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Journal of Soils and Sediments ISSN 1439-0108Volume 18Number 2 J Soils Sediments (2018) 18:610-623DOI 10.1007/s11368-017-1773-6

Assessment of potassium speciation insoil using traditional single leaching andmodified sequential extraction processes

Chakkrit Poonpakdee, Jing-Hua Tzeng,Chih-Huang Weng & Yao-Tung Lin

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SOILS, SEC 5 • SOIL AND LANDSCAPE ECOLOGY • RESEARCH ARTICLE

Assessment of potassium speciation in soil using traditional singleleaching and modified sequential extraction processes

Chakkrit Poonpakdee1 & Jing-Hua Tzeng1 & Chih-Huang Weng2 & Yao-Tung Lin1

Received: 26 April 2017 /Accepted: 23 June 2017 /Published online: 1 July 2017# Springer-Verlag GmbH Germany 2017

AbstractPurpose The bioavailability of potassium (K) depends on itsspeciation distribution in the soil. Different methods are com-monly used to estimate K speciation including traditional sin-gle leaching (TSL) and sequential extraction process (SEP).However, K speciation is largely affected by soil pretreatmentmethods. The effects of both TSL and SEP soil pretreatmentmethods were evaluated.Materials and methods The TSL method classifies K specia-tion content based on bioavailability, while the SEP classifiesthe metal speciation based on the effects of environmentalconditions. These two methods, together with a modified se-quential single leaching (SSL) scheme, were used to evaluatefive types of soil including soil without potassium fertiliza-tion, soil with long-term K fertilization, alkaline soil, red soil,and forest soil. The soil samples were gathered randomly atdepths varying up to 30 cm before being dried in air at roomtemperature. The samples were then ground and mixed beforepassing through a sieve (10 mesh or 100 mesh) in order toperform K speciation analysis via the modified SSL tech-nique, the TSL method, and the four schemes of SEP.

Results and discussion Soil pretreatment influenced K speci-ation, with higher concentration in soil samples sievedthrough 100 mesh than through 10 mesh. In alkaline soil,potassium was observed to be associated with carbonate. Forthe various SEP schemes, K speciation was found to begreatest in the residual fraction, with only 3% observed inthe carbonate, exchangeable, metal organic complex, or amor-phous hydroxides of Fe or Mn. After following the first twosteps of the SEP schemes, the available K was similar to thatof the TSLmethod. Distribution of non-exchangeable K usingthe TSL method was comparable with the five combined SEPextraction steps which were all affected by environmentalconditions.Conclusions Pretreatment affected K speciation distributionand total amount of metal in the soil. The 100 mesh sievewas more effective in estimating K soil speciation. The SEPmethod was acceptable for estimating K speciation, with theKrishnamurti et al. (Analyst 120:659–665, 1995) scheme as auseful appraisal of K bioavailability. Combination analysesusing both TSL and SEP methods are useful techniques toenable a better understanding of K speciation transformationin soil.

Keywords Potassium . Sequential extraction process . Singleleaching . Soil fertility . Soil pretreatment

1 Introduction

Potassium (K) is crucial for sustaining life on Earth. It is also avital macronutrient to support the growth of plants. In soil, Kmay be present in several different species which bind to thesoil components. The distribution of K species in soil has amajor effect on its behavior regarding bioavailability, mobili-ty, and potential toxicity (Manouchehri et al. 2014). Methods

Responsible editor: Renduo Zhang

Electronic supplementary material The online version of this article(doi:10.1007/s11368-017-1773-6) contains supplementary material,which is available to authorized users.

* Yao-Tung Linyaotung@nchu.edu.tw

1 Department of Soil and Environmental Science, National ChungHsing University, Taichung 40227, Taiwan

2 Department of Civil and Ecological Engineering, I-Shou University,Kaohsiung 84008, Taiwan

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are commonly used to estimate K speciation including tradi-tional single leaching (TSL) and sequential extraction process(SEP). In these analytical techniques, identification of K spe-ciation in soil is a tedious process, which consists of pretreat-ment, wet chemical extraction, and quantification. In the soilpretreatment stage, the samples underwent air drying at roomtemperature before they were ground and mixed. The sampleswere then passed through a sieve. Soil particles finer than<2 mm (10 mesh sieve) were routinely analyzed for physico-chemical characteristics (Jones, 2001; Chelabi et al. 2016).For speciation analysis, the literature suggested that the soilsamples should be finer and passed through a sieve higherthan 10 mesh (Kalembkiewicz and Soco 2002; Tokalıoğluand Kartal 2005; Palumbo-Roe et al. 2015; Zhang et al.2017). Soil that passed through a 100 mesh sieve was ana-lyzed for metal speciation with acceptable results (Lin et al.2011; Duan et al. 2016; Sun et al. 2016). Because elementquantification is affected by the degree of soil grinding inthe pretreatment stage (Petrofanov 2012; Chelabi et al.2016), soil particle size distribution may display spatial het-erogeneity in K speciation.

Chemical analyses were the chief means of soil diagnosisto determine the direct relationship between soil nutrient avail-ability and plant growth. Speciation analysis techniques havebeen studied by wet chemical extraction for both single andmultiple step processes (Anju and Banerjee 2011;Manouchehri et al. 2014). In the studied processes, the com-ponents of the extractant are essentially similar; nonetheless,speciation products can be different.

