Published in Soil Sci. Soc. Am. J. 69:522-530 (2005).
© 2005 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
Division S-8—Nutrient Management & Soil & Plant Analysis
Soil Lime Requirement by Direct Titration with a Single Addition of Calcium Hydroxide
Min Liu,
D. E. Kissel*,
M. L. Cabrera and
P. F. Vendrell
Dep. of Crop and Soil Sciences and Agricultural and Environmental Services Labs., 2400 College Station Road, Univ. of Georgia, Athens, GA 30602
* Corresponding author (dkissel{at}uga.edu)
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ABSTRACT
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Direct titration of acid surface soils is often used to measure soil acidity. However, titration has not been used for routine determination of the lime requirement (LR) in soil testing laboratories, because it is too time-consuming, requiring multiple additions of base and long equilibration times between additions. Since soil pH as a function of added base can be described well by a linear equation, titration may be adopted by soil testing laboratories using a minimum number of base additions. Our objective was to evaluate the accuracy of a simplified titration procedure, based on an initial pH reading and a second reading following the addition of one dose of Ca(OH)2, followed by extrapolation to the target pH. Seventeen soils were titrated with Ca(OH)2 in both water and 0.01 M CaCl2 with a 30-min interval between additions. The slopes from the first two data points of the titration in water were frequently in error for estimation of the slopes regressed by all data points to pH 6.5. However, the first two data points in the 0.01 M CaCl2 titration were found to be more reliable for estimating the slopes. Both the initial pH in water and in 0.01 M CaCl2 were used to calculate the LR with the two-point slope in 0.01 M CaCl2. The LR predicted using the initial pH in 0.01 M CaCl2 gave better estimates of the LR than the initial water pH when compared with the standard 3-d Ca(OH)2 incubation. A linear regression of LR by the single addition method in 0.01 M CaCl2 (Y) on LR determined with the 3-d Ca(OH)2 incubation (X) gave the linear equation Y = 0.88 X, r2 = 0.93. It is concluded that the LR predictions with the single addition method in 0.01 M CaCl2 are sufficiently accurate to justify further evaluation under routine laboratory conditions.
Abbreviations: A-E, Adams-Evans • CEC, cation exchange capacity • LR, lime requirement • OAc, acetate • SMP, Shoemaker–McLean–Pratt
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INTRODUCTION
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IN ROUTINE SOIL TESTING LABORATORIES in the USA, the LR of acid soils is typically determined by using a buffer method, such as the Adams-Evans (A-E) buffer procedure (Adams and Evans, 1962) in the Southeast USA and the Shoemaker–McLean–Pratt (SMP) buffer that is widely used in the Midwest USA (Shoemaker et al., 1961). Both of these buffers contain p-nitrophenol, a potentially toxic compound, therefore alternative procedures should be considered.
An alternative to the use of buffers is to determine the LR by direct titration. Direct titration was studied by Dunn (1943) by equilibrating acid soils with multiple rates of 0.022 M Ca(OH)2 for time periods of up to 4 d, but their titration–incubation procedures have been generally considered to be too time-consuming for use in routine soil testing. Nevertheless, their 3-d incubation with Ca(OH)2 is a widely accepted reference method (Follett and Follett, 1980; Alabi et al., 1986; McConnell et al., 1990; Owusu-Bennoah et al., 1995) used for comparison with other procedures to determine the LR.
Studies by Magdoff and Bartlett (1985) indicated that the titration curves of acid surface soils are approximately linear. Weaver et al. (2004) found that the titration data of pH vs. added base were described well by a linear equation in the pH range of 4.5 to 6.5 for a group of soils from the coastal plain of Georgia. Liu et al. (2004) continued titration studies with a wider range of 17 soils from throughout Georgia. They found that at least 30 min were needed between additions of 0.022 M Ca(OH)2 with no background electrolyte to reach a stable pH. Titrations to a target pH of 6.5 were linear with 15 of the 17 soils giving r2 values > 0.992.
To adapt a titration procedure for routine determination of the LR, a minimal number of pH measurements would be required to reduce measurement time. In titrations conducted by Liu et al. (2004), the first three data points after addition of Ca(OH)2 gave slopes and intercepts by linear regression that were similar to those for the whole titration to a target pH of 6.5. The soil pH without Ca(OH)2 additions was not used in the linear regression because the pH value was depressed below the y intercept in over 50% of the soils. The LR was estimated by extrapolating the linear regression of the first three data points after Ca(OH)2 addition to a target pH of 6.5. The LR by this method estimated only 80% of the LR determined by the 3-d incubation procedure of Dunn (1943). However, the linear fit between the two methods was good with an r2 of 0.96 and the titration method estimated LR of soils with relatively high and low LRs equally well. In contrast, when compared with the 3-d incubation, the A-E procedure overestimated the LR for soils with relatively low LRs and underestimated the LR for those soils with relatively high LRs. In summary, Liu et al. (2004) indicated that titration with Ca(OH)2 had merit for routine use provided that it could be simplified further.
The initial soil pH in water being below the y intercept is problematic. To minimize the number of pH measurements, it would be preferable to use the initial soil pH. However, using the initial soil pH results in a higher slope, which lowers the calculated LR. In preliminary titrations done in 0.01 M CaCl2, we noted that the initial pH in a titration agreed more closely with the y intercept from linear regression of pH vs. Ca(OH)2 added. With good agreement between these two values, it may be possible to estimate the slope of the titration curve with sufficient accuracy from two pH readings, one taken before and one after the addition of Ca(OH)2. Then the LR could be calculated with
Eq. [1]
 | [1] |
where b is the slope of the relationship of pH vs. Ca(OH)2 added (a measure of the soil's pH buffering capacity). Since the ionic strength of the soil solution has a substantial effect on the pH measurement (Schofield and Taylor, 1955; Ryti, 1965), it might be appropriate to make the pH measurements in 0.01 M CaCl2 to eliminate any effect of variable ionic strength in the titration results. The objectives of this study were to further test the feasibility and accuracy of doing titrations of acid soils in 0.01 M CaCl2 and to evaluate the accuracy of a simple titration procedure based on an initial pH reading and a second reading following the addition of one dose of Ca(OH)2.
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MATERIALS AND METHODS
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Seventeen soil samples with a wide range of clay and soil organic C contents were collected from five of the major land resource areas of Georgia. Approximately 5 kg of soil was collected from the Ap horizon of agricultural soils and the A horizon of forested soils at each location. The soils were oven-dried at a temperature of 35°C, crushed, and then sieved (2 mm) to remove gravel and nondecayed crop residue, which consisted of <1% of the soil by weight. Soils were then stored in sealed Ziploc bags (S.C. Johnson & Son, Racine, WI) until analyzed. The soils were analyzed for total C and N by dry micro-Dumas combustion with a Leco 2000 Analyzer (Leco, St. Joseph, MI). Particle-size distribution was determined by the pipette method described by Kilmer and Alexander (1949). Exchangeable Al was determined by the titration method of Yuan (1959) and cation exchange capacity (CEC) was determined by a modified soil survey laboratory method (Soil Survey Staff, 1996). In the CEC procedure, 5 g of soil is leached with 50 mL of sodium acetate (OAc), pH 7.0 on a Centurion Model 24-01 and Model 12-01 Automatic Extractor (Lincoln, NE). Excess NaOAc was removed by leaching with 100 mL of ethanol. The Na was replaced by 50 mL of NH4Oac, pH 7.0.
The properties of the soils are given in Table 1. Briefly, the soils ranged in their clay contents from a low of 21 to a high of 507 g clay kg–1. Total soil C ranged from a low of 4215 to a high of 31805 mg C kg–1 soil. The soil pH buffering capacities, determined from the slope (b) of the linear regression of pH vs. mmol OH–1 added from the Ca(OH)2 incubations (see below) and expressed as 1/b, (0 point omitted) ranged from 0.70 to 5.79 cmolc kg–1 pH–1. Saturated Ca(OH)2 solution (0.022 M), prepared as described by Liu et al. (2004), was used as the standard base to titrate the selected acid soils.
