Polish raw milk artisanal cheese may pose a threat to consumer safety due to pathogen presence. The aim of this study was to assess the microbiological safety, quality and physicochemical composition of cow’s and goat’s milk fresh cheeses produced by farmers on a small scale. A total of 62 samples of six cheese types were analyzed for Listeria monocytogenes, Salmonella spp., lactic acid bacteria and coliform presence and concentration levels. The physicochemical analysis estimated energy, water, protein, fat, carbohydrate, ash and salt content. The cheeses were also tested for heavy metal contamination. Listeria monocytogenes and Salmonella spp. were not detected in any of the samples. Coliforms were present in all the goat’s milk cheeses and only in two of the cow’s milk cheeses. Low levels of cadmium, below 0.008 ppm, were detected in three of the cows’ milk samples. The raw milk cheeses studied were free of the pathogens examined and were of high nutritional value.

In the framework of Quantitative Microbiological Risk Assessment, the estimation of the ingested dose of a hazard by the consumer is of paramount importance. This may be calculated by means of predictive modeling of growth/inactivation of the pathogen studied. For products that spend the majority of their shelf life in the domestic refrigerator, storage temperature will significantly impact the microbial population dynamics. To describe the variability of domestic storage temperatures in Poland, a survey including 77 participants, was carried out in Lodz, Poland. Participants were provided with temperature data loggers, which measured their refrigerator temperature for 24 h in 5-min intervals. The temperature-time profiles were used to calculate the mean working temperature, standard deviation, minimum and maximum values, and the data were statistically analyzed to find the best fitting probability distribution using R programming language. Out of the tested refrigerators, 49.35% had a mean working temperature of over 5 °C and 3.9% exceeded 10 °C. Distribution fitting scenarios were tested for goodness of fit, and the final selected distribution was a truncated normal distribution. This study can prove useful in Monte Carlo simulation analysis for stochastic quantitative food risk assessment in Poland.