Spectroscopy and Spectral Analysis, Volume. 34, Issue 7, 1826(2014)
Application of Near-Infrared Spectroscopy to Distinguish Brands of Soy Milk Powder and Fake Soy Milk Powder
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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ZHANG Chu, LIU Fei, KONG Wen-wen, HE Yong. Application of Near-Infrared Spectroscopy to Distinguish Brands of Soy Milk Powder and Fake Soy Milk Powder[J]. Spectroscopy and Spectral Analysis, 2014, 34(7): 1826
Received: Oct. 8, 2013
Accepted: --
Published Online: Jul. 22, 2014
The Author Email: Chu ZHANG (chuzh@zju.edu.cn)