Skip to contents

Rosso full growth model

Source: R/rosso_full.R
RossoFM.Rd

RossoFM function to fit the Rosso full growth model to complete microbial growth curve. Returns the model parameters estimated according to data collected in microbial growth experiments.

Usage

RossoFM(t, Y0, MUmax, Ymax, lag)

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

MUmax

is the maximum specific growth rate given in time units

Ymax

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

lag

is the duration of the lag phase in time units

Value

An object of nls class

Details

Model's inputs are:s

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(X(t)).

References

Rosso L, Bajard S, Flandrois JP, Lahellec C, Fournaud J, Veit P (1996). “Differential growth of Listeria monocytogenes at 4 and 8 ºC: Consequences for the Shelf Life of Chilled Products.” Journal of Food Protection, 59(9), 944-949. ISSN 0362-028X, doi:10.4315/0362-028X-59.9.944 , https://meridian.allenpress.com/jfp/article-pdf/59/9/944/1666209/0362-028x-59\_9\_944.pdf.

Author

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

Examples

## Example: Rosso full model
library(gslnls)
data(growthfull)  # simulated data set.
initial_values = list(Y0=0.04, Ymax=21, MUmax=1.9, lag=5.0) # define the initial values
fit <- gsl_nls(lnN ~ RossoFM(Time, Y0, Ymax, MUmax, lag),
           data=growthfull,
           start =  initial_values)
summary(fit)
#> 
#> Formula: lnN ~ RossoFM(Time, Y0, Ymax, MUmax, lag)
#> 
#> Parameters:
#>       Estimate Std. Error t value Pr(>|t|)    
#> Y0      0.0501     0.2562   0.196    0.849    
#> Ymax    1.8592     0.0600  30.989 1.86e-10 ***
#> MUmax  21.1323     0.2237  94.485 8.45e-15 ***
#> lag     5.0812     0.2447  20.761 6.53e-09 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> Residual standard error: 0.4438 on 9 degrees of freedom
#> 
#> Number of iterations to convergence: 25 
#> Achieved convergence tolerance: 1.55e-12
#>