Microbial Identification Through Multispectral Infrared Imaging of Colonies: A New Type of Morpho‐Spectral Fingerprinting

We describe a proof of concept for a new microbial identification technique using Direct Frequency Infrared (DFIR) multispectral imaging. This approach combines Quantum Cascade Laser (QCL) light sources with a microbolometer array in a lensless configuration to capture detailed multispectral images of microbial colonies. These optical fingerprints blend both morphological and spectral information, without the need for staining or colony picking. A proof-of-concept database was acquired, comprising 10 strains from 8 species across 4 distinct genera. In total, 2253 microbial colonies were imaged at 9 different mid-infrared wavelengths. Machine learning classification correctly identified up to 94.4% ± 1.6 of colonies fingerprints, efficiently discriminating even closely related strains. Reducing the number of wavelengths to 4 maintained high classification performance, demonstrating the method's robustness. The resulting system is faster and simpler than existing FTIR imaging systems, making it a promising tool for microbial identification.

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Publication Details

Journal
Microbial Biotechnology
Published
2025-02-01
DOI
https://doi.org/10.1111/1751-7915.70093
Citations
4
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
6.54
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article

Microbial Identification Through Multispectral Infrared Imaging of Colonies: A New Type of Morpho‐Spectral Fingerprinting

V. Rebuffel, Pierre R. Marcoux, Mathieu Dupoy, Joël Le Galudec et al.
4 citations
Microbial Biotechnology
Spectroscopy Techniques in Biomedical and Chemical Research
6.54
article

Microbial Identification Through Multispectral Infrared Imaging of Colonies: A New Type of Morpho‐Spectral Fingerprinting

V. Rebuffel, Pierre R. Marcoux, Mathieu Dupoy, Joël Le Galudec, Laurent Duraffourg
article en
4 citations

Abstract

We describe a proof of concept for a new microbial identification technique using Direct Frequency Infrared (DFIR) multispectral imaging. This approach combines Quantum Cascade Laser (QCL) light sources with a microbolometer array in a lensless configuration to capture detailed multispectral images of microbial colonies. These optical fingerprints blend both morphological and spectral information, without the need for staining or colony picking. A proof-of-concept database was acquired, comprising 10 strains from 8 species across 4 distinct genera. In total, 2253 microbial colonies were imaged at 9 different mid-infrared wavelengths. Machine learning classification correctly identified up to 94.4% ± 1.6 of colonies fingerprints, efficiently discriminating even closely related strains. Reducing the number of wavelengths to 4 maintained high classification performance, demonstrating the method's robustness. The resulting system is faster and simpler than existing FTIR imaging systems, making it a promising tool for microbial identification.

Microbial BiotechnologyVol. 18(2)
Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), CEA Grenoble (FR), Laboratoire d'Électronique des Technologies de l'Information (FR), Université Grenoble Alpes (FR)
Reduced inequalities
Openalex Percentile: Top 4%
Spectroscopy Techniques in Biomedical and Chemical Research
6.54
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Microbial Identification Through Multispectral Infrared Imaging of Colonies: A New Type of Morpho‐Spectral Fingerprinting — V. Rebuffel, Pierre R. Marcoux, et al. · Microbial Biotechnology (2025) | TGRS Research Map | TGRS