scholarly journals Sorption capacity of phosphate in mineral soils: II Dependence of sorption capacity on soil properties

1990 ◽  
Vol 62 (1) ◽  
pp. 9-15
Author(s):  
Raina Niskanen
Keyword(s):  
Soil Properties ◽  
Sorption Capacity ◽  
Mineral Soil ◽  
Clay Content ◽  
Organic C ◽  
Phosphate Sorption ◽  
P Sorption ◽  
P Sorption Capacity ◽  
Mineral Soils ◽  
Extractable Al

The dependence of the indicator of phosphate sorption capacity on extractable Al and Fe and other soil properties was studied in a material consisting of 102 mineral soil samples. The sum of P adsorbed on soil during two days from a solution containing P 5 mmol/l and P extracted by 0.02 M EDTA (pH 5.3) as an estimate of the initial P content in the soil was used as the indicator of P sorption capacity. In clay and silt soils (n = 51), the Al and Fe extracted by 0.05 M oxalate (pH 2.9) together with the organic C content explained 85 %, the Al and Fe extracted by 0.05 M K4P2O7 (pH 10) together with the clay content 87 %, the Al and Fe extracted by 0.02 M EDTA (pH 5.3) 91 %, and the Al extracted by 1 M CH3COONH4 (pH 4.8) together with the organic C and clay contents 78 % of the variation of the indicator of phosphate sorption capacity. In coarse soils (n = 51), the variation of the indicator was explained well only by oxalate-extractable metals, which together with soil pH and clay content explained 80 % of the variation. Extractable Al was generally the most important explainer of variation. The results suggest that forms of extractable Al and Fe explaining the variation of the indicator of P sorption capacity in clay and silt soils are partially different from those in coarse soils.

Phosphorus auditing cannot account for all of the phosphorus applied to different pasture soils

Soil Research ◽  
2004 ◽  
Vol 42 (1) ◽  
pp. 89 ◽  
Author(s):  
L. L. Burkitt ◽  
C. J. P. Gourley ◽  
P. W. G. Sale
Keyword(s):  
Soil Properties ◽  
Sorption Capacity ◽  
Vertical Movement ◽  
Single Application ◽  
Macropore Flow ◽  
P Sorption ◽  
P Sorption Capacity ◽  
Sampling Zone ◽  
P Movement ◽  
Total P

Five field sites established in the high rainfall zone of southern Victoria were used to examine the downwards vertical movement of phosphorus (P) fertiliser on soils which ranged in P sorption capacity. Fertiliser was applied either as a single application of 280 kg P/ha at the beginning of the experiment (April 1998), or as 35�kg�P/ha reapplied every 6 months (totalling 210 kg P/ha by the end of the third year). Soil cores were sampled in June 2001 to a depth of 40 cm, and soil at depths of 0–5, 5–10, 10–20, 20–30, and 30–40 cm was analysed for a range of soil properties and total P concentration.Total P concentration changed very little down the profile, indicating that there was minimal vertical movement of P fertiliser below the 10 cm layer of 5 pasture soils following the single application of 280 kg P/ha or 35 kg P/ha reapplied every 6 months. Soils with low to moderate surface P sorption capacity showed a trend for higher total P concentrations at depth. However, quantitative relationships between vertical P movement and soil properties at depth were poor. A P audit resulted in variable recovery of the applied P (45–128%) in the surface 40 cm at each of the 5 sites. Consistently low P recoveries were achieved at one site, where the surface soil had a high P sorption capacity. Some applied P may have bypassed the high P sorbing surface layers at this site through macropore flow and moved beyond the 40 cm sampling zone, or have been lost to surface runoff. These results question the usefulness of P audit or mass-balance methods for accounting for P movement in a pasture-based system, as spatial heterogeneity of soil properties, both horizontally and vertically, was high in the current study.

