Chemometrics Combined with Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry for the Identification of Baijiu Vintage

Abstract

Chemometrics combined with GC×GC-TOFMS was applied for the identification of baijiu Vintage. The data of 75 samples were finally compressed from 4.26 GB to 3.74 MB, reducing the data size by more than 1000 times without losing key information. Then, the data were analyzed by MCR-ALS, and pure mass spectra and corresponding concentration profiles were obtained. Twenty-four key principal components were selected using CARS-PLS. The errors were less than one year, indicating that the model can predict the storage year of baijiu based on volatile substances well. A PLS-DA (partial least squares-discriminant analysis) model was also built and 30 principal components were screened as candidate markers. The results showed that the combination of GC × GC -TOFMS and ROI-MCR can be a powerful approach for the analysis of large amount of high-dimensional data with overlapping compound elution curves and low accuracy of multi-dimensional peak alignment.

Keywords: Chemometrics, Multivariate Curve Resolution-Alternating Least Squares, Comprehensive Two-Dimensional Gas Chromatography - Time-of-flight Mass Spectrometry, Competitive Adaptive Reweighted Sampling-Partial Least Squares, Partial Least Squares-Discriminant Analysis, Vintage of Baijiu