Analysis of Essential Oils from Cassia Bark and Cassia Twig Samples by GC-MS Combined with Multivariate Data Analysis

Abstract

Cinnamomum cassia is one of several species of Cinnamomum which has been widely used as a spice. In this study, the chemical profiles of its bark and twig were characterized by gas chromatography-mass spectrometry (GC-MS) and multivariate data analysis. Principle component analysis (PCA) and orthogonal projection to latent structures discriminate analysis (OPLS-DA) of GC-MS data provided a clear separation between those samples. The result obviously showed that the metabolome of cinnamon bark (CB) and cinnamon twig (CT) is different, and the corresponding loading S-plots revealed that the differential metabolites between the essential oils of CB and CT were trans-cinnamaldehyde, trans-anethole, α-cubebene, γ-muurolene, γ-amorphene, δ-cadinene, (−)-calamenene, and o-methoxycinnamaldehyde. Our study demonstrates that the combination of GC-MS spectrum and multivariate data analysis can be applied to identify essential oils from different parts of C. cassia.