|Hugo Fabian Lobatón García||Facultad de Ingeniería, Universitaria Agustiniana, Ak. 86 #11b-95, Bogotá, Bogotá D.C., Cundinamarca, postal code 110811, Colombia|
|Natali López Mejia||Facultad de Ingeniería, Universitaria Agustiniana, Ak. 86 #11b-95, Bogotá, Bogotá D.C., Cundinamarca, postal code 110811, Colombia|
objective of this research was to develop a mathematical model for batch
photoautotrophic cultivation of Arthrospira platensis and to validate it
against data obtained in experiments. All trials were carried at 30°C, under a
light intensity of 60 or 120 µmol m-2s-1. The purpose of
the model was to determine the optimal concentration of carbon dioxide, as well
as to investigate the formation of phycocyanin. For the experimental conditions
in this study, the optimal concentration carbon dioxide (0.8% CO2,
v/v) was predicted using the model according to the initial bicarbonate level,
the carbon uptake by the microalga, the pH, and the mass transfer process. The
use of this optimal value in the gas inlet seems to be a suitable option for
maintaining the optimal pH (9.5), thereby eliminating the need for a pH
controller in the bioreactor system. According to the simulations, the mass
fraction of the phycocyanin formation rate seems to depend on the internal
light level. The percentage of adjustment obtained (R2) was ?75%.
The velocity of phycocyanin formation was enhanced at intensities up to 120
µmol m-2s-1. However, the actual internal irradiance
values were lower than the light compensation point (4.5 µmol m-2s-1),
so phycocyanin formation ceased. The mathematical model may facilitate the
examination of optimal carbon delivery, as well as the light input, in several A.
platensis culture conditions aimed at phycocyanin production.
Arthrospira platensis; Carbon dioxide; Light intensity; Mathematical model; Phycocyanin
Arthrospira platensis is a prokaryotic photoautotrophic cyanobacterium characterized by high levels of lipids that are currently being used as a fuel source (Jamilatun et al., 2019; Sukarni et al., 2019; Jamilatun et al., 2020). Its biomass also contains protein and other valuable substances, so A. platensis is now also cultivated to market it as complete biomass. Among the valuable compounds found in this microalga is phycocyanin, a protein of great interest to the food industry for its antioxidant capacity and to the cosmetic interest for its bright blue color. Other potential compounds of interest include ?-linoleic acid, which is an important unsaturated fatty acid, and spirulan calcium, which is a sulfated exopolysaccharide with promising biological functions (Borowitzka, 2013). A. platensis is cultivated in open cropping systems, but this cultivation method has a low biomass productivity (0.04 g DW L-1d-1) (Jiménez et al., 2003) and produces a low-quality phycocyanin compared to cultivation in photobioreactors.
Open cropping systems have a 20-fold lower biomass production than photoreactors (Bezerra et al., 2011; Chen et al., 2013) because the environment in open ponds cannot be controlled for the variables that determine the productivity of microalgae (temperature, pH, light intensity, nutrient levels, carbon, etc.) (Borowitzka, 2013). This control is possible in bioreactors, but the cultivation of microalgae in photobioreactors is only economically feasible if it produces an optimal yield with low investment costs, including the operation of the facility (Bertucco et al., 2014). The important aspects needed for bioreactor technology to be successful and efficient are the use of optimal strategies for carbon delivery and precision in the use of light.
A. platensis is a filamentous cyanobacterium capable of naturally forming colonies in waters that contain high levels of carbonates and bicarbonates (Binaghi et al., 2003). Therefore, increasing the production of A. platensis is possible by avoiding carbon limitations and taking advantage of carbon dioxide capture, since the main source of inorganic carbon of A. platensis is the bicarbonate ion (HCO3-) (Cornet et al., 1998). Naturally occurring bicarbonate present in the medium, which is approximately 117 mM, is taken up by the cyanobacteria and used in photosynthesis to support growth (de Morais and Costa, 2007). This uptake also controls the pH (Pawlowski et al., 2014), because the loss of dissolved carbon dioxide due to uptake into cyanobacterial cells is partly compensated by regeneration from carbonates and bicarbonates, so carbon dioxide uptake is accompanied by changes in pH (Rubio et al., 1999). In bubble column photobioreactors, a carbon dioxide line is opened or closed automatically according to an established pH set point. This implies that these reactors require pH sensors (Doucha et al., 2005; Spalding, 2008), thereby increasing investment and operating costs. However, a mathematical model for the control of CO2 supply could overcome this challenge.
