Application of Infrared Spectroscopy Combined with Bayesian Information Fusion for Identification of Different Original Wines

A technique of Bayesian information fusion on near-infrared transmission( NIR) spectra and mid-infrared( MIR) attenuated total reflectance( ATR) spectra which have different limit of detection was proposed to identify different original wines. NIR and MIR spectra of three different variety wines( cabernet sauvignon,merlot,cabernet gernischt) and different aging wines( oak barrel,oak chips,stainless steel tank) were collected separately. Partial least squares discriminate analysis( PLS-DA) method was used to establish discriminant models,and then use the Bayesian methods to achieve the integration of the two kinds of discrimination results. The recognition accuracy after Bayesian information fusion were below: for wine variety identification,the accuracy rate of cross-validation was 95. 08% and validation set was 94. 68%,for wine aging ways identification,the accuracy rate of cross-validation is 98. 91% and validation set was 98. 75%, which achieved better results on classification than individual spectroscopy. These results suggest that spectral information fusion technology helps to improve the effect of discriminant model and is feasible for fast identification on different variety and aging red wines.