Microalgae lipids detection and quantification method towards online real-time monitoring: A review

Abstract

Bioprospecting toward biofuel has appeared as a sustainable and alternative energy option as fossil fuels are finite and causing a large number of environmental problems such as global warming by the greenhouse effect, leading the development of alternative substantial energy has attracted more and more attention. Microalgae are potential candidates as third generation biofuel producers to tackle this problem as they can produce an abundance of value-added products such as triacylglycerols which is an energy-rich fatty acid under stress-condition. However, the productivity of such biofuels is still low as the lipid accumulation phase of microalgae varies from time to time. In order to improve productivity, microalgae lipids must be harvested at the most suitable time when microalgae accumulated the highest amount lipids. Hence, this review highlights various quantification and detection methods of microalgae lipids, ranging from conventional methods like gravimetric and chromatographic techniques to non-conventional methods like fluorescent staining, Raman scattering, and dielectric insulation. While conventional methods require a series of procedures, including biomass dehydration and lipid extraction, non-conventional methods provide advantages such as rapidity, low cost, and smaller sample sizes needed. Future prospects revealed that real-time monitoring and online measurement of lipid content in microalgae is required to quantify the intracellular lipid level of microalgae in controlling and rapidly adjusting the growing conditions for cultivation. These real-time results, combined with the Internet of Things (IoT) technology, can be further processed using machine learning to maximize the productivity of microalgae as an alternative biofuel producer.