Characterization of Botanical Parts of <i>Erythrina crista-galli</i> Using Pyrolysis-Gas Chromatography/Mass Spectrometry and Multivariate Analysis

Erythrina crista-galli is commonly used in folk medicines for its pharmacological properties which are associated with the bioactive compounds. Profiling botanical parts of E. crista-galli is an exciting topic and essential to uncover the similarity and clustering based on their chemical content. Th...

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Bibliographic Details
Main Authors: Abd. Wahid Rizaldi Akili, Ari Hardianto, Jalifah Latip, Maya Ismiyati, Tati Herlina
Format: Article
Language:English
Published: Department of Chemistry, Universitas Gadjah Mada 2023-08-01
Series:Indonesian Journal of Chemistry
Subjects:
Online Access:https://jurnal.ugm.ac.id/ijc/article/view/77325
Description
Summary:Erythrina crista-galli is commonly used in folk medicines for its pharmacological properties which are associated with the bioactive compounds. Profiling botanical parts of E. crista-galli is an exciting topic and essential to uncover the similarity and clustering based on their chemical content. The botanical parts of E. crista-galli, including bark, flowers, leaves, roots, and twigs, were subjected to pyrolysis-gas chromatography/mass spectrometry. The samples were pyrolyzed using a multi-shot pyrolyzer. The relative abundance of the pyrolysate was subjected to multivariate analysis, i.e., principal component analysis (PCA) and hierarchical cluster analysis (HCA). The scree plot for PC.1, PC. 2, and PC. 3 accounted for 36.5%, 27.2%, and 20.3%, respectively. Together, the first three PCs explain 84% of the total variance. The PCA allows characterizing the roots of E. crista-galli by the highest relative abundance of lignin G, followed by the twigs, bark, and leaves, while the flowers had the least relative abundance of lignin G. The HCA allows to cluster the botanical parts of E. crista-galli into three different clusters based on their chemical component similarity, i.e., flowers-leaves, twigs, and roots-bark. In conclusion, Py-GC/MS analysis can be used in conjunction with multivariate data analysis to characterize the botanical parts of E. crista-galli.
ISSN:1411-9420
2460-1578