Assessing the Performance of Cooling Models for Cooked, Uncured Meat and Poultry Products

Abstract

Heat-resistant spores of Clostridium perfringens may germinate and multiply in cooked meat and poultry products when the rate and extent of cooling does not occur in a timely manner. Therefore, six cooling models (PMP 7.0 broth model; PMIP uncured beef, chicken, and pork models; Smith-Schaffner version 3; and UK IFR ComBase Perfringens Predictor) were evaluated for relative performance in predicting growth of C. perfringens under dynamic temperature conditions encountered during cooling of cooked, uncured meat and poultry products. The predicted growth responses from the models were extensively compared with those observed in food. Data from 188 time-temperature cooling profiles (176 for single-rate exponential cooling and 12 for dual-rate exponential cooling) were collected from 17 independent sources (16 peer-reviewed publications and one report) for model evaluation. Data were obtained for a variety of cooked products, including meat and poultry slurries, ground meat and poultry products with and without added ingredients (e.g., potato starch, sodium triphosphate, and potassium tetrapyrophosphate), and processed products such as ham and roast beef. Performance of the models was evaluated using three sets of criteria, and accuracy was defined within a 1- to 2-log range. The percentages of accurate, fail-safe, or fail-dangerous predictions for each cooling model differed depending on which criterion was used to evaluate the data set. Nevertheless, the combined percentages of accurate and fail-safe predictions based on the three performance criteria were 34.66 to 42.61% for the PMP 7.0 beef broth model, 100% for the PMIP cooling models for uncured beef, uncured pork and uncured chicken, 80.11 to 93.18% for the Smith-Schaffner cooling model, and 74.43 to 85.23% for the UK IFR ComBase Perfringens Predictor model during single-rate exponential chilling. Except for the PMP 7.0 broth model, the other five cooling models (PMIP, Smith-Schaffner, and UK IFR ComBase) are useful and reliable tools that food processors and regulatory agencies can use to evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules.

Modeling and Statistical Issues Related to Salmonella in Low Water Activity Foods

“…Mohr et al (2015) explain that Criterion 1 has a fail-safe boundary set at twice the level of the faildangerous boundary because greater error can be tolerated in the fail-safe direc tion, as originally noted by Oscar (2005bOscar ( , 2007. The boundaries for Criterion 2 are based on the levels of microbial growth that an expert food microbiologist would consider significant.…”

“…Finally the authors reiterate that it is still important to visually examine a plot of predicted versus observed values to guard against any systematic devia tions that might not be revealed by the bias and accuracy factors. Mohr et al (2015) published an extensive validation and assessment of six Clostridium perfringens cooling models, with some relevant insights on model validation in general. These authors define a model as "validated" when its predictions have been "extensively compared to laboratory data, provided the model's performance is acceptable. "…”

“…These authors define a model as "validated" when its predictions have been "extensively compared to laboratory data, provided the model's performance is acceptable. " Mohr et al (2015) used three sets of criteria, each based on different definitions for "accurate, " "fail-safe, " and "fail-dangerous" to evaluate model performance. These criteria are summarized in Table 10.3 and are all modifications of the acceptable prediction zone (APZ) method (Oscar, 2005a), although Mohr et al (2015) redefine "A" in "APZ" to be "accurate" and not "acceptable" as in the original definition by Oscar (2005a).…”

“…Any decisions should also take into consideration any lot-to-lot variation in the formulation and composition of the food (NACMCF, 2010). While a detailed discussion of the proper design of micro biological experiments, including sampling intervals, inoculation methods, and Mohr et al (2015) based on the values of the residual (observed minus predicted value).…”

Current Challenges in Enhancing the Microbiological Safety of Raw Meat

“…In terms of food safety, type A is commonly associated with foodborne illness outbreaks and is in the most part limited to perfuse diarrhea lasting 24-48 h (Mohr et al, 2015;Silveira Silva and Faria Lobato, 2015). perfringens represents the most commonly encountered clostridia associated with meats.…”