Lethality Prediction for Escherichia Coli O157:H7 and Uropathogenic E. coli in Ground Chicken Treated with High...

Pathogenic Escherichia coli, intestinal (O157:H7) as well as extraintestinal types (for example, Uropathogenic E. coli [UPEC]) are commonly found in many foods including raw chicken meat. The resistance of E. coli O157:H7 to UPEC in chicken meat under the stresses of high hydrostatic Pressure (HHP, also known as HPP-high pressure processing) and trans-cinnamaldehyde (an essential oil) was investigated and compared. UPEC was found slightly less resistant than O157:H7 in our test parameter ranges. With the addition of trans-cinnamaldehyde as an antimicrobial to meat, HPP lethality enhanced both O157:H7 and UPEC inactivation. To facilitate the predictive model development, a central composite design (CCD) was used to assess the 3-parameter effects, that is, pressure (300 to 400 MPa), trans-cinnamaldehyde dose (0.2 to 0.5%, w/w), and pressure-holding time (15 to 25 min), on the inactivation of E. coli O157:H7 and UPEC in ground chicken. Linear models were developed to estimate the lethality of E. coli O157:H7 (R² = 0.86) and UPEC (R² = 0.85), as well as dimensionless nonlinear models. All models were validated with data obtained from separated CCD combinations. Because linear models of O157:H7 and UPEC had similar R² and the significant lethality difference of CCD points was only 9 in 20; all data were combined to generate models to include both O157:H7 and UPEC. The results provide useful information/tool to predict how pathogenic E. coli may survive HPP in the presence of trans-cinnamaldehyde and to achieve a great than 5 log CFU/g reduction in chicken meat. The models may be used for process optimization, product development and to assist the microbial risk assessment.

The study provided an effective means to reduce the high hydrostatic pressure level with incorporation of antimicrobial compound to achieve a 5-log reduction of pathogenic E. coli without damaging the raw meat quality. The developed models may be used to predict the high pressure processing lethality (and process optimization), product development (ingredient selection), and to assist the microbial risk assessment.