Enabling computer-aided food process engineering: Property estimation equations for transport phenomena-based models

During processing of a food, its temperature, moisture and other compositions, structure, etc., can change, continuously changing its physical properties. Realistic simulation of food processes require dynamic estimation of the food physical properties as they continue to change during the process. Having a few data points for a few states of the material, as is true for the majority of food properties data, is not sufficient for realistic process simulations. The goal of this article is a practical one: it is to develop a concise resource for the equations that can estimate food properties as they change during processing. Such a resource should make computer-aided food product, process and equipment design one step closer to reality by making the necessary input parameters available in one location and in a format that can be readily used in a simulation software. Several equilibrium, transport and electrical properties are included. The estimation equations for any property are chosen from among the most successful and accurate, staying away from property estimators that have theoretical basis but have not been as successful for food materials. For each property, implementation of its prediction equations in a computer model has also been discussed. Accuracy of each property estimation process have been included from the literature, showing most properties can be estimated to within 10% accuracy, sufficient for modeling purposes. Having such reasonable prediction models has the important implication that unavailability of sufficient data, that is expected to be always true due to the variety and complexity of food materials and processes, is not a bottleneck for computer-aided food process engineering.

► The article focuses on estimating food properties in dynamic simulation environment.
► Models discussed range from completely theoretical to completely empirical.
► Preferred choice of models have been the ease of implementation and better accuracy.