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The objective of this study is to stochastically assess the inactivation probabilities of four common foodborne pathogens ( Listeria ,  Salmonella ,  Escherichia coli , and  Campylobacter ) in chicken meat during ohmic heating (OH) in a salt solution. A mechanistic model was used to accomplish this, coupling heat transfer, laminar fluid flow, and the electric field, and solved numerically using COMSOL Multiphysics ®  v5.6. The 3D model represented 1000 particles randomly placed on the meat’s surface to determine the 7-log reduction of bacterial load probability. These particles are virtual representatives of bacterial colonies in the model. The influence of uncertain input parameters (specific heat capacity and electrical conductivity) and OH conditions (salt concentration of the heating medium, applied voltage, and heating time) was explained using logistic regression. The same analysis was repeated for the slowest heating point of chicken meat, as well. According to the findings, cold spots are observed at the corners of the meat piece during OH, requiring additional attention to the meat surface temperature to prevent under-processing. Sensitivity analysis revealed that the applied voltage and brine concentration are the main factors affecting the inactivation probabilities of pathogenic bacterial cells on the chicken meat surface.  Salmonella  and  Listeria  may require higher electrical conductivity of chicken meat and longer processing times. The developed model enables predicting inactivation probabilities of microorganisms that can be found on the outer surface by measuring the core temperature of the meat. However, especially for bacteria with higher heat resistance, it is better to consider the cold spot temperature found in the corners of the food material during OH.

Stochastic inactivation evaluation of foodborne pathogens during ohmic heating of poultry meat