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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #329926

Research Project: Sensing Technologies for the Detection and Characterization of Microbial, Chemical, and Biological Contaminants in Foods

Location: Environmental Microbial & Food Safety Laboratory

Title: Waveband selection and algorithm development to distinguish fecal contamination using multispectral imaging with solar light

Author
item Everard, Colm - Us Forest Service (FS)
item Cho, Hyunjeong - Us Forest Service (FS)
item Kim, Moon
item O'donnell, Colm - University College Dublin

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 6/8/2016
Publication Date: 7/30/2016
Citation: Everard, C., Cho, H., Kim, M.S., O'Donnell, C. 2016. Waveband selection and algorithm development to distinguish fecal contamination using multispectral imaging with solar light. ASABE Annual International Meeting, St. Joseph, MI. ASABE Paper No. 162461723.

Interpretive Summary: Fecal contamination in fresh produce fields caused by animals entering the fields can lead to outbreaks of foodbourne illnesses. E.coli O157:H7 originating in the intestines of animals can transfer onto leafy greens via fecal matter. Leafy greens are often eaten fresh without thermal treatments such as cooking which may kill pathogenic bacteria. Therefore, there is a need to identify fecal contamination in the produce field to allow the producer to take steps to prevent contaminated produce reaching the consumer. In this study, a multispectral imaging device, utilizing a two waveband algorithm, was successfully used to detect fecal contamination on soil. The technique presented in this study will be beneficial to produce growers and processing industries.

Technical Abstract: Fecal contamination in fresh produce fields caused by animals or livestock entering the fields can lead to outbreaks of foodbourne illnesses. E.coli O157:H7 originating in the intestines of animals can transfer onto leafy greens via fecal matter. Leafy greens are often eaten fresh without thermal treatments such as cooking which may kill pathogenic bacteria. Therefore, there is a need to identify fecal contamination in the produce field to allow the producer to take steps to prevent contaminated produce reaching the consumer. In this study, spectral features of fecal matter, spinach leaves, and soil were recorded from 368-1048 nm. A multispectral imaging device, utilizing a two waveband algorithm was successfully used to detect fecal contamination on Holtville soil.