Simulation of Dynamic Microbial Inactivation

Prediction and adjustment to experimental data of microbial inactivation. Several models available in the literature are implemented.

bioinactivation: a package for modelling microbial inactivation in R.

The bioinactivation package implements several function for the modelization of microbial inactivation in R. It includes:

  • functions for the prediction of isothermal or non-isothermal microbial inactivation.
  • functions for the adjustment of inactivation models to isothermal experiments.
  • functions for the fitting of inactivation models to dynamic experiments.
  • functions for the calculation of prediction intervals for isothermal or non-isothermal microbial inactivation processes.

The inactivation models most commonly used in industry and academia are implemented in this package:

  • Bigelow's model.
  • Peleg's model.
  • Mafart's model.
  • Geeraerd's model.

Furthermore, this package includes some training data sets mimicking isothermal and non-isothermal inactivation experiments.


Version 1.2.1

  • Corrected a bug in the plotting of dynamic predictions when the profile was isothermal.

Version 1.2.0

  • Implemented the ggplot2 plotting of isothermal fit objects.
  • Added the option to include the temperature profile in the plot.
  • The fitting and prediction functions now also accept logN0, as well as N0. If logN0 is a fitting parameters, this variable is fitted, rather than N0 (which is more stable numerically).
  • Added the Arrhenius model.

Version 1.1.5

  • Corrected the DOI in the citation file.

Version 1.1.4

  • Added CITATION file with the information of the paper recently published in Food Research International.

Version 1.1.3

  • Added the possibility to pass additional arguments to ode when making predictions.
  • Minor corrections and improvements to the vignette.

Version 1.1.2

  • Corrected a bug in Geeraerd's model.

Version 1.1.1

  • Added graphics::legend to NAMESPACE.
  • Added stats::coef and stats::vcov to NAMESPACE.

Version 1.1.0

  • The adjustment is, by default, made targetting the logarithmic count for all cases now.
  • Added a tolerance to avoid observations at time 0 causing singularities.
  • Function predict_inactivation_MCMC for the calculation of prediction intervals using Monte Carlo methods.
  • Plots with ggplot2.
  • MCMC prediction intervals using MCMC.
  • is. methods for all the objects defined.
  • Some minor corrections in function documentation.
  • Extended README file.
  • Corrected names of the authors in DESCRIPTION.

Reference manual

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1.2.1 by Alberto Garre, a year ago

Browse source code at

Authors: Alberto Garre [aut, cre] , Pablo S. Fernandez [aut] , Jose A. Egea [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports dplyr, deSolve, FME, lazyeval, ggplot2, MASS, graphics, stats, rlang

Suggests knitr, testthat

Imported by bioOED.

See at CRAN