Automated phenotyping of microalgae: scalable solution for high-throughput analysis

Laboratory automation is transforming biotechnology, yet current microalgal phenotyping platforms lack the integration and scalability needed for comprehensive trait analysis under diverse conditions. To address this, PhenoSelect was developed, an automated system combining robotics, spectroscopy, fluorometry, flow cytometry, and data analytics for high-throughput, multi-trait phenotyping. Five algal species were profiled across 96 environmental and chemical conditions, quantifying photosynthetic efficiency, growth rate, and cell size. Phenotypic plasticity was quantified using convex hull volume, with trait patterns visualized through Ranked Spider Plots and heatmaps. Haematococcus pluvialis exhibited the largest phenome size, indicating broad plasticity, while Nannochloropsis australis showed the smallest. Optimal growth and photosynthetic performance varied by species, with low light and nutrient-rich media as key drivers. PhenoSelect enables precise, reproducible phenotyping with minimal manual input, supporting applications in biofuels, bioremediation, and nutraceuticals. By accelerating strain screening and optimisation, PhenoSelect bridges phenotyping gaps and drives scalable microalgal biotechnology.