Modeling the Effect of Temperature and pH on the Growth of Salmonella in Cut Tomatoes

Introduction: Outbreaks of salmonellosis associated with fresh cut produce have been an increasing food safety concern recently and tomato is one of the popular produce. When tomatoes are cut, Salmonella can be transferred from the tomato surface to the flesh, where growth can occur.

Purpose: The manipulation of pH and storage temperature provides one feasible method for Salmonella control in cut tomato products. The purpose of this research was to expand our existing understand of Salmonella growth in fresh cut tomatoes, resulting in regression models able to predict both growth rate and lag time of Salmonella as a function of pH and temperature.

Methods: Whole red round tomatoes were dip-inoculated in a mixture of four Salmonella strains obtained from the CDC, which were human isolates from cases associated with prior tomato salmonellosis outbreaks. Inoculated tomatoes were dried, cut into slices and incubated at temperatures from 10 to 30°C at 5-degree intervals. The pH of the cut tomatoes was adjusted from 3.7 to 4.4 by the addition of 5% citric acid. Samples were enumerated by plate counts on XLT4 agar until Salmonella growth reached stationary phase. Growth rates and lag time were calculated by an Excel add-on DMFit. Regression models were built by SAS.

Results: Both the growth rate and lag time of Salmonella were described as multivariate regression functions of temperature and pH with good fit (both with P < 0.0001 & R²>0.40). The probability of the end of lag time was described as a logistic function of time, temperature and pH with a good fit (P < 0.0001).

Significance: The models of growth rate and lag time of Salmonella in cut tomatoes built in this project provide useful tools in the risk assessment and risk management of estimating the risk by different temperature abuse and pH manipulation.