Validation of predictive mathematical models describing the growth of Listeria monocytogenes

Abstract

Growth of Listeria monocytogenes and Listeria innocua in commercially available sterile homogeneous foods was investigated at different temperatures, pH values, and NaCl concentrations. Growth data were fitted to the Gompertz equation and the resulting growth kinetics were compared with predictions from the Pathogen Modeling Program and Food MicroModel. In general, good agreement was obtained when comparing growth rates and generation times for both models. Differences were observed when comparing lag phases, which ranged from 117 h shorter to 4.9 h longer than predicted for L. monocytogenes. Despite differences in lag phase, under most conditions, the models gave good predictions of microbial growth. Predictive modeling appears to be a useful tool in determining growth rates of Listeria in foods.