Mathematical Modeling and Experimental Evaluation of Heat and Mass Transfer During Pork Loin Roasting

ABSTRACT Meat is an important source of nutrients in the human diet, and proper cooking is essential to enhance food safety, digestibility, and sensory quality. This study aimed to develop a mathematical model based on heat and mass transfer equations to simulate pork loin roasting in an electric oven. The model treats meat as a saturated porous medium, incorporating anisotropy due to muscle fiber orientation and the effects of thermal protein denaturation on moisture transfer. It accounts for thermal radiation and convective heat and mass transfer at the surface, along with conduction, moisture diffusion, and pressure‐driven water flow within the meat, described by Darcy's law. The Finite Element Method (FEM) was used to solve the model, and predictions of meat temperature and moisture content were validated against roasting experiments at 180°C, 200°C, and 220°C. Experimental methods determined meat emissivity via thermal imaging and convective heat transfer coefficients using the lumped thermal capacity approach. Water permeability and effective moisture diffusion coefficients were obtained through optimization. The model accurately predicts transient temperature, moisture content, and pressure distributions. Results show that moisture loss is primarily due to dripping (~70%), and thermal radiation accounts for 60%–80% of total heat transfer. Sensitivity analysis identified relative humidity inside the oven as a critical factor influencing moisture loss and cooking time, while anisotropy had a limited effect under the conditions studied. The developed model combines accurate predictions with fewer parameters than previous multiphase transport models, while remaining adaptable to various processing conditions, making it suitable for process design and control.