Experimental performance and artificial neural network modeling of solar drying of litchi in the parabolic greenhouse dryer


  • Serm Janjai Department of Physics, Faculty of Science, Silpakorn University
  • K. Tohsing
  • N. Lamlert
  • T. Mundpookhier
  • W. Chanalert
  • B. K. Bala


Artificial neural network, parabolic greenhouse dryer, litchi, drying


This paper presents experimental performance and artificial neural network modeling of drying of litchi flesh in a parabolic greenhouse solar dryer. The dryer consists of a parabolic roof structure covered with polycarbonate sheets on a concrete floor. This dryer has the base area of 5.5´8.2 m2 and the height of 3.25 m. To investigate the experimental performance of the dryer for the drying of litchi flesh, 10 experiments were conducted. One hundred kilograms of litchi flesh were used for each experiment. The drying time of litchi flesh in the dryer was 3 days, whereas 5-6 days were required for natural sun drying under similar weather conditions. An artificial neural network (ANN) approach was used to model the performance of the dryer for the drying of litchi flesh. Using solar drying data of litchi flesh, the ANN model has been trained using the back-propagation algorithm. Seven sets of data were used for training and three sets were used for testing the ANN model. The performance of the dryer predicted by model was found to be very good.


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El-Shiatry MA, Muller J, Muhlbauer W, (1991). Drying fruits and vegetables with solar energy in Egypt. Agricultural Mechanization in Asia Africa and Latin America 22(2), 61–64.

Sharma VK, Colangelo A, Spanga G, (1995). Experimental investigation of different solar driers suitable for fruits and vegetable drying. Renewable Energy 6, 413–424.

Schirmer P, Janjai S, Esper A, Smitabhindu R, Muhlbauer W, (1996). Experimental investigation of the performance of the solar tunnel dryer for drying bananas. Renewable Energy 7(2), 119–129.

Karathanos VT, Belessiotis VG, (1997). Sun and artificial air drying kinetics of some agricultural products. Journal of Food Engineering 31, 35–46.

Bala BK, Mondol MRA, (2001). Experimental investigation on solar drying of fish using solar tunnel drier. Drying Technology 19(2), 1–10.

Bala BK, Mondol MRA, Das Choudhury BL, (2002). Solar drying of mango using solar tunnel drier. Journal of Agricultural Engineering 38(14), 43–50.

Bala BK, Mondol MRA, Biswas BK, Das Choudhury BL, Janjai S, (2003). Solar drying of pineapple using solar tunnel drier. Renewable Energy 28, 183–190.

Janjai S, Lambert N, Intawee P, Mahayothee B, Haewsungcharern M, Bala BK, Müller J, (2008a). Finite element simulation of drying of mango. Biosystems Engineering 99, 523–531.

Janjai S, Lambert N, Intawee P, Mahayothee B, Haewsungcharern M, Bala BK, Nagle M, Leis H, Müller J, (2008b). Finite element simulation of drying of longan fruit. Drying Technology 26, 666–674.

Janjai S, Mahayothee B, Lambert N, Bala BK, Precoppe M, Nagle M, Müller J, (2010). Diffusivity, shrinkage and simulated drying of litchi fruit (Litchi Chinensis Sonn.). Journal of Food Engineering 96, 214–221.

Janjai S, Precoppe, M, Lamlert N, Mahayothee B, Bala BK, Nagle M, Müller J, (2011). Thin-layer drying of litchi (Litchi chinensis Sonn.). Food and Bioproducts Processing 89, 194-201.

Amer BMA, Hossain MA, Gottschalk K, (2010). Design and performance evaluation of a new hybrid solar dryer for banana. Energy Conversion and Management 51, 813-820.

Nilnont W, Thepa S, Janjai S, Kasayapanand N, Thamrongmas C, Bala BK, (2012). Finite element simulation of coffee (Coffea Arabica) drying. Food and Bioproducts Processing 90, 341-350.

Reyes A, Mahn A, Cubillos F, Huenulaf P, (2013). Mushroom dehydration in a hybrid-solar dryer. Energy Conversion and Management 70, 31-39.

Mohajer A, Nematollahi O, Joybari MM, Hashemi SA, Assari MR, (2013). Experimental investigation of a hybrid solar drier and water heater system. Energy Conversion and Management 76, 935-944.

Mohanraj M, (2014). Performance of a solar-ambient hybrid source heat pump drier for copra drying under hot-humid weather conditions. Energy for Sustainable Development 23, 165-169.

Shalaby SM, Bek MA, (2014). Experimental investigation of a novel indirect soalr dryer implementing PCM as energy storage medium. Energy Conversion and Management 83, 1-8.

Fudholi A, Sopian K, Yazdi MH, Ruslan MH, Gabbasa M, Kazem HA, (2014). Performance analysis of solar drying system for red chili. Solar Energy 99, 47-54.

Reyes A, Mahn A, Vasquez F, (2014). Mushrooms dehydration in a hybrid-solar dryer, using a phase change material. Energy Conversion and Management 83, 241-248.

Fudholi A, Sopian K, Bakhtyar B, Gabbasa M, Othman MY, Ruslan MH, (2015). Review of solar drying systems with air based solar collectors in Malaysia. Renewable and Sustainable Energy Reviews 51, 1191-1204.

Kaminski W, Tomczak E, Strumill P, (1998). Neurocomputing approaches to modeling of drying process dynamics. Drying Technology 16, 967–992.

Huang B, Mujumdar AS, (1993). Use of neural network to predict industrial dryer performance. Drying Technology 11, 525–541.

Trelea IC, Courtois F, Trystram G, (1997). Dynamic models for drying and wet milling quality degradation of corn using neural networks. Drying Technology 15, 1095–1102.

Farkas I, Remenyl P, Biro A, (2000). Modelling aspects of grain drying with a neural network. Computers and Electronics in Agriculture 29, 99–113.

Hernandez-Perez JA, Garcia-Alvarado MA, Trystram G, Heyd B, (2004). Neural networks for the heat and mass transfer prediction during drying of cassava and mango. Innovative Food Science and Emerging Technologies 5, 57–64.

Bala BK, Ashraf MA, Uddin MA, Janjai S, (2005). Experimental and neural network prediction of the performance of a solar tunnel drier for drying jackfruit bulbs and leather. Journal of Food Process Engineering 28, 552–566.

Erenturk S, Erenturk K, (2007). Comparison of genetic algorithm and neural network approaches for the drying process of carrot. Journal of Food Engineering 78, 905–912.

Movagharnejad K, Nikzad M, (2007). Modeling of tomato drying using artificial neural network. Computers and Electronics in Agriculture 59, 78–85.

Chegini GR, Khazaei J, Ghobadian B, Goudarzi AM, (2008). Prediction of process and product parameters in an orange juice spray dryer using artificial neural networks. Journal of Food Engineering 84, 534–543.

Cakmak G, Yildiz C, (2001). The prediction of seedy grape drying rate using a neural network method. Computers and Electronics in Agriculture 75, 132–138.

Aghbashloa M, Mobli H, Rafiee S, Madadlou A, (2012). The use of artificial neural network to predict exergetic performance of spray drying process: A preliminary study. Computers and Electronics in Agriculture 88, 32–43.

Khazaei NB, Tavakoli T, Ghassemian H, Khoshtaghazaa MH, Banakar A, (2013). Applied machine vision and artificial neural network for modeling and controlling of the grape drying process. Computers and Electronics in Agriculture 98, 205–213.

Janjai S, Lambert N, Intawee P, Mahayothee B, Bala BK, Nagle M, Müller J, (2009). Experimental and simulated performance of a PV ventilated solar greenhouse dryer for drying of peeled longan and banana. Solar Energy 83, 1550-1565.

Chen CR, Ramaswamy HS, (2002). Modeling and optimization of variable retort temperature (VRT) thermal processing using coupled neural networks and genetic algorithms. Journal of Food Engineering 28, 552–566.

Izadifar M, Jahromi MZ, (2007). Application of genetic algorithm for optimization of vegetable oil hydrogenation process. Journal of Food Engineering 78, 1–8.

Erzin Y, Rao HB, Singh DN, (2008). Artificial neural network models for predicting soil thermal resistivity. International Journal of Thermal Sciences 47, 1347–1358.

Hecht-Nielsen R, (1989). Theory of backpropagation neural network. In Proceedings of International Joint Conference on Neural Networks. Washington DC, 593-605.

Zhang Q, Yang SX, Mittal GS, Yi S, (2002). Prediction performance indices and optimal parameters of rough rice drying using neural networks. Biosystems Engineering 83(3), 281–290.

Wasserman PD, (1989). Neural Computation, Theory and Practice. Van Nostrand Reinhold, New York, NY.

Krokida MK, Tsami E, Maroulis ZB, (1998). Kinetics on color changes during drying of some fruits and vegetables. Drying Technology 16(3–5), 667–685.

Maskan M, (2001). Kinetics of colour change of kiwifruits during hot air and microwave drying. Journal of Food Engineering 48(2), 169–175.

Zhang M, De Baerdemaeker J, Schrevens E, (2003). Effects of different varieties and shelf storage conditions of chicory on deteriorative color changes using digital image processing and analysis. Food Research International 36(7), 669–676.

O’Callaghan JR, Menzies DJ, Bailey PH, (1971). Digital simulation of agricultural drier performance. Journal of Agricultural Engineering Research 16, 223-244.




How to Cite

Janjai, S., Tohsing, K., Lamlert, N., Mundpookhier, T., Chanalert, W., & Bala, B. K. (2018). Experimental performance and artificial neural network modeling of solar drying of litchi in the parabolic greenhouse dryer. Journal of Renewable Energy and Smart Grid Technology, 13(1). Retrieved from https://ph01.tci-thaijo.org/index.php/RAST/article/view/56849