Modeling Heat Transfer During Cooling of Ready-to-eat Meat and Poultry Products Using Three-dimensional Finite Element Analysis and Web-based Simulation

The meat industry is required to comply with processing performance standards for preventing the growth of foodborne pathogens in products. These performance standards, established by the United States Department of Agriculture - Food Safety and Inspection Service (USDA-FSIS) require a reduction of Salmonella spp (lethality standard) and limit the growth of sporeforming bacteria (stabilization standard) in certain processed meat products. In general, strategies used to comply with these standards are associated with thermal processing. Meat processors have difficulties complying with these performance standards. Moreover, thermal processing deviations are an issue in the meat industry that generate uncertainty regarding the safety of finished products. When thermal processing deviations occur, the USDA-FSIS recommends the use of computer models (i.e. heat transfer and microbial growth predictive models) as tools to evaluate the severity of the deviation. The objective of this study was to develop a heat transfer model for simulating cooling of cooked irregular-shaped, ready-to-eat meat and poultry products. The developed heat transfer model considered conduction as the governing equation, subject to combined convection, radiation and evaporation boundary conditions. A three-dimensional finite element algorithm implemented in JavaTM (Version 6, update 23, Sun Microsystems, 2010) was used to solve the model. Model validation was conducted using data collected in four different meat processing facilities, under real time-varying processing conditions. The model was adapted to receive input parameters that are readily available and can easily be provided by meat processors such as air relative humidity, air temperature, air velocity, type of casing, duration of water shower, and product weight and core temperature prior to entering the chiller. The mean deviation between the observed and predicted values was 1.2 °C for core temperatures; 1.7 °C for temperatures 5.08 cm from core; and 2 °C for surface temperatures. The developed heat transfer model can be integrated with predictive microbiology models; which can be particularly useful for evaluating the severity of thermal processing deviations caused by unexpected processing disruptions. This integration can be the foundation for open source software packages which can serve as quantitative tools to support food safety management in the meat industry