Impact of Ibuprofen on Marine Algal Metabolites Investigated Using a Coplanar Microwave Sensing Probe and Machine Learning

Seaweed is an important primary producer of seawater. Its existence is not only of great significance to the Marine ecosystem, but also creates economic value through algae metabolites such as lipids, sugars, and pigments. As the seaweed grows, other nutrients in the environment, as well as metabolites from other Marine organisms, cause the algae to produce some natural pigments that have high nutritional value for the human body. However, in recent years, the identification of a class of pollutants known as emerging pollutants (EPs) has brought attention to their role as significant water contaminants, adversely impacting the endocrine systems of both humans and wildlife. When these pollutants enter the sea water, they affect the growth of seaweed and indirectly cause the change of algae metabolites. Consequently, there will be a variety of secondary pollutants that complicated the understanding of their impact on marine ecosystems. Thus, there is an urgent need to develop smart and intelligent techniques to monitor the EPs and their impacts on marine organisms. Dielectric spectroscopy can quickly and accurately obtain information regarding the material properties, so as to realize the non-destructive and rapid measurement of the samples. Thus, this method is more and more favored by researchers. In this paper, a customized one port PCB based CPW probe for dielectric spectroscopy is proposed to study the influence of ibuprofen as an example of emerging pollutants on marine algae growth activity. Leveraging machine learning in conjunction with traditional techniques, we analyze the impact of different concentrations of ibuprofen on marine algae growth activity in this work.