A predictive model for Salmonella spp. growth in ground pork was developed and validated
using kinetic growth data. Salmonella spp. kinetic growth data in ground pork were
collected at several isothermal conditions (between 10 and 45°C) and Baranyi model
was fitted to describe the growth at each temperature, separately. The maximum growth
rates (μ(max)) estimated from the Baranyi model were modeled as a function of temperature
using a modified Ratkowsky equation. To estimate bacterial growth under dynamic temperature
conditions, the differential form of the Baranyi model, in combination with the modified
Ratkowsky equation for rate constants, was solved numerically using fourth order Runge-Kutta
method. The dynamic model was validated using five different dynamic temperature profiles
(linear cooling, exponential cooling, linear heating, exponential heating, and sinusoidal).
Performance measures, root mean squared error, accuracy factor, and bias factor were
used to evaluate the model performance, and were observed to be satisfactory. The
dynamic model can estimate the growth of Salmonella spp. in pork within a 0.5 log
accuracy under both linear and exponential cooling profiles, although the model may
overestimate or underestimate at some data points, which were generally<1 log. Under
sinusoidal temperature profiles, the estimates from the dynamic model were also within
0.5 log of the observed values. However, underestimation could occur if the bacteria
were exposed to temperatures below the minimum growth temperature of Salmonella spp.,
since low temperature conditions could alter the cell physiology. To obtain an accurate
estimate of Salmonella spp. growth using the models reported in this work, it is suggested
that the models be used at temperatures above 7°C, the minimum growth temperature
for Salmonella spp. in pork.