Comparison of PCR Techniques in Adulteration Identification of Dairy Products

Baiyi Li, Mingxue Yu, Weiping Xu, Lu Chen () and Juan Han ()
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Baiyi Li: Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
Mingxue Yu: Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
Weiping Xu: Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
Lu Chen: Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
Juan Han: Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081, China

Agriculture, 2023, vol. 13, issue 7, 1-12

Abstract: Economic profit-driven food adulteration has become widespread in the dairy industry. One of the most common forms of dairy adulteration is the substitution of low-priced milk for high-priced milk. This has prompted regulatory authorities to focus on various means of authenticity testing. So far, many methods have been developed. Since milk adulteration has been upgraded, which has forced the testing methods to meet the needs of detection, which include DNA-based PCR methods. PCR and PCR-derived methods exhibit multiple advantages for authenticity testing, such as high stability, fast speed, and high efficiency, which meet the needs of modern testing. Therefore, it is important to develop rapid, reliable, and inexpensive PCR-based assays for dairy adulteration identification. In order to provide perspectives for improving adulteration identification methods, this review first summarizes the DNA extraction methods, then compares the advantages and disadvantages of various PCR authenticity testing methods, and finally proposes the directions for improving dairy product adulteration identification methods.

Keywords: PCR; adulteration identification method; dairy products; quality control; food fraud (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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