Traditional single leaching (TSL) serves a one-step ap-proach to K speciation for individual analysis. On the basisof its bioavailability (whether it involves mineral K, non-exchangeable K, exchangeable K, and water-soluble K), thistechnique can be applied to classify K speciation. In the caseof available K (water-soluble K and exchangeable K), a TSLreagent to estimate the available K that was developed overseven generations (Table S1, Electronic SupplementaryMaterial). The first reagent (1 M ammonium acetate at a pHvalue of 7.0) was applied (Schollenberger and Simon 1945),but this technique was later altered using the Morgan solution(Morgan, 1941), Mehlich no. 1 (Mehlich 1953), pure water(Bower and Wilcox 1965), 1 M ammonium bicarbonate in0.005 M DTPA at a pH value of 7.6 (Soltanpour andSchwab 1977), Mehlich no. 3 (Mehlich 1984), or 0.01 Mcalcium chloride (Houba et al. 1990). Although different ap-proaches are feasible, the most widely used extractant nowa-days when establishing the available K is 1 M ammoniumacetate at a pH value of 7.0 (Brady and Weil 2008;Schneider et al. 2013). Nevertheless, a total metal analysis isinsufficient to obtain information relevant to the various metalforms. Although the TSL method is most commonly appliedfor speciation analysis in soil science studies, some of thereagents used in the TSL method can extract K from more

than one fraction. Another drawback of the TSL method isthat the analytical results can not reflect the influence of envi-ronmental conditions on K speciation.

The sequential extraction process (SEP) is a continual mul-tistep analysis used for evaluating various element-bindingforms (Vojtekova et al. 2003). The SEP aims to imitate themanner in which the weakly bound to the strongly boundselected target phase is released with a crystalline structurethat is affected by environment conditions (Tessier et al.1979). The SEP approach gives information about the metalfractionation which takes place throughout the various latticeswithin a given soil sample. While techniques may vary slight-ly (Tessier et al. 1979; Shuman 1983; Ure et al. 1993;Krishnamurti et al. 1995), the SEP approach defines up toeight separate categories for speciation: exchangeable, car-bonate, easily oxidizable, easily reducible, moderately reduc-ible, oxidizable oxides and sulfides, poorly reducible, and re-sidual forms. While the SEP approach was developed in orderto analyze trace metals (Tessier et al. 1979), it can also belegitimately applied to estimate heavy metals (Nielsen et al.2015; Xia et al. 2016; Gope et al. 2017; Xu et al. 2017).Furthermore, the approach has been shown to be effective inestimating non-trace elements including iron (Larner et al.2006), aluminum (Dai et al. 2011), magnesium (Luo et al.2011), and also phosphorus (Wang et al. 2013).

There are in excess of 13,768 published literatures relevantto K speciation up to April 24, 2017. Most researchersemployed the TSL method for analyzing and comparing Kspeciation using different reagents; however, comparisons be-tween the TSL and SEP methods were not ever discussed.This paper is the first to compare K speciation results obtainedfrom TSL and SEP methods using different soil pretreatmentsthrough 10 and 100 mesh filters. Potassium speciation analy-sis by the TSL and SEP methods can lead to a better under-standing and identification of the transformation methods forK speciation in soil. Potassium speciation in two different soilpretreatments was evaluated and compared for five soil typesby both TSL and SEP methods.

2 Materials and methods

2.1 Soil collection and pretreatment

Five types of soil were selected in Taiwan, four from farmingplantations after crop harvest, and one from a forest area. Thesoil samples were subjected to different management practicesand comprised soil without K fertilization (10-year period noK fertilizer), soil with long-term K fertilization (10-year peri-od using 168–240 kg of K2O per hectare per year), red soil(using 450–500 kg of K2O per hectare per year), alkaline soil(using 164 kg of K2O per hectare per year), and soil from theforest (Table S2, Electronic Supplementary Material). Every

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soil sample used in the study was gathered from depths vary-ing up to 30 cm, and the samples were dried in air at roomtemperature, ground, mixed, and passed through 10 mesh(particle sizes <2 mm) or 100 mesh (particle sizes<0.149 mm) stainless steel sieves to remove large litter andgravel.

2.2 Reagents and quality control

All reagents used to prepare the extracting solution were ana-lytical grade. All solutions and dilutions were prepared usingdouble deionized water (DI water; 18.2 MΩ cm−1). The prep-aration of all working standard K solutions was performed viadilution using a certified standard solution (1000 mg K L−1,Merck, Germany). Working standards of varying K concen-trations were matrix-matched with the extraction solutions toreduce matrix effects. Blanks and extractions were carried outin triplicate. In addition to matrix-matching, both QC (qualitycontrol) and blank solutions were analyzed in order to assessvariables such as accuracy and precision, which can be affect-ed by instrument drift. Every item of glassware or plasticequipment used in the laboratory was soaked overnight in5% (v/v) HNO3 before rinsing in deionized water.

2.3 Soil physicochemical properties analysis

Soil physicochemical properties were assessed using the stan-dard method (Jones, 2001). Initially, the pH value of the soilwas measured along with electrical conductivity (EC) within1:5 w/v (soil/DI water). Cation exchange capacity (CEC) wasdetermined by saturating the exchange sites with 1 MNH4OAc at a pH value of 7.0. The Walkley-Black methodwas then applied to determine the organic matter (OM) con-tent. The Bray II technique was applied to establish the avail-able phosphorus, and the Kjeldahl method was used to mea-sure the total nitrogen level. The hydrometer method assessedthe distribution of particle sizes, while X-ray diffraction(XRD) patterns of the clay minerals were derived via Cu Kαradiation, under a scanning range between 3° and 70°(Rezapour et al. 2009).

2.4 Traditional single leaching

The approach of Helmke and Sparks (1996) was appliedfor the TSL method. Determination of water-soluble Kwas achieved through the extraction of 5 g of soil using25 mL deionized water, which was subsequently shakenfor 5 min. In contrast, the determination of available K asexchangeable K and water-soluble K was achievedthrough extraction in 1 M NH4OAc at a pH value of7.0. The determination of HNO3-K, or HNO3 extractableK, was achieved through boiling 2.5 g of soil in 25 mL of1 M HNO3 for 25 min at a temperature of 113 °C. This

HNO3-K comprised both non-exchangeable K and avail-able K. It was determined that non-exchangeable K rep-resents the difference between available K and HNO3-K.The total K was then digested in a Teflon beaker usingconcentrated hydrogen fluoride (HF) and aqua regia(HNO3/HCl; 1:3 v/v). The difference between total Kand HNO3-K was held to be mineral K.

