Date of Award

Spring 5-2024

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Food Science

First Advisor

Dr. Rosalee Hellberg

Second Advisor

Dr. Christina Ann DeWitt

Third Advisor

Dr. Lilian Were Senger

Abstract

Seafood is vulnerable to species mislabeling due to factors such as complex global supply chains, varying prices, and similar appearance of species. Numerous studies have been published reporting a range of mislabeling rates for various forms of seafood. However, these studies oftentimes focus on lesser-consumed species that are vulnerable to species mislabeling. As a result, the overall mislabeling rate of commercially sold seafood in the U.S. remains unknown, especially for the most consumed species. Thus, the objective of the current study was to compile the results of seafood mislabeling studies into a single resource to provide informative statistics on U.S. seafood mislabeling. A meta-analysis was conducted on U.S. seafood mislabeling studies from peer-reviewed and informal articles that tested commercial samples from 2010 or later. Articles were found using a combination of Google, Google Scholar, the Web of Science, cited references, and the Google Scholar “cited by” function. A total of 33 studies, including 4,101 samples from 33 U.S. states, were analyzed, revealing an overall mislabeling rate of 39.4%. The leading form of mislabeling was species substitution (26.2%), followed by unacceptable market names (17.1%) and conflicting market names (1.3%). The overall mislabeling rate for the top 10 consumed seafoods in the U.S. was 31%, compared to 53% for the most frequently investigated species. On average, 14% of the top 10 consumed seafoods were substituted on the basis of species compared to 43% of frequently investigated species. The results of this investigation provide comprehensive information on the mislabeling rates of seafood sold in the U.S., with the potential to influence policy decisions and improve public trust in the seafood industry.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Available for download on Friday, May 08, 2026

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