Complete Titration Curves
The soil pH measurements and titrations were performed in a 1:1 suspension while being stirred. A propeller shaped stirrer was adjusted to fit into 120-mL polypropylene beakers so that all soil particles were suspended throughout the titration. A Visco Alpha Multi-task version 2.0 digital titrator (Visco Alpha, Middletown, NY) was used to titrate each soil. Through programming the titration software, the number of aliquots, the interval time between two aliquots, and the stirring speed during titration can be adjusted. A Titronic Universal Piston Burette (SCHOTT Glas Business Segment Labware, Hattenbergstraße, Mainz, Germany) was used to add the Ca(OH)2 solution with an accuracy of ±0.01 mL. A SCHOTT glass pH electrode (SCHOTT Glas Business Segment Labware, Hattenbergstraße, Mainz, Germany) with a calomel reference was used to determine pH. The pH meter was calibrated with standard pH 4.00 and 7.00 buffers before each titration. Specifically, the titrations were done by adding 30 mL of deionized water or 30 mL of 0.01 M CaCl2 to 30 g of soil (1:1 ratio) followed by either 1 mL of 0.022 M Ca(OH)2 per addition for less buffered soil samples (CP1 to CP6, RV1 to RV4, SP2, and SP3) or 3 mL of 0.022 M Ca(OH)2 per addition to the remaining soils. Thirty minutes were chosen as the time interval between additions based on the results from Liu et al. (2004). The soil suspension was continuously stirred during the titration and the pH was measured while being stirred at the end of each time interval. Increments of Ca(OH)2 were added until pH reached 6.5 to 7.0. For electrode safety, the pH electrode was stored in the 7.00 buffer between measurements. The electrode was rinsed with deionized water after each measurement, before placing into the buffer. The rinsate was discarded.
Calculation of Titration Slopes
Linear regression of the complete titration curves was performed using SigmaPlot software (SPSS Inc., 2002). For titrations performed in deionized water, the soil pH without Ca(OH)2 addition was omitted because its pH value was frequently below the y intercept, but all remaining data to pH 6.5 were included. The titration data were plotted and regressed with base addition in units of Mg CaCO3 ha–1 using the following conversion equations:
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where V is the milliliter volume of Ca(OH)2 added, and M is the molarity of Ca(OH)2. With M equal to 0.022 M, Eq. [2] becomes
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Considering the weight of soil titrated as 0.03 kg and assuming 2.24 x 106 kg soil ha–1 results in:
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Combining Eq. [4] with Eq. [3] results in
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For calculation of titration slopes from the initial two data points, the following equation was used:
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where pH1 is the pH before addition of Ca(OH)2, pH2 is the pH after addition of Ca(OH)2, V is the volume of Ca(OH)2 added (3 mL was used in all calculations, regardless of soil's pH buffering capacity), M is the molarity of Ca(OH)2 (0.022 M in this study), and the weight of soil is in units of kilograms (0.03 kg in this study). The slope has units of pH (mg CaCO3/kg soil)–1 and can be used to calculate the LR as mg CaCO3 (kg soil)–1 using Eq. [1]. With the assumption of 2.24 x 106 kg soil ha–1, mg CaCO3 (kg soil)–1 was converted to Mg CaCO3 ha–1 using the following equation:
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Calcium Hydroxide Incubations
Each soil sample was also incubated for 4 d with three amounts of a 0.022 M Ca(OH)2 solution added to 30 mL of deionized water (0.01 M CaCl2 was not used) and 30 g of each soil in a 120-mL polypropylene beaker. After thoroughly mixing for 30 min by stirring intermittently with a glass rod, the initial pH of each sample was measured while stirring at the same speed as that used for titration. Three amounts of 0.022 M Ca(OH)2 solution equivalent to either 0.5, 1, or 1.5 times the LR to the target pH of 6.5, calculated from the full titration curves, were added to each soil. Three drops of chloroform were added to depress microbial activity. The samples were then covered with PARAFILM (Royal Purple, Ltd., Porter, TX) to reduce evaporation. A 10-mm long slit was cut through the film for air exchange. A glass stirring rod was inserted through the opening for mixing the soil periodically. The soil samples were incubated for 4 d at room temperature (23 ± 2°C). The pH was measured at 24, 48, 72, and 96 h while being stirred, the same as during the titrations. For purposes of comparison with the two-point titration method, the 72 h (3 d) data was selected. The 3-d data was selected because in the study by Liu et al. (2004), pH dropped from Day 1 to 2, but changed little from Day 2 to 3 and increased slightly on Day 4. Approximately half of the soil treatments were duplicated to determine precision. The relationship of soil pH versus Ca(OH)2 added (expressed as the equivalent CaCO3) was fitted for each soil by nonlinear regression using Table Curve 2D (Systat Software Inc., Richmond, CA) and the Ca(OH)2 incubation LR to pH 6.5 was calculated from this equation. The nonlinear equation used for all soils was y = a + bxc, where y is soil pH, x is Ca(OH)2 added, and a, b, and c are fitting coefficients. A nonlinear equation was used to fit this data because for most soils, the data of pH vs. lime added typically becomes nonlinear near and certainly above pH 6.5, and the 1.5 times LR treatment gave pH values above 6.5 for all soils.
