Lime Requirement Determination Research Articles

Evaluation and Validation of Simple and Quick Methods of Lime Rate Determination under Acid Soil-Affected Areas of West Shewa Zone, Ethiopia

Liming acid soils is one of the available intervention options to amend soil acidity and increase crop production and productivity. The selection of a lime requirement determination easy and cheap method that is suitable to the soil conditions in a particular area is a pressing issue. Three lime requirement (LR) estimation methods i.e. (Exchangeable acidity, laboratory pH, and portable pH/Artikilee 3000) methods with one control treatment were tested in acid soils of the dhumuga learning watershed. A field study was conducted to verify the lime requirement (LR) by using portable pH methods and investigate the wheat response to lime. The treatments were laid out in an RCBD design with two farmers’ replications. The result showed that there a was significant (p<0.05) yield response to the liming. The highest grain yield of 5512.3kg ha 1 was obtained from lime treated with the pH method statistically at par with Exchangeable acidity and article 3000 methods. LR rates estimated by the Exchangeable acidity method were lower than those estimated by laboratory pH and portable pH/ Artikilee 3000. However, both methods (laboratory pH and portable pH/ Artikilee 3000) overestimated the lime requirements of the study soil. The exchangeable acidity method was lower than the LR estimated with the article 3000 method by an average of 38 %, which indicates article 3000 methods overestimated the LR for the present study area, while exchangeable acidity methods were found to be reliable estimation LR. Lime rates determined with the three lime testing methods (pH method, Portable pH or Artikilee 3000 and exchangeable acidity) gave yield advantages of 31.94, 24.93 and 20.45%, respectively over the non-limed treatment. From the results of this study, it was concluded that the exchangeable acidity method gives a more reliable estimation of the lime requirements of acid soils of the study area.

Determination of Lime Requirement with Compost on Acidic Ultisols for Wheat Crop in the Gurage Zone of Ethiopia

Acidic soil adversely affects the plant growth and production. Various ameliorating strategies are known, but the optimum rate of lime and compost rate determination for better nutrient management and production in acid Ultisols was not well studied, so the main objective of this study was to determine optimum lime and compost rate for wheat production. A pot experiment was performed on the soil collected from Yefereze (Cheha District). The incubation trail was conducted in factorial combination of four level lime (8.44, 6.33, 4.22, and 0 t·ha−1) and compost (15, 10, 5, and 0 t·ha−1). The sixteen treatments were arranged in completed randomized design (CRD) with triplicate replications in the greenhouse. After 75 days, each pot that was planted with wheat and crop performance had been monitored. The textural class of the soils of the experiment was clay with strongly acidic pH. The organic carbon (2.17%) and total nitrogen content (0.17%) status was medium. The available phosphorus (Av. P) contents were very low (1.63 ppm). The experimental study result revealed that all the three rates of lime and compost continuously improve the soil pH throughout the study periods and the maximum soil pH (6.53) was obtained in combination of 8.44 t·ha−1 and 10 t·ha−1 lime and compost, respectively. The compost amended treatment indicated slight improvement in soil reaction which assert that using compost alone did not reduce soil acidity within 75-day periods in strongly acidic soil condition for suitable wheat production. Liming alone or integrated application increases soil pH (4.69 to 6.53), cation exchangeable capacity (CEC) (27.18 to 31.58 cmolckg−1), exchangeable calcium (3.56 to 8.43 cmolckg−1), available phosphorus (Av.P) (1.63 to 5.27 ppm), total nitrogen (TN) (0.19 to 0.24 ppm), and exchangeable acidity reduced (0.73 cmolckg−1 to trace). Integrated application of 8.44 and 5 t·ha−1 lime and compost rates improve the overall soil property and maximize the wheat yield by 24.26%. Generally, the limiting factor for wheat production of the study area was the acidity of the soil. The combined application of lime and compost raised the pH and improved the suitability of the soil for wheat production. However, the status of Av. P was low after the amendment, and it is advisable to integrate phosphorus containing fertilizer in addition to lime and compost for optimum and sustainable production of wheat in the study area. Since the incubation and greenhouse experiment were conducted in a controlled environment, there is a need for field verification. It is also advisable to assess the economic feasibility of the different rates of lime and compost for an appropriate soil management decision.

