Work

Scenario-based risk estimation using a newly developed predictive model for Vibrio parahaemolyticus in fresh flounder

Year: 2026

Type: article

Abstract: In this study, we developed a predictive growth model for Vibrio parahaemolyticus in fresh flounder using strains with higher growth potential than existing V. parahaemolyticus flounder models. Growth data were fitted to the Baranyi and second-order polynomial models, both showing high predictive performance. The secondary models yielded coefficients of determination (R2) ranging from 0.977 to 0.992 for individual strains in tryptic soy broth (TSB) and 0.997 for the cocktail in fresh flounder. Validation metrics indicated acceptable fit, with bias factors of 0.974–1.132 in TSB and 0.969 in flounder, and accuracy factors of 1.038–1.169 and 1.047, repectively. The models were validated under simulated fluctuating temperature profiles, confirming their high predictive performance. Monte Carlo simulations were employed to compare the risk of vibriosis from ready-to-eat flounder consumption across three seasonal scenarios (baseline, summer, and winter). The probabilities of infection estimated by the model developed in this study were consistently higher than those estimated by previous models across all scenarios. These findings highlight the critical importance of stringent temperature management throughout seafood distribution. The developed model provides a realistic and protective tool for microbial risk assessment and seafood safety management.

Source: LWT

DOI: 10.1016/j.lwt.2026.119366

Authors: Soo Min Park, Jin Hwa Park, Seok In Hong, Hyun Jung Kim

Institutions: Korea Food Research Institute, Korea University of Science and Technology

Language: English

Topic: Vibrio bacteria research studies

Subfield: Endocrinology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDGs: Life below water, Zero hunger

Open Access status: gold

Estimated APC paid: $3,240