Light-dark cycles on the s timescale are typical of cell cycling through photobioreactors and high-rate ponds and can significantly impact microalgae cultivation efficiency. Here, a novel formulation of the Camacho-Rubio microalgae growth model was developed to simulate dynamic growth under pulsed light (s timescale). It simultaneously captures the dynamics of the photosynthetic units (PSUs: open, closed and photoinhibited) and their impact on biomass productivity over time. Theoretical knowledge of PSU mediated processes operating on characteristic timescales was used to identify intra- and inter-light cycle variable dynamics and guide the model formulation. For model calibration, dynamic profiles of microalgae growth under pulsed light in a High-Throughput Screening platform were employed, after Principal Component Analysis (PCA), to remove biological noise. Model parameters were estimated for Chlorella sp., and the model validated against additional data under both pulsed and continuous light. The average prediction error for OD750 (measure of biomass) was 8% under pulsed light and 15% under continuous light. For OD680/OD750 (measure of Chlorophyll cell−1) it was 8% under pulsed and continuous light, demonstrating the model's ability to represent highly variable conditions with good accuracy.

Modelling dynamics of photosynthetic units and microalgae growth based on high throughput pulsed light screens

Saccardo A.;Bezzo F.;
2024

Abstract

Light-dark cycles on the s timescale are typical of cell cycling through photobioreactors and high-rate ponds and can significantly impact microalgae cultivation efficiency. Here, a novel formulation of the Camacho-Rubio microalgae growth model was developed to simulate dynamic growth under pulsed light (s timescale). It simultaneously captures the dynamics of the photosynthetic units (PSUs: open, closed and photoinhibited) and their impact on biomass productivity over time. Theoretical knowledge of PSU mediated processes operating on characteristic timescales was used to identify intra- and inter-light cycle variable dynamics and guide the model formulation. For model calibration, dynamic profiles of microalgae growth under pulsed light in a High-Throughput Screening platform were employed, after Principal Component Analysis (PCA), to remove biological noise. Model parameters were estimated for Chlorella sp., and the model validated against additional data under both pulsed and continuous light. The average prediction error for OD750 (measure of biomass) was 8% under pulsed light and 15% under continuous light. For OD680/OD750 (measure of Chlorophyll cell−1) it was 8% under pulsed and continuous light, demonstrating the model's ability to represent highly variable conditions with good accuracy.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3513382
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