In this work, the nonlinear dynamical model of a lactic fermentation process is widely analysed and control experiments are achieved. More precisely, a production of yogurt by Streptococcus termophilus and Lactobacillus bulgaricus in batch operation is taken into consideration. The process model is expressed by a set of nonlinear differential equations that describes the evolution of concentrations in the fermentation process. To validate the model, several simulations are performed in the Matlab programming and development environment. Furthermore, two experimental setups are used for batch fermentation experiments. From control point of view, the temperature and the pH are the basic dynamical factors that need monitoring and control in order to regulate the microbial growth and the lactic acid production. Different control architectures and tuning procedures are implemented. Specialized data acquisition and control software tools are used to perform the experiments. By using the features of these software tools, the time evolution of various process variables can be plotted and analysed. Several comparisons between the results obtained via simulation and with the two bioreactor setups are achieved.
This paper’s main contribution is to validate the dynamical model of a lactic fermentation process by using simulators and laboratory bioreactors. A production of yogurt by Streptococcus termophilus and Lactobacillus bulgaricus in batch operation is considered. Different control architectures and tuning procedures are implemented, and several comparisons are achieved.
Biotechnology, Fermentation processes, Modelling, Control engineering.
ADCOSBIO, 2015. ADCOSBIO Technical Report, Phase II. University of Craiova, UEFISCDI, PN-II-PT-PCCA-2013-4-0544.
BIOSTAT, 2006. BIOSTAT a plus operating manual, Micro – DCU system operating manual, MFCS/DA user manual. Sartorius BBI Systems GmbH.
Caraman, S. and D. Selișteanu, 2013. Pilot and laboratory bioreactors and equipment for fermentation bioprocesses and wastewater treatment processes. Workshop on Optimization Based Control and Estimation, Supélec, Gif sur Yvette, France.
Dima, A., 2015. Monitoring of biotechnological processes parameters. Master Thesis, University of Craiova.
Dochain, D., 2008. Automatic control of bioprocesses. London, UK: ISTE and John Wiley & Sons.
Eppendorf, E., 2012. New brunswick BioFlo®/CelliGen®115 benchtop fermentor & bioreactor operating manual, M1369-0050.
Kostov, G., M. Angelov, P. Koprinkova-Hristova, M. Ignatova and A. Orsoni, 2009. Modeling of oxygen effect on kinetics of batch fermentation process for yogurt starter culture formation. Proc. of 23rd European Conference on Modelling and Simulation, Madrid, Spain, IBS-109.
Lan, C.Q., G. Oddone, D.A. Mills and D.E. Block, 2006. Kinetics of lactococcus lactis growth and metabolite formation under aerobic and anaerobic conditions in the presence or absence of hemin. Biotechnology and Bioengineering, 95(6): 1070-1080. View at Google Scholar | View at Publisher
Nisipeanu, I.A., E. Bunciu and R. Stănică, 2011. Bioprocesses parameters control in the case of a BIOSTAT A PLUS bioreactor. Annals of the Univ. of Craiova, Series: Automation, Computers, Electronics and Mechatronics, 8(2): 31-35. View at Google Scholar
Selişteanu, D., E. Petre and V. Răsvan, 2007. Sliding mode and adaptive sliding-mode control of a class of nonlinear bioprocesses. International Journal of Adaptive Control and Signal Processing, 21(8-9): 795-822. View at Google Scholar | View at Publisher
Taskila, S. and H. Ojamo, 2013. The current status and future expectations in industrial production of lactic acid by lactic acid bacteria. In: Lactic acid bacteria – R & D for food, health and livestock purposes (M. Kongo Ed.). InTech, Rijeka, Croatia.. pp: 615-632.
This work was supported by UEFISCDI, Project ADCOSBIO no. 211/2014, PN-II-PT-PCCA-2013-4-0544.
The authors declare that they have no competing interests.
All authors contributed equally to the conception and design of the study.