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Proceedings Paper

The development of a line-scan imaging algorithm for the detection of fecal contamination on leafy geens
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Paper Abstract

This paper reports the development of a multispectral algorithm, using the line-scan hyperspectral imaging system, to detect fecal contamination on leafy greens. Fresh bovine feces were applied to the surfaces of washed loose baby spinach leaves. A hyperspectral line-scan imaging system was used to acquire hyperspectral fluorescence images of the contaminated leaves. Hyperspectral image analysis resulted in the selection of the 666 nm and 688 nm wavebands for a multispectral algorithm to rapidly detect feces on leafy greens, by use of the ratio of fluorescence intensities measured at those two wavebands (666 nm over 688 nm). The algorithm successfully distinguished most of the lowly diluted fecal spots (0.05 g feces/ml water and 0.025 g feces/ml water) and some of the highly diluted spots (0.0125 g feces/ml water and 0.00625 g feces/ml water) from the clean spinach leaves. The results showed the potential of the multispectral algorithm with line-scan imaging system for application to automated food processing lines for food safety inspection of leafy green vegetables.

Paper Details

Date Published: 29 May 2013
PDF: 7 pages
Proc. SPIE 8721, Sensing for Agriculture and Food Quality and Safety V, 87210G (29 May 2013); doi: 10.1117/12.2016030
Show Author Affiliations
Chun-Chieh Yang, Agricultural Research Service (United States)
Moon S. Kim, Agricultural Research Service (United States)
Yung-Kun Chuang, National Taiwan Univ. (Taiwan)
Hoyoung Lee, Agricultural Research Service (United States)

Published in SPIE Proceedings Vol. 8721:
Sensing for Agriculture and Food Quality and Safety V
Moon S. Kim; Shu-I Tu; Kuanglin Chao, Editor(s)

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