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

https://doi.org/10.22146/ijc.77325

Abd. Wahid Rizaldi Akili(1), Ari Hardianto(2), Jalifah Latip(3), Maya Ismiyati(4), Tati Herlina(5*)

(1) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Padjajaran, Jl. Raya Bandung Sumedang Km 21 Jatinangor, Sumedang 45363, Indonesia
(2) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Padjajaran, Jl. Raya Bandung Sumedang Km 21 Jatinangor, Sumedang 45363, Indonesia
(3) School of Chemical Sciences and Food Technology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Selangor 46300, Malaysia
(4) Research Center for Biomass and Bioproducts, National Research and Innovation Agency (BRIN), Jl. Raya Bogor Km 46, Cibinong 16911, Indonesia
(5) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Padjajaran, Jl. Raya Bandung Sumedang Km 21 Jatinangor, Sumedang 45363, Indonesia
(*) Corresponding Author

Abstract


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.

Keywords


E. crista-galli; pyrolysis-GC/MS; multivariate analysis; principal component analysis; hierarchical clustering analysis

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DOI: https://doi.org/10.22146/ijc.77325

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