Lime requirement for agricultural soils: A review of the current and potential methods for routine use

AbstractLiming is one of the key agronomic practices to improve crop yields in acid soils because, among other things, it reduces aluminum toxicity and creates favorable conditions for crop growth. For an effective liming program, the methods to determine lime requirement should be as precise as possible. This paper reviews the existing lime requirement methods and discusses the potential of a new one suitable for routine use in the laboratory to test most agricultural soils. The most widely used lime requirement methods can be categorized into four groups: titration, incubation, buffer, and field methods. Other methods such as spectroscopy method or the use of empirical equations have also been adopted. Although some methods are highly reliable, they are not optimal for routine use because they are inconvenient during the laboratory procedures or cannot be validated for all conditions. Based on the linearity between soil pH and the added base in the pH range from 4.5–6.5 in most agricultural soils, a titration‐based method on 1:1 soil:0.01 M CaCl2 slurry of a single sample appears to be a promising candidate for routine use. In further studies, this generally applicable method should be evaluated to provide a better comparison to established methods for lime requirement determination.

Evaluating buffer methods for determining lime requirement on acidified agricultural soils of the Palouse

AbstractAcidification of agricultural soils under intense management in the Palouse region of eastern Washington and northern Idaho is of increasing concern. Buffer methods can provide lime requirement estimates (LREs); however, locally calibrated methods are lacking. Our objective was to evaluate buffer methods and to determine which can produce optimal LREs for Palouse agricultural soils. Samples from 10 regionally dominant agricultural soils (initial pH ≤5.3) were assessed for pH changes after incubation with nine levels of calcium carbonate (CaCO3) for 90 d under laboratory conditions. Achieving a target pH of 6 in the top 15 cm of the soil profile required 3.36–8.36 Mg ha−1 of CaCO3. Laboratory incubation results were compared with LREs calculated from 10 established calibrations using data from seven buffer methods: Shoemaker–McLean–Pratt (SMP), Adams and Evans (AE), Woodruff 6, Woodruff 7, Western Region Woodruff 7, Sikora, and Modified Mehlich (MM). The SMP (R2 = .47) and AE (R2 = .56) calibrations demonstrated the lowest correlation with observed incubation lime requirement (LR) and are not recommended for use on Palouse soils. The MM (R2 = .90), Woodruff 6 (R2 = .78), and Woodruff 7 (R2 = .75) buffer calibrations produced the strongest correlation between LREs and the LRs determined by laboratory incubation. Combining organic matter (OM) with KCl‐extractable aluminum (KCl‐Al) or soil pH was also predictive of LR (R2 = .72) in a stepwise multivariate analysis. The recommendation from this study is to assess LR on Palouse soils using the MM buffer or to use soil analytical results and compute LR from OM and KCl‐Al or pH.

New methods for estimating lime requirement to attain desirable pH values in Brazilian soils

In Brazil, empirical models are traditionally used to determine lime requirement (LR), but their reliability is doubtful in most cases, since they can lead to under- or overestimation of LR for different soil types. In this study, the most critical characteristics influencing LR were selected to develop reliable models for predicting LR that raise soil pH to optimum values for crop production in Brazil. Soil samples (n = 22) with varying proportions of clay (5-88 %) and organic matter [...]

