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ACQUA: Automated Cyanobacterial Quantification Algorithm for toxic filamentous genera using spline curves, pattern

Emanuele Gandola1, Manuela Antonioli2, Alessio Traficante3

  • 1University of Rome Tor Vergata, Department of Biology, via della Ricerca Scientifica 1, 00133 Rome, Italy; Department of Mathematics, University of Rome Tor Vergata, via della Ricerca Scientifica 1, 00133 Rome, Italy.

Journal of Microbiological Methods
|March 26, 2016
PubMed
Summary

Automated Cyanobacterial Quantification Algorithm (ACQUA) accurately identifies toxic cyanobacteria in water. This automated method aids in rapid freshwater quality assessment and monitoring of harmful algal blooms.

Keywords:
AlgorithmBright field imagingCyanobacteriaFilamentous generaImage analysisQuantification

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Area of Science:

  • Environmental microbiology
  • Water quality monitoring
  • Algorithmic analysis

Background:

  • Toxigenic cyanobacteria pose global health risks through water contamination.
  • Microscopy is crucial for monitoring cyanobacteria abundance and growth.

Purpose of the Study:

  • To introduce ACQUA, a novel automated image analysis method for filamentous cyanobacteria.
  • To enable accurate identification and quantification of specific toxic cyanobacteria genera.

Main Methods:

  • Developed a pre-processing algorithm to isolate cyanobacteria filaments.
  • Utilized spline-fitting for accurate morphometric analysis of complex filaments.
  • Implemented a machine-learning algorithm with 17 pattern indicators for genus recognition.

Main Results:

  • ACQUA accurately distinguishes between five key freshwater cyanobacteria genera.
  • Validated against manual counts in Italian volcanic lake samples.
  • Demonstrated high speed and accuracy in cyanobacterial assemblage characterization.

Conclusions:

  • ACQUA offers a fast and reliable tool for automated cyanobacteria monitoring.
  • Enhances the assessment of freshwater quality and management of harmful algal blooms.
  • Facilitates rapid characterization of cyanobacterial communities in aquatic environments.