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Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions

1
Laboratory of Bioprocess Engineering, Latvian State Institute of Wood Chemistry, LV-1006 Riga, Latvia
2
Latvian Biomedical Research and Study Centre, LV-1067 Riga, Latvia
3
Department of Automation, Kaunas University of Technology, LT-51367 Kaunas, Lithuania
*
Author to whom correspondence should be addressed.
Academic Editor: Andrea Facchinetti
Sensors 2021, 21(4), 1268; https://doi.org/10.3390/s21041268
Received: 20 October 2020 / Revised: 30 January 2021 / Accepted: 4 February 2021 / Published: 10 February 2021
(This article belongs to the Section Intelligent Sensors)
Microbial biomass concentration is a key bioprocess parameter, estimated using various labor, operator and process cross-sensitive techniques, analyzed in a broad context and therefore the subject of correct interpretation. In this paper, the authors present the results of P. pastoris cell density estimation based on off-line (optical density, wet/dry cell weight concentration), in-situ (turbidity, permittivity), and soft-sensor (off-gas O2/CO2, alkali consumption) techniques. Cultivations were performed in a 5 L oxygen-enriched stirred tank bioreactor. The experimental plan determined varying aeration rates/levels, glycerol or methanol substrates, residual methanol levels, and temperature. In total, results from 13 up to 150 g (dry cell weight)/L cultivation runs were analyzed. Linear and exponential correlation models were identified for the turbidity sensor signal and dry cell weight concentration (DCW). Evaluated linear correlation between permittivity and DCW in the glycerol consumption phase (<60 g/L) and medium (for Mut+ strain) to significant (for MutS strain) linearity decline for methanol consumption phase. DCW and permittivity-based biomass estimates used for soft-sensor parameters identification. Dataset consisting from 4 Mut+ strain cultivation experiments used for estimation quality (expressed in NRMSE) comparison for turbidity-based (8%), permittivity-based (11%), O2 uptake-based (10%), CO2 production-based (13%), and alkali consumption-based (8%) biomass estimates. Additionally, the authors present a novel solution (algorithm) for uncommon in-situ turbidity and permittivity sensor signal shift (caused by the intensive stirrer rate change and antifoam agent addition) on-line identification and minimization. The sensor signal filtering method leads to about 5-fold and 2-fold minimized biomass estimate drifts for turbidity- and permittivity-based biomass estimates, respectively. View Full-Text
Keywords: biomass concentration; in-situ and soft-sensors; turbidity; permittivity; signal filtering; off-gas analysis; stirred-tank bioreactor; Pichia pastoris biomass concentration; in-situ and soft-sensors; turbidity; permittivity; signal filtering; off-gas analysis; stirred-tank bioreactor; Pichia pastoris
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MDPI and ACS Style

Grigs, O.; Bolmanis, E.; Galvanauskas, V. Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions. Sensors 2021, 21, 1268. https://doi.org/10.3390/s21041268

AMA Style

Grigs O, Bolmanis E, Galvanauskas V. Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions. Sensors. 2021; 21(4):1268. https://doi.org/10.3390/s21041268

Chicago/Turabian Style

Grigs, Oskars, Emils Bolmanis, and Vytautas Galvanauskas. 2021. "Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions" Sensors 21, no. 4: 1268. https://doi.org/10.3390/s21041268

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