Skip to main content
SpringerLink
Log in

Discrimination between ethanol inhibition models in a continuous alcoholic fermentation process using flocculating yeast

  • Original Articles
  • Published:
Applied Biochemistry and Biotechnology Aims and scope Submit manuscript

Abstract

Discrimination between different rival models for describing the inhibitory effect of ethanol both on yeast growth and on fermentation was studied for a continuous process of alcoholic fermentation in a tower reactor with recycling of flocculating cells. Models tested include linear, parabolic, hyperbolic, exponential, and generalized nonlinear power-law types. The best expressions were identified under the criteria that all the kinetic parameters should assume acceptable values in a feasible range and should result in the best fit of the experimental data. The kinetic parameters were estimated from steady-state data of several sugar concentrations in feeding stream (S0 = 160, 170, 180, 190, 200 g/L), constant dilution rate (D = 0.2 h-1), recycle ratio (α = 13.6), and temperature (T = 30°C). The best model for the yeast growth was of power-law type, whereas for the product formation the best model was of linear type. These models were able to reproduce the trends of the process variables satisfactorily.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Jones, S. T., Korus, R. A., Admassu, W., and Heimsch, R. C. (1984),Biotechnol. Bioeng. 26, 742–747.

    Article  CAS  Google Scholar 

  2. Paiva, T. C. B., Sato, S., Visconti, A. E. S., and Castro, L. A. B. (1996),Appl. Biochem. Biotechnol. 57/58, 535–541.

    Article  CAS  Google Scholar 

  3. Limtong, S., Nakata, M., Funahashi, H., Yoshida, T., Seki, T., Kumnuanta, J., et al. (1984),J. Ferment. Technol. 62, 55–62.

    CAS  Google Scholar 

  4. Bu’Lock, J. D., Comberbach, D. M., and Ghommidh, C. (1984),Chem. Eng. J. 29, B9-B24.

    Article  CAS  Google Scholar 

  5. Admassu, W., Korus, R. A., and Heimsch, R. C. (1985),Chem. Eng. J. 31, B1-B8.

    Article  CAS  Google Scholar 

  6. Comberbach, D. M., Ghommidh, C., and Bu’Lock, J. D. (1987),Enzyme Microb. Technol. 9, 676–684.

    Article  CAS  Google Scholar 

  7. Monod, J. (1950),Ann. Inst. Pasteur 79(4), 390–410.

    CAS  Google Scholar 

  8. Andrews, J. F. (1968),Biotechnol. Bioeng. 10, 707–723.

    Article  CAS  Google Scholar 

  9. Contois, D. E. (1959),J. Gen. Microbiol. 21, 40–50.

    CAS  Google Scholar 

  10. Ghose, T. K. and Tyagi, R. D. (1979),Biotechnol. Bioeng. 21, 1401–1420.

    Article  CAS  Google Scholar 

  11. Bazua, C. D. and Wilke, C. R. (1977),Biotechnol. Bioeng. Symp. 7, 105–118.

    CAS  Google Scholar 

  12. Novak, M., Strehaiano, P., Moreno, M., and Goma, G. (1981),Biotechnol. Bioeng. 23, 201–211.

    Article  CAS  Google Scholar 

  13. Aiba, S., Shoda, M., and Nagatani, M. (1968),Biotechnol. Bioeng. 10, 845–864.

    Article  CAS  Google Scholar 

  14. Aiba, S. and Shoda, M. (1969),J. Ferment. Technol. 47(12), 790–794.

    CAS  Google Scholar 

  15. Luong, J. H. T. (1985),Biotechnol. Bioeng. 27, 280–285.

    Article  CAS  Google Scholar 

  16. Godia, F., Casa, C., and Sola, C. (1988),J. Chem. Tech. Biotechnol. 41, 155–165.

    CAS  Google Scholar 

  17. Levenspiel, O. (1980),Biotechnol. Bioeng. 22, 1671–1687.

    Article  CAS  Google Scholar 

  18. Lafforgue-Delorme, C., Delorme, P., and Goma, G. (1994),Biotechnol. Lett. 16(7), 741–746.

    Article  CAS  Google Scholar 

  19. Jarzebski, A. B., Malinowski, J. J., and Goma, G. (1989),Biotechnol. Bioeng. 34, 1225–1230.

    Article  CAS  Google Scholar 

  20. Lee, Y., Lee, W. G., Chang, Y. K., and Chang, H. N. (1995),Biotechnol. Lett. 17(8), 791–796.

    Article  CAS  Google Scholar 

  21. Lee, J. M., Pollard, J. F., and Coulman, G. A. (1983),Biotechnol. Bioeng. 25, 497–511.

    Article  CAS  Google Scholar 

  22. Marquardt, D. W. (1963),J. Soc. Indust. Appl. Math. 11(2), 431–441.

    Article  Google Scholar 

  23. Seidel, A. (1990),Chem. Eng. Sci. 45(9), 2970–2973.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departmento de Biotecnologia, Faculdade de Engenhoria Química de Lorena, P.O. Box 116, 12600-000, Lorena, SP, Brazil

    Samuel C. Oliveira, Teresa C. B. Paiva & Alexandre E. S. Visconti

  2. Departamento de Engenharia Química, Escola Politécnica, Universidade de São Paulo, LSCP-taboratório de Simulação e Controle de Processos, P.O. Box 61548, 05424-970, São Paulo, SP, Brazil

    Reinaldo Giudici

Authors
  1. Samuel C. Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Teresa C. B. Paiva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alexandre E. S. Visconti
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Reinaldo Giudici
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Samuel C. Oliveira.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Oliveira, S.C., Paiva, T.C.B., Visconti, A.E.S. et al. Discrimination between ethanol inhibition models in a continuous alcoholic fermentation process using flocculating yeast. Appl Biochem Biotechnol 74, 161–172 (1998). https://doi.org/10.1007/BF02825963

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02825963

Index Entries

Search

Navigation