Towards a general kinetic microalgae model: extending a semi-deterministic green microalgae model for the cyanobacterium Arthrospira platensis and red alga Porphyridium purpureum
Manhaeghe, D.; Arashiro, L.T.; Van Hulle, S.W.H.; Rousseau, D.P.L. (2021). Towards a general kinetic microalgae model: extending a semi-deterministic green microalgae model for the cyanobacterium Arthrospira platensis and red alga Porphyridium purpureum. Bioresour. Technol. 342: 125993. https://dx.doi.org/10.1016/j.biortech.2021.125993 In: Bioresource Technology. Elsevier: Barking. ISSN 0960-8524; e-ISSN 1873-2976, more | |
Keywords | Arthrospira platensis Gomont, 1892 [WoRMS]; Chlorella vulgaris Beijerinck, 1890 [WoRMS]; Porphyridium purpureum (Bory) K.M.Drew & R.Ross, 1965 [WoRMS] Marine/Coastal | Author keywords | Chlorella vulgaris; Arthrospira platensis; Porphyridium purpureum; Kinetic modelling; Universal model |
Authors | | Top | - Manhaeghe, D., more
- Arashiro, L.T., more
- Van Hulle, S.W.H., more
- Rousseau, D.P.L., more
| | |
Abstract | Mathematical models for microalgae and cyanobacteria are seldomly validated for different algal species, as such limiting their applicability. Therefore, in this research, a previously developed kinetic model describing the growth of the green microalgae species Chlorella vulgaris was used to simulate the growth of the cyanobacterium Arthrospira platensis and the red alga Porphyridium purpureum. Based on a global sensitivity analysis, the model parameter µmax,A was calibrated using respirometric-titrimetric data. Calibration yielded values of 5.76 ± 0.17 d-1, 2.06 ± 0.16 d-1 and 1.06 ± 0.09 d-1 for Chlorella vulgaris, Arthrospira platensis and Porphyridium purpureum, respectively. Model simulations revealed that the biological growth equations in this model are adequate. However, increased light intensities triggered a survival mechanism for Arthrospira platensis, which is currently not taken into account by the model, leading to bad model accuracy under these circumstances. Future work should address the most important survival mechanisms and include those in the model to widen its applicability. |
|