Skip to main content
ARS Home » Research » Publications at this Location » Publication #170782
Title: QUANTIFYING THE ROBUSTNESS OF A BROTH-BASED MODEL FOR PREDICTING LISTERIA MONOCYTOGENES GROWTH IN MEAT AND POULTRY PRODUCTS

Author
item MARTINO, KARINA - MICH. STATE UNIV.
item BRADLEY, MARKS - MICH. STATE UNIV.
item CAMPOS, DANIEL - MICH. STATE UNIV.
item Tamplin, Mark

Submitted to: Journal of Food Protection
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/11/2005
Publication Date: 7/1/2006
Citation: Martino, K., Bradley, M., Campos, D., Tamplin, M.L. 2006. Quantifying the robustness of a broth-based model for predicting listeria monocytogenes growth in meat and poultry products. Journal of Food Protection. 68:2310-2316.

Interpretive Summary: The U.S. Department of Agriculture ' Agricultural Research Service Pathogen Modeling Program (PMP) is a tool widely used by the food industry to estimate pathogen growth, survival, and inactivation in food, and for designing Hazard Analysis and Critical Control Points (HACCP) food safety systems. Furthermore, predictive models are useful in microbial risk assessments for estimating levels of human exposure to pathogens. However, inadequate attention has been directed at measuring the accuracy of model predictions for specific types of food. In response to this need, a model robustness index (RI), was developed to compare the error of model prediction in a new food, to the error of the prediction in the original food; a very robust model would have a RI value close to 1. Given the importance of Listeria monocytogenes as a risk factor in meat and poultry products, we evaluated a PMP broth-based L. monocytogenes growth model against 65 sets (time versus microbial level curves) of independent data covering a range of food conditions inside and outside the original model domain. Inside the original model domain, the best RI for application to meat products was 0.37; the worst was 3.96. Outside the model domain, the best RI was 0.40, and the worst was 1.22. In general, the results indicated that the RI value is a useful tool to determine the robustness of a model for different food applications.

Technical Abstract: Given the importance of Listeria monocytogenes as a risk factor in meat and poultry products, there is a need to evaluate the relative robustness of predictive growth models applied to meat products. The U.S. Department of Agriculture ' Agricultural Research Service Pathogen Modeling Program (PMP) is a tool widely used by the food industry to estimate pathogen growth/survival/inactivation in food. However, the robustness of the PMP broth-based L. monocytogenes growth model in meat and poultry applications has not been specifically evaluated. In the present study, this model was evaluated against independent data in terms of predicted microbial counts covering a range of conditions inside and outside the original model domain. The Robustness Index (RI) was calculated as the ratio of the standard error of prediction (root mean square error [RMSE] of the model against an independent data set not used to create the model), to the standard error of calibration (RMSE of the model against the data set used to create the model). Inside the calibration domain of the PMP, the best RI for application to meat products was 0.37 and the worst was 3.96. Outside the domain, the best RI was 0.40, and the worst was 1.22. Product type influenced the RI values (p<0.01). In general, the results indicated that broth-based predictive models should be validated against independent data in the domain of interest; otherwise, significant predictive errors can occur.