Nature of the clay–cation bond affects soil structure as verifiedby X-ray computed tomography

Alla MarchukA,C, Pichu RengasamyA, Ann McNeillA, and Anupama KumarB

ASoil Science, School of Agriculture, Food and Wine, Waite Campus, The University of Adelaide,SA 5064, Australia.

BCSIRO Land and Water, Waite Campus, PMB2, Glen Osmond, SA 5064, Australia.CCorresponding author. Email: alla.marchuk@adelaide.edu.au

Abstract. Non-destructive X-ray computed tomography (mCT) scanning was used to characterise changes in porearchitecture as influenced by the proportion of cations (Na, K, Mg, or Ca) bonded to soil particles. These observed changeswere correlated with measured saturated hydraulic conductivity, clay dispersion, and zeta potential, as well as cation ratioof structural stability (CROSS) and exchangeable cation ratio. Pore architectural parameters such as total porosity, closedporosity, and pore connectivity, as characterised from mCT scans, were influenced by the valence of the cation and theextent it dominated in the soil. Soils with a dominance of Ca or Mg exhibited a well-developed pore structure and poreinterconnectedness, whereas in soil dominated byNa or K there were a large number of isolated pore clusters surrounded bysolid matrix where the pores were filled with dispersed clay particles. Saturated hydraulic conductivities of cationic soilsdominated by a single cation were dependent on the observed pore structural parameters, and were significantly correlatedwith active porosity (R2 = 0.76) and pore connectivity (R2 = 0.97). Hydraulic conductivity of cation-treated soils decreasedin the order Ca >Mg >K >Na, while clay dispersion, as measured by turbidity and the negative charge of the dispersedclays from these soils, measured as zeta potential, decreased in the order Na >K >Mg >Ca.

The results of the study confirm that structural changes during soil–water interaction depend on the ionicity ofclay–cation bonding. All of the structural parameters studied were highly correlated with the ionicity indices of dominantcations. The degree of ionicity of an individual cation also explains the different effects caused by cations within amonovalent or divalent category.While sodium adsorption ratio as a measure of soil structural stability is only applicable tosodium-dominant soils, CROSS derived from the ionicity of clay–cation bonds is better suited to soils containing multiplecations in various proportions.

Additional keywords: ECR, CT scanning, soil porosity, soil structure.

Received 17 September 2012, accepted 30 October 2012, published online 14 January 2013

Introduction

Water and air movements in soil depend on the soil structure ingeneral and are important in agricultural systems and soilengineering operations. They depend particularly on the sizeand shape of the soil particles, and the arrangement of pores, asinfluenced by pore fluids. The chemical composition of porefluids, dictated by the exchangeable cations, affects swelling,dispersion, and flocculation of clay minerals associated with soilaggregates, and causes changes in soil structural parameterssuch as hydraulic conductivity and the architecture of poresystems. Several studies have shown that exchangeablecations strongly influence the structural conditions of soilswith similar mineralogy and organic matter contents (e.g.Rengasamy and Sumner 1998). The roles of exchangeablesodium and calcium are well known, with the consensus thatsodium causes structural deterioration and calcium is beneficialin preserving structural integrity (e.g. Marchuk and Rengasamy2011). However, both positive and negative effects of

exchangeable potassium and magnesium on soil structurehave been reported (El Swaify et al. 1970; Emerson andSmith 1970; Ravina 1973; Rengasamy et al. 1986; Keren1991; Smiles and Smith 2004).

Rengasamy and Sumner (1998) suggested that the stability ofsoil aggregates when in contact with water depends on the natureand persistence of linkages between the particles and cations,which, in turn, are functions of the type of bonding, covalentand/or ionic. In natural systems, heteronuclear bonds have amixture of covalent and ionic character (Huheey et al. 1993).Attempts have been made to describe the partial ionic characterof covalent bonds on the basis of relative electronegativity ofatoms (Pauling 1967). Covalent bonding between a cation andan anion is facilitated by their polarisability, which depends ontheir ionic potentials. Further, hardness and softness of a cationare also indicative of low and high polarisability. Theseparameters are quantified by Misono’s softness parameter(Sposito 1989).

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Soil Research, 2012, 50, 638–644http://dx.doi.org/10.1071/SR12276

Clay associations with biopolymers in soils are veryheterogeneous and can be considered as large-size anions withhigh charge, causing them to be strongly influenced by thepolarising cation. Therefore, Marchuk and Rengasamy (2011)concluded that the degree of ionicity or covalency of a cationwill reflect the degree of covalent or ionic character of clay –

cation bonds. Combining the ionic potential and Misono’ssoftness parameter, they derived the ionicity index of a cation (II)as: II = 1– (Iz/Iz+1) Z

0.5,whereZ is the valence of the cationwhoseionisation potential is Iz, and Iz+1 is the ionisation potential whenthe valence of the cation changes to Z + 1 (Marchuk andRengasamy 2011). Experimenting with homoionic clays, thoseresearchers obtained significant relationships between ionicityindices of monovalent and divalent cations and clay behaviour inaqueous suspensions, such as dispersibility, zeta potential, andparticle-size distribution.

Knowledge of soil structure and pore connectivity is vital tounderstand and predict changes in soil aeration, hydraulicconductivity, and sequestration or emission of greenhouse gases.Porosity plays a crucial role in facilitating numerous physical,chemical, and biological processes occurring in soil. However,despite the significance of pore structure, it has historicallybeen difficult to quantify (Cárdenas et al. 2012; Vogel 2000;Vogel et al. 2010). