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Proceedings Paper

Detection of fecal/ingesta contaminants at slaughter plants from a number of characteristic visible and near-infrared bands
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Paper Abstract

Several of visible and NIR bands were sought to explore the potential for the classification of fecal / ingesta ("F/I") objectives from rubber belt and stainless steel ("RB/SS") backgrounds. Spectral features of "F/I" objectives and "RB/SS" backgrounds showed large differences in both visible and NIR regions, due to the diversity of their chemical compositions. Such spectral distinctions formed the basis on which to develop simple three-band ratio algorithms for the classification analysis. Meanwhile, score-score plots from principal component analysis (PCA) indicated the obvious cluster separation between "F/I" objectives and "RB/SS" backgrounds, but the corresponding loadings did not show any specific wavelengths for developing effective algorithms. Furthermore, 2-class soft independent modeling of class analogy (SIMCA) models were developed to compare the correct classifications with those from the ratio algorithms. Results indicated that using ratio algorithms in the visible or NIR region could separate "F/I" objectives from "RB/SS" backgrounds with a success rate of over 97%.

Paper Details

Date Published: 20 October 2006
PDF: 9 pages
Proc. SPIE 6381, Optics for Natural Resources, Agriculture, and Foods, 63810U (20 October 2006); doi: 10.1117/12.686225
Show Author Affiliations
Yongliang Liu, Univ. of Maryland, College Park (United States)
Kuanglin Chao, USDA Agricultural Research Service (United States)
Yud-Ren Chen, USDA Agricultural Research Service (United States)
Moon S. Kim, USDA Agricultural Research Service (United States)
Xiangwu Nou, USDA Agricultural Research Service (United States)
Diane E. Chan, USDA Agricultural Research Service (United States)
Chun-Chieh Yang, Univ. of Kentucky (United States)


Published in SPIE Proceedings Vol. 6381:
Optics for Natural Resources, Agriculture, and Foods
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

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