(480e) Dynamic Modeling of Photoproduction, Photoregulation and Photoinhibition in Microalgae Using Chlorophyll Fluorescence

Algal-derived biofuel has been considered a potential alternative source of renewable energy since the 1970s, yet many problems have to be overcome on the path to making large-scale production of microalgal biofuel feasible [1,2]. In this context, the development of mathematical models that are capable of predicting the behavior of a microalgae culture accurately is paramount. At a fundamental level, models used in conjunction with experiments are invaluable tools to unveil and untangle the underlying photosynthetic and metabolic mechanisms. For process development purposes likewise, models can be used to improve the design, operation and control of a microalgae culture in order to enable and sustain a higher biomass production or lipid content.

Chlorophyll-a fluorescence is a powerful tool for the analysis of the photoproduction, photoinhibition and photoregulation processes [3], which has led to important discoveries over the past 40 years. Today's state-of-the-art equipments, such as Pulse Amplitude Modulation (PAM), can implement complex protocols with great measurement accuracy. In order to fully exploit this capability, experimental protocols have been developed that relate the measured fluorescence fluxes with key photosynthetic parameters such as the quantum yield of photosynthesis, the photosynthetic apparatus activity, and the NPQ activity. But even though the level of understanding of the various fluorescence measures has improved significantly over the past few years, little effort has been devoted to developing dynamic models that relate specific photosynthetic mechanisms to those parameters.

The main contribution of this presentation is a mathematical model that can predict the fluorescence fluxes in terms of the photosynthetic mechanisms occurring inside the chloroplasts. Our model builds upon the widely-accepted state-transition model proposed by Han [4] for predicting photoproduction and photoinhibition. We propose an extension of this model in the form of a semi-empirical expression in order to encompass a particular type of photoregulation, namely qE quenching. Moreover, we express the chlorophyll-a fluorescence flux based on the work by Huot [3], for a specific type of Photosystem II arrangement, the so-called Lake model. The novelty and originality of our model lies in the way the states of the PSUs, as given by the (extended) Han model, are related to the measured fluorescence parameters, and how it does so by accounting for qE quenching.

A large number of parameters in the model can be calibrated with reasonable confidence from the characteristic fluorescence fluxes measured with a PAM fluorometer. Here, we present such calibration results for the microalgae Nannochloropsis Salina. For validation purposes, we consider various PAM experiments with different actinic light profiles, for both dark- and light-adapted samples, demonstrating a good agreement of the model with the experimental data for challenging experimental protocols.

References:
[1] le B. Williams, P.J. and Laurens, L.M.L. (2010). Microalgae as biodiesel & biomass feedstocks: Review & analysis of the biochemistry, energetics & economics. Energy & Environmental Science, 3(5), 554-590.
[2] Bernard, O. (2011). Hurdles and challenges for modelling and control of microalgae for CO2 mitigation and biofuel production. Journal of Process Control, 21(10), 1378-1389.
[3] Huot, Y. and Babin, M. (2010). Overview of fluorescence protocols: theory, basic concepts, and practice. In: Chlorophyll a Fluorescence in Aquatic Sciences: Methods and Applications, 31-74. Springer.
[4] Han, B.P. (2002). A mechanistic model of algal photoinhibition induced by photodamage to photosystem-II. Journal of Theoretical Biology, 214(4), 519-527.