Ms. Olubunmi Adejimi

In the mass production systems of microalgal species, it is important to ensure the safety and quality of the biomass and product. This requires effective monitoring tools that are sensitive, rapid and simple to use. In this study, hyperspectral transmittance spectroscopy (HTS) was applied for the detection, cell density quantification and classification of algal and cyanobacterial species. A database of HTS data was assembled from samples of seven algal and cyanobacterial species at different cell densities and used for quantifying and classifying the species, using chemometric and machine learning algorithms. The results obtained showed the ability to quantify the species with a detection limit of 104 cells/mL for the Support Vector Machine (SVM) models applied and classify the species at concentrations >105 cells/mL. The current study suggests that HTS is applicable for the quantification of cell density and the classification of species of cyanobacteria and algal cell cultures and may prove an effective tool for the effective monitoring and management of microalgal bioreactors.