Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 3/6/2023
Publication Date: 6/15/2023
Citation: Sheen, S., Huang, L. 2023. Dynamic heating temperature simulation using numerical analysis with iPMP applications for thermal lethality evaluation of foodborne pathogens in meats. Meeting Abstract. V19(2) 361-371. https://doi.org/10.1002/aic.690180219.
Technical Abstract: The inactivation and survival potential of foodborne pathogens are very important parameters for the food industry to manufacture wholesome consumer products. Most processes of meat products involving heat treatment may encounter a dynamic temperature stress history which affects the meat quality attributes and microbial safety. To achieve the optimization in all aspects, the temperature profile should be made attainable. One way to reach this target is to solve the heat conduction partial differential equations (PDE) with its associated initial and boundary conditions. The physicial properties of food are temperature dependent; therefore, the non-linear PDE can only be solved numerically. We developed the finite volume scheme to solve the non-linear PDE in which the IMSL subroutine IVPAG was used to facilitate the numerical solutions. For a one-dimensional condition in a round-ball shape product (e.g., meat ball), the domain can be divided into N (e.g., 10) shells of equal thickness. An energy balance equation may be established for each shell in the finite difference scheme, then, a set of ordinary differential equations was solved simultaneously using the IMSL subroutine. The finite difference was flexible for different physical properties of food, such as thermal conductivity (k), specific heat (Cp), surface heat transfer coefficient (h) etc.; and was able to predict the temperature profile of a 90% lean beef meat ball (135 grams) heated in an oven with the temperature set at 150ºC and the temperature recorded at every 5 seconds. The thermal conductivities (k) were obtained using the TRIDENT, C-Therm Technologies. The k value is a function of temperature based on data measured between 4ºC and 60ºC (at 5, 10, 20, 30, 45 and 60ºC). The simulation temperature profile was examined against the experiment results which can be integrated with the iPMP (integrated Pathogen Modeling Program, developed by USDA/ARS), to estimate/calculate the overall thermal process lethality. With this simulation capacity, the process optimization may be achieved for better food quality and operation cost saving, while microbial safety maintains a top priority. The numerical simulation may predict the dynamic temperature profile for better thermal lethality estimation and microbial food safety enhancement.