Three non-invasive tools to estimate microalgal growth online and in real-time

On-line monitoring of bioprocesses is a cumbersome task that is relentlessly needed for accurate control and maximization of process efficiency, productivity, and yields. For microalgal processes, developing proper monitoring systems can be especially challenging due to their diverse characteristics. In this study, a novel approach is presented for non-invasively estimating microalgal growth in batch processes by online monitoring of the required nitric acid supply for pH control based on the proton stoichiometric imbalance of nitrate metabolism. Employing this strategy, we further increase measurement redundancy and estimate reliability by integrating gas analysis of carbon dioxide and oxygen fractions in the off-gas to determine biomass growth on-line. The obtained estimates of biomass concentrations were tested and validated in three autotrophic batch cultivations of Tetradesmus obliquus at a laboratory scale with a working volume of 1.8 L. All three online monitoring approaches could be employed for biomass estimation with outstanding results. Compared to offline measurements of biomass dry weight, correlation coefficients (R²) of 0.96, 0.94, and 0.96 were achieved for the three monitoring methods. Differences in measurements of cell dry weight were determined to lie within 8 %, 7.1 %, and 6.7 % for normalized root mean square deviations (N-RMSD). The presented method of mass-balance-based growth determination proved suitable for real-time monitoring of microalgal biomass production. We believe this work paves the way for further process automation of the microalgal output by expanding on-line monitoring capabilities for biomass and cell state in parallel.