Comparison between Continuous and Discontinuous Method of Kinetic Evaluation for Osmotic Dehydration of Cherry Tomato

Abstract

Discontinuous method is the commonly used method of obtaining the experimental data for osmotic dehydration curves, in which, different samples with similar size are used at different dehydration times. Moreover, the continuous method is based on the measurement of weight loss, in a single sample, at different dehydration times and measurement of the final moisture content at the end of the dehydration process. In this method, one sample is used throughout the osmotic dehydration process. In this paper, continuous and discontinuous methods of kinetic evaluation were compared for water loss and solid gain during osmotic dehydration of cherry tomato in salt solution. The osmotic dehydration experiments were conducted at different solution concentrations (10, 18 and 25% w/w) and temperatures (30 and 40C). The moisture and salt effective diffusivities were estimated using the analytical solution of Fick's second law of diffusion in the spherical coordinate. Although continuous method makes it easier to predict the variations of moisture loss and solute gain as a function of dehydration time, this method predicts the same kinetics for water loss and solid gain and also the same values for moisture and solute diffusivities. The results show that using the discontinuous method results in more dispersion of the experimental data than when the continuous method was employed. Practical Applications The present study compares two well-known method of kinetic evaluation for osmotic dehydration of foodstuff. This comparison shows the shortcoming of the continuous method for prediction of kinetics of water loss and solid gain and also the values of moisture and solute effective diffusivities. These parameters are used in the mathematical modeling of osmotic dehydration process. Mathematical models provide information about the process to which they are applied, and help the designers and researchers find the best design parameters and the most effective process conditions.