Hazard analysis applied to microbial growth in foods: Development and application of three-dimensional models to predict bacterial growth

Broughall, J. M.; Brown, Charles W.

doi:10.1016/0740-0020(84)90005-4

Cited by 68 publications

(38 citation statements)

References 9 publications

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“…in laboratory broth (Baranyi and others 1996;Gibson and others 1988;Koutsoumanis and others 1998), in milk (Broughall and Brown 1984;Davey 1989), and in beef (Daughty and others 1997; Dickson and others 1992;Mackey and Kerridge 1988). A Pathogenic Modeling Program (U.S. Dept of Agriculture/Agriculture Research Service (USDA/ARS) Eastern Regional Research Center, Wyndmoor, Pa.) is available and provides the growth and survival models of Salmonella spp.…”

Section: Salmonellamentioning

confidence: 97%

Predictive Models for the Survival/death of Campylobacter jejuni and Salmonella Typhimurium in Poultry Scalding and Chilling

Yang¹,

Wang²,

Li³

et al. 2002

Journal of Food Science

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Predictive models for the survival/death of Campylobacter jejuni and Salmonella Typhimurium during poultry scalding and chilling, as functions of temperature (50 to 60 °C), chlorine level (0 to 50 ppm) and water age (0, 10 h for scalding; 0, 8 h for chilling), were evaluated and developed using the data from previous study. As primary models, the Weibull distribution, exponential, logistic, and Gompertz models were compared. The secondary models were developed by modifying the Davey and polynomial models. Mean Square Errors (MSE) and the plots of predicted in contrast to observed survivors showed a good fit and prediction. The Weibull distribution-based secondary model was selected due to its fewer parameters and better prediction (MSEs < 0.4) compared to the other models.

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Section: Salmonellamentioning

confidence: 97%

Predictive Models for the Survival/death of Campylobacter jejuni and Salmonella Typhimurium in Poultry Scalding and Chilling

Yang¹,

Wang²,

Li³

et al. 2002

Journal of Food Science

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show abstract

“…It was concluded that an interaction between the effects of temperature and water activity, revealed by their modelling studies, was an important consideration in the valid application of HACCP analysis to food processing and distribution cycles. Broughall and Brown (1984) extended this work to include pH effects and again stressed the wider application of their models to risk analysis and HACCP. Roberts (1989) also indicated the complementary nature of HACCP and predictive modelling, a theme expanded by McMeekin et al (1992) who considered that predictive microbiology could be viewed as an extension of the HACCP concept.…”

Section: Relationship Of Predictive Modelling To Haccpmentioning

confidence: 97%

Predictive microbiology and HACCP

Ross¹,

McMeekin²

1995

HACCP in Meat, Poultry, and Fish Processing

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“…It fitted the data well, was easy to program and the statistical properties of the estimates were favourable. The Gompertz equation was used to describe the growth of Salmonella in several media (Bratchell, Gibson, Truman, Kelly, & Roberts, 1989;Broughall & Brown, 1984;Gibson et al, 1988;Mackey & Kerridge, 1988;Mackey, Roberts, Mansfield, & Farkas, 1980). Secondary models describe the dependence of the parameters of the primary model on specified environmental conditions, for example, temperature, pH, water activity, atmosphere composition, naturally occurring organic acids or added preservatives.…”

Section: Modelling Growthmentioning

confidence: 99%