Aghajanzadeh, Sara, Ganjeh, Mohammad, Jafari, Seid Mahdi, Kashaninejad, Mahdi, Ziaiifar, Aman Mohammad. (1399). Prediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks. , 3(2), 95-100. doi: 10.22059/jfabe.2020.306719.1057
Sara Aghajanzadeh; Mohammad Ganjeh; Seid Mahdi Jafari; Mahdi Kashaninejad; Aman Mohammad Ziaiifar. "Prediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks". , 3, 2, 1399, 95-100. doi: 10.22059/jfabe.2020.306719.1057
Aghajanzadeh, Sara, Ganjeh, Mohammad, Jafari, Seid Mahdi, Kashaninejad, Mahdi, Ziaiifar, Aman Mohammad. (1399). 'Prediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks', , 3(2), pp. 95-100. doi: 10.22059/jfabe.2020.306719.1057
Aghajanzadeh, Sara, Ganjeh, Mohammad, Jafari, Seid Mahdi, Kashaninejad, Mahdi, Ziaiifar, Aman Mohammad. Prediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks. , 1399; 3(2): 95-100. doi: 10.22059/jfabe.2020.306719.1057

Prediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks

Journal of Food and Bioprocess Engineering
دوره 3، شماره 2، اسفند 2020، صفحه 95-100    اصل مقاله (672.02 K)
نوع مقاله: Original research
شناسه دیجیتال (DOI): 10.22059/jfabe.2020.306719.1057
نویسندگان
Sara Aghajanzadeh1؛ Mohammad Ganjeh2؛ Seid Mahdi Jafari1؛ Mahdi Kashaninejad1؛ Aman Mohammad Ziaiifar* 1
1Department of Food Materials and Process Design Engineering, Faculty of Food Science and Technology, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
2Department of Food Science, Kherad institute of higher education, Bushehr, Iran
چکیده
Thermal processing of the key lime juice leads to the inactivation of pectin methylesterase (PME) and the degradation of ascorbic acid (AA). These changes affect directly the cloud stability and color of the juice. In this study, an artificial neural network (ANN) model was applied for designing and developing an intelligent system for prediction of the thermal processing effects on the physicochemical properties of key lime juice during conventional and infrared (IR) heating. The inputs of this network were time and temperature and the outputs were changes in PME activity, AA content, browning index (BI) and also cloud stability of the juice.The feed-forward neural network with a logarithmic transfer function, Levenberg–Marquardt training algorithm and eight neurons in the hidden layer (topology 2-8-4) was chosen as the best ANN model (R2> 0.95, RMSE=0.47 and SE=0.28). The predicted values using the optimal ANN model vs. experimental values represented a correlation coefficient higher than 0.95 and 0.90 during IR and conventional thermal processing, respectively. This model can therefore be applied in prediction of the effects of thermal processing on the physicochemical properties of the lime juice in pilot plants, processing factories and online monitoring.
کلیدواژه‌ها
IR thermal processing؛ Physicochemical properties؛ Key lime juice؛ ANN؛ Modeling
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