Predictive modeling of biomass production by Chlorella vulgaris in a drafttube airlift photobioreactor

The objective of this study was to investigate the growth rate of Chlorella vulgaris for CO2 biofixation and biomass production. Six mathematical growth models (Logistic, Gompertz, modified Gompertz, Baranyi, Morgan and Richards) were used to evaluate the biomass productivity in continuous processes and to predict the following parameters of cell growth: lag phase duration (λ), maximum specific growth rate (μmax), and maximum cell concentration (Xmax). The low root-meansquare error (RMSE) and high regression coefficients (R2) indicated that the models employed were well fitted to the experiment data and it could be regarded as enough to describe biomass production. Using statistical and physiological significance criteria, the Baranyi model was considered the most appropriate for quantifying biomass growth. The biological variables of this model are as follows: μmax=0.0309 h−1, λ=100 h, and Xmax=1.82 g/L.

Keywords:

Chlorella vulgaris , CO2 , Photobioreactor , Predictive modeling