Adams-Evans Buffer Procedure
The A-E buffer procedure was used to predict the LR of each soil sample. Twenty milliliters of deionized water was added to 20 g of each soil. After 40 min, the pH was measured while being stirred. Then, 20 mL of A-E buffer was added to each soil suspension. The soil suspensions were shaken for 10 min at 400 excursions min–1 and then allowed to stand for 0.5 h. The buffer pH was then measured while being stirred. The A-E procedure was duplicated for each soil and the mean value was used in the analysis.
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RESULTS AND DISCUSSION
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The titration curves of five soils, randomly selected from each of the five major land resources areas, and performed in both water and 0.01 M CaCl2 are shown in Fig. 1
. Soil pHs in 0.01 M CaCl2 were depressed at all levels of Ca(OH)2 addition in all soils, a common effect due to displacement of Al+3 and H+ from increased soil solution concentration of Ca+2, and due to elimination of the junction potential effect (Bloom, 2000). The initial soil pH in 0.01 M CaCl2 was closer to the y intercept from linear regression in nearly every soil, when compared with the corresponding pH in water. For the titrations performed in water, the initial pH before Ca(OH)2 addition was lower than the "y" intercept in about 60% of the soils. Therefore, for titrations done in water, the use of two data points (0 and 3 mL) would result in erroneously high slope values (
pH/CaCO3). Furthermore, when the slope of the relationship (or the linear equation) is extrapolated to the target pH, it would therefore underestimate the LR. In comparison, the initial pH in 0.01 M CaCl2 was more nearly equal to the "y" intercept (Fig. 1). This difference is most apparent for soil samples CP4 and SP1 in Fig. 1.
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Fig. 1. Titration of five soils with 0.022 M Ca(OH)2 in water or 0.01 M CaCl2. Units of Mg ha–1 CaCO3 were calculated from mL Ca(OH)2 as described in Materials and Methods.
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A comparison of slopes from the fitted linear regression for titrations done in deionized water with those done in 0.01 M CaCl2 is shown in Fig. 2
. The slopes from the titrations done in water were regressed using all data points to pH 6.5 without the initial pH point because, as noted above, it was sometimes below the y intercept. The slopes from titrations done in 0.01 M CaCl2 were regressed by using all data points to pH 6.5. The fitted linear equation of slope values by the two titrations was:
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Fig. 2. Comparison of titration slopes (pH/Mg CaCO3/ha) determined by linear regression of all titration data points to pH 6.5 in 0.01 M CaCl2 and all titration data points except the first in deionized water.
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The 95% confidence interval for the slope bracketed one; therefore it was not statistically different from 1. Further, the 95% confidence interval for the intercept bracketed zero, therefore it was not statistically different from zero. The paired-T test using STATISTIX 7.0 (Analytical Software, 1985) was also performed to determine differences in the two sets of slopes. The resulting P value was 0.2126, which meant that they were statistically equal. However, as can be noted from the regressions in Fig. 1, the slopes in 0.01 M CaCl2 were slightly greater than those in water for four of the five soils shown.
To establish the accuracy of determining the slope from a two-point titration curve, we first compared the slopes determined from two-points (0 and 3 mL) in water with those obtained by regressing all data points (except 0) to pH 6.5 (Fig. 3)
. The fitted linear equation was:
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Fig. 3. Comparison of titration slopes (pH/Mg CaCO3/ha) in water determined by regression of all data points to pH 6.5 except the first vs. slopes calculated from two data points [0 and 3 mL Ca(OH)2].
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The equation indicated that the straight line determined from two data points [0 and 3 mL Ca(OH)2] gave slopes on average of 1.46 times those from using multiple data points for the regression. This difference in slope values is directly due to the depression of the pH in water of the first data point [without addition of Ca(OH)2] for several of the soils. A similar comparison was made for those titrations done in 0.01 M CaCl2. When slopes determined from regression of all data points to pH 6.5 were compared with those determined from only two points (0 and 3 mL), the agreement was better, as shown in Fig. 4
. The comparison of slope values of the 17 soils gave the following result:
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Fig. 4. Comparison of titration slopes (pH/Mg CaCO3/ha) in 0.01 M CaCl2 determined by regression of all data points to pH 6.5 vs. slopes calculated from two points [0 and 3 mL Ca(OH)2].
