Vijay Rayamajhi

Mudasir Hussain, Vijay Rayamajhi, Kiwan Kim, SangMok Jung, and HyunWoung Shin. Microbiol. Biotechnol. Lett. 2026;54:1-18. https://doi.org/10.48022/mbl.2607.07011

Vijay Rayamajhi, Yunji An, Huijeong Byeon, Jihyun Lee, Taesoo Kim, AhJung Choi, JongDae Lee, KwangSoo Lee, ChulHyun Kim, HyunWoung Shin, and SangMok Jung. Microbiol. Biotechnol. Lett. 2026;54:1-13. https://doi.org/10.48022/mbl.2603.03015

Microalgae are unicellular, industrially important organisms that are used extensively in a range of industrial, environmental, and biorefinery applications. They can produce lipids, carbohydrates, and possibly additional vital bioactive substances. The increasing popularity of artificial intelligence (AI) in microalgae research can be attributed to its algorithms’ ability to manage the complexity of unexpected biosystems. In the case of microalgae-based biorefineries, AI technology can also help uncover system dynamics and uncertainties, provide helpful predictive analytics, and expedite the optimisation process. AI is used in microalgal cultivation to optimise carbon capture, biomass production, and conditions for growth. Additionally, it is employed for genome editing, automated monitoring, and lipid accumulation enhancement. However, its uses are broad and constantly growing. Furthermore, critical environmental parameters in microalgae culture, including temperature, light intensity, pH, dissolved oxygen, and nutrient levels, may be continually monitored and controlled by internet of things (IoT)-based devices. This review comprehensively summarises the latest applications of AI technology in the field of microalgae cultivation and the role of IoT-based automatic control.