It is crucial to determine the thermophysical properties of high-moisture extruded samples (HMESs) to properly understand the texturization process of high-moisture extrusion (HME), especially when the primary objective is the production of high-moisture meat analogues (HMMAs). Therefore, the study's aim was to determine thermophysical properties of high-moisture extruded samples made from soy protein concentrate (SPC ALPHA® 8 IP). Thermophysical properties such as the specific heat capacity and the apparent density were experimentally determined and further investigated to obtain simple prediction models. These models were compared to non-HME-based literature models, which were derived from high-moisture foods, such as soy-based and meat products (including fish). Furthermore, thermal conductivity and thermal diffusivity were calculated based on generic equations and literature models and showed a significant mutual influence. The combination of the experimental data and the applied simple prediction models resulted in a satisfying mathematical description of the thermophysical properties of the HME samples. The application of data-driven thermophysical property models could contribute to understanding the texturization effect during HME. Further, the gained knowledge could be applied for further understanding in related research, e.g., with numerical simulation studies of the HME process.
Keywords: data-driven prediction models; high-moisture extrusion; high-moisture meat analogues (HMMAs); protein texturization; thermophysical properties of HMMAs.