On a real time method for the detection of mold using fluorescence imaging
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Authors
Macklin, M.
Holmes, W.S.
Sidhu, Deepinder
Yee, Nigel
Holmes, W.S.
Sidhu, Deepinder
Yee, Nigel
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2025-11-06
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Conference Contribution - Oral Presentation
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Keyword
mould growth detection
fungal spores
fluorescence microscopy
fungal spores
fluorescence microscopy
ANZSRC Field of Research Code (2020)
Citation
Macklin, M., Holmes, W.S., Sidhu, D. & Yee, N. (2025, November, 6). On a real time method for the detection of Mold using fluorescence imaging [Paper presentation] School of Environmental and Animal Sciences Research Symposium 2025, Auckland, New Zealand
https://hdl.handle.net/10652/7111
Abstract
Indoor Mold contamination poses significant health risks including respiratory irritation, asthma exacerbation, allergic reactions, and mycotoxin exposure, yet current detection methods remain slow and costly. Current Mold detection methods, such as ERMI testing and traditional culturing require specialized laboratory facilities, trained personnel, and long processing times, hence limiting real-time assessment and rapid response to contamination. This project investigates a low-cost, rapid Mold detection system using ultraviolet (UV) fluorescence of ergosterol, a fungal sterol with strong emission when excited at ~280 nm, as a specific biomarker distinguishing fungal spores from plant debris and other particulates. To reduce false positives, the system combines ergosterol fluorescence with polarized light to detect chitin birefringence in fungal cell walls. The prototype system combines a Raspberry Pi HQ camera, UV LED excitation array, and optical long-pass filters within a modified 3D printer enclosure with an automated XYZ gantry. It explores automated imaging and machine vision as a replacement for manual microscopy for detection, offering scalability and enabling future machine learning–based detection and characterisation. This approach aims to provide continuous, automated environmental monitoring at substantially reduced cost, with applications in indoor air quality assessment, food safety, and HVAC contamination detection. Rapid, accessible mold screening could improve building health management, reduce remediation costs, and mitigate health risks for sensitive populations.
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