Estimation of Chlamydomonas reinhardtii Growth in a Torus Photobioreactor

Microalgae culture is used in various biotechnological applications. Optimisation of the system productivity needs reliable sensors. However, physical sensors for biomass and dissolved dioxide carbon concentrations are expensive and not accurate, especially for online measurements. In this context, robust and efficient software sensors have to be developed. In this paper, an Unscented Kalman filter (UKF) methodology is proposed to estimate components concentrations in a photobioreactor. The microalgae Chlamydomonas reinhardtii is used as model organism. The aim of this paper is to develop an online software estimator that reconstructs the biomass, carbon dioxide and oxygen concentrations in the liquid phase, from online measurements of components molar fraction in the output gas provided by a mass spectrometer. The proposed estimator is validated through experimental data collected on a lab-scale photobioreactor.