OCHOA MARTINEZ, Claudia Isabel. Artificial neural network in response of mass transfer parameters predictions (moisture loss and solid gain) during osmotic dehydration of fruits. []. , 65, 4, pp.318-325. ISSN 0120-2812.  https://doi.org/10.15446/acag.v65n4.50382.

Models for the prediction of water loss (ML) and solid gain (SG) in osmotic dehydration process based on artificial neural network (ANN) perform better as compared to other models developed for osmotic dehydration, because these models mathematically correlate a wide quantity of processing variables with ML and SG. The main advantage of these models is that they are predictive rather than correlative, also these models can be easily implemented in a spreadsheet, and they are very useful and practical for process design and control. The aim of this work is to use a developed model based on ANN to predict outcomes in osmotic dehydration processes. Predictions were made with different process conditions and were validate by using experimental data reported in literature. Good predictions of ML (MRE 19%) and variable behavior for SG (MRE: 62%) were obtained.

: Agroindustrial applications; ANN model; drying; fruits; moisture.

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