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In this case, the slopes using two points from the titration in 0.01 M CaCl2 (Y) were only slightly larger on average than those from regression of all data points to pH 6.5 (X). This improved agreement was due primarily to the fact that the pH at 0 addition in 0.01 M CaCl2 was closer to the y intercept from the regression analysis.
As noted above, the slopes determined from the water titration and the slopes determined from the 0.01 M CaCl2 titration were not significantly different when all data points were used except 0 for those in water. We also found from Fig. 4 that the slopes calculated from the two point (0 and 3 mL) titration in 0.01 M CaCl2 were only slightly higher than those regressed using all data points to pH 6.5. Since we showed earlier that slopes from two data points in water were frequently in error, the two-point titrations should be done in 0.01 M CaCl2 to assure better accuracy. It is less clear, however, what initial pH should be used for the LR calculations. Either water pH or pH in 0.01 M CaCl2 could be used. To determine the best choice, we calculated the LR using both, but using the two-point slope determined in 0.01 M CaCl2. We compared these LRs (Y) with the LRs (X) considered to be the standard, that is, the LRs from the 3-d incubation with Ca(OH)2. The first comparison using water pH is shown in Fig. 5
. The fitted linear relationship was:
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Fig. 5. A comparison of LR (Mg CaCO3/ha) based on an initial pH in water and slopes determined from two point titrations in 0.01 M CaCl2 [0 and 3 mL Ca(OH)2] extrapolated to pH 6.5 vs. LR from the 3 d Ca(OH)2 incubation.
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The slope of 0.64 indicated that the LR predicted using the initial water pH was about 64% of those from the standard 3-d incubation. As can be noted from Fig. 5, the greatest divergence from the 1:1 line was for four samples with medium to high LRs. These samples included three from the Atlantic Coast Flatwoods, of which two had water pHs at least 0.7 pH units higher than those measured in 0.01 M CaCl2. All three of the Atlantic Coast Flatwoods soils are identified in Fig. 5. When those soils were excluded from the regression analysis, the agreement between the two methods improved, although the slope was 0.906, indicating an underprediction of the LR. This result led to a further effort to predict the LR using both the initial pH and slope determined in 0.01 M CaCl2, since this would mask differences in ionic strength that might occur between the two pH readings taken on the same soil.
The LRs predicted from the two point slope and initial pH in 0.01 M CaCl2 vs. the LRs from 3-d Ca(OH)2 incubation were then compared. The linear regression of LRs predicted from the two point slope and initial pH in 0.01 M CaCl2 vs. the LRs from the 3-d Ca(OH)2 incubation gave the relation:
where Y = LR from two data points, as described, and X was the LR from the 3-d Ca(OH)2 incubation, expressed as Mg CaCO3 ha–1. The results of the regression seemed to be heavily influenced by three soils from the Atlantic Coast Flatwoods (all forested and relatively high in organic C) and when they were not included in the regression, the fitted linear relationship was:
The intercept of both regressions were not different from 0, so the regressions were also done with intercept equal to zero, with the results shown in Fig. 6
. In this case the fitted linear equation was:
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Fig. 6. A comparison of LR (Mg CaCO3/ha) based on an initial pH in 0.01 M CaCl2 and slopes from two point titrations [0 and 3 mL Ca(OH)2] in 0.01 M CaCl2 extrapolated to pH 6.5 vs. LR from the 3-d Ca(OH)2 incubation.
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This result indicates that on average across all 17 soils, the method tested predicts an average of 88% of the LR determined by the 3-d standard incubation. Furthermore, when the three soils from Atlantic Coast Flatwoods (all forested and relatively high in organic C) were not included in the regression, the fitted linear relationship was:
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The slope value of 1.04 was not significantly different from one at the 95% confidence interval. Based on these results, it appears likely that the LR can be predicted with two pH measurements per sample if saturated Ca(OH)2 is added between the two measurements and adequate mixing and equilibration time (at least 30 min), as shown by Liu et al. (2004), is provided before the second pH measurement. To ensure that the change in pH following the addition of Ca(OH)2 is due only to the added OH– ions and not due to other factors such as a slight change in the ionic strength of the soil solution, it is recommended that the two pH measurements be made in 0.01 M CaCl2. This will ensure a higher and more uniform ionic strength for both pH measurements.
