Limnological parameters, metabarcoding, infrared spectroscopy, and chemometrics for characterizing freshwater cyanobacteria communities.

Harmful cyanobacterial blooms pose risks to the environment, humans, and animals. Rapid identification of these microorganisms is essential but still relies on costly and time-consuming techniques. This study evaluates the potential of attenuated total reflectance infrared spectroscopy (ATR-FTIR) combined with chemometrics, supported by molecular methods, to detect potentially harmful cyanobacteria. Samples were collected from 14 sites in the Rio Pardo Valley, RS, Brazil, with limnological parameters measured. Spectra (4000-650 cm⁻¹) in triplicate, and 16S rRNA metabarcoding was performed using Dada2, Phyloseq, and the CyanoSeq database. PCA and OPLS analyses were applied to integrate spectral, taxonomic, and environmental data. Twelve cyanobacterial genera were identified. Sphaerospermopsis (Zapomelová et al., 2010) dominated SP14, associated with aluminum, iron, and nitrogen levels. Dolichospermum ((Bornet & Flahault) P. Wacklin, L. Hoffmann & Komárek, 2009) and Wollea (Bornet & Flahault, 1886) correlated with phosphorus and sodium. Planktothricoides (S. Suda & M. Watanabe, 2002) showed 95.15% abundance at SP01. PC1×PC2 plots revealed location-based clustering of spectral data. ATR/OPLS models showed strong correlations with relative abundances derived from metabarcoding data, with RMSECV values from 1.3×10⁻⁵ to 5.3×10⁻⁴ and R² > 0.99. These results support ATR-FTIR and chemometrics as a promising exploratory approach for the assessment of cyanobacterial community composition in freshwater systems.