The dawn of intelligent technologies in tea industry

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Wei, Yang;Wen, Yongqi;Huang, Xiaolin;Ma, Peihua;Wang, Li;...

通讯作者：

Wei, XL

作者机构：

[Wang, Li; Wei, Xinlin; Wei, Yang; Pan, Yi; Wen, Yongqi] Shanghai Jiao Tong Univ, Sch Agr & Biol, Dept Food Sci & Technol, 800 Dongchuan Rd, Shanghai 200240, Peoples R China.

[Huang, Xiaolin] Shanghai Jiao Tong Univ, Dept Automat, 800 Dongchuan Rd, Shanghai 200240, Peoples R China.

[Ma, Peihua] Univ Maryland, Coll Agr & Nat Resources, Dept Nutr & Food Sci, College Pk, MD USA.

[Yang, Xiufang; Lv, Yangjun] Hangzhou Tea Res Inst, Zhejiang Key Lab Transboundary Appl Technol Tea Re, CHINA COOP, Hangzhou 310016, Peoples R China.

[Wang, Hongxin] Jiangnan Univ, Sch Food Sci & Technol, Wuxi 214122, Jiangsu, Peoples R China.

通讯机构：

[Wei, XL ] 8

800 Dongchuan Rd, Shanghai 201100, Peoples R China.

语种：

英文

关键词：

Tea industry;Quality assessment;Intelligent technologies;Machine learning;Computer vision;Application

期刊：

Trends in Food Science & Technology

ISSN：

0924-2244

年：

2024

卷：

144

页码：

104337

DOI：

10.1016/j.tifs.2024.104337

基金类别：

National Key R & D Program of China [2022YFD2101104]

机构署名：

本校为其他机构

院系归属：

园艺园林学院

摘要：

Background: Tea is a globally significant agricultural product, renowned for its economic and cultural value. The process of tea cultivation and production involves tea plantation management, disease control, harvesting, processing, sorting and safety and quality assessment. The quality of tea can be affected by many factors, involving variety, environment, picking and processing. Nevertheless, quality assessment of tea often relies on manual experience and specialized knowledge, which is accompanied by subjectivity and inconsistency. Furthermore, the tea production process also faces several ...

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