食品安全
业务
鉴定(生物学)
肉类包装业
风险分析(工程)
食品工业
生物技术
计算机科学
食品科学
生物
植物
作者
Junhua Du,Mailin Gan,Zhongwei Xie,Chengpeng Zhou,Menglin Li,Meng Wang,Haodong Dai,Zhiyang Huang,Lei Chen,Ye Zhao,Lili Niu,Shunhua Zhang,Zongyi Guo,Jinyong Wang,Xuewei Li,Linyuan Shen,Li Zhu
出处
期刊:Food Control
[Elsevier]
日期:2023-05-04
卷期号:152: 109842-109842
被引量:23
标识
DOI:10.1016/j.foodcont.2023.109842
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI