Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy

• Published in: Journal of applied spectroscopy 2017-03, Vol.84 (1), p.76-81
• Main Authors: Zhao, J. H., Yuan, H. C., Peng, Y. J., Hong, Q., Liu, M. H.
• Format: Article
• Language: English
• Subjects: Analytical Chemistry; Atomic/Molecular Structure and Spectra; Cations; Correlation coefficients; Least squares; Physics; Physics and Astronomy; Pork; Raman spectroscopy; Residues; Support vector machines; Wavelet transforms
• ISSN: 0021-9037; 1573-8647
• DOI: 10.1007/s10812-017-0430-6

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 identifi cation 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 coeffi cient 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 classifi cation model for the identifi cation 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 identifi cation of RAC and CL residues in pork.