The ability of X-rays to traverse through matter and reveal hidden contaminants or defects has led to their extensive use in manufacturing industries for quality control inspection. The difficulties inherent in the detection of defects and contaminants in food products have kept the use of X-ray in that industry limited mainly to the packaged foods sector. Nevertheless, the need for non-destructive internal product inspection has motivated a considerable research effort in this field spanning many decades. Improvements in technology, especially more compact and affordable high voltage power sources, high speed computing, and high resolution detector arrays, have made many X-ray detection tasks possible today that were previously unfeasible. These improvements can be expected to continue into the future. The purpose of this article is to give a review of research activity related to the use of X-ray imaging for the detection of defects and contaminants in agricultural commodities and discuss improvements in technology required to improve these detection capabilities.

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A non-destructive, real time device was developed to detect insect damage, sprout damage, and scab damage in kernels of wheat. Kernels are impacted onto a steel plate and the resulting acoustic signal analyzed to detect damage. The acoustic signal was processed using four different methods: modeling of the signal in the time-domain, computing time-domain signal variances and maximums in short-time windows, analysis of the frequency spectrum magnitudes, and analysis of a derivative spectrum. Features were used as inputs to a stepwise discriminant analysis routine, which selected a small subset of features for accurate classification using a neural network. For a network presented with only insect damaged kernels (IDK) with exit holes and undamaged kernels, 87% of the former and 98% of the latter were correctly classified. It was also possible to distinguish undamaged, IDK, sprout-damaged, and scab-damaged kernels. © 2005 Elsevier Inc. All rights reserved

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