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Food Microbiol. 2010 Feb;27(1):37-43. doi: 10.1016/ Epub 2009 Jul 24.

Mathematical modeling the cross-contamination of Escherichia coli O157:H7 on the surface of ready-to-eat meat product while slicing.

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  • 1Microbial Food Safety Research Unit, US Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, Wyndmoor, PA 19038, USA.


Microbial cross-contamination either at home or production site is one of the major factors of causing contamination of foods and leading to the foodborne illness. The knowledge regarding Escherichia coli O157:H7 surface transfer on ready-to-eat (RTE) deli meat and the slicer used for slicing different RTE products are needed to ensure RTE food safety. The objectives of this study were to investigate and to model the surface cross-contamination of E. coli O157:H7 during slicing operation. A five-strain cocktail of E. coli O157:H7 was inoculated directly onto a slicer's round blade rim area at an initial level of ca. 4, 5, 6, 7 or 8 log CFU/blade (ca. 3, 4, 5, 6 or 7 log CFU/cm(2) of the blade edge area), and then the RTE deli meat (ham) was sliced to a thickness of 1-2 mm. For another cross-contamination scenario, a clean blade was initially used to slice ham which was pre-surface-inoculated with E. coli O157:H7 (ca. 4, 5, 6, 7 or 8 log CFU/100 cm(2) area), then, followed by slicing un-inoculated ham. Results showed that the developed empirical models were reasonably accurate in describing the transfer trend/pattern of E. coli O157:H7 between the blade and ham slices when the total inoculum level was >or=5 log CFU on the ham or blade. With an initial inoculum level at <or=4 log CFU, the experimental data showed a rather random microbial surface transfer pattern. The models, i.e., a power equation for direct-blade-surface-inoculation, and an exponential equation for ham-surface-inoculation are microbial load and sequential slice index dependent. The surface cross-contamination prediction of E. coli O157:H7 for sliced deli meat (ham) using the developed models were demonstrated. The empirical models may provide a useful tool in developing the RTE meat risk assessment.

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