Fit Groot model — fit_groot • rumenGP

Fits the Groot gas production model to each bottle in a rumen_gp dataset.

Usage

fit_groot(data, start = NULL)

Arguments

data

A rumen_gp object.

start

Optional list of starting values. May contain any of:

VF
b
k

Value

A groot_fit object containing:

Parameter estimates
Model diagnostics
Predicted values
Residuals

Details

Equation

$$ V(t) = \frac{VF} { 1+\left(\frac{b}{t}\right)^k } $$

where:

$V(t)$ is cumulative gas production at time $t$
$VF$ is asymptotic gas production
$b$ is the half-time parameter
$k$ is the shape parameter

Interpretation

The Groot model is a flexible sigmoidal model widely used in rumen gas production studies.

The parameter $b$ represents the time required to reach approximately half of the asymptotic gas production, while $k$ controls curve shape and steepness.

Advantages

Excellent flexibility
Biologically interpretable parameters
Often produces excellent fits
Widely used in rumen fermentation studies

Limitations

Requires positive incubation times
Shape parameter may be less intuitive than simple exponential models

Notes

The Groot model is mathematically equivalent to the generalized Michaelis-Menten model implemented in fit_mm().

Parameter correspondence:

VF = A
b = K
k = c

Both formulations produce identical fitted values, residuals, diagnostics, AIC, BIC, RMSE, and R-squared when convergence is achieved.

Researchers may choose either formulation according to the terminology commonly used in their field.

Examples



files <- example_data()

raw_data <- read_ankom(
  files$ankom
)

metadata <- read_metadata(
  files$metadata
)

gp <- process_ankom(
  raw_data,
  metadata,
  headspace_ml = 210,
  temperature_c = 39
)

# Fit using package default starting values
fit_default <- fit_groot(
  gp
)
#> Warning: Large negative pressure values detected. Minimum PSI = -1.274 . Please inspect the affected bottles.
#> rumenGP data validation passed.
#> Observations: 1752
#> Heads: 24
#> Treatments: 5

summary(fit_default)
#> 
#> Groot model summary
#> -------------------
#> Total bottles: 24
#> Successful fits: 23
#> Failed fits: 1
#> Low R-squared (< 0.90): 2
#> 

# Fit using custom starting values
fit_custom_start <- fit_groot(
  gp,
  start = list(
    VF = 120,
    b = 10,
    k = 2
  )
)
#> Warning: Large negative pressure values detected. Minimum PSI = -1.274 . Please inspect the affected bottles.
#> rumenGP data validation passed.
#> Observations: 1752
#> Heads: 24
#> Treatments: 5

summary(fit_custom_start)
#> 
#> Groot model summary
#> -------------------
#> Total bottles: 24
#> Successful fits: 24
#> Failed fits: 0
#> Low R-squared (< 0.90): 3
#>