This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Microalgae (microscopic organisms that use light and carbon dioxide to grow) can be used to make ingredients and food for animals, pigments and potentially renewable fuels. But growing microalgae efficiently at an industrial scale is difficult.
My own research with microalgae began with their potential for biofuel production. I have been exploring how AI can help scientists scale up the growth of microalgae, particularly for the production of biofuel from microalgal species such as Chlorella vulgaris and Nannochloropsis oculata. Thousands of species of tiny microalgae are abundant in seas, rivers and lakes.
They act as primary producers, using the process of photosynthesis to convert light into proteins, fats and carbohydrates as well as other organic compounds. Microalgae can be grown in photobioreactors. These industrial systems have been designed to provide suitable conditions for photosynthetic microorganisms.
Several parameters need to be controlled during cultivation. These include light, temperature, pH and the concentration of oxygen. These parameters also influence each other.
For example, insufficient light can limit photosynthesis, while excessive light can cause photoinhibition, where too much light reduces photosynthetic efficiency. As the amount of microalgae in the reactor increases, the cells can also shade each other and reduce the amount of light available. Aeration can affect carbon dioxide supply, oxygen removal and pH at the same time.
Controlling all these parameters during cultivation can be difficult. My current research is looking at this cultivation problem more closely in the laboratory. Part of my work explores how AI-assisted monitoring and imaging could be used to analyze microalgal growth and improve cultivation.
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