Shrimp is one of the most popular and widely consumed seafood products worldwide. It is highly perishable due to its high moisture content. Thus, dehydration is commonly used to extend its shelf life, mostly via air drying, leading to a temperature increase, moisture removal, and matrix shrinkage. In this study, a mathematical model was developed to describe the changes in moisture and temperature distribution in shrimp during hot-air drying. The model considered the heat and mass transfer in an irregular-shaped computational domain and was solved using the finite element method. Convective heat and mass transfer coefficients (57.0–62.9 W/m²∙K and 0.007–0.008 m/s, respectively) and the moisture effective diffusion coefficient (6.5 × 10⁻¹⁰–8.5 × 10⁻¹⁰ m²/s) were determined experimentally and numerically. The shrimp temperature and moisture numerical solution were validated using a cabinet dryer with a forced air circulation at 60 and 70 °C. The model predictions demonstrated close agreement with the experimental data ($R^2\ge$ 0.95 for all conditions) and revealed three distinct drying stages: initial warming up, constant drying rate, and falling drying rate at the end. Initially, the shrimp temperature increased from 25 °C to around 46 °C and 53 °C for the process at 60 °C and 70 °C. Thus, it presented a constant drying rate, around 0.04 kg/kg min at 60 °C and 0.05 kg/kg min at 70 °C. During this stage, the process is controlled by the heat transferred from the surroundings. Subsequently, the internal resistance to mass transfer becomes the dominant factor, leading to a decrease in the drying rate and an increase in temperatures. A numerical analysis indicated that considering the irregular shape of the shrimp provides more realistic moisture and temperature profiles compared to the simplified finite cylinder geometry. Furthermore, a sensitivity analysis was performed using the validated model to assess the impact of the mass and heat transfer parameters and relative humidity inside the cavity on the drying process. The proposed model accurately described the drying, allowing the further evaluation of the quality and safety aspects and optimizing the process.

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.