Advances in Algal Monitoring Technologies: From Conventional Methods to Fluorescence-Based Intelligent Detection

Shuhan Huang

doi:10.54691/k0cxky68

Authors

Shuhan Huang School of Navigation, Shandong Jiaotong University, Weihai 264209, China

DOI:

https://doi.org/10.54691/k0cxky68

Keywords:

Algal monitoring; Phytoplankton; Chlorophyll fluorescence; Fluorescence spectroscopy; LED-induced fluorescence; Remote sensing; Machine learning.

Abstract

Algal monitoring supports water-quality assessment, ecosystem observation, and the timely detection of potentially harmful blooms. However, the technologies used for this purpose differ substantially in analytical target, taxonomic resolution, spatial coverage, and suitability for field deployment. This review critically examines microscopy, extracted-pigment spectrophotometry, chromatography, satellite remote sensing, and optical spectroscopy, with particular emphasis on fluorescence-based monitoring. The technological progression from laboratory chlorophyll determination to continuous in-vivo fluorescence, multi-wavelength excitation, and compact LED-based systems has increased measurement frequency and expanded opportunities for estimating algal group composition. Machine learning further enables classification and quantitative interpretation of spectral and imaging data, although reported laboratory performance does not necessarily transfer to mixed natural communities. Key limitations include spectral overlap, variable cellular pigment content, physiological regulation of fluorescence, interference from suspended particles and dissolved organic matter, calibration differences, and restricted training datasets. Portable systems additionally require demonstrated resistance to fouling and stable operation over extended deployments. Future progress is likely to depend on informative excitation channels, complementary optical measurements, embedded processing, and independent validation across environments. Integrating local sensors with regional remote sensing and targeted laboratory confirmation offers a practical route toward low-cost, real-time, intelligent monitoring while preserving the specificity and traceability required for defensible environmental decisions.

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