<b>Analytical modeling and numerical optimization of the biosurfactants production in solid-state fermentation by <i>Aspergillus fumigatus</i></b> - doi: 10.4025/actascitechnol.v36i1.17818

Autores

  • Gabriel Castiglioni Universidade Federal do Rio Grande
  • George Stanescu Universidade Federal do Paraná
  • Luiz Alberto Oliveira Rocha Universidade Federal do Rio Grande
  • Jorge Alberto Vieira Costa Universidade Federal do Rio Grande

DOI:

https://doi.org/10.4025/actascitechnol.v36i1.17818

Palavras-chave:

Aspergillus fumigatus, biosurfactant, solid-state fermentation

Resumo

This is an experimental, analytical and numerical study to optimize the biosurfactants production in solid-state fermentation of a medium containing rice straw and minced rice bran inoculated with Aspergillus fumigatus. The goal of this work was to analytically model the biosurfactants production in solid-state fermentation into a column fixed bed bioreactor. The Least-Squares Method was used to adjust the emulsification activity experimental values to a quadratic function semi-empirical model. Control variables were nutritional conditions, the fermentation time and the aeration. The mathematical model is validated against experimental results and then used to predict the maximum emulsification activity for different nutritional conditions and aerations. Based on the semi-empirical model the maximum emulsification activity with no additional hydrocarbon sources was 8.16 UE·g-1 for 112 hours. When diesel oil was used the predicted maximum emulsification activity was 8.10 UE·g-1 for 108 hours.

 

 

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Publicado

2014-01-07

Como Citar

Castiglioni, G., Stanescu, G., Rocha, L. A. O., & Costa, J. A. V. (2014). <b>Analytical modeling and numerical optimization of the biosurfactants production in solid-state fermentation by <i>Aspergillus fumigatus</i></b> - doi: 10.4025/actascitechnol.v36i1.17818. Acta Scientiarum. Technology, 36(1), 61–67. https://doi.org/10.4025/actascitechnol.v36i1.17818

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Engenharia Quí­mica

 

0.8
2019CiteScore
 
 
36th percentile
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0.8
2019CiteScore
 
 
36th percentile
Powered by  Scopus

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