Detection of goat meat adulteration by real-time PCR based on a reference primer

• Published in: Food chemistry Vol. 277; pp. 554 - 557
• Main Authors: Li, Ting Ting, Jalbani, Yar Muhammad, Zhang, Gui Lan, Zhao, Zhi Yong, Wang, Zhi Ying, Zhao, Xiao Yan, Chen, Ai Liang
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 30.03.2019
• Subjects: adulterated products; Adulteration; Animals; Calibration; Evaluation Studies as Topic; False-negative; False-positive; Food Contamination - analysis; food safety; Goat meat; Goats; packaging; pork; quantitative analysis; quantitative polymerase chain reaction; Real-time PCR; Real-Time Polymerase Chain Reaction; Red Meat - analysis; Swine; Goat meat; Real-time PCR; Adulteration; False-positive; False-negative
• ISSN: 0308-8146; 1873-7072; 1873-7072
• DOI: 10.1016/j.foodchem.2018.11.009

•The novel method was developed for the quantitative determination of goat meat adulteration.•This method can avoid the false negative and false positive.•The study with a good linear correlation (R2 = 0.9929) and the average recovery of simulation samples as 108.74%. Economically motivated adulteration (EMA) has become one of the most concerned food safety issues. However, existing mainstream PCR methods could neither achieve qualitative detection purposes, nor detect all possible meat species involved in adulteration. When meat has been adulterated with unidentified species but the result indicates no adulteration, it is a false negative; when meat has not been adulterated deliberately but has somehow been polluted during its processing or packaging, a false positive emerges. A novel reference primer based real-time PCR approach was developed in this study for quantitative determination of goat meat adulterated with pork. By calculating the ratio of Ct (specificity/reference), a good linear correlation (R2 = 0.9929) could be deduced for the goat meat content. We also successfully amplified simulated samples and the results showed high accuracy with an average recovery of 108.74% for the samples.