A modeling approach to extend fluid milk shelf-life
Fluid Milk
The goal of this collection of models is to 1) predict microbial spoilage in fluid milk due to raw milk contamination by psychrotolerant spore-formers and post-pasteurization contamination (PPC) by Gram-negative bacteria, 2) identify key quality management practices that influence contamination of fluid milk, and 3) optimize benefit-cost ratio for the existing intervention strategies.
Milk spoilage model
Web interfaces for Monte-Carlo simulation models that predict the spoilage of fluid milk due to psychrotolerant spore-formers and post-pasteurization contamination.
Tutorial - Predictive Model for Milk Spoilage Due to Spores
Tutorial - Predictive Model for Milk Spoilage Due to Postpasteurization Contamination
Stakeholder webinar on development of data-informed approaches to reducing food waste
Models published
- Murphy SI, Reichler SJ, Martin NH, Boor KJ, Wiedmann M. 2021. Machine learning and advanced statistical modeling can identify key quality manageme
- nt practices that affect post-pasteurization contamination of fluid milk. J Food Prot. doi: 10.4315/JFP-20-431.
- Enayaty-Ahangar, F., Murphy, S. I., Martin, N. H., Wiedmann, M., Ivanek, R. 2021. Optimizing Pasteurized Fluid Milk Shelf-Life Through Microbial Spoilage Reduction. Front. sustain. food syst. 5:1–21. doi:10.3389/fsufs.2021.670029.
- Buehler, A. J., Martin, N. H., Boor, K. J., Wiedmann, M. 2018. Psychrotolerant spore-former growth characterization for the development of a dairy spoilage predictive model. J. Dairy Sci. 101:6964–6981. doi:10.3168/jds.2018-14501.
- Lau, S., Trmcic, A., Martin, N. H., Wiedmann, M., Murphy, S. I. 2022. Development of a Monte Carlo simulation model to predict pasteurized fluid milk spoilage due to post-pasteurization contamination with gram-negative bacteria. J Dairy Sci. , 105(3), 1978-1998. doi: 10.3168/jds.2021-21316
Models under development
- Cost-benefit analysis of intervention strategies to reduce PPC in fluid milk
- Extension of milk spore model to account temperature shift during supply chain
- A combined model that predicts spoilage due to both psychrotolerant spore-former and PPC
Acknowledgments
The funding for development of predictive models of fluid milk spoilage has been provided by the Foundation for Food and Agriculture Research (FFAR; Award #CA18-SS-0000000206) and by the New York State Milk Promotion Advisory Board (Albany, NY) who funds the Voluntary Shelf-Life Program.