Back to Search
Start Over
Bacteriological evaluation and advanced SYBR-green multiplex real-time PCR assay for detection of minced meat adulteration.
- Source :
- Open Veterinary Journal; 2024, Vol. 14 Issue 1, p389-397, 9p
- Publication Year :
- 2024
-
Abstract
- Background: Minced meat is a valuable source of nutrients, but it is vulnerable to contamination by microorganisms commonly present in the environment. In addition, there is a risk of adulteration with cheaper meat sources, which can be harmful to consumers. Aim: It is crucial to identify meat adulteration with distinct microbiological analysis for legal, economic, religious, and public health purposes. Methods: A total of 100 minced meat samples were collected from several markets in Sharkia Governorate, Egypt. These samples were then subjected to bacteriological testing and an advanced multiplex PCR method. This method enables the detection of bovine, equine, porcine, and dog species in meat samples with just one step. Results: The adulterated samples had a higher total bacterial count and pH values compared to pure bovine meat. These differences in bacterial count and pH values were statistically significant, with p-values of 0.843 (log<subscript>10</subscript>) and 0.233, respectively. The frequency of Escherichia coli occurrence was 13%, and the O111 serotype was predominant in the adulterated samples. Listeria monocytogenes and Staphylococcus aureus were isolated with prevalence rates of 3% and 29%, respectively. Besides, the SYBR-green multiplex real-time PCR assay used in this study detected adulteration with dog, equine, and porcine meats in the examined samples at rates of 9%, 5%, and 4%, respectively. Conclusion: This method provides a sensitive and specific approach to detect issues related to well-being and safety. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22264485
- Volume :
- 14
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Open Veterinary Journal
- Publication Type :
- Academic Journal
- Accession number :
- 175731383
- Full Text :
- https://doi.org/10.5455/OVJ.2024.v14.i1.35