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Fluid milk

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.

Models published 

  • 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



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.