Literature DB >> 10573388

Predictive food microbiology for the meat industry: a review.

K McDonald1, D W Sun.   

Abstract

Predictive food microbiology (PFM) is an emerging multidisciplinary area of food microbiology. It encompasses such disciplines as mathematics, microbiology, engineering and chemistry to develop and apply mathematical models to predict the responses of microorganisms to specified environmental variables. This paper provides a critical review on the development of mathematical modelling with emphasis on modelling techniques, descriptions, classifications and their recent advances. It is concluded that the role and accuracy of predictive food microbiology will increase as understanding of the complex interactions between microorganisms and food becomes clearer. However the reliance of food microbiology on laboratory techniques and skilled personnel to determine process and food safety is still necessary.

Mesh:

Year:  1999        PMID: 10573388     DOI: 10.1016/s0168-1605(99)00126-9

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


  11 in total

Review 1.  Methodologies for the characterization of microbes in industrial environments: a review.

Authors:  Johanna Maukonen; Jaana Mättö; Gun Wirtanen; Laura Raaska; Tiina Mattila-Sandholm; Maria Saarela
Journal:  J Ind Microbiol Biotechnol       Date:  2003-05-23       Impact factor: 3.346

2.  Development of a microbial model for the combined effect of temperature and pH on spoilage of ground meat, and validation of the model under dynamic temperature conditions.

Authors:  K Koutsoumanis; A Stamatiou; P Skandamis; G-J E Nychas
Journal:  Appl Environ Microbiol       Date:  2006-01       Impact factor: 4.792

3.  Use of artificial neural networks and a gamma-concept-based approach to model growth of and bacteriocin production by Streptococcus macedonicus ACA-DC 198 under simulated conditions of Kasseri cheese production.

Authors:  Panayiota Poirazi; Frédéric Leroy; Marina D Georgalaki; Anastassios Aktypis; Luc De Vuyst; Effie Tsakalidou
Journal:  Appl Environ Microbiol       Date:  2006-12-08       Impact factor: 4.792

4.  A combined model to predict the functionality of the bacteriocin-producing Lactobacillus sakei strain CTC 494.

Authors:  Frédéric Leroy; Luc De Vuyst
Journal:  Appl Environ Microbiol       Date:  2003-02       Impact factor: 4.792

5.  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

6.  Use of modified Richards model to predict isothermal and non-isothermal microbial growth.

Authors:  Jhony Tiago Teleken; Alessandro Cazonatto Galvão; Weber da Silva Robazza
Journal:  Braz J Microbiol       Date:  2018-03-07       Impact factor: 2.476

7.  Effect of combined function of temperature and water activity on the growth of Vibrio harveyi.

Authors:  Kang Zhou; Meng Gui; Pinglan Li; Shaohua Xing; Tingting Cui; Zhaohui Peng
Journal:  Braz J Microbiol       Date:  2012-06-01       Impact factor: 2.476

Review 8.  Colonial vs. planktonic type of growth: mathematical modeling of microbial dynamics on surfaces and in liquid, semi-liquid and solid foods.

Authors:  Panagiotis N Skandamis; Sophie Jeanson
Journal:  Front Microbiol       Date:  2015-10-29       Impact factor: 5.640

9.  Growth Simulation and Discrimination of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum Using Hyperspectral Reflectance Imaging.

Authors:  Ye Sun; Xinzhe Gu; Zhenjie Wang; Yangmin Huang; Yingying Wei; Miaomiao Zhang; Kang Tu; Leiqing Pan
Journal:  PLoS One       Date:  2015-12-07       Impact factor: 3.240

10.  Modeling of starter cultures growth for improved Thai sausage fermentation and cost estimating for sausage preparation and transportation.

Authors:  Wiramsri Sriphochanart; Wanwisa Skolpap
Journal:  Food Sci Nutr       Date:  2018-06-28       Impact factor: 2.863

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