Food and Fermentation Industries >

2022 , Vol. 48 >Issue 7: 85 - 90

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.028164

An online method for predicting acidity value,water and starch content in fermented grains of light-flavor Baijiu

  • WANG Kun ,
  • TUO Xianguo ,
  • ZHANG Guiyu ,
  • LUO Lin ,
  • LUO Qi ,
  • LIU Jie
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  • 1(Artificial Intelligence Key Laboratory of Sichuan Province,Sichuan University of Science ＆ Engineering,Yibin 644000,China)
    2(School of Automation＆Information Engineering,Sichuan University of Science ＆ Engineering,Yibin 644000,China)
    3(School of Information Engineering,Southwest University of Science and Technology,Mianyang 621010,China)

Received date: 2021-06-01

  Revised date: 2021-08-17

  Online published: 2022-04-27

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Abstract

The current inspection of acidity value,water and starch content of fermented grains can only be performed offline through chemical methods, which are very complex with heavy workload. Through the research on the fermentation mechanism, the oxygen, carbon dioxide, humidity and temperature generated during the fermentation process were collected as the monitoring indicators, and an automated system to collect fermentation parameters was established with the multi-sensor monitoring technology by the wireless communication network. At the same time, chemical methods are used to detect three indicators of the fermented-grain samples, namely, moisture, acidity value and starch content. With oxygen, carbon dioxide, humidity and temperature values of the fermentation environment as independent variables, and with the moisture, acidity value and starch content as dependent variables, a partial least squares soft-sensing model was established, and a multi-element linear regression model was established for comparison. The result of comparison confirmed that partial least squares regression was the best. The root mean square error of the model was 1.89, 0.12, 1.93, and it was concluded that the influence from oxygen and carbon dioxide on the acid value and starch content was extremely critical, followed by temperature and humidity.

Key words： Baijiu; fermentation model; partial least squares regression; multi-element linear regression; soft measurement model

Cite this article

WANG Kun , TUO Xianguo , ZHANG Guiyu , LUO Lin , LUO Qi , LIU Jie . An online method for predicting acidity value,water and starch content in fermented grains of light-flavor Baijiu[J]. Food and Fermentation Industries, 2022 , 48(7) : 85 -90 . DOI: 10.13995/j.cnki.11-1802/ts.028164

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