Enhancement of Lipid Accumulation in Microalga Desmodesmus sp. VV2: Response Surface Methodology and Artificial Neural Network Modeling for Biodiesel Production

Abstract

Microalgae are the most attractive renewable energy sources for the production of biofuels because of their luxurious growth and lipid accumulation ability in diverse nutritional conditions. In the present study, Desmodesmus sp. VV2, an indigenous microalga, was evaluated for its biodiesel potential using Response Surface Methodology (RSM) to improve the lipid accumulation with the combination of nutrients stress NaNO3 starvation, CaCl2 depletion, and supplementation of magnesium oxide nanoparticles (MgO). Among different stress conditions, 57.6% lipid content was achieved from RSM optimized media. Owing to this, RSM results were also validated by the Artificial Neural Network (ANN) with 11 training algorithms and it is found that RSM was more significant. In addition, the saturated fatty acid (SFA) content was noticeably increased in RSM optimized media