Determination of the Osmotic Dehydration Parameters of Mushrooms using Constrained Optimization

Year 2019, Volume: 2 Issue: 4, 77 - 83, 30.12.2019

İhsan Pençe Melike Şişeci Çeşmeli Ramazan Kovacı

Abstract

To
keep and transport the agricultural products have importance especially in
terms of health. These products have to be kept properly so as to transport
distant places. Recently, Osmotic Dehydration Technology has become more
important in keeping the products well for a longer time and among the other
food dehydration methods it provides better color, flavor, and nutritiousness.
In this study, it is studied on the drying of mushrooms with osmotic
dehydration method which is also one of the most significant export commodities
in Turkey and determination of the best dehydration parameters is carried out
using optimization. For optimization process, a heuristic method is used and
internet of things based prototype design which can control the system automatically
is formed.

Keywords

Constrained optimization, IOT, Mushroom, Netduino, Osmotic dehydration

References

• Şevik, S., Aktaş, M., Doğan, H. & Koçak, S. (2013). Mushroom drying with solar assisted heat pump system. Energy Conversion and Management, 72, 171-178.
• Indian Institute of Horticultural Research, Indian Council of Agricultural Research (ICAR-IIHR), (02.10.2018). Retrieved from https://www.iihr.res.in/post-harvest-technologies.
• Çınar, İ. (2009). Osmotic dehydration, mechanism and applications. The Journal of Food, 34(5), 325-329.
• Mehta, B. K., Jain, S. K., Sharma, G. P., Mudgal, V. D., Verma, R. C., Doshi, A., & Jain, H. K. (2012). Optimization of osmotic drying parameters for button mushroom (Agaricus bisporus). Applied Mathematics, 3(10), 1298.
• Karimi, F., Rafiee, S., Taheri-Garavand, A., & Karimi, M. (2012). Optimization of an air drying process for Artemisia absinthium leaves using response surface and artificial neural network models. Journal of the Taiwan Institute of Chemical Engineers, 43(1), 29-39.
• Sun, D. W. (2014). Emerging technologies for food processing. Elsevier, London: Academic.
• Yeomans, J. S. (2014). A parametric testing of the firefly algorithm in the determination of the optimal osmotic drying parameters of mushrooms. Journal of Artificial Intelligence and Soft Computing Research, 4(4), 257-266.
• Yeomans, J. S. (2015). Determining optimal osmotic dehydration process parameters for papaya: a parametric testing of the Firefly Algorithm for Goal Programming optimization. Scientia Agriculturae, 10, 127-136.
• Yıldız, A. K., Polatcı, H., & Uçun, H. (2015). Drying of the banana (Musa cavendishii) fruit and modeling the kinetics of drying with artificial neural networks under different drying conditions. Journal of agricultural Machinery Science, 11(2), 173-178. Gupta, P., Bhat, A., Chauhan, H., Ahmed, N., & Malik, A. (2015). Osmotic dehydration of button mushroom. International Journal of Food and Fermentation Technology, 5(2), 177.
• Smith, A. M. (2015). Optimization of pulsed-vacuum osmotic dehydration of blueberries. (Doctoral dissertation), West Virginia University.
• Ahmed, I., Qazi, I. M., & Jamal, S. (2016). Developments in osmotic dehydration technique for the preservation of fruits and vegetables. Innovative Food Science & Emerging Technologies, 34, 29-43.
• Bahmani, A., Jafari, S. M., Shahidi, S. A., & Dehnad, D. (2016). Mass transfer kinetics of eggplant during osmotic dehydration by neural networks. Journal of food processing and preservation, 40(5), 815-827.
• Cao, T., & Yeomans, J. S. (2017). An evolutionary firefly algorithm, goal programming optimization approach for setting the osmotic dehydration parameters of papaya. Journal of Software Engineering and Applications, 10(2), 128.
• Yeomans, J. S. (2018). Computing optimal food drying parameters using the firefly algorithm. GSTF Journal on Computing (JoC), 4(1).
• Goula, A. M., Kokolaki, M., & Daftsiou, E. (2017). Use of ultrasound for osmotic dehydration. The case of potatoes. Food and Bioproducts Processing, 105, 157-170.
• Ramya, V., & Jain, N. K. (2017). A Review on osmotic dehydration of fruits and vegetables: an integrated approach. Journal of Food Process Engineering, 40(3), e12440.
• Akpınar, E. K., & Daş, M. (2018). Mushroom drying in air heated solar collector drying system and modeling of drying performance with artificial neural network. Erzincan University Journal of Science and Technology, 11(1), 23-30.
• Das, I., & Arora, A. (2018). Alternate microwave and convective hot air application for rapid mushroom drying. Journal of Food Engineering, 223, 208-219.
• Anshu, S., & Anju, B. (2018). Effect of osmotic dehydration on quality of oyster mushrooms. IJCS, 6(2), 1601-1605.
• González-Pérez, J. E., López-Méndez, E. M., Luna-Guevara, J. J., Ruiz-Espinosa, H., Ochoa-Velasco, C. E., & Ruiz-López, I. I. (2019). Analysis of mass transfer and morphometric characteristics of white mushroom (Agaricus bisporus) pilei during osmotic dehydration. Journal of Food Engineering, 240, 120-132.
• Imanirad, R., & Yeomans, J. S. (2015). Fireflies in the fruits and vegetables: combining the firefly algorithm with goal programming for setting optimal osmotic dehydration parameters of produce. In Recent Advances in Swarm Intelligence and Evolutionary Computation (pp. 49-69). Springer, Cham.
• Pence, I., Cesmeli, M. S., Senel, F. A., & Cetisli, B. (2016). A new unconstrained global optimization method based on clustering and parabolic approximation. Expert Systems with Applications, 55, 493-507.