JOURNAL ARTICLE

Detection of fecal contamination on leafy greens by hyperspectral imaging

Sukwon KangKangjin LeeJae-Ryong SonMoon S. Kim

Year: 2011 Journal:   Procedia Food Science Vol: 1 Pages: 953-959   Publisher: Elsevier BV

Abstract

Because the contaminated fresh produce and raw materials for food with animal fecal matter can introduce foodborne illness, it is necessary to develop an automatic inspection system to detect the fecal contamination on fresh produce. The hyperspectral fluorescence imaging system using ultraviolet-A excitation (320∼400 nm) was investigated to detect the bovine fecal contamination on the abaxial and adaxial surfaces of romaine lettuce and baby spinach leaves. An image processing algorithm to detect the fecal contamination spots for public health concern was investigated while it correctly indentifies the clean leaf surfaces. The developed algorithm could successfully detect the fecal contamination spots on the adaxial and abaxial surfaces of romaine lettuce and baby spinach.

Keywords:
Contamination Spinach Feces Hyperspectral imaging Fecal coliform Leafy Biology Environmental science Horticulture Artificial intelligence Computer science Microbiology Ecology

Metrics

20
Cited By
1.76
FWCI (Field Weighted Citation Impact)
13
Refs
0.81
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Listeria monocytogenes in Food Safety
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Biotechnology
Spectroscopy and Chemometric Analyses
Physical Sciences →  Chemistry →  Analytical Chemistry
Meat and Animal Product Quality
Life Sciences →  Agricultural and Biological Sciences →  Animal Science and Zoology

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