Abstract:
Aflatoxin contamination in corn is a serious problem for both producers and consumers. The present study applied the Spectral Angle Mapper classification technique to cla...Show MoreMetadata
Abstract:
Aflatoxin contamination in corn is a serious problem for both producers and consumers. The present study applied the Spectral Angle Mapper classification technique to classify single corn kernels into contaminated and healthy groups. Fluorescence hyperspectral images were used in the classification. Actual corn aflatoxin concentration was chemically determined using the VICAM analytical method for quantification purpose. An obvious fluorescence peak shift was observed to be associated with the aflatoxin contaminated corn. Aflatoxin classification levels were based on Food and Drug Administration's regulation, including 20 ppb (parts per billion) for human consumption and 100 ppb for feed. Classification accuracy for the 20 ppb level is 86% with a false positive rate of 15%. For the 100 ppb level, the accuracy is 88% with a false positive rate of 16%. The results indicate that the Spectral Angle Mapper method and fluorescence hyperspectral imagery have the potential to classify aflatoxin contaminated corn kernels.
Published in: 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
Date of Conference: 14-16 June 2010
Date Added to IEEE Xplore: 04 October 2010
ISBN Information: