Combined effect of lysozyme and nisin at different incubation temperature and mild heat treatment on the probability of time to growth of Bacillus cereus

Stochastic models can be useful to predict the risk of foodborne illness. The presence of Bacillus cereus in liquid egg can pose a serious hazard to the food industry, since a mild heat treatment cannot guarantee its complete inactivation. However, most of the information available in the scientific literature is deterministic, including growth of B. cereus. In this paper, a stochastic approach to evaluate growth of B. cereus cells influenced by different stresses (presence of nisin and lysozyme separately or in combination) was performed, using an individual-based approach of growth through OD measurements. Lag phase duration was derived from the growth curves obtained. From results obtained, histograms of the lag phase were generated and distributions were fitted. Normal and Weibull distributions were ranked as the bestfit distributions in experiments performed at 25 °C. At 16 °C, lag values (obtained in presence of combinations of both antimicrobials) were also fitted by a Gamma distribution. Predictions were compared with growth curves obtained in liquid egg exposed to mild heat, nisin and/or lysozyme to assess their validity.