|Yao, Haibo - ITD|
|Hruska, Zuzana - ITD|
|Dicrispino, Kevin - ITD|
|Lewis, David - ITD|
|Beach, Jim - ITD|
Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: December 15, 2004
Publication Date: December 30, 2004
Citation: Yao, H., Hruska, Z., Dicrispino, K., Lewis, D., Beach, J., Brown, R.L., Cleveland, T.E. 2004. Hyperspectral imagery for characterization of different corn genotypes. Proceedings of SPIE. 5587:144-152. Interpretive Summary: Aflatoxins are poisons produced by the fungus Aspergillus flavus after it infects agricultural commodities such as corn. Since aflatoxins in food and feed are regulated, enhanced ability to detect and measure fungal growth and aflatoxin contamination of corn could contribute significantly towards the separation of contamination from healthy grain. A collaboration between ARS-SRRC, Food and Feed Safety Research Unit and the Institute for Technology Development (ITD), Stennis Space Center, MS, is exploring the use of hyperspectral imaging non-destructive technology (developed by ITD) to detect mycotoxin-producing fungi in grain products. The initial experiments were performed on corn kernels to observe whether this technology could characterize genetically-similar and dissimilar corn lines. Results indicate that hyperspectral imaging can be successfully employed to differentiate corn lines with genetic differences. Further experiments may lead to this technology being used to rapidly and accurately detect/measure Aspergillus flavus infection/aflatoxin contamination of corn without destruction of healthy grain. This could provide a useful tool to both growers and buyers in the corn industry that could enhance protection of food and feed, as well as increase profits.
Technical Abstract: USDA and the Institute for Technology Development are currently collaborating on a project using hyperspectral imagery to detect pathogens such as mycotoxin producing molds in grain products. The initial experiments are being implemented on corn kernels. When molds appear on corn, reflectance spectra from the molds and corn are mixed. Therefore, it is important to characterize the corn reflectance, which is the background reflectance in the image. The objective of this study was to qualitatively identify and quantify kernel signatures of several corn genotypes. Four different corn genotypes (genetically distinct corn lines) and four near isogenic corn lines were prepared at the USDA laboratory. The study used a visible-near-infrared hyperspectral imaging system for data acquisition. The imaging system utilizes focal plane pushbroom scanning for high spatial and high spectral resolution imaging. Procedures were developed for optimum image calibration and image processing. It was expected that the results would be useful for reducing the background influence of corn in mold detection and would also be applicable in corn genotype identification, especially among corn lines with different resistance levels to molds.