Base Neutralizing Capacity of Agricultural Soils in a Quaternary Landscape of North-East Germany and Its Relationship to Best Management Practices in Lime Requirement Determination

Despite being a natural soil-forming process, soil acidification is a major agronomic challenge under humid climate conditions, as soil acidity influences several yield-relevant soil properties. It can be counterbalanced by the regular application of agricultural lime to maintain or re-establish soil fertility and to optimize plant growth and yield. To avoid underdose as well as overdose, lime rates need to be calculated carefully. The lime rate should be determined by the optimum soil pH (target pH) and the response of the soil to lime, which is described by the base neutralizing capacity (BNC). Several methods exist to determine the lime requirement (LR) to raise the soil pH to its optimum. They range from extremely time-consuming equilibration methods, which mimic the natural processes in the soil, to quick tests, which rely on some approximations and are designed to provide farmers with timely and cost-efficient data. Due to the higher analytical efforts, only limited information is available on the real BNC of particular soils. In the present paper, we report the BNC of 420 topsoil samples from Central Europe (north-east Germany), developed on sediments from the last ice age 10,000 years ago under Holocene conditions. These soils are predominantly sandy and low in humus, but they exhibit a huge spatial variability in soil properties on a small scale. The BNC was determined by adding various concentrations of Ca(OH)2 and fitting an exponential model to derive a titration curve for each sample. The coefficients of the BNC titration curve were well correlated with soil properties affecting soil acidity and pH buffer capacity, i.e., pH, soil texture and soil organic matter (SOM). From the BNC model, the LRs (LRBNC) were derived and compared with LRVDLUFA based on the standard protocol in Germany as established by the Association of German Agricultural Analytic and Research Institutes (VDLUFA). The LRBNC and LRVDLUFA correlated well but the LRVDLUFA were generally by approximately one order of magnitude higher. This is partly due to the VDLUFA concept to recommend a maintenance or conservation liming, even though the pH value is in the optimum range, to keep it there until the next lime application during the following rotation. Furthermore, the VDLUFA method was primarily developed from field experiments where natural soil acidification and management practices depressed the effect of lime treatment. The BNC method, on the other hand, is solely based on laboratory analysis with standardized soil samples. This indicates the demand for further research to develop a sound scientific algorithm that complements LRBNC with realistic values of annual Ca2+ removal and acidification by natural processes and N fertilization.

Mid-infrared spectroscopy as an alternative to laboratory extraction for the determination of lime requirement in tillage soils

Lime is a crucial soil conditioner to bring agricultural soils to optimum pH values for nutrient availability. Lime recommendations are typically determined in laboratory extractions, the most common being the “Shoemaker-McLean and Pratt” (SMP) buffer method, that requires carcinogenic reagents soon to be abolished under the EU legislation. As an alternative to wet chemistry, mid-infrared (MIR) spectroscopy has shown to be a cost-and time effective method at predicting soil properties. The capability and feasibility of diffuse reflectance infrared spectroscopy (DRIFTS) to predict lime requirement (LR) in tillage fields is examined. Samples from 41 cereal tillage fields (n = 655) are used to build a calibration for DRIFTS using partial least squares regression (PLSR). The samples were split into calibration set (31 fields, n = 495) and validation set (10 fields, n = 160). After pre-processing with trim, smoothing and standard normal variate, a calibration model using 6 latent variables, provided R2 of 0.89 and root mean square error of cross-validation (RMSECV)of 1.56 t/ha. Prediction of all fields from the validation set resulted in R2 of 0.76 and root mean square error of prediction (RMSEP) of 1.68 t/ha. The predictions of the single fields ranged from R2 values of 0.41 to 0.72, RMSEP of 0.48 to 4.2 t/ha and ratios of performance to inter-quartile distance (RPIQ) of 0.45 to 3.56. It was shown that the signals of soil constituents having an influence on the LR were picked up in the spectra and were identified in the loading weights of the PLSR. While the error is too high to predict the variability of LR within the field, MIR prediction using field averages provided a viable alternative to current laboratory methods for blanket spreading of lime on tillage fields.

