Assessment of temperature distribution of cold and hot meals in food services and the prediction growth of Salmonella spp. and Listeria monocytogenes

Abstract

Abstract Food distribution temperature is one of the most important factors to be controlled in order to prevent foodborne illnesses in food services. In this study, 339,548 records of food temperatures were collected from corporate catering food services and were analyzed, aiming to identify different scenarios and possible factors predictive of Salmonella and Listeria monocytogenes growth. Data fitting showed a Beta General distribution as the most appropriate model to describe the distribution temperature for most of the cold foods while the Triangular distribution fit best for hot foods. Temperature profiles and intrinsic parameters of the most frequently consumed cold foods were considered to predict Salmonella and L. monocytogenes growth using ComBase models. Salmonella exposed to temperatures of 7, 10, 15, 21, 36.5 and 40\u202f°C was able to grow from 0.11 to 1.06 log CFU/g after 6\u202fh, considering this period to be the maximum time of distribution of foods. L. monocytogenes exposed to temperatures of 1, 5, 10, 15, 21, 36.5 and 40\u202f°C showed growth between 0.05 and 2.09 log CFU/g during the same time period. According to the predictive model, Salmonella spp. and L. monocytogenes were not able to grow on cold foods stored for 6\u202fh at temperatures below 10\u202f°C. These temperatures therefore can be suggested as safe for the distribution of cold foods over periods shorter than 6\u202fh. Controlling the time elapsed in different distribution scenarios is necessary to prevent microbial multiplication.