| 光谱学与光谱分析 |
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| Application of Near-Infrared Spectroscopy to Distinguish Brands of Soy Milk Powder and Fake Soy Milk Powder |
| ZHANG Chu, LIU Fei, KONG Wen-wen, HE Yong* |
| College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China |
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Abstract Near-infrared spectroscopy combined with chemometrics was used to investigate the feasibility of identifying different brands of soymilk powder and the counterfeit soymilk powder products. For this purpose, partial least squares-discriminant analysis (PLS-DA), linear discriminant analysis (LDA) and back-propagation neural network (BPNN) were employed as pattern recognition methods to class ify soymilk powder samples. The performances of different pretreatments of raw spectra were also compared by PLS-DA. PLS-DA models based on De-trending and multiplicative scatter correction (MSC)combined with De-trending(MSC+De-trending) spectra obtained best results with 100% prediction accuracy, respectively. Six and seven optimal wavenumbers selected by x-loading weights of the best two PLS-DA models were used to build LDA and BPNN models. Results showed that BPNN performed best and correctly classified 100% of the soymilk powder samples for both the calibration and the prediction set. The overall results indicated that NIR spectroscopy could accurately identify branded and counterfeit soymilk powder products.
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Received: 2013-10-08
Accepted: 2014-01-26
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Corresponding Authors:
HE Yong
E-mail: yhe@zju.edu.cn
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