Food and Fermentation Industries >

2021 , Vol. 47 >Issue 5: 186 - 192

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.025054

Classification of liquor sorghum varieties based on hyperspectral imaging technology

  • SUN Ting ,
  • TIAN Jianping ,
  • HU Xinjun ,
  • LUO Huibo ,
  • HUANG Dan ,
  • HUANG Haoping
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  • 1(College of Mechanical Engineering, Sichuan University of Science & Engineering, Yibin 644000, China)
    2(College of Biotechnology Engineering, Sichuan University of Science & Engineering, Yibin 644000, China)
    3(Sichuan Key Laboratory of Brewing Biotechnology and Application, Yibin 644000, China)

Received date: 2020-07-14

  Revised date: 2020-09-16

  Online published: 2021-03-31

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Abstract

In order to solve the problem in classifying liquor sorghum, and to improve the classification accuracy, a method using hyperspectral imaging technology combined with spectral and image information was proposed. The hyperspectral data of 550 sorghum samples from 11 classes were collected, 48 characteristic wavelengths were selected using the successive projection algorithm from the pre-processed spectrum of multiple scattering correction, and then the gray level co-occurrence matrix were extracted as image feature, the support vector machine (SVM), partial least squares discriminant analysis and extreme learning machine classification models were established using the texture feature, full spectrum, feature spectrum and their combined image feature. Finally, 220 non-participating modeling samples were collected for external verification of the built models. The results showed that SVM model based on the feature spectrum combined with texture feature had the best effect, and the recognition rate of the training set and testing set was 96% and 95.3%, respectively. The recognition rate of the verification set was 91.8%, which was higher than the modeling effect of single spectral data, the effects indicated that the combination of spectral and image information could improve classification recognition rate of liquor sorghum. A feasible method was developed for high-precision classification of sorghum varieties and rapid non-destructive testing of different brewing materials.

Key words： sorghum; hyperspectral; characteristic wavelength; grey level co-occurrence matrix; machine learning

Cite this article

SUN Ting , TIAN Jianping , HU Xinjun , LUO Huibo , HUANG Dan , HUANG Haoping . Classification of liquor sorghum varieties based on hyperspectral imaging technology[J]. Food and Fermentation Industries, 2021 , 47(5) : 186 -192 . DOI: 10.13995/j.cnki.11-1802/ts.025054

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