A predictive model for the influence of food components on survival of Listeria monocytogenes LM 54004 under high hydrostatic pressure and mild heat conditions

The combination of high hydrostatic pressure with mild temperature was explored to achieve a predictive model of microbial inactivation in food matrix processing. The pressure processing conditions were fixed at 448 MPa for 11 min at the treatment temperature of 41 °C, which have been determined as the optimum processing conditions considering six log-cycle reductions of Listeria monocytogenes. Based on the results, response surface methodology (RSM) was performed in the present work, the influence of food components like soybean protein (0–5.00%), sucrose (0.25–13.25%), bean oil (0–10.00%), and pH (4–10) of the food matrix on survival of L. monocytogenes by high pressure and mild heat was studied, and a quadratic predictive model for the influence of food components and pH of food matrix on L. monocytogenes reduction by high pressure and mild heat was built with RSM accurately. The experimental results showed that the efficiency of L. monocytogenes reduction in milk buffer and food matrix designed in the present work, under the HPP treatment process parameters described above, were different. The soybean protein (P = 0.0086), sucrose (P < 0.0001), and pH (P = 0.0136) significantly affected reduction of L. monocytogenes, but the effect of bean oil on reduction of L. monocytogenes was not significant (P = 0.1028). The predictive model is significant since the level of significance was P < 0.0001 and the calculated F value (11.53) is much greater than the tabulated F value (F0.01 (14, 5) = 9.77). Moreover, the adequacy of the predictive model equation for predicting the level of L. monocytogenes reduction was verified effectively by the validation data.