Interrelations between soil pH measurements in various electrolytes and soil solution pH in acidic soils

Soil Research ◽  
1991 ◽  
Vol 29 (4) ◽  
pp. 483 ◽  
Author(s):  
RL Aitken ◽  
PW Moody
Keyword(s):  
Ionic Strength ◽  
Soil Solution ◽  
Soil Ph ◽  
Low Ph ◽  
Acidic Soils ◽  
Solution Ph ◽  
Ph Measurements ◽  
The Best Approximation ◽  
Water Ph ◽  
The Difference

Ninety soil samples (81 surface, 9 subsurface) were collected from eastern Queensland and soil pH (1:5 soi1:solution) was measured in each of deionized water (pH,), 0.01 M CaCl2, 0-002 M CaCl2 and 1 M KCl. Soil solution was extracted from each soil after incubation for 4 days at the 10 kPa matric suction moisture content, and pH (pHss) and electrical conductivity were measured. The objectives of this work were to investigate interrelationships between soil pH measurements in various electrolytes and soil solution pH in a suite of predominantly acidic soils. Although the relationships between pHw and pH measured in the other electrolytes could be described by linear regression, the fitting of quadratic equations improved the coefficients of determination, indicating the relationships were curvilinear. The majority of soils exhibited variable charge characteristics (CEC increases with soil pH) and the curvilinear trend is explained on this basis. At low pH, the difference between pH, and pH measured in an electrolyte will be small compared with the difference at higher pH values because, in general, at low pH, soils will be closer to their respective PZSE (pH at which electrolyte strength has no effect). Of the electrolytes used, pH measured in 0.002 M CaCl2 gave the closest approximation to pHs,. However, when soils with ionic strengths greater than 0.018 M were selected (predominantly cultivated surface soils), pH in 0.01 M CaCl2 gave the best approximation to pHss. For predicting pHss, the ionic strength of the electrolyte will need to be matched to that of the soils studied. For a suite of soils with a large range in soil solution ionic strength (as in this study), it is preferable to measure pHss directly.

Field amelioration of acidic soils in south-east Queensland. III. Relationships of maize yield response to lime and unamended soil properties

1998 ◽  
Vol 49 (4) ◽  
pp. 649 ◽  
Author(s):  
P. W. Moody ◽  
T. Dickson ◽  
R. L. Aitken
Keyword(s):  
Grain Yield ◽  
Soil Solution ◽  
Soil Ph ◽  
Maximum Yield ◽  
Maize Yield ◽  
Soil Types ◽  
Yield Response ◽  
Lime Treatment ◽  
Acidic Soils ◽  
Solution Ph

Maize (Zea mays) grain yield responses to rates of lime were measured at 19 sites onseveral soil types in south-east Queensland. At some sites, one rate of gypsum or phosphogypsum was also applied. Relative grain yield (100 mean yield of nil lime treatment/maximum yield) was correlated with each of soil pH (1 : 5 water and 1 : 5 0·01 M CaCl2), soil solution pH, exchangeable (1 M KCl) Al, exchangeable (1 M NH4Cl) Ca, Al saturation of the effective cation exchange capacity (ECEC), Ca saturation of the ECEC, and 0·01 M CaCl2 extractable Mn and Al. Across all soil types, Mitscherlich fits indicated that most of the variation in relative grain yield was accounted for by either Ca saturation (R2 = 0·62) or soil solution pH (R2 = 0·61), although soil pH(water) (R2 =0·53), Al saturation (R2 = 0·46), exchangeable Ca (R2 = 0·42), soil pH(CaCl2) (R2 = 0·40), and CaCl2-extractable Mn (R2 = 0·33) also accounted for significant (P < 0·05) amounts of variation. These results demonstrate that one or both of Al and Mn toxicities were having an impact on yieldat different sites. The contrast between the lack of responses to gypsum/phosphogypsum at mostlime responsive sites and the observation that Ca saturation was well correlated with relative grainyield suggested an ameliorating effect of Ca on Al toxicity. This effect was captured by an index,Al saturation/Ca saturation, which was well correlated with relative grain yield (R2 = 0·66 for a Mitscherlich fit). A step-up regression approach indicated that most variation in relative grain yield (RY) could beaccounted for by the following equation: The assessment of factors likely to limit yield on strongly acidic soils of the region will therefore needto include indices of Al and Mn toxicities as well as Ca status. Soil pH integrated the effects of these factors on yield, and as a single index, was shown to bean effective diagnostic tool. Relative grain yields of 90% were associated with pH values in the soil solution, 1 : 5 water and 1 : 5 0·01 M CaCl2 of 4·5, 5·2, and 4·4, respectively.

