Study on Recognition of the True or False Red Wine Based on Visible-Near Infrared Spectroscopy
GUO Hai-xia1, WANG Tao1, LIU Yang1, WU Hai-yun1, ZUO Yue-ming1*, SONG Hai-yan1, HE Jin-yu2
1. College of Engineering, Shanxi Agricultural University, Taigu 030801, China 2. Pomology Institute, Shanxi Academy of Agricultural Sciences, Taigu 030815, China
Abstract：This study selected 90 samples from different brands of red wine. In order to eliminate the impact of spectral curve’s baseline, the first derivatives of all of spectral curves were calculated and the principal component analysis was carried out on the first derivative spectra. The result showed that the contribution rate of the first two principal components was over 80 percent. By the first two principal components, all the red wine samples were obviously divided into two classes. Furthermore a 3-layer artificial neural network predictive model was built with the first four principal components as input variables and 100 percent correct prediction rate was gained. The research showed that the visible-near infrared spectroscopy combined with principal component analysis provides an accurate and reliable new method to rapidly and nondestructively recognize the true or false red wines.
Key words：Red wine;Visible-near infrared spectroscopy;BP neural network;Ture or false;Recognition
郭海霞1，王 涛1，刘 洋1，吴海云1，左月明1*，宋海燕1，贺晋瑜2 . 基于可见-近红外光谱技术的葡萄酒真伪鉴别的研究[J]. 光谱学与光谱分析, 2011, 31(12): 3269-3272.
GUO Hai-xia1, WANG Tao1, LIU Yang1, WU Hai-yun1, ZUO Yue-ming1*, SONG Hai-yan1, HE Jin-yu2 . Study on Recognition of the True or False Red Wine Based on Visible-Near Infrared Spectroscopy . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31(12): 3269-3272.
