Mathematical Modelling of (Dynamic) Microbial Inactivation

Functions for modelling microbial inactivation under isothermal or dynamic conditions. The calculations are based on several mathematical models broadly used by the scientific community and industry. Functions enable to make predictions for cases where the kinetic parameters are known. It also implements functions for parameter estimation for isothermal and dynamic conditions. The model fitting capabilities include an Adaptive Monte Carlo method for a Bayesian approach to parameter estimation.


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.

News

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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install.packages("bioinactivation")

1.2.3 by Alberto Garre, a year ago


Browse source code at https://github.com/cran/bioinactivation


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, purrr

Suggests knitr, testthat, rmarkdown


Imported by bioOED.


See at CRAN