Quality grade discrimination of Chinese strong aroma type liquors using mass spectrometry and multivariate analysis

article i nfo Article history: Food quality control and grade identification have an importance for protecting consumer benefits. In this paper, taking Yanghe Daqu for instance, we studied quality grade discrimination of Chinese liquor with strong aroma type. 108 samples were divided into calibration set (81 samples) and validation set (27 samples), whose mass spectra were obtained by head space-solid phase microextraction-mass spectrometry (HS-SPME-MS) technolo- gy in the range of m/z 55-191. And then, the partial least squares (PLS) regression and principal component regression (PCR) models were constructed by calibration set and predicted the quality grade of validation set. Discrimination accuracy of the PLS model was N96.3% for both calibration set and validation set, which was obviously superior to PCRmodel.The supportvector machine (SVM) modelswere built by differention selection methods, PLS regression coefficients, PLS X-loading, PCR regression coefficients, and PCR X-loading. Of these, the optimalSVM model was achieved with ions (m/z 112,134,140,162,167,168, 175, 187, and 191) selected by PLS regression coefficients, whose prediction accuracy for the validation set was up to 92.6%. The overall results indi- cated that the PLS regression coefficients was a powerful way for selecting effective ion variables and mass spec- trometry combined with SVM could well discriminate the quality grade of liquor.

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