Application of fractal theory for prediction of shrinkage of dried kiwifruit using artificial neural network and genetic algorithm

Drying Technology

Volumn 29, Issue 8, 2011, Pages 918-925

  Fathi, Milad ^a   Mohebbi, Mohebbat ^a   Razavi, Seyed M A ^a  

^a FERDOWSI UNIVERSITY OF MASHHAD   (Iran)

Author keywords

Artificial neural network; Dried kiwifruit; Fractal dimension; Genetic algorithm; Shrinkage

Indexed keywords

BOX-COUNTING METHOD; COMBINATION OF NEURAL-NETWORK; CORRELATION COEFFICIENT; DETECTION APPROACH; DIGITAL IMAGE; DRIED PRODUCTS; FRACTAL THEORY; HIGH POTENTIAL; INTELLIGENT MODELS; KIWIFRUITS; OPTIMAL MODEL;

EDGE DETECTION; FRACTAL DIMENSION; NEURAL NETWORKS; SHRINKAGE;

GENETIC ALGORITHMS;

EID: 84861029763     PISSN: 07373937     EISSN: 15322300     Source Type: Journal    
DOI: 10.1080/07373937.2011.553755     Document Type: Article

References (33)

1. Rodrigues, S.; Oliveira, F.I.P.; Gallao, M.I.; Fernandes, F.A.N. Effect of immersion time in osmosis and ultrasound on papaya cell structure during dehydration. Drying Technology 2009, 27(2), 220-225.
2. Chua, K.J.; Mujumdar, A.S.; Chou, S.K.; Hawlader, M.N.A.; Ho, J.C. Convective drying of banana, guava and potato pieces: Effect of cyclical variations of air temperature on drying kinetics and color change. Drying Technology 2000, 18(4), 907-936.
3. Mayor, L.; Sereno, A.M. Modelling shrinkage during convective drying of food materials: A review. Journal of Food Engineering 2004, 61(3), 373-386.
4. Nahimana, H.; Zhang, M.; Mujumdar, A.S.; Ding, Z. Mass transfer modeling and shrinkage consideration during osmotic dehydration of fruits and vegetables. Food Reviews International 1997, 34(4), 387-410.
5. Mandelbrot, B.B. The Fractal Geometry of Nature; W.H. Freeman & Co.: New York, 1977.
6. Xu, P.; Mujumdar, A.S.; Yu, B. Fractal theory on drying: A review. Drying Technology 2008, 26(6), 640-650.
7. Chanona, P.J.J.; Alamilla, B.L.; Farrera, R.R.R.; Quevedo, R.; Aguilera, J.M.; Gutiérrez, L.G.F. Description of the convective air drying of a food model by means of the fractal theory. Food Science and Technology International 2003, 9(3), 207-213.
8. Tang, D.; Marangoni, A. Computer simulation of fractal dimensions of fat crystal networks. Journal of the American Oil Chemists' Society 2006, 83(4), 309-314.
9. Kerdpiboon, S.; Kerr, W.L.; Devahastin, S. Neural network prediction of physical property changes of dried carrot as a function of fractal dimension and moisture content. Food Research International 2006, 39(10), 1110-1118.
10. Kerdpiboon, S.; Devahastin, S. Fractal characterization of some physical properties of a food product under various drying conditions. Drying Technology 2007, 25(1), 135-146.
11. Velazquez-Camilo, O.; Bolaños-Reynoso, E.; Rodriguez, E.; Alvarez-Ramirez, J. Characterization of cane sugar crystallization using image fractal analysis. Journal of Food Engineering 2010, 100(1), 77-84.
12. Ochoa-Martínez, C.I.; Ramaswamy, H.S.; Ayala-Aponte, A.A. ANN-based models for moisture diffusivity coefficient and moisture loss at equilibrium in osmotic dehydration process. Drying Technology 2007, 25(5), 775-783.
13. Zenoozian, M.S.; Devahastin, S.; Razavi, M.A.; Shahidi, F.; Poreza, H.R. Use of artificial neural network and image analysis to predict physical properties of osmotically dehydrated pumpkin. Drying Technology 2008, 26(1), 132-144.
14. Youssefi, S.; Emam-Djomeh, Z.; Mousavi, S.M. Comparison of artificial neural network (ANN) and response surface methodology (RSM) in the prediction of quality parameters of spray-dried pomegranate juice. Drying Technology 2009, 27(7), 910-917.
