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Title: FECAL CONTAMINATION, DETECTION, AND CLASSIFICATION ON CANTALOUPES USING HYPERSPECTRAL FLUORESCENCE IMAGERY

Author
item Vargas, Angela
item Kim, Moon
item TAO, YANG - UNIVERSITY OF MARYLAND
item Lefcourt, Alan
item Chen, Yud
item Luo, Yaguang - Sunny
item SONG, YOSOON - FDA

Submitted to: Journal of Food Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/15/2005
Publication Date: 7/1/2005
Citation: Vargas, A.M., Kim, M.S., Tao, Y., Lefcourt, A.M., Chen, Y.R. 2005. Fecal Contamination, detection, and classification on cantaloupes using hyperspectral fluorescence imaging. J. of Food Science. 70(8):E471-E476.

Interpretive Summary: The Food and Drug Administration has determined fecal contamination of produce is a major food safety issue. To determine if detection of fecal contamination on cantaloupes is possible, images of cantaloupes artificially contaminated with dairy cattle feces were acquired in the visible region of the spectrum. Images were analyzed using different mathematical algorithms. Results show that fecal contamination was easily detected in the red region, and that images at 675 nm exhibited the greatest contrast between treated and untreated surface areas. Detection rates were improved using ratios of images; the ratios with the best contrast were 695/595, 675/555 and 555/665 nm. Using automated classification methods, we were able to reduce false positive detection and isolate the feces treated areas. Additionally, the contrast between treated and normal surface areas was enhanced. These results indicate that fluorescence imaging is a potentially viable technology for commercial applications involving detection of fecal contamination on cantaloupes.

Technical Abstract: The Food and Drug Administration has determined fecal contamination of produce is a major food safety issue. To determine if detection of fecal contamination on cantaloupes is possible, cow feces were acquired from 415 to 770 nm in response to UV-A excitation. Samples were treated with 10, 20, 30 and 40 ml of 1:10, 1:50, 1:100, 1:300 and 1:500 feces dilutions. Images were analyzed using band ratios, unsupervised (ISODATA) classification, and principal component analysis. Results showed that fecal contamination was easily detected in the red band, and that images at 675 nm exhibited the greatest contrast between treated and untreated surface areas. Detection rates were improved using ratio images; the best results were provided by 695/595, 675/555 and 555/665 nm. An unsupervised classification method was effective for reducing false positives and isolating the treated areas. The first six principal component (PC) images exhibited useful attributes for fecal contamination detection. In PC-2 and PC-5 the contrast between treated and normal surface areas was enhanced. PC-5 also differentiated responses of feces from those of damaged tissue; thus, reducing false positives. These results indicate that fluorescence imaging is a potentially viable technology for commercial applications for detection of fecal contamination on cantaloupes.