Inulinase production in a batch bioreactor using agroindustrial residues as the substrate: experimental data and modeling.
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.
Mazutti
Marcio A
MA
Department of Food Engineering, URI, Campus de Erechim, Erechim, RS CEP 99700-000, Brazil. marciom@fea.unicamp.br.
Corazza
Marcos L
ML
Maugeri Filho
Francisco
F
Rodrigues
Maria Isabel
MI
Corazza
Fernanda C
FC
Treichel
Helen
H
D000383:Agriculture / Q000379:methods*; D018533:Biomass; D019149:Bioreactors; D003470:Culture Media; D005285:Fermentation; D006026:Glycoside Hydrolases / Q000096:biosynthesis* / Q000737:chemistry / Q000378:metabolism; D007218:Industrial Microbiology / Q000295:instrumentation* / Q000379:methods*; D007700:Kinetics; D007716:Kluyveromyces / Q000378:metabolism; D008962:Models, Theoretical; D008965:Molasses; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D013696:Temperature; D003313:Zea mays / Q000378:metabolism
D003470:Culture Media; D006026:Glycoside Hydrolases; C023086:inulinase