Model-Based Design of Experiments for the identification of microalgae growth models with limiting nutrients

Nutrients play a major role in several microalgal industrial processes and their efficient exploitation has an impact on environmental sustainability. The Droop model is suitable for the description of nutrients effect on microalgal growth but presents challenges in parameter identification for the high experimental effort required. In this work, a Model-Based Design of Experiments (MBDoE) was employed to plan information-rich experiments for precise parameter estimation. An initial dynamic sensitivity analysis showed that parameters of the Droop model can be practically identified with measurements of biomass and nitrogen content of the medium only. Finally, MBDoE was employed to plan in silico experiments, proving that two optimal experiments are sufficient to achieve accurate parameters estimation.