Classification of on-line poultry carcasses with backpropagation neural networks

被引:36
作者
Chen, YR [1 ]
Park, B [1 ]
Huffman, RW [1 ]
Nguyen, M [1 ]
机构
[1] USDA ARS, Beltsville Agr Res Ctr, Instrumentat & Sensing Lab, Beltsville, MD 20705 USA
关键词
D O I
10.1111/j.1745-4530.1998.tb00437.x
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
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.
引用
收藏
页码:33 / 48
页数:16
相关论文
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