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Modeling the Drying Kinetics of Green Bell Pepper in a Heat Pump Assisted Fluidized Bed Dryer

Jafari, S.M. and Ghanbari, V. and Ganje, M. and Dehnad, D. (2016) Modeling the Drying Kinetics of Green Bell Pepper in a Heat Pump Assisted Fluidized Bed Dryer. Journal of Food Quality, 39 (2). pp. 98-108.

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Abstract

In this research, green bell pepper was dried in a pilot plant fluidized bed dryer equipped with a heat pump humidifier using three temperatures of 40, 50 and 60C and two airflow velocities of 2 and 3m/s in constant air moisture. Three modeling methods including nonlinear regression technique, Fuzzy Logic and Artificial Neural Networks were applied to investigate drying kinetics for the sample. Among the mathematical models, Midilli model with R=0.9998 and root mean square error (RMSE)=0.00451 showed the best fit with experimental data. Feed-Forward-Back-Propagation network with Levenberg-Marquardt training algorithm, hyperbolic tangent sigmoid transfer function, training cycle of 1,000 epoch and 2-5-1 topology, deserving R=0.99828 and mean square error (MSE)=5.5E-05, was determined as the best neural model. Overall, Neural Networks method was much more precise than two other methods in prediction of drying kinetics and control of drying parameters for green bell pepper. Practical Applications: This article deals with different modeling approaches and their effectiveness and accuracy for predicting changes in the moisture ratio of green bell pepper enduring fluidized bed drying, which is one of the most concerning issues in food factories involved in drying fruits and vegetables. This research indicates that although efficiency of mathematical modeling, Fuzzy Logic controls and Artificial Neural Networks (ANNs) were all acceptable, the modern prediction methods of Fuzzy Logic and especially ANNs were more productive and precise. Besides, this report compares our findings with previous ones carried out with the view of predicting moisture quotients of other food crops during miscellaneous drying procedures. © 2016 Wiley Periodicals, Inc.

Item Type: Article
Additional Information: cited By 0
Uncontrolled Keywords: Backpropagation; Backpropagation algorithms; Bells; Dryers (equipment); Drying; Fuzzy logic; Fuzzy neural networks; Heat pump systems; Hyperbolic functions; Kinetics; Mean square error; Neural networks; Pilot plants; Topology, Air flow velocity; Drying parameters; Feed-forward back propagation networks; Fluidized bed dryers; Hyperbolic tangent sigmoid transfer function; Levenberg-Marquardt training algorithm; Nonlinear regression technique; Root mean square errors, Fluidized beds
Subjects: مقالات نمایه شده محققین دانشگاه در سایت ,Web of Science ,Scopus
Divisions: معاونت تحقیقات و فناوری
Depositing User: GOUMS
Date Deposited: 07 Sep 2016 10:20
Last Modified: 26 Sep 2016 07:47
URI: http://eprints.goums.ac.ir/id/eprint/4564

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