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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Residue Chemistry and Predictive Microbiology Research » Research » Publications at this Location » Publication #351940

Research Project: Development of Predictive Microbial Models for Food Safety using Alternate Approaches

Location: Residue Chemistry and Predictive Microbiology Research

Title: Dynamic analysis of competitive growth of escherichia coli 0157:H7 in raw ground beef

Author
item Hwang, Cheng-an - Andy
item Huang, Lihan

Submitted to: Food Control
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/10/2018
Publication Date: N/A
Citation: N/A

Interpretive Summary: Escherichia coli O157:H7 has been implicated in outbreaks of foodborne illnesses linked to the consumption of ground beef. This study examined and mathematically modeled the interactive growth of E. coli O157:H7 and background flora in ground beef at temperatures that a product may be exposed to before consumption. Predictive dynamic models were successfully developed and validated. The models can be used for predicting the shelf-life of ground beef and conducting risk assessment of pathogenic E. coli.

Technical Abstract: The objective of this study was to investigate the growth of Escherichia coli O157:H7 in raw ground beef under competition from background flora. The growth of E. coli O157:H7 was observed in sterile irradiated and non-irradiated raw ground beef under dynamically changing temperature conditions. A one-step dynamic analysis method was used to directly construct tertiary models for describing bacterial growth with and without competition and to estimate the kinetic parameters from dynamic growth curves to prove the hypothesis that the growth of E. coli O157:H7 was significantly affected by competition from background flora in raw ground beef. The one-step dynamic method successfully modelled the growth of E. coli O157:H7 and background flora in ground beef and the competition between the two. The estimated minimum growth temperature for E. coli O157:H7 was 7.7°C, and the maximum cell concentration was 9.0 log CFU/g. Under competition, the specific growth rate of E. coli O157:H7 was reduced by approximately 18% in raw ground beef. The resulting dynamic models and kinetic parameters were validated with separate dynamic growth data, showing that the Root Mean Square Error (RMSE) was < 0.5 log CFU/g for both background flora and E. coli O157:H7 in sterile and raw ground beef. In addition, the models were validated with the growth data of background flora and non-O157 Shiga toxin-producing E. coli (STEC) in raw ground beef obtained in a previous study, also yielding a RMSE of < 0.5 log CFU/g. This result also suggests that the growth kinetics of E. coli O157:H7 and non-O157 STEC may be similar in ground beef. The results of this study demonstrated that the one-step dynamic analysis was a useful and efficient method for investigating bacterial growth with and without competition under dynamic conditions and for developing growth kinetic models. Since the dynamic models have been validated, they can be used to predict the shelf-life of ground beef (background flora) and conduct risk assessment of E. coli O157:H7 and non-O157 STEC.