Abstract:
Aflatoxins are the toxic metabolites produced by certain kinds of Aspergillus molds that are found naturally all over the world; they can contaminate food crops and pose a serious health threat to humans and livestock. They have been studied extensively because of being associated with various chronic and acute diseases especially immunosuppression and cancer. Aflatoxin occurrence is influenced by certain environmental conditions such as drought seasons and agronomic practices. Peanuts is highly Susceptible for aflatoxin contamination during harvesting, production and storage. Aflatoxin detection based on chemical methods is fairly accurate. However, they are time consuming, expensive and destructive. hyperspectral imaging can be used as an alternative for detection of such contaminants in a rapid and nondestructive manner. In order to classify aflatoxin contaminated peanuts from uncontaminated ones, a compact machine vision system based on hyperspectral imaging is proposed. In the proposed system both UV and Halogen excitations are used. Under ultraviolet 365 nm illumination, aflatoxin contaminated samples exhibit bright green yellowish fluorescence (BGYF). This phenomenon is used as a base for detecting aflatoxin contaminated peanuts.