scholarly journals Calculating pH from EC and SAR values in salinity models and SAR from soil and bore water pH and EC data.

Soil Research ◽  
1990 ◽  
Vol 28 (6) ◽  
pp. 1001 ◽  
Author(s):  
CW Robbins ◽  
WS Meyer
Keyword(s):  
Soil Ph ◽  
Soil Salinity ◽  
Field Method ◽  
Soil Extract ◽  
Subsurface Water ◽  
Calibration Data ◽  
Exchangeable Sodium ◽  
Solution Ph ◽  
Simple Method ◽  
Water Ph

Currently used soil salinity models do not contain a mechanism for including exchangeable sodium effects on soil pH. A method is needed that allows pH calculation from the sodium adsorption ratio (SAR) or exchangeable sodium percentage (ESP) and electrical conductivity (EC) data. This study developed a simple method for calculating saturated soil paste and aqueous solution pH from SAR (or ESP) and EC data and compared the results with measured values from a number of soils and subsurface waters. The equation pH =A+{B*(SAR)1/2/(1+C*EC)} estimated soil pH from EC and SAR or ESP values. When rewritten as: SAR or ESP={(pH-A)(1 + C*EC)/B)2, the SAR or ESP was estimated from pH and EC data. By using shallow bore (well) water and soil extract data from the Murray Basin, values were determined for the scalar terms A, B and C. These values differed among subsurface water and soil types, however, the range of each scalar was reasonably small. It was found that a range of at least 2.5 pH units in the calibration data was necessary to obtain reliable regression between predicted and measured pH and SAR or ESP values. When these conditions were met, the predicted results were satisfactory. These relationships provide a method for pH calculation in soil salinity models which takes into account soil EC and sodium effects. They also provide a rapid field method to estimate SAR or ESP from easily obtainable EC and pH data. Further research is needed to define the factors that determine the values of A, B and C.

Effects of aluminium and calcium in the soil solution of acid soils on root elongation of Glycine max cv. Forrest

1988 ◽  
Vol 39 (3) ◽  
pp. 319 ◽  
Author(s):  
RC Bruce ◽  
LA Warrell ◽  
DG Edwards ◽  
LC Bell
Keyword(s):  
Root Growth ◽  
Soil Solution ◽  
Soil Ph ◽  
Activity Ratio ◽  
Acid Soils ◽  
Exchange Capacity ◽  
Al Toxicity ◽  
Solution Ph ◽  
Diagnostic Indices ◽  
Exchangeable Ca