Rapid determination of lime requirement by mid‐infrared spectroscopy: A promising approach for precision agriculture

AbstractMid‐infrared spectroscopy (MIRS) has proven to be a cost‐effective, high throughput measurement technique for soil analysis. After multivariate calibration mid‐infrared spectra can be used to predict various soil properties, some of which are related to lime requirement (LR). The objective of this study was to test the performance of MIRS for recommending variable rate liming on typical Central European soils in view of precision agriculture applications. In Germany, LR of arable topsoils is commonly derived from the parameters organic matter content (SOM), clay content, and soil pH (CaCl2) as recommended by the Association of German Agricultural Analytical and Research Institutes (VDLUFA). We analysed a total of 458 samples from six locations across Germany, which all revealed large within‐field soil heterogeneity. Calcareous topsoils were observed at some positions of three locations (79 samples). To exclude such samples from LR determination, peak height at 2513 cm−1 of the MIR spectrum was used for identification. Spectra‐based identification was accurate for carbonate contents > 0.5%. Subsequent LR derivation (LRSPP) from MIRS‐PLSR predictions of SOM, clay, and pH (CaCl2) for non‐calcareous soil samples using the VDLUFA look‐up tables was successful for all locations (R2 = 0.54–0.82; RMSE = 857–1414 kg CaO ha−1). Alternatively, we tested direct LR prediction (LRDP) by MIRS‐PLSR and also achieved satisfactory performance (R2 = 0.52–0.77; RMSE = 811–1420 kg CaO ha−1; RPD = 1.44–2.08). Further improvement was achieved by refining the VDLUFA tables towards a stepless algorithm. It can be concluded that MIRS provides a promising approach for precise LR estimation on heterogeneous arable fields. Large sample numbers can be processed with low effort which is an essential prerequisite for variable rate liming in precision agriculture.

Saturação por bases para o cafeeiro baseada no ph do solo e no suprimento de Ca e Mg

O método da saturação por bases, utilizado para determinação da necessidade de calagem (NC), pode gerar doses inadequadas, uma vez que a saturação por bases esperada (Ve) é fixa, independentemente do tipo de solo. O objetivo do trabalho foi estabelecer valores adequados de saturação por bases esperada (Ve) para os cafeeiros arábica e conilon decorrentes da relação existente entre essa característica, o pH e o suprimento de Ca e Mg para as plantas, em solos com diferentes classes de CTC pH 7,0 (T). Foram analisadas quimicamente 599 amostras de solos sob café, sendo determinadas suas características químicas. Foi realizada análise de correlação linear e selecionadas equações que melhor representassem a relação entre o pH e V. Foram estimadas saturações por bases que estariam relacionadas a valores de pH sugeridos para os cafés arábica e conilon, bem como ao suprimento adequado de Ca e Mg, considerando solos com CTC pH 7,0 classificada como baixa, média ou boa. A relação existente entre pH do solo e V não é linear. Para um mesmo pH, o valor de V varia de acordo com a CTC pH 7,0 do solo. Foram estabelecidas distintas equações que relacionam pH e V, considerando a classe de CTC pH 7,0. Recomendam-se os seguintes valores de saturação por bases esperada (Ve) para o cafeeiro, de acordo com a classe de CTC pH 7,0 do solo (T): Ve = 90% (T baixa: TBa< 4,30 cmolc dm-3), Ve = 70% (T média: 4,30 < TM< 8,60 cmolc dm-3) e Ve = 60% (T boa: 8,60 < TBo< 15,00 cmolc dm-3).

Classical Methods and Calculation Algorithms for Determining Lime Requirements

The methods developed for determination of lime requirements (LR) are based on widely accepted principles. However, the formulas used for calculation have evolved little over recent decades, and in some cases there are indications of their inadequacy. The aim of this study was to compare the lime requirements calculated by three classic formulas and three algorithms, defining those most appropriate for supplying Ca and Mg to coffee plants and the smaller possibility of causing overliming. The database used contained 600 soil samples, which were collected in coffee plantings. The LR was estimated by the methods of base saturation, neutralization of Al3+, and elevation of Ca2+ and Mg2+ contents (two formulas) and by the three calculation algorithms. Averages of the lime requirements were compared, determining the frequency distribution of the 600 lime requirements (LR) estimated through each calculation method. In soils with low cation exchange capacity at pH 7, the base saturation method may fail to adequately supply the plants with Ca and Mg in many situations, while the method of Al3+ neutralization and elevation of Ca2+ and Mg2+ contents can result in the calculation of application rates that will increase the pH above the suitable range. Among the methods studied for calculating lime requirements, the algorithm that predicts reaching a defined base saturation, with adequate Ca and Mg supply and the maximum application rate limited to the H+Al value, proved to be the most efficient calculation method, and it can be recommended for use in numerous crops conditions.

Adaptation of regional digital soil mapping for precision agriculture

In the initial phase of a national project to map clay, sand and soil organic matter (SOM) content in arable topsoil in Sweden, a study area in south-west Sweden comprising about 100 000 ha of arable land was assessed. Models were created for texture, SOM and two estimated variables for lime requirement determination (target pH and buffering capacity), using a data mining method (multivariate adaptive regression splines). Two existing reference soil datasets were used: a grid dataset and a dataset created for individual farms. The predictor data were of three types: airborne gamma-ray spectrometry data, digital elevation from airborne laser scanning, and legacy data on Quaternary geology. Validations were designed to suit applicability assessments of prediction maps for precision agriculture. The predictor data proved applicable for regional mapping of topsoil texture at 50 × 50 m2 spatial resolution (root mean square error: clay = 6.5 %; sand = 13.2 %). A novel modelling strategy, ‘Farm Interactive’, in which soil analysis data for individual farms were added to the regional data, and given extra weight, improved the map locally. SOM models were less satisfactory. Variable-rate application files for liming created from derived digital soil maps and locally interpolated soil data were compared with ‘ground truth’ maps created by proximal sensors on one test farm. The Farm Interactive methodology generated the best predictions and was deemed suitable for adaptation of regional digital soil maps for precision agricultural purposes.

Evaluation of Modified Mehlich and Sikora Buffer Methods as an Alternative to Modified Woodruff Buffer in Determining Lime Requirement for Missouri Soils

The modified Woodruff buffer (MWB) test is used to determine lime requirement (LR) for Missouri soils. Though this method is proven to work for Missouri soils, it uses p-nitrophenol, which is a hazardous substance. Soil-testing laboratories are under increasing pressure to reduce hazardous wastes, which must be collected and disposed of following U.S. Environmental Protection Agency protocols. The goal of this study was to evaluate the modified Mehlich buffer (MMB) and the Sikora buffer (SB) as alternatives to the MWB in determining the LR for Missouri soils. Thirty soils were collected from major agricultural areas in Missouri, treated with calcium carbonate (CaCO3), and incubated for 90 days. Soil pHs [0.01 M calcium chloride (CaCl2) 1:1] was regressed against CaCO3 rate, and the actual LR was estimated for each soil to raise the soil pHs to target levels of 5.8, 6.3, and 6.8. The MWB, MMB, and SB pHs were regressed against the actual LR for all 30 soils to evaluate the effectiveness of each test for estimating the LR. The MMB and SBs were found to be as good as or better than MWB in predicting LR in Missouri soils. Both buffers (MMB and SB) were found to be equally effective in generating accurate estimates of the LR to raise soils to pHS 5.8, 6.3, and 6.8 (for pH values 5.8: R2 = 0.76, 0.82, 0.81; for pH values 6.3: R2 = 0.80, 0.88, 0.86; and pH values 6.8: R2 = 0.77, 0.89, 0.87 for MWB, MMB, and SB, respectively). A test to evaluate the stability of the buffers over time indicated that MMB had the shortest bench life (about 21 days) when compared to the MWB and SB, thus making it less feasible for use by soil test laboratories. Based on performance and stability, SB is a better alternative than MWB for Missouri soils.

