Optical Parameters for Using Visible-Wavelength Reflectance or Fluorescence Imaging to Detect Bird Excrements in Produce Fields
Source abstract
Abstract
Consumption of produce contaminated with pathogens of fecal origin is the most common source of food borne illnesses. Current practice is to visually survey fields for evidence of fecal contamination, and to exclude problematic areas from harvest. Bird excrement is known to contain human pathogens, and is often not detectable in produce fields using current survey methods. The goal of this project was to identify parameters for optical detection of bird excrements to support development of instruments to be used to supplement existing visual surveys. Under daylight ambient conditions, results suggested that reflectance imaging at around 500–530 nm or 610–640 nm could be used to detect excrements from the three bird species tested. Images were acquired using ad hoc camera parameters; however, normalizing intensities for individual images at 525 nm and using a fixed detection threshold allowed detection of 100% of bird excrements with no false positives against the background that consisted of local soil and fresh romaine and spinach leaves. Similar results were obtained using fluorescence imaging. Fluorescent imaging was accomplished in a darkened room using 405-nm illumination. The largest consistent differences in intensity responses between excrements and the brightest non-excrement object in the background matrix occurred at around 550 nm. Results suggested that using reflectance or fluorescence imaging for detection of bird excrements could be a valuable tool for reducing risks of consuming contaminated produce. One possibility would be to incorporate appropriate reflectance imaging capabilities in drones under the control of the individuals currently conducting field surveys.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Listeria monocytogenes in Food Safety · Spectroscopy and Chemometric Analyses · Salmonella and Campylobacter epidemiology
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
USDA (United States Department of Agriculture) Agricultural Research Service, Rm 21, Bldg 303, BARC-East, Powder Mill Rd., Beltsville, MD 20705, USA
Department of Agricultural and Biosystems Engineering, University of Arizona, Yuma Agricultural Center, 6425 W. 8th St., Yuma, AZ 85364, USA
Department of Soil, Water, and Environmental Science, University of Arizona Cooperative Extension, Yuma Agricultural Center, 6425 W. 8th St., Yuma, AZ 85364, USA
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