Fahimeh Sadat Mohammadi - Chemical Engineering-Biotechnology Student-Bioscience and Biotechnology Research Center,Malek Ashtar University of Technology, Tehran, Iran
Daryush Arabian - Faculty member of Bioscience and Biotechnology Research Center, Malek Ashtar University of Technology, Tehran, Iran
Rasoul Khalilzadeh - Faculty member of Bioscience and Biotechnology Research Center, Malek Ashtar University of Technology, Tehran, Iran

The green microalgae Chlorella vulgaris is one of the most interesting feedstocks for biodiesel production because of its fatty acid composition. In order to enhance biomass productivity, response surface methodology (RSM) was used with Box- Behnken design (BBD) to optimize the medium composition of microalgae. The results included a second-order polynomial regression equation with a high coefficient of determination in analysis of variance. By using this experimental design the interaction of parameters was revealed. The greatest biomass productivity reached 152 mg/l.d under the optimal conditions of sodium bicarbonate concentration 0.94 g/l, sodium nitrate concentration 2.75 g/l and magnesium sulfate concentration 1.47 g/l. By using this optimization method ,the biomass productivity of C. vulgaris enhanced from 83.3 mg/l.d in unoptimized phototrophic medium to 152 mg/l.d giving 1.8-fold increse in biomass productivity

Chlorella vulgaris, Biomass productivity, Optimization, Response surface methodology