. cannabina.

Bangladesh J. Sci. Ind. Res.55(3), 215-220, 2020

Downloads

Download data is not yet available.
Abstract
27
PDF
29

Downloads

Published

2020-09-24

How to Cite

Chanda, S., Razzak, M. A., Haque, M. E., & Sarwar, A. G. (2020). Multivariate analysis of morphological descriptors for identification of Sesbania Scop. accessions. Bangladesh Journal of Scientific and Industrial Research, 55(3), 215–220. https://doi.org/10.3329/bjsir.v55i3.49395

Issue

Vol. 55 No. 3 (2020)

Section

Articles

License

Bangladesh Council of Scientific and Industrial Research (BCSIR) holds the copyright to all contents published in Bangladesh Journal of Scientific and Industrial Research (BJSIR). A copyright transfer form should be signed by the author(s) and be returned to BJSIR.

The entire contents of the BJSIR are protected under Bangladesh Council of Scientific and Industrial Research (BCSIR) copyrights.

Creative Commons Licence
BJSIR is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC) Creative Commons Attribution-NonCommercial 4.0 International License which allows others remix, tweak, and build upon the articles non-commercially, and although their new works must also acknowledge and be non-commercial, they don’t have to license their derivative works on the same terms.