Literature DB >> 29579905

Parameter estimations in predictive microbiology: Statistically sound modelling of the microbial growth rate.

Simen Akkermans1, Filip Logist2, Jan F Van Impe3.   

Abstract

When building models to describe the effect of environmental conditions on the microbial growth rate, parameter estimations can be performed either with a one-step method, i.e., directly on the cell density measurements, or in a two-step method, i.e., via the estimated growth rates. The two-step method is often preferred due to its simplicity. The current research demonstrates that the two-step method is, however, only valid if the correct data transformation is applied and a strict experimental protocol is followed for all experiments. Based on a simulation study and a mathematical derivation, it was demonstrated that the logarithm of the growth rate should be used as a variance stabilizing transformation. Moreover, the one-step method leads to a more accurate estimation of the model parameters and a better approximation of the confidence intervals on the estimated parameters. Therefore, the one-step method is preferred and the two-step method should be avoided.
Copyright © 2017. Published by Elsevier Ltd.

Keywords:  Confidence intervals; Exponential phase; Sampling variance; Secondary model; Variance stabilizing transformation

Mesh:

Year:  2017        PMID: 29579905     DOI: 10.1016/j.foodres.2017.11.083

Source DB:  PubMed          Journal:  Food Res Int        ISSN: 0963-9969            Impact factor:   6.475


  2 in total

1.  On the use of in-silico simulations to support experimental design: A case study in microbial inactivation of foods.

Authors:  Alberto Garre; Jose Lucas Peñalver-Soto; Arturo Esnoz; Asunción Iguaz; Pablo S Fernandez; Jose A Egea
Journal:  PLoS One       Date:  2019-08-27       Impact factor: 3.240

2.  Isolation and Molecular Identification of the Native Microflora on Flammulina velutipes Fruiting Bodies and Modeling the Growth of Dominant Microbiota (Lactococcus lactis).

Authors:  Qi Wei; Xinyuan Pan; Jie Li; Zhen Jia; Ting Fang; Yuji Jiang
Journal:  Front Microbiol       Date:  2021-05-21       Impact factor: 5.640

  2 in total

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