We aim to predict the population density of Salmonella spp. through the pork supply chain under dynamic environmental conditions (pH, a(w) and temperature) that fluctuate from growth to survival/slow inactivation. To do this, the dependence of the probability of growth, and of the growth and inactivation rate on the temperature, pH and a(w) were modelled. Probabilistic and kinetic measurements, i.e. growth and survival curves, were collected from the ComBase database (www.combase.cc). Conditions at which selected data used to fit the models were generated covered wide ranges that are relevant to the pork supply chain. Probabilistic and kinetic models were combined to give predictions on the concentration of Salmonella spp. at any stage of the pork supply chain under fluctuating pH, a(w) and/or temperature. Models were implemented in a user-friendly computing tool freely available from http://www.ifr.ac.uk/safety/SalmonellaPredictions/. This program provides estimates on the population dynamics of Salmonella spp. at any stage of the pork supply chain and its predictive performance has been validated in several pork products.
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