Linking fermentation and drying kinetics to Listeria monocytogenes inactivation in salami: A dynamic process monitoring approach.

Dry fermented sausages (DFS) rely on fermentation and drying to control pathogens; however, these processes are dynamic, and the relationship between changing process conditions and pathogen inactivation remains poorly characterized. This study evaluated starter culture-dependent differences in Listeria monocytogenes inactivation during DFS fermentation and developed predictive models linking dynamic process conditions to pathogen reduction. Three commercial starter cultures were compared using fermentation pH kinetics and primary inactivation modeling. During fermentation and drying, 4969 real-time pH measurements and 186 L. monocytogenes and water activity (aw) measurements were collected. Random forest analysis identified aw, pH, and Relative humidity (RH) as the most influential process variables associated with pathogen reduction. Secondary models incorporating continuously changing pH and aw conditions were then developed. The estimated Dr-value of 14.3 h for Listeria monocytogenes in salami from the model using dynamic pH and aw data was significantly greater (P < 0.05) than the Dr-value of 29.66 h from the model using dynamic pH only. These results suggested that the combined pH + aw model better capture the hurdle effects. These findings demonstrate that integrating real-time fermentation and drying data with pathogen reduction measurements improves L. monocytogenes inactivation model interpretability for DFS processing and provides a framework for process validation and quantitative microbial risk assessment (QMRA) applications.