Probabilistic Model for Listeria monocytogenes Growth during Distribution,Retail Storage,and Domestic Storage of Pasteurized Milk

A survey on the time-temperature conditions of pasteurized milk in Greece during transportation to retail, retail storage, and domestic storage and handling was performed. The data derived from the survey were described with appropriate probability distributions and introduced into a growth model of Listeria monocytogenes in pasteurized milk which was appropriately modified for taking into account strain variability. Based on the above components, a probabilistic model was applied to evaluate the growth of L. monocytogenes during the chill chain of pasteurized milk using a Monte Carlo simulation. The model predicted that, in 44.8% of the milk cartons released in the market, the pathogen will grow until the time of consumption. For these products the estimated mean total growth of L. monocytogenes during transportation, retail storage, and domestic storage was 0.93 log CFU, with 95th and 99th percentiles of 2.68 and 4.01 log CFU, respectively. Although based on EU regulation 2073/2005 pasteurized milk produced in Greece belongs to the category of products that do not allow the growth of L. monocytogenes due to a shelf life (defined by law) of 5 days, the above results show that this shelf life limit cannot prevent L. monocytogenes from growing under the current chill chain conditions. The predicted percentage of milk cartons—initially contaminated with 1 cell/1-liter carton—in which the pathogen exceeds the safety criterion of 100 cells/ml at the time of consumption was 0.14%. The probabilistic model was used for an importance analysis of the chill chain factors, using rank order correlation, while selected intervention and shelf life increase scenarios were evaluated. The results showed that simple interventions, such as excluding the door shelf from the domestic storage of pasteurized milk, can effectively reduce the growth of the pathogen. The door shelf was found to be the warmest position in domestic refrigerators, and it was most frequently used by the consumers for domestic storage of pasteurized milk. Furthermore, the model predicted that a combination of this intervention with a decrease of the mean temperature of domestic refrigerators by 2°C may allow an extension of pasteurized milk shelf life from 5 to 7 days without affecting the current consumer exposure to L. monocytogenes.L. monocytogenes is an important safety concern for the dairy industry. Several listeriosis outbreaks have been associated with the consumption of dairy products, including pasteurized milk (13, 22). An effective control of L. monocytogenes in pasteurized milk should be based on the selection of raw milk and the controls of the processing, packaging, distribution, and storage conditions. In general, the pathogen is effectively controlled during pasteurization. However, its presence in the finished product is possible as a result of postpasteurization contamination from sources in the plant environment. Considering that the levels of postpasteurization contamination are usually very low, the extent of L. monocytogenes growth during distribution, retail storage, and domestic storage is of major significance for the safety status of pasteurized milk at the time of consumption.The growth of L. monocytogenes during distribution and storage of pasteurized milk can be evaluated using the available predictive models. During the last decade, a large number of mathematical models for L. monocytogenes growth have been published (9, 11, 16, 19, 21, 24, 26, 31, 38), and some of them have been targeted to pasteurized milk (1, 40, 49). However, since the available data show that conditions that prevail during the chill chain vary significantly (8, 17, 23, 27, 28, 34, 44, 45, 48), the value of a deterministic application of these models as a tool in safety management of pasteurized milk would be limited.In recent years the need for taking into account the variabilities of the various factors in predictive microbiology has been increasingly recognized, leading to a more sophisticated modeling approach called probabilistic or stochastic modeling. The main characteristic of probabilistic modeling is the specific quantification of variabilities using probability distributions for the input data rather than point estimates. The importance of characterizing variability was stressed by Nauta (41), who illustrated the differences in decisions that could result if variability is ignored. Probabilistic modeling is being used with increasing frequency in the area of food safety. It has been extensively applied in quantitative microbial risk assessments (12, 18, 20), in quality and safety management systems (25, 30, 32), and recently for more specific topics, such as the evaluation of the effects of food processing (39) and the compliance of food products to safety criteria set by regulations (33).In the present study a probabilistic modeling approach was applied for evaluating the growth of Listeria monocytogenes in pasteurized milk from production to the time of consumption based on a Monte Carlo simulation. The objectives of the study were (i) to estimate the growth of the pathogen at the various stages of the chill chain, including transportation to retail, retail storage, and domestic storage, (ii) to analyze the importance of the chill chain factors, (iii) to evaluate the effects of selected intervention scenarios related to the improvement of the chill chain and handling conditions, and (iv) to evaluate the effect of a potential extension of milk shelf life on the growth of Listeria monocytogenes.