Monte Carlo simulation model predicts bactofugation can extend shelf-life of pasteurized fluid milk, even when raw milk with low spore counts is used as the incoming ingredient

Bacterial spores from raw milk that survive the pasteurization process are responsible for half of all the spoilage of fluid milk. Bactofugation has received more attention as a nonthermal method that can reduce the presence of bacterial spores in milk and with it the spoilage of fluid milk. The objective of this work was to determine the effectiveness of bactofugation in removing spores from raw milk and estimate the effect the spore removal could have on shelf-life of fluid milk. The study was conducted in a commercial fluid milk processing facility where warm spore removal was performed using one-phase bactofuge followed by warm cream separation and high temperature, short time pasteurization. Samples from different stages of fluid milk processing with and without the use of bactofuge were tested for total plate count, mesophilic spore count, psychrotolerant spore count (PSC), and somatic cell count. Results were evaluated to determine the count reductions during different stages of fluid milk processing and compare counts in fluid milk processed with and without bactofugation. Bactofugation on average reduced the total plate count by 1.81 ± 0.72 log cfu/mL, mesophilic spore count by 1.08 ± 0.71 log cfu/mL, PSC by 0.86 ± 0.59 log cfu/mL, and somatic cell count by 135,881 ± 43,942 cells/mL. Psychrotolerant spore count in final pasteurized skim milk processed with and without bactofugation was used to predict the shelf-life of the pasteurized skim milk using the Monte Carlo simulation model. Although PSC in the initial raw milk was already low (−0.63 ± 0.47 log cfu/mL), the predicted values from the simulation model showed that bactofugation would extend the shelf-life of pasteurized skim milk by approximately 2 d. The results of this study will directly help fluid milk processors evaluate the benefits of using bactofugation as an intervention in their plants, and also demonstrate the benefits of using mathematical modeling in decision making.