Iranian Research Organization for Science and Technology Advances in Environmental Technology 2476-6674 2 3 2017 04 22 Predictive modeling of biomass production by Chlorella vulgaris in a draft-tube airlift photobioreactor 119 126 433 10.22104/aet.2017.433 EN Mohsen Mansouri Department of Chemical Engineerin, Ilam University Journal Article 2016 04 26 The objective of this study was to investigate the growth rate of <em>Chlorella vulgaris</em> for CO<sub>2</sub> 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 (μ<sub>max</sub>), and maximum cell concentration (X<sub>max</sub>). The low root-mean-square error (RMSE) and high regression coefficients (R<sup>2</sup>) 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: μ<sub>max</sub>=0.0309 h<sup>−1</sup>, λ=100 h, and X<sub>max</sub>=1.82 g/L. Chlorella vulgaris CO2, Photobioreactor Predictive modeling https://aet.irost.ir/article_433_6bed85cba15d1e65c79b03959829a11a.pdf