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United States Department of Agriculture

Agricultural Research Service

Related Topics


Location: Food and Feed Safety Research

2010 Annual Report

1a. Objectives (from AD-416)
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.

1b. Approach (from AD-416)
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.

3. Progress Report
Based on the initial reflectance based imaging experiments, a fluorescence hyperspectral (using many individual wavelengths of light from visible light, as well as, ultraviolet to infrared) imaging system was developed and used to study fluorescence hyperspectral properties of healthy and contaminated corn kernels. The contaminated corn kernels were prepared by inoculating corn ears with Aspergillus flavus spores in the field. After imaging, each corn kernel was examined for aflatoxin (a potent carcinogen) concentration using single kernel chemical analysis. The results indicate fluorescence hyperspectral imaging has the potential for detecting aflatoxin contaminated corn. A Fluorescence Peak Shift (FPS) phenomenon was identified among groups of kernels with different aflatoxin contamination levels. The peak shifted toward longer wavelength, in the blue region, for the highly contaminated kernels and vice versa. Highly contaminated kernels also had a lower fluorescence peak magnitude compared with the less contaminated kernels. It was also found that a general negative correlation exists between measured aflatoxin and the fluorescence image bands in the blue and green spectral regions. An aflatoxin detection algorithm (a defined set of mathematical parameters to achieve a result) is under development by using significant wavelengths identified in the analysis. The algorithm is used with the prototype fluorescence multi-spectral imaging system. The fluorescence multi-spectral imaging system will have the ability to tune to specific key wavelengths for aflatoxin detection and will be suitable for rapid detection and easy deployment. The system is currently being tested in scaled-up experiments where groups of corn kernels are examined simultaneously for the detection of aflatoxin. Each image includes 25 grams of corn, which is half the size of a standard sample for chemical analyses widely used in grain inspection stations. A 1 kg sample processing system is also in the construction phase, and will be tested in 2011. Research progress was monitored through teleconferencing, frequent email communications, and reports.

4. Accomplishments

Last Modified: 10/18/2017
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