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The sustainable and economically viable production of microalgae biomass for biofuels and high-value bioproducts is highly dependent on precise, multi-parametric monitoring of cultivation systems. This review provides a comprehensive overview of current approaches and technological advances in multi-sensor systems applied to photobioreactors, including flow cytometry, IR spectroscopy, RGB sensors, in situ microscopy, and software-based sensors. The integration of artificial intelligence (AI), the Internet of Things (IoT) and metaheuristic algorithms into monitoring systems is also discussed as a promising way to optimise key ecological, physicochemical, and biological parameters in real time. The report highlights critical factors that influence biomass growth and product yield, such as nutrient concentrations, light intensity, CO2 levels, pH and temperature. In addition, current technological limitations are highlighted, and future strategies for improving monitoring accuracy, automating cultivation, and improving the biosynthesis of metabolites are outlined. Through a synthesis of the literature and technological trends, this work contributes to the development of smart photobioreactor systems and provides actionable insights to improve large-scale, highly efficient microalgae cultivation in energy and environmental biotechnology.
Dębowski et al. (Sun,) studied this question.
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