(untitled) (Applied Biological Research, 2024)
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.