2.5 Sequential extraction process

Four different SEP schemes such as Tessier et al.(1979), Shuman (1983), BCR (Bureau Communautairede Référence), Ure et al. (1993), and Krishnamurtiet al. (1995) were used according to the protocol or intheir modified form to determine residual K in the finalstep. Extraction details are shown in Tables S3, S4, S5,and S6 (Electronic Supplementary Material). One gramof soil sample with three replicates was weighed andsuspended in the corresponding extractant in 50 mLTeflon centrifuge tubes. Each suspension was centri-fuged at relative centrifugal force (RCF) 1588×g for10 min. The supernatant was then extracted using adropper, and then filtered before the K concentrationwas measured. Following extraction, the soil was thencleaned using 10 mL of deionized water and thenplaced in the centrifuge. In order to remove any remain-ing reactant, the second supernatant was removed. Thesubsequent reagent was added to extract the next Kspeciation. After the final speciation extraction, soil par-ticles were moved to a Teflon beaker and subsequentlydigested following the addition of concentrated HClO4

and HF to determine the residual K.

2.6 SSL

This method was modified by mixing the TSL and SEPmethods. One gram of soil sample was weighed into a50-mL Teflon centrifuge tube. The reagents used werethe same as for the TSL method, but we utilized thesequence extraction from the SEP method to establishthe levels of water-soluble K, exchangeable K, non-exchangeable K, and mineral K. Following the removalof the non-exchangeable K, soil particles were trans-ferred to Teflon beakers for digestion to measure min-eral K.

2.7 Measurement of K concentration

All the solutions for K speciation were measured by anatomic absorption spectrophotometer (AAS) to quantifythe K concentration. The detection limit (DL) of K con-centration was 0.018 μg mL−1. The K speciation obtain-ed by SEP was calculated according to the steps

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specified in Table 1 in order to make a comparison withthe TSL method resul ts for avai lable K, non-exchangeable K, and mineral K. Analytical results werevalidated through the recovery test as preferable forcontrolling the accuracy of the methods studied. Thepercentage of K recovery was measured relative to totalK and obtained by a single digestion using the TSLmethod. The K recovery was defined as

K recovery %ð Þ ¼ ∑nSequential extractionTotal K

� 100

where n is the concentration of a speciation. K recov-eries based on the analysis of all the SEP schemes werewithin 5% error of the TSL certified values. The accu-racy of K recoveries in all methods studied was reason-able, with values in good agreement and ranging from94.6 to 105.4%.

3 Results

3.1 Soil characterization

Soil physicochemical properties are shown in Table 2. Soil pHranged from acidic to alkaline with values between 4.30 and7.59. The EC value ranged between 0.087 and 0.294 dS m−1.Forest soil had the highest CEC (24.18 cmolc kg

−1), OM(35.60 g kg−1), and total nitrogen (1.99 g kg−1). Taken togeth-er, the different soils had CEC values between 10.02 and24.18 cmolc kg−1 and available phosphorus ranged from24.07 to 78.92 mg kg−1 with red soil showing the highest.Exchangeable Ca and Mg content were high in alkaline soiland soil without K fertilization. Soils without K fertilizationand soil long-term K fertilization were classified as sandyloam, whereas red soil, forest soil, and alkaline soil were re-spectively categorized as clay loam, sandy clay loam, and siltyclay. Illite, kaolinite, and chlorite were the dominant clay min-erals among all soils studied.

3.2 Influence of soil pretreatment

Total K concentrations in all soils studied were higher in soilpassed through a 100 mesh than a 10 mesh sieve (Fig. 1). Theratios of total K concentration in soil passed through a 100mesh relative to a 10 mesh sieve indicated that soil pretreat-ment influenced the quantity of total K (Table 3). The averageratio of total K concentration from the various extractionschemes for soil without K fertilization, soil with long-term

Table 1 Steps used to calculate available, non-exchangeable, andmineral K speciation in the four SEP schemes

K speciation SEP steps used to calculate K speciation based onbioavailability

Tessier et al.(1979)

Shuman(1983)

BCR Krishnamurtiet al. (1995)

Available K 1–2 1 1 1–2

Non-exchangeable K 3–4 2–4 2–3 3–7

Mineral K 5 5 4 8

Table 2 Physicochemical properties of the soil samples

Soil property Soil sample

Soil without K fertilization Soil with long-term K fertilization Redsoil

Alkaline soil Forest soil

pH (soil/water; 1:5) 6.16 5.67 4.45 7.59 4.30

EC (dS m−1) 0.099 0.292 0.087 0.294 0.108

OM (g kg−1) 8.83 9.90 15.43 22.63 35.60

Total N (g kg−1) 0.48 0.61 1.08 0.97 1.99

Avai. P (mg kg−1) 45.00 76.58 78.92 60.53 24.07

Exch. Ca (mg kg−1) 511.72 205.69 93.67 950.12 88.00

Exch. Mg (mg kg−1) 74.77 31.04 15.36 117.08 26.34

CEC (cmolc kg−1) 10.02 11.18 18.60 14.35 24.18

Sand (%) 69.81 64.23 44.43 12.83 69.23

Silt (%) 21.15 21.79 17.14 43.97 10.52

Clay (%) 9.04 13.98 38.43 43.20 20.25

Texture Sandy loam Sandy loam Clay loam Silty clay Sandy clay loam

Clay mineral I (32%), K (18%),Ch (14%)

I (38%), K (18%), Ch (19%) I (32%), K (16%) I (41%), K (9%),Ch (5%)

I (33%), K (19%),Ch (16%)

Number in the parentheses represent the clay mineral percentages

I illite, K kaolinite, Q quartz, Ch chlorite

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K fertilization, red soil, alkaline soil, and forest soil was 1.83,1.64, 1.22, 1.97, and 2.01, respectively (Table 3). These ratiosindicated that soil pretreatment by passing it through a 100mesh sieve were high advantage to estimate K speciation.Therefore, the results of K speciation focused only on soilsieved using a 100 mesh sieve.

3.3 Potassium speciation by TSL and SSL

Distributions of the different species of K extracted using ei-ther TSL or SSL method are shown in Fig. 2. Potassium dis-tributions in all soil samples analyzed by SSL were similar tothose analyzed by TSL method. Much of the remaining K was

Fig. 1 Potassium concentration (mg kg−1) in soil samples analyzed by a TSL, b SSL, c Tessier et al. (1979), d Shuman (1983), e BCR, and fKrishnamurti et al. (1995) schemes using soil passed through 10 or 100 mesh sieves. Vertical bars represent the standard deviation (SD)

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seen to be present in the form of mineral K, non-exchangeableK, and available K, respectively. Additionally, the concentra-tion ratios of various K speciations obtained from SSL andTSL in the five types of soil samples ranged from 97.71 to105.77 for available K, 95.34 to 105.16 for non-exchangeableK, and between 96.00 and 99.16 for mineral K (Table 4).

3.4 Potassium fractionation using the SEP

3.4.1 Tessier et al. (1979) scheme

Potassium speciation distribution patterns are illustratedin Fig. 3a. Residual K represented more than 97% oftotal K, while only 3% or less of total K was associatedwith OM (0.21–0.78%), Fe and Mn oxides (0.36–0.60%), carbonate (<detection limit to 0.20%), and ex-changeable K (0.36–1.08%) (Table 5). The exchangeableK fractions were red soil (1.08%), alkaline soil (0.53%),soil with long-term K fertilization (0.44%), forest soil

(0.36%), and soil without K fertilization (0.36%). Theamount of K associated with the carbonate fraction wasbelow the detection limit (0.018 μg mL−1) for soil with-out K fertilization, soil with long-term K fertilization,red soil, and forest soil, but carbonate was recorded inthe alkaline soil (0.20%). Potassium distribution associ-ated with Fe and Mn oxides at 0.36–0.60% was highestin soil without K fertilization (0.60%) and lowest inforest soil (0.36%). Meanwhile, K linked to organicmatter was found in the greatest quantity in red soil(0.78%) and in the smallest amounts in alkaline soil(0.19%). The residual K fraction was considerableamong all K speciation (98.15–98.98%), with forest soil(98.98%) having the highest distribution and red soil(98.15%) the lowest. Different K speciations were cal-culated with respect to their bioavailability (Table 1).Resu l t s i nd i ca t ed tha t ava i l ab l e K and non-exchangeable K distributions were lower than obtainedusing the TSL method (Table 6). Mineral K distributionfollowing Tessier et al. (1979) was higher than obtainedusing the TSL method. Moreover, the portion of total Kin both the Tessier et al. (1979) scheme and the TSLmethod yielded similar results for % recovery (Table 6).

3.4.2 Shuman (1983) scheme

Figure 3b shows distribution patterns of K speciation.Residual K represented more than 97%, while <3%was foundin other fractions including amorphous Fe oxide (0.04–0.15%), Mn oxides (0.20–0.56%), OM (0.16–0.44%), andexchangeable K (0.36–1.17%) (Table 5). The exchangeableK fraction was at its greatest in the red soil (1.17%) whilethe lowest levels were found in soil without K fertilization(0.36%). Potassium associated with OM was found to begreatest in forest soil (0.44%) while the smallest quantitiesappeared in alkaline soil (0.16%). Potassium associated withMn oxide reached its peak in red soil (0.56%) and its mini-mum levels in soil with long-term K fertilization (0.20%).Potassium associated with amorphous Fe oxide had thehighest content in red soil (0.15%), whereas it was lowest in

Table 3 Ratio of total Kconcentration in soil passedthrough 100 mesh/10 mesh sieves

Soil sample Total K concentration ratio (soil passed through a 100 mesh/10 mesh)

TSL SSL Tessier et al.(1979)

Shuman(1983)

BCR Krishnamurtiet al. (1995)

Mean ± SD

Soil without Kfertilization

1.82 1.87 1.80 1.79 1.85 1.90 1.83 ± 0.04

Soil with long-termK fertilization

1.61 1.63 1.64 1.58 1.72 1.63 1.64 ± 0.04

Red soil 1.19 1.18 1.30 1.21 1.15 1.26 1.22 ± 0.05

Alkaline soil 2.01 2.00 1.94 2.09 1.95 1.83 1.97 ± 0.08

Forest soil 1.96 1.95 2.07 1.96 2.08 2.03 2.01 ± 0.05

Fig. 2 Comparison of K distribution (%w/w) in soil samples analyzed byTSL and SSL methods. W = soil without K fertilization; L = soil withlong-term K fertilization; R = red soil; A = alkaline soil; F = forest soil

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alkaline soil (0.04%). For all soil types, a considerable propor-tion of total K speciation remained in the residual K fraction(97.86–99.00%). Levels of residual K were found to begreatest in alkaline soil (99.00%) but were at their lowest levelin red soil (97.86%). The distribution of available K showedred soil (1.17%) as the highest and soil without K fertilization(0.36%), the lowest. Non-exchangeable K gave a value be-tween 0.44 and 0.97% (Table 6). The proportion of non-exchangeable K showed red soil (0.97%) as the most abun-dant, while alkaline soil (0.44%) had the least. Potassium per-centage recovered employing the Shuman (1983) scheme was94.57–105.25%.

3.4.3 BCR scheme

Distribution patterns of K speciation are illustrated in Fig. 3c.The highest amount of K (97%) was obtained in the residualfraction, while approximately 3% of total K was found in Kassociated with OM (0.22–0.40%), Fe and Mn oxides (0.19–0.47%), and exchangeable K/carbonate K (0.49–1.45%)(Table 5). The exchangeable K/carbonate K fraction wasfound to be greatest in red soil (1.45%) and at its lowest inthe samples which had not been fertilized with potassium(0.49%). Potassium levels associated with Fe-Mn oxides werehighest in red soil (0.47%) and lowest in soil with long-termK

Fig. 3 Distribution (% w/w) of Kanalyzed using a Tessier et al.(1979), b Shuman (1983), cBCR,and d Krishnamurti et al. (1995)schemes. W = soil without Kfertilization; L = soil with long-term K fertilization; R = red soil;A = alkaline soil; F = forest soil

Table 4 Potassium concentrationratio (%) for SSL/TSLmethods insoil passed through a 100 meshsieve

K speciation The K concentration ratio (%)

Soil without Kfertilization

Soil with long-term K fertilization

Redsoil

Alkalinesoil

Forestsoil

Mean ± SD

Available K 97.71 95.73 91.71 97.10 105.77 97.61 ± 4.58

Non-exchangeableK

95.34 96.04 105.16 98.64 97.98 98.63 ± 3.48

Mineral K 98.74 99.16 98.49 96.07 96.00 97.69 ± 1.37

Recovery (%) 98.65 99.08 98.46 96.13 96.10 97.68 ± 1.30

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fertilization (0.19%). The highest levels for K associated withOM were recorded in forest soil (0.40%) while the lowestlevels were found in alkaline soil (0.22%). Residual K washighest in soil without K fertilization (98.97%) and lowest inred soil (97.85%). The distribution of available K reached itspeak in red soil (1.45%) but was at its minimum in soil with noK fertilization (0.49%). Non-exchangeable K was 0.45–0.71%. Red soil had the greatest distribution of non-exchangeable K (0.71%) while samples which had experi-enced long-term K fertilization showed the lowest levels(0.45%). The distribution of mineral K was highest in soilwithout K fertilization (98.97%) and lowest in red soil(97.85%).

3.4.4 Krishnamurti et al. (1995) scheme

Distribution patterns of K speciation are illustrated in Fig. 3d.The highest amount of K was obtained in the residual fraction

(>96%), while approximately 4% of the total K was associatedwith crystalline Fe oxide (0.50–0.69%), amorphous mineralcolloid (0.05–0.16%), H2O2 extractable organic (0.36–1.10),easily reducible metal oxide (0.06–0.18%), metal-organiccomplex (0.28–0.51%), carbonate (< detection limit of0.24%), and exchangeable fraction (0.35–1.29%) (Table 5).The fraction of exchangeable K reached its highest level inthe red soil (1.29%) and was at its minimum in the forest soil(0.35%). Potassium associated with the carbonate fraction wasonly observed in alkaline soil (0.24%). Between 0.28 and0.51% of the total K was associated with metal organic com-plexes, highest in forest soil (0.51%) and lowest in alkalinesoil (0.28%). Red soil (0.18%) had the highest K associatedwith easily reducible metal oxide, while forest soil (0.06%)had the lowest. Potassium associated with H2O2 extractableorganic was highest in soil without K fertilization (1.10%) andlowest in alkaline soil (0.36%). Potassium associated withamorphous mineral colloid peaked in the red soil at 0.16%

Table 5 Potassium speciationdistribution (% w/w) for the fourSEP schemes in soil passedthrough a 100 mesh sieve

K speciation (% w/w) Soil without Kfertilization

Soil with long-term Kfertilization

Redsoil

Alkalinesoil

Forestsoil

Tessier et al. (1979)

Exchangeable 0.36 0.44 1.08 0.53 0.36

Carbonate ND ND ND 0.20 ND

Fe and Mn oxide 0.60 0.41 0.56 0.50 0.36

Organic matter 0.25 0.21 0.78 0.19 0.30

Residual 98.96 98.94 98.15 98.58 98.98

Shuman (1983)

Exchangeable 0.36 0.48 1.17 0.56 0.54

Organic matter 0.36 0.32 0.28 0.16 0.44

Mn oxide 0.31 0.20 0.56 0.24 0.23

Amorphous Fe oxide 0.09 0.07 0.15 0.04 0.06

Residual 98.89 98.93 97.86 99.00 98.74

BCR

Exchangeable/carbonate 0.49 0.64 1.45 0.65 0.71

Fe and Mn oxide 0.25 0.19 0.47 0.29 0.28

Organic matter 0.30 0.27 0.25 0.22 0.40

Residual 98.97 98.91 97.85 98.84 98.62

Krishnamurti et al. (1995)

Exchangeable 0.38 0.56 1.29 0.65 0.35

Carbonate ND ND ND 0.24 ND

Metal-organic complex 0.43 0.31 0.38 0.28 0.51

Easily reducible metaloxide

0.18 0.11 0.18 0.12 0.06

H2O2 extractableorganic

1.10 0.97 0.81 0.36 0.46

Amorphous mineralcolloid

0.08 0.05 0.16 0.06 0.08

Crystalline Fe oxide 0.52 0.53 0.50 0.69 0.59

Residual 97.39 97.52 96.78 97.66 98.00

The concentration lower than the detection limit (0.018 μg mL−1 )

ND not detectable

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and was at its minimum in soil which had undergone K fertil-ization over the long term (0.05%). Alkaline soil (0.69%)contained the highest amount of K associated with crystallineFe oxide, whereas red soil (0.50%) contained the least. Inevery phase, a significant amount of the overall K speciationwas still present in the residual K fraction. The residual K wasfound to be greatest in the forest soil (98.00%) and was at itslowest levels in the red soil (96.78%). Available K was foundto be at its greatest in red soil (1.25%) with its lowest levelsseen in forest soil (0.34%). Non-exchangeable K distributionwas found to be between 1.48 and 2.24%. Distribution of non-exchangeable K showed soil without K fertilization (2.24%)as the highest and alkaline soil (1.48%) the lowest. Mineral Kdistribution was 96.78–98.00%, where forest soil (98.00%)

had the highest and red soil (96.78%) the lowest.Furthermore, the ratios of available K, mineral K, non-exchangeable K, and the total K in the findings ofKrishnamurti et al. (1995) and those using the TSL techniqueswere broadly similar, as shown in Table 6.

4 Discussion

4.1 Influence of soil pretreatment

Both TSL and SSL methods showed that K speciation con-centration and distribution were higher in soils passed througha 100mesh compared to a 10mesh sieve (Fig. 1; Table 3). Soil

Table 6 Potassium speciationdistribution (% w/w) for TSL,SSL, and the four SEP schemes insoil passed through a 100 meshsieve

K speciation (% w/w) Soil without Kfertilization

Soil with long-term Kfertilization

Redsoil

Alkalinesoil

Forestsoil

TSL

Available K 0.47 0.76 1.97 0.75 0.71

Non-exchangeableK

2.64 1.79 1.54 1.88 1.36

Mineral K 96.89 97.45 96.49 97.37 97.92

SSL

Available K 0.47 0.74 1.84 0.76 0.79

Non-exchangeableK

2.55 1.74 1.64 1.93 1.39

Mineral K 96.98 97.53 96.52 97.31 97.82

Recovery (%) 98.65 99.08 98.46 96.13 96.10

Tessier et al. (1979)

Available K 0.36 0.44 1.10 0.73 0.36

Non-exchangeableK

0.84 0.62 0.78 0.69 0.67

Mineral-K 98.80 98.94 98.15 98.58 98.98

Recovery (%) 98.82 99.14 105.40 99.10 102.07

Shuman (1983)

Available K 0.36 0.48 1.17 0.56 0.54

Non-exchangeableK

0.75 0.58 0.97 0.44 0.72

Mineral-K 98.89 98.93 97.86 99.00 98.74

Recovery (%) 94.57 98.23 98.61 105.25 97.64

BCR

Available K 0.49 0.64 1.45 0.65 0.71

Non-exchangeableK

0.54 0.45 0.71 0.51 0.67

Mineral-K 98.97 98.91 97.85 98.84 98.62

Recovery 96.98 104.55 98.56 95.55 100.69

Krishnamurti et al.(1995)Available K 0.37 0.56 1.25 0.87 0.34

Non-exchangeableK

2.24 1.93 1.97 1.48 1.66

Mineral-K 97.39 97.50 96.78 97.66 98.00

Recovery (%) 98.64 96.99 100.11 94.78 99.75

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passed through a 100 mesh sieve eliminates the fine sand(0.10–0.25 mm), medium sand (0.25–0.50 mm), coarse sand(0.50–1.00 mm), and very coarse sand (1.00–2.00 mm), alongwith large OM particles (Brady and Weil 2008). Soil withoutK fertilization and forest soil had high sand particle content(Table 2). Following sieving of the sample using the 100 meshsieve, the soil was found to comprise principally clay frag-ments and high silt. These clay particles are important as asource of illite and smectite which are secondary K minerals(Britzke et al. 2012); these are also highly negatively chargedmaking them affinity to adsorb cations, such as K+. The sandfraction normally lacks K-bearing minerals (Britzke et al.2012) and exhibits in low negative charge; thus, a coarse-textured soil has lower total K than a fine-textured soil(Havlin et al. 2005). Although, soils passed through a 10meshsieve are commonly used and recommended for soil physico-chemical property evaluation (Jones, 2001; Chelabi et al.2016). We recommend that in pretreatment in K speciationanalysis, the soil sample should be air dried at room temper-ature before being ground and mixed, and then sieved using a100 mesh sieve.

4.2 TSL method

Distribution of available K in soil is between 0.47 and 1.97%(Fig. 2), which are close to the value (1–2%) found in theliterature (Havlin et al. 2005). Available K can be consideredas K speciation, which is readily available to plants (Zörb et al.2014). Available K in agricultural soils is normally associatedto application of K fertilizer. Soil samples which have notundergone exposure to K fertilizer have smaller quantities ofavailable K (Madaras et al. 2014). The distribution of non-exchangeable K was between 1.36 and 2.64%. The greatestamounts of non-exchangeable K found in the alkaline soil,which had not undergone K fertilization because of the presentof high levels of illite (Table 2). The expansible interlayerspace of illite ((K, H3O

+)(Al, Mg, Fe)2(Si, Al)4O10(OH)2,H2O) is occupied by poorly hydrated K+ (Essington 2004),and the K content in the clay structure makes up around 8%(Li et al. 2015). This portion of K in illite may also slowlycontribute to the available K form to supply the plant K-requirement (Wang et al. 2011; Sarkar et al. 2013). Some plantspecies such as ryegrass (Li et al. 2015), maize, pak choi, andalfalfa (Wang et al. 2000) are not only efficient in the absorp-tion of available K, but also in the mobilization of non-exchangeable K via root exudates that release organic acidto subsequently release non-exchangeable K and make it bio-available (Zörb et al. 2014). Furthermore, organic acids suchas oxalic acids or citric acids are often secreted by K solubi-lizing microorganisms which attack the surface and cleavefrom the K minerals to release K (Zörb et al. 2014; Wanget al. 2016). Most (>96%) of the K in the soil remains inmineral form and is not directly bioavailable. This speciation

becomes more readily available after weathering, but this pro-cess in the environment is very slow.

4.3 SSL method

The distribution obtained under both the SSL and TSLmethods was found to be similar for available K, non-exchangeable K, and mineral K as indicated in Fig. 2.Available K include fraction of water-soluble K and ex-changeable K (Brady andWeil 2008). Water-soluble K is gen-erally referred to soil solution K (Helmke and Sparks 1996).The fraction of exchangeable K is referred to K+ ions adsorbedon the surfaces of negatively charged clay particles and humicsubstances due mainly to electrostatic forces interaction(Havlin et al. 2005). This form of K+ can be leached fromsoils via exchangeable cations, such as NH4

+, Ca2+, H+, andothers (Zörb et al. 2014). The amount of available K can bediminished in agricultural land by continuous plantingwithoutK fertilization (Darunsontaya et al., 2012). Non-exchangeableK is trapped in the interlayers of secondary mineral com-pounds (Rezapour et al. 2009) or the OM (Jalali 2008). Asolution of 1 M HNO3 extractant not only extracted the non-exchangeable K but also extracted both exchangeable K andwater-soluble K (Helmke and Sparks 1996). The SSL methodcan be modified and used in sequential extraction. However,in the extraction process, the time and speed of centrifugationmust be increased to avoid the effect of slurries, with thesupernatant removed slowly to prevent soil loss. However,the SSL method was inferior in estimating K speciationcompared to the TSL method.

4.4 Potassium distribution using the four SEP methods

4.4.1 Tessier et al. (1979) scheme

Positively charged K+ can be adsorbed onto negativelycharged soil constituents and exchangeable speciations caninfluence the environmental sorption-desorption processes(Tessier et al. 1979). Available K extracted by the Tessieret al. (1979) scheme was lower than the TSL method(Table 6). The direct effect was that NH4

+ in the ammoniumacetate solution (NH4OAc) gained an advantage by exchang-ing with K+ because the presence of the hydrated NH4

+ hasionic radius more similar to K+ than Mg2+ (Brady and Weil2008) from magnesium chloride (MgCl2) solution in the firstextraction step of the Tessier et al. (1979) scheme. It is difficultfor large hydrated cations including Ca2+ and Mg2+ to fit ap-propriately into a wedge zone (Sarkar et al. 2013). NH4OAcextracted not only water-soluble K and exchangeable K butalso the carbonate fraction (Cheng et al. 2011). The carbonatefraction exhibits significantly lower solubility when dissolvedin 1 M CH3COONa at a pH value of 8.2 than in neutral 1 MNH4OAc (Chapman 1965). However, 1 M CH3COONa was

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shown to liberate the carbonate fraction in the SEP method(Tessier et al. 1979; Krishnamurti et al. 1995). ExchangeableK and K bound to carbonate species are broadly consideredBbioavailable^ since they are relatively mobile within theirenvironment. The K fraction associated with carbonate wasonly noted in alkaline soil with a high pH of 7.83 (Table 1).Evidence indicated that the carbonate fraction could be affect-ed when the environmental pH values were altered (Tessieret al. 1979; Cheng et al. 2011). Potassium bound with Fe andMn oxides showed a low (0.36–0.60%) relative distribution(Table 5) because of their low negative charges which wereneeded to adsorb cations (Brady and Weil 2008). The Fe andMn atoms coordinated with oxygen atoms to form hydroxylgroups and coatings on the soil particles (Brady and Weil2008). The negative charge of Fe oxide is caused by the re-moval or addition of hydrogen ions at the surface of oxy-hydroxyl groups (Brady and Weil 2008). OM which includesnatural organic materials, detritus, living things, or even thecoatings which are found covering mineral particles (Tessieret al. 1979) can be degraded to release K. Plant tissue K con-centration ranged from 0.5 to 6% in dry matter (Havlin et al.2005) depending on crop species and plant age. Therefore,this scheme was the popular used to classify the fractionation.However, the non-exchangeable K distributions using thisscheme were decreased 2- to 3-fold compared with TSLmeth-od (Table 6).

4.4.2 Shuman (1983) scheme

This procedure was developed to extract the OM fraction inthe SEP. The extractant used (1MMg(NO3)2 pH 7.0) was lessaggressive in extracting exchangeable K than the TSLmethod(1 M NH4OAc pH 7.0). However, the distribution of ex-changeable K obtained using the Shuman (1983) schemewas similar to the Tessier et al. (1979) scheme (1 M MgCl2pH 7.0) (Table 5). The basic solution (5.3% NaOCl pH 8.5and 0.025 M DTPA) used to dissolve OM in the Shuman(1983) scheme was modified to suit the SEP method andproved to be more efficient in dissolving OM than theTessier et al. (1979) scheme (0.02 M HNO3 and 30% H2O2

pH 2.0). Moreover, an alternative approach using 0.1 M sodi-um or potassium pyrophosphate (Na4P2O7 or K4P2O7) atpH 10.0 as to disperse the colloidal organic material can bedispersed (Kaplan et al. 2011). Humic substances that includefulvic acid, humic acid, and humin comprise 60–80% of OMand are easily dissolved in alkali solutions (Brady and Weil2008). Results indicated that NaOCl (pH 8.5) destroyed moreOM than H2O2. Similar findings reported that organic carbonin the soil was completely destroyed by NaOCl using theWalkley-Black method for the estimation of OM (Shuman1983). The K which is linked to the OM fraction is not per-ceived to be either mobile or available since it is believed to berelated to stable humic substances with high molecular

weights which will typically release metals gradually in smallquantities (Rao et al. 2008). Extractants, which are able toperform a complexing role, including Na2EDTA or EDTA,have the effect of displacing metals from their insoluble or-ganic or organometallic complexes as well as those whichhave been sorbed on the inorganic components of soil(Kaplan et al. 2011). Manganese oxide readily dissolved inhydroxylamine hydrochloride (NH2OH·HCl) solution.However, this solution can dissolve, on average, only 85%of Mn oxide (Chao 1972) and does not completely dissolveFe oxide (Chao 1972; Rauret 1998). The quantity of K asso-ciated with Mn oxides obtained using the Shuman (1983)scheme was similar to the amount of K associated with Feand Mn oxides obtained using the BCR scheme (Table 5).Hydroxylamine hydrochloride solution can be used to dis-solve Mn oxide selectively without excessive concomitantattack on Fe oxide (Chao 1972). The amorphousoxyhydroxides of Fe and Mn can readily sorb the metal ele-ments. While these will at first take an exchangeable form, themetals in this phase will later become transformed to formswhich are less mobile and can be specifically adsorbed(Kaplan et al. 2011). For example, solutions of 0.1 MNH2OH·HCl are able to release metals derived primarily fromthe amorphous Mn oxide. Furthermore, small quantities canbe extracted from Fe oxide (Rao et al. 2008). An efficientattack upon the amorphous Fe oxide is produced when theconcentration of NH2OH·HCl is raised to 0.5 M while simul-taneously lowering the pH value from 2.0 to 1.5, while stillreleasing metals from Mn oxide (Kaplan et al. 2011).Moreover, the distribution of K associated with amorphousFe oxide tends to be similar to amorphous mineral colloidfractions in the Krishnamurti et al. (1995) scheme (Table 5).However, the K speciation distributions obtained using thisscheme were not related with obtained by TSL method(Table 6).

4.4.3 BCR scheme

This scheme was modified from Tessier et al. (1979) and hasthe support of the Bureau Communautaire de Référence (Ureet al. 1993). Instead of analyzing the exchangeable and car-bonate fractions separately, the BCR scheme allows the anal-ysis of both within the initial fraction. Since the carbonateform is a loosely bound phase, it can be altered easily underdifferent environmental conditions. Changes in pH values alsoaffect this phase, which is typically obtained through the useof mild acids such as 1 M CH3COOH and buffer solution 1 MCH3COONa pH 5.0 with CH3COOH (Kaplan et al. 2011). Acomparatively small percentage of the total K content is usu-ally found in the carbonate fraction, while the acid-solublemetal fraction can be obtained by using 0.11 M CH3COOH.The CH3COOH not only dissolved the carbonate fraction butalso extracted the exchangeable K fraction simultaneously

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(Nemati et al. 2011). Some extractants used in this schemewere similar to other schemes, but K speciation in the productswas different. A 1 M NH4OAc solution in this scheme wasused to extract K association with OM while it was used forexchangeable K extraction in the TSL method (Table S5,Electronic Supplementary Material). This scheme showedgreater efficiency in extracting available K than the Shuman(1983) and Krishnamurti et al. (1995) schemes (Table 6).However, the non-exchangeable K distribution was not simi-lar to obtain using TSL method.

4.4.4 Krishnamurti et al. (1995) scheme

This scheme was developed from suggested to differentiatethe Fe- andMn oxide-bound species into three distinct speciesand to reflect the metal bound to organic complexes(Krishnamurti et al. 1995). The scheme was included metalspeciation bound with metal oxides which can be readily re-duced, organic complexes, crystalline Fe oxide, and amor-phous mineral colloids (Krishnamurti et al. 1995). Various soilclusters exhibit some small differences; it was found that thedominant component was an Fe-dominated compound (Fe-Al) which was extracted under conditions of high acid con-centration, and whose source was probably the dissolution ofan Fe oxyhydroxide phase. Iron and Al oxides and hydroxidesare the main metal scavengers in soil samples, especially theFe forms, because Fe and Al exist in the lithosphere. Soilcolloids such as Fe oxide (goethite) with low net charge +20to −5 cmolc kg−1 (Brady and Weil 2008) adsorb cations.Manganese oxides are easily dissolved in H2O2 (Neamanet al. 2004). In addition, someMn is incorporated in the struc-ture of Fe oxide and, thus, cannot be released by H2O2

(Neaman et al. 2004). Metal oxides which can be easily re-duced are normally found in the form of oxides or hydrousoxides, nodules, concretions, or as stains and coating on soilparticle surfaces (Chao 1972). Amorphous mineral colloids,such as the oxides, hydroxides, or oxyhydroxides of Fe andAl, exist in the form of concretions or as coatings upon themineral components of the soil (Krishnamurti et al. 1995).Crystalline Fe oxides are produced prior to the clay mineral-ogy (Krishnamurti et al. 1995), and Fe and Mn oxides arehighly effective in scavenging for metals. They also exhibitthermodynamic instability in anoxic conditions, such as lowEh. (Tessier et al. 1979). The summation of K concentrationlinked to metal oxides which can be easily reduced, othermetal-organic complexes, H2O2 extractable organics, crystal-line Fe oxides, and amorphous mineral colloids through stages3–7 of the process was similar to non-exchangeable K, andsteps 1–2 were related to available K that classified K speci-ation based on its bioavailability by the TSLmethod (Table 6).This scheme had an advantage and was suitable to separate Kspeciation. All weakly to strongly bound K speciations were

affected by environmental conditions and results are summa-rized in Table S7.

5 Conclusions

Soil pretreatment influenced the amount of total K, and Kspeciation distribution. Although soil which had been sievedusing a 10-mesh sieve was widely utilized in routine physico-chemical analysis, results indicated that soil which had beensieved using a 100-mesh sieve showed greater suitability, asthe K partitioning estimation and identification of K specieswas enhanced over the case for soil sieved using only a 10mesh sieve. Standard soil sample preparation methods for Kspeciation analysis were air drying at room temperaturefollowed by grinding, mixing, and passing through a 100-mesh sieve. Wet chemical extraction using TSL and SEPmethods indicated that both were lacking in critical K distri-bution examination. A combination analysis using both TSLand SEP methods proved beneficial to understand Kpartitioning and the environmental influence correlated to Kbioavailability. This research suggested that the SEP methodcan be regarded as acceptable for K speciation estimation.Available K from two steps (exchangeable, and carbonatefractions) of the SEP were similar to available fractions inthe TSL method. Potassium quantity using the Krishnamurtiet al. (1995) scheme can compare how K speciation is affectedby environmental conditions based on its bioavailability andthis scheme was suitable for K speciation analysis. Furtherstudy on the correlation of K speciation transformation in soiland plants, as well as the combination of indirect (wet chem-ical extraction) and direct methods (X-ray absorption spec-troscopy), is required to increase knowledge regarding thesecomplex processes.

Acknowledgments This study was supported by the Ministry ofScience and Technology of R.O.C. (Grant Nos. NSC 98-2221-E-005-021, 99-2120-M-005-003, 100-2120-E-005-002, 102-2221-E-005-001-MY3, MOST 105-2221-E-005-005-MY3) and Industrial DevelopmentBureau, Ministry of Economic Affairs of R.O.C. (101-EC-17-A-A21-S1-229).

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