Literature DB >> 8856374

Application of predictive microbiology to estimate the number of Bacillus cereus in pasteurised milk at the point of consumption.

M H Zwietering1, J C de Wit, S Notermans.   

Abstract

A procedure is presented to quantitatively estimate the growth of a particular organism in a food product during chilled storage using predictive microbiology. This results in a quantification of the contribution of every individual process step to the total number of organisms, which may be a useful tool to support decisions on existing process lines as well as in process and product design. It is demonstrated that predictive microbiology will only estimate to within orders of magnitude of bacterial growth. This helps to pinpoint the most important aspects of a line. The calculations can be helpful to set critical limits and to detect hazards by performing 'what if' analyses. The procedure is explained for the growth of Bacillus cereus in milk. It is indicated, that with the current information, the effect of time/temperature can be estimated. However, to make an accurate exposure analysis, more information will be needed.

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Year:  1996        PMID: 8856374     DOI: 10.1016/0168-1605(96)00991-9

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


  8 in total

1.  Comparing nonsynergistic gamma models with interaction models to predict growth of emetic Bacillus cereus when using combinations of pH and individual undissociated acids as growth-limiting factors.

Authors:  Elisabeth G Biesta-Peters; Martine W Reij; Leon G M Gorris; Marcel H Zwietering
Journal:  Appl Environ Microbiol       Date:  2010-07-16       Impact factor: 4.792

2.  Optimization of transportation routing problem for fresh food in time-varying road network: Considering both food safety reliability and temperature control.

Authors:  Zhixue Zhao; Xiamiao Li; Xiancheng Zhou
Journal:  PLoS One       Date:  2020-07-27       Impact factor: 3.240

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.  Comparison of two optical-density-based methods and a plate count method for estimation of growth parameters of Bacillus cereus.

Authors:  Elisabeth G Biesta-Peters; Martine W Reij; Han Joosten; Leon G M Gorris; Marcel H Zwietering
Journal:  Appl Environ Microbiol       Date:  2010-01-15       Impact factor: 4.792

5.  Modeling and Validation of the Ecological Behavior of Wild-Type Listeria monocytogenes and Stress-Resistant Variants.

Authors:  Karin I Metselaar; Tjakko Abee; Marcel H Zwietering; Heidy M W den Besten
Journal:  Appl Environ Microbiol       Date:  2016-08-15       Impact factor: 4.792

6.  Modeling the growth of Listeria monocytogenes in soft blue-white cheese.

Authors:  Per Sand Rosshaug; Ann Detmer; Hanne Ingmer; Marianne Halberg Larsen
Journal:  Appl Environ Microbiol       Date:  2012-09-14       Impact factor: 4.792

Review 7.  Status and future of Quantitative Microbiological Risk Assessment in China.

Authors:  Q L Dong; G C Barker; L G M Gorris; M S Tian; X Y Song; P K Malakar
Journal:  Trends Food Sci Technol       Date:  2015-03       Impact factor: 12.563

8.  Prevalence, Virulence Genes, Antimicrobial Susceptibility, and Genetic Diversity of Bacillus cereus Isolated From Pasteurized Milk in China.

Authors:  Tiantian Gao; Yu Ding; Qingping Wu; Juan Wang; Jumei Zhang; Shubo Yu; Pengfei Yu; Chengcheng Liu; Li Kong; Zhao Feng; Moutong Chen; Shi Wu; Haiyan Zeng; Haoming Wu
Journal:  Front Microbiol       Date:  2018-03-26       Impact factor: 5.640

  8 in total

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