(62d) Medium Optimization for Enhanced Lipid Production by Chlorella Protothecoides UTEX25

Algal biodiesel as the third generation biofuels has received considerable attention in recent years because of its renewable, biodegradable, and nontoxic fuel properties. Algal also exhibit several advantages over other energy crops, such as higher photosynthetic efficiency, higher biomass production and lipid content, and faster growth rate. The composition of algal-produced hydrocarbons vary among the microalgae species resulting in many different lipids, hydrocarbons, and other complex oils.

In the present study, a fresh water microalgae, Chlorella protothecoides (UTEX25), was evaluated for its lipid productivity through medium optimization. A one-factor-at-a-time approach was applied to determine the influence of each ingredient of proteose medium on both biomass and lipid production. MgSO₄°E7H₂O, NaNO₃, CaCl₂°E2H₂O, K₂HPO₄ and KH₂PO₄, and NaCl were removed individually from the culture medium, and the results were compared with the one obtained from the original medium. After 11-day cultivation, the results demonstrated that the removal of MgSO4°E7H₂O has positive effect on both biomass growth and lipid production. The biomass reached 0.95 g/L (the biomass production obtained from original medium was 0.54 g/L). The lipid content also increased to from 4.6 to 9.5 % when MgSO4 was removed. On the other hand, the removal of NaNO₃ and proteose adversely reduced biomass growth. The biomass production decreased from 0.54 to 0.37 and 0.29 g/L, respectively, when NaNO₃ and proteose was removed. Therefore, MgSO4°E7H₂O, NaNO₃, and proteose were chosen for further evaluation.

A statistical experimental design, response surface methodology (RSM), was applied to determine the optimal concentration of the three nutrients for both biomass and lipid production. The predicted results of these three nutrients are validated in comparison with experimental data. The change of the lipid profiles obtained from original and optimized medium are evaluated using GC-FID. Results are applied to minimize nutrient requirements in large-scale pond cultivation.