Solubility and retention of phosphate in soils of the northwestern Canadian prairie

1991 ◽  
Vol 71 (4) ◽  
pp. 453-463 ◽  
Author(s):  
Y. K. Soon
Keyword(s):  
Organic Matter ◽  
Sorption Capacity ◽  
Agricultural Soils ◽  
Clay Content ◽  
Phosphorus Concentration ◽  
Canadian Prairie ◽  
P Sorption ◽  
P Sorption Capacity ◽  
P Concentration ◽  
Order Of Magnitude

Phosphate solubility and sorption characteristics of 39 agricultural soils in the northwestern Canadian Prairie were studied to gain insights into the retention of fertilizer P added to soil. The soils were mostly acidic with base saturation of 59–95%. The solubility of P as determined by the equilibrium P concentration and phosphoric acid potential was low and appeared to be controlled by sorption of phosphate by soil components. The mean equilibrium solution P concentration was 0.03 mg L−1. Phosphorus concentration in saturation extracts was about one order of magnitude higher, but would have included organic and colloidal P since P analysis in these extracts was done by ICP. Sorption capacity of P as determined by Langmuir isotherm was greater for the Dark Gray and Black soils and gleysols, i.e., soils with higher amounts of organic matter, than the Gray Luvisolic and Solodic soils by about 30%. Partial correlation showed that clay content, Al-organic matter complexes (AlOM) and amorphous iron oxide (FeOX) were significantly correlated with P sorption capacity. When both topsoils and subsoils were considered, clay content was the most important soil property influencing P sorption capacity, followed by AlOM and FeOX (standard partial regression coefficients, b′, of 0.47, 0.39 and 0.38, respectively). When only topsoils were considered, AlOM and FeOX became more important than clay content in influencing P sorption (b′ = 0.47, 0.47, and 0.33, respectively). Native P, estimated by oxalate and anion-resin extractions, was associated with the hydrous iron oxides only, although soil pH also affected the resin-extractable P fraction. Key words: P retention, solubility, Luvisols, solodic soils

scholarly journals Sorption capacity of phosphate in mineral soils: I Estimation of sorption capacity by means of sorption isotherms

1990 ◽  
Vol 62 (1) ◽  
pp. 1-8
Author(s):  
Raina Niskanen
Keyword(s):  
Ionic Strength ◽  
Sorption Capacity ◽  
Sorption Isotherms ◽  
Clay Content ◽  
Langmuir Equation ◽  
Soil Samples ◽  
Organic Carbon Content ◽  
Sorption Data ◽  
Mineral Soils ◽  
Extractable Al

The sorption capacity of phosphate in seven soil samples (clay content 1—70 %, organic carbon content 0.8—10.7 %, soil pH 4.2—5.3, oxalate-extractable Al 11—222 and Fe 11—202 mmol/kg soil) was studied by means of sorption isotherms. The soils were equilibrated, for two to seven days at +5 and +20°C, with solutions containing phosphate 0—10 mmol/l (0—200 mmol/kg soil) at a constant ionic strength of 0.01 . Prolongation of the reaction time increased the sorption of phosphate only partially. The rise in temperature, from +5 to +20°C, increased the sorption from higher phosphate concentrations. At +20°C, the sorption curves of three soils showed a sorption maximum of 4, 19 and 34 mmol/kg soil. The sorption data of six soils was in accordance with the Langmuir equation; the sorption maximum ranged from 15 to 119 mmol/kg soil, and were of the same magnitude as the maximums determined experimentally.

Extractable iron and aluminium predict the P sorption capacity of Thai soils

Soil Research ◽  
2005 ◽  
Vol 43 (6) ◽  
pp. 757 ◽  
Author(s):  
W. Wiriyakitnateekul ◽  
A. Suddhiprakarn ◽  
I. Kheuruenromne ◽  
R. J. Gilkes
Keyword(s):  
Sorption Capacity ◽  
Stepwise Regression ◽  
Clay Content ◽  
Langmuir Equation ◽  
Soil Types ◽  
Sorption Data ◽  
P Sorption ◽  
P Sorption Capacity ◽  
Freundlich Equation ◽  
Extractable Iron

