Journal of Applied Microbiology, Vol.110, No.4, 995-1006, 2011
Kinetic model-based prediction of the persistence of Salmonella enterica serovar Typhimurium under tropical agricultural field conditions
Aim: Present a kinetic model-based approach for using isothermal data to predict the survival of manure-borne enteric bacteria under dynamic conditions in an agricultural environment. Methods and Results: A model to predict the survival of Salmonella enterica serovar Typhimurium under dynamic temperature conditions in soil in the field was developed. The working hypothesis was that the inactivation phenomena associated with the survival kinetics of an organism in an agricultural matrix under dynamic temperature conditions is for a large part due to the cumulative effect of inactivation at various temperatures within the continuum registered in the matrix in the field. The modelling approach followed included (i) the recording of the temperature profile that the organism experiences in the field matrix, (ii) modelling the survival kinetics under isothermal conditions at a range of temperatures that were registered in the matrix in the field; and (iii) using the isothermal-based kinetic models to develop models for predicting survival under dynamic conditions. The time needed for 7 log CFU g-1Salmonella Typhimurium in manure and manure-amended soil to reach the detection limit of the enumeration method (2 log CFU g-1) under tropical conditions in the Central Agro-Ecological Zone of Uganda was predicted to be 61-68 days and corresponded with observed CFU of about 2 center dot 2-3 center dot 0 log CFU g-1, respectively. The Bias and Accuracy factor of the prediction was 0 center dot 71-0 center dot 84 and 1 center dot 2-1 center dot 4, respectively. Conclusions: Survival of Salm. Typhimurium under dynamic field conditions could be for 71-84% determined by the developed modelling approach, hence substantiating the working hypothesis. Significance and Impact of the Study: Survival kinetic models obtained under isothermal conditions can be used to develop models for predicting the persistence of manure-borne enteric bacteria under dynamic field conditions in an agricultural environment.