Browsing Articles and other publications by RIVM employees by Subjects
Now showing items 1-2 of 2
Predictable and unpredictable survival of foodborne pathogens during non-isothermal heating.In previous work, extreme survival of various bacterial species during cooking was reported when attached to chicken meat. In this paper the effects of an extremely high challenge temperature on survival of Salmonella Typhimurium and Campylobacter jejuni, attached to chicken breast fillets or pork to test for matrix effects are reported. Survival was predicted, using standard D- and z-values from the literature, and compared to experimentally obtained data. Attached to meat, both S. Typhimurium and C. jejuni survived longer than predicted, longer when attached to chicken meat than when attached to pork. Additionally, the effect of non-isothermal heating on survival of almonella in buffer is described. In buffer, when slowly heated, Salmonella died off as predicted. When Salmonella was heated in buffer according to a heating profile mimicking that of the surface of meat in boiling water, it appeared that cells died off much slower than predicted. It is shown that the thermal characteristics of Salmonella surviving the first 35 s of fast heating had changed. After these 35 s, remaining Salmonella survived for minutes, even at a challenge temperature of 90 °C. During heating, cell size decline was observed. A loss of intracellular water during cooking might have resulted in smaller, dehydrated cells, in cells with altered thermal resistance characteristics. This could explain why the use of standard D-and z-values did not allow the correct prediction of survival of Salmonella during fast heating in buffer, or during cooking, being attached to the surface of meat. Many factors affect the level of heat resistance of bacteria. The results of this and a former study show that attachment to meat contributes to an increased level of heat resistance of bacteria. A fast heating process further contributes to the increased level of heat resistance possibly as the result of changed thermal characteristics due to a loss of water.
Probabilistic inversion for chicken processing linesWe discuss an application of probabilistic inversion techniques to a model of campylobacter transmission in chicken processing lines. Such techniques are indicated when we wish to quantify a model which is new and perhaps unfamiliar to the expert community. In this case there are no measurements for estimating model parameters, and experts are typically unable to give a considered judgment. In such cases, experts are asked to quantify their uncertainty regarding variables which can be predicted by the model. The experts’ distributions (after combination) are then pulled back onto the parameter space of the model, a process termed “probabilistic inversion”. This study illustrates two such techniques, iterative proportional fitting (IPF) and PARmeter fitting for uncertain models (PARFUM). In addition, we illustrate how expert judgement on predicted observable quantities in combination with probabilistic inversion may be used for model validation and/or model criticism.