APPLICATION OF PREDICTIVE INACTIVATION MODELS TO EVALUATE SURVIVAL OF STAPHYLOCOCCUS AUREUS IN FRESH-CUT APPLES TREATED WITH DIFFERENT PLANT HYDROSOLS

Abstract

In this study, inhibitory effects of bayleaf, rosemary, sage, and thyme hydrosols on the growth of Staphylococcus aureus inoculated on fresh-cut apples were investigated using several sigmoidal models (modified Gompertz, logistic, Richards, Stannard, and Whiting and Buchanan). In addition, these models were compared to describe the inactivation of S. aureus by fitting the experimental data using nonlinear models and various statistical parameters (the mean percentage error, the mean bias error, the root mean square error, the modeling efficiency, and chi-square parameters) as well as determination of coefficient (R-2). The modified Gompertz, logistic, and Stannard models exhibited better fits than Richards and Whiting and Buchanan models regarding these statistical parameters. Rosemary and thyme hydrosols were found to be the most efficient sanitizers in reducing the S. aureus numbers. Results demonstrate that predictive models could be utilized for describing the inactivation or survival of S. aureus on fresh-cut apple with the effects of the treatments with plant hydrosols.