| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4561777 | Food Research International | 2012 | 7 Pages |
The lethal effect of high pressure on microorganisms is influenced by a number of factors in relation to the technological variables, microorganisms and food matrix, which have to be considered when designing high pressure processes. The present work aimed to develop and validate a model of the inactivation of Salmonella enterica on dry-cured ham by high pressure processing (HPP), as a function of the technological parameters: intensity, length and fluid temperature. Dry-cured ham inoculated with S. enterica was treated at different HPP conditions (at 347 to 852 MPa; for 2.3 to 15.75 min; at 7.6 to 24.4 °C) following a central composite design. Bacterial inactivation was assessed in terms of logarithmic reductions of Salmonella counts on selective media. According to the best fitting and most significant polynomial equation, pressure and time were the most important factors determining the inactivation extent. Temperature showed significant influence through its interaction with both pressure and holding time. The model was validated with results obtained from further experiments within the range of the experimental domain. The accuracy factor and bias factor were within the proposed acceptable values indicating the suitability of the model for predictive purposes, for instance to predict the process criteria to meet the lethality safety standards. The results of this work may help food processors to select optimum processing conditions of HPP to ensure the microbiological safety of pressure-treated foods.
Research highlights► The empirical RSM approach was applied to model the HPP inactivation of Salmonella on dry-cured ham. ► In comparison to other food and beverages, dry-cured ham exerted a baroprotective effect. ► Pressure, holding time and initial fluid temperature showed significant influence on Salmonella HPP-induced inactivation. ► The validation of the polynomial model proved its suitability for predictive purposes. ► Process criteria for cold-pasteurisation to meet the safety standards were estimated.
