Predictive model for growth of Listeria monocytogenes in untreated and treated lettuce with alkaline electrolyzed water

This study was performed to develop predictive models for the growth kinetics of Listeria monocytogenes in Ready-to-Eat (RTE) lettuce treated with or without alkaline electrolyzed water. Firstly, growth curves of L. monocytogenes in treated and untreated RTE lettuce were obtained at several isothermal conditions (4, 10, 15, 20, 25, 30, and 35°C) and were then fitted into Gompertz model with a high correlation coefficient (R2 > 0.99). Growth parameters such as growth rate (GR) and lag time (LT) estimated by Gompertz model were found mostly have significant difference (P < 0.05) with those predicted by Combined database for predictive microbiology (ComBase). Moreover, increased GR and decreased LT were observed with increasing storage temperatures from 4 to 35°C and untreated lettuce showed lowest GR or longest LT, and followed by treated lettuce and ComBase, respectively. Furthermore, square root equation was employed to establish the secondary models for the GR to evaluate the effect of different storage temperatures on the growth rate of L. monocytogenes in untreated lettuce and treated lettuce. After that, verification of the developed models has been carried out using several mathematical or statistical indicators such as R2, the average mean square error (MSE), bias factor (Bf) and accuracy factor (Af). It showed that R2 values were close to 1 (>0.95), and MSE calculated from models of untreated and treated lettuce were 0.0011 and 0.0008, respectively. Also, Bf values of 0.980 and 1.034 and Af values of 1.107 and 1.118 were all in the acceptable range. This demonstrated that overall predictions showed good agreement with the experimental values, indicating success at providing reliable predictions of L. monocytogenes growth in RTE lettuce.