The application of attenuated total reflectance infrared spectroscopy (ATR-IR), Raman spectroscopy (RS) and combination of ATR-IR and RS for measurements of total antioxidant capacity (TAC) and total phenolic content (TPC) of Chinese rice wine (CRW) were investigated in this study. Synergy interval partial least-squares (SiPLS), support vector machine (SVM) and principal component analysis (PCA) were applied to process the merged data from two individual instruments. It was observed that the performances of models based on the RS spectra were better than those based on the ATR-IR spectra. In addition, SVM models based on the efficient information extracted from ATR-IR and RS spectra were superior to PLS models based on the same information and PLS models based on ATR-IR or RS spectra. The overall results demonstrated that integrating ATR-IR and RS was possible and could improve the prediction accuracy of TAC and TPC in CRWs.
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