Identification of the significant factors in food quality using global sensitivity analysis and the accept-and-reject algorithm. Part II: Application to the cold chain of cooked ham

• A method to model time temperature variability of cooked ham was proposed.
• The growth of L. monocytogenes through cold chain was modeled.
• Important factors on consumers’ exposure were identified.
• 0.67% Of all products had more than 100 CFU/g at the consumption.

The aim of this manuscript is to apply the methodology proposed in an accompanying part I describing the different sources of variability in the cold chain of cooked ham allowing the identification of significant factors on the microbiological safety. The methodology uses a kinetic model to predict the evolution of Listeriamonocytogenes and stochastic models to account for the variability of product time-temperature history, biological properties and initial contamination. The cold chain is composed of chilled storage, distribution warehouse, supermarket display cabinet, transport by consumer and domestic refrigerator. Then, the simulation results issued from the method presented in part I (global sensitivity analysis and accept-and-reject algorithm) were analysed. The impact of input factors was calculated and ranked. It was found that the variability of the product time temperature profile was the most important one influencing the final contamination level of L.monocytogenes. A refined analysis by accept-and-reject algorithm revealed the impact of the chilled storage, display cabinet and domestic fridge on this final contamination level.