logistic_model

Modelling of population growth under static and dynamic environmental conditions.
Includes functions for model fitting and making prediction under isothermal and
dynamic conditions. The methods (algorithms & models) are based on
predictive microbiology (See Perez-Rodriguez and Valero (2012, ISBN:978-1-4614-5519-6)).

Alberto Garre

biogrowth

Modelling of Population Growth

Jeroen Koomen

Heidy den Besten

Marcel Zwietering

logistic_model function

<dl><dt>times</dt>
<dd>Numeric vector of storage times</dd>
<dt>logN0</dt>
<dd>Initial log microbial count</dd>
<dt>mu</dt>
<dd>Maximum specific growth rate (in ln CFU/<a href="/link/t?package=biogrowth&version=1.0.6" data-mini-rdoc="biogrowth::t">t</a>)</dd>
<dt>lambda</dt>
<dd>Lag phase duration</dd>
<dt>C</dt>
<dd>Difference between <code>logN0</code> and the maximum log-count.</dd></dl>

Arguments

Logistic growth model — logistic_model

<dl>

<dt>times</dt>
<dd>Numeric vector of storage times</dd>


<dt>logN0</dt>
<dd>Initial log microbial count</dd>


<dt>mu</dt>
<dd>Maximum specific growth rate (in ln CFU/<a href='https://rdrr.io/r/base/t.html'>t</a>)</dd>


<dt>lambda</dt>
<dd>Lag phase duration</dd>


<dt>C</dt>
<dd>Difference between <code>logN0</code> and the maximum log-count.</dd>

</dl>

logistic_model: Logistic growth model

Description

Usage

Value

Arguments