A multispectral imaging system using solar illumination to distinguish fecal matter on leafy greens and soils

Authors: EVERARD, COLM - Forest Service (FS); Kim, Moon; SIEMENS, MARK - Arizona State University; CHO, HYUNJEONG - Forest Service (FS); Lefcourt, Alan; ODONNEL, COLM - University College Dublin

Submitted to: Biosystems Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/2/2018
Publication Date: 7/1/2018
Citation: Everard, C.D., Kim, M.S., Siemens, M., Cho, H., Lefcourt, A.M., Odonnel, C. 2018. A multispectral imaging system using solar illumination to distinguish fecal matter on leafy greens and soils. Biosystems Engineering. 171:258-264. https://doi.org/10.1016/j.biosystemseng.2018.05.001.
DOI: https://doi.org/10.1016/j.biosystemseng.2018.05.001

Interpretive Summary: Fresh produce contaminated with animal fecal matter has been linked to several outbreaks of foodborne diseases. In-field detection of fecal matter would allow the producer to take action to reduce fecal contaminated produce entering the post-harvest processing line and the human food supply. In recent years, ARS researchers have developed a prototype imaging system to detect fecal matter on leafy greens. The system was tested on spinach leaves and three types of soils in an outdoor environment. On all samples evaluated, the imaging system successfully distinguished fecal matter from spinach leaves and soil under varying outdoor illumination conditions. The technique and results demonstrated in this investigation provide a means to detect fecal contaminated produce and will benefit produce growers and processing industries.

Technical Abstract: Fecal contaminated fruits and vegetables have been linked to several outbreaks of foodbourne diseases. In-field detection of fecal matter would allow the producer to take action to reduce fecal contaminated produce entering the post-harvest processing line and the human food supply. No viable systems to accomplish this task have been developed to date. To address this, a prototype imaging system was developed to detect fecal matter on leafy greens. The system principally comprised of two monochrome cameras that were used to simultaneously capture images of the same target at two separate wavelengths, 690 and 710 nm, by utilizing a beam-splitter and bandpass filters. An image algorithm was developed to create a single image from the ratio of the 710 nm image to the 690 nm image on a pixel by pixel basis. A thresholding technique was used on the resulting image to classify pixels as fecal matter or non-fecal matter. The system was tested on spinach leaves (Spinacia olerace) and three types of soils in an outdoor environment. On all samples evaluated, the imaging system, coupled with this waveband ratio normalization method, successfully distinguished fecal matter from spinach leaves and soil under varying atmospheric conditions. These findings are very encouraging and further study is needed to determine if such a technique would reliably detect fecal material in an agricultural field environment where leaf orientation and contamination concentration levels are highly variable.