Fuzzy intelligence for investigating the correlation between growth performance and metabolic yields of a Chlorella sp. exposed to various flue gas schemes.

A Chlorella sp. was cultivated in a photobioreactor under different experimental conditions to investigate its acclimation to high-CO exposures. When the microalgae was grown under controlled flue gas sparging and optimised nutrients, the biomass concentration increased to 3.415±0.145gL and the maximum protein yield was obtained (57.500±0.351% ww). However, when the culture was exposed to continuous flue gas, the lowest biomass growth (1.665±0.129gL) was noted. Under these conditions, high carbohydrate and lipid values were recorded (38.600±1.320% ww and 30.200±0.150% ww), respectively. A Sugeno-type fuzzy model was employed to understand the correlation between peak biomass concentration (B), CO uptake rate (qCO), and maximum relative electron transport rate (rETR) as inputs and carbohydrate, protein, and lipid yields as outputs. Results of the model were in agreement with the experimental data (r-value >0.985).

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