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Current progress on meat food authenticity detection methods

delete2023-10-01
delete19
PRE
AI
J
Junhua Du
M
Mailin Gan
Z
Zhongwei Xie
C
Chengpeng Zhou
M
Menglin Li
M
Meng Wang
H
Haodong Dai
Z
Zhiyang Huang
L
Lei Chen
Y
Ye Zhao
牛丽莉 封面图
牛丽莉 (Lili Niu)
S
Shunhua Zhang
Z
Zongyi Guo
王
王金勇 (Jinyong Wang)
X
Xuewei Li
沈林園 封面图
沈林園 (Linyuan Shen)
朱砺 封面图
朱砺 (Li Zhu) *
DOI:10.1016/j.foodcont.2023.109842delete
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摘要

摘要

En 中文
Meat adulteration could be intentional or unintentional, which may infringe consumers' rights and interests, endanger public health, disrupt the market, and hinder the development of the meat industry. Determining fast and efficient meat adulteration detection methods is therefore critical for the development of the food industry and the safety of consumers. Based on the classification of target substances, adulteration detection technologies are classified in protein-, metabolite-, or nucleic acids-based. Although these detection techniques have yielded good identification results when applied to meat adulteration detection, certain shortcomings are still observed. This review aims to summarize the latest progress on meat adulteration detection technologies, thus providing a reference basis for food safety and surveillance departments and researchers within this field.
Keyword:
Meat
Adulteration detection
Detection technology

期刊

Food Control 封面图
Food Control
IF:
6.3
论文数:
1.2W
被引数:
4.0W

机构

S
Sichuan Agricultural University
学者数:
2.3W
论文数: 9.5K
被引数: 1.4W
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