Prediction of effective moisture diffusivity in plant tissue food materials over extended moisture range

Effective moisture diffusivity provides an easy and expeditious route to understanding many moisture transport processes involving food materials. Instead of making the moisture diffusivity a parameter obtained from curve-fitting a given experimental data that severely restricts its predictive value for the different sets of conditions, a simple but mechanistic approach is provided that for its prediction uses very little empirical information. This approach is based on treating the food as porous media and using parameters such as relative permeability, porosity, tortuosity, and constrictivity. The parameters are predicted using well-known relationships. The model is a combination of liquid and vapor diffusion-weighted by the respective volumes present in the porous medium that provides effective moisture diffusivity. Our model is compared to a mechanistic model that is backboned by Kelvin’s capillary pressure equation and experimental isotherms data. In addition, the prediction is thoroughly validated against available experimental data and the general understanding of liquid/vapor transport in porous media literature. The more mechanistic approach enables prediction over a broader range of moisture content and a greater range of food materials with acceptable RMSE compared to other literature models.