摘要
食品风味对于感官具有重要作用,是消费者偏好和选择的关键因素,因此风味分析方法非常重要。传统的分析方法具有局限性,十分耗时,还无法处理大样本的数据,机器学习的出现将会解决这一难题。机器学习具有分析和处理海量样本、识别高维变量空间中的复杂模式、从已知数据中独立自主学习、基于新数据生成和自动优化算法实现预测的能力。机器学习的出现给食品科学领域提供了理解复杂风味特征的新方法。本文综述了传统和新型机器学习方法的优缺点,以及与分析仪器电子舌、电子鼻和气相色谱-质谱联用的不同应用场景。此外还综述了机器学习在食品风味分析中的应用。经过研究发现,不同机器学习方法对应了不同食品风味分析的场景,需要根据样本的实际情况,有选择性地使用。机器学习在提高食品质量、安全性和消费者满意度方面具有重大的潜力,多种机器学习模型和分析技术相结合,对食品风味分析将产生重要作用。
Flavor plays a crucial role in the sensory perceptionof food and is a key determinant forconsumer preference and choice.Therefore,flavoranalysismethods are of paramount importance.Traditional methods for flavor analysis have limitations such as time-consuming and unable to handle large sample data.The emergence of machine learning is poised to address these problems.Machine learning possesses the capability to analyze and process vast amounts of data,identify complex patterns in high-dimensional variable spaces,autonomously learn useful information from known data,and automatically generate and optimize algorithms for prediction based on new data.The emergence of machine learning providesa new method for understanding the complex flavor characteristics of food.This articleprovides a comprehensive review of the advantages and disadvantages of traditional and novel machine learning methods as well as their various application scenarios in conjunction with analytical instruments such as electronic tongue,electronic nose,and gas chromatography-mass spectrometry(GC-MS).Additionally,it reviews the application of machine learning in food flavor analysis.Through research,it has been found that different scenarios of food flavor analysis require different machine learning methods.Machine learning holds significant potential for enhancing food quality,safety and consumer satisfaction.The combination of multiple machine learning models and analytical techniques will play a crucial role in food flavor analysis.
作者
沈潇
王海涛
姚凌云
孙敏
王化田
宋诗清
李雪
冯涛
SHEN Xiao;WANG Haitao;YAO Lingyun;SUN Min;WANG Huatian;SONG Shiqing;LI Xue;FENG Tao(School of Perfume and Aroma Technology,Shanghai Institute of Technology,Shanghai 201418,China;School of Health Science and Engineering,University of Shanghai for Science and Technology,Shanghai200093,China)
出处
《食品科学》
EI
CAS
CSCD
北大核心
2024年第12期31-41,共11页
Food Science
关键词
机器学习
食品风味
风味感知
质量控制
感官分析
成分优化
machine learning
food flavor
flavor perception
quality control
sensory analysis
composition optimization
