Recognition of alcohol-free beer by fluorescent spectroscopy and probabilistic neural network

WEI Bai-lin; CHEN Guo-qing; XU Jiang-cai; YAN Guan-feng; MA Chao-qun; ZHU Tuo; GAO Shu-mei

doi:10.3969/j.issn.1001-3806.2010.06.020

LASER TECHNOLOGY > 2010 > 34(6): 794-797. > DOI: 10.3969/j.issn.1001-3806.2010.06.020

WEI Bai-lin, CHEN Guo-qing, XU Jiang-cai, YAN Guan-feng, MA Chao-qun, ZHU Tuo, GAO Shu-mei. Recognition of alcohol-free beer by fluorescent spectroscopy and probabilistic neural network[J]. LASER TECHNOLOGY, 2010, 34(6): 794-797. DOI: 10.3969/j.issn.1001-3806.2010.06.020

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Recognition of alcohol-free beer by fluorescent spectroscopy and probabilistic neural network

School of Science, Jiangnan University, Wuxi 214122, China

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Received Date: November 24, 2009
Revised Date: January 14, 2010
Published Date: November 24, 2010

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Abstract

In order to identify alcohol-free beer and ordinary beer quickly and accurately,a recognition model of the alcohol-free beer was established,which was based on fluorescent spectroscopy and probabilistic neural network.It was found experimentally that both alcohol-free beer and ordinary beer excited by ultraviolet-visible light could generate strong fluorescence. The fluorescent spectrum for alcohol-free beer is within a range from 420nm to 620nm,its peak wavelength of the fluorescence is about 490nm.The approximate coefficients,obtained by wavelet transform,were used as the network data,and a probabilistic neural network was trained and constructed.The trained probabilistic neural network was employed to recognize sixty beer samples,and the recognition rate was up to 98.33%.The whole research outcomes will provide a new method for recognizing alcohol-free beer.
- spectroscopy,
- alcohol-free beer,
- wavelet transform,
- probabilistic neural network,
- classification and recognition

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