Paper
7 November 2005 Hyperspectral imagery for observing spectral signature change in Aspergillus flavus
Kevin DiCrispino, Haibo Yao, Zuzana Hruska, Kori Brabham, David Lewis, Jim Beach, Robert L. Brown, Thomas E. Cleveland
Author Affiliations +
Abstract
Aflatoxin contaminated corn is dangerous for domestic animals when used as feed and cause liver cancer when consumed by human beings. Therefore, the ability to detect A. flavus and its toxic metabolite, aflatoxin, is important. The objective of this study is to measure A. flavus growth using hyperspectral technology and develop spectral signatures for A. flavus. Based on the research group's previous experiments using hyperspectral imaging techniques, it has been confirmed that the spectral signature of A. flavus is unique and readily identifiable against any background or surrounding surface and among other fungal strains. This study focused on observing changes in the A. flavus spectral signature over an eight-day growth period. The study used a visible-near-infrared hyperspectral image system for data acquisition. This image system uses focal plane pushbroom scanning for high spatial and high spectral resolution imaging. Procedures previously developed by the research group were used for image calibration and image processing. The results showed that while A. flavus gradually progressed along the experiment timeline, the day-to-day surface reflectance of A. flavus displayed significant difference in discreet regions of the wavelength spectrum. External disturbance due to environmental changes also altered the growth and subsequently changed the reflectance patterns of A. flavus.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kevin DiCrispino, Haibo Yao, Zuzana Hruska, Kori Brabham, David Lewis, Jim Beach, Robert L. Brown, and Thomas E. Cleveland "Hyperspectral imagery for observing spectral signature change in Aspergillus flavus", Proc. SPIE 5996, Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, 599606 (7 November 2005); https://doi.org/10.1117/12.631066
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Cited by 4 scholarly publications.
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KEYWORDS
Reflectivity

Contamination

Hyperspectral imaging

Fungi

Imaging systems

Calibration

Spectral resolution

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