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United States Department of Agriculture

Agricultural Research Service

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Research Project: DEVELOPMENT OF RAPID, NON-DESTRUCTIVE HYPERSPECTRAL IMAGING METHODOLOGY TO MEASURE FUNGAL GROWTH AND AFLATOXIN CONTAMINATION

Location: Food and Feed Safety Research

Project Number: 6435-42000-021-09
Project Type: Specific Cooperative Agreement

Start Date: Jul 01, 2009
End Date: Jun 30, 2014

Objective:
Identify and quantify aflatoxin-producing fungi on corn, using a non-destructive hyperspectral imaging system. Produce spectral libraries for fungus alone and in infected corn. Determine spectral differences between different corn varieties, resistant and susceptible to aflatoxin contamination and infected and un-infected with aflatoxin producing fungi. Develop rapid, non-destructive hyperspectral imaging methodology to measure fungal growth and aflatoxin in corn kernels and spectral signatures associated with traits for resistance to fungal infection and aflatoxin contamination in corn kernels. Test system's effectiveness in laboratory and field situations.

Approach:
Corn kernel varieties with varying levels of resistance to aflatoxin producing fungi will be collected and imaged using a tabletop hyperspectral scanning imaging system. Kernels will be spectrally analyzed to determine how much the UV, visible, and near infrared portions of the electromagnetic spectrum differ from one corn variety to another. Cultures of aflatoxin producing and non-producing fungi will also be imaged and the spectral fingerprints will be collected to produce a "spectral library" of the different strains of fungi. These data will be used to determine if hyperspectral imaging can then be used to differentiate and quantitate the varying fungal strains and/or their aflatoxin production both in pure fungal culture and in fungally infected kernels from corn varieties either resistant or susceptible to aflatoxin contamination. Techniques also will be investigated during ongoing experiments to determine the best imaging environment in which to accomplish hyperspectral analyses, such as type and direction of lighting. Once appropriate algorithms are developed, the system will be tested in various laboratory and field experiments to determine the efficacy of the system.

Last Modified: 8/27/2014
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