Predictive Modeling for the Growth of Aeromonas hydrophila on Lettuce as a Function of Combined Storage Temperature and Relative Humidity.

Abstract

This study developed predictive growth models of Aeromonas hydrophila on lettuce as a function of combined storage temperature (15-35°C) and relative humidity (RH, 60-80%) using a polynomial equation. The primary model of specific growth rate, lag time, and maximum population density showed a good fit (R2 ≥ 0.95) with a Gompertz equation. A secondary model was obtained using a quadratic polynomial equation. The appropriateness of the secondary model was verified by mean square error (0.0001-0.8848), bias factor (Bf = 0.962-1.009), and accuracy factor (Af = 1.002-1.104). The newly developed secondary models for A. hydrophila could be incorporated into the tertiary modeling program to predict the growth of A. hydrophila as a function of combined temperature and RH. The developed model may be useful to predict potential A. hydrophila growth on lettuce, which is important for food safety purpose during the overall food chain of lettuce from farm to table. It could offer reliable and useful information of growth kinetics for the quantification of microbial risk assessment of A. hydrophila on lettuce.