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- M. H. Zwietering
- Department of Food Science, Agricultural University Wageningen, P.O. Box 8129, 6700 EV Wageningen, The Netherlands
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- I. Jongenburger
- Department of Food Science, Agricultural University Wageningen, P.O. Box 8129, 6700 EV Wageningen, The Netherlands
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- F. M. Rombouts
- Department of Food Science, Agricultural University Wageningen, P.O. Box 8129, 6700 EV Wageningen, The Netherlands
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- K. van 't Riet
- Department of Food Science, Agricultural University Wageningen, P.O. Box 8129, 6700 EV Wageningen, The Netherlands
書誌事項
- 公開日
- 1990-06
- 権利情報
-
- https://journals.asm.org/non-commercial-tdm-license
- DOI
-
- 10.1128/aem.56.6.1875-1881.1990
- 公開者
- American Society for Microbiology
この論文をさがす
説明
<jats:p> Several sigmoidal functions (logistic, Gompertz, Richards, Schnute, and Stannard) were compared to describe a bacterial growth curve. They were compared statistically by using the model of Schnute, which is a comprehensive model, encompassing all other models. The <jats:italic>t</jats:italic> test and the <jats:italic>F</jats:italic> test were used. With the <jats:italic>t</jats:italic> test, confidence intervals for parameters can be calculated and can be used to distinguish between models. In the <jats:italic>F</jats:italic> test, the lack of fit of the models is compared with the measuring error. Moreover, the models were compared with respect to their ease of use. All sigmoidal functions were modified so that they contained biologically relevant parameters. The models of Richards, Schnute, and Stannard appeared to be basically the same equation. In the cases tested, the modified Gompertz equation was statistically sufficient to describe the growth data of <jats:italic>Lactobacillus plantarum</jats:italic> and was easy to use. </jats:p>
収録刊行物
-
- Applied and Environmental Microbiology
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Applied and Environmental Microbiology 56 (6), 1875-1881, 1990-06
American Society for Microbiology
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詳細情報 詳細情報について
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- CRID
- 1363670319720352896
-
- ISSN
- 10985336
- 00992240
- http://id.crossref.org/issn/00992240
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- データソース種別
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- Crossref

