High-Fidelity Modelling Methodology of Light-Limited Photosynthetic Production in Microalgae

Abstract

Reliable quantitative description of light-limited growth in microalgae is key to improving the design and operation of industrial production systems. This article shows how the capability to predict photosynthetic processes can benefit from a synergy between mathematical modelling and lab-scale experiments using systematic design of experiment techniques. A model of chlorophyll fluorescence developed by the authors [Nikolaou et al., J Biotechnol 194:91–99, 2015] is used as starting point, whereby the representation of non-photochemical-quenching (NPQ) process is refined for biological consistency. This model spans multiple time scales ranging from milliseconds to hours, thus calling for a combination of various experimental techniques in order to arrive at a sufficiently rich data set and determine statistically meaningful estimates for the model parameters. The methodology is demonstrated for the microalga Nannochloropsis gaditana by combining pulse amplitude modulation (PAM) fluorescence, photosynthesis rate and antenna size measurements. The results show that the calibrated model is capable of accurate quantitative predictions under a wide range of transient light conditions. Moreover, this work provides an experimental validation of the link between fluorescence and photosynthesis-irradiance (PI) curves which had been theoricized.

Exploration of Plant Biodiversity to Investigate Regulation of Photosynthesis in Natural Environment

“…During this light treatment, several parameters describing the properties of both PSI and PSII and their ability to activate photo-protection responses like NPQ were measured using a DUAL-PAM-100 (Table 1). Plant response to increasing illumination intensity is a complex phenomenon and in order to describe it quantitatively NPQ induction curves were fitted with a sigmoidal function found to be the most suitable to describe the kinetics, similarly to what was previously observed in algae (Bernardi et al ., 2016) (Figure S3).…”

“…Collected data were processed to obtain quantitative parameters describing the recorded kinetics. NPQ induction curves were fitted with a sigmoidal function (Hill function (y=V max *x n *(k n +x n )-1) found to be the most suitable to describe its activation in leaves treated with increasing actinic light intensities, as already observed in algae (Bernardi et al ., 2016). Three main parameters were obtained, V max that is the maximal NPQ value reached during the experiment, k is the light intensity needed to activate 2/3 of the NPQ; and n is a parameter describing the sigmoidicity of the curve.…”

The potential of quantitative models to improve microalgae photosynthetic efficiency

“…Some models not only describe the static effect of light on growth, but aim at representing the dynamics of photosynthesis, accounting for regulation and inhibition (Eilers and Peeters , Han et al ). This idea was then further exploited and validated to model the dynamics of photo‐inhibitory and photo‐regulatory phenomena (Nikolaou et al , Bernardi et al ), also including a description of some major photosynthetic features influencing microalgae growth such as pigments content, antenna size and NPQ.…”

“…Developing models with mathematical identifiability is one of the main challenges of biological phenomena, since the information on the underlying molecular mechanisms and the number of available experimental data points is usually limited. To address these challenges, the ability to design the experiments maximizing the information that may be collected (Bernardi et al ), and to efficiently collect large experimental dataset testing the effect of multiple parameters will be strategic. In this perspective, the development of micro‐scale devices (Kim et al , Luke et al , Perin et al ) is opening the possibility to investigate the effect of multiple variables (e.g.…”

How Mixing and Light Heterogeneity Impact the Overall Growth Rate in Photobioreactors

“…More refined dynamic models accounting for the dynamic response of the photon absorption chain have been published, e.g., by Nicolaou, Bernard and co‐workers . However, their intrinsic complexity in terms of number of variables limits their use to homogeneous reactors , and leads to parameter identification issues.…”