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DNA Barcoding: A Tool To Deect Fraud In Seafood Products

Author

Listed:
  • Diyana Tarmizi

    (Department of Biotechnology, Kulliyyah of Science, International Islamic University Malaysia, Jalan Sultan Ahmad Shah, Bandar Indera Mahkota, 25200 Kuantan, Pahang, Malaysia)

  • Zarina Zainuddin

    (Department of Plant Science, Kulliyyah of Science, International Islamic University Malaysia, Jalan Sultan Ahmad Shah, Bandar Indera Mahkota,25200 Kuantan, Pahang, Malaysia)

Abstract

Fraud of seafood products is a serious issue in global market. Fraud occurs when there is misnaming or mislabelling of species due to several reasons like different vernacular name in different regions for same species or same vernacular name is being used for different species, unintentional mislabeling and substitution to less expensive fish. DNA barcoding can be a tool to identify species correctly and to detect seafood fraud. The main purpose of this study is to investigate the effectiveness of DNA barcoding in identifying a variety of seafood products commercially marketed in Malaysia. Six samples of seafood product which were Pacific dory frosty fillet, pectoral fins for steak of ‘tenggiri’, battered pollock fillet, battered with breaded cod finger fish, canned sardine, and salmon sushi were purchased at various seafood outlets. Using Qiagen DNeasy® Blood and Tissue DNA Extraction Kit genomic DNA was successfully extracted from all samples. Successful amplification of 16S rDNA for processed food and COI gene for the remaining samples with the right size of band was achieved using Polymerase Chain Reaction (PCR). Results of sequencing of the amplified sequences only manage to identify three samples namely battered pollock fillet, salmon sushi and canned sardine and the names given tally with the labels. Thus, it can be said that DNA barcoding is a reliable tool that can be used to detect fraud in seafood product.

Suggested Citation

  • Diyana Tarmizi & Zarina Zainuddin, 2020. "DNA Barcoding: A Tool To Deect Fraud In Seafood Products," Big Data In Agriculture (BDA), Zibeline International Publishing, vol. 2(1), pages 20-22:2, March.
  • Handle: RePEc:zib:zbnbda:v:2:y:2020:i:1:p:20-22
    DOI: 10.26480/bda.01.2020.20.22
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