One of the main functions of phycocyanin in microalgae is the capture of light; therefore, the intensity of light has an important influence on the accumulation of this phycobiliprotein (Chen et al., 2013). However, the reported optimal light intensity values required to achieve a high production of phycocyanin show no consistency, which could reflect different intensities of internal light within the culture. This discrepancy may also be a consequence of different bioreactor configurations and culture conditions (Xie et al., 2015). Again, the use of a mathematical model could aid in identifying the optimal light intensity for a particular cyanobacterial crop.
The biomass growth and pH variations predicted with the model agree with the experimental measurements. Cultivations with either 3% or 0.035% CO2 led to a suboptimal pH, so the model was used to determine a CO2 concentration that results in an optimal pH of 9.5. For the experimental conditions in this work (60 µmol m-2s-1), a 0.8% CO2 concentration was selected. A sensitive analysis with higher light intensity (120 µmol m-2s-1) showed an increment in the biomass productivity, as well as in the optimal CO2 concentration (1.2% CO2). The mass fraction of phycocyanin was produced at a rate that was mainly controlled by the internal light in the photobioreactor before nitrate limitations appeared. At light intensities of 120 µmol m-2s-1, the biomass productivity was two times greater than the experimental results at 60 µmol m-2s-1. According to the simulations, the average internal light should be between 140 µmol m-2s-1 and 4.5 µmol m-2s-1 (the CO2 compensation point for A. platensis). Lower or higher values seem to have an adverse effect on the phycocyanin mass fraction.
summary, the mathematical model proposed here can help to eliminate the need
for pH sensing in cyanobacterial cultivation by forecasting the CO2 level
required to regulate the pH. The results showed a good adjusted R2
(coefficient of determination) between the model data and the experimental data
(R2 ? 75%). The model can support the investigation of other culture
conditions (i.e., light intensity) or photobioreactor modifications (i.e.,
light path) and their influence on phycocyanin production.
Aiba, S., Ogawa, T., 1977. Assessment of Growth Yield of a Blue-green Alga, Spirulina platensis, in Axenic and Continuous Culture. Journal of General Microbiology, Volume 102(1), pp. 179–182
Bennett, A., Bogorad, L., 1973. Complementary Chromatic Adaptation in a Filamentous Blue-green Alga. The Journal of Cell Biology, Volume 58(2), pp. 419–435
Bertucco, A., Beraldi, M., Sforza, E., 2014. Continuous Microalgal Cultivation in a Laboratory-Scale Photobioreactor Under Seasonal Day–night Irradiation: Experiments and Simulation. Bioprocess and Biosystems Engineering, Volume 37(8), pp. 1535–1542
Bezerra, R.P., Montoya, E.Y.O., Sato, S., Perego, P., de Carvalho, J.C.M., Converti, A., 2011. Effects of Light Intensity and Dilution Rate on the Semicontinuous Cultivation of Arthrospira (Spirulina) platensis. A Kinetic Monod-type Approach. Bioresource Technology, Volume 102(3), pp. 3215–3219
Binaghi, L., Del Borghi, A., Lodi, A., Converti, A., Del Borghi, M., 2003. Batch and Fed-batch Uptake of Carbon Dioxide by Spirulina platensis. Process Biochemistry, Volume 38(9), pp. 1341–1346
Borowitzka, M., 2013. High-value Products from Microalgae—Their Development and Commercialisation. Journal of Applied Phycology, Volume 25(3), pp. 743–756
Chen, C.Y., Kao, P.C., Tsai, C.J., Lee, D.J., Chang, J.S., 2013. Engineering Strategies for Simultaneous Enhancement of C-phycocyanin Production and CO2 Fixation with Spirulina platensis. Bioresource Technology, Volume 145, pp. 307–312
Cornet, J.F., Dussap, C.G., Cluzel, P., Dubertret, G., 1992. A Structured Model for Simulation of Cultures of the Cyanobacterium Spirulina platensis in Photobioreactors: II. Identification of Kinetic Parameters under Light and Mineral Limitations. Biotechnology and Bioengineering, Volume 40(7), pp. 826–834
