Microalgae are considered to be promising producers of bioactive chemicals, feeds and fuels from carbon dioxide by photosynthesis. Thus, the prediction of microalgal growth profiles is important for the planning of cost-effective and sustainable cultivation–harvest cycles. This paper proposes a mathematical model capable of predicting the effect of light flux into culture and medium concentration on the growth profiles of microalgae by incorporating these growth-limiting factors into a logistic equation. The specific form of the equation is derived based on the experimentally measured growth profiles of Monoraphidium sp., a microalgal strain isolated by the authors, under 16 conditions consisting of combinations of incident light fluxes into culture and initial medium concentrations. Using a cross-validation method, it is shown that the proposed model has the ability to predict necessary incident light flux into culture and initial medium concentration for harvesting target biomass at a target time. Finally, model-guided cultivation planning is performed and is evaluated by comparing the result with experimental data.

Microalgae are considered to be promising producers of bioactive chemicals, feeds, and fuels from carbon dioxide by photosynthesis. Thus, the prediction of microalgal growth profiles is important for the planning of cost-effective and sustainable cultivation-harvest cycles. This paper proposes a mathematical model capable of predicting the effect of light flux into culture and media concentration on the growth profiles of microalgae by incorporating these growth-limiting factors into the logistic equation. The specific form of the equation is derived based on the experimentally measured growth profiles of Monoraphidium sp., a microalgal strain isolated by the authors. Using a cross-validation method, it is shown that the proposed model has the ability to predict necessary incident light flux into culture and initial media concentration for harvesting target biomass at target time. Finally, the model-guided cultivation planning is performed and is evaluated by comparing the result with the experimental data.