Thermal processing is a critical step in shelf-stable food manufacturing to the ensure safety of the food products. To accurately model and establish the thermal processes, temperature-dependent thermal properties are needed. Existing methods for measuring the temperature-dependent thermal diffusivity (α), thermal conductivity (k) and volumetric heat capacity (C) are time consuming, tend to have high errors, and cannot provide results in a single experiment, especially at temperatures above

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... C. A novel bench scale device, named Thermal Properties Cell (TPCell), was custom made to rapidly estimate the temperature-dependent thermal parameters of food products. The TPCell used thin film heaters as the heating elements. The first study focused on estimating the thermal properties of a thin film heater. Using mathematical modeling and sequential parameter estimation, the effective thermal diffusivity of the thin film heater was found at different temperatures. The estimated thermal properties of the thin film heater were used for the second study. The objective of the second study was to design optimal complementary experiments using TPCell. Complementary experiments are a combination of experiments that enable estimation of multiple thermal parameters from the experimental temperature data, based on sensitivity analysis. Sensitivity coefficients indicate the extent of change in a measured variable due to a change in value of an input parameter. Designs of experiments were simulated and their impact on sensitivity and optimality criteria was analyzed. Results from the simulated profiles were validated using sweet potato puree. Learnings from this work can be directly applied for the optimization of all types of food thermal processes, including retort and aseptic processing. Optimally designed processes increase preservation of the heat labile nutrients, color, flavor, and taste compounds, thereby enhancing the quality of food products.