| dc.contributor.author |
Lee, J |
en |
| dc.contributor.author |
Skandamis, P |
en |
| dc.contributor.author |
Park, A |
en |
| dc.contributor.author |
Yoon, H |
en |
| dc.contributor.author |
Hwang, I-G |
en |
| dc.contributor.author |
Lee, S-H |
en |
| dc.contributor.author |
Cho, J-I |
en |
| dc.contributor.author |
Yoon, Y |
en |
| dc.date.accessioned |
2014-06-06T06:52:26Z |
|
| dc.date.available |
2014-06-06T06:52:26Z |
|
| dc.date.issued |
2013 |
en |
| dc.identifier.issn |
13446606 |
en |
| dc.identifier.uri |
http://dx.doi.org/10.3136/fstr.19.331 |
en |
| dc.identifier.uri |
http://62.217.125.90/xmlui/handle/123456789/6008 |
|
| dc.subject |
Dynamic model |
en |
| dc.subject |
Predictive model |
en |
| dc.subject |
Sauce |
en |
| dc.subject |
Staphylococcus aureus |
en |
| dc.subject.other |
Acceptable performance |
en |
| dc.subject.other |
Goodness of fit |
en |
| dc.subject.other |
Growth parameters |
en |
| dc.subject.other |
Model validation |
en |
| dc.subject.other |
Predictive models |
en |
| dc.subject.other |
Root mean square errors |
en |
| dc.subject.other |
Sauce |
en |
| dc.subject.other |
Staphylococcus aureus |
en |
| dc.subject.other |
Bacteria |
en |
| dc.subject.other |
Digital storage |
en |
| dc.subject.other |
Forecasting |
en |
| dc.subject.other |
Mean square error |
en |
| dc.subject.other |
Molluscs |
en |
| dc.subject.other |
Shellfish |
en |
| dc.subject.other |
Dynamic models |
en |
| dc.title |
Development of mathematical models to predict Staphylococcus aureus growth in sauces under constant and dynamic temperatures |
en |
| heal.type |
journalArticle |
en |
| heal.identifier.primary |
10.3136/fstr.19.331 |
en |
| heal.publicationDate |
2013 |
en |
| heal.abstract |
This study developed kinetic models to predict the fate of Staphylococcus aureus in sauces. S. aureus was inoculated in Carbonara and Octopus sauce. Total bacterial and S. aureus cell counts were enumerated during storage. Growth data were fitted to the Baranyi model to calculate growth parameters. The parameters were then fitted to secondary models, and dynamic models were developed. Root mean square error (RMSE) was calculated for model validation. Growth of total bacteria and S. aureus was observed in Carbonara and Octopus sauces. Goodness of fit for primary, secondary model, and dynamic model was good. In addition, the developed model had acceptable performance (RMSE: 0.326 (Carbonara), 0.361 (Octopus sauce)). The results indicate that the developed models for Carbonara and Octopus sauces should be useful in predicting S. aureus growth. |
en |
| heal.journalName |
Food Science and Technology Research |
en |
| dc.identifier.issue |
2 |
en |
| dc.identifier.volume |
19 |
en |
| dc.identifier.doi |
10.3136/fstr.19.331 |
en |
| dc.identifier.spage |
331 |
en |
| dc.identifier.epage |
335 |
en |