L monocytogenes Predictive Models for Cooked Meats

The USDA-FSIS requires RTE meat and poultry processors to minimize the risk of L. monocytogenes in the RTE processing environment and the RTE meat and poultry products. The USDA-FSIS final rule on ''Listeria monocytogenes Contamination of the Ready-to-Eat Meat and Poultry Products'' has identified three alternatives for RTE meat and poultry processors to address this pathogen in their food safety programs. RTE meat and poultry processors can control L. monocytogenes by (i) using a post-lethality treatment and an antimicrobial agent or process (Alternative 1); (ii) using either a post-lethality treatment or an antimicrobial agent or process (Alternative 2); or (iii) control of L. monocytogenes in the post-lethality processing environment through sanitation procedures only (Alternative 3). For Alternatives 1 and 2, the RTE processors can use antimicrobial agents to minimize the risk of L. monocyto-genes growth in their products, resulting in a lower risk of foodborne illness (USDA-FSIS, 2003).

The antimicrobial agents commonly used in the RTE meat and poultry industry in the USA currently include mixtures of organic acid salts (sodium or potassium salts of lactic acid or citric acid in combination with sodium diacetate). The USDA-FSIS defined antimicrobial agent as a substance in, or added to, a RTE product that has the effect of either reducing or eliminating a microorganism, including a pathogen such as L. monocytogenes, or that can limit or suppress the growth of L. monocytogenes. The antimicrobial should be effective throughout the shelf life of the product (USDA-FSIS, 2000). The antimicrobial can be added to the product during formulation, to the finished product, or to the packaging material to inhibit growth of L. monocytogenes in the post-lethality exposed product during its refrigerated shelf life.

While seafood and dairy products have also been identified as risk factors in foodborne illness due to L. monocytogenes, RTE meat and poultry products have been the focus for development of most predictive models in the USA. The application of predictive models for L. monocytogenes has been to evaluate the potential shelf life (safety based) the RTE meat and poultry processor can declare on the label to meet the regulatory requirements. As such, models that were developed using microbiological media are of limited use in this context. A good example of a model that the industry routinely uses is the Opti.Form model, developed and marketed by Purac America (Lincolnshire, IL). This tertiary model allows the user to define the product specifications such as moisture and salt content and the expected "time to growth'' (time to 1 log increase) or alternatively the shelf life (safety based) is predicted based on the concentrations of lactate and/or diacetate. Most RTE meat processors use this model as supporting documentation for their HACCP plans and as justification for regulatory purposes.

The initial iteration of the model was based on the study by Seman, Borger, Meyer, Hall, and Milkowski (2002); subsequent study (Legan, Seman, Milk-owski, Hirschey, & Vandeven, 2004) incorporated the option to include whether the product contained sodium nitrite (cure) or not. The model was developed using a generalized regression approach, alternatively termed "survival analysis'' or "reliability analysis'' within the biomedical and engineering fields of study. Basically, the model is a "boundary" model that defines the time to reach 1 log growth of L. monocytogenes in a product (based on its composition). The use of least squares regression to develop such models has the disadvantage that the points where no growth was observed cannot be included. The study highlights the significance of product composition (moisture, salt, and sodium nitrite) on L. monocytogenes growth and provides the user to predict the potential L. monocytogenes growth for a specific product, rather than providing a "conservative" estimate of the growth. This ability to tailor the predictions to their specific product is very useful for the processors in designing their product formulations to attain a specific "shelf life'' based on microbiological safety. A similar approach was adopted by Seman, Quickert, Borger, and Meyer (2008) to predict L. monocytogenes growth on RTE meat and poultry products containing sodium benzoate as an antimicrobial agent.

However, a drawback of the model is that the experimental design included only one specific storage temperature (4°C) to predict L. monocytogenes growth, and the model does not allow or predict growth at other refrigeration temperatures. While it is desirous to maintain a specific temperature, in reality, it is impossible to achieve that throughout the cold chain, and especially at the consumer stage. Further, the product temperature fluctuations occur throughout the cold chain and the models that can predict L. monocytogenes growth during those fluctuating or constantly varying temperatures (dynamic) such as those for C. perfringens will be of more utility for the processors as well as regulators in evaluating the realistic growth potential of the organism in the marketplace. The model design adopted by Seman et al. (2002) and Legan et al. (2004) does not render itself useful in such circumstances.

In a recent study, Monsalve (2008) developed a model to predict the growth of L. monocytogenes on RTE roast beef and turkey using the traditional approach of obtaining growth parameters under isothermal conditions and subsequently developed the dynamic model (Baranyi). While the model does not include a range of moisture and salt concentrations in the products, Mon-salve incorporated various temperatures, allowing for prediction of the potential L. monocytogenes growth at a minimal salt concentration (2%) using a traditional product formulation, with different concentrations of the antimicrobial (buffered sodium citrate containing sodium diacetate). This model allows a "conservative'' prediction of potential L. monocytogenes growth in the products at different concentrations of the antimicrobial under dynamic temperature conditions (Fig. 22.5). Such models will be very helpful for

Fig. 22.5 Predicted and observed growth of L. monocytogenes on cured, RTE turkey hams containing buffered sodium citrate (BSC) and sodium diacetate (SD); BSC + SD (0%) and BSC + SD (1%) at constantly varying temperatures (Monsalve, 2008)

processors to evaluate the safety of the product under existing distribution channels or the potential risk of introducing a RTE meat and poultry product into new marketing channel by measuring and incorporating the temperature profiles of the distribution channels (cold chain).

While other models have been developed and published in the literature, they do not serve the needs of the cooked meats (RTE) processors or the risk managers the tool to evaluate the potential risk of L. monocytogenes growth during the shelf life of the product and through to the consumption stage.

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