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Differentiation of Fungi Using Hyperspectral Imagery for Food Inspection

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  053127,  2005 ASAE Annual Meeting . (doi: 10.13031/2013.19828) @2005
Authors:   Haibo Yao, Zuzana Hruska, Kevin DiCrispino, Kori Brabham, David Lewis, Jim Beach, Robert L. Brown, Thomas E. Cleveland
Keywords:   hyperspectral image, fungi, classification

This paper is part of a project of using hyperspectral imagery to detect pathogens such as mycotoxin-producing fungi, in grain products, such as corn. Traditionally, corn kernels have been examined for evidence of bright greenish-yellow fluorescence (BGYF), indicative of the presence of A. flavus, when illuminated with a high-intensity ultra-violet light. The BGYF approach is time and labor intensive and somewhat inaccurate. Several previous studies have examined spectral-based, non-destructive methods for the detection of fungi and toxins. This research focuses on using spectral image data for fungi and toxin detection. A tabletop hyperspectral imaging system, VNIR- 100E, is used in the study for high spectral and high spatial resolution spectral data acquisition. In this paper, a total of five toxin producing fungal species were used in two experiments. They are Penicillium chrysogenum, Fusarium moniliforme, Aspergillus parasiticus, Trichoderma viride, and Aspergillus flavus. All fungal isolates were cultured on agar in Petri-dishes under lab conditions and were imaged on day 5 of growth. The objective of this study is to use hyperspectral imagery for classification of different fungi.

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