A modeling approach to extend fluid milk shelf-life
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.
- Murphy SI, Reichler SJ, Martin NH, Boor KJ, Wiedmann M. 2021. Machine learning and advanced statistical modeling can identify key quality management practices that affect post-pasteurization contamination of fluid milk. J Food Prot. doi: 10.4315/JFP-20-431.
- Enayaty-Ahangar, F., S.I. Murphy, N.H. Martin, M. Wiedmann, and R. Ivanek. 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., N.H. Martin, K.J. Boor, and M. Wiedmann. 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.
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