Performance assessment of a predictive microbiology framework for Listeria monocytogenes growth in dry-cured fish

The consumption of processed seafood in the European Union has significantly grown, raising food safety concerns, especially for ready to eat products that are consumed without cooking. This growing market interest has driven innovations, including patented fish dry-curing cabinets. Among biological hazards, Listeria monocytogenes is of particular concern in seafood, prompting regulatory scrutiny and the need for predictive modelling to assess its potential growth. This study aims to assess the performance of a model predicting the behavior of L. monocytogenes in vacuum-packed dry-cured fish under dynamic temperature conditions. The fish tested included salmon, swordfish, and tuna, processed following standardized curing and processing methods. A mixture of three L. monocytogenes strains was used for the challenge tests, ensuring a controlled level of contamination. Microbiological and physicochemical parameters, as well as growth dynamics of L. monocytogenes, were measured throughout the shelf life of the products. A dynamic Baranyi model coupled with a secondary cardinal model was employed to simulate the bacterial growth under varying temperature profiles, utilizing established equations to predict microbial behavior. Initial water activity (a w ) and pH values showed stability throughout the study period. L. monocytogenes exhibited growth in salmon and swordfish, while it declined in tuna, probably due to unfavorable a w conditions (0.904 ± 0.010). The model demonstrated good predictive accuracy, with the majority of predictions (88.89% for salmon and 77.22% for swordfish) falling within an acceptable prediction zone. This study provides valuable insights into the growth dynamics of L. monocytogenes in dry-cured fish products. The evaluated predictive model can be applied by seafood producers to assess L. monocytogenes risk and make informed decisions about dry-cured fish products shelf life and storage conditions. • Dry-curing cabinets are developed to meet demands for prolonged shelf-life. • The increase in RTE seafood consumption raises food safety concerns regarding LM. • A predictive model for LM growth was validated under dynamic temperature conditions. • The model predicted the growth of LM with good accuracy. • The model can assist food business operators in assessing LM growth in dry-cured fish.