A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food.
Meat adulteration is a worldwide concern. In this paper, a new droplet digital PCR (ddPCR) method was developed for the quantitative determination of the presence of chicken in sheep and goat meat products. Meanwhile, a constant (multiplication factor) was introduced to transform the ratio of copy numbers to the proportion of meats. The presented ddPCR method was also proved to be more accurate (showing bias of less than 9% in the range from 5% to 80%) than real-time PCR, which has been widely used in this determination. The method exhibited good repeatability and stability in different thermal treatments and at ultra-high pressure. The relative standard deviation (RSD) values of 5% chicken content was less than 5.4% for ultra-high pressure or heat treatment. Moreover, we confirmed that different parts of meat had no effect on quantification accuracy of the ddPCR method. In contrast to real-time PCR, we examined the performance of ddPCR as a more precise, sensitive and stable analytical strategy to overcome potential problems of discrepancies in amplification efficiency discrepancy and to obtain the copy numbers directly without standard curves. The method and strategy developed in this study can be applied to quantify the presence and to confirm the absence of adulterants not only to sheep but also to other kinds of meat and meat products.
College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China.|Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, Beijing, China.
Junan
J
Ren
College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China.|Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, Beijing, China.
Tingting
T
Deng
Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, Beijing, China.
Wensheng
W
Huang
Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, Beijing, China.
Ying
Y
Chen
College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China.|China Rural Technology Development Center, Beijing, China.
Yiqiang
Y
Ge
D000818:Animals; D001717:Birds / Q000235:genetics; D005506:Food Contamination / Q000032:analysis*; D005511:Food Handling / Q000379:methods; D016014:Linear Models; D008322:Mammals / Q000235:genetics; D008461:Meat Products / Q000032:analysis*; D060888:Real-Time Polymerase Chain Reaction / Q000379:methods*; D051716:Replication Protein A / Q000235:genetics; D015203:Reproducibility of Results
D051716:Replication Protein A