Salmonella in Egg Predictor models the growth of antibiotic resistant salmonella (Typhimurium DT104) in Liquid Egg Products between 10°C and 42°C.
The model is based on observed growth of the organism in four commercial liquid egg products held at 10, 20, 30, 37, and 42 degrees C for 0 to 384 hours, as in
Musgrove (et al.), 2009: Growth and Survival of Antibiotic-Resistant Salmonella Typhimurium DT104 in Liquid Egg Products. Journal of Food Protection 72/9.
The specific subset of data used to create the model can be found in the ComBase Database for the indicated range of temperatures.
Salmonella in Egg Predictor uses the model of Baranyi and Roberts (1994) as the primary model. To create the secondary models, the logarithm of the specific growth rate has been described as a function of the environmental factors by a standard quadratic multivariate polynomial.
Input values are temperature, pH and water activity, which can be also provided in terms of sodium chloride (%NaCl). The %NaCl values are automatically transformed into water activity values by the formula:
Aw=1-%NaCl*(5.2471+0.12206*%NaCl)/1000 (Resnik and Chirife, 1988)
To get a prediction, values for
- Initial level (initial cell count expressed as log10 cfu/ml)
- Physiological state (physiological state of the cells expressed in terms of a value between 0 and 1) and
- Time (desired duration of observation in hours)
must be also provided, although default values are automatically supplied by the predictor. The default value for the physiological state corresponds to the typical value for the curves used to estimate the parameters of the model.
Output: maximum specific growth rate, doubling time and a graphical representation of the predicted growth curve. Time vs. cell concentration data points for the predicted curve are also displayed and may be selected and copied for use in other applications (e.g. Excel)