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Proceedings Paper

Hyperspectral imaging system for food safety: detection of fecal contamination on apples
Author(s): Moon S. Kim; Kevin Chao; Yud-Ren Chen; Diane Chan; Patrick M. Mehl
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Paper Abstract

We examined fecal contamination on apples, as part of on-going food safety research, with the use ofthe recently developed hyperspectral imaging system that has a spectralrange spanning the VIS to NIR region ofthe spectrum from 400 to 900 nm. Both reflectance and fluorescence techniques for detection ofexogenous fecal contamination on four apple varieties, 'Red Delicious', 'Gala', 'Fuji' and 'Golden Delicious' were evaluated. Thick patches and thin, transparent smear spots offresh dairy cow manure were empirically created on these apples to emulate fecal contamination. In addition, these spots were created on sun-exposed side and shaded side surfaces to account for natural color variations due to environmental growth conditions and ripeness. Spectral features from both reflectance and fluorescence spectra of samples including fecal contaminated spots were evaluated to determine wavelengths where minima, maxima, and plateau occur. Images at these wavelengths were used to create combinations ofsimple two band ratios, second differences, normalized differences, and absorption depth images. Preliminary results ofthese simplistic multispectralapproaches indicatedthatthe reflectance method can differentiate thickpatches ofmanure from regions of normal apple surfaces using a two NIR band ratio (R8501R800) with a simple threshold. However, for the detection ofthin manure spots, the reflectance methodmay require more complicated image processing approaches. Fluorescence techniques with a simple two band ratio (F6801F450) differentiated normal apple surfaces from contaminated spots regardless of apple skin coloration and thickness of manure treatments. These results will be further refmed to develop a rapid on-line multispectral detection system.

Paper Details

Date Published: 13 March 2001
PDF: 11 pages
Proc. SPIE 4206, Photonic Detection and Intervention Technologies for Safe Food, (13 March 2001); doi: 10.1117/12.418727
Show Author Affiliations
Moon S. Kim, U.S. Department of Agriculture (United States)
Kevin Chao, U.S. Department of Agriculture (United States)
Yud-Ren Chen, U.S. Department of Agriculture (United States)
Diane Chan, U.S. Department of Agriculture (United States)
Patrick M. Mehl, U.S. Department of Agriculture (United States)

Published in SPIE Proceedings Vol. 4206:
Photonic Detection and Intervention Technologies for Safe Food
Yud-Ren Chen; Shu-I Tu, Editor(s)

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