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Detection of produce residues on processing equipment surfaces using fluorescence imaging
Author(s): Chansong Hwang; Changyeun Mo; Giyoung Kim; Moon Kim
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Paper Abstract

A rapid and reliable inspection technique for determining sanitation status of produce processing equipment surfaces in processing facilities is needed to help reduce potential food safety risks. In this study, fluorescence imaging methods were evaluated to detect produce residues on the surfaces of food processing equipment such as stainless steel (STS). Contamination spots on the STS were created using droplets of a range of dilutions of carrot juice. Hyperspectral fluorescence images of the sample surfaces were obtained using excitation light sources based on ultraviolet LEDs (365 nm) and on violet LEDs (405 nm) for comparison. Image and spectral data were analyzed to determine optimal single bands and two-band ratios to detect the juice residue spots of the STS, and a support vector machine (SVM) algorithm was applied to the ratio images to determine classification accuracies. These results suggest that the simple multispectral fluorescence imaging methods can potentially be incorporated into portable imaging devices for spot-checking food contact surfaces for contaminants in processing facilities.

Paper Details

Date Published: 30 April 2019
PDF: 6 pages
Proc. SPIE 11016, Sensing for Agriculture and Food Quality and Safety XI, 110160O (30 April 2019); doi: 10.1117/12.2520764
Show Author Affiliations
Chansong Hwang, U.S. Dept. of Agriculture, Agricultural Research Service (United States)
Changyeun Mo, Rural Development Administration (Korea, Republic of)
Giyoung Kim, Rural Development Administration (Korea, Republic of)
Moon Kim, U.S. Dept. of Agriculture, Agricultural Research Service (United States)


Published in SPIE Proceedings Vol. 11016:
Sensing for Agriculture and Food Quality and Safety XI
Moon S. Kim; Bryan A. Chin; Byoung-Kwan Cho, Editor(s)

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