Cornet, J.F., Dussap, C.G., Gros, J.B., 1998. Kinetics and Energetics of Photosynthetic Micro-organisms in Photobioreactors. In: Bioprocess and Algae Reactor Technology, Apoptosis, Advances in Biochemical Engineering Biotechnology, Volume 59, Springer, Berlin Heidelberg, Germany, pp. 153–224
de Morais, M.G., Costa, J.A.V., 2007. Biofixation of Carbon Dioxide by Spirulina sp. and Scenedesmus obliquus Cultivated in a Three-stage Serial Tubular Photobioreactor. Journal of Biotechnology, Volume 129(3), pp. 439–445
Doucha, J., Straka, F., Livansky, K., 2005. Utilization of Flue Gas for Cultivation of Microalgae (Chlorella sp.) in an Outdoor Open Thin-layer Photobioreactor. Journal of Applied Phycology, Volume 17(5), pp. 403–412
He, L., Subramanian, V.R., Tang, Y.J., 2012. Experimental Analysis and Model-based Optimization of Microalgae Growth in Photo-bioreactors using Flue Gas. Biomass and Bioenergy, Volume 41, pp. 131–138
Jamilatun, S., Budhijanto, B., Rochmadi., Yuliestyan, A., Budiman, A., 2019. Effect of Grain Size, Temperature and Catalyst Amount on Pyrolysis Products of Spirulina platensis Residue (SPR). International Journal of Technology, Volume 10(3), pp. 541–550
Jamilatun, S., Budhijanto, Rochmadi, Yuliestyan, A., Aziz, M., Hayashi, J., Budiman, A., 2020. Catalytic Pyrolysis of Spirulina platensis Residue (SPR): Thermochemical Behavior and Kinetics. International Journal of Technology, Volume 11(3), pp. 522–531
Jiménez, C., Cossío, B.R., Niell, F.X., 2003. Relationship Between Physicochemical Variables and Productivity in Open Ponds for the Production of Spirulina: A Predictive Model of Algal Yield. Aquaculture, Volume 221(1-4), pp. 331–345
Kern, D.M., 1960. The Hydration of Carbon Dioxide. Journal of Chemical Education, Volume 37(1), pp. 1–14
Keymer, P., Lant, P., Pratt, S., 2014. Modelling Microalgal Activity as a Function of Inorganic Carbon Concentration: Accounting for the Impact of pH on the Bicarbonate System. Journal of Applied Phycology, Volume 26(3), pp. 1343–1350
Levert, J.M., Xia, J., 2001. Modeling the Growth Curve for Spirulina (Arthrospira) maxima, a Versatile Microalga for Producing Uniformly Labelled Compounds with Stable Isotopes. Journal of Applied Phycology, Volume 13(4), pp. 359–367
Lobaton, H.F.G., 2017. Mathematical Modelling as a Research Tool in the Cyanobacteria. Dissertation. Graduate Program, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Miller, A.G., Colman, B., 1980. Evidence for HCO3? Transport by the Blue-Green Alga (Cyanobacterium) Coccochloris peniocystis. Plant Physiology, Volume 65(2), pp. 397–402
Pawlowski, A., Fernández, I., Guzmán, J.L., Berenguel, M., Acién, F.G., Normey-Rico, J.E., 2014. Event-based Predictive Control of pH in Tubular Photobioreactors. Computers and Chemical Engineering, Volume 65, pp. 28-39
Rubio, F.C., Acien, F.G., Sanchez, J.A., Garcia, F., Molina, E., 1999. Prediction of Dissolved Oxygen and Carbon Dioxide Concentration Profiles in Tubular Photobioreactors for Microalgal Culture. Biotechnology and Bioengineering, Volume 62(1), pp. 71–86
Spalding, M.H., 2008. Microalgal Carbon-dioxide-concentrating Mechanisms: Chlamydomonas Inorganic Carbon Transporters. Journal of Experimental Botany, Volume 59(7), pp. 1463–1473
Sukarni, S., Sumarli, S., Nauri, I.M., Prasetiyo, A., Puspitasari, P., 2019. Thermogravimetric Analysis on Combustion Behavior of Marine Microalgae Spirulina Platensis Induced by MgCO3 and Al2O3 Additives. International Journal of Technology, Volume 10(6), pp. 1174–1183
Ürek, R.Ö., Tarhan, L., 2012. The Relationship Between the Antioxidant System and Phycocyanin Production in Spirulina maxima with Respect to Nitrate Concentration. Turkish Journal of Botany, Volume 36(4), pp. 369–377
Uusitalo, J., 1996. Algal Carbon Uptake and the Difference Between Alkalinity and High pH ("alkalization"), Exemplified with a pH Drift Experiment. Scientia Marina, Volume 60(1), pp. 129–134
Xie, Y., Jin, Y., Zeng, X., Chen, J., Lu, Y., Jing,
K., 2015. Fed-batch Strategy for Enhancing Cell Growth and C-phycocyanin Production
of Arthrospira (Spirulina) platensis Under Phototrophic Cultivation. Bioresource
Technology, Volume 180, pp. 281–287