Contact Us

For Marketing, Sales and Subscriptions Inquiries
Rockefeller Center, 45 Rockefeller Plaza
20th Flr Unit #5, New York, NY 10111
United States

Conference List

Journal of Food Technology Research

March 2017, Volume 4, 1, pp 7-15

Experimental Model Validation and Control of a Lactic Fermentation Process

Dan Selisteanu


Monica Roman


Dorin Sendrescu

Dan Selisteanu 1 ,

Monica Roman 1 Dorin Sendrescu 1 
  1. Department of Automatic Control and Electronics, University of Craiova, Romania 1

Pages: 7-15

DOI: 10.18488/journal.58.2017.41.7.15

Share :

Article History:

Received: 25 January, 2017
Revised: 17 March, 2017
Accepted: 30 March, 2017
Published: 19 April, 2017


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.

Contribution/ Originality
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.



  1. ADCOSBIO, 2015. ADCOSBIO Technical Report, Phase II. University of Craiova, UEFISCDI, PN-II-PT-PCCA-2013-4-0544.
  2. BIOSTAT, 2006. BIOSTAT a plus operating manual, Micro – DCU system operating manual, MFCS/DA user manual. Sartorius BBI Systems GmbH.
  3. 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.
  4. Dima, A., 2015. Monitoring of biotechnological processes parameters. Master Thesis, University of Craiova.
  5. Dochain, D., 2008. Automatic control of bioprocesses. London, UK: ISTE and John Wiley & Sons.
  6. Eppendorf, E., 2012. New brunswick BioFlo®/CelliGen®115 benchtop fermentor & bioreactor operating manual, M1369-0050.
  7. 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.
  8. 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
  9. 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 
  10. 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
  11. 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.


Google Scholor ideas Microsoft Academic Search bing Google Scholor


This work was supported by UEFISCDI, Project ADCOSBIO no. 211/2014, PN-II-PT-PCCA-2013-4-0544.

Competing Interests:

The authors declare that they have no competing interests.


All authors contributed equally to the conception and design of the study.

Related Article

( 1 ) Biochemical and Electron Microscopic Changes Induced by Giardia in Experimentally Infected Lambs
( 2 ) Experimental Model Validation and Control of a Lactic Fermentation Process
( 3 ) Monte Carlo Modeling for Aflatoxin B1 Distribution in Pistachio Samples: A Prerequisite for Sampling Plan Validation
( 4 ) Development of a Mathematical Model for Angle of Soil Failure Plane in Case of 3-Dimenssional Cutting
( 6 ) Runoff Response to Climate Variability: An Analysis of Thika River Basin in Kenya Using Hydrological Simulation Model (Hysim)
( 7 ) Forecasting Goat Milk Production in Turkey Using Artificial Neural Networks and Box-Jenkins Models
( 8 ) Uncertainty Analysis and Calibration of Swat Model for Estimating Impacts of Conservation Methods on Streamflow and Sediment Yield in Thika River Catchment, Kenya
( 9 ) Tabu-Genetic Algorithm-Based Model for Poultry Feed Formulation
( 10 ) Modelling and Optimization of Rice (Oryza sativa L.) Paddy Pre-Treatments for Optimum Chemical Property using Response Surface Methodology
( 11 ) Application of Analytical Hierarchical Process (AHP) in Development of Suitability Model for Rice Production in Taraba State
( 12 ) A Mathematical Model for Dehydration by Successive Pressure Drops: Simulation of Discarded Potatoes Dehydration
( 15 ) Growing Jatropha Curcas and Jatropha Gossypiifolia as a Interculture with Sunflower for Control of Meloidogyne Javanica in Egypt
( 17 ) Insecticide Spraying Regime to Control Insect Pest of Cowpea: Management and Monitored Application of Cypermethrin in Lomami Province, DR Congo
( 18 ) High-Sensitivity Testing of Effectiveness of Citrus Limon, Vitis Vinifera and Citrus Sinensis in the Postharvest Control of Callosobruchus Maculatus Fabricius (Coleoptera: Chrysomelidae) Infestation of Cowpea Seeds
( 19 ) Two Stubborn Storage Insect Pests, Callosobruchus maculatus and Sitophilus zeamais: Biology, Food Security Problems and Control Strategies
( 20 ) On-Farm Evaluation of Conservation Agriculture Practice on Weed Control and Yield of Wheat in Northern Bangladesh
( 21 ) Chemical Control of Alternaria Brown Spot on Mandarins Cultivars in Tunisia
( 22 ) Antifungal Activities of Selected Plant Extracts in In-Vitro Control of Anthracnose and Root Rot Diseases on Cucumber (Cucumis sativus B.)
( 25 ) Small-Scale Milk Processing, Utilization and Marketing of Traditional Dairy Products in Bahir Dar Zuria and Mecha Districts, Northwestern Ethiopia
( 26 ) The Effect of Steaming Process on Fat Soluble Vitamins Content and Fatty Acid Profile in Bluefish and Rainbow Trout Fillets
( 27 ) Variation in Density and Shrinkage between Sawmill and Hand Processed Khaya Senegalensis Woodin Sokoto, North-Western Nigeria
( 29 ) Effect of Tuber Sections, Heat Treatment and Rehydration with Process Chemicals on the Physicochemical Properties of Sweet Potato (Ipomoea Batatas L. (Lam)) Flour
( 30 ) The Oils Refining Process and Contaminants in Edible Oils: A Review
( 31 ) Effects of Inclusion of Processed Grapefruit Pulp on Wheat Flour Biscuit