MORPHOMETRIC IDENTIFICATION OF Calotropis procera (Aiton) Dryand and Jatropha curcas L. IN NORTHERN NIGERIA

Authors

  • Abdulrahman Mahmoud Dogara Biology Education Department, Tishk International University, Erbil (Iraq)

DOI:

https://doi.org/10.48165/abr.2024.26.01.2

Keywords:

Calotropis procera, discrimination, Jatropha curcas, plant taxonomy, phenetic

Abstract

Phenetic analysis is a method for comparing plant species to establish their  degree of genetic similarity. To identify and classify the enormous variety of  plant life, morphological traits are essential. As the primary characteristics of  Calotropis procera and Jatropha curcas species, subspecies, and variety were  inadequately documented, there has been long-standing misunderstanding  and controversy concerning the taxonomic designations of these species. This  study aimed to use morphometric data to taxonomically identify C. procera and J. curcas using multivariate analysis. From the wild of Randagi, Sabon  Gero, and Kabara in Kaduna state, Northern Nigeria, twelve samples of C. procera and J. curcas each were collected. SIMCA-P (V.14.1, Umetrics  Sweden) was used for unsupervised multivariate analysis along with numerical  phenetic analysis. The analysis of this phenetic data yielded a spectrum filter  model with the strongest predictive power (fitness of the model) (Q2 (cum)  0.977) and the maximum variation (R2X (cum) 0.988). Principal component  analysis (PCA) showed clustering between the species under examination  along PCs 1 and 2, with C. procera clustering along the Y axis and J. curcas clustering along the X axis. A useful technique for avoiding adulteration is  phenetic analysis-based taxonomic identification of plants in conjunction with  multivariate analysis. However, to specifically analyse their relationships, a  combination of molecular and developmental datasets is still required. 

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Published

2024-03-23

How to Cite

MORPHOMETRIC IDENTIFICATION OF Calotropis procera (Aiton) Dryand and Jatropha curcas L. IN NORTHERN NIGERIA. (2024). Applied Biological Research, 26(1), 18–25. https://doi.org/10.48165/abr.2024.26.01.2