Grasas y Aceites, Vol 65, No 4 (2014)

The use of artificial neural network modeling to represent the process of concentration by molecular distillation of omega-3 from squid oil


https://doi.org/10.3989/gya.0231141

P. Rossi
Facultad de Ingeniería, Universidad Nacional de Río Cuarto, Argentina

M. F. Gayol
Facultad de Ingeniería, Universidad Nacional de Río Cuarto, Argentina

C. Renaudo
Facultad de Ingeniería, Universidad Nacional de Río Cuarto, Argentina

M. C. Pramparo
Facultad de Ingeniería, Universidad Nacional de Río Cuarto, Argentina

V. Nepote
ICTA, Facultad de Ciencias Exactas, Físicas y Naturales (UNC), IMBIV-CONICET, Argentina

N. R. Grosso
Química Biológica, Facultad de Ciencias Agropecuarias (UNC), IMBIV-CONICET, Argentina

Abstract


The concentration of omega-3 compounds obtained for the esterification of squid oil by molecular distillation was carried out in two stages. This operation can process these thermolabile and high molecular weight components at very low temperatures. Given the mathematical complexity of the theoretical model, artificial neural networks (ANN) have provided an alternative to a classical computing analysis. The objective of this study was to create a predictive model using artificial neural network techniques to represent the concentration process of omega-3 compounds obtained from squid oil using molecular distillation. Another objective of this study was to analyze the performance of two different alternatives of ANN modeling; one of them is a model that represents all variables in the process and the other is a global model that simulates only the input and output variables of the process. The alternative of the ANN global model showed the best fit to the experimental data.

Keywords


Artificial Neural Networks; DHA; EPA; Molecular Distillation; Omega-3

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