Modeling key thermophysical properties for high-pressure food processing: Foundations for a digital knowledge base

High hydrostatic pressure (HHP) processing is increasingly used in the food industry to enhance safety, improve quality, and support the development of novel products. During processing, heat exchange occurs between the HHP unit walls, the pressure-transmitting medium, and the food being processed. Moreover, the extreme pressures involved can significantly alter thermophysical properties, making their estimation essential for predicting product behavior and guiding process design. In particular, computer-aided design of safe, high-quality products and related HHP processes requires reliable thermophysical properties as a function of pressure and temperature to simulate temperature evolution and other key process variables. However, the limited availability of such data under high-pressure conditions remains a major bottleneck. To address this issue, we have compiled and critically discussed theoretical, semi-empirical, and empirical models—currently scattered across the literature—for estimating thermophysical properties relevant to HHP processing, along with assessments of their predictive accuracy. These properties include initial freezing point, ice content, density, thermal expansivity, isothermal compressibility, specific heat capacity, thermal conductivity, enthalpy, and viscosity. While theoretical models are constrained by limited knowledge of pressure effects on individual food components beyond water and typically assume homogeneous systems, thus overlooking explicit structural heterogeneity, more empirical models are often restricted to specific pressure and temperature ranges and compositions. Despite these limitations, the accuracy of the models presented in this review is likely sufficient for design purposes. Product, process, and equipment design and optimization in HHP—particularly when using computer simulations—would be greatly facilitated by this extensive and nearly exhaustive collection of predictive models available today. • Compiled models for relevant thermophysical properties of foods under pressure • Reviewed and discussed theoretical, semi-empirical, and empirical approaches • Created a nearly exhaustive collection of predictive models available today • Facilitated the design and optimization of HHP processes in foods