清脆的
鉴定(生物学)
计算机科学
质量(理念)
食品安全
生化工程
食品科学
生物
工程类
物理
生物化学
植物
量子力学
基因
作者
Yaqun Liu,Liyun Lin,Huagui Wei,Qiulan Luo,Peikui Yang,Mouquan Liu,Zhonghe Wang,Xianghui Zou,Hui Zhu,Guangcai Zha,Junjun Sun,Yuzhong Zheng,Min Lin
标识
DOI:10.1016/j.crfs.2023.100609
摘要
In recent years, meat adulteration safety incidents have occurred frequently, triggering widespread attention and discussion. Although there are a variety of meat quality identification methods, conventional assays require high standards for personnel and experimental conditions and are not suitable for on-site testing. Therefore, there is an urgent need for a rapid, sensitive, high specificity and high sensitivity on-site meat detection method. This study is the first to apply RPA combined with CRISPR/Cas12a technology to the field of multiple meat identification. The system developed by parameter optimization can achieve specific detection of chicken, duck, beef, pork and lamb with a minimum target sequence copy number as low as 1 × 100 copies/μL for 60 min at a constant temperature. LFD test results can be directly observed with the naked eye, with the characteristics of fast, portable and simple operation, which is extremely in line with current needs. In conclusion, the meat identification RPA-CRISPR/Cas12a-LFD system established in this study has shown promising applications in the field of meat detection, with a profound impact on meat quality, and provides a model for other food safety control programs.
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