Development of predictive model for the growth of Staphylococcus aureus in Kimbab

被引：18

作者：

Ding, Tian ^{[1
,2
]}

Shim, Young-Hwan ^{[1
,2
]}

Kim, Ha-Na ^{[1
,2
]}

Ha, Sang-Do ^{[3
]}

Chung, Myung-Sub ^{[3
]}

Hwang, In-Gyun ^{[4
]}

Oh, Deog-Hwan ^{[1
,2
]}

机构：

[1] Kangwon Natl Univ, Dept Food Sci & Biotechnol, Chunchon 200701, Gangwon, South Korea

[2] Kangwon Natl Univ, Inst Biosci & Biotechnol, Chunchon 200701, Gangwon, South Korea

[3] Chung Ang Univ, Dept Food Sci & Technol, Anseong 456756, Gyeonggi, South Korea

[4] Korea Food & Drug Adm, Dept Food Microbiol, Cheongwon 122704, Chungbuk, South Korea

来源：

FOOD SCIENCE AND BIOTECHNOLOGY | 2011年 / 20卷 / 02期

关键词：

Staphylococcus aureus; primary model; secondary model; kimbab; verification; TO-EAT KIMBAB; LISTERIA-MONOCYTOGENES; TEMPERATURE; PH; SALMONELLA;

D O I：

10.1007/s10068-011-0065-y

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

This study was conducted to develop predictive models for the growth of Staphylococcus aureus in kimbab as a function of storage temperatures (7, 10, 12, 14, 16, 20, 25, and 30A degrees C). The growth data were fitted into the modified Gompertz model and the Logistic model, and the goodness-of-fit of primary models was compared using determination of coefficient, mean square error, and Akaike's information criterion. The modified Gompertz model was found to be more suitable to describe the growth data. Therefore, the growth rate (GR) and lag time (LT) obtained from the modified Gompertz model were employed to establish the secondary models. The newly developed models were validated using root mean square error (RMSE), bias factor (B-f), and accuracy factor (A(f)). The results showed that RMSE < 0.20 and B-f and A(f) values were within the reliable range, which indicated that the presented predictive models can be used to assess the risk of S. aureus infection in kimbab.

引用

页码：471 / 476

页数：6

共 32 条

[1]

ADAIR C, 1989, Food Microbiology (London), V6, P7, DOI 10.1016/S0740-0020(89)80033-4

[2] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].