Applied Microbiology and Biotechnology

, Volume 41, Issue 2, pp 192–196 | Cite as

Modelling the acidifying activity profile of Lactobacillus bulgaricus cultures

  • B. S. Torrestiana
  • E. Brito de la Fuente
  • C. Lacroix
  • L. Choplin
Biotechnology Original Paper

Abstract

A model that fully describes the typical pH(t) profile representing the lactic acid production kinetics of Lactobacillus bulgaricus cultures is reported. The model, a four-parameter function [pH = (A−D)/(1 + (t/C)B) + D], is able to fit any change on the experimental pH-time curves, due to variations on the inoculum cell concentration of the culture. The four fitting parameters(A, B, C and D) of this model are closely related to the lactic acid fermentation and they have a physical meaning. Parameters A and D represent the initial and final pH of the culture, respectively. Parameter B is related to the slope of the linear decreasing region from the pH-time curve and C represents the time at which half of the total decrement of pH is achieved. The proposed model can be used not only for evaluating and comparing the acidifying capacity of homolactic cultures but also for predictions of final fermentation times.

Keywords

Fermentation Lactic Acid Lactobacillus Acid Production Activity Profile 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Latrille E, Picque D, Perret B, Corrieu G (1992) Characterizing acidification kinetics by measuring pH and electrical conductivity in batch thermophilic lactic fermentations. J Ferm and Bioeng 74: 32–38Google Scholar
  2. Latrille E, Corrieu G, Thibault J (1993) pH prediction and final fermentation time determination in lactic acid batch fermentations. European Symposium on Computer Aided Process Engineering (ESCAPE) 2 (5–7 Oct. 1992) Toulouse, France. Supplement to “Computer & Chemical Eng”. Vol. 17: S423-S428Google Scholar
  3. Lievense LC, van't Riet K, Noomen A (1990) Measuring and modelling the glucose-fermenting activity of Lactobacillus plantarum. Appl Microbiol Biotechnol 32: 669–673Google Scholar
  4. Marquardt DW (1963) An algorithm for least squares estimation of nonlinear parameters. J Soc Ind Appl Math 11: 431–444MATHGoogle Scholar
  5. Picque D, Perret B, Latrille E, Corrieu G (1992) Caracterisation et classification de bacteries lactiques a partir de la mesure de leur cinetique d'acidification. Lebensm Wiss u Technol 25: 181–186Google Scholar
  6. Soet JJ de, Graaff J de (1988) An improved method with computer registration of fermentation activities of microorganisms. J Ferment Technol 66: 239–242Google Scholar
  7. Spinnler HE, Corrieu G (1989) Automatic method to quantify starter activity based on pH measurement. J dairy Res 56: 755–764Google Scholar

Copyright information

© Springer-Verlag 1994

Authors and Affiliations

  • B. S. Torrestiana
    • 1
  • E. Brito de la Fuente
    • 2
  • C. Lacroix
    • 3
  • L. Choplin
    • 1
  1. 1.Chemical Engineering DepartmentUniversité LavalSte-Foy, QuébecCanada
  2. 2.Departamento de Alimentos y BiotecnologiaFacultad de Química, UNAMMéxico, D. F.
  3. 3.Centre de Recherche STELA, Pavillon ComtoisUniversité LavalQuébecCanada

Personalised recommendations