Lett Appl Microbiol. 2021 Jun 5. doi: 10.1111/lam.13519. Online ahead of print.
ABSTRACT
The development of microalgae culture technology has been an integral part to produce biomass feedstock to biofuel production. Due to this, numerous attempts have been made to improve some operational parameters of microalgae production. Despite this, specialized research in cell growth monitoring, considered as a fundamental parameter to achieve profitable applications of microalgae for biofuels production, presents some opportunity areas mainly related to the development of specific and accurate methodologies for growth monitoring. In this work, predictive models were developed through statistical tools that correlate a specific microalgal absorbance with cell density measured by cell count (cells∙mL-1 ), for three species of interest for biofuels production. The results allow the precise prediction of cell density through a logistic model based on spectrophotometry, valid for all the kinetics analyzed. The adjusted determination coefficients (r2adj ) for the developed models were 0.993, 0.995 and 0.994 for Dunaliella tertiolecta, Nannochloropsis oculata and Chaetoceros muelleri, respectively. The results showed that the equations obtained here can be used with an extremely low error (≤ 2%) for all the cell growth ranges analyzed, with low operational cost and high potential of automation. Finally, a user-friendly software was designed to give practical use to the developed predictive models.
PMID:34091927 | DOI:10.1111/lam.13519
