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United States Department of Agriculture

Agricultural Research Service

Research Project: PATHOGEN PERSISTENCE AND PROCESSING OPTIMIZATION FOR ELIMINATION IN FOODS

Location: Food Safety and Intervention Technologies Research

Title: Development and validation of predictive models for growth of non-0157 shiga-toxigenic Escherichia coli (STEC) and Salmonella spp. in ground beef, lettuce, and non fat dry milk)

Author
item Speight, Brandon
item Thippareddi, Harsyhavardhan
item Cepeda, Jihan
item Harper, Nigel
item Phebus, Randall
item Senecal, Andre
item Luchansky, John
item Porto-fett, Anna

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/28/2013
Publication Date: 7/28/2013
Citation: Speight, B., Thippareddi, H., Cepeda, J., Harper, N., Phebus, R.K., Senecal, A., Luchansky, J.B., Porto Fett, A.C. 2013. Development and validation of predictive models for growth of non-0157 shiga-toxigenic Escherichia coli (STEC) and Salmonella spp. in ground beef, lettuce, and non fat dry milk. Meeting Abstract.IAFP Annual Meeting, Charlotte, NC, July 28-31, 2013., 76:144(P2-55).

Interpretive Summary:

Technical Abstract: Microbial predictive models are food safety tools that can be used to evaluate potential risk of pathogen growth in foods to facilitate effective decision-making. Research is limited regarding growth characteristics of non-O157 Shiga-toxigenic E. coli (STEC) in food and on Salmonella spp. in lettuce and reconstituted non-fat dry milk. Therefore, we developed and validated predictive models for growth of Salmonella spp. and non-O157 STEC in the above mentioned targeted food matrices. Ground beef and shredded iceberg lettuce were inoculated with a six-serotype STEC cocktail (O26, O45, O103, O111, O121 and O145). A five-serovar Salmonella spp. cocktail was used to inoculate reconstituted non-fat dry milk (NDM) and lettuce. Isothermal growth data was collected for each of the pathogen cocktails at various temperatures (5.0-47.5 deg C). A Baranyi model was used to fit the primary model. A modified Ratkowsky model was used to generate the secondary model. Two sinusoidal temperature profiles (5-15 deg C and 10-40 deg C) were used to validate the dynamic models. Mean absolute relative error (MARE) was used to judge the accuracy of the models, with 0% MARE indicating best fit. MARE values for the ground beef model for low and high temperature non-O157 STEC profiles were 8.5 and 1.7%, respectively. MARE values for growth of non-O157 STEC in lettuce were 26.7 and 4.8% for the low and high temperature profiles, respectively. Similarly, the dynamic model predicted the growth of Salmonella spp. on lettuce with MARE values of 5.4 and 6.3%, respectively, for high and low temperatures. MARE values for Salmonella in NDM were 5.8 and 6.6% for high and low temperature, respectively. The dynamic models for both pathogens and the foods they were evaluated in resulted in low MARE% values (1.7-8.5%) at both storage temperature ranges, indicating acceptable model accuracy. MARE values for non-O157 STEC in iceberg lettuce stored at low temperatures (26.7% MARE) indicated a lack of fit of the model and a need for additional research.

Last Modified: 8/24/2016
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