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CLASSIFICATION OF ON-LINE POULTRY CARCASSES WITH BACKPROPAGATION NEURAL NETWORKS1
Authors:Y.R. CHEN  B. PARK  R.W. HUFFMAN  M. NGUYEN
Abstract:A transportable system equipped with an overhead shackle conveying line and a visible/near-infrared (Vis/NIR) spectrophotometer system was assembled and used at a poultry slaughter plant. The reflectance spectra of each poultry carcass hung on the moving shackle was measured with a stationary fiber optic probe, which was set 2 to 5 cm away from the carcass, depending on the size. Reflectance spectra of wholesome and unwholesome poultry carcasses on the moving shackle, set at 60 or 90 birds/min, were measured, either under room light or in a dark environment. The scanning time for each carcass was 0.32 s. Most of the unwholesome poultry carcasses for this study were septicemic and air-sacculitic. The average accuracy in classifying wholesome and unwholesome carcasses was above 94%. All the misclassified carcasses were air-sacculitic. With a shackle speed of 90 birds/min, the highest average accuracy was obtained when the reflectance was measured in the dark (97.5%). The results showed that the accuracy of classification could be improved with the maintenance of a consistent lighting environment. All results indicated the Vis/NIR spectrophotometer system would be a highly accurate, robust tool for on-line, real-time classification of wholesome and unwholesome carcasses.
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