Modelling of red abalone (Haliotis rufescens) slices drying process: Effect of osmotic dehydration under high pressure as a pretreatment

Simultaneous application of osmotic dehydration and high pressure as a pretreatment to drying process on red abalone (Haliotis rufescens) slices was studied. During drying process the process time was reduced by increasing temperature from 40 to 60 degrees C along with the application of different pretreatments: high pressure (350 and 550 MPa), pressure time (5 and 10 min), and osmotic solution (10 and 15% NaCl). Effective moisture diffusivity was determined and varied from 435 to 9.95 x 10(-9) m(2)/s, for both control and pretreated samples (R-2 >= 0.97). The Weibull, Logarithmic and Midilli-Kucuk models were applied to drying experimental data, where Midilli-Kucuk model was found to be the best fitting model. Furthermore, all drying curves were normalized and then modelled by the same three above models showing a R-2 >= 0.96. As to energy consumption and efficiency values for drying processes were found to be in the range of 777-1815 kJ/kg and 822-19.20%, respectively. Thus, knowledge on moisture transfer kinetics, energy consumption and data normalization, is needed to manage and control efficiently drying process under different pretreatment conditions. Industrial relevance: This article deals with the mass transfer modelling and energy consumption during simultaneous high hydrostatic pressure treatment and osmotic dehydration as a pretreatment to drying process of abalone slices. Water and salt transfer during this combined process was satisfactorily simulated with the Midilli-Kucuk model. Results indicated that application of this combined innovative technology improved abalone slices dehydration rates compared to atmospheric pressure operation resulting in a dried abalone with intermediate moisture content ready to be used as input material of further processes. Furthermore, the different energetic features were,determined in order to realize the importance of the changes that can influence to alter process time. (C) 2016 Elsevier Ltd. All rights reserved.