KINETIC MODEL SIMULATION OF THIN-LAYER DRYING OF ORANGE FRUIT (VAR. THOMPSON) USING ARTIFICIAL NEURAL NETWORK

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SHARIFI MOHAMMAD; RAFIEI SHAHIN; KEYHANI A.R.; OMID MAHMOUD

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Journal: IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY Year:2010 | Volume:7 | Issue:1 Page(s): 39-49

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Title

KINETIC MODEL SIMULATION OF THIN-LAYER DRYING OF ORANGE FRUIT (VAR. THOMPSON) USING ARTIFICIAL NEURAL NETWORK

Author(s)

SHARIFI MOHAMMAD | RAFIEI SHAHIN | KEYHANI A.R. | OMID MAHMOUD | Issue Writer Certificate

Keywords

ORANGE (VAR. THOMPSON)Q3

THIN-LAYERQ2

ARTIFICIAL NEURAL NETWORKQ2

MOMENTUMQ3

LEVENBERG-MARQUARDTQ3

Abstract

Citrus, especially orange, are of great important among agricultural products in the world. In this study THIN-LAYER drying of orange (var. Thompson) was modeled using ARTIFICIAL NEURAL NETWORK (ANN). An experimental dryer was used. THIN-LAYER of orange slices at five air temperatures (40, 50, 60, 70 & 80°C), three air velocities (0.5, 1 & 2 m/s) and three thicknesses (2, 4 & 6 mm) were artificially dried. Initial M.C. during all experiments was between 5.4 to 5.7 (g/g) (d.b.). Mass of samples were recorded and saved every 5 sec. using a digital balance connected to a PC. MLP with MOMENTUM and LM were used to train the ANNS. In order to develop ANN's models, temperatures, air velocity and time are used as input vectors and moisture ration as the output. Results showed a 3-6- 1 topology for thickness of 2 mm, 3-7-1 topology for thickness of 4 mm and 3-5-1 topology for thickness of 6 mm, with LM algorithm and TANSIG activation function were able to predict moisture ratio with R2 of 0.99906, 0.99919 and 0.99930 respectively. The corresponding MSE for this topology were 0.00013, 0.00012 and 0.00009 respectively.

Cites

MICROWAVE-ASSISTED EXTRACTION OF PHENOLIC COMPOUNDS FROM EUCALYPTUS CAMALDULENSIS DEHN LEAVES AND ESTIMATION OF EXTRACTION PROCESS BY ARTIFICIAL NEURAL NETWORKS

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APA: Copy

SHARIFI, MOHAMMAD, RAFIEI, SHAHIN, KEYHANI, A.R., & OMID, MAHMOUD. (2010). KINETIC MODEL SIMULATION OF THIN-LAYER DRYING OF ORANGE FRUIT (VAR. THOMPSON) USING ARTIFICIAL NEURAL NETWORK. IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY, 7(1), 39-49. SID. https://sid.ir/paper/71928/en

Vancouver: Copy

SHARIFI MOHAMMAD, RAFIEI SHAHIN, KEYHANI A.R., OMID MAHMOUD. KINETIC MODEL SIMULATION OF THIN-LAYER DRYING OF ORANGE FRUIT (VAR. THOMPSON) USING ARTIFICIAL NEURAL NETWORK. IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY[Internet]. 2010;7(1):39-49. Available from: https://sid.ir/paper/71928/en

IEEE: Copy

MOHAMMAD SHARIFI, SHAHIN RAFIEI, A.R. KEYHANI, and MAHMOUD OMID, “KINETIC MODEL SIMULATION OF THIN-LAYER DRYING OF ORANGE FRUIT (VAR. THOMPSON) USING ARTIFICIAL NEURAL NETWORK,” IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY, vol. 7, no. 1, pp. 39–49, 2010, [Online]. Available: https://sid.ir/paper/71928/en

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