Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: March 16, 2009
Publication Date: April 20, 2009
Citation: Ononye, A.E., Yao, H., Hruska, Z., Kincaid, R., Brown, R.L., Cleveland, T.E. 2009. Automatic Detection of Aflatoxin Contaminated Corn Kernels using Dual-Band Imagery. Proceedings of 2009 SPIE Conference, April 13-17, 2009, Orlando, Florida. 7315:73150R-1-11. 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 contaminated from healthy grain. A collaboration between ARS-SRRC, Food and Feed Safety Research Unit and Mississippi State University, Stennis Space Center, MS is exploring the use of hyperspectral imaging non-destructive technology (developed by ITD) to detect mycotoxin-producing fungi and mycotoxins in grain products. In this study, a technique is explored that automatically detects aflatoxin contaminated corn kernels by using dual-band imagery. The method makes use of fluorescence emissions from corn kernels captured under 365 nm ultra-violet light excitation. 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: Aflatoxin is a mycotoxin predominantly produced by Aspergillus flavus and Aspergillus parasitiucus fungi that grow naturally in corn, peanuts and in a wide variety of other grain products. Corn, like other grains is used as food for human and feed for animal consumption. It is known that aflatoxin is carcinogenic; therefore, ingestion of corn infected with the toxin can lead to very serious health problems such as liver damage if the level of the contamination is high. The US Food and Drug Administration (FDA) has strict guidelines for permissible levels in the grain products for both humans and animals. The conventional approach used to determine these contamination levels is one of the destructive and invasive methods that require corn kernels to be ground and then chemically analyzed. Unfortunately, each of the analytical methods can take several hours depending on the quantity, to yield a result. The development of high spectral and spatial resolution imaging sensors has created an opportunity for hyperspectral image analysis to be employed for aflatoxin detection. However, this brings about a high dimensionality problem as a setback. In this paper, we propose a technique that automatically detects aflatoxin contaminated corn kernels by using dual-band imagery. The method exploits the fluorescence emission spectra from corn kernels captured under 365 nm ultra-violet light excitation. Our approach could lead to a non-destructive and non-invasive way of quantifying the levels of aflatoxin contamination. The preliminary results shown here, demonstrate the potential of our technique for aflatoxin detection.