In the course of three experiments, soybean (Glycerine max (L.) Merr.) cv. Forrest was grown in 21 soils (four surface soils and 17 subsoils) amended with liming materials (CaCO3 and Mg CO3) and soluble Ca salts (CaSO4.2H20 and CaCl2.2H2O). In most soils, the soluble salts increased concentrations and activities of Al species in solution to levels that restricted root growth, and MgCO3, induced a Ca limitation to root growth. Root lengths after three days were related to so11 and soil solution attributes.Suitable diagnostic indices for the prediction of Ca limitations to root growth were either Ca saturation of the effective cation exchange capacity or Ca activity ratio of the soil solution, which was defined as the ratio of the activity of Ca to the sum of the activities of Ca, Mg, Na, and K. Values corresponding to 90% relative root length (RRL) of soybean were 0.05 for the Ca activity ratio and 11% for Ca saturation. Calcium activity and Ca concentration in the soil solution and exchangeable Ca were less useful for this purpose.Soil Al saturation was not a good predictor of Al toxicity, but soil solution measurements were. The activities of Al3+ and AlOH2+ gave the best associations with RRL, and values corresponding to 90% RRL were 4 8M and 0.5 8M respectively. The results suggested that Al(OH)3� , Al(OH)2+, and AlSO4+, were not toxic species. Soil solution pH and soil pH measured in water were more sensitive indicators of root growth than soil pH measured in 0.01 M CaCl2.Using a Ca activity ratio of 0.05 and an Al3+ activity of 4 8M as diagnostic indices, none of the 20 soils in two experiments were toxic in Al, while 13 (all subsoils) were deficient in Ca. Thus the first limitation on root growth was Ca deficiency and not Al toxicity, in spite of high Al saturations and relatively low pH in these soils. However, Al toxicity could be induced by increasing the ionic strengths of soil solutions.

Surface soil-pH map of Queensland

Soil Research ◽  
1994 ◽  
Vol 32 (2) ◽  
pp. 212 ◽  
Author(s):  
CR Ahern ◽  
MMG Weinand ◽  
RF Isbell
Keyword(s):  
Soil Ph ◽  
Surface Soil ◽  
Low Ph ◽  
Buffering Capacity ◽  
Chemical Processes ◽  
Gis Technology ◽  
Acidic Soils ◽  
Naturally Occurring ◽  
Surface Soil Ph

Surface soil pH can influence biological activity, nutrition and various chemical processes in the soil. Low pH or acidity is causing major concern in southern Australia, prompting requests for details on the extent, severity and distribution of acidic soils in Queensland. By creating a soil pH database, using an appropriate base map, rainfall isohyets and GIS technology, a coloured pH map of surface soils was produced at a 1:5000000 scale for the entire State. As most samples were from virgin or little disturbed sites, the map generally reflects naturally occurring soil pH. Developed horticultural, agricultural and fertilized pastoral areas are likely to have lower pH than that mapped. About two thirds (63.1%) of Queensland's soils have acidic surfaces, 9.5% neutral and the remaining 26.9% are alkaline. The major proportion (74%) of the > 1200 mm rainfall zone is strongly acid, and the remainder is medium acid or acid. Much of the sugar growing areas occur in this zone. Surface soil pH generally decreases as rainfall increases and to a lesser extent from subtropical to tropical climate. In addition to climate, identification of the soil type assists with predicting pH, as the organic, coarse and medium textured soils and massive earths are more likely to be acid and have low buffering capacity. Depending on the land use, such soils may require regular liming or minimizing of net acidifying practices for long term sustainability.

Effect of depth and lime or phosphorus-fertilizer applications on the soil solution chemistry of some New Zealand pastoral soils

Soil Research ◽  
1995 ◽  
Vol 33 (3) ◽  
pp. 461 ◽  
Author(s):  
DM Wheeler ◽  
DC Edmeades
Keyword(s):  
Soil Solution ◽  
Soil Ph ◽  
Maximum Yield ◽  
Solution Chemistry ◽  
Phosphorus Fertilizer ◽  
Solution Ph ◽  
Soil Solutions ◽  
P Fertilizer ◽  
P Rate ◽  
Mn Concentrations

