Development and validation of a predictive model for pathogenic Escherichia coli in fresh-cut produce.

Abstract

This study was performed to develop and validate a predictive growth model of pathogenic Escherichia coli to ensure the safety of fresh‐cut produce. Samples were inoculated with a cocktail of seven E. coli strains of five pathotypes (EHEC, Enterohemorrhagic E. coli; ETEC, Enterotoxigenic E. coli; EPEC, Enteropathogenic E. coli; EIEC, Enteroinvasive E. coli, and EAEC, Enteroaggregative E. coli) and stored at 4, 10, 12, 15, 25, 30, and 37°C. Growth of pathogenic E. coli was observed above 12°C. The primary growth model for pathogenic E. coli in fresh‐cut produce was developed based on the Baranyi model. The secondary model was developed as a function of temperature for lag phase duration (LPD) and maximum specific growth rate (μmax) based on the polynomial second‐order model. The primary and secondary models for pathogenic E. coli were fitted with a high degree of goodness of fit (R2 ≥ 0.99). The bias factor (Bf), accuracy factor (Af), and root mean square error (RMSE) were 0.995, 1.011, and 0.084, respectively. The growth model we developed can provide useful data for assessing the quantitative microbial risk of pathogenic E. coli in fresh‐cut produce intended for human consumption. In addition, it is thought to be widely available in industries that produce, process, distribute, and sell fresh‐cut produce.