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Predict microbial growth under dynamic environmental conditions

Source: R/dynamic_growth.R
predict_dynamic_growth.Rd

predict_dynamic_growth() solves a differential Huang-type growth model over a time-varying environmental profile. It is intended for forward prediction under dynamic temperature conditions and uses an internal fourth-order Runge-Kutta solver.

Usage

predict_dynamic_growth(
  profile,
  model = "huang",
  secondary = "huang_sqrt",
  start,
  times = NULL,
  scale = c("log10", "ln"),
  dt = 0.01,
  method = "rk4",
  temperature = "temperature"
)

Arguments

profile

A dynamic_profile() object or data frame with a time column and an environmental variable, usually temperature.

model

Character string. Currently only "huang" is supported.

secondary

Character string defining the secondary model for the growth rate. One of "huang_sqrt", "huang_full_sqrt", or "constant".

start

Named list of parameters. Use logN0 and logNmax for base-10 input, or Y0 and Ymax for natural-log input. For secondary = "huang_sqrt", supply a and Tmin. For secondary = "huang_full_sqrt", also supply b and Tmax. For secondary = "constant", supply MUmax.

times

Optional numeric vector of output times. If NULL, a regular sequence covering the profile is created from dt.

scale

Scale of the returned response column. One of "log10" or "ln".

dt

Maximum integration step used by the internal RK4 solver.

method

Solver method. Currently only "rk4" is implemented.

temperature

Name of the temperature column in profile.

Value

A predmicror_dynamic_prediction data frame with time, prediction, lnN, logN, temperature, and metadata attributes.

Examples

profile <- dynamic_profile(
  time = c(0, 5, 10, 15, 20),
  temperature = c(10, 4, 15, 15, 10)
)
pred <- predict_dynamic_growth(
  profile = profile,
  start = list(logN0 = 2, logNmax = 8.8, a = 0.0886, Tmin = 8.91, lag = 2),
  dt = 0.25
)
head(pred)
#> dynamic_growth prediction
#>   model: huang
#>   secondary: huang_sqrt
#>   rows: 6
#>   time response      lnN     logN temperature
#> 1 0.00 2.000000 4.605170 2.000000        10.0
#> 2 0.25 2.000000 4.605171 2.000000         9.7
#> 3 0.50 2.000001 4.605173 2.000001         9.4
#> 4 0.75 2.000002 4.605174 2.000002         9.1
#> 5 1.00 2.000002 4.605174 2.000002         8.8
#> 6 1.25 2.000002 4.605174 2.000002         8.5