Inulinase production in a batch bioreactor using agroindustrial residues as the substrate: experimental data and modeling |
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Authors: | Marcio A. Mazutti Marcos L. Corazza Francisco Maugeri Filho Maria Isabel Rodrigues Fernanda C. Corazza Helen Treichel |
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Affiliation: | (1) Department of Food Engineering, URI, Campus de Erechim, P. O. Box 743, Erechim, RS, CEP 99700-000, Brazil;(2) Department of Food Engineering, Faculty of Food Engineering, UNICAMP, P. O. Box 6121, Campinas, SP, CEP 13083-862, Brazil |
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Abstract: | The production of inulinase employing agroindustrial residues as the substrate is a good alternative to reduce production costs and to minimize the environmental impact of disposing these residues in the environment. This study focused on the use of a phenomenological model and an artificial neural network (ANN) to simulate the inulinase production during the batch cultivation of the yeast Kluyveromyces marxianus NRRL Y-7571, employing a medium containing agroindustrial residues such as molasses, corn steep liquor and yeast extract. It was concluded that due to the complexity of the medium composition it was rather difficult to use a phenomenological model with sufficient accuracy. For this reason, an alternative and more cost-effective methodology based on ANN was adopted. The predictive capacity of the ANN was superior to that of the phenomenological model, indicating that the neural network approach could be used as an alternative in the predictive modeling of complex batch cultivations. |
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Keywords: | Inulinase Kluyveromyces marxianus NRRL Y-7571 Phenomenological model ANN |
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