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Fang no lag growth model

Source: R/fang_nolag.R
FangNLM.Rd

FangNLM function to fit the Fang no lag growth model to an incomplete microbial growth curve. Returns the model parameters estimated according to data collected in microbial growth experiments.

Usage

FangNLM(t, Y0, Ymax, MUmax)

Arguments

t

is a numeric vector indicating the time of the experiment

Y0

is the natural logarithm of the initial microbial concentration (ln(N0)) at time=0

Ymax

is the natural logarithm of the maximum concentration (ln(Nmax)) reached by the microorganism

MUmax

is the maximum specific growth rate given in time units

Value

An object of nls class

Details

Model's inputs are:

t: time, assuming time zero as the beginning of the experiment.

Y(t): the natural logarithm of the microbial concentration (ln(N(t)) measured at time t.

Users should make sure that the microbial concentration input is entered in natural logarithm, Y(t) = ln(N(t)).

References

Fang T, Gurtler JB, Huang L (2012). “Growth Kinetics and Model Comparison of Cronobacter sakazakii in Reconstituted Powdered Infant Formula.” Journal of Food Science, 77(9), E247-E255. doi:10.1111/j.1750-3841.2012.02873.x , https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1750-3841.2012.02873.x, https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1750-3841.2012.02873.x. Fang T, Liu Y, Huang L (2013). “Growth kinetics of Listeria monocytogenes and spoilage microorganisms in fresh-cut cantaloupe.” Food Microbiology, 34(1), 174-181. ISSN 0740-0020, doi:10.1016/j.fm.2012.12.005 .

Author

Vasco Cadavez, vcadavez@ipb.pt and Ursula Gonzales-Barron, ubarron@ipb.pt

Examples

## Example: Fang no lag model
library(gslnls)
data(growthnolag)  # simulated data set.
initial_values = list(Y0=0, Ymax=22, MUmax=1.7) # define the initial values
fit <- gsl_nls(lnN ~ FangNLM(Time, Y0, Ymax, MUmax),
           data=growthnolag,
           start =  initial_values)
summary(fit)
#> 
#> Formula: lnN ~ FangNLM(Time, Y0, Ymax, MUmax)
#> 
#> Parameters:
#>       Estimate Std. Error t value Pr(>|t|)    
#> Y0     1.75827    0.36368   4.835  0.00189 ** 
#> Ymax  21.13234    0.24673  85.650 7.79e-12 ***
#> MUmax  1.85922    0.06619  28.091 1.86e-08 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> Residual standard error: 0.4896 on 7 degrees of freedom
#> 
#> Number of iterations to convergence: 5 
#> Achieved convergence tolerance: 1.386e-12
#>