Abstract
Kinetic growth models are a useful tool for a better understanding of microalgal cultivation and for optimizing cultivation conditions. The evaluation of such models requires experimental data that is laborious to generate in bioreactor settings. The experimental shake flask setting used in this study allows to run 12 experiments at the same time, with 6 individual light intensities and light durations. This way, 54 biomass data sets were generated for the cultivation of the microalgae Chlorella vulgaris. To identify the model parameters, a stepwise parameter estimation procedure was applied. First, light-associated model parameters were estimated using additional measurements of local light intensities at differ heights within medium at different biomass concentrations. Next, substrate related model parameters were estimated, using experiments for which biomass and nitrate data were provided. Afterwards, growth-related model parameters were estimated by application of an extensive cross validation procedure.Graphic abstract
Highlights
Microalgae as a quickly growing renewable resource allow the production of biofuels, nutraceuticals, cosmetics, and pharmaceuticals [1, 2]
A mechanistic model for biomass growth of C. vulgaris was adapted to the shake flask setting, using equations from Cornet et al [29] for light attenuation and from del Rio-Chanona et al [33] for nitrate consumption. 54 shake flask cultivations at different light conditions, regarding light hours per day and light intensity, were performed and the biomass data was used to conduct a stepwise parameter estimation: First exploring parameters concerning light and focusing on the nitrate parameters, the growth parameters were identified in the main parameter estimation as third step
The availability of numerous cultivation data sets with individual combinations of light intensity and lighting duration allowed to estimate a set of mean parameter values suitable to simulate biomass growth for different light intensities and periods
Summary
Microalgae as a quickly growing renewable resource allow the production of biofuels, nutraceuticals, cosmetics, and pharmaceuticals [1, 2]. Since microalgae produce energy photosynthetically, light is the primary substrate which is attenuated with increasing cell density [3, 4]. This is due to scattering, shading, and absorption by the cells. Parameters like temperature, lighting duration, pH-value, and agitation have to be taken into account for the optimization of the cultivation of microalgae [6]. To describe such a cultivation process, and to gain better understanding, it is beneficial to provide a mathematical model
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