SCIENCE AND TECHNOLOGY OF CEREALS, OILS AND FOODS

Chinese Science Citation Database (CSCD)
A Guide to the Core Journals of China (2023)
The Key Magazine of China Science and Technology
"2022、2023 Bilingual Communication Project for Chinese STM Journals"
"2022、2024 China Fine Periodical Exhibition"
Elsevier-Scopus Database
Directory of Open Access Journals (DOAJ)
EBSCO Research Database
Chemical Abstracts (CA)
Food Science and Technology Abstract (FSTA)
CAB International (CABI) Database
Japan Science and Technology Agency (Chinese Bibliographic Database) (JSTChina)
Ulrich’s Periodicals Directory (UPD)

Application and Exploration of Starch Rapid Detection in Grain for Winemaking
DOI:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Chinese liquor was made from sorghum, corn, wheat, rice, and glutinous rice with high starch content as raw materials, and was prepared through multiple processes. The amount of starch in the raw material was directly related to the liquor yield. In order to effectively shorten the time for detecting starch content in grain and reduce human error during operation, a fast method for detecting starch content was established. In the sample pre-treatment stage, fast microwave digestion instead of reflux acid hydrolysis is used to speed up starch hydrolysis and improve the completeness of hydrolysis. In the sample detection stage, instrumental detection instead of artificial micro-boiling titration is used which improves the ease of experimental operation. In this paper, the starch content of a variety of brewing grains was tested using the rapid starch detection method, and compared with the results of the national standard method GB 5009.9—2016. There were no significant differences between the results of the two detection methods. The rapid starch detection method can be applied to the detection of total starch content in a variety of brewing grains, greatly shorten the detection time, reduce the artificial operation error, and have good repeatability and reproducibility. The linear regression and correlation coefficient ≥ 0.999 7.

    Reference
    Related
    Cited by
Get Citation
分享
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: September 16,2020
  • Published: