eCite Digital Repository

Predictive microbiology: Quantitative science delivering quantifiable benefits to the meat industry and other food industries

Citation

McMeekin, TA, Predictive microbiology: Quantitative science delivering quantifiable benefits to the meat industry and other food industries, Meat Science, 77, (1 SPEC. ISS.) pp. 17-27. ISSN 0309-1740 (2007) [Refereed Article]

DOI: doi:10.1016/j.meatsci.2007.04.005

Abstract

Predictive microbiology is considered in the context of the conference theme "chance, innovation and challenge", together with the impact of quantitative approaches on food microbiology, generally. The contents of four prominent texts on predictive microbiology are analysed and the major contributions of two meat microbiologists, Drs. T.A. Roberts and C.O. Gill, to the early development of predictive microbiology are highlighted. These provide a segue into R&D trends in predictive microbiology, including the Refrigeration Index, an example of science-based, outcome-focussed food safety regulation. Rapid advances in technologies and systems for application of predictive models are indicated and measures to judge the impact of predictive microbiology are suggested in terms of research outputs and outcomes. The penultimate section considers the future of predictive microbiology and advances that will become possible when data on population responses are combined with data derived from physiological and molecular studies in a systems biology approach. Whilst the emphasis is on science and technology for food safety management, it is suggested that decreases in foodborne illness will also arise from minimising human error by changing the food safety culture. © 2007 Elsevier Ltd. All rights reserved.

Item Details

Item Type:Refereed Article
Research Division:Biological Sciences
Research Group:Microbiology
Research Field:Microbiology not elsewhere classified
Objective Division:Health
Objective Group:Public Health (excl. Specific Population Health)
Objective Field:Food Safety
Author:McMeekin, TA (Professor Thomas McMeekin)
ID Code:50367
Year Published:2007
Web of Science® Times Cited:17
Deposited By:Agricultural Science
Deposited On:2007-08-01
Last Modified:2009-12-15
Downloads:0

Repository Staff Only: item control page