Volume 21, Issue 155 (2024)
FSCT 2024, 21(155): 213-224 |
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Salehi F, Ghazvineh S, Amiri M. Investigating the effect of microwave power on moisture diffusivity and drying kinetics of faba beans: An experimental and modeling study. FSCT 2024; 21 (155) :213-224
URL: http://fsct.modares.ac.ir/article-7-76484-en.html
URL: http://fsct.modares.ac.ir/article-7-76484-en.html
1- Associate Professor, Department of Food Science and Technology, Faculty of Food Industry, Bu-Ali Sina University, Hamedan, Iran , fs1446@yahoo.com
2- BSc Student, Department of Food Science and Technology, Faculty of Food Industry, Bu-Ali Sina University, Hamedan, Iran
2- BSc Student, Department of Food Science and Technology, Faculty of Food Industry, Bu-Ali Sina University, Hamedan, Iran
Abstract: (42 Views)
In this research, the influence of microwave power on drying behavior and moisture diffusivity of faba bean (dehulled) was investigated. The fresh samples were dried as single layers at four different power levels (220, 330, 440, and 550 W). The results showed that the processing time was significantly decreased with increasing power (p<0.05). Six kinetic models were examined to simulate the experimental drying kinetics and the Midilli model showed the best performance. The average values of effective moisture diffusivity were calculated to be in the range of 1.92×10-9 m2/s to 5.16×10-9 m2/s, and increased significantly with increasing microwave power (p<0.05). The average rehydration ratio of dried faba beans changed from 239.12% to 325.05%, and increased with increasing microwave power. In addition, in this study a genetic algorithm-artificial neural network method was used for prediction of the moisture ratio of faba beans. This network structure has two inputs of microwave power and treatment time. The optimal network contained 10 neurons in hidden later was able to predict the moisture ratio of faba beans with a coefficient of determination (r) of 0.994. Sensitivity analysis results showed that treatment time is the most sensitive factor in predicting the moisture ratio of faba beans. In summary, the predictions of the genetic algorithm-artificial neural network model have high agreement with the testing datasets and they are useful for understanding and controlling the factors affecting the drying rate of faba beans during microwave drying.
Keywords: Artificial neural network, Effective moisture diffusivity, Genetic algorithm, Midilli model, Rehydration
Article Type: Original Research |
Subject:
Food Chemistry
Received: 2024/08/9 | Accepted: 2024/10/29 | Published: 2024/12/21
Received: 2024/08/9 | Accepted: 2024/10/29 | Published: 2024/12/21
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