Growth and survival of Salmonella Paratyphi A in roasted marinated chicken during refrigerated storage: Effect of temperature abuse and computer simulation for cold chain management. (April 2017) - Li, Miaoyun; Huang, Lihan; Yuan, Qianqian
Abstract: This research was conducted to evaluate the feasibility of using a one-step dynamic numerical analysis and optimization method to directly construct a tertiary model to describe the growth and survival of Salmonella Paratyphi A (SPA) in a marinated roasted chicken product. Multiple dynamic growth and survival curves obtained under different fluctuating temperature conditions between 4 and 35 °C were used to determine the growth kinetics of SPA. In combination with appropriate secondary models, the study examined both growth and survival of SPA simultaneously by an integrated one-step approach using a set of differential equations. The estimated minimum growth temperature (Tmin ) of SPA was 8.91 °C, matching well with the growth characteristics of this microorganism. The growth at temperatures above Tmin and the survival below Tmin was accurately simulated by the predictive models. For model development, the root mean square error (RMSE) was 0.26 log CFU/g. The predictive models and kinetic parameters were validated using two dynamic growth and survival curves along with one isothermal thermal growth curve. The validation also showed that the models were accurate in predicting the growth and survival of the bacterium, with the RMSE of predictions only 0.52 log CFU/g. The errors of predictions were within normal experimental errors. The results of this work may be used to predict the change in the population of SPA in the marinated roasted chickens in the cold chain and during temperature abuse and to conduct risk assessment of this pathogen. Highlights: One-step dynamic kinetic analysis is used to directly construct growth and survival models. The growth and survival of Salmonella Paratyphi A (SPA) in roasted marinated chickens is simultaneously analyzed. The models accurately predict the growth and survival of SPA during validation. The models can be used in the cold chain management.