Quantifying the Robustness of a Broth-Based Escherichia coli O157:H7 Growth Model in Ground Beef†

Author:

CAMPOS DANILO T.1,MARKS BRADLEY P.1,POWELL MARK R.2,TAMPLIN MARK L.3

Affiliation:

1. 1Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, Michigan 48824

2. 2U.S. Department of Agriculture, Office of Risk Assessment and Cost-Benefit Analysis, Washington, D.C. 20250

3. 3Microbial Food Safety Research Unit, Eastern Regional Research Center, Agricultural Research Service, U.S Department of Agriculture, Wyndmoor, Pennsylvania 19023, USA

Abstract

The robustness of a microbial growth model must be assessed before the model can be applied to new food matrices; therefore, a methodology for quantifying robustness was developed. A robustness index (RI) was computed as the ratio of the standard error of prediction to the standard error of calibration for a given model, where the standard error of calibration was defined as the root mean square error of the growth model against the data (log CFU per gram versus time) used to parameterize the model and the standard error of prediction was defined as the root mean square error of the model against an independent data set. This technique was used to evaluate the robustness of a broth-based model for aerobic growth of Escherichia coli O157:H7 (in the U.S Department of Agriculture Agricultural Research Service Pathogen Modeling Program) in predicting growth in ground beef under different conditions. Comparison against previously published data (132 data sets with 1,178 total data points) from experiments in ground beef at various experimental conditions (4.8 to 45°C and pH 5.5 to 5.9) yielded RI values ranging from 0.11 to 2.99. The estimated overall RI was 1.13. At temperatures between 15 and 40°C, the RI was close to and smaller than 1, indicating that the growth model is relatively robust in that temperature range. However, the RI also was related (P < 0.05) to temperature. By quantifying the predictive accuracy relative to the expected accuracy, the RI could be a useful tool for comparing various models under different conditions.

Publisher

International Association for Food Protection

Subject

Microbiology,Food Science

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