Poster + Presentation + Paper
4 March 2022 Optical determination of colony size and color of common veterinary bacteria on a chromogenic agar
Author Affiliations +
Conference Poster
Abstract
Companion and farm animals can be an important source of antimicrobial-resistance microorganisms. In pets like dogs and cats, urinary tract infections (UTI) are a common reason for using antibiotics, often prescribed empirically due to the high costs and long duration of the official laboratory tests. Therefore, chromogenic agars for in-clinic use have recently appeared, which offer bacteria species identification and antimicrobial susceptibility testing (AST). In our work, we employed machine vision for colony color and diameter determination of some prevalent companion animal bacteria, which grew after 24 or 48 hours of incubation on the commercially available chromogenic agar Uriselect. We analyzed 26 samples, including Staphylococcus pseudintermedius (10), Staphylococcus felis (4), Escherichia coli (4), Enterococcus faecalis (4), and Pseudomonas aeruginosa (4). Results showed that E. coli and Ent. faecalis exhibited unique colony colors (red, blue) and diameter (larger or smaller). Furthermore, the colony size did not change significantly during the entire incubation time. On the other hand, both staphylococcus colonies were small initially, but their size almost tripled in the following 24 hours, when colonies finally exhibited a pink color. P. aeruginosa proved to be orange-green. This study showed that our optical system could detect uniquely colored and sized canine and feline bacteria colonies, which grew on Uriselect chromogenic agar.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Blaž Cugmas, Jaša Samec, Blaž But, Eva Štruc, and Miha Avberšek "Optical determination of colony size and color of common veterinary bacteria on a chromogenic agar", Proc. SPIE 11939, Photonic Diagnosis, Monitoring, Prevention, and Treatment of Infections and Inflammatory Diseases 2022, 1193904 (4 March 2022); https://doi.org/10.1117/12.2607596
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KEYWORDS
Bacteria

Machine vision

Image processing

Microorganisms

Pathogens

Resistance

RGB color model

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