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Rapid detection methods and field applications for two types of red tide algae in Fujian coastal areas

Rapid detection methods and field applications for two types of red tide algae in Fujian coastal areas
Red tides in Fujian’s coastal waters—dominated by Prorocentrum donghaiense and Skeletonema costatum—are increasing in frequency and impact, yet prevailing detection methods (microscopy, molecular assays) are labor-intensive, time-consuming, and instrument-dependent, limiting rapid field deployment. We generated species-specific monoclonal antibodies against P. donghaiense and S. costatum and established a colloidal gold immunochromatographic (GIC) test strip workflow for on-site detection. The assay provides semi-quantitative readouts (10–15 minutes) without complex instrumentation, using standardized visual interpretation (control-line validity; test-line positivity) and image analysis for optional T/C-based trend estimation. Field applicability was evaluated at fixed sites in Yundang Lake, with strip results compared against routine microscopic enumeration to assess sensitivity, specificity, and agreement. The GIC strips enabled rapid, on-site identification of the target species within 10–15 minutes and showed strong discrimination against non-target algae under standardized conditions. Operational detection limits were suitable for near-threshold early warning, and test-line intensities reflected spatial differences in algal abundance across sites. Field results closely matched microscopy, supporting reliable tracking of site-level density trends and confirming practical performance in a real-world lagoon environment.This GIC-based approach addresses a key monitoring gap by coupling speed, simplicity, and field portability with species-level specificity, enabling near-real-time decision support for harmful algal bloom management. The method reduces reliance on specialized personnel/equipment and can be integrated into routine surveillance as a rapid screening tool; future work can extend species coverage (panelization), strengthen early-detection capability (e.g., preconcentration, reader-based quantification), and validate robustness across broader aquatic matrices.

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#climate monitoring
#in-situ monitoring
#climate change impact