Literature DB >> 9797300

Analysis of the influence of environmental parameters on Clostridium botulinum time-to-toxicity by using three modeling approaches.

D W Schaffner1, W H Ross, T J Montville.   

Abstract

This study used the technique of waiting time modeling to analyze the combined effects of temperature, pH, carbohydrate, protein, and lipid on the time-to-toxicity of Clostridium botulinum 56A. Waiting time models can be used whenever the time to the occurrence of some event is the variable of interest. In the case of the time-to-toxicity data, the variable is the time from the beginning of an experiment until a tube is identified as positive. The statistical analysis used the SAS procedure LIFEREG and included determination of the form of the response surface, identification of the error distribution, and simplification of the response surface. We found that increasing the macromolecule concentration decreased the probability of toxin formation. The probability of toxin formation also decreased at lower temperatures and at pHs further from the optimum. The waiting time modeling approach to developing models for botulinal toxin formation compared favorably with other approaches but had one specific advantage. Waiting time models have the inherent advantage that safety concerns regarding predictions are automatically quantified in the analysis by formally identifying a distribution of times-to-toxicity. The use of this time-to-toxicity distribution permits a customizable margin of safety (e.g., one in a million) not possible with other approaches.

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Year:  1998        PMID: 9797300      PMCID: PMC106662     

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  15 in total

1.  Growth and toxigenesis of C. botulinum type E in fishes packaged under modified atmospheres.

Authors:  D A Baker; C Genigeorgis; J Glover; V Razavilar
Journal:  Int J Food Microbiol       Date:  1990-05       Impact factor: 5.277

2.  Combined effect of water activity and pH on inhibition of toxin production by Clostridium botulinum in cooked, vacuum-packed potatoes.

Authors:  K L Dodds
Journal:  Appl Environ Microbiol       Date:  1989-03       Impact factor: 4.792

3.  Time-to-turbidity model for non-protective type B Clostridium botulinum.

Authors:  R C Whiting; J C Oriente
Journal:  Int J Food Microbiol       Date:  1997-04-29       Impact factor: 5.277

4.  Predictive model of the effect of temperature, pH and sodium chloride on growth from spores of non-proteolytic Clostridium botulinum.

Authors:  A F Graham; D R Mason; M W Peck
Journal:  Int J Food Microbiol       Date:  1996-08       Impact factor: 5.277

Review 5.  A dynamic approach to predicting bacterial growth in food.

Authors:  J Baranyi; T A Roberts
Journal:  Int J Food Microbiol       Date:  1994-11       Impact factor: 5.277

Review 6.  Predictive microbiology.

Authors:  T Ross; T A McMeekin
Journal:  Int J Food Microbiol       Date:  1994-11       Impact factor: 5.277

7.  Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory.

Authors:  R M Schoolfield; P J Sharpe; C E Magnuson
Journal:  J Theor Biol       Date:  1981-02-21       Impact factor: 2.691

8.  Proteases of Clostridium botulinum. IV. Inhibitors against proteases from Clostridium botulinum.

Authors:  T B Tjaberg; K Fossum
Journal:  Acta Vet Scand       Date:  1973       Impact factor: 1.695

9.  The effect of sodium chloride and temperature on the rate and extent of growth of Clostridium botulinum type A in pasteurized pork slurry.

Authors:  A M Gibson; N Bratchell; T A Roberts
Journal:  J Appl Bacteriol       Date:  1987-06

10.  Modeling lag phase of nonproteolytic Clostridium botulinum toxigenesis in cooked turkey and chicken breast as affected by temperature, sodium lactate, sodium chloride and spore inoculum.

Authors:  J Meng; C A Genigeorgis
Journal:  Int J Food Microbiol       Date:  1993-07       Impact factor: 5.277

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  1 in total

1.  Application of superabsorbent polymers (SAP) as desiccants to dry maize and reduce aflatoxin contamination.

Authors:  Duncan O Mbuge; Renata Negrini; Livine O Nyakundi; Serge P Kuate; Ranajit Bandyopadhyay; William M Muiru; Baldwyn Torto; Raffaele Mezzenga
Journal:  J Food Sci Technol       Date:  2016-08-24       Impact factor: 2.701

  1 in total

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