Mathematical Modeling of Thin Layer Drying of Pomegranate (Punica granatum L.) Arils: Various Drying Methods

Authors
Z. Mazandarani 1
N. Aghajani 2
A. Daraei Garmakhany 3
M. Baniardalan 4
M. Nouri 5
1 Islamic Azad University, Azadshahr Branch, Azadshahr, Islamic Republic of Iran.
2 Department of Food Science and Technology, Bahar Faculty of Food Science and Technology, Bu-Ali Sina University, Bahar City, Hamedan, Islamic Republic of Iran.
3 Department of Food Science and Technology, Toyserkan Faculty of Industrial Engineering, Bu-Ali Sina University, Beheshti Ave., Bahri Esfahani Ave., Toyserkan, Hamadan, Islamic Republic of Iran.
4 Department of language & linguistics, Bu-Ali Sina University, Hamedan, Iran.
5 Department of Linguistics, Humanities Faculty, Bu -Ali Sina University, Hamedan, Islamic Republic of Iran.
Abstract
For years, sun and hot air drying have been considered as traditional drying methods. Today, using microwave is one the newest methods of drying. Iran is one of the main producers of pomegranate fruit in the world. To manufacture better product, drying needs to be handled in controlled and optimized process, therefore investigation of process condition kinetic is an obligation. In this study, thin layer drying behavior of pomegranate arils using microwave drier at 4 power levels (180, 360, 540 and 720W), oven drier at 4 temperature levels (45, 55, 65 and 75°C) and sun drying was studied. Page, Henderson and Pabis, Midilli et al., Newton, Logarithmic and Two-Term models were compared according to their Root Mean Square error (RMSE), Chi-square (χ2), Mean Bias Error (MBE) and correlation coefficient (R2). The results of the studied models indicated that Midilli et al., model exhibited the best fit to the data obtained for oven, microwave and sun drying. Increasing the oven drier temperature and the microwave drier power lead to an increase in the drying rate. Dried samples at 75˚C exhibited the highest R2= 0.9998, and the least RMSE and χ2, 0.2059 and 0.5576 respectively in comparison with other samples. While dried samples by microwave, 720W, showed the highest R2= 0.9998 and the least RMSE and χ2 were 0.1894 and 0.4203, respectively in comparison with other samples. Sun dried samples had the highest R2 in Midilli Model, the least RMSE and X2 were 0.0338 and 0.7059 respectively.

Keywords

1. Abbasi, S., Motevali, A., Minaei, S. and Ghaderi, A. 2010. Selection of a Mathematical Model for Drying Kinetics of Sour Cherry (Prunus cerasus L.) in a Microwave-Vacuum Dryer. Iran J. Nutr. Food Sci. Food Technol., 6(2): 55-64.
2. Aghajani, N., Ansaripour, E. and Kashaninejad, M. 2012a. Effect of Moisture Content on Physical Properties of Barley Seeds. J. Agr. Sci. Tech., 14(1): 161-172.
3. Aghajani, N., Kashaninejad, M., Dehghani, A. A. and Daraei Garmakhany, A. 2012b. Comparison between Artificial Neural Networks and Mathematical Models for Moisture Ratio Estimation in Two Varieties of Green Malt. Qual. Assur. Saf. Crop., 4(2): 93- 101.
4. Aghajani, N., Kashiri, M. and Kashaninejad, M. 2010. Thin-Layer Drying Characteristics and Modeling of Two Varieties Green Malt. J. Agr. Sci. Tech., 4: 70- 76.
5. Akpinar, k., Bicer, Y. and Cetinkay, F. 2006. Modelling of Thin Layer Drying of Parsley Leaves in a Convective Dryer and Under Open Sun. J. Food Eng., 3: 308-315.
6. Anonymous. Wealth of Indian raw materials (Vol. 8, p. 321). New Delhi: Publication and Information Directorate, Council of Scientific and Industrial Research; 1969.
