No abstract

No abstract

In vivo pigment fluorescence methods allow simple real-time detection and quantification of freshwater algae and cyanobacteria. Available models are still limited to high-cost fluorometers, validated for single instruments or individual water bodies, preventing data comparison between multiple instruments, and thus, restricting their use in large-scale monitoring programs. Moreover, few models include corrections for optical interference (water turbidity and colored dissolved organic matter, CDOM). In this study, we developed simple models to predict phytoplankton and cyanobacterial chlorophyll a (Chl a) concentrations based on Chl a and C-phycocyanin in vivo fluorescence, using multiple low-cost handheld fluorometers. We aimed to: (1) fit models to mixed cyanobacterial and microalgal cultures; (2) cross-calibrate nine fluorometers of the same brand and series; (3) correct the CDOM and turbidity effects; and (4) test the algorithms' performance with natural samples. We achieved comparable results between nine instruments after the cross-calibration, allowing their simultaneous use. We obtained algorithms for total and cyanobacterial Chl a estimation. We developed parametric corrections to remove CDOM and turbidity interferences in the algorithms. Five sampling sites (from a lake, a stream, and an estuary) were used to test the algorithms using eight cross-calibrated fluorometers. The models showed their best performance after CDOM and turbidity corrections (total Chl a: R 2 = 0.99, RMSE = 7.8 μg Chl a L −1 ; cyanobacterial Chl a: R 2 = 0.98, RMSE = 9.8 μg Chl a L −1 ). In summary, our models can quantify total phytoplankton and cyanobacterial Chl a in real time with multiple low-cost fluorometers, allowing its implementation in large-scale monitoring programs.