Rapid Identification of 3 Natural Leathers with IR and Principal Component Analysis

The IR spectra for 3 natural leathers of pig, cow and sheep were collected directly by attenuated total reflectance accessory. The characteristics and locations of IR absorption peaks of main groups in amino acid structure of leather were analyzed. The principal component analysis was preceeded after preprocessing of spectra data and choosing the appropriate areas. Firstly, the samples were identified directly via building principal component score space. It was found that the principal component score space of cow leather sample overlapped with sheep leather sample mostly due to the extremely similar with spectra of the 2 leather samples. Then the discriminant model of principal component regression was established after using 3 natural leather samples of pig, cow and sheep as 3 components. The prediction correlation coefficients of the model for the 3 components were in the range of 0.965-0.990, with RMSEC and RMSEP were no more than 0.122 and 0.213, respectively, which exhibited well stability. The model was verified using the test samples. The results showed that the 3 leather samples could be identified quickly and easily according to the predicted value of each component.