7. Arslan, D. and Ozcan, M. M. 2010. Study the Effect of Sun, Oven and Microwave Drying on Quality of Onion Slices. J. Food Sci. Tech., 43: 1121-1127.
8. Bala, B. K. and Woods, J. L. 1992. Thin Layer Drying Models for Malt. J. Food Eng., 16(4): 239-249.
9. Daraei Garmakhany, A., Kashaninejad, M., Amiri, S. S. and Mehregan Nikoo, A. R. 2013. Effect of Moisture Content on Biophysical Properties of Pomegranate Seeds. Minerva Biotechnol., 25(1): 9-16.
10. Dhandar, D. G. and Singh, D. B. 2002. Current Status and Future needs for the Development of Pomegranate. In: Programme and Discussion Papers. New Delhi: National Horticulture Conference; P 12.
11. Diamante, L. M., Ihns, R., Savage, G. P. and Vanhanen, L. 2010. A New Mathematical Model for Thin Layer Drying of Fruits. J. Food Sci. Tech., 45: 1956-1962.
12. Doymaz, I. 2004. Convective Air Drying Characteristics of Thin Layer Carrots. J. Food Eng., 61: 359-364.
13. Doymaz, I. 2012. Prediction of Drying Characteristics of Pomegranate Arils. Food Anal. Method., 5(4): 841- 848.
14. Ertekin, C. and Yaldiz, O. 2004. Drying of Eggplant and Selection of a Suitable Thin Layer Drying Model. J. Food Eng., 63: 349–359.
15. Garau, M. C., Simal, S., Rosselló, C. and Femenia. A. 2007. Effect of Air-Drying Temperature on Physico-Chemical Properties of Dietary Fiber and Antioxidant Capacity of Orange (Citrus aurantium v. Canoneta) By-Products. Food Chem., 104: 1014-1024.
16. Giri, S. K. and Prasad, S. 2007. Optimization of Microwave-Vacuum Drying of Button Mushrooms Using Response Surface Methodology. Dry Technol., 25(5): 901–911.
17. Golpour, I., Amiri Chayjan, R., Amiri Parian, J. and Khazaei, J. 2015. Prediction of Paddy Moisture Content during Thin Layer Drying Using Machine Vision and Artificial Neural Networks. J. Agr. Sci. Tech., 17(2): 287-298.
18. Guiné, R. P. F., Pinho, S. and Barroca, M. J. 2011. Study of the Convective Drying of Pumpkin (Cucurbita maxima). Food Bioprod. Process., 89: 422-428.
19. Henderson, S. and Pabis, S. 1961. Grain Drying Theory. 1. Temperature Affection Drying Coefficient. J. Agr. Eng., 6: 169-170.
20. Hodgson, R. W. 1971. The Pomegranate. Calif. Agric. Export Stat. Bull. 276: 163-192.
21. Kadam, D. M., Rai, D. R., Patil, R. T., Wilson, R. A., Kaur, S. and Kumar, R. 2011. Quality of Fresh and Stored Foam Mat Dried Mandarin Powder. Int. J. Food Sci. Tech., 46: 793-799.
22. Kingsly, A. R. P. and Singh, D. B. 2007. Drying Kinetics of Pomegranate Arils. J. Food Eng., 79(2): 741-749.
23. Martin-Esparza, M. E. M., Contreras, C., Chiralt, A. and Martınez-Navarrete, N. 2008. Influence of Microwave Application on Convective Drying: Effects on Drying Kinetics and Optical and Mechanical Properties of Apple and Strawberry. J. Food Eng., 88: 55–64.
24. Menges H. O. and Ertekin, C. 2006. Mathematical Modeling of Thin Layer Drying of Golden Apples. J. Food Eng., 77: 119–125.
25. Mokhtarian, M. and Daraei Garmakhany, A. 2017. Prediction of Ultrasonic Osmotic Dehydration Properties of Courgette by ANN. Qual. Assur. Saf. Crop. DOI: http://dx.doi.org/10.3920/QAS2015.0662.
