Dynamic growth models for L. monocytogenes during ripening in Camembert cheese

S. Liu, V. M. Puri

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Population density curves for L. monocytogenes in Camembert cheese were obtained during ripening. The pH, moisture content, and the specific growth rate values for survival and growth data for each trial were used to develop and verify three levels of accuracy Camembert cheese Dynamic Models (CDMs) (location, region, and section-specific dynamic growth models). The location-specific dynamic growth model provided the most detailed information and had highest accuracy for the prediction of L. monocytogenes during ripening of Camembert cheese. Experimental data had a good fit with calculated values for the three levels of CDMs: (1) for location-specific dynamic growth model, the R2 values for top center (TC), top surface (TS), center (C), bottom center (BC), and bottom surface (BS) regions were 0.92, 0.94, 0.91, 0.94, and 0.95, respectively. The standard error ranged from 0.19 to 0.24 log(CFU/g). (2) For region-specific dynamic growth model, the R2 values for two regions were 0.93 (TS and C) and 0.94 (TC, BC, and BS), respectively. The standard errors were 0.19 and 0.22 log(CFU/g), respectively. (3) For section-specific dynamic growth model, the R2 value was 0.93 with standard error of 0.27 log(CFU/g).

Original languageEnglish (US)
Pages (from-to)511-520
Number of pages10
JournalLWT - Food Science and Technology
Volume41
Issue number3
DOIs
StatePublished - Apr 1 2008

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Camembert cheese
Cheese
dynamic models
growth models
ripening
Growth
Population Density
specific growth rate
cheeses
population density
Survival Rate
water content
prediction

All Science Journal Classification (ASJC) codes

  • Food Science

Cite this

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abstract = "Population density curves for L. monocytogenes in Camembert cheese were obtained during ripening. The pH, moisture content, and the specific growth rate values for survival and growth data for each trial were used to develop and verify three levels of accuracy Camembert cheese Dynamic Models (CDMs) (location, region, and section-specific dynamic growth models). The location-specific dynamic growth model provided the most detailed information and had highest accuracy for the prediction of L. monocytogenes during ripening of Camembert cheese. Experimental data had a good fit with calculated values for the three levels of CDMs: (1) for location-specific dynamic growth model, the R2 values for top center (TC), top surface (TS), center (C), bottom center (BC), and bottom surface (BS) regions were 0.92, 0.94, 0.91, 0.94, and 0.95, respectively. The standard error ranged from 0.19 to 0.24 log(CFU/g). (2) For region-specific dynamic growth model, the R2 values for two regions were 0.93 (TS and C) and 0.94 (TC, BC, and BS), respectively. The standard errors were 0.19 and 0.22 log(CFU/g), respectively. (3) For section-specific dynamic growth model, the R2 value was 0.93 with standard error of 0.27 log(CFU/g).",
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Dynamic growth models for L. monocytogenes during ripening in Camembert cheese. / Liu, S.; Puri, V. M.

In: LWT - Food Science and Technology, Vol. 41, No. 3, 01.04.2008, p. 511-520.

Research output: Contribution to journalArticle

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