Title: Using Genetic Algorithm to predict the suitable light intensity for best influence on lipid characteristics and fatty acid profile of freshwater Microalgae for biodiesel production

Biography:

Marzie is PhD candidate at research branch of Islamic Azad University in reproduction and culture of aquatic. She is hiring as an expert at Organization of Agriculture, Tehran, Iran. Also, she works as a consultant member at Agricultural and Natural Resources Engineering Organization, Tehran, Iran.

Abstract

The present study was purposed to predict the suitable light intensity on the lipid Accumulation properties of a freshwater microalga Chlorococcum Oleofaciens KF584224.1 to get the highest lipid content. Based on some previous studies and gathered data for light intensity, by using Genetic Algorithm via R programming language, we predicted that if we cultivate the body of these microalgae species at two different light intensities (200 and 400 μmol photons m^-2s^-1) then we will get the highest lipid content at highest probability. In continuation, the microalga was isolated from a freshwater body and cultivated at five different light intensities of 50, 100, 200, 400, and 800 μmol photons m^-2s^-1 for 20 days. Once algae reached the stationary phase, the maximum biomass productivity (367.82±4.26mgL^-1d^-1) was found in culture illuminated with 200 μmol photons m^-2s^-1, while the highest lipid content (59.18±1.62%) and lipid productivity (126.72±3.27mgL^-1d^-1) were achieved in culture illuminated with 400 μmol photons m^-2s^-1. The properties of biodiesel obtained from C. oleofaciens cultured fewer than 50 μmol photons m^-2s^-1 met the specifications provided by the international biodiesel standards (European EN 14214 and US ASTM D6751), higher light illumination improved the biodiesel quality which makes C. oleofaciens as a potential feedstock for biodiesel production especially under 400 μmol photons m^-2s^-1 light intensity.