## 4 Modeling of Physicochemical Parameters and Their Impact on Thermal Processes  
### Influence of Food Structure and Physical Properties on Heat Transfer  
The heat transfer mechanisms within food systems are critically influenced by the physicochemical properties of the food matrix, including its structural characteristics and intrinsic physical properties. The primary modes of heat transfer--conduction, convection, and radiation--are intricately affected by the spatial arrangement and interactions of food components at both the microscopic and macroscopic levels. In particular, heterogeneous distributions of temperature are observed due to the complex phase transitions and material heterogeneity present within food structures. For instance, the presence of fats, water, and air pockets significantly alters thermal conductivity, leading to complex temperature gradients that must be accurately modeled to understand the overall heat transfer efficiency during food processing [56,126]. The thermal conductivity of food materials exhibits a high degree of variability, often depending on the composition and moisture content of the matrix. Proteins, typically exhibiting thermal conductivities in the range of 0.2 W/m\(\cdot\)K, display markedly lower heat transfer rates compared to fats, which can have thermal conductivities as high as 0.5 W/m\(\cdot\)K. This disparity directly impacts the rate of heat penetration during thermal treatments such as baking, frying, and pasteurization [11]. The variability in these thermal properties underscores the need to account for specific heat capacities, thermal diffusivities, and the phase transitions (for example, water to vapor, fat melting) that occur within the food matrix during processing [127]. The food microstructure, encompassing properties such as porosity, bulk density, and the organization of fibre networks, is a critical determinant of heat transfer behavior. For instance, an increase in porosity can facilitate convective heat transfer by providing pathways for air or fluid movement within the food product. Air pockets, in particular, have been shown to enhance heat transfer by reducing thermal resistance. In contrast, denser matrices with lower porosity--common in meat and some vegetables--tend to impede thermal penetration, resulting in temperature gradients and non-uniform cooking or processing. Additionally, factors such as water activity and phase changes (for example, the melting of fats and evaporation of water) exert significant influence over the effective thermal properties of food, directly impacting the heat transfer efficiency during different processing stages [56]. Mathematically, the modeling of heat transfer within food systems is grounded in the application of [PERSON]'s law of heat conduction, expressed as (Equation (13)) [34,128]:  
\[q=-k\
abla T \tag{13}\]  
where \(q\) is the heat flux (W/m\({}^{2}\)), \(k\) is the thermal conductivity (W/m\(\cdot\)K), and \(\
abla T\) is the temperature gradient (K/m). In the case of convection, the convective heat transfer rate is described by [PERSON]'s law of cooling (Equation (14)) [72,81]:  
\[q=hA(T_{s}-T_{\infty}) \tag{14}\]  
where \(h\) is the convective heat transfer coefficient (W/m\({}^{2}\cdot\)K), \(A\) is the heat transfer area (m\({}^{2}\)), \(T_{s}\) is the surface temperature, and \(T_{\infty}\) is the ambient temperature of the surrounding medium. Additionally, radiation heat transfer is often modeled using the Stefan-Boltzmann law (Equation (15)):  
\[q=\sigma\epsilon A\left(T^{4}-T_{env}^{4}\right) \tag{15}\]  
where \(\sigma\) is the Stefan-Boltzmann constant, \(\epsilon\) is the emissivity of the surface, \(A\) is the surface area, and \(T\) and \(T_{env}\) are the temperatures of the object and surrounding environment, respectively [34]. CFD provides an advanced framework for the integrated modeling of these complex heat transfer phenomena, allowing for the simulation of fluid flow and heat conduction within food matrices.