Thirteen trails were sampled to investigate the effects of depth, or the surface application of lime and phosphorus (P) fertilizer, on solution composition. Soil solutions were extracted by centrifuge from field moist soils within 24 h of sampling. Solution Ca, Mg, Na and K, Al, Mn and Fe concentrations generally decreased and Al, Mn and Fe concentrations generally increased with depth; although exceptions occurred. The largest decrease occurred in the first 25-50 mm of soil. Higher solution Al concentrations occurred in a band at a depth of between 50 and 100 mm in some soils. Lime generally increased solution pH and solution Ca, Mg and HCO3 concentrations, and reduced solution Al, Fe and Mn concentrations in the topsoils. In one soil (Matapiro silt loam) 2 years after lime was applied, lime increased solution pH down to a depth of 100 mm, Ca and HCO3 down to 75 mm and Mg down to 50 mm. Lime also decreased solution Al and Mn down to 75 mm and Fe down to 50 mm. In one series of trials, lime increased solution Ca concentrations at a depth of 50-100 mm 4 years after application in six out of the eight sites. In the same trial series, the application of P fertilizer increased solution P concentrations at 0-50 mm from a mean of 5 �M in the no-added P plots up to a mean of 56 �M at the highest P rate. The highest solution P concentration recorded was 194 �M. The increase in solution P concentrations for a given application of fertilizer P varied from 0.05 to 1.03 �M P per kg P ha-1 applied. Maximum pasture yield and 90% maximum yield occurred when solution P concentrations were about 28 and 14 �M respectively. Solution P concentrations determined from P adsorption isotherms were not a good indicator of solution P concentrations measured in soil. Solution pH was higher than soil pH (1:2.5 soil:water ratio, 2 h equilibration) with a solution pH of 6.0 corresponding to a soil pH in water of about 5.2.

scholarly journals Estimates of soil solution ionic strength and the determination of pH in West Australian soils

Soil Research ◽  
1985 ◽  
Vol 23 (2) ◽  
pp. 309 ◽  
Author(s):  
PJ Dolling ◽  
GSP Ritchie
Keyword(s):  
Ionic Strength ◽  
Soil Solution ◽  
Field Capacity ◽  
Deionized Water ◽  
Distilled Water ◽  
Ph Measurements ◽  
Solution Ionic Strength

The average ionic strength of 20 West Australian soils was found to be 0.0048. The effects of three electrolytes (deionized water, CaCl2 and KNO3), three ionic strengths (0.03, 0.005 and soil ionic strength at field capacity, Is) and two soil liquid ratios (1:5 and 1:10) on the pH of 15 soils were investigated. pH measurements in solutions of ionic strength 0.005 differed the least from measurements made at Is. The differences that occurred in comparisons with distilled water or CaCl2 of ionic strength 0.03 (0.01 M) were much greater (20.4 pH units). An extractant with an ionic strength of 0.005 may provide a more realistic measure of pH in the field than distilled water or 0.01 M CaCl2 for West Australian soils.

Soil solution pH measurements using in-line chambers with tension lysimeters

2000 ◽  
Vol 80 (2) ◽  
pp. 283-288 ◽  
Author(s):  
Bo Elberling ◽  
Bjarne H. Jakobsen
Keyword(s):  
Soil Solution ◽  
Soil Acidification ◽  
Solution Ph ◽  
Ph Change ◽  
Ph Measurements ◽  
Partial Pressures ◽  
Arctic Soil ◽  
Soil Solutions ◽  
Speciation Modelling ◽  
Ph Range

During soil water extraction, pH can change as a result of atmospheric gas exchange. The pH change is important for monitoring soil acidification and determination of mineralogic controls on the solution composition. As part of a global change programme in Greenland for monitoring long-term changes in Arctic soil solutions we observed that the pH of extracted soil solutions increased in the order of a half pH unit during traditional sampling and handling of the soil solution. CO2 degassing is often considered the most important factor causing such a pH increase. Thus, traditional as well as in-line pH measurements were performed during the summers 1997 and 1998. The in-line method was designed to eliminate atmospheric contact with soil solutions prior to pH measurements. The time-dependent pH error was quantified based on laboratory experiments with soil solution under controlled temperatures and CO2 partial pressures. Equilibrium speciation modelling was used to predict pH values observed in the field and in the laboratory and the model was found to reproduce the observations well. We conclude that traditional pH measurements on extracted soil solutions in the pH range from 5 to 7 are not appropriate for detailed pH measurements due to errors associated with CO2 degassing. In-line measurements provide more accurate measurement necessary for detailed studies on soil acidification dynamics. Key words: pH, carbon dioxide degassing, soil solution, tension lysimeter, arctic soil

