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Optimization and modeling of laccase production by Trametes versicolor in a bioreactor using statistical experimental design

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Abstract

Experimental design and response surface methodologies were applied to optimize laccase production by Trametes versicolor in a bioreactor. The effects of three factors, initial glucose concentration (0 and 9 g/L), agitation (100 and 180 rpm), and pH (3.0 and 5.0), were evaluated to identify the significant effects and its interactions in the laccase production. The pH of the medium was found to be the most important factor, followed by initial glucose concentration and the interaction of both factors. Agitation did not seem to play an important role in laccase production, nor did the interaction agitation x medium pH and agitation x initial glucose concentration. Response surface analysis showed that an initial glucose concentration of 11 g/L and pH controlled at 5.2 were the optimal conditions for laccase production by T. versicolor. Under these conditions, the predicted value for laccase activity was >10,000 U/L, which is in good agreement with the laccase activity obtained experimentally (11,403 U/L). In addition, a mathematical model for the bioprocess was developed. It is shown that it provides a good description of the experimental profile observed, and that it is capable of predicting biomass growth based on secondary process variables.

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Authors and Affiliations

  1. Departamento de Química, CICECO, COPNA, Universidade de Aveiro, 3810-193, Aveiro, Portugal

    A. P. M. Tavares, M. S. M. Agapito, J. A. P. Coutinho & A. M. R. B. Xavier

  2. Departamento de Engenharia Bioquímica, EQ/UFRJ, Bloco E, Lab. 113, 2194-900, Rio de Janeiro, Brazil

    M. A. Z. Coelho

Authors
  1. A. P. M. Tavares
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  2. M. A. Z. Coelho
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  3. M. S. M. Agapito
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  4. J. A. P. Coutinho
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  5. A. M. R. B. Xavier
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Correspondence to A. M. R. B. Xavier.

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Tavares, A.P.M., Coelho, M.A.Z., Agapito, M.S.M. et al. Optimization and modeling of laccase production by Trametes versicolor in a bioreactor using statistical experimental design. Appl Biochem Biotechnol 134, 233–248 (2006). https://doi.org/10.1385/ABAB:134:3:233

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  • DOI: https://doi.org/10.1385/ABAB:134:3:233

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