As a further test of the method, we compared the LR predicted from the two pH measurements in 0.01 M CaCl2 with the LR by the A-E buffer procedure, the method currently used by the University of Georgia Soil Testing Laboratory. When the LRs by A-E were regressed on LRs by two point titration for the 17 soils, the relationship found was LR A-E (Mg CaCO3) = 0.860 + 0.699 LR two point titration (Mg CaCO3). This result, shown in Fig. 7
, is similar to that of Liu et al. (2004), who compared LR (A-E) with LR by the 3 d Ca(OH)2 incubation. Generally, the agreement was good between the two methods with slightly higher LR by A-E on some soils with LR < 4 Mg CaCO3 ha–1. The two soils with the highest LR gave higher LR by titration.
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Fig. 7. A comparison of LR (Mg CaCO3/ha) based on an initial pH in 0.01 M CaCl2 and slopes from two point titrations [0 and 3 mL Ca(OH)2] in 0.01 M CaCl2 extrapolated to pH 6.5 vs. LR by the Adams-Evans procedure with a target pH of 6.5.
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The relatively good agreement of LR predicted from the two-point titration in 0.01 M CaCl2 with the standard 3-d Ca(OH)2 incubation was somewhat surprising, given that the standard 3-d incubation was done in water and the two-point titration was done in 0.01 M CaCl2. This good agreement may be due to offsetting differences in equilibration times. The incubation with Ca(OH)2 in water took 3 d and the equilibration time with the two-point titration was only 30 min. If left to equilibrate much longer than 30 min, the two-point titration in 0.01 M CaCl2 may result in a higher LR with continual neutralization of added base with soil acidity and a reduction in pH. The 3-d Ca(OH)2 incubation in water may be considered to be fully equilibrated and reacted with soil acidity. The two-point titration with 0.01 M CaCl2 for 30 min may not be fully equilibrated with soil acidity. But, since initial pH is lower in the presence of 0.01 M CaCl2, the LR is going to be on the high side and the net result is a LR that agrees well with a fully equilibrated 3-d incubation in water.
Before the two-point titration can be implemented for routine use, it needs to be tested under laboratory conditions with the range of samples that are typically submitted to a soil testing laboratory. The results are sufficiently promising, however, to take that next step. Care should be taken to add an aliquot of Ca(OH)2 of sufficient volume to give adequate sensitivity for determining the slope, without raising pH in 0.01 M CaCl2 to above 6.5, because the slopes become nonlinear around this pH. For the soils in our study, an aliquot size of 1 mL saturated Ca(OH)2 per 10 g of soil appeared to work well.
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CONCLUSIONS
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In an earlier study of the titration of acid surface soils, (Liu et al., 2004) found that the increase in soil pH from the addition of Ca(OH)2 could be described well with a linear equation. The use of only three data points from the titrations were sufficient to define accurately the slope of the titration curves. As noted above, the LR can be easily calculated from the slope, the initial soil pH, and the target pH. In the work reported here, we tested a procedure that uses only two measurements of pH, one before and one after the addition of Ca(OH)2 (with a suitable equilibration period) to determine the slope of the titration curve.
The slopes of complete titrations to pH 6.5 determined from linear regression of pH vs. Ca(OH)2 added from titrations in water were not significantly different from those done in 0.01 M CaCl2. The slope calculated from a two-data point titration in 0.01 M CaCl2 gave a more accurate estimate of slopes determined from all data points than the two-data point slope from titrations in water. Both water pH and pH in the 0.01 M CaCl2 were used to calculate the LRs using the two-point slope from the 0.01 M CaCl2 titration. When both sets of the LRs were compared with the standard 3-d Ca(OH)2 incubation method, the LRs calculated from the pH in the 0.01 M CaCl2 had a better relationship with a linear equation of Y = 0.88X, r2 = 0.93. Furthermore, when the three forest soils with high organic C were eliminated from the data set, the linear equation had a slope not different from one. Therefore, the simple titration procedure in 0.01 M CaCl2 is recommended for further development for routine laboratory use based on an initial pH reading and second reading following the addition of one dose of Ca(OH)2. The recommended procedure for routine use will be most accurate if the dose of Ca(OH)2 is mixed thoroughly with all soil for at least 30 min using an appropriate stirrer or shaker to ensure equilibration of Ca(OH)2 with all soil before taking the second pH reading. It is also recommended that both pH readings be taken with the same electrode/meter to eliminate any bias from that source. Further evaluation of the procedure is recommended under typical operating conditions. Adaptation of this procedure to robotic pH analyzers would be desirable.
Received for publication June 18, 2004.
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ABSTRACT
INTRODUCTION