Grouping Soils by Taxonomic Order to Improve Lime Recommendations

The success of a liming program is dependent upon the accuracy of the lime recommendation, which in turn depends on the quality of the underlying correlations and calibrations. Because of the expense, large-scale field calibration experiments are rarely conducted. The relatively low economic returns from pastures make it even more unlikely that a calibration experiment would be conducted, especially in West Virginia. Therefore, any improvements in lime recommendations have to be made from lime correlations. Moreover, it is unlikely that a single lime correlation can accurately identify appropriate lime rates for all soils. Hence, the objectives of this study were to improve the accuracy of lime recommendations by using quick tests that account for soil order and to develop lime correlations for acidic pasture soils of West Virginia. Twenty-five surface soil samples (0–7.5 cm) from the three major soil orders in the state (Alfisols, Inceptisols, Ultisols) were collected, most in cooperation with state soil scientists. Standard procedures for the determination of lime requirements by the Adams–Evans buffer (AEB), Mehlich single buffer (MB), and Shoemaker–McLean–Pratt single buffer methods (SMPB) were used. Statistically significant improvements in lime recommendations for target pH values of 6.5 and 5.5 were achieved by accounting for soil order. Mehlich single buffer recommendations were better for Alfisols and Ultisols than for Entisols to achieve pH 6.5. Lime correlations were developed for all three chemical buffers by multiple regression where the independent variables were target pH and soil-buffer pH. The AEB predicted lime rates better for target pH 5.5.

The Moore–Sikora Buffer for Lime Requirement Determinations

Paranitrophenol in the Adams–Evans (AE) buffer used for determining lime requirement (LR) is considered a hazardous chemical due to its toxicity. The Moore–Sikora (MS) buffer, which mimics AE soil‐buffer pH, was developed without hazardous chemicals and is currently used for routine soil testing at Clemson University. The MS buffer was designed by considering probable chemicals with pKa values in the desired pH range, potential reaction of the components with soil, and longevity of the buffer during storage. Boric acid, 3‐(N‐morpholino)propanesulfonic acid (MOPS), and 2‐(N‐morpholino)ethanesulfonic acid hydrate (MES) were considered for the new buffer. Once chemicals were identified, a technique of finding appropriate concentrations was utilized by using an equation that could predict the acid titration of a buffer and refining pKa and concentration values until a match was found with measured pH titrations of the AE buffer. The MS buffer contains 212, 131, and 34.8 mmol L−1 of B(OH)3, MOPS, and MES, respectively. The buffer also contains 200 mmol L−1 KOH and 1 mol L−1 KCl. The MS buffer was compared with the AE buffer for determining soil‐buffer pH values on 222 South Carolina soils and 41 North American Proficiency Testing Program soils. The MS soil‐buffer pH was strongly related to AE soil‐buffer pH (r2 > 0.98). Soil‐buffer pH was slightly less with MS buffer than AE buffer, with a mean difference of 0.03 pH units. The lower soil‐buffer pH with MS buffer caused a slightly higher LR than the AE buffer, with a mean difference of 0.34 Mg ha−1 on South Carolina soils. Forty‐four percent of the samples indicating a need for lime did not have a difference in LR between the two buffers. The slightly higher LR with the MS buffer on some of the samples is not expected to raise soil pH too high above target pH values.

