###### Abstract
The interaction of various thermal processing parameters--temperature, humidity, and airflow--significantly influences the denaturation of proteins in goose meat. Higher temperatures accelerate the denaturation process, causing proteins such as myosin and actin to unfold and coagulate, leading to changes in texture and moisture retention. Increased humidity during cooking can help maintain meat juiciness by reducing water loss, thus affecting the extent and rate of protein denaturation. Conversely, low humidity might enhance surface dehydration and protein hardening. Airflow also plays a crucial role; consistent airflow ensures even heat distribution, preventing localized overheating and uneven protein denaturation. Therefore, optimizing these parameters is essential to achieve the desired texture, flavor, and moisture levels in cooked goose meat [4; 17; 18]. Previous studies on the phytochemical composition of goose breast meat have shown that it is essential to understand the diversity of phytochemicals in their different parts and their impact on physicochemical properties and thermal parameters. Goose meat, like other types of meat, contains complex mixtures of chemical compounds, including proteins, lipids, carbohydrates, vitamins, and minerals. The composition of these compounds can vary depending on the part of the meat, affecting its texture, flavor, and reactions to heat treatment. Phytochemical composition models enable precise mapping of these compounds, which is crucial for understanding the protein denaturation processes during cooking. Protein denaturation, a process of altering the tertiary structure of proteins under the influence of temperature, is a key factor affecting the texture and juiciness of the meat. Thermal parameters, i.e., heat capacity, thermal conductivity, and specific temperatures, are closely related to the phytochemical composition, influencing the efficiency of thermal processes in the food industry. Understanding these compounds and their interactions during heat treatment allows for the optimization of technological processes, potentially leading to improved quality of the final product [4; 18; 19]. Innovative approaches based on computational engineering methods, especially Computational Fluid Dynamics (CFD), are revolutionizing research on protein denaturation in food. CFD is an indispensable tool for modeling heat, mass flow, and chemical reactions during thermal processes [20; 21]. This method allows precise simulation of conditions during the thermal processing of goose meat, providing crucial information on how environmental factors affect protein denaturation at the molecular level [22]. CFD enablesthe development of complex yet realistic heat flow models, which are essential for the analysis and optimization of thermal processes Conventional methods and computational fluid dynamics (CFD) differ significantly in predicting protein denaturation and cooking loss. Conventional methods typically rely on experimental measurements and empirical models, which can be time-consuming and expensive, often requiring simplifications and assumptions that may reduce accuracy. In contrast, CFD uses advanced algorithms and computer simulations to provide more detailed and comprehensive modeling of the thermal and chemical processes occurring in proteins. This allows CFD to offer more accurate predictions of protein denaturation and cooking loss, and it is more time-efficient as it enables rapid simulations of multiple scenarios without the need for numerous experiments. As a result, CFD can greatly enhance the precision and efficiency of the prediction process compared to traditional methods. The application of CFD to predict protein denaturation in complex food matrices faces several limitations and challenges. These include the inherent complexity and heterogeneity of food matrices, which can make it difficult to accurately model the physical and chemical environments.