Abstract:The headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) detection method and metabolomics data processing technology were creatively applied in the identification of characteristic compounds in liquor and the assessment of liquor adulteration. Seventeen liquor samples were processed through headspace solid phase microextraction, and the volatile compounds in the liquor samples were accumulated. The dimension reduction of the GC-MS data set was achieved using the metabolomics technique. The clustering analysis was employed to correctly distinguish between contaminated and authentic liquors. The classification results from other series of liquors were generally consistent with actual liquor samples. In a principal component analysis, PC1 and PC2 were extracted, and accounted for 58.7% of the variance in the characteristic variables of different liquor samples. Among them, 44.7% of variance was explained by PC1, and a clear distinction was observed between the Hotelling’s elliptical regions of authentic and contaminated liquor samples. The information for authentic liquor samples was maintained in other samples. A liquor related model was established based on a partial least squares discriminant analysis for the removal of base liquor samples, so that the substance difference between authentic and contaminated liquor samples became significant. A variable importance table was generated and 12 related substances were obtained from the database. The top three characteristic compounds in terms of significant difference were butyl acetate, isoamyl caproate, and hexanoic acid isopropyl ester.
