DETECTION OF RACTOPAMINE AND CLENBUTEROL HYDROCHLORIDE RESIDUES IN PORK USING SURFACE ENHANCED RAMAN SPECTROSCOPY

Abstract

Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identification of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 cm^{- 1} were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = -4.3683x - 11.059 and -0.9726. Second-level wavelet detail signal intensities at 1258 cm^-1 were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coefficient were y=33.595x+36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classification model for the identification of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identification of RAC and CL residues in pork.