Literature DB >> 2641486

Predicting microbial growth: the consequences of quantity of data.

N Bratchell1, A M Gibson, M Truman, T M Kelly, T A Roberts.   

Abstract

Having developed a mathematical model of the growth responses in a laboratory medium of salmonellae (mixed inoculum of Salmonella thompson, S stanley and S. infantis) as affected by pH level, NaCl concentration and storage temperature, the consequences of systematic removal of data has been examined. Three-dimensional plots of fitted response surfaces for the whole data set and the data reduced by three strategies highlighted differences between models and illustrated the consequences of using insufficient data. The risk of an erroneous model was demonstrated.

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Year:  1989        PMID: 2641486     DOI: 10.1016/0168-1605(89)90079-2

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


  3 in total

1.  Modeling of the bacterial growth curve.

Authors:  M H Zwietering; I Jongenburger; F M Rombouts; K van 't Riet
Journal:  Appl Environ Microbiol       Date:  1990-06       Impact factor: 4.792

2.  Mathematical Models for the Effects of pH, Temperature, and Sodium Chloride on the Growth of Bacillus stearothermophilus in Salty Carrots.

Authors:  T M Ng; D W Schaffner
Journal:  Appl Environ Microbiol       Date:  1997-04       Impact factor: 4.792

3.  The pattern of growth observed for Clostridium botulinum type A1 strain ATCC 19397 is influenced by nutritional status and quorum sensing: a modelling perspective.

Authors:  Adaoha E C Ihekwaba; Ivan Mura; Michael W Peck; G C Barker
Journal:  Pathog Dis       Date:  2015-10-07       Impact factor: 3.166

  3 in total

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