Time course of 2,4,5-trichlorophenoxyacetic acid, and the corresponding 2,4,5-trichlorophenol and 2,4,5-trichloroanisole as recovered in diethylether extracts.

mccall81_245T

Format

A dataframe containing the following variables.

name

the name of the compound observed. Note that T245 is used as an acronym for 2,4,5-T. T245 is a legitimate object name in R, which is necessary for specifying models using mkinmod.

time

a numeric vector containing sampling times in days after treatment

value

a numeric vector containing concentrations in percent of applied radioactivity

soil

a factor containing the name of the soil

Source

McCall P, Vrona SA, Kelley SS (1981) Fate of uniformly carbon-14 ring labelled 2,4,5-Trichlorophenoxyacetic acid and 2,4-dichlorophenoxyacetic acid. J Agric Chem 29, 100-107 doi:10.1021/jf00103a026

Examples

  SFO_SFO_SFO <- mkinmod(T245 = list(type = "SFO", to = "phenol"),
    phenol = list(type = "SFO", to = "anisole"),
    anisole = list(type = "SFO"))
#> Temporary DLL for differentials generated and loaded
  # \dontrun{
    fit.1 <- mkinfit(SFO_SFO_SFO, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
    summary(fit.1)$bpar
#>                         Estimate   se_notrans   t value       Pr(>t)
#> T245_0              1.038550e+02 2.1847074943 47.537272 4.472189e-18
#> k_T245              4.337042e-02 0.0018983965 22.845818 2.276911e-13
#> k_phenol            4.050581e-01 0.2986993738  1.356073 9.756990e-02
#> k_anisole           6.678742e-03 0.0008021439  8.326114 2.623177e-07
#> f_T245_to_phenol    6.227599e-01 0.3985340721  1.562626 6.949414e-02
#> f_phenol_to_anisole 1.000000e+00 0.6718440131  1.488441 7.867790e-02
#> sigma               2.514628e+00 0.4907558973  5.123989 6.233159e-05
#>                            Lower        Upper
#> T245_0              99.246061490 1.084640e+02
#> k_T245               0.039631621 4.746194e-02
#> k_phenol             0.218013879 7.525762e-01
#> k_anisole            0.005370739 8.305299e-03
#> f_T245_to_phenol     0.547559080 6.924813e-01
#> f_phenol_to_anisole  0.000000000 1.000000e+00
#> sigma                1.706607296 3.322649e+00
    endpoints(fit.1)
#> $ff
#>    T245_phenol      T245_sink phenol_anisole    phenol_sink 
#>   6.227599e-01   3.772401e-01   1.000000e+00   3.072478e-10 
#> 
#> $distimes
#>               DT50      DT90
#> T245     15.982025  53.09114
#> phenol    1.711229   5.68458
#> anisole 103.784093 344.76329
#> 
    # formation fraction from phenol to anisol is practically 1. As we cannot
    # fix formation fractions when using the ilr transformation, we can turn of
    # the sink in the model generation
    SFO_SFO_SFO_2 <- mkinmod(T245 = list(type = "SFO", to = "phenol"),
      phenol = list(type = "SFO", to = "anisole", sink = FALSE),
      anisole = list(type = "SFO"))
#> Temporary DLL for differentials generated and loaded
    fit.2 <- mkinfit(SFO_SFO_SFO_2, subset(mccall81_245T, soil == "Commerce"),
      quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
    summary(fit.2)$bpar
#>                      Estimate   se_notrans   t value       Pr(>t)        Lower
#> T245_0           1.038550e+02 2.1623653059 48.028439 4.993108e-19 99.271020328
#> k_T245           4.337042e-02 0.0018343666 23.643268 3.573556e-14  0.039650976
#> k_phenol         4.050582e-01 0.1177237651  3.440752 1.679255e-03  0.218746589
#> k_anisole        6.678742e-03 0.0006829745  9.778903 1.872894e-08  0.005377083
#> f_T245_to_phenol 6.227599e-01 0.0342197873 18.198824 2.039411e-12  0.547975634
#> sigma            2.514628e+00 0.3790944250  6.633250 2.875782e-06  1.710983655
#>                         Upper
#> T245_0           108.43904079
#> k_T245             0.04743877
#> k_phenol           0.75005593
#> k_anisole          0.00829550
#> f_T245_to_phenol   0.69212307
#> sigma              3.31827222
    endpoints(fit.1)
#> $ff
#>    T245_phenol      T245_sink phenol_anisole    phenol_sink 
#>   6.227599e-01   3.772401e-01   1.000000e+00   3.072478e-10 
#> 
#> $distimes
#>               DT50      DT90
#> T245     15.982025  53.09114
#> phenol    1.711229   5.68458
#> anisole 103.784093 344.76329
#> 
    plot_sep(fit.2)

  # }