Development and Validation of a Rapid RPA-PfAgo-Based Meat Species Identification System
2025
Yaqun Liu | Lianghui Chen | Jialin Wang | Nantao Lin | Kang Zhang | Peikui Yang | Yicun Chen | Chengsong Xie | Min Lin | Zhenxia Zhang | Yuzhong Zheng
This study presents a novel detection system combining recombinase polymerase amplification (RPA) with the Argonaute protein from Pyrococcus furiosus (PfAgo) for accurate identification of meat species. The RPA-PfAgo method provides a rapid, sensitive, and specific approach for detecting duck, chicken, beef, pork, and mutton, addressing challenges in food fraud and regulatory compliance. Systematic optimization of key parameters ensures high specificity and sensitivity, with validation against commercial and adulterated samples. This method offers a practical solution for onsite testing, supporting transparency in the food supply chain.
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