A 3D-CFD-heat-transfer-based model for the microbial inactivation of pasteurized food products

The Development of a Digital Twin to Improve the Quality and Safety Issues of Cambodian Pâté: The Application of 915 MHz Microwave Cooking

Foodborne diseases are common in Cambodia and developing good food hygiene practices is a mandatory goal. Moreover, developing a low-carbon strategy and energy efficiency is also a priority. This study focuses on pâté cooking, a very common food product in Cambodia. In this paper, the authors chose to develop a digital twin dedicated to perfectly predict the temperature for cooking in a 915 MHz single-mode cavity, instead of using a classical and energy-consuming steaming method. The heating strategy is based on a ramp-up heating and a temperature-holding technique (with Tylose® as the model food and Cambodian pâté). The model developed with COMSOL® Multiphysics software can accurately predict both local temperatures and global moisture losses within the pâté sample (RMSE values of 2.83 and 0.58, respectively). The moisture losses of Cambodian pâté at the end of the process was 28.5% d.b (dry basis) after a ramp-up heating activity ranging from 4 to 80 °C for 1880 s and a temperature-holding phase at 80 °C for 30 min. Overall, the accurate prediction of local temperatures within Cambodian pâté is mainly dependent on the external heat-transfer coefficient during the temperature-holding phase, and is specifically discussed in this study. A 3D model can be used, at present, as a digital twin to improve the temperature homogeneity of modulated microwave power inputs in the future.

The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art

Predictive microbiology has steadily evolved into one of the most important tools to assess and control the microbiological safety of food products. Predictive models were traditionally developed based on experiments in liquid laboratory media, meaning that food microstructural effects were not represented in these models. Since food microstructure is known to exert a significant effect on microbial growth and inactivation dynamics, the applicability of predictive models is limited if food microstructure is not taken into account. Over the last 10-20 years, researchers, therefore, developed a variety of models that do include certain food microstructural influences. This review provides an overview of the most notable microstructure-including models which were developed over the years, both for microbial growth and inactivation.

Optimizing Thermal Processing of Broccoli: Model Development, Numerical Simulation, Experimental Validation

Kinetic models describing the thermal inactivation of peroxidase and degradation of broccoli (Brassica Oleracea var. Italica) color were coupled with heat transfer equation (2D conductive heat transfer in cylindrical packed broccoli samples), and their simultaneous numerical simulation followed by experimental validation was carried out. Obtained results revealed that modeling the rate constants of the reactions with log logistic equation provides a better prediction in comparison with the most popular Arrhenius equation. It was observed that processing at temperatures lower than 80 °C is not recommended for processing of broccoli due to its adverse effect on the color of samples and considerable longer process time needed for assuring sufficient inactivation of enzyme at the cold spot. Temperatures above 80 °C were suitable for this purpose because the process time needed for inactivating peroxidase at the cold spot of sample not only affected the green color of samples negatively, but oppositely it resulted in a higher greenness than the original value.