Original scientific paper
https://doi.org/10.15255/CABEQ.2018.1387
Software Sensors for Biomass Concentration Estimation in Filamentous Microorganism Cultivation Process
P. Hrnčiřík
orcid.org/0000-0002-6533-4541
; Department of Computing and Control Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Praha 6, Czech Republic
T. Moucha
; Department of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Praha 6, Czech Republic
J. Mareš
; Department of Computing and Control Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Praha 6, Czech Republic
J. Náhlík
; Department of Computing and Control Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Praha 6, Czech Republic
D. Janáčová
; Faculty of Applied Informatics, Tomas Bata University in Zlín, Nad Stráněmi 4511, 760 05 Zlín, Czech Republic
Abstract
In this study, the potential of two software sensors for on-line estimation of biomass concentration during cultivation of filamentous microorganisms is examined. The first sensor is based on common bioreactor off-gas analyses, and uses the assumption of the
biomass concentration linear dependence on the square root of cumulative O2 consumption. Parameters of the semi-empirical data-driven software sensor based on off-gas analysis were calculated from experimental cultivation data using linear regression. The second
sensor is based on biocalorimetry, i.e., the on-line calculation of metabolic heat flux from general enthalpy balance of the bioreactor. The software sensor based on biocalorimetry thus essentially represents a model-driven approach, making use of a fundamental process model based on the enthalpy balance around the bioreactor. This approach has
been combined with the experimental identification of the specific biomass heat production, which represents the main process-specific parameter of the software sensor based on biocalorimetry. For this sensor, the accuracy requirements on the process variable on-line measurements were also analysed. The experimental data from the pilot-scale antibiotics Nystatin production by a bacterium Streptomyces noursei were used to calculate the specific bioprocess heat production value using linear regression. The achieved results enabled us to propose a new on-line indicator calculated as the ratio of the outputs
of both sensors, which can serve as a timely warning of the risk of undesired nutritional conditions of a culture characterized as underfeeding.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Keywords
software sensors; filamentous fermentation; biomass; calorimetry; process monitoring
Hrčak ID:
218891
URI
Publication date:
10.4.2019.
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