(460d) Modeling the Effect of Light Intensity in Microalgae Growth

Microalgae-based processes are considered one of the most promising alternative technologies for the production of liquid fuels in the transport sector [1]. The main advantages of microalgae among other possible feedstock are the high potential productivity and the absence of the competition with traditional crops. This potential is however still quite theoretical and algae production on large scale is still far from being competitive.. Several issues need to be addressed, ranging from algae cultivation, harvesting and products extraction.

The availability of reliable models to steer design, scale-up and quality monitoring throughout process definition and operation is therefore of critical importance to (i) describe the fundamental physical, chemical and biological phenomena, (ii) assess the interactions between equipment design and product yields, and (iii) scale-up and optimize design and operation. Clearly the reliable representation of algal growth is of paramount importance. Growth is affected by several operation variables such as nutrient availability, temperature, mixing, etc. However, being algae photosynthetic organisms all energy supporting their growth originated from sunlight and therefore illuminating conditions have a key influence by influencing photosynthesis efficiency and kinetics.

In this work a microscale first principles model is proposed to represent biomass growth as a function of light intensity. The model is derived after a data-driven procedure allowing to discriminate among two candidate models taken from the literature [2-3]. A sensitivity-based analysis was carried out to assess the model identifiability (i.e. the possibility to estimate the set of model parameters in a unique way) under the investigated experimental conditions. The model parameters were estimated by using growth curves at different light intensities, using data from an algal species, Nannochloropsis salina, in non-limiting nutrient conditions and at low biomass concentrations in order to minimize the effect of light attenuation and scattering [4].

Data from in vivo fluorescence measurements [5] provide a direct measurement of the excitation state of the photo-synthetic apparatus. Such measurements under different illuminations thus provide additional information to make the growth description more reliable in order to include these biological insights from performed experiments the model structure needed several modifications and a re-parameterization of the model was carried out in order to exploit the information obtained in such a way to ensure model identifiability. The new model can describe the photo-inhibition process and also represent the maintenance factor.

The model is capable of representing quite well all experimental data, particularly with concern to the dependence of growth rate as function of light intensity.

Future work will aim at extending the approach so as to incorporate light attenuation due the algae concentration and the effect of light-dark cycles due to mixing in a photobioreactor. A multiscale approach will be exploited to include all relevant phenomena acting at different length scale so as to assess the model applicability for photobioreactor design.

ACKNOWLEDGEMENTS

This work was supported by ERC starting grant BIOLEAP nr 309485 to TM.

References

[1]    Hannon, M.; Gimpel, J.; Tran, M.; Rasala, B.; Mayfield, S. (2010). Biofuels from algae: challenges and potential. Biofuels, 1, 763-784.

[2]    Wu, X.; Merchuck, J.C. (2001). A model integrating fluid dynamics in photosynthesis and photoinhibition  processes. Chemical Engineering Science, 56, 3527-3538.

[3]    Camacho Rubio, F.; Garcia Camacho, F.; Fernandez Sevilla, J.M.; Chisti, Y.; Molina Grima, E. (2003). A mechanicistic model of photosynthesis in microalgae. Biotechnology Bioenergy, 81, 459-473.

[4]    Sforza, E.; Simionato, D.; Giacometti, G.M.; Bertucco, A.; Morosinotto, T. (2012). Adjusted light and dark cycles can optimize photosynthetic efficiency in algae growing in photobioreactors. PLoS ONE, 7, art. no. e38975.

[5]    Kramer, D.M.; Johnson, G.; Kiirats, O.; Edwards, G.E. (2004). New fluorescence parameters for determination of Q_A redox state and excitation energy fluxes. Photosynthesis Research, 79, 209-218.