机器学习算法在预测茉莉花茶风味品质中的应用  

Application of Machine Learning Algorithms in Predicting Flavor and Quality of Jasmine Tea

作　　者：黄叶群 周晗林 童秀平 吉伟明[2] 孙意岚 饶建青 温成荣[5] 庞杰[1] HUANG Ye-qun;ZHOU Han-lin;TONG Xiu-ping;JI Wei-ming;SUN Yi-lan;RAO Jian-qing;WEN Cheng-rong;PANG Jie(College of Food Science,Fujian Agriculture and Forestry University,Fuzhou,Fujian 350002,China;School of Computer and Information Sciences,Fujian Agriculture and Forestry University,Fuzhou,Fujian 350002,China;Center for Agroforestry Mega Data Science,Haixia Institute of Science and Technology,Fujian Agriculture and Forestry University,Fuzhou,Fujian 350002,China;Fujian Shunchang Rao’s Baiyu Food Co.,Ltd.,Nanping,Fujian 353200,China;School of Food Science and Technology,Dalian Polytechnic University,Dalian,Liaoning 116038,China)

机构地区：[1]福建农林大学食品科学学院,福建福州350002 [2]福建农林大学计算机与信息学院,福建福州350002 [3]福建农林大学海峡联合研究院农林大数据研究中心,福建福州350002 [4]福建省顺昌县饶氏佰钰食品有限公司,福建南平353200 [5]大连工业大学食品学院,辽宁大连116038

出　　处：《粮油食品科技》2024年第5期142-150,共9页Science and Technology of Cereals,Oils and Foods

基　　金：十四五国家重点研发计划(2022YFD2101102)。

摘　　要：机器学习作为人工智能的一个子领域,因其能够在大量数据中学习模型总结经验的出色能力得到广泛应用。针对茉莉花茶风味品质预测中存在耗时耗力、客观性差、准确率低等问题,引入机器学习算法。机器学习算法作为人工智能和计算机科学的一个分支,利用数据和算法来模拟或实现人类的学习行为,在处理无关信息、提取特征变量、建立校准模型等方面具有强大能力,在食品行业有着广泛的应用。近年来,针对机器学习在茶叶加工中的应用研究报道较多,但有关该技术应用于茉莉花茶风味品质中的报道较少。本文综述了随机森林、支持向量机、卷积神经网络等常用机器学习原理模型及其对茉莉花茶风味品质预测,介绍了当前机器学习模型在其风味品质预测中物理测试、化学指标、微生物和病虫害检测研究等方面的应用,为机器学习在茉莉花茶产业发展中的应用提供参考。As a subfield of artificial intelligence,machine learning has gained widespread application due to its exceptional ability to learn models and summarize experiences from large datasets.To address the issues of time consumption,labor intensity,poor objectivity,and low accuracy in the flavor quality prediction of jasmine tea,machine learning algorithms were introduced.As a branch of artificial intelligence and computer science,machine learning utilizes data and algorithms to simulate or replicate human learning behavior,exhibiting strong capabilities in handling irrelevant information,extracting feature variables,and building calibration models.It has found broad applications in the food industry.In recent years,there have been numerous reports on the application of machine learning in tea processing,but there are relatively few review articles specifically focused on the application of machine learning techniques in predicting the flavor quality of jasmine tea.This paper reviewed the principles of commonly used machine learning models and their application in predicting the flavor quality of jasmine tea.It introduced the application of current machine learning models in the physical testing,chemical indicators,and microbial and pest detection aspects of jasmine tea flavor quality prediction,with the aim of providing a reference for the application of machine learning in the development of the jasmine tea industry.

关 键 词：机器学习 茉莉花茶 预测 风味品质 应用 

分 类 号：TS201.1[轻工技术与工程—食品科学]