Nutrient Concentrations in Soil Solution in an Alfisol under Grapefruit Production

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 498d-498
Author(s):  
Z.L. He ◽  
A.K. Alva ◽  
D.V. Calvert ◽  
D.J. Banks ◽  
Y.C. Li
Keyword(s):  
Soil Solution ◽  
Fine Sand ◽  
Drainage Water ◽  
Tree Canopy ◽  
Nutrient Concentrations ◽  
Sour Orange ◽  
Parallel Study ◽  
Ph Measurements ◽  
The Mean ◽  
N Rates

A field experiment was conducted in a Riviera fine sand (Alfisol) with 25-year-old `White Marsh' grapefruit trees on Sour orange rootstock to monitor the downward transport of nutrients from fertilization practices. Fertilizer was applied as either dry granular broadcast (three applications/year) or fertigation (15 applications/year) at N rates of 56, 112, 168, and 336 kg/ha per year using a N:P:K blend (1.0:0.17:1.0). Soil solution was sampled bi-weekly from suction lysimeters, installed under the tree canopy, about 120 cm from the tree trunk, at two depths representing above (120 cm) and below (180 cm) the hard pan. The concentrations of K, Ca, and Mg were greater at the 180- than at 120-cm depth, whereas, the converse was true with respect to the concentration of P in soil solution. Over a 2-year period, the mean concentrations of P and K varied from 0.031-0.976 and 150-250 mg·L–1, respectively. Increased rate of fertilization also appeared to increase the concentrations of Ca and Mg in the soil solution. This could be due to effects of slight acidification of the soil with increased rates of ammonium form of N. A parallel study on pH measurements has shown evidence of soil acidification, under the tree canopy, with increased rates of ammonium fertilization. In a bedded grove, the soil solution above the hard pan is likely to seep into the water furrow, which is discharged into the drainage water.

Decolorisation of natural organic matter by Phanerochaete chrysosporium: the effect of environmental conditions

2004 ◽  
Vol 4 (4) ◽  
pp. 175-182 ◽  
Author(s):  
K. Rojek ◽  
F.A. Roddick ◽  
A. Parkinson
Keyword(s):  
Organic Matter ◽  
Ionic Strength ◽  
Natural Organic Matter ◽  
Phanerochaete Chrysosporium ◽  
Fungal Growth ◽  
Low Ph ◽  
Colour Removal ◽  
Humic Material ◽  
Carbon And Nitrogen ◽  
Carbon And Nitrogen Content

Phanerochaete chrysosporium was shown to rapidly decolorise a solution of natural organic matter (NOM). The effect of various parameters such as carbon and nitrogen content, pH, ionic strength, NOM concentration and addition of Mn2+ on the colour removal process was investigated. The rapid decolorisation was related to fungal growth and biosorption rather than biodegradation as neither carbon nor nitrogen limitation, nor Mn2+ addition, triggered the decolorisation process. Low pH (pH 3) and increased ionic strength (up to 50 g L‒1 added NaCl) led to greater specific removal (NOM/unit biomass), probably due to increased electrostatic bonding between the humic material and the biomass. Adsorption of NOM with viable and inactivated (autoclaved or by sodium azide) fungal pellets occurred within 24 hours and the colour removal depended on the viability, method of inactivation and pH. Colour removal by viable pellets was higher under the same conditions, and this, combined with desorption data, confirmed that fungal metabolic activity was important in the decolorisation process. Overall, removals of up to 40–50% NOM from solution were obtained. Of this, removal by adsorption was estimated as 60–70%, half of which was physicochemical, the other half metabolically-dependent biosorption and bioaccumulation. The remainder was considered to be removed by biodegradation, although some of this may be ascribed to bioaccumulation and metabolically-dependent biosorption.

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