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A novel modelling approach for predicting microbial growth in a raw cured meat product stored at 3°C and at 12°C in air

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dc.contributor.author Aggelis, G en
dc.contributor.author Samelis, J en
dc.contributor.author Metaxopoulos, J en
dc.date.accessioned 2014-06-06T06:43:46Z
dc.date.available 2014-06-06T06:43:46Z
dc.date.issued 1998 en
dc.identifier.issn 01681605 en
dc.identifier.uri http://dx.doi.org/10.1016/S0168-1605(98)00095-6 en
dc.identifier.uri http://62.217.125.90/xmlui/handle/123456789/1442
dc.subject Modelling en
dc.subject Predictive microbiology en
dc.subject Raw cured meat en
dc.subject Sausage en
dc.subject.other ambient air en
dc.subject.other article en
dc.subject.other controlled study en
dc.subject.other ecosystem en
dc.subject.other food storage en
dc.subject.other growth rate en
dc.subject.other kinetics en
dc.subject.other mathematical model en
dc.subject.other meat en
dc.subject.other methodology en
dc.subject.other microbial growth en
dc.subject.other nonhuman en
dc.subject.other parameter en
dc.subject.other prediction en
dc.subject.other regression analysis en
dc.subject.other temperature en
dc.subject.other Bacteria en
dc.subject.other Cold en
dc.subject.other Colony Count, Microbial en
dc.subject.other Enterobacteriaceae en
dc.subject.other Food Microbiology en
dc.subject.other Forecasting en
dc.subject.other Greece en
dc.subject.other Humidity en
dc.subject.other Hydrogen-Ion Concentration en
dc.subject.other Kinetics en
dc.subject.other Lactobacillus en
dc.subject.other Least-Squares Analysis en
dc.subject.other Meat Products en
dc.subject.other Microscopy, Phase-Contrast en
dc.subject.other Models, Biological en
dc.subject.other Pseudomonadaceae en
dc.subject.other Refrigeration en
dc.subject.other Sodium Chloride en
dc.subject.other Yeasts en
dc.title A novel modelling approach for predicting microbial growth in a raw cured meat product stored at 3°C and at 12°C in air en
heal.type journalArticle en
heal.identifier.primary 10.1016/S0168-1605(98)00095-6 en
heal.publicationDate 1998 en
heal.abstract To predict microbial growth during chill storage of a traditional Greek raw sausage, a numerical model was developed and validated. In our novel approach, the specific growth rate of each microbial population was calculated on the basis of the main microbial populations grown in the sausage. In addition, the specific destructive effect of the sausage ecosystem was introduced to evaluate microbial growth. The model was integrated by the Runge-Kutta method and the parameter values were optimised by the least squares method. Fitting of the model to the experimental data derived from four sausage batches stored aerobically at 3 and 12°C successfully described the microbial growth kinetics in the sausage niche. Finally, the parameter values estimated by the fitting of the model on the data set from each batch were used to predict microbial growth in the other batches at both storage temperatures. en
heal.journalName International Journal of Food Microbiology en
dc.identifier.issue 1-2 en
dc.identifier.volume 43 en
dc.identifier.doi 10.1016/S0168-1605(98)00095-6 en
dc.identifier.spage 39 en
dc.identifier.epage 52 en


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