26. Mokhtarian, M., Heydari Majd, M., Koushki, F., Bakhshabadi, H., Daraei Garmakhany, A. and Rashidzadeh, Sh. 2014a. Optimization of Pumpkin Mass Transfer Kinetic during Osmotic Dehydration Using Artificial Neural Network and Response Surface Methodology Modelling. Qual. Assur. Saf. Crop. 6(2): 201- 214.
27. Mokhtarian, M., Koushki, F., Bakhshabadi, H., Askari, B., Daraei Garmakhany, A. and Rashidzadeh, Sh. 2014b. Feasibility Investigation of Using Artificial Neural Network in Process Monitoring of Pumpkin Air Drying. Qual. Assur. Saf. Crop. 6(2): 191- 199.
28. Motevali, A., Minaei, S., Ahmadi, E. and Azizi, M. H. 2012. Mathematical Models of Drying Pomegranate Arils in Vacuum and Microwave Dryer. J. Agr. Sci. Tech., 14: 311-325.
29. Nagy, P., Shaw, P. E. and Wordowski, W. F. 1990. Fruit of Tropical and Subtropical Origin. Florida Science Source. 328-47.
30. Ozbek, B. and Dadali, G. 2007. Thin-Layer Drying Characteristics and Modelling of Mint Leaves Undergoing Microwave Treatment. J. Food Eng., 83: 541–549.
31. Page, G. 1949. Factors Influencing the Maximum Rates of Air Drying Shelled Corn in Thin Layers. Lafayette, Purdue University.
32. Parashar, A., Gupta, S. K. and Kumar, A. 2009. Studies Separation Techniques of Pomegranate Seeds and Their Effect on Quality of Anardana. Afr. J. Biochem. Res., 3(10): 340-343.
33. Prasad, S. K. and Giri, S. 2007. Drying Kinetics and Rehydration Characteristics of Microwave-Vacuum and Convective Hot-Air Dried Mushrooms. J. Food Eng., 78: 512–521.
34. Riyahi, R., Rafiee, S., Delvand, M. J. and Keyhani, A. 2011. Some Physical Characteristics of Pomegranate: Seeds and Arils. J. Agr. Tech., 7(6): 1523-1537.
35. Saxena, A. K., Mevah, J. K. and Berry, S. K. 1987. Pomegranate -post harvest Technology, Chemistry and Processing. Indian Food Packer. 1: 43.
36. Singh, N. J. and Pandey, R. K. 2012. Convective Air Drying Characteristics of Sweet Potato Cubs. Food Bioprod. Process., 90: 317- 322.
37. Soysal, Y., Öztekin, S. and Eren, Ö. 2006. Microwave Drying of Parsley: Modelling Kinetics, and Energy Aspects. Biosyst. Eng., 4: 403-413.
38. Taheri-Garavand, A., Rafiee, S. and Keyhani, A. 2011. Mathematical Modeling of Thin Layer Drying Kinetics of Tomato Influence of Air Dryer Conditions. Int Trans. J. Eng. Manage. Sci. Tech., 2: 147–160.
39. Tavakolipour, H. and Mokhtarian, M. 2012. Neural Network Approaches for Prediction of Pistachio Drying Kinetics. Int. J. Food Eng., 8: 3-42.
40. Togrul, I. and Pehlivan, D. 2004. Modelling of Thin-Layer Drying Kinetics of Some Fruits under Open-Air Sun Drying Process. J. Food Eng., 65: 413–25.
41. Westerman, P. W., White, G. M. and Ross, I. J. 1973. Relative Humidity Effect on the High Temperature Drying of Shelled Corn. Trans. ASAE. University of Kentucky, America.
42. Zhang, M., Tang, J., Mujumdar, A. S. and Wang, S. 2006. Trends in Microwave- Related Drying of Fruits and Vegetables. Trend. Food Sci. Technol., 17: 524-534.
Journal of Agricultural Science and Technology
Volume 19, Issue 7
November and December 2017
Pages 1527-1537