Predictive thermal inactivation model for the combined effect of temperature, cinnamaldehyde and carvacrol on starvation-stressed multiple Salmonella serotypes in ground chicken

We investigated the combined effect of three internal temperatures (60, 65 and 71.1 °C) and four concentrations (0.0, 0.1, 0.5 and 1% vol/wt) of two natural antimicrobials on the heat resistance of an eight-strain cocktail of Salmonella serovars in chicken meat. A complete factorial design (3 × 4 × 4) was used to assess the effects and interactions of heating temperature and the two antimicrobials, carvacrol and cinnamaldehyde. The 48 variable combinations were replicated to provide a total of 96 survivor curves from the experimental data. Mathematical models were then developed to quantify the combined effect of these parameters on heat resistance of starved Salmonella cells. The theoretical analysis shows that the addition of plant-derived antimicrobials overcomes the heat resistance of starvation-stressed Salmonella in ground chicken meat. The influence of the antimicrobials allows reduced heat treatments, thus reducing heat-induced damage to the nutritional quality of ground-chicken products. Although the reported omnibus log-linear model with tail and the omnibus sigmoid model could represent the experimental survivor curves, their discrepancy only became apparent in the present study when lethality times (D-values and t7.0) from each of the models were calculated. Given the concave nature of the inactivation curves, the log-linear model with tail greatly underestimates the times needed to obtain 7.0 log lethality. Thus, a polynomial secondary model, based on the sigmoid model, was developed to accurately predict the 7.0-log reduction times. The three-factor predictive model can be used to estimate the processing times and temperatures required to achieve specific log reductions, including the regulatory recommendation of 7.0-log reduction of Salmonella in ground chicken.