摘要 : Predictive microbiology is a tool used to support food safety management systems. It employs mathematical descriptions of changes in microbial populations in foods, including dairy foods. This study determined growth of <i>Listeri... 展开 Predictive microbiology is a tool used to support food safety management systems. It employs mathematical descriptions of changes in microbial populations in foods, including dairy foods. This study determined growth of <i>Listeria monocytogenes</i> strain 38 added to milk during storage for 21 days at temp. ranging from 3 to 15 degrees C. The <i>L. monocytogenes</i> 38 count was obtained using a calibrated impedance monitoring system. Before a mathematical model is deemed a suitable tool for predicting microbial growth it needs to be validated. In order to achieve this, the bacterial growth counts results obtained were fitted to the Baranyi model using the DMFit program (an add-in for Microsoft Office Excel). The specific growth rates calculated in DMFit were used to validate, graphically, 2 existing general models, namely Pathogen Modelling Program 7.0 (PMP7.0; USDA, USA) and ComBase Predictor (CP; Inst. of Food Res., Norwich, UK). The usefulness and suitability of these models were also verified using selected mathematical coeff., namely the bias factor and the accuracy factor. This validation indicated that, of the programs used, program CP had the highest prediction accuracy. 收起