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Rapid Discrimination of Aroma Components in Natural and Artificial Agarwood Incense by Static Headspace Sampling – Gas Chromatography – Mass Spectrometry (SHS-GC-MS) with Principal Component Analysis (PCA) and Partial Least Squares – Discrimination Analysis (PLS-DA)

Wenxia Sun, Shenghong Wu, Peng-Jian Zhu, Shimin Deng, Xin Zhou, Xiaohua Liu, Jing Zhao, Weimin Zhang, Xiaoxia Gao, Xiaoying Chen

2022Analytical Letters10 citationsDOI

Abstract

Agarwood is a resinous, fragrant wood produced by tropical tree species of the genus Aquilaria, and is highly valued for its wide range of uses in medicine, incense, and perfume. In this study, the quality of agarwood and patterns of chemical constituents induced in natural and artificial agarwood by physical injury, chemical inducer, and chemical plus fungal infection were compared using static headspace sampling gas chromatography – mass spectrometry (SHS-GC-MS). The optimal agarwood heating temperature was determined to be 180 °C. The fingerprints of 40 batches of agarwood were established. Multivariate statistical analysis was utilized to identify 15 common and ten differentiating components, respectively. Agarwood induced by the physical method was more similar to natural agarwood. Exploration of the pyrolysis products of chromone derivatives and sesquiterpenes was undertaken to discover the causes of differences in chemical compositions between artificial and natural agarwood. Our findings revealed that benzylacetone, baimuxinal, and guaiol were significant for agarwood incense and these compounds may be used as markers for classification.

Topics & Concepts

AgarwoodIncenseChemistryGas chromatography–mass spectrometryChemometricsChromatographyGas chromatographyMass spectrometryAlternative medicineMedicinePathologyPhilosophyTheologyWood and Agarwood ResearchCultural Heritage Materials AnalysisMicrobial Metabolism and Applications
Rapid Discrimination of Aroma Components in Natural and Artificial Agarwood Incense by Static Headspace Sampling – Gas Chromatography – Mass Spectrometry (SHS-GC-MS) with Principal Component Analysis (PCA) and Partial Least Squares – Discrimination Analysis (PLS-DA) | Litcius