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Study on Identification of Counterfeit Salmon Meat Based on Infrared Spectroscopy |
WU Ting1, ZHONG Nan1*, YANG Ling2 |
1. College of Engineering, South China Agricultural University,Key Laboratory of Key Technology on Agricultural Machine and Equipment(South China Agricultural University), Ministry of Education,Guangdong Provincial Key Laboratory of Food Quality and Safety, Guangzhou 510642,China
2. School of Information Science and Technology,Zhongkai University of Agriculture and Engineering,Guangdong Province Research Center of Food Safety and Intelligent Control Engineering Technology, Guangzhou 510225,China |
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Abstract There are various salmons of different varieties and prices at domestic salmon market. As Norwegian salmon can be sold at higher prices, the counterfeit problem of Norwegian salmon has become extremely serious in China. However, the identification methods are limited and it’s hard for consumers to identify different salmons. Therefore, a quick and accurate identification method is urgently needed. In the paper, infrared spectroscopy and partial least squares discriminant analysis (PLS-DA) were used to detect Norwegian salmon and three counterfeit Norwegian salmons (Heilongjiang salmon, freshwater rainbow trout, Chile Pacific salmon). The study used Fourier transform infrared (FITR) spectrometer and KBr pressed pellet method to acquire the original spectrum of the above four salmons. To eliminate interference factors such as noise and particles scattering, original spectra were preprocessed with multiplicative scatter correction (MSC), Savitzky-Golay, first derivative, standard normal variate (SNV) and peak area normalization respectively and the impact of each method on the model was studied as well. To establish PLS-DA model, spectra of the above four salmons were assigned reference score -3, -1, 1, 3 respectively at threshold range 1 to test the accuracy of the model. The results showed that PLS-DA model achieved the best performance when peak area normalization was used, with determination coefficient of calibration sets 0.97, cross validation sets 0.96, root mean square error of calibration sets(RMSEC) 0.37 and root mean square error of cross validation(RMSECV) 0.52. The model could significantly distinguish four salmons and achieved 96% accuracy when test sets was predicted. Mahalanobis distance method was also used in the study to find the differences of four kinds of spectra. The results showed Norwegian salmon had largest mahalanobis distance with rainbow trout and had smallest mahalanobis distance with Chile Pacific salmon, which was consistent with the difference of salmons’ species and living environments. In summary, infrared spectroscopy combined with PLS-DA is proved to be an effective method for detecting counterfeit salmons and the method may provide a way to distinguish other kinds of meat.
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Received: 2016-07-07
Accepted: 2016-11-12
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Corresponding Authors:
ZHONG Nan
E-mail: zhongnan@scau.edu.cn
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