Using E. coli populations to predict foodborne pathogens in pastured poultry farms.

Authors: XU, XINRAN - University Of Georgia; Rothrock, Michael; REEVES, JAXK - University Of Georgia; MISHRA, ABHINAV - University Of Georgia

Submitted to: Food Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/12/2022
Publication Date: 7/14/2022
Citation: Xu, X., Rothrock Jr, M.J., Reeves, J., Mishra, A. 2022. Using E. coli populations to predict foodborne pathogens in pastured poultry farms. Food Microbiology. https://doi.org/10.1016/j.fm.2022.104092.
DOI: https://doi.org/10.1016/j.fm.2022.104092

Interpretive Summary: Escherichia coli is the most widely used indicator of fecal contamination in food. The purpose of this study is to investigate the association between E. coli and foodborne pathogens such as Campylobacter, Salmonella, and Listeria in pastured poultry farms, as well as in related processing facilities. Five different sample types: (i) feces, (ii) soil, (iii) whole carcass rinse during processing (WCR-P), (iv) whole carcass rinse of final product after chilling and storage (WCR-F), and (v) ceca were measured for E. coli populations. A logistic regression model for pathogen presence was developed for each sample type. The increase of E. coli population significantly increased the predicted probability of Salmonella presence for soil and WCR-P samples (p = 0.0011 and p = 0.0157 respectively). For Campylobacter, the initial prevalence in feces and ceca were high and a decreasing trend of detecting Campylobacter was observed as E. coli concentration increased. In soil and WCR-P models, the probability of Campylobacter presence significantly increased as E. coli population increased. These models provide a practical and effective way of evaluating the relationship between E. coli and foodborne pathogens and enable prediction of foodborne pathogen presence based on E. coli prevalence within the pastured poultry farm-to-fork continuum.

Technical Abstract: Escherichia coli is the most widely used indicator of fecal contamination in food. The purpose of this study is to investigate the association between E. coli and foodborne pathogens such as Campylobacter, Salmonella, and Listeria in pastured poultry farms, as well as in related processing facilities. Five different sample types: (i) feces, (ii) soil, (iii) whole carcass rinse during processing (WCR-P), (iv) whole carcass rinse of final product after chilling and storage (WCR-F), and (v) ceca were measured for E. coli populations. A logistic regression model for pathogen presence was developed for each sample type. The increase of E. coli population significantly increased the predicted probability of Salmonella presence for soil and WCR-P samples (p = 0.0011 and p = 0.0157 respectively). For Campylobacter, the initial prevalence in feces and ceca were high and a decreasing trend of detecting Campylobacter was observed as E. coli concentration increased. In soil and WCR-P models, the probability of Campylobacter presence significantly increased as E. coli population increased. These models provide a practical and effective way of evaluating the relationship between E. coli and foodborne pathogens and enable prediction of foodborne pathogen presence based on E. coli prevalence within the pastured poultry farm-to-fork continuum.