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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 #324763
Title: Distinguishing bovine fecal matter on spinach leaves using field spectroscopy

Author
item EVERARD, COLM - University College Dublin
item Kim, Moon
item O'DONNELL, COLM - University College Dublin

Submitted to: Applied Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/24/2016
Publication Date: 8/27/2016
Citation: Everard, C., Kim, M.S., O'Donnell, C. 2016. Distinguishing bovine fecal matter on spinach leaves using field spectroscopy. Applied Sciences. 6:246-254.

Interpretive Summary: Fecal contamination of leafy greens has been associated with pathogenic foodbourne illnesses. In this study a passive field spectroscopy technique, measuring reflectance and fluorescence created by the sun’s light, was used to distinguish fecal contaminant on spinach leaves from soil on spinach leaves and uncontaminated spinach leaf samples. Numerical models developed using a training set of 216 sample spectra successfully predicted all test set sample types. Application of these techniques in-field to avoid harvesting of fecal contaminated leafy greens may lead to a reduction in produce waste by reducing opportunities for cross-contamination, as well as reducing the risks of foodbourne illnesses. The spectral techniques and research results are beneficial to produce growers and producers.

Technical Abstract: Detection of fecal contaminants on leafy greens in the field will allow for decreasing cross-contamination of produce during and post-harvest. Fecal contamination of leafy greens has been associated with E.coli O157:H7 outbreaks and foodbourne illnesses. In this study passive field spectroscopy, measuring reflectance and fluorescence created by the sun’s light, coupled with numerical normalization techniques are used to distinguish fecal contaminant on spinach leaves from soil on spinach leaves and uncontaminated spinach leaf samples. A Savitzky-Golay first derivative transformation and a waveband ratio of 710:688 nm as normalising techniques were assessed. A SIMCA (soft independent modeling of class analogies) procedure using a training set of 216 samples successfully predicted all 54 test set sample types, using a spectral waveband of 600-800 nm. The ratio of 710:688 nm along with set thresholds separated all 270 samples by type. Application of these techniques in-field to avoid harvesting of fecal contaminated leafy greens may lead to a reduction in produce waste by reducing opportunities for cross-contamination, as well as reducing the risks of foodbourne illnesses.