Zanenhlanhla Gumbi
University of KwaZulu Natal, South Africa
Title: Optimization of biomass and lipid production from a local Chlorella isolates using response surface methodology and artificial neural network
Biography
Biography: Zanenhlanhla Gumbi
Abstract
The exhaustion of the world’s fossil fuel supplies and global warming are driving the search for renewable sources of fuel. Microalgae have received great interest as an alternative to fossil fuels due to their fast growth rates and high photosynthetic efficiencies. This study focuses on the optimization of biomass and lipid yield from an indigenous Chlorella isolate using the Response Surface Method. The input parameters consisted of NaNO3, NaHCO3 and NaCl within the ranges of 0.05-2.0g/l, 0.5-3.0g/l and 0-10mM respectively. Data from seventeen experiments with varied culture conditions was used to develop a polynomial model. Analysis of variance (ANOVA) of the model gave a coefficient of determination (R2) of 0.72. The predicted optimum conditions for biomass formation were 1.55 g/l NaNO3, 3.0 NaHCO3 and 0mM NaCl. The response graphs showing the interaction of NaHCO3 and NaNO3 on algal growth revealed that an increase in NaNO3 and NaHCO3 medium concentration enhanced the biomass formation whereas NaCl did not impact on biomass formation. These findings revealed that under optimal conditions the indigenous Chlorella isolate could be a potential strain for high biomass formation required for biodiesel production.