Issue 22, 2023

AI facilitated fluoro-electrochemical phytoplankton classification

Abstract

Marine phytoplankton is extremely diverse. Counting and characterising phytoplankton is essential for understanding climate change and ocean health not least since phytoplankton extensively biomineralize carbon dioxide whilst generating 50% of the planet's oxygen. We report the use of fluoro-electrochemical microscopy to distinguish different taxonomies of phytoplankton by the quenching of their chlorophyll-a fluorescence using chemical species oxidatively electrogenerated in situ in seawater. The rate of chlorophyll-a quenching of each cell is characteristic of the species-specific structural composition and cellular content. But with increasing diversity and extent of phytoplankton species under study, human interpretation and distinction of the resulting fluorescence transients becomes increasingly and prohibitively difficult. Thus, we further report a neural network to analyse these fluorescence transients, with an accuracy >95% classifying 29 phytoplankton strains to their taxonomic orders. This method transcends the state-of-the-art. The success of the fluoro-electrochemical microscopy combined with AI provides a novel, flexible and highly granular solution to phytoplankton classification and is adaptable for autonomous ocean monitoring.

Graphical abstract: AI facilitated fluoro-electrochemical phytoplankton classification

Supplementary files

Article information

Article type
Edge Article
Submitted
04 apr 2023
Accepted
02 maj 2023
First published
02 maj 2023
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2023,14, 5872-5879

AI facilitated fluoro-electrochemical phytoplankton classification

H. Chen, S. Barton, M. Yang, R. E. M. Rickaby, H. A. Bouman and R. G. Compton, Chem. Sci., 2023, 14, 5872 DOI: 10.1039/D3SC01741A

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