Optimizing lipid production in oleaginous yeasts for sustainable bioenergy: A review of process parameters, cultivation strategies, and machine learning integration

Abstract

The depletion of petroleum reserves has intensified the global pursuit of renewable and sustainable alternative fuels. Single-cell oils (SCOs), produced by microorganisms, have emerged as a promising substitute for traditional fossil fuels and other biological sources owing to their renewability, environmental sustainability, energy efficiency, versatility, and potential to reduce carbon emissions and the reliance on finite resources, all while fostering economic growth and innovation. Among the different microbial sources, oleaginous yeasts are particularly notable for their ability to efficiently synthesize lipids. This review examines the key factors influencing lipid synthesis in yeasts, including carbon sources, carbon-to-nitrogen ratio (C/N), nitrogen sources, aeration rate, agitation speed, pH, and temperature. It also explores the various cultivation strategies, such as batch, sequencing batch, fed-batch, and continuous modes, as well as advanced configurations like two-stage batch configuration and two-stage configuration with feed supply, analyzing their respective advantages and limitations. Lastly, the current trend, that is, the application of machine learning in enhancing lipid productivity has been discussed. This review comprehensively summarizes the overall research implications, and seeks to serve as a compendium on lipid production in oleaginous yeasts that also includes the recommendations for future progress in the field.