Food and Fermentation Industries >

2022 , Vol. 48 >Issue 4: 255 - 260

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.027968

Hyperspectral detection method for the acidity detection of Baijiu fermented grains

  • JU Jie ,
  • TIAN Jianping ,
  • HU Xinjun ,
  • HUANG Dan ,
  • HUANG Haoping ,
  • PENG Xinghui ,
  • LUO Huibo
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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(Liquor Making Biotechnology and Application Key Laboratory of Sichuan Province, Yibin 644000, China)

Received date: 2021-05-18

  Revised date: 2021-09-23

  Online published: 2022-03-16

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Abstract

Acidity value is one of the important indexes to evaluate the quality of fermented grains. In order to further improve the detection accuracy of the acidity value of fermented grains, a hyperspectral imaging method has been proposed to detect the acidity value of fermented grains. A hyperspectral imaging system was used to collect the spectral information of fermented grains samples in the range of 900-1 700 nm and the average spectral data of all samples was extracted. Multiple scattering correction (MSC) was identified as the best pretreatment method of three tested pretreatment methods. On the basis of ensuring the detection accuracy and improving the detection efficiency, the competitive adaptive reweighted sampling (CARS) algorithm adopted to select feature bands was developed as the optimization method, and the PLSR and LS-SVM prediction models were established. The results showed that the LS-SVM prediction model, based on 38 characteristic wavelengths selected by CARS algorithm presented good prediction effect. The correlation coefficient of the prediction set R2p was 0.961 8, and the root mean square error of the prediction set was 0.058 0 g/kg. The results indicated that hyperspectral imaging had better accuracy than other techniques in detecting the acidity of fermented grains. At the same time, an effective way to detect the content of other ingredients in liquor process was explored.

Key words： fermented grains; hyperspectral imaging; acidity value; rapid detection; modeling algorithm

Cite this article

JU Jie , TIAN Jianping , HU Xinjun , HUANG Dan , HUANG Haoping , PENG Xinghui , LUO Huibo . Hyperspectral detection method for the acidity detection of Baijiu fermented grains[J]. Food and Fermentation Industries, 2022 , 48(4) : 255 -260 . DOI: 10.13995/j.cnki.11-1802/ts.027968

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