Use of Modeling to Enhance the Microbiological Safety of the Food System

Abstract

This article is part of a collection entitled "Models for Safety, Quality, and Competitiveness of the Food Processing Sector," published in Comprehensive Reviews in Food Science and Food Safety. It has been peer-reviewed and was written as a follow-up of a pre-IFT workshop, partially funded by the USDA NRI grant 2005-35503-16208.ABSTRACT: The use of modeling techniques for safety and risk prediction in the food supply is strongly supported by the incidence of foodborne outbreaks worldwide. In microbiological food safety, important parameters include incidence, microbial growth, microbial inactivation or survival, and dose response of the host. The goals of the modeler should include (1) identifying possible inputs and outputs for a particular concern and (2) choosing factors for integration into a larger, overall model. A case study of ground beef from the farm to the consumer reviews multiple points of concern where relevant parameters for Escherichia coli O157:H7 can be modeled. The prevalence and concentration of E. coli O157:H7 in cattle have been confirmed and studies have explored various feeding regimens and hide-cleaning methods for controlling the pathogen prior to slaughter. There is significant impact of incidence and cross-contamination during slaughter operations. Intervention methods such as washing and heat treatments and proper carcass handling may reduce the contamination level. Microbial growth in meat products can be extensive, given the possibility of temperature abuse during transportation and storage. Dose-response models for susceptible consumers provide a safety perspective for quantitative microbial models. Growth prediction and lethality models, available online, are valuable tools for both researchers and processors. The goal of the processor should be the "highest reduction possible" (to meet adequate safety requirements) prior to the preparation of raw product. The researcher must continually question the use of a model and the availability of data to validate any conclusions.

Thermal Tolerance Characteristics of Non-O157 Shiga Toxigenic Strains of Escherichia coli (STEC) in a Beef Broth Model System Are Similar to Those of O157:H7 STEC

“…Tailing has been attributed to the presence of a few large clumps of cells or a more heattolerant subspecies of cells (19,25,35). To account for deviations from first order kinetics, researchers have obtained D-values from the linear portion of the curve (2,21,52) or have used mathematical models to address nonlinearity (5,12,22,23). Although mathematical models are helpful for predicting the death rate of microbial populations, they have limitations when determining thermal death parameters (26).…”

High-Pressure Processing Technologies for the Pasteurization and Sterilization of Foods

“…Since pressure-treated foods first appeared on the market, significant advances in the modeling of microbial inactivation have been accomplished (e.g., McMeekin et al 1993;Baranyi and Roberts 1995;Peleg and Cole 1998;Xiong et al 1999a;Ahn et al 2007b;Corradini and Peleg 2007;Klotz et al 2007;Koseki and Yamamoto 2007b;Black and Davidson 2008;Pérez Lamela and Torres 2008b). Many authors have reported that in thermal processes, the survival curves for microorganisms deviate from the expected linear behavior (Kamau et al 1990;Bhaduri et al 1991;Linton et al 1995Linton et al , 1996Anderson et al 1996;Buzrul 2007).…”

A user-friendly general-purpose predictive software package for food safety

“…The effects of such variability can be included using the COMSOL Multiphysics interface directly, as already mentioned under property estimation. Finally, there are a number of risk factors associated with microbiological food safety which have not been modeled to date and that could contribute to the overall safety of a food product (Black and Davidson, 2008).…”