Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: October 2, 2008
Publication Date: October 2, 2008
Citation: Sheen,S. 2008.Predictive Microbiology and Food Safety Applications [abstract].Lecture-Graduate School.Rutgers University,New Brunswick,NJ.p.1.
Mathematical modeling is the science of systematic study of recurrent events or phenomena. When models are properly developed, their applications may save costs and time. For microbial food safety research and applications, predictive microbiology models may be developed based on the fact that most bacterial behaviors are reproducible, and can be quantified by characterizing the environmental factors that affect growth, survival, and inactivation. The Pathogen Modeling Program (PMP), a collection of predictive microbiology models, is currently expanding when new models become available. The PMP can be accessed through the Predictive Microbiology Information Portal (PMIP) or used as stand-alone software. Recently, a set of surface transfer models has been included for Listeria monocytogenes cross-contamination on smoked salmon during the mechanical slicing.
The PMIP development was coordinated by the Microbial Food Safety Research Unit (MFSRU) at the Eastern Regional Research Center (ERRC) of USDA-Agriculture Research Service, in collaboration with USDA-Food Safety and Inspection Service (FSIS) and other non-USDA partners in industry and academia. The PMIP (http://www.ars.usda.gov/naa/errc/mfsru/portal) is a comprehensive web portal which re-launched in early 2008, by MFSRU. The current version of PMIP is particularly useful to small and very small processing companies in the use and interpretation of models that predict the growth and inactivation of pathogens in foods and in the acquisition of regulations and other information of relevance to the safety, quality, and wholesomeness of foods, particularly ready-to-eat (RTE) meat and poultry products. The key feature is the online access to the PMP (http://www.ars.usda.gov/naa/errc/mfsru/pmp), which currently contains 40+ models (65% foods and 35% broth models) and includes both static and dynamic temperature models. These models allow users to include food formulation, as well as processing and handling conditions, to predict and/or to control the growth, survival, and death of various bacterial food-borne pathogens. The PMP has become one of the popular modeling tools that is also used by government agencies and food processing companies in the food safety applications and is downloaded more than 8,000 times each year in over 35 countries. Some user-friendly features allow the client to easily input food-relevant criteria and then to predict how pathogenic bacteria may react to specific food environments. The PMIP also can access the ComBase data base, which provides the useful published pathogen data for food safety concerns. This presentation will address the key features and usefulness of the PMIP/PMP in addition to the microbial predictive models.