Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: September 23, 2010
Publication Date: September 23, 2010
Citation: Sheen,S. 2010. Predictive microbiology for food packaging applications [abstract]. Lecture,Graduate School,Dept. of food Science,Rutgers University. New Brunswick, NJ. p.1. Technical Abstract: Mathematical modeling has been applied to describe the microbial growth and inactivation in foods for decades and is also known as ‘Predictive microbiology’. When models are developed and validated, their applications may save cost and time. The Pathogen Modeling Program (PMP), a collection of models, is currently expanding to cover actual food products and complicated conditions. However, reliable model development for food packaging applications needs further advancement. The PMP was developed at the Eastern Regional Research Center (ERRC) of USDA-Agriculture Research Service, in collaboration with the USDA-Food Safety and Inspection Service (FSIS) and other non-USDA partners in industry and academia. The continuously updated Predictive Microbiology Information Portal (PMIP) (http://portal.arserrc.gov/) is a comprehensive web portal which re-launched in early 2008. The PMIP is particularly valuable to small and very small processing companies for the use and interpretation of models that predict the growth and inactivation of pathogens in foods, and in the development of regulations and other information of relevance to food safety, quality, and wholesomeness. These models allow users to include formulation, as well as processing and handling conditions, to predict and/or to monitor the growth, survival, and death of various food-borne pathogens. Some surface transfer models (microbial cross-contamination) for RTE meats during slicing were added in the most current version. The PMP has become one of the more 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. 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 useful published pathogen growth and inactivation food safety concerns. This presentation will address the key features and usefulness of the PMIP/PMP/ComBase in addition to the microbial predictive models. Special discussion will focus on the application potential and needs/gap of the predictive microbiology to food packaging and safety.