Objective To systematically analyze the differences in volatile components of Chenxiang (Aquilariae Lignum Resinatum) essential oil (AEO) from various origins and extraction methods using an electronic nose combined with chemometrics, aiming to establish a novel method for rapid identification of AEO origins and extraction processes. Methods A total of 38 batches of AEO samples were collected from seven major origins using two extraction methods. Their chemical compositions were analyzed using gas chromatography-mass spectrometry (GC-MS), while overall aroma fingerprint information was obtained via electronic nose. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were comprehensively applied for pattern recognition of multi-source data. Results GC-MS analysis revealed that the common major components in all samples were benzylacetone, agarospirol, dehydrofuranone, and 2-(2-phenylethyl)chromone. Seven key differential compounds, including 2-(2-phenylethyl)chromone and 6-methoxy-2-(2-phenylethyl)chromone, were screened through variable importance projection (VIP > 1). The PCA results of the electronic nose response values show a good correlation with the origin or extraction method of AEO samples. The established OPLS-DA discriminant model exhibited excellent performance: the origin discriminant model achieved R_X² = 0.839, R_Y² = 0.794, Q² = 0.572 > 0.500, and the extraction method discriminant model achieved R_X² = 0.790, R_Y² = 0.647, Q² = 0.633 > 0.500, which can effectively classify AEO samples. Conclusion This study successfully combined the rapid identification of electronic nose with GC-MS component analysis, which confirmed that the combined strategy could accurately identify the extraction method and geographical origins of AEO, and clarified its material basis, providing an efficient and reliable new method for the classification and identification of AEO.

Aquilariae Lignum Resinatum essential oil  /  electronic nose  /  chemometrics  /  origin  /  extraction method  /  GC-MS  /  principal component analysis  /  partial least squares-discriminant analysis  /  orthogonal partial least squares-discriminant analysis  /  benzylacetone  /  agarospirol  /  dehydrofuranone  /  2-(2-phenylethyl)chromone  /  variable importance projection