Cultivation of Chlorella sorokiniana and Scenedesmus obliquus in wastewater: Fuzzy intelligence for evaluation of growth parameters and metabolites extraction

This study attempted to investigate the reuse potential of flocculated wastewater for the growth of microalgae species and to understand the relationship between microalgae growth parameters and metabolites extraction using a fuzzy logic model. For these purposes, batch experiments were conducted using two microalgae species, namely, Chlorella sorokiniana and Scenedesmus obliquus, cultivated in different types of flocculated wastewater, viz., BlueGreen (BG11), polymer (P_ww), chitosan (CH_ww) and alum (A_ww). Results indicated that a logistic model fitted well the biomass profiles with r²-values >0.95. The carrying capacities of C. sorokiniana (K: 45.13 mg L⁻¹) and S. obliquus (K: 71.59 mg L⁻¹) grown in the CH_ww medium were significantly (p < 0.01) higher than other flocculants. Additionally, the two microalgae species cultivated in CH_ww showed a good physiological health throughout the growth period. It was found that higher extraction yields of lipids: 16.0–19.8% and carbohydrates: 19.98–20.43% (w/w) of the dry weight were obtained when the microalgae species were grown in the CH_ww wastewater. Further, a fuzzy inference system confirmed the experimental data by predicting the yields of lipids, carbohydrates, and proteins at particular inputs of logistic model parameters and physiological health condition (r²-values > 0.98). It was concluded that CH_ww could be used as an efficient flocculated wastewater for the growth of microalgae species and that the suggested modeling technique was promising.