A Study of Drying Rate of Sliced Potatoes during Radiation-Vacuum Drying Process using Regression and Artificial Neural Network Models

Document Type : Research Paper



In this study, a single layer sliced potato was dried using an infrared lamp heating under vacuum over three levels of radiant power including 100, 150 and 200 W, three slices thickness 1, 2 and 3 mm and the absolute pressure of 20, 80, 140 and 760 mmHg. Samples were dried in triplicate to achieve 6% moisture content (wet based) which is suitable for long-term storage. Drying rate was monitored during experiments. The shrinkage of sliced potato was measured using image processing. The results showed that increasing infrared radiation and reducing absolute pressure at the same slice thickness, could cause drying time to be reduced but shrinkage increased. Thickness of the slices and infrared radiation power had a significant impact (P<0.01) on shrinkage. Results also showed that the neural network model (R2=0.9732) predicted drying time better than linear (R2=0.819) and nonlinear (R2=0.870) Regression Model.


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