食品工业科技2024，Vol.45Issue(13)：360-367,8.DOI:10.13386/j.issn1002-0306.2023070288
机器学习在传统发酵食品微生物结构及品质控制中的应用研究进展
Advances in the Application of Machine Learning to Microbial Structure and Quality Control of Traditional Fermented Foods
摘要
Abstract
The unique flavor properties and rich nutrients of traditional fermented food are closely related to its complex and variable microbial structure,which also makes it difficult to control the quality of final fermented product.In order to explore the changes of microbial structure and sensory property and nutritional property in the process of food fermentation and the internal relationship between them,the data analysis process is a key step.Therefore,it is necessary to establish a fast and accurate data analysis method for quality control of fermented food.Machine learning has the advantages of high-dimensional simplification rate,large data throughput and high prediction accuracy,showing great application potential in the field of quality control of fermented food.Hence,machine learning has become one of the research hotspots.This paper reviews the application of machine learning in the quality control of fermented food.On the basis of an overview of common models of machine learning,this paper systematically summarizes the application of machine learning in the prediction of microbial structure evolution,flavor compound composition analysis and customization of personalized consumption in the process of food fermentation.The problems and developmental trends in the application of machine learning to quality control of traditional fermented food are summarized and prospected.Although the application of machine learning in fermented food is still confined by the problems such as insufficient general applicability of the model,limited quality indicators,and limited personalized consumption scenario,etc.,with the iterative update of the technical model,the adaptation for multi-factors and whole process,and the application expansion in the background of personalized consumption,machine learning will show a greater value for practical application in the field of fermented food.The purpose of this study is to provide guidance for the further application of machine learning in the standardized and controllable production of traditional fermented food.关键词
机器学习/传统发酵食品/数据处理/微生物结构/风味/个性化消费Key words
machine learning/traditional fermented food/data processing/microbial structure/flavor/personalized consumption分类
轻工纺织引用本文复制引用
王宁晓璇,李欣,黄玉立,王雅利,赖海梅,杨梦露,汤臣薇,葛黎红,赵楠..机器学习在传统发酵食品微生物结构及品质控制中的应用研究进展[J].食品工业科技,2024,45(13):360-367,8.基金项目
四川省自然科学基金(2022NSFSC1648) （2022NSFSC1648）
四川省重点研发项目(2022YFN0017,2022YFN0014) （2022YFN0017,2022YFN0014）
四川省农业科学院"1+9"揭榜挂帅项目(1+9KJGG007). （1+9KJGG007）
