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ZJUS-B
Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology)  2008, Vol. 9 Issue (12): 982-989    DOI: 10.1631/jzus.B0820057
Biotechnology     
Application of principal component-radial basis function neural networks (PC-RBFNN) for the detection of water-adulterated bayberry juice by near-infrared spectroscopy
Li-juan XIE, Xing-qian YE, Dong-hong LIU, Yi-bin YING
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China
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Abstract  Near-infrared (NIR) spectroscopy combined with chemometrics techniques was used to classify the pure bayberry juice and the one adulterated with 10% (w/w) and 20% (w/w) water. Principal component analysis (PCA) was applied to reduce the dimensions of spectral data, give information regarding a potential capability of separation of objects, and provide principal component (PC) scores for radial basis function neural networks (RBFNN). RBFNN was used to detect bayberry juice adulterant. Multiplicative scatter correction (MSC) and standard normal variate (SNV) transformation were used to preprocess spectra. The results demonstrate that PC-RBFNN with optimum parameters can separate pure bayberry juice samples from water-adulterated bayberry at a recognition rate of 97.62%, but cannot clearly detect water levels in the adulterated bayberry juice. We conclude that NIR technology can be successfully applied to detect water-adulterated bayberry juice.

Key words： Near-infrared (NIR) spectroscopy      Principal component-radial basis function neural networks (PC-RBFNN)      Bayberry juice      Adulteration      Chemometrics technique     
Received: 24 February 2008     
CLC:  O43  
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Li-juan XIE
Xing-qian YE
Dong-hong LIU
Yi-bin YING
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Li-juan XIE, Xing-qian YE, Dong-hong LIU, Yi-bin YING. Application of principal component-radial basis function neural networks (PC-RBFNN) for the detection of water-adulterated bayberry juice by near-infrared spectroscopy. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2008, 9(12): 982-989.

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http://www.zjujournals.com/xueshu/zjus-b/10.1631/jzus.B0820057     OR     http://www.zjujournals.com/xueshu/zjus-b/Y2008/V9/I12/982

[1] Li-juan XIE, Yi-bin YING. Use of near-infrared spectroscopy and least-squares support vector machine to determine quality change of tomato juice[J]. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2009, 10(6): 465-471.
[2] GUAN Rong-fa, LIU Dong-hong, YE Xing-qian, YANG Kai. Use of fluorometry for determination of skim milk powder adulteration in fresh milk[J]. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2005, 6(11): 9-.