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United States Department of Agriculture

Agricultural Research Service

Research Project: DEVELOPMENT OF SENSING AND INSTRUMENTATION TECHNOLOGIES FOR FOOD SAFETY AND SANITATION INSPECTION IN FRESH FRUIT AND VEGETABLE PROCESSING

Location: Environmental Microbial and Food Safety Laboratory

Title: Detection of fresh-cut produce processing residues on food contact surface materials using hyperspectral imaging

Authors
item Wiederoder, Michael
item Lefcourt, Alan
item Kim, Moon
item Lo, Y.

Submitted to: Sensing and Instrumentation for Food Quality and Safety
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 11, 2012
Publication Date: November 2, 2012
Citation: Wiederoder, M., Lefcourt, A.M., Kim, M.S., Lo, Y. 2012. Detection of fresh-cut produce processing residues on food contact surface materials using hyperspectral imaging. Sensing and Instrumentation for Food Quality and Safety. DOI: 10.1007/s11694-012-9132-1.

Interpretive Summary: Cleaning and sanitation is an important mechanism for reducing the incidence of foodborne illness. In produce processing plants, all food contact surfaces are thoroughly cleaned and sanitized at least once a day. By far the most common method of evaluating the effectiveness of these cleaning procedures is visual observation using the naked eye. The question addressed in this study was whether it might be possible to improve upon this visual inspection using a camera-based imaging system. By imaging produce residues collected from a processing plant, and also created in the laboratory using produce purchased in local markets, it was found that very small quantities of test materials could be detected by looking at the fluorescence response when an ultraviolet light was shined on the materials. A similar test of cleaning and sanitizing agents showed that these agents did not fluoresce, which means that these agents should not interfere with the ability to detect produce residues. The results of this study support the idea of developing a small, hand-held, imaging device that could be used by cleaning crews in produce plants to monitor the effectiveness of cleaning procedures. This device would allow workers to locate areas that still harbored produce residues after cleaning. This work will be of interest to scientists and regulators interested in food safety, as well as industry personnel that work with produce.

Technical Abstract: To reduce the risk of foodborne-illness, produce processors currently clean and sanitize food contact surfaces daily before production starts. Current methods to verify the efficacy of cleaning procedures include visual inspection and direct surface sampling using ATP bioluminescence assays and culturing methods. To assess the possibility of augmenting these existing verification methods, this study investigated the potential to use imaging techniques to detect fresh-cut produce residues. A laboratory hyperspectral system was used to image produce residues obtained from a commercial processing plant, cantaloupe and honeydew residues generated in-house, and selected cleaning and sanitizing agents. Test materials were dispensed onto stainless steel and high density polyethylene coupons. The coupon materials were selected to represent common surfaces used in production facilities. Analysis of VIS/NIR hyperspectral reflectance and fluorescence images showed that the cleaning and sanitizing agents were essentially undetectable; thus, demonstrating that presence of these substances would not result in false-positives. In contrast, produce residues in microgram showed fluorescence peaks encompassing the regions from 480 to 560 nm and from 670 to 690 nm. However, auto-fluorescence responses of high density polyethylene at shorter wavelengths were found to obscure the 480 to 560 nm peaks for some residues. These results suggest that fluorescence imaging techniques can be used to enhance surface hygiene inspection in produce processing plants and, given the immediate availability of imaging results, to help optimize routine cleaning procedures.

Last Modified: 10/24/2014
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