Development and validation of a predictive model for growth of Salmonella Infantis in ground turkey

Authors: Oscar, Thomas

Submitted to: Journal of Food Protection
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/18/2024
Publication Date: 10/23/2024
Citation: Oscar, T.P. 2024. Development and validation of a predictive model for growth of Salmonella Infantis in ground turkey. Journal of Food Protection. 87 Issue 12. https://doi.org/10.1016/j.jfp.2024.100387.
DOI: https://doi.org/10.1016/j.jfp.2024.100387

Interpretive Summary: Most packages of ground turkey purchased at the supermarket contain no or low levels of Salmonella. However, if the ground turkey is left on the kitchen counter for too long, the Salmonella can grow to high levels that can get you sick. So, how long is too long? That depends on the temperature in the kitchen. Therefore, a study was undertaken to determine how long is too long. Data (600 samples) for growth of Salmonella in ground turkey were collected for up to 28 h at 60 to 104F. They were used to develop a computer model for home use. How does the model work? It's simple, just enter the time and temperature, and the model tells you how much growth of Salmonella is expected. For example, what if I left my ground turkey on the kitchen counter for 1 hour at 72F, is it still safe? The computer model predicts that it would take Salmonella about 6 hours to start to grow at 72F in ground turkey, so, yes, the ground turkey is still safe to cook and eat. Thus, the computer model can provide an objective and science based answer to the simple question, how long is too long? Where can I find the model? Once this research is published, the computer model will be incorporated into the USDA, Pathogen Modeling Program, which is free and open access to everyone at: https://portal.errc.ars.usda.gov/.

Technical Abstract: Most retail samples (25 g) of ground turkey contain no or low levels of Salmonella. However, temperature abuse after retail can lead to spread and growth of Salmonella in the package. In addition, it can lead to levels that pose a significant risk of salmonellosis. This is especially true when the serotype is a top human clinical isolate, like Infantis. Therefore, the current study was undertaken to develop and validate a predictive model for growth of Salmonella Infantis in ground turkey subjected to temperature abuse. The purpose was to fill an important data and modeling gap in risk assessments for this pathogen and food combination. Storage trials with a low initial inoculum (0.85 log10) of Salmonella Infantis in commercial ground turkey samples (0.2 g) with native microflora were conducted at 16 to 40C for 0 to 28 h. Salmonella was enumerated in ground turkey samples using an automated, whole sample enrichment, miniature, most probable number (MPN) assay. The MPN data were fitted to a three-phase linear primary model. Then secondary models for primary model parameters were developed and used in the primary model to create a tertiary model. It predicted growth of Salmonella Infantis in ground turkey as a function of time and temperature. Data and tertiary model predictions were evaluated using the test data, model performance, and model validation criteria of the Acceptable Prediction Zones method in the Validation Software Tool. The tertiary model predictions were considered to have acceptable bias and accuracy when the proportion of residuals (observed – predicted) in the partly and fully acceptable prediction zones (pAPZ) was = 0.7. The overall pAPZ of the tertiary model was 0.866 for dependent data (n = 406) and 0.853 for independent data for interpolation (n = 177). However, there were local prediction problems that limited the validated prediction range to a region from 0 to 8 h at 16 to 40C. Nonetheless, this validation range was sufficient to simulate temperature abuse of ground turkey during meal preparation in the consumers’ home. Thus, the model fills an important data and modeling gap in risk assessments for Salmonella and ground turkey. Additional data is needed to repair and fully validate the model.