Abstract
Psychrotolerant gram-negative bacteria introduced as post-pasteurization contamination (PPC) are a major cause of spoilage and reduced shelf life of high-temperature, short-time pasteurized fluid milk. To provide improved tools to (1) predict pasteurized fluid milk shelf life as influenced by PPC and (2) assess the effectiveness of different potential interventions that could reduce spoilage due to PPC, we developed a Monte Carlo simulation model that predicts fluid milk spoilage due to psychrotolerant gram-negative bacteria introduced as PPC. As a first step, 17 gram-negative bacterial isolates frequently associated with fluid milk spoilage were selected and used to generate growth data in skim milk broth at 6°C. The resulting growth parameters, frequency of isolation for the 17 different isolates, and initial concentration of bacteria in milk with PPC, were used to develop a Monte Carlo model to predict bacterial number at different days of shelf life based on storage temperature of milk. This model was then validated with data from d 7 and 10 of shelf life, collected from commercial operations. The validated model predicted that the parameters (1) maximum growth rate and (2) storage temperature had the greatest influence on the percentage of containers exceeding 20,000 cfu/mL standard plate count on d 7 and 10 (i.e., spoiling due to PPC), which indicates that accurate data on maximum growth rate and storage temperature are important for accurate predictions. In addition to allowing for prediction of fluid milk shelf life, the model allows for simulation of "what-if" scenarios, which allowed us to predict the effectiveness of different interventions to reduce overall fluid milk spoilage due to PPC through a set of proof-of-concept scenario (e.g., frequency of PPC in containers reduced from 100% to 10%; limiting distribution temperature to a maximum of 6°C). Combined with other models, such as previous models on fluid milk spoilage due to psychrotolerant spore-forming bacteria, the data and tools developed here will allow for rational, digitally enabled, fluid milk shelf life prediction and quality enhancement.
Highlights
Microbial spoilage is a contributor to food loss and waste globally, and represents a challenge for maintaining the quality and expected shelf life of many foods, including fluid milk (Hoover, 2017; FAO, 2019)
The quality of fluid milk and dairy products can be degraded via different mechanisms, microbial growth is the predominant mechanism for pasteurized fluid milk spoilage (Martin et al, 2016)
post-pasteurization contamination (PPC) can introduce a variety of different organisms, key organisms of concern for their potential to cause spoilage are those that can grow in refrigerated fluid milk
Summary
Microbial spoilage is a contributor to food loss and waste globally, and represents a challenge for maintaining the quality and expected shelf life of many foods, including fluid milk (Hoover, 2017; FAO, 2019). Fluid milk production, processing, and transport is estimated to be responsible for 2.4 kg of CO2 equivalents (CO2e) per kilogram of milk (FAO, 2010). One of the main causes of microbial fluid milk spoilage is post-pasteurization contamination (PPC) with gram-negative bacteria during processing. Existing data show that in the United States approximately 50% of HTST-pasteurized fluid milk spoilage is due to PPC (Alles et al, 2018; Reichler et al, 2018). PPC can introduce a variety of different organisms, key organisms of concern for their potential to cause spoilage are those that can grow in refrigerated fluid milk (e.g., around 6°C). Most studies suggest that the majority of fluid milk spoilage is caused by psychro-
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