Use of Ftir Spectroscopy and Pls-regression in Monitoring Biomolecules in Spirulina Platensis During Its Growth in an Internally-illuminated Photobioreactor

Abstract

This study developed a rapid and non-destructive analytical method for biochemical analysis of the Spirulina biomass via FTIR spectroscopy and PLS regression. It was then used to monitor the biochemical changes in the biomass during an 8-day cultivation period in a 3-L internally-illuminated concentric-tube airlift photobioreactor at different light intensities (69, 110, and 166 µmol photons m^-2 s^-1). It was found that PLS-regression have better predictive power than multipoint regression. It also yielded statistically similar results with conventional biochemical methods. This new method reduced the time for sample preparation and eliminated the extraction of target biomolecule for analysis. It was also found to be valuable in monitoring the changes in the total protein, carbohydrate and lipid content (% w/w of total biomolecules) in Spirulina biomass during its growth. It was observed that the protein content of the biomass decreased initially, which was compensated by an increase in the carbohydrate content. This may imply that biomass production may be driven by production of more carbohydrates during the early period of growth. Protein content then started to increase until the third day of growth and remained constant thereafter. Carbohydrate and lipid content also remained constant from the third day of growth. The lowest light intensity was found to have the highest protein content (60.4± 0.87 %w/w) but it has the lowest overall biomass productivity (0.090 ± 0.017 g L^-1 d^-1). While at the highest light intensity, protein content was slightly lower (57.3 ± 0.777 %w/w) than that of the lowest light intensity. But it has the highest overall biomass productivity (0.141 ±0.007 g L^-1 d^-1).