Development and Validation of a Predictive Growth Model for Pathogenic Escherichia coli O157:H7 in Red Leaf Lettuce

Introduction: Escherichia coli O157:H7, an occasional contaminant of fresh produce, can present a serious health risk in minimally processed leafy green vegetables. To manage this human pathogen in leafy greens effectively, several predictive models for E. coli O157:H7 in leafy greens such as iceberg and romaine lettuce have developed. But predictive models that describe the behavior of E. coliO157:H7 in red leaf lettuce are lacking.

Purpose: This experiment was conducted to develop an appropriate predictive model for QMRA (Quantitative Microbial Risk Assessment) on E. coli O157:H7 in red leaf lettuce.

Methods: First, growth curves of E. coliO157:H7 in lettuce were obtained at several isothermal conditions (5, 10, 15, 20, 25, 30 and 37°C) and were then fitted into Gompertz model with a high correlation coefficient.

Results: The resulting values for SGR and LT were fitted by quadratic and inverse second order equation, respectively. After that, verification of the developed models has been carried out using several mathematical or statistical indicators such as R², bias factor (Bf) and accuracy factor (Af).

Significance: We showed that R² values were close to 1, and Bf values of 0.84 and 1.03 and Af values of 1.27 and 1.24 were all in the acceptable range. This result demonstrated that overall predictions showed good agreement with the experimental values, indicating success at providing reliable predictions of E. coli O157:H7 growth in red leaf lettuce.