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Sustainability 2018, 10(11), 4126;

Apple Cubes Drying and Rehydration. Multiobjective Optimization of the Processes

Department of Fundamental Engineering, Warsaw University of Life Sciences, Nowoursynowska 164 St., 02-787 Warsaw, Poland
Author to whom correspondence should be addressed.
Received: 17 October 2018 / Revised: 1 November 2018 / Accepted: 5 November 2018 / Published: 9 November 2018
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The effect of convective drying temperature (Td), air velocity (v), rehydration temperature (Tr), and kind of rehydrating medium (pH) was studied on the following apple quality parameters: water absorption capacity (WAC), volume ratio (VR) color difference (CD). To model, simulate, and optimize parameters of the drying and rehydration processes hybrid methods artificial neural network and multiobjective genetic algorithm (MOGA) were developed. MOGA was adapted to the apple tissue, where the simultaneous minimization of CD and VR and the maximization of WAC were considered. The following parameters range were applied, 50 ≤ Td ≤ 70 °C and 0.01 ≤ v ≤ 6 m/s for drying and 20 ≤ Tr ≤ 95 °C for rehydration. Distilled water (pH = 5.45), 0.5% solution of citric acid (pH = 2.12), and apple juice (pH = 3.20) were used as rehydrating media. For determining the rehydrated apple quality parameters the mathematical formulas were developed. The following best result was found. Td = 50.1 °C, v = 4.0 m/s, Tr = 20.1 °C, and pH = 2.1. The values of WAC, VR, and CD were determined as 4.93, 0.44, and 0.46, respectively. Experimental verification was done, the maximum error of modeling was lower than 5.6%. View Full-Text
Keywords: optimization; genetic algorithm; artificial neural network; apple; drying; rehydration optimization; genetic algorithm; artificial neural network; apple; drying; rehydration

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Winiczenko, R.; Górnicki, K.; Kaleta, A.; Janaszek-Mańkowska, M.; Choińska, A.; Trajer, J. Apple Cubes Drying and Rehydration. Multiobjective Optimization of the Processes. Sustainability 2018, 10, 4126.

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