The objective of this study was to determine if dithionite- and oxalate-extractable Fe and Al can be used to predict the P sorption capacity of Thai soils. Forty-five samples from diverse soil types were taken from surface and subsurface horizons of soils on sandstone, shale/limestone, granite, and basalt. The samples were analysed for P sorption, dithionite- and oxalate-extractable Fe and Al (Fed, Feo, Ald, Alo), specific surface area (SSA), and other soil properties. Generally P sorption data for these soils were slightly better fitted by the Langmuir equation than the Freundlich equation. The Langmuir P sorption maximum ranged from 35 to 1111 μg/g with a median value of 370 μg/g soil. Soils developed on basalt had higher values of P sorption maximum (xm) (range 400–1111 μg/g, median 597 μg/g) than soils on other parent materials. Fed concentrations in soils (4–74 g/kg) were much higher than Feo concentrations (0.2–13.8 g/kg) with values of Feo/Fed ranging from 0.01 to 0.28 (median 0.09), indicating that most of the free iron oxides were crystalline. Amounts of Ald and Alo were about equal with median values of 1.6 and 1.0 g/kg, respectively. About 80% of the samples had SSA values <40 m2/g. Both the P sorption maximum and Freundlich k were linearly related to SSA (R2 = 0.77, 0.74), Ald (R2 = 0.78, 0.79), Alo (R2 = 0.64, 0.74), Fed (R2 = 0.48, 0.41), Feo (R2 = 0.43, 0.72), and clay content (R2 = 0.48, 0.36). Stepwise regression indicated that 81% of the variability in P sorption by these soils could be explained by a combination of dithionite and oxalate Fe and Al, however, Ald alone is almost as effective in predicting the P sorption capacity of Thai soils.

Relationships between extractable Al, selected soil properties, pH buffer capacity and lime requirement in some acidic Queensland soils

Soil Research ◽  
1992 ◽  
Vol 30 (2) ◽  
pp. 119 ◽  
Author(s):  
RL Aitken
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Soil Properties ◽  
Buffer Capacity ◽  
Clay Content ◽  
Ph Buffering ◽  
Ph Buffer ◽  
Mineral Soils ◽  
Chloride Salts ◽  
Hydrolysis Of

The objectives of this study were to examine (1) interrelationships between various forms of extractable A1 and selected soil properties, (2) the contribution of extractable A1 to pH buffer capacity, and (3) investigate the use of extractable A1 to predict lime requirement. Aluminium was extracted from each of 60 Queensland soils with a range of chloride salts: 1 M KCl (AlK), 0.5 M CuCl2 (AlCu), 0.33 M LaCl3 (AlLa) and 0.01 M CaCl2 (AlCa). The amounts of A1 extracted were in the order AlCu > AlLa > Alk > AlCa. Little or no A1 was extracted by KC1 or Lac13 in soils with pHw values greater than 5.5 , whereas CuCl2 extracted some A1 irrespective of soil pH. The greater amounts of A1 extracted by CuCl2 were attributed mainly to A1 from organic matter, even though all of the soils were mineral soils (organic carbon 54.7%). Both AlCu and AlLa, were significantly (P < 0.001) correlated with organic carbon, whereas none of the extractable A1 measures was correlated with clay content. AlK and A~L, were poorly correlated to pH buffer capacity. The linear relationship between AlCu and pH buffer capacity (r2 = 0.49) obtained in this study supports the view of previous researchers that the hydrolysis of A1 adsorbed by organic matter is a source of pH buffering in soils. However, the change in CEC with pH accounted for 76% of the variation in pH buffer capacity, indicating that other mechanisms such as deprotonation of organic groups and variable charge minerals are also involved in pH buffering. The ability of CuCl2 and LaCl3extractable Al to estimate lime requirement depended on the target pH. The results suggest that lime requirements based on neutralization of AlLa would be sufficient to raise pHw to around 5.5, whereas requirements based on neutralization of AlCu substantially overestimated the actual lime requirement to pHw 5.5, but gave a reasonable estimation of the lime requirement to pHw 6 5.

