Royal Netherlands Institute for Sea Research
Royal Netherlands
Institute for Sea Research

Pattern Recognition of Seaweed Constituents; correlation, differences and quality

Metabolomics, multivariate analysis, modelling (R)

Fourier transform infrared spectroscopy proved to be a convenient and reliable technique to evaluate plant quality and authenticity. The main goal of this research is to investigate the possibility for seaweed. The obtained data is associated with multivariate analysis to identify biochemical changes. Is it possible to discriminate between seaweed cultivated and treated under different conditions (PCA) or is it even suitable to perform partial least square (PLS) on major biopolymers such as polysaccharides, proteins, lipids or polyphenols? It would lead to a much faster method for researchers to determine the effect of treatments on the prominent constituents present. No laborious sample treatment would be necessary anymore.

Within a project that deals with the effect of abiotic changes on seaweed growth we have samples (and FTIR data) available for the following research topic:

  • Comparison of the use and results of a web-based metabolomics platform with metabolomics R packages present. 

We are seeking a bachelor or master student with an interest in metabolomics who likes to model in R. A student that is interested in chemical composition and multivariate data interpretation. Students that hold a keen interest in research on the cutting edge between marine biology, chemistry, mathematics and modeling. A student in bioinformatics. 

More information & contact

For more information and to apply, please contact Dorien Derksen,

Relevant publications

Wagner, H., Jebsen, C. and Wilhelm, C. (2019), Monitoring cellular C:N ratio in phytoplankton by means of FTIR-spectroscopy. J. Phycol., 55, 543-551,

Eva Gómez-Ordóñez, Pilar Rupérez (2011), FTIR-ATR spectroscopy as a tool for polysaccharide identification in edible brown and red seaweeds, Food Hydrocolloids, 25, 1514-1520,