Mathematical modeling of Kluyveromyces marxianus growth in solid-state fermentation using a packed-bed bioreactor |
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Authors: | Marcio A Mazutti Giovani Zabot Gabriela Boni Aline Skovronski Débora de Oliveira Marco Di Luccio Maria Isabel Rodrigues Francisco Maugeri Helen Treichel |
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Institution: | (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, University of Campinas, UNICAMP, P.O. Box 6121, Campinas, SP, CEP 13083-862, Brazil; |
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Abstract: | This work investigated the growth of Kluyveromyces marxianus NRRL Y-7571 in solid-state fermentation in a medium composed of sugarcane bagasse, molasses, corn steep liquor and soybean
meal within a packed-bed bioreactor. Seven experimental runs were carried out to evaluate the effects of flow rate and inlet
air temperature on the following microbial rates: cell mass production, total reducing sugar and oxygen consumption, carbon
dioxide and ethanol production, metabolic heat and water generation. A mathematical model based on an artificial neural network
was developed to predict the above-mentioned microbial rates as a function of the fermentation time, initial total reducing
sugar concentration, inlet and outlet air temperatures. The results showed that the microbial rates were temperature dependent
for the range 27–50°C. The proposed model efficiently predicted the microbial rates, indicating that the neural network approach
could be used to simulate the microbial growth in SSF. |
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