The employment of real-time polymerase chain reaction for analysis of canine meat in meatball products for halal authentication analysis
Keywords:
Canine meat; meatball; speciesspecific primers; real-time PCR; halal certification.Abstract
Objective: Meatballs are a popular meat-based food consumed widely in Indonesian society. However, the issue of unethical substitution of halal meatballs with non-halal meats, particularly pork and canine meat (CM), has emerged. The existence of non-halal meats, including CM, in food products is prohibited in Islam, necessitating the development of reliable analytical techniques for their identification. In this study, we designed species-specific primers (SSPs) targeting the D-loop region of mitochondrial DNA for CM meatball product identification.
Materials and Methods: The study was commenced by creating specific primers for canine DNA using Integrated DNA Technologies software and subsequently performing DNA isolation. The designed primers were then subjected to comprehensive evaluation using RT-PCR, including specification, linearity, limit of detection, efficiency, and repeatability.
Results: The results indicated that the primer D-Loop 443 (forward: 5’-GGG ACA TCT CGA TGG ACTA ATG-3’, reverse: 5’-GCG GTC ATA GAT GAG TGA TAG C-3’) designed and validated in silico using primer-basic local alignment search tool nucleotide (BLAST) program from NCBI accurately identified canine DNA when the optimal annealing temperature was set at 57.5oC. The real-time PCR technique utilizing the D-loop 443 primer exhibited the ability to amplify canine DNA down to a minimum quantity of 100 pg, with an efficiency value of 91.8%, a correlation coefficient (R) of 0.990, and a precision value (RSD) of 0.30%.
Conclusion: The SSP-based RT-PCR method developed is a versatile and efficient tool for detecting CM in meatballs. Its implementation helps maintain consumer trust and addresses concerns regarding the substitution of halal meats with non-halal alternatives.
Adv. Vet. Anim. Res., 11(2): 247-253, June 2024
Downloads
30
30
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Rumiyati Rumiyati, Rien Larasati Arini, Purwanto Purwanto, Abdul Rohman
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
