Bridging artificial intelligence and fucoxanthin for the recovery and quantification from microalgae

A review on machine learning approaches for microalgae cultivation systems

Microalgae plays a crucial role in biomass production within aquatic environments and are increasingly recognized for their potential in generating biofuels, biomaterials, bioactive compounds, and bio-based chemicals. This growing significance is driven by the need to address imminent global challenges such as food and fuel shortages. Enhancing the value chain of bio-based products necessitates the implementation of an advanced screening and monitoring system. This system is crucial for tailoring and optimizing the cultivation conditions, ensuring the lucrative and efficient production of the final desired product. This, in turn, underscores the necessity for robust predictive models to accurately emulate algae growth in different conditions during the initial cultivation phase and simulate their subsequent processing in the downstream stage. In pursuit of these objectives, diverse mechanistic and machine learning-based methods have been independently employed to model and optimize microalgae processes. This review article thoroughly examines the techniques delineated in the literature for modeling, predicting, and monitoring microalgal biomass across various applications such as bioenergy, pharmaceuticals, and the food industry. While highlighting the merits and limitations of each method, we delve into the realm of newly emerging hybrid approaches and conduct an exhaustive survey of this evolving methodology. The challenges currently impeding the practical implementation of hybrid techniques are explored, and drawing inspiration from successful applications in other machine-learning-assisted fields, we review various plausible solutions to overcome these obstacles.

Microalgae biofuels: illuminating the path to a sustainable future amidst challenges and opportunities

The development of microalgal biofuels is of significant importance in advancing the energy transition, alleviating food pressure, preserving the natural environment, and addressing climate change. Numerous countries and regions across the globe have conducted extensive research and strategic planning on microalgal bioenergy, investing significant funds and manpower into this field. However, the microalgae biofuel industry has faced a downturn due to the constraints of high costs. In the past decade, with the development of new strains, technologies, and equipment, the feasibility of large-scale production of microalgae biofuel should be re-evaluated. Here, we have gathered research results from the past decade regarding microalgae biofuel production, providing insights into the opportunities and challenges faced by this industry from the perspectives of microalgae selection, modification, and cultivation. In this review, we suggest that highly adaptable microalgae are the preferred choice for large-scale biofuel production, especially strains that can utilize high concentrations of inorganic carbon sources and possess stress resistance. The use of omics technologies and genetic editing has greatly enhanced lipid accumulation in microalgae. However, the associated risks have constrained the feasibility of large-scale outdoor cultivation. Therefore, the relatively controllable cultivation method of photobioreactors (PBRs) has made it the mainstream approach for microalgae biofuel production. Moreover, adjusting the performance and parameters of PBRs can also enhance lipid accumulation in microalgae. In the future, given the relentless escalation in demand for sustainable energy sources, microalgae biofuels should be deemed a pivotal constituent of national energy planning, particularly in the case of China. The advancement of synthetic biology helps reduce the risks associated with genetically modified (GM) microalgae and enhances the economic viability of their biofuel production.