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F Morgan Wallace, Bridget Andaloro, Dawn Fallon, Nisha Corrigan, Stephen Varkey, Daniel DeMarco, Andrew Farnum, Monica Tadler, Steven Hoelzer, Julie Weller, Eugene Davis, Jeffrey Rohrbeck, George Tice, Patrick Bird, Erin Crowley, Jonathan Flannery, Kiel Fisher, Travis Huffman, Megan Boyle, M Joseph Benzinger, Paige Bedinghaus, Katie Goetz, William Judd, Jim Agin, David Goins, Collaborators: , Detection of Salmonella species in a Variety of Foods by the DuPont™ BAX® System Real-Time PCR Assay for Salmonella: First Action 2013.02, Journal of AOAC INTERNATIONAL, Volume 97, Issue 3, 1 May 2014, Pages 868–875, https://doi.org/10.5740/jaoacint.13-407
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Abstract
A multilaboratory study was conducted to evaluate the ability of the DuPont™ BAX® System Real-Time PCR Assay for Salmonella to detect the target species in a variety of foods and environmental surfaces. Internal validation studies were performed by DuPont Nutrition & Health on 24 different sample types to demonstrate the reliability of the test method among a wide variety of sample types. Two of these matrixes—pork and turkey frankfurters and pasteurized, not-from-concentrate orange juice without pulp—were each evaluated in 14 independent laboratories as part of the collaborative study to demonstrate repeatability and reproducibility of the internal laboratory results independent of the end user. Frankfurter samples were evaluated against the U. S. Department of Agriculture, Food Safety and Inspection Service reference method as a paired study, while orange juice samples were evaluated against the U. S. Food and Drug Administration reference method as an unpaired study, using a proprietary media for the test method. Samples tested in this study were artificially inoculated with a Salmonella strain at levels expected to produce low (0.2–2.0 CFU/test portion) or high (5 CFU/test portion) spike levels on the day of analysis. For each matrix, the collaborative study failed to show a statistically significant difference between the candidate method and the reference method using the probability of detection statistical model.