15. Islam, M.R.; Sablani, S.S.; Mujumdar, A.S. An artificial neural network model for prediction of drying rates. Drying Technology 2003, 21(9), 1867-1884.
16. Mohebbi, M.; Akbarzadeh-T, M.-R.; Shahidi, F.; Moussavi, M.; Ghoddusi, H.-B. Computer vision systems (CVS) for moisture content estimation in dehydrated shrimp. Computers and Electronics in Agriculture 2009, 69(2), 128-134.
17. Fathi, M.; Mohebbi, M.; Razavi, S. Application of image analysis and artificial neural network to predict mass transfer kinetics and color changes of osmotically dehydrated kiwifruit. Food and Bioprocess Technology (in press), DOI: 10.1007=s11947-009-0222-y
18. Morimoto, T. Genetic algorithm, in food and bioprocess modeling techniques. In Handbook of Food and Bioprocess Modeling Techniques; Sablani, S.S., Datta, A.K., Shafiur Rahman, M., Mujumdar, A.S., Ed.; CRC Press: New York, 2006.
19. Mohebbi, M.; Barouei, J.; Akbarzadeh-T, M.R.; Rowhanimanesh, A.R.; Habibi-Najafi, M.B.; Yavarmanesh, M. Modeling and optimization of viscosity in enzyme-modified cheese by fuzzy logic and genetic algorithm. Computers and Electronics in Agriculture 2008, 62(2), 260-265.
20. Liu, X.; Chen, X.; Wu, W.; Peng, G. A neural network for predicting moisture content of grain drying process using genetic algorithm. Food Control 2007, 18(8), 928-933.
21. Shafiur Rahman, M. Mass-volume-area-related properties of foods. In Engineering Properties of Food; Rao, M.A., Rizvi, S.S.H., Datta, A.K., Eds.; CRC Press: Boca Raton, FL, 2005; 1-39.
22. Razavi, S.M.A.; Fathi, M. Moisture-dependent physical properties of grape (vitis venifera L.) seed. The Philippine Agricultural Scientist 2009, 92(2), 201-212.
23. Quevedo, R.; Aguilera, J.; Pedreschi, F. Color of salmon fillets by computer vision and sensory panel. Food and Bioprocess Technology 2010, 3(5), 637-643.
24. Ridler, T.W.; Calvard, S. Picture thresholding using an iterative selection method. Systems, Man and Cybernetics, IEEE Transactions 1978, 8(8), 630-632.
25. Castleman, K. Digital Image Processing; Prentice Hall: Englewood Cliffs, NJ, 1996.
26. Alamilla-Beltrán, L.; Chanona-Pérez, J.J.; Jiménez-Aparicio, A.R.; Gutiérrez-López, G.F. Description of morphological changes of particles along spray drying. Journal of Food Engineering 2005, 67(1-2), 179-184.
27. Campos-Mendiola, R.; Hernández-Sánchez, H.; Chanona-Pérez, J.J.; Alamilla-Beltrán, L.; Jiménez-Aparicio, A.; Fito, P.; Gutiérrez-López, G.F. Non-isotropic shrinkage and interfaces during convective drying of potato slabs within the frame of the systematic approach to food engineering systems (SAFES) methodology. Journal of Food Engineering 2007, 83(2), 285-292.
28. Salvador, P.; Toldrà, M.; Saguer, E.; Carretero, C.; Parés, D. Microstructure-function relationships of heat-induced gels of porcine haemoglobin. Food Hydrocolloids 2009, 23(7), 1654-1659.
29. Peitgen, H.O.; Jürgens, H.; Saupe, D. Chaos and Fractal; Frontiers of Science: New York, 2004.
30. Heckerling, P.S.; Gerber, B.S.; Tape, T.G.; Wigton, R.S. Use of genetic algorithms for neural networks to predict community-acquired pneumonia. Artificial Intelligence in Medicine 2004, 30(1), 71-84.
31. Izadifar, M.; Jahromi, M.Z. Application of genetic algorithm for optimization of vegetable oil hydrogenation process. Journal of Food Engineering 2007, 78(1), 1-8.
32. Mohebbi, A.; Taheri, M.; Soltani, A. A neural network for predicting saturated liquid density using genetic algorithm for pure and mixed refrigerants. International Journal of Refrigeration 2008, 31(8), 1317-1327.
33. Mujumdar, A.S. Drying Technology in Agriculture and Food Sciences; Science Publishers: Enfield, NH, 2000.