Identifying fecal matter contamination in produce fields using multispectral reflectance imaging under ambient solar illumination

Colm D. Everard; Moon S. Kim; Hoonsoo Lee; Colm P. O'Donnell

doi:10.1117/12.2229810

17 May 2016 Identifying fecal matter contamination in produce fields using multispectral reflectance imaging under ambient solar illumination

Colm D. Everard, Moon S. Kim, Hoonsoo Lee, Colm P. O'Donnell

Author Affiliations +

Proceedings Volume 9864, Sensing for Agriculture and Food Quality and Safety VIII; 986416 (2016) https://doi.org/10.1117/12.2229810
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

Abstract

An imaging device to detect fecal contamination in fresh produce fields could allow the producer avoid harvesting fecal contaminated produce. E.coli O157:H7 outbreaks have been associated with fecal contaminated leafy greens. In this study, in-field spectral profiles of bovine fecal matter, soil, and spinach leaves are compared. A common aperture imager designed with two identical monochromatic cameras, a beam splitter, and optical filters was used to simultaneously capture two-spectral images of leaves contaminated with both fecal matter and soil. The optical filters where 10 nm full width half maximum bandpass filters, one at 690 nm and the second at 710 nm. These were mounted in front of the object lenses. New images were created using the ratio of these two spectral images on a pixel by pixel basis. Image analysis results showed that the fecal matter contamination could be distinguished from soil and leaf on the ratio images. The use of this technology has potential to allow detection of fecal contamination in produce fields which can be a source of foodbourne illnesses. It has the added benefit of mitigating cross-contamination during harvesting and processing.

Citation Download Citation

Colm D. Everard, Moon S. Kim, Hoonsoo Lee, and Colm P. O'Donnell "Identifying fecal matter contamination in produce fields using multispectral reflectance imaging under ambient solar illumination", Proc. SPIE 9864, Sensing for Agriculture and Food Quality and Safety VIII, 986416 (17 May 2016); https://doi.org/10.1117/12.2229810

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