Application of a DNA Mini-Barcoding System based on the Mitochondrial Control Region for the Identification of Raw and Processed Tuna Products

<p>Accurate species identification methods are needed to combat tuna fraud, improve tuna stock regulation, and mitigate health risks associated with mislabeled tuna products. The objective of this study was to conduct a market survey of raw and processed tuna products using a DNA mini-barcoding system based on the mitochondrial control region (CR). A total of 80 samples of raw, dried, and canned tuna products were collected at the retail level for CR mini-barcoding analysis. The samples underwent DNA extraction, polymerase chain reaction (PCR), and DNA sequencing of the 236-bp CR mini-barcode. The resulting sequences were searched against GenBank using the nucleotide Basic Local Alignment Search Tool (BLAST) to determine the species. The study achieved species identification for 100% of the raw samples, 95% of the dried samples, and 50% of the canned samples for an overall success rate of 82% (n = 69 samples). Mislabeling occurred in 11 of the identified samples (16%), including 8 products (raw, dried, and canned) marketed as yellowfin tuna, 2 samples (dried and canned) labeled as skipjack tuna, and 1 raw fillet sold as bluefin tuna. PCR amplification was successful in all 80 samples, but sequencing was unsuccessful for half of the canned products. The reduced success in canned products may have been due to highly fragmented DNA caused by the canning process and/or the presence of multiple species in these products. Overall, the DNA mini-barcoding system proved to be a promising method in identifying tuna species in both raw and processed samples. Future research should explore optimization of this method for improved identification of canned tuna samples.</p>

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Food Science

Year dc:date.available

2021

Author dc:creator

• Roungchun, Jiahleen

Contributors dc:contributor

• Rosalee Hellberg
• Anuradha Prakash
• Lilian Were

• Food Science

Repository record dc:identifier

https://digitalcommons.chapman.edu/food_science_theses/20

OAI identifier oai:identifier

oai:digitalcommons.chapman.edu:food_science_theses-1020