Literature DB >> 7873330

Modelling the growth, survival and death of microorganisms in foods: the UK food micromodel approach.

P J McClure1, C W Blackburn, M B Cole, P S Curtis, J E Jones, J D Legan, I D Ogden, M W Peck, T A Roberts, J P Sutherland.   

Abstract

Techniques for the development of mathematical models in the area of predictive microbiology have greatly improved recently, allowing better and more accurate descriptions of microbial responses to particular environmental conditions, thus enabling predictions of those responses to be made with greater confidence. Recognising the potential value of applying these techniques in the food industry, the Ministry of Agriculture, Fisheries and Food (MAFF) initiated a nationally coordinated five-year programme of research into the growth and survival of microorganisms in foods, with the aim of developing a computerised Predictive Microbiology Database in the UK. This initiative has resulted in the systematic generation of data, through protocols which ensure consistency of methodology, so that data in the database are truly comparable and compatible, and lead to reliable predictive models. The approaches taken by scientists involved in this programme are described and the various stages in the development of mathematical models summarized. It is hoped that this initiative and others being developed in the USA, Australia, Canada and other countries, will encourage a more integrated approach to food safety which will influence all stages of food production and, eventually, result in the development of an International Predictive Microbiology Database.

Mesh:

Year:  1994        PMID: 7873330     DOI: 10.1016/0168-1605(94)90156-2

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  8 in total

1.  Predictive modeling of the shelf life of fish under nonisothermal conditions.

Authors:  K Koutsoumanis
Journal:  Appl Environ Microbiol       Date:  2001-04       Impact factor: 4.792

2.  Individual and combined effects of ph and lactic acid concentration on Listeria innocua inactivation: development of a predictive model and assessment of experimental variability.

Authors:  M Janssen; A H Geeraerd; A Cappuyns; L Garcia-Gonzalez; G Schockaert; N Van Houteghem; K M Vereecken; J Debevere; F Devlieghere; J F Van Impe
Journal:  Appl Environ Microbiol       Date:  2007-01-05       Impact factor: 4.792

3.  Staphylococcus aureus growth boundaries: moving towards mechanistic predictive models based on solute-specific effects.

Authors:  Cynthia M Stewart; Martin B Cole; J David Legan; Louise Slade; Mark H Vandeven; Donald W Schaffner
Journal:  Appl Environ Microbiol       Date:  2002-04       Impact factor: 4.792

4.  Modeling yeast spoilage in cold-filled ready-to-drink beverages with Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Candida lipolytica.

Authors:  Alyce Stiles Battey; Siobain Duffy; Donald W Schaffner
Journal:  Appl Environ Microbiol       Date:  2002-04       Impact factor: 4.792

5.  Characterization of unexpected growth of Escherichia coli O157:H7 by modeling.

Authors:  M Cornu; M L Delignette-Muller; J P Flandrois
Journal:  Appl Environ Microbiol       Date:  1999-12       Impact factor: 4.792

6.  Influence of the natural microbial flora on the acid tolerance response of Listeria monocytogenes in a model system of fresh meat decontamination fluids.

Authors:  J Samelis; J N Sofos; P A Kendall; G C Smith
Journal:  Appl Environ Microbiol       Date:  2001-06       Impact factor: 4.792

7.  A competitive microflora increases the resistance of Salmonella typhimurium to inimical processes: evidence for a suicide response.

Authors:  T G Aldsworth; R L Sharman; C E Dodd; G S Stewart
Journal:  Appl Environ Microbiol       Date:  1998-04       Impact factor: 4.792

8.  Development and validation of experimental protocols for use of cardinal models for prediction of microorganism growth in food products.

Authors:  Anthony Pinon; Marcel Zwietering; Louise Perrier; Jeanne-Marie Membré; Benoît Leporq; Eric Mettler; Dominique Thuault; Louis Coroller; Valérie Stahl; Michèle Vialette
Journal:  Appl Environ Microbiol       Date:  2004-02       Impact factor: 4.792

  8 in total

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