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Biocatalysts and Bioreactor Design
Kinetic modeling of the photosynthetic growth of Chlamydomonas reinhardtii in a photobioreactor
Article first published online: 2 MAY 2012
DOI: 10.1002/btpr.1545
Copyright © 2012 American Institute of Chemical Engineers (AIChE)
Additional Information
How to Cite
Takache, H., Pruvost, J. and Cornet, J.-F. (2012), Kinetic modeling of the photosynthetic growth of Chlamydomonas reinhardtii in a photobioreactor. Biotechnol Progress, 28: 681–692. doi: 10.1002/btpr.1545
Publication History
- Issue published online: 9 JUN 2012
- Article first published online: 2 MAY 2012
- Accepted manuscript online: 29 MAR 2012 06:38AM EST
- Manuscript Revised: 13 MAR 2012
- Manuscript Received: 9 SEP 2011
Funded by
- AlgoH2 ANR Program (French National Program) and by the European SolarH2 FP7 Program
- Abstract
- Article
- References
- Cited By
Keywords:
- Chlamydomonas reinhardtii;
- modeling;
- photosynthetic growth;
- pigment;
- photoinhibition;
- microalgae;
- photobioreactor;
- photosynthesis
Abstract
The aim of this study was to establish and validate a model for the photosynthetic growth of Chlamydomonas reinhardtii in photobioreactors (PBRs). The proposed model is based on an energetic analysis of the excitation energy transfer in the photosynthesis apparatus (the Z-scheme for photosynthesis). This approach has already been validated in cyanobacteria (Arthorspira platensis) and is extended here to predict the volumetric biomass productivity for the microalga C. reinhardtii in autotrophic conditions, taking into consideration the two metabolic processes taking place in this eukaryotic microorganism, namely photosynthesis and respiration. The kinetic growth model obtained was then coupled to a radiative transfer model (the two-flux model) to determine the local kinetics, and thereby the volumetric biomass productivity, in a torus PBR. The model was found to predict PBR performances accurately for a broad set of operating conditions, including both light-limited and kinetic growth regimes, with a variance of less than 10% between experimental results and simulations. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012