Development of an automated Raman system and use of principal component analysis to classify real and counterfeit liquors.

Abstract

We developed an automated Raman measurement platform for the customized design of various solution containers. We used the software LabVIEW to integrate the entire automatic measurement process. By designing an intuitive human-machine interface, the user only needs to input a few setting parameters and can efficiently operate the machine in automation mode for an array of solutions containing real or counterfeit liquors such as kaoliang liquor, vodka, rum, gin, rice wine, ethanol, and methanol. In this study, data from various alcoholic beverage solutions were subjected to principal component analysis (PCA) to distinguish from the low-concentration counterfeit liquors (methanol <50 g L-1). Moreover, several brands of liquors with the same alcohol concentration were successfully classified into different groups based on a combination of Raman spectroscopy and PCA analysis.