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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Food Safety and Intervention Technologies Research » Research » Publications at this Location » Publication #290798
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 - Kansas State University
item THIPPAREDDI, HARSYHAVARDHAN - University Of Nebraska
item CEPEDA, JIHAN - University Of Nebraska
item HARPER, NIGEL - Kansas State University
item PHEBUS, RANDALL - Kansas State University
item SENECAL, ANDRE - Natick Soldier Center
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.