Phosphorus Extraction with Soil Test Methods Affected by Soil P Sorption Capacity

2020 ◽  
Vol 20 (4) ◽  
pp. 1882-1890 ◽  
Author(s):  
Gilmar Luiz Mumbach ◽  
Luciano Colpo Gatiboni ◽  
Daniel João Dall’Orsoletta ◽  
Djalma Eugênio Schmitt ◽  
Patrícia Pretto Pessotto ◽  
...  
Keyword(s):  
Sorption Capacity ◽  
Test Methods ◽  
Soil Test ◽  
Soil P ◽  
P Sorption ◽  
P Sorption Capacity ◽  
Phosphorus Extraction

Phosphorus sorption and chemical characteristics of lightweight aggregates (LWA)-potential filter media in treatment wetlands

1997 ◽  
Vol 35 (5) ◽  
pp. 103-108 ◽  
Author(s):  
T. Zhu ◽  
P. D. Jenssen ◽  
T. Mæhlum ◽  
T. Krogstad
Keyword(s):  
Sorption Capacity ◽  
Metal Content ◽  
Exchange Capacity ◽  
Chemical Characteristics ◽  
Phosphorus Sorption ◽  
Filter Media ◽  
Total Metal Content ◽  
P Sorption ◽  
P Sorption Capacity ◽  
Total Metal

Five light-weight aggregates (LWAs), suitable for filter media in subsurface flow constructed wetlands, were tested for potential removal of phosphorus (P). P-sorption variation is dependent on the chemical characteristics of the LWA. All LWAs exhibited high pH and high total metal content; however, P-sorption capacity varied by two orders of magnitude. Of the LWAs' chemical characteristics (total metal content, cation exchange capacity, and oxalate soluble Fe and Al), total metal content has the closest relationship with the P-sorption capacity. Among the four major metal ions (Mg, Ca, Fe and Al), Ca has the strongest correlation with the P-sorption capacity.

scholarly journals Field Proximal Soil Sensor Fusion for Improving High-Resolution Soil Property Maps

Soil Systems ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 52
Author(s):  
Gustavo M. Vasques ◽  
Hugo M. Rodrigues ◽  
Maurício R. Coelho ◽  
Jesus F. M. Baca ◽  
Ricardo O. Dart ◽  
...  
Keyword(s):  
Soil Properties ◽  
Ordinary Kriging ◽  
Soil Property ◽  
Clay Content ◽  
Exchange Capacity ◽  
Organic C ◽  
Covariate Data ◽  
Independent Validation ◽  
Soil Sensors ◽  
Dense Grid

Mapping soil properties, using geostatistical methods in support of precision agriculture and related activities, requires a large number of samples. To reduce soil sampling and measurement time and cost, a combination of field proximal soil sensors was used to predict and map laboratory-measured soil properties in a 3.4-ha pasture field in southeastern Brazil. Sensor soil properties were measured in situ on a 10 × 10-m dense grid (377 samples) using apparent electrical conductivity meters, apparent magnetic susceptibility meter, gamma-ray spectrometer, water content reflectometer, cone penetrometer, and portable X-ray fluorescence spectrometer (pXRF). Soil samples were collected on a 20 × 20-m thin grid (105 samples) and analyzed in the laboratory for organic C, sum of bases, cation exchange capacity, clay content, soil volumetric moisture, and bulk density. Another 25 samples collected throughout the area were also analyzed for the same soil properties and used for independent validation of models and maps. To test whether the combination of sensors enhances soil property predictions, stepwise multiple linear regression (MLR) models of the laboratory soil properties were derived using individual sensor covariate data versus combined sensor data—except for the pXRF data, which were evaluated separately. Then, to test whether a denser grid sample boosted by sensor-based soil property predictions enhances soil property maps, ordinary kriging of the laboratory-measured soil properties from the thin grid was compared to ordinary kriging of the sensor-based predictions from the dense grid, and ordinary cokriging of the laboratory properties aided by sensor covariate data. The combination of multiple soil sensors improved the MLR predictions for all soil properties relative to single sensors. The pXRF data produced the best MLR predictions for organic C content, clay content, and bulk density, standing out as the best single sensor for soil property prediction, whereas the other sensors combined outperformed the pXRF sensor for the sum of bases, cation exchange capacity, and soil volumetric moisture, based on independent validation. Ordinary kriging of sensor-based predictions outperformed the other interpolation approaches for all soil properties, except organic C content, based on validation results. Thus, combining soil sensors, and using sensor-based soil property predictions to increase the sample size and spatial coverage, leads to more detailed and accurate soil property maps.

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