BaranyiFM function to fit the Baranyi & Roberts full growth model to a complete microbial growth curve.
Returns the model parameters estimated according to data collected in microbial growth experiments.
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
- lag
is the duration of the lag phase in time units
Details
The 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
Baranyi J, Roberts TA (1994). “A dynamic approach to predicting bacterial growth in food.” International Journal of Food Microbiology, 23, 277-294.
Author
Vasco Cadavez vcadavez@ipb.pt and Ursula Gonzales-Barron ubarron@ipb.pt
Examples
library(gslnls)
data(growthfull)
initial_values = list(Y0=-0.1, Ymax=22, MUmax=1.7, lag=5)
fit <- gsl_nls(lnN ~ BaranyiFM(Time, Y0, Ymax, MUmax, lag),
data=growthfull,
start = initial_values)
summary(fit)
#>
#> Formula: lnN ~ BaranyiFM(Time, Y0, Ymax, MUmax, lag)
#>
#> Parameters:
#> Estimate Std. Error t value Pr(>|t|)
#> Y0 -0.01043 0.27279 -0.038 0.97
#> Ymax 21.13052 0.22783 92.748 9.98e-15 ***
#> MUmax 1.86815 0.06507 28.712 3.67e-10 ***
#> lag 5.08623 0.28282 17.984 2.31e-08 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 0.4525 on 9 degrees of freedom
#>
#> Number of iterations to convergence: 7
#> Achieved convergence tolerance: 0
#>