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Fit Orskov and McDonald model

Source: R/fit_orskov.R
fit_orskov.Rd

Fits the Orskov and McDonald gas-production model to each bottle in a rumen_gp dataset.

Usage

fit_orskov(data, start = NULL)

Arguments

data

A rumen_gp object.

start

Optional list of starting values. May contain any of:

  • VF

  • b

  • k

Value

An orskov_fit object containing:

  • Parameter estimates

  • Model diagnostics

  • Predicted values

  • Residuals

Details

Equation

$$ V(t) = VF + b \left( 1-e^{-kt} \right) $$

where:

  • \(V(t)\) is cumulative gas production at time \(t\)

  • \(VF\) is the intercept (initial gas volume)

  • \(b\) is the fermentable fraction

  • \(k\) is the fractional rate constant

Interpretation

The Orskov and McDonald model partitions gas production into:

  • An intercept term (\(VF\))

  • A fermentable fraction (\(b\))

The asymptotic gas production is:

$$ VF + b $$

The parameter \(k\) controls the rate at which the asymptote is approached.

Advantages

  • Widely used in ruminant nutrition research

  • Parameters have straightforward biological interpretation

  • Stable convergence

  • Useful benchmark model for comparison

Limitations

  • No explicit lag parameter

  • Limited flexibility for highly sigmoidal fermentation profiles

  • Less adaptable than Gompertz, Groot, or Dual Logistic models

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_orskov(
  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)
#> 
#> Orskov and McDonald model summary
#> ---------------------------------
#> Total bottles: 24
#> Successful fits: 24
#> Failed fits: 0
#> Low R-squared (< 0.90): 4
#> 

# Fit using custom starting values
fit_custom_start <- fit_orskov(
  gp,
  start = list(
    VF = 5,
    b = 120,
    k = 0.05
  )
)
#> 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)
#> 
#> Orskov and McDonald model summary
#> ---------------------------------
#> Total bottles: 24
#> Successful fits: 24
#> Failed fits: 0
#> Low R-squared (< 0.90): 5
#>