A Buffer that Mimics the SMP Buffer for Determining Lime Requirement of Soil

The Shoemaker‐McLean‐Pratt (SMP) buffer used for determining lime requirement of soil contains chromium and p‐nitrophenol, which classifies the solution as a hazardous waste. A buffer without hazardous chemicals producing the same pH as SMP buffer would eliminate hazardous waste and have no effect on agronomic interpretation. Chemicals chosen to replace chromium and p‐nitrophenol were 2‐(N‐morpholino)ethanesulfonic acid monohydrate (MES) and imidazole. Acid titrations of SMP buffer and various mixtures of a new buffer were performed to duplicate the acid‐base characteristics of the SMP buffer. The new buffer is adjusted to pH 7.70 and contains 69.6, 13.7, 31.4, 89.3, and 2000 mM of triethanolamine, imidazole, MES monohydrate, acetic acid, and KCl, respectively. Coefficients of determination (r2) for linear regressions of soil‐buffer pH with the new buffer versus SMP buffer on 255 Kentucky and 87 North American Proficiency Testing (NAPT) soils were 0.974 and 0.967, respectively. The linear regression equation for new buffer versus SMP buffer lime recommendations in Mg ha−1 was y = 0.226 + 0.994x with an r2 of 0.935 for 158 Kentucky soils requiring lime and y = 1.42 + 0.876x with an r2 of 0.876 for 27 NAPT soils requiring lime. Repeated soil‐buffer pH measurements were made using 10 Kentucky soils and 11 NAPT soils over 150 d. Only one of the soil samples showed a significant drift in soil‐buffer pH with time using the new buffer, and the drift was also observed using SMP buffer. With 88 measurements of soil‐buffer pH using the new buffer on 11 NAPT soils, 2 measurements fell outside NAPT warning limits for SMP soil‐buffer pH. The new buffer without hazardous chemicals mimicked the soil‐buffer pH obtained with SMP buffer, provided lime recommendations similar to that with SMP buffer, and had a laboratory shelf life of at least 150 d.

Using pH-dependent CEC to determine lime requirement

Controlling soil pH is important to ensure good crop yield. This study was conducted to determine whether the accuracy of the existing Shoemaker-McLean-Pratt (SMP) pH-buffer method could be improved by using the pH-dependent cation exchange capacity curve (CECpd). Soil pH, SMP and CECpd measurements were performed on 18 acid surface horizon soil samples, with textures from sandy loam to clay loam. These soils were incubated with three levels of calcium carbonate for 12 wk, after which the soil pH and the effective cation exchange capacity (CECe) were measured. The correlation coefficient (R2) for the CECpd and CECe curves was 0.96. The main factor affecting the slope of the curves is the soil organic matter content. The increase of CECe in the soil was also found to be directly proportional to the amount of lime applied, regardless of the type of soil. By using the slope of the Qv versus pH curve for each soil and the relationship between CECe and lime application, we were able to determine the lime required to raise the soil pH in water to 6.5. As an alternative to the current practice of using the SMP buffer, we propose that it should be possible to estimate the pH-dependent CEC curve from measurable soil properties (e.g., organic matter) and to estimate the lime requirement as the difference in CECpd between the existing and desired pH values. Once the slope of the Qv/pH relationship has been determined or estimated for a soil, the only measurement necessary for calculating lime requirement in subsequent years would be the soil pH. The proposed method would provide lime requirement estimates while decreasing the annual cost of soil analysis. Key words: Lime requirement, cation exchange capacity, Non-Ideal Competitive Adsorption, soil properties, organic matter, Fe oxides

A Modification to the Adams‐Evans Soil Buffer Determination Solution

Many soil analysis labs routinely determine lime requirement of acidic soils using different buffer solutions for optimum plant growth. The Adams‐Evans lime determination solution was introduced more than 40 years ago and has been used by many soil analysis labs. Even though many buffer solutions have been developed since then, very little attention has been paid to address the toxic nature of chemicals involved in buffer solutions. The most commonly used buffer solutions, such as the Adams-Evans, Shoemaker‐McLean‐Pratt (SMP), Woodruff, and others, contain p‐nitrophenol, which is toxic to humans and the environment. Use of p‐nitrophenol requires prescribed containment and disposal procedures, that creates extra burden on soil analysis labs that provide their invaluable service at low cost. Replacing p‐nitrophenol with monobasic potassium phosphate (KH2PO4), which has similar buffering capacity but with no known toxicity, is beneficial to soil testing labs and the environment. The original Adams‐Evans buffer solution was compared with the modified Adams‐Evans buffer solution with soils of different pH, cation exchange capacity and lime requirement. The linear regression between the buffer pH values and lime recommendations made by Adams‐Evans and the modified Adams‐Evans solutions were highly significant. Thus, the modified Adams‐Evans buffer solution can be used without loss of established recommendation criteria as the original buffer solution.

Comparison of Two Methods of Lime Requirement Determination

Two lime requirement (LR) estimation methods i.e. (Adams‐Evans [AE] and Shoemaker, McLean, and Pratt [SMP] Single‐Buffer Methods) were tested in 138 acid soils from Greece that ranged widely in pH (4.5–6.4), organic matter (0.23–3.38%), and clay content (7–47%). LR rates estimated by Adams‐Evans method (LRAE) were lower than those estimated by the SMP method (LRSMP). However, both methods overestimated the LR of the soils. Soil pH, clay, and organic matter content were the main soil factors affecting the LR rates. These factors explained about 70% of LR variation estimated by the AE method in soils containing 15–30% clay. The same factors explained about 38% of the LR variation estimated by the SMP method. From the results of this study it was concluded that the Adams‐Evans method gives a more reliable estimation of LR of these acid soils.

Soil pH Variation Within a Soil. III. pH Variation in Limed Soil

There are many methods for determining lime requirement, but no single method is suitable for all soils. A fast and efficient method to evaluate lime effect is needed. Soil buffering capacity tests and column-leaching tests were applied to the limed Van Rockel soil at the depth of 0–30 cm to evaluate pH distribution after liming. Two groups of the Van Rockel soil were taken for soil buffering capacity test and two replicates were applied to each column-leaching test. The objective of this study was to evaluate some relationships in pH variation in soil after liming. The buffering capacity of a soil depends on the rate of acidification of the soil. Equilibrium of pH value was reached at about collector #7 after which there was no change of pH value. It was concluded that pH differentials of the lowest and the highest fractions of 0.5 units indicated that liming had an influenced effect. Although adequate, more lime decreased soil pH differential not less than 0.3 units in all fractions.

Comparison of Laboratory pH Buffer Methods for Predicting Lime Requirement for Acidic Soils of Eastern Botswana

The suitability of pH buffer methods that determine lime requirement (L.R.) of acid soils of the eastern region of Botswana has not been determined, and the soil physiochemical properties that influence L.R. are not known. As a result, a number of laboratory pH buffer methods for determining L.R. were evaluated by using acid soils from that region. The methods evaluated were the Yuan double buffer (Yuan–DB) method, Shoemaker, McLean, and Pratt double, and single buffer (SMP–DB and SMP–SB) methods, and the Adams, and Evans single buffer (AE–SB) method. The evaluation was based on the ability of the methods to predict the actual L.R. to pH 6.5 determined by the soil–CaCO3–moist–incubation (SCMI) method. The incubation, physiochemical properties, and L.R. by laboratory pH buffer methods were determined in triplicates. All the pH buffer methods were (P < 0.001) significantly correlated (0.79 < r < 0.94) with the SCMI method. The performance was in the order of Yuan–DB method > SMP–DB method > SMP–SB method > AE–SB. However, the SMP–SB has been recommended for routine analysis of soils of eastern Botswana, because it is simple and rapid. The relationship between SCMI method actual L.R. and the physiochemical properties (0.55 < r < 0.71) reveals that the buffer capacity, organic carbon, exchangeable acidity, and extractable aluminum are the most important soil properties influencing L.R. of soils in eastern Botswana.