Master Thesis

P-release kinetic as a predictor for P-availability in the STYCS Trials

Marc Jerónimo Pérez y Ropero

Introduction

  • In my Internship I studied the current GRUD, particularly Mg, P and K

  • Fertilizer requirement models imply \(Y\sim STP + Clay\) & \(P-\text{Export}\sim STP + Clay\)

  • Currently only stationary measurement of STP are considered

  • Could a kinetic desorption-model better explain the soil status and yield data?

    GRUD 2017

Experimental Setup

  • LTE STYCS, all treatment conditions equal except P-fertilization, which is in 6 Levels, 3 were considered(\(P0\),\(P100\),\(P166\))
  • 5 Sites regarded; Cadenazzo, Ellighausen, Rümlang-Altwi, Oensingen, Zürich-Reckenholz
  • 5 Sites, 4 blocks per site, 6 Treatment-Levels, 4 Repetitions
  • Years 2017-2022 were observed, kinetic data was collected for year 2022 and used to predict 2017-2022
  • kinetic data worth one year vs STP worth 6 years to predict the same data-set

Kinetic Model

Flossmann & Richter conducted in 1982 experiments that should:

  • improve the classification of P-supply in soils
  • work in tandem with a current STP-method e.g. CAL or Olsen

The net-desorption was observed, a kinetic of first order was assumed: \[\frac{dP}{dt}=k\times(P^S-P)\] When solved with \(P(0)=0\), the following equation was obtained: \[P(t)=P^S\times(1-e^{-kt})\] The researchers estimated the plateau \(P^S=P_\text{CAL/Olsen}-P_{H_2O}\) and linearized as follows: \[log(1-\frac{P(t)}{P^S})=-kt\] \(PS\), \(k\) and \(k*PS\) were extracted, \(k*PS\) being the average net-release speed.

Kinetic-Experiment Setup

Could a kinetic desorption-model better explain the soil status and yield data?

Relevant Variables

Soil Variables:

  • \(P-CO_2\) & \(P-AAE10\) stand for the GRUD STP-measurements in [\(g~P/kg ~ Soil\)]
  • \(k\)(\(s^{-1}\)) can be interpreted as the relative speed of net-desorption of orthophosphate
  • \(k*PS\)(\(g~Ps^{-1}\)) can be interpreted as the average net-release speed
  • \(PS\)(\(mg~P/L~H_2O\)) is the equilibrium concentration of \(PO_4^{3-}\) of the net-desorption experiment
  • From the 0-20cm Horizon: Clay-, Silt-,\(C_{org}\)-content and pH

Yield Variables:

  • For a year \(X\) and crop \(C\) \(Y_{main-rel}\) stands for \(Y_{main-rel}:=Y_C^{X}/mean(Y_C~\text{in year}~X~\text{in CH})\)
  • For every year:site:crop combination the yield was normalised using: \(Y_\text{norm}:=Y/median(Y_{P166})\)
  • The P-Export was calculated as the P-Uptake of the main product
  • The P-Balance was calculated as the difference \(P_{Fertilized}-\text{P-Export}\)

Research Questions

  • I: Is the method presented by Flossmann and Richter (1982) with the double extraction replicable with the soils from the STYCS-trial?
  • II: How do GRUD-measurements of STP correlate to the soil properties \(C_\text{org}\)-content, clay-content, silt-content and pH?
  • III: Are the kinetic coefficients \(k\) and \(PS\) correlated to soil properties?
  • IV: How well can current GRUD methods of STP (\(P-CO_2\) & \(P-AAE10\)) predict the Yield-parameters, P-Export and P-Balance?
  • V: How well can the kinetic parameters \(k\) & \(PS\) predict Yield-parameters, P-Export and P-Balance?

QI: Replicability of kinetic model in STYCS

Observation

  • The estimation \(PS=P_{Olsen}-P_{H_2O}\) did not deliver reasonable and significant models in terms of residuals and significance

QII & III: STP, k & PS correlate to soil properties?

The following random structure was chosen:

(1|year) + (1|Site) + (1|Site:block) + (Treatment|Site)

Do P-CO2, P_AAE10, k and PS correlate with soil characteristics?

Coefficient Table for Soil Covariates. Significant codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
Covariate PS k log(k*PS) k*log(PS) CO2 AAE10
(Intercept) ***-3.807 -0.130 ***-6.108 -0.216 * -2.034 -0.419
soil_0_20_clay 0.018 -0.004 -0.006 * 0.014 0.002 0.012
soil_0_20_Corg ** 0.507 -0.007 0.128 0.077 * 0.364 ** 0.502
soil_0_20_pH_H2O 0.021 ** 0.033 * 0.191 -0.066 * 0.141 ***0.323
soil_0_20_silt -0.013 * 0.007 0.018 -0.013 -0.017 -0.004
R2m 0.074 0.356 0.024 0.238 0.035 0.091
R2c 0.955 0.704 0.917 0.867 0.931 0.931

Observation

  • P-CO2 and P-AAE10 did not correlate with clay-content
  • k does not correlate with Treatment but with pH and silt-content
  • \(k*log(PS)\) had significant effects for clay- and silt-content as well as pH, but lower in Treatment
  • PS was the covariate best predicted by soil properties: \(R^2_m=0.858\)

QIV & V: Correlation k, PS & STP to Yield and P-metrics

Yield model summary:

Coefficient Table for Yield Variables. Significant codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
Covariate Yn-STP-CO2 Yn-STP-AAE10 Yn-STP-GRUD Yn-Kinetic Yr-STP-CO2 Yr-STP-AAE10 Yr-STP-GRUD Yr-Kinetic
(Intercept) ***1.059 ***0.532 ***1.096 0.980 ***104.862 ***75.343 ***108.494 56.375
k 2.262 ** 377.498
k:log(PS) 0.931 ** 171.507
log(PS) -0.063 * -27.486
log(soil_0_20_P_AAE10) ***0.120 -0.006 ** 7.111 -0.933
log(soil_0_20_P_CO2) ***0.162 0.137 ** 8.853 * 9.692
log(soil_0_20_P_CO2):log(soil_0_20_P_AAE10) 0.016
R2m 0.218 0.198 0.220 0.014 0.074 0.063 0.073 0.022
R2c 0.358 0.474 0.365 0.360 0.569 0.537 0.577 0.439

Observation

  • \(k*log(PS)\) and \(k\) showed the strongest effects in the prediction of Ynorm and Yrel
  • P-AAE10 did show a significant effect in prediction of Yrel

P-Export model summary:

Coefficient Table for P-export. Significant codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
Covariate CO2_Pexport AAE10_Pexport Grud_Pexport Kin_Pexport
(Intercept) ***27.522 8.090 ** 24.726 ***29.599
k 22.622
k:log(PS) 11.928
log(PS) 1.954
log(soil_0_20_P_AAE10) ***4.824 0.724
log(soil_0_20_P_CO2) ***5.177 * 4.563
R2m 0.064 0.073 0.066 0.064
R2c 0.625 0.603 0.621 0.648

Observations

  • P-CO2 did show strong effects in predicting Pexport

P-balance model summary:

Coefficient Table for P-balance. Significant codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
Covariate CO2_Pbalance AAE10_Pbalance Grud_Pbalance Kin_Pbalance
(Intercept) 4.441 7.691 6.575 ***43.833
k 84.993
k:log(PS) 33.029
log(PS) ***16.947
log(soil_0_20_P_AAE10) -0.794 -0.546
log(soil_0_20_P_CO2) -0.928 -0.430
R2m 0.001 0.001 0.001 0.572
R2c 0.810 0.807 0.810 0.744

Observation

  • \(PS\) showed the strongest effect in predicting P_balance and k showed substantial \(R^2_m\)

Concluding Remarcs

  • The net-desorption of P probably follows a first-order-kinetic, but \(PS\) is difficult to directly estimate.
  • The kinetic parameters \(k\) and \(PS\) could comparably and sometimes better explain Ynorm, Yrel and P-Balance.
  • Regarding the difference between \(R^2_m\) and \(R^2_C\) confounded effects seem to be buried in the sites.
  • P-CO2 and P-AAE10 are not as well explainable as \(PS\) and \(k\), in particular not by clay-content.
  • P-CO2 correlated however significantly with P-Export

Thank you for your attention