Characterization and optimization of continuous ohmic thermal sterilization based on the development of a predictive computational toolbox

Continuous thermal processing (CTP) is a common method for sterilizing food. However, it can result in an uneven temperature distribution, which can lead to a varying degree of processing intensity. Ohmic heating (OH) can be advantageous in this regard, as it enables volumetric heating for more homogenous treatments. However, evaluating the processing intensity distribution inside the equipment for OH is challenging due to the complex interaction between electrical, mechanical and thermal phenomena. Furthermore, the comparison of OH and conventional heating treatments often lack a profound basis of comparable treatment intensity considerations. To gain a deeper mechanistic understanding of the technology, a numerical computational fluid dynamics model for the OH sterilization of a clear carrot juice from the heating region to the cooling process was developed. The model was validated with thermal and electrical measurements and showed an error rate below 2.5% in its prediction capacities. Moreover, the model was implanted for the validation of the products sterilization and compared to a conventional validation approach, reviling a 33.3% underestimation of the thermal load by conventional manners, which can lead to faulty sterilization of the food product. Additionally, the model was expanded to also be able to predict the microbial inactivation ratio of the system with an average error of $1.10\pm 0.74\%$. In addition, results indicate that the numerical calculation of the F₀ values and their validation with the microbial inactivation ratio have a notable potential for localization and evaluation of hotspots in OH simulations. Therefore, it can be seen as a promising step for establishing a foundation for computer-assisted optimization of CTP and targeted processing.