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
A dataframe containing the following variables.
namemkinmod.timevaluesoilMcCall P, Vrona SA, Kelley SS (1981) Fate of uniformly carbon-14 ring labeled 2,4,5-Trichlorophenoxyacetic acid and 2,4-dichlorophenoxyacetic acid. J Agric Chem 29, 100-107 http://dx.doi.org/10.1021/jf00103a026
SFO_SFO_SFO <- mkinmod(T245 = list(type = "SFO", to = "phenol"), phenol = list(type = "SFO", to = "anisole"), anisole = list(type = "SFO"))#>#> Model cost at call 1 : 13655.2 #> Model cost at call 2 : 13655.2 #> Model cost at call 8 : 9191.59 #> Model cost at call 16 : 5663.584 #> Model cost at call 17 : 5663.582 #> Model cost at call 18 : 5663.566 #> Model cost at call 19 : 5663.55 #> Model cost at call 23 : 3035.567 #> Model cost at call 24 : 3035.566 #> Model cost at call 26 : 3035.561 #> Model cost at call 27 : 3035.559 #> Model cost at call 28 : 3035.558 #> Model cost at call 30 : 2252.97 #> Model cost at call 31 : 2252.965 #> Model cost at call 32 : 2252.965 #> Model cost at call 36 : 2252.958 #> Model cost at call 37 : 1220.201 #> Model cost at call 38 : 1220.2 #> Model cost at call 39 : 1220.199 #> Model cost at call 41 : 1220.183 #> Model cost at call 45 : 507.1358 #> Model cost at call 48 : 507.1353 #> Model cost at call 52 : 198.5695 #> Model cost at call 55 : 198.5694 #> Model cost at call 60 : 175.8239 #> Model cost at call 63 : 175.8239 #> Model cost at call 67 : 170.6316 #> Model cost at call 69 : 170.6316 #> Model cost at call 74 : 165.881 #> Model cost at call 77 : 165.881 #> Model cost at call 81 : 161.6423 #> Model cost at call 84 : 161.6423 #> Model cost at call 88 : 158.2953 #> Model cost at call 91 : 158.2953 #> Model cost at call 95 : 156.7311 #> Model cost at call 97 : 156.731 #> Model cost at call 103 : 155.998 #> Model cost at call 106 : 155.998 #> Model cost at call 110 : 155.6263 #> Model cost at call 113 : 155.6262 #> Model cost at call 116 : 155.6262 #> Model cost at call 117 : 155.1202 #> Model cost at call 120 : 155.1202 #> Model cost at call 124 : 154.4133 #> Model cost at call 125 : 153.8489 #> Model cost at call 126 : 152.7413 #> Model cost at call 129 : 152.7413 #> Model cost at call 132 : 152.7413 #> Model cost at call 133 : 150.3995 #> Model cost at call 134 : 148.7256 #> Model cost at call 135 : 147.2618 #> Model cost at call 137 : 147.2618 #> Model cost at call 139 : 147.2618 #> Model cost at call 142 : 145.115 #> Model cost at call 144 : 145.115 #> Model cost at call 145 : 145.115 #> Model cost at call 146 : 145.115 #> Model cost at call 147 : 145.115 #> Model cost at call 150 : 143.7878 #> Model cost at call 157 : 142.8531 #> Model cost at call 160 : 142.8531 #> Model cost at call 164 : 142.7325 #> Model cost at call 167 : 142.7325 #> Model cost at call 169 : 142.7325 #> Model cost at call 172 : 141.8393 #> Model cost at call 173 : 141.8393 #> Model cost at call 174 : 141.8393 #> Model cost at call 179 : 141.3446 #> Model cost at call 180 : 141.3446 #> Model cost at call 181 : 141.3446 #> Model cost at call 186 : 141.1111 #> Model cost at call 193 : 140.7786 #> Model cost at call 200 : 140.451 #> Model cost at call 207 : 140.1395 #> Model cost at call 214 : 139.7903 #> Model cost at call 221 : 139.5476 #> Model cost at call 228 : 139.4441 #> Model cost at call 235 : 139.3204 #> Model cost at call 242 : 139.2508 #> Model cost at call 249 : 139.1891 #> Model cost at call 256 : 139.1561 #> Model cost at call 263 : 139.137 #> Model cost at call 270 : 139.1278 #> Model cost at call 271 : 139.1278 #> Model cost at call 279 : 139.1211 #> Model cost at call 280 : 139.1211 #> Model cost at call 281 : 139.1211 #> Model cost at call 282 : 139.1211 #> Model cost at call 286 : 139.1179 #> Model cost at call 287 : 139.1179 #> Model cost at call 291 : 139.1179 #> Model cost at call 294 : 139.1179 #> Model cost at call 298 : 139.1158 #> Model cost at call 299 : 139.1158 #> Model cost at call 302 : 139.1158 #> Model cost at call 310 : 139.1148 #> Model cost at call 311 : 139.1148 #> Model cost at call 315 : 139.1148 #> Model cost at call 322 : 139.1143 #> Model cost at call 323 : 139.1143 #> Model cost at call 326 : 139.1143 #> Model cost at call 334 : 139.114 #> Model cost at call 335 : 139.114 #> Model cost at call 338 : 139.114 #> Model cost at call 339 : 139.114 #> Model cost at call 346 : 139.1139 #> Model cost at call 347 : 139.1139 #> Model cost at call 350 : 139.1139 #> Model cost at call 351 : 139.1139 #> Model cost at call 358 : 139.1139 #> Model cost at call 359 : 139.1139 #> Model cost at call 362 : 139.1139 #> Model cost at call 363 : 139.1139 #> Model cost at call 370 : 139.1138 #> Model cost at call 382 : 139.1138 #> Model cost at call 390 : 139.1138 #> Model cost at call 395 : 139.1138 #> Model cost at call 403 : 139.1138 #> Model cost at call 408 : 139.1138 #> Model cost at call 416 : 139.1138 #> Model cost at call 421 : 139.1138 #> Model cost at call 429 : 139.1138 #> Model cost at call 434 : 139.1138 #> Model cost at call 442 : 139.1138 #> Model cost at call 447 : 139.1138 #> Model cost at call 455 : 139.1138 #> Model cost at call 460 : 139.1138 #> Model cost at call 468 : 139.1138 #> Model cost at call 473 : 139.1138 #> Model cost at call 481 : 139.1138 #> Model cost at call 486 : 139.1138 #> Model cost at call 494 : 139.1138 #> Model cost at call 499 : 139.1138 #> Model cost at call 507 : 139.1138 #> Model cost at call 512 : 139.1138 #> Model cost at call 519 : 139.1138 #> Model cost at call 520 : 139.1138 #> Model cost at call 525 : 139.1138 #> Model cost at call 538 : 139.1138 #> Model cost at call 545 : 139.1138 #> Model cost at call 546 : 139.1138 #> Model cost at call 551 : 139.1138 #> Model cost at call 558 : 139.1138 #> Model cost at call 559 : 139.1138 #> Model cost at call 564 : 139.1138 #> Model cost at call 571 : 139.1138 #> Model cost at call 580 : 139.1138 #> Model cost at call 588 : 139.1138#> Warning: Optimisation by method Port did not converge. #> Convergence code is 1summary(fit.1, data = FALSE)#> mkin version: 0.9.44.9000 #> R version: 3.3.2 #> Date of fit: Fri Nov 18 15:19:33 2016 #> Date of summary: Fri Nov 18 15:19:33 2016 #> #> #> Warning: Optimisation by method Port did not converge. #> Convergence code is 1 #> #> #> Equations: #> d_T245/dt = - k_T245_sink * T245 - k_T245_phenol * T245 #> d_phenol/dt = + k_T245_phenol * T245 - k_phenol_sink * phenol - #> k_phenol_anisole * phenol #> d_anisole/dt = + k_phenol_anisole * phenol - k_anisole_sink * anisole #> #> Model predictions using solution type deSolve #> #> Fitted with method Port using 590 model solutions performed in 3.45 s #> #> Weighting: none #> #> Starting values for parameters to be optimised: #> value type #> T245_0 100.9000 state #> k_T245_sink 0.1000 deparm #> k_T245_phenol 0.1001 deparm #> k_phenol_sink 0.1002 deparm #> k_phenol_anisole 0.1003 deparm #> k_anisole_sink 0.1004 deparm #> #> Starting values for the transformed parameters actually optimised: #> value lower upper #> T245_0 100.900000 -Inf Inf #> log_k_T245_sink -2.302585 -Inf Inf #> log_k_T245_phenol -2.301586 -Inf Inf #> log_k_phenol_sink -2.300587 -Inf Inf #> log_k_phenol_anisole -2.299590 -Inf Inf #> log_k_anisole_sink -2.298593 -Inf Inf #> #> Fixed parameter values: #> value type #> phenol_0 0 state #> anisole_0 0 state #> #> Optimised, transformed parameters with symmetric confidence intervals: #> Estimate Std. Error Lower Upper #> T245_0 103.9000 NA NA NA #> log_k_T245_sink -4.1130 NA NA NA #> log_k_T245_phenol -3.6120 NA NA NA #> log_k_phenol_sink -26.3900 NA NA NA #> log_k_phenol_anisole -0.9037 NA NA NA #> log_k_anisole_sink -5.0090 NA NA NA #> #> Parameter correlation:#> Warning: Could not estimate covariance matrix; singular system:#> Could not estimate covariance matrix; singular system: #> #> Residual standard error: 2.78 on 18 degrees of freedom #> #> Backtransformed parameters: #> Confidence intervals for internally transformed parameters are asymmetric. #> t-test (unrealistically) based on the assumption of normal distribution #> for estimators of untransformed parameters. #> Estimate t value Pr(>t) Lower Upper #> T245_0 1.039e+02 4.282e+01 7.236e-20 NA NA #> k_T245_sink 1.636e-02 8.901e-01 1.926e-01 NA NA #> k_T245_phenol 2.701e-02 1.504e+00 7.498e-02 NA NA #> k_phenol_sink 3.457e-12 1.230e-11 5.000e-01 NA NA #> k_phenol_anisole 4.051e-01 2.518e+00 1.075e-02 NA NA #> k_anisole_sink 6.679e-03 8.146e+00 9.469e-08 NA NA #> #> Chi2 error levels in percent: #> err.min n.optim df #> All data 10.070 6 16 #> T245 7.908 3 5 #> phenol 106.445 2 5 #> anisole 5.379 1 6 #> #> Resulting formation fractions: #> ff #> T245_sink 3.772e-01 #> T245_phenol 6.228e-01 #> phenol_sink 8.534e-12 #> phenol_anisole 1.000e+00 #> anisole_sink 1.000e+00 #> #> Estimated disappearance times: #> DT50 DT90 #> T245 15.982 53.091 #> phenol 1.711 5.685 #> anisole 103.784 344.763# No covariance matrix and k_phenol_sink is really small, therefore fix it to zero fit.2 <- mkinfit(SFO_SFO_SFO, subset(mccall81_245T, soil == "Commerce"), parms.ini = c(k_phenol_sink = 0), fixed_parms = "k_phenol_sink", quiet = TRUE) summary(fit.2, data = FALSE)#> mkin version: 0.9.44.9000 #> R version: 3.3.2 #> Date of fit: Fri Nov 18 15:19:35 2016 #> Date of summary: Fri Nov 18 15:19:35 2016 #> #> Equations: #> d_T245/dt = - k_T245_sink * T245 - k_T245_phenol * T245 #> d_phenol/dt = + k_T245_phenol * T245 - k_phenol_sink * phenol - #> k_phenol_anisole * phenol #> d_anisole/dt = + k_phenol_anisole * phenol - k_anisole_sink * anisole #> #> Model predictions using solution type deSolve #> #> Fitted with method Port using 246 model solutions performed in 1.477 s #> #> Weighting: none #> #> Starting values for parameters to be optimised: #> value type #> T245_0 100.9000 state #> k_T245_sink 0.1000 deparm #> k_T245_phenol 0.1001 deparm #> k_phenol_anisole 0.1002 deparm #> k_anisole_sink 0.1003 deparm #> #> Starting values for the transformed parameters actually optimised: #> value lower upper #> T245_0 100.900000 -Inf Inf #> log_k_T245_sink -2.302585 -Inf Inf #> log_k_T245_phenol -2.301586 -Inf Inf #> log_k_phenol_anisole -2.300587 -Inf Inf #> log_k_anisole_sink -2.299590 -Inf Inf #> #> Fixed parameter values: #> value type #> phenol_0 0 state #> anisole_0 0 state #> k_phenol_sink 0 deparm #> #> Optimised, transformed parameters with symmetric confidence intervals: #> Estimate Std. Error Lower Upper #> T245_0 103.9000 2.35200 98.930 108.8000 #> log_k_T245_sink -4.1130 0.13250 -4.390 -3.8350 #> log_k_T245_phenol -3.6120 0.05002 -3.716 -3.5070 #> log_k_phenol_anisole -0.9037 0.30580 -1.544 -0.2637 #> log_k_anisole_sink -5.0090 0.11180 -5.243 -4.7750 #> #> Parameter correlation: #> T245_0 log_k_T245_sink log_k_T245_phenol #> T245_0 1.00000 0.63761 -0.1742 #> log_k_T245_sink 0.63761 1.00000 -0.3831 #> log_k_T245_phenol -0.17416 -0.38313 1.0000 #> log_k_phenol_anisole -0.05948 0.08745 -0.3047 #> log_k_anisole_sink -0.16208 -0.60469 0.5227 #> log_k_phenol_anisole log_k_anisole_sink #> T245_0 -0.05948 -0.1621 #> log_k_T245_sink 0.08745 -0.6047 #> log_k_T245_phenol -0.30470 0.5227 #> log_k_phenol_anisole 1.00000 -0.1774 #> log_k_anisole_sink -0.17744 1.0000 #> #> Residual standard error: 2.706 on 19 degrees of freedom #> #> Backtransformed parameters: #> Confidence intervals for internally transformed parameters are asymmetric. #> t-test (unrealistically) based on the assumption of normal distribution #> for estimators of untransformed parameters. #> Estimate t value Pr(>t) Lower Upper #> T245_0 1.039e+02 44.160 6.462e-21 98.930000 108.80000 #> k_T245_sink 1.636e-02 7.545 1.978e-07 0.012400 0.02159 #> k_T245_phenol 2.701e-02 19.990 1.607e-14 0.024320 0.02999 #> k_phenol_anisole 4.051e-01 3.270 2.014e-03 0.213600 0.76820 #> k_anisole_sink 6.679e-03 8.942 1.544e-08 0.005285 0.00844 #> #> Chi2 error levels in percent: #> err.min n.optim df #> All data 9.831 5 17 #> T245 7.908 3 5 #> phenol 99.808 1 6 #> anisole 5.379 1 6 #> #> Resulting formation fractions: #> ff #> T245_sink 0.3772 #> T245_phenol 0.6228 #> phenol_anisole 1.0000 #> phenol_sink 0.0000 #> anisole_sink 1.0000 #> #> Estimated disappearance times: #> DT50 DT90 #> T245 15.982 53.091 #> phenol 1.711 5.685 #> anisole 103.784 344.763