Quantitative Analysis of Pork Adulteration in Beef by Double Antibody Sandwich Enzyme‐Linked Immunosorbent Assay Combined With Mathematical Models
Adulterating pork into other meat is a global concern, and efficient methods for identifying meat species are of prime importance in quality assurance and regulation. Enzyme‐linked immunosorbent assay (ELISA) is one of the most widely used methodologies for porcine speciation. Thermostable proteins were used as suitable marker proteins for species identification in heat‐processed or commercial meat products. However, the continuous pursuit of higher sensitivity narrowed the analytical range of quantitation (ROQ) resulting in reduced resolution. In our study, murine monoclonal antibodies (sTn‐4C10 and sTn‐4B1‐HRP) which are specific to skeletal muscle troponin were used as capture antibodies and detection antibodies in a double antibody sandwich ELISA (DAS–ELISA) to measure the percentage of pork in beef. When the optimal loading concentrations of sTn‐4C10, sTn‐4B1‐HRP, and adulterated samples were set as 2, 0.2, and 20 μg/mL, respectively, this DAS–ELISA assay combined with the optimal mathematical model had an analytical ROQ of 5.79%–91.33% ( w / w ) in the absence of beef. The recovery rates ranged from 96% to 100%, and the coefficient of variation was below 4.5% within the ROQ. This work has widened the analytical ROQ and improved the detection resolution.
Authors
- Hejie Li (ORCID: https://orcid.org/0000-0002-4851-7194)
- Yujing Li
- Yan Zhang (ORCID: https://orcid.org/0000-0002-2947-1629)
- Jingjing Liu (ORCID: https://orcid.org/0000-0002-2933-9644)
- Chunsheng Li (ORCID: https://orcid.org/0000-0002-0422-0196)
- Jing Zhang (ORCID: https://orcid.org/0000-0003-1637-5336)
Institutions
- Hebei Food Inspection and Research Institute (CN)
- Hebei Academy of Sciences (CN)
Publication Details
- Journal
- Journal of Food Quality
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1155/jfq/6363488
- Citations
- 3
- Primary Topic
- Identification and Quantification in Food
- Type
- article
- Field-Weighted Citation Impact
- 2.42
Funders
- Hebei Normal University