Potential Application of Fluorescence Imaging for Assessing Fecal Contamination of Soil and Compost Maturity

Abstract

Pathogenic microorganisms can lead to serious outbreaks of foodborne illnesses, particularly if fresh produce becomes contaminated and then happens to be inappropriately handled in a manner that can incubate pathogens. Pathogenic microbial contamination of produce can occur through a variety of pathways, such as from the excrement of domesticated and wild animals, biological soil amendment, agricultural water, worker health and hygiene, and field tools used during growth and harvest. The use of mature manure compost and preventative control of fecal contamination from wildlife and livestock are subject to safety standards to minimize the risk of foodborne illness associated with produce. However, in a field production environment, neither traces of animal feces nor the degree of maturity of manure compost can be identified by the naked eye. In this study, we investigated hyperspectral fluorescence imaging techniques to characterize fecal samples from bovine, swine, poultry, and sheep species, and to determine feasibilities for both detecting the presence of animal feces as well as identifying the species origin of the feces in mixtures of soil and feces. In addition, the imaging techniques were evaluated for assessing the maturity of manure compost. The animal feces exhibited dynamic and unique fluorescence emission features that allowed for the detection of the presence of feces and showed that identification of the species origin of fecal matter present in soil-feces mixtures is feasible. Furthermore, the results indicate that using simple single-band fluorescence imaging at the fluorescence emission maximum for animal feces, simpler than full-spectrum hyperspectral fluorescence imaging, can be used to assess the maturity of manure compost.

Predicting Key Agronomic Soil Properties with UV-Vis Fluorescence Measurements Combined with Vis-NIR-SWIR Reflectance Spectroscopy: A Farm-Scale Study in a Mediterranean Viticultural Agroecosystem

“…In particular, emission spectra shift towards longer wavelengths with increasing humification [ 11 , 12 , 13 ]. Most studies involving fluorescence spectroscopy of soils have been carried out on liquid extracts of soil samples and were devoted to soil organic compounds [ 11 , 14 , 15 , 16 ]. Few studies relied on fluorescence measurements performed on solid soil samples or “whole soil samples,” with the exception of Van Vliet-Lanöe [ 17 ], for the purpose of applying fluorescence observations to soil micromorphology, or McMurtrey et al [ 18 ] and Daughtry et al [ 19 ], for the purpose of discriminating crop residues from soils.…”

Development of Fluorescence Imaging Technique to Detect Fresh-Cut Food Organic Residue on Processing Equipment Surface

“…The transfer table includes a step motor (Velmex, Bloomfield, NY, USA) and linear motion guide. The UV-A light source is composed of two pairs of four 10-W light-emitting diodes (LEDs; LedEngin, San Jose, CA, USA) that emit excitation light at 365-nm [26].…”

“…8, Kodak, Rochester, NY, USA). Through this acquisition process, hyperspectral image cubes composed of 502 × 501 × 70 (spatial × spatial × spectral) were collected using the in-house developed software [10,26].…”

“…Hyperspectral fluorescence imaging is a sensitive optical technique that uses selected light excitation of a sample to induce light emissions from the sample at wavelengths different from the excitation light of 365 nm [6,22,26]. In studies targeting detection of bacterial biofilm, feces, organic residues, and insects in agricultural produce for food safety, non-destructive and non-contact fluorescence imaging using fluorescence regions from 480 to 560 nm and from 670 to 690 nm has been demonstrated to be an effective technique for rapid detection of contaminants [6,16,[26][27][28][29][30][31].…”

A Neural Network for Hyperspectral Image Denoising by Combining Spatial–Spectral Information

“…Hyperspectral cameras have become increasingly popular in environmental monitoring due to their ability to capture continuous spectral bands and high spectral resolution. These cameras provide both spatial and spectral information of objects on the ground [1], making them valuable for applications, such as mineral exploration [2,3], food hygiene [4][5][6], and feature classification [7]. However, hyperspectral images are prone to noise interference caused by factors, such as sensor non-uniformity, atmospheric disturbances, and variations in lighting conditions [8,9].…”