Modeling the growth rate of Listeria monocytogenes using absorbance measurements and calibration curves

The influence of environmental conditions (temperature and pH on the relationship between growth data expressed by absorbance (ABS) and data transformed to cell count (CC) measurements was studied, using calibration curves for predicting Listeria monocytogenes growth rate. With this aim, 19 calibration curves at different stress conditions were performed. A shift in the calibration curves was observed for the most stringent conditions, which affected cell viability. Subsequently, a Baranyi model was fitted to be ABS and CC data to obtain growth rate (GR(ABS) microbial growth, as a strong relationship between GR(ABS) and and GR(CC) data with temperature, citric acid, and ascorbic acid. The goodness of fit of both ABS and CC models to the data was observed (RMSE = 0.0223 and 0.0221; SEP[%]= 29 and 25, respectively). Mathematical validation was carried out by calculating bias and accuracy factors, providing reasonably acceptable values for both absorbance and cell count models (B-f = 1.11 and 1.09, A(f) = 1.44 and 1.41, respectively). Predictions for GR(CC) were compared to data from Growth Predictor software at different temperatures and pH. Response surface model predictions showed that a suitable combination of preservative factors can inhibit L. monocytogenes growth. These results highlight accurate predictions of growth parameters of L. monocytogenes.