Drying process modeling of basil seed mucilage by infrared dryer using artificial neural network

Authors
1 MSc Student, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
2 Assistant Professor, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
Abstract
Today, plant and commercial gums are used to improve the rheological, textural and sensorial properties of food. Basil seeds have significant amounts of gum (mucilage) with good functional properties that after extracting from the seeds and drying, can be used as a powder in the formulation of various products. In this study, to drying of basil seed mucilage, infrared radiation (IR) method was used. The effect of infrared lamp power (150, 250 and 375 W), the distance of sample from lamp (4, 8 and 12 cm) and mucilage thickness (0.5, 1 and 1.5 cm) on drying time of basil seed mucilage were investigated. The results of basil seed mucilage drying using infrared method showed that with increasing lamp power and decreases in sample distance from the heat source, drying time was decreased. With increasing in the lamps distance from 4 to 12 cm, the average drying time of basil seed mucilage increased from 131.37 minutes to 336.41 minutes. With increasing sample thickness from 0.5 to 1.5 cm, the average drying time of basil seed mucilage increased from 103.67 to 367.67 minutes. The process was modeled by an artificial neural network with 3 inputs (lamp power, lamp distance and thickness) and 1 output (drying time). The results of artificial neural network modeling showed that a network with 8 neurons in a hidden layer and using the sigmoid activation function could predict the drying time of basil seed mucilage using the infrared dryer (r=0.96). The results of sensitivity analysis by optimal neural network showed that sample thickness is the most effective factor in controlling the drying time of basil seed mucilage.
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[1] Salehi, F. 2019. Characterization of new biodegradable edible films and coatings based on seeds gum: A review, Journal of Packaging Technology and Research. 3, 193-201.
[2] Salehi, F. 2019. Improvement of gluten-free bread and cake properties using natural hydrocolloids: A review, Food science & nutrition. 7, 3391-3402.
[3] Zameni, A., Kashaninejad, M., Aalami, M., Salehi, F. 2015. Effect of thermal and freezing treatments on rheological, textural and color properties of basil seed gum, Journal of Food Science and Technology. 52, 5914-5921.
[4] Wang, Y., Wang, L.-J., Li, D., Xue, J., Mao, Z.-H. 2009. Effects of drying methods on rheological properties of flaxseed gum, Carbohydrate Polymers. 78, 213-219.
[5] Amid, B. T., Mirhosseini, H. 2012. Influence of different purification and drying methods on rheological properties and viscoelastic behaviour of durian seed gum, Carbohydrate Polymers. 90, 452-461.
[6] Cunha, R. L., Maialle, K. G., Menegalli, F. C. 2000. Evaluation of the drying process in spouted bed and spout fluidized bed of xanthan gum: focus on product quality, Powder Technology. 107, 234-242.
[7] Sundaram, J., Durance, T. D. 2008. Water sorption and physical properties of locust bean gum–pectin–starch composite gel dried using different drying methods, Food Hydrocolloids. 22, 1352-1361.
[8] Nep, E. I., Conway, B. R. 2011. Physicochemical characterization of grewia polysaccharide gum: Effect of drying method, Carbohydrate Polymers. 84, 446-453.
[9] Salehi, F., Kashaninejad, M. 2014. Effect of different drying methods on rheological and textural properties of balangu seed gum, Drying Technology. 32, 720-727.
[10] Salehi, F. 2020. Recent applications and potential of infrared dryer systems for drying various agricultural products: A review, International Journal of Fruit Science. 1-17.
[11] Doymaz, İ. 2012. Infrared drying of sweet potato (Ipomoea batatas L.) slices, Journal of Food Science and Technology. 49, 760-766.
[12] Hebbar, H. U., Vishwanathan, K., Ramesh, M. 2004. Development of combined infrared and hot air dryer for vegetables, Journal of Food Engineering. 65, 557-563.
[13] Hosseini Ghaboos, S. H., Seyedain Ardabili, S. M., Kashaninejad, M., Asadi, G., Aalami, M. 2016. Changes in the physico-chemical and engineering parameters of pumpkin (C. moschata) with infrared drying method, Journal of Innovation in Food Science and Technology. 8, 93-102.
[14] Salehi, F. 2020. Recent advances in the modeling and predicting quality parameters of fruits and vegetables during postharvest storage: a review, International Journal of Fruit Science. 1, 1-15.
[15] Toğrul, H. 2006. Suitable drying model for infrared drying of carrot, Journal of Food Engineering. 77, 610-619.
[16] Rasouli, M. 2018. Convective drying of garlic (Allium sativum L.): Artificial neural networks approach for modeling the drying process, Iranian Food Science and Technology Research Journal. 14, 53-62.
[17] Salehi, F., Abbasi Shahkoh, Z., Godarzi, M. 2015. Apricot osmotic drying modeling using genetic algorithm - artificial neural network, Journal of Innovation in Food Science and Technology. 7, 65-76.
[18] Salehi, F., Razavi, S. M. A. 2012. Dynamic modeling of flux and total hydraulic resistance in nanofiltration treatment of regeneration waste brine using artificial neural networks, Desalination and Water Treatment. 41, 95-104.
[19] Nimmol, C. 2010. Vacuum far-infrared drying of foods and agricultural materials, The Journal of the King Mongkut’s University of Technology North Bangkok. 20, 37-44.
[20] Pan, Z., Shih, C., McHugh, T. H., Hirschberg, E. 2008. Study of banana dehydration using sequential infrared radiation heating and freeze-drying, LWT-Food Science and Technology. 41, 1944-1951.
[21] Bahramparvar, M., Salehi, F., Razavi, S. 2014. Predicting total acceptance of ice cream using artificial neural network, Journal of Food Processing and Preservation. 38, 1080–1088.
[22] 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.
[23] Lertworasirikul, S., Saetan, S. 2010. Artificial neural network modeling of mass transfer during osmotic dehydration of kaffir lime peel, Journal of Food Engineering. 98, 214-223.