To improve the efficiency of microalgal production it is essential to optimise cultivation conditions and characterise production strains. We have developed a customised robotic platform that enables high-throughput screenings of environmental conditions (e.g. nutrients, light) and cell response characterisation.

Objective/mission (The vision): To further enhance automation, reproducibility and data analysis pipelines.

Research approach (The initiative): Streamline the automated data processing pipeline from data collection to data analysis across different software packages. Optimisation and integration of process controls of key variables.

Impacts and applications: High-throughput nutrient and light optimisation screens fast tracks production species selection, bioprocess optimisation and scale up. Data from these screens also supports mathematical, technoeconomic and life cycle modelling of advanced next generation solar factory systems.

Project members

Key contacts

Professor Ben Hankamer

Professorial Research Fellow
Institute for Molecular Bioscience

Dr Juliane Wolf

Research Fellow
Institute for Molecular Bioscience