• Spectroscopy and Spectral Analysis
  • Vol. 38, Issue 8, 2511 (2018)
GU Jiao1、2, CHEN Guo-qing1、2, ZHANG Xiao-he1、2, LIU Huai-bo1、2, MA Chao-qun1、2, ZHU Chun1、2, and LIAO Cui-cui1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2018)08-2511-05 Cite this Article
    GU Jiao, CHEN Guo-qing, ZHANG Xiao-he, LIU Huai-bo, MA Chao-qun, ZHU Chun, LIAO Cui-cui. Classification and Year Prediction of Chinese Liquors Based on Wavelet Decomposition and Factor Analysis[J]. Spectroscopy and Spectral Analysis, 2018, 38(8): 2511 Copy Citation Text show less

    Abstract

    In this paper, a method to identify the flavor and year of Chinese liquors was proposed based on continuous wavelet decomposition and factor model on analyzing the fluorescence spectra of liquor. The three-dimensional fluorescence spectrum of liquor contained the information of the fluorescent substance, and its decomposition factor was related to the intensity of the characteristic peak. The decomposition of the three-dimensional fluorescence spectrum by Gaussian wavelet can avoid the problem of selecting the specific excitation wavelength when decomposing the two-dimensional fluorescence spectrum. After the wavelet decomposition of the three-dimensional fluorescence spectrum of the sample, the orthogonal factor model was constructed by the fourth layer approximation coefficient, and the liquor was discriminated by the factor loading. The results showed that the factors with small contribution contain unique information of the sample, which can not be neglected in the comparison of similar samples. In the classification of liquor flavor, the three-dimensional fluorescence spectra of the samples were decomposed by Gaussian wavelet, and the fourth-layer approximation coefficients were used for factor analysis to obtain multiple factors with large and small contribution rates. According to the factor of the factor loading, the cluster analysis was carried out. The results showed that the factor with a small contribution rate can increase the correct rate to 90%. By analyzing the correlation between the factor loading and the year of liquors, the contribution rate of the first six factors was larger than that of the liquor, and the correlation between the factors and the year of liquor was small, so the first six factor can be used to predict the year of Chinese liquors. By selecting the factors with different contribution rates to predict the year of liquor, the average error can be reduced to 0.9 years.
    GU Jiao, CHEN Guo-qing, ZHANG Xiao-he, LIU Huai-bo, MA Chao-qun, ZHU Chun, LIAO Cui-cui. Classification and Year Prediction of Chinese Liquors Based on Wavelet Decomposition and Factor Analysis[J]. Spectroscopy and Spectral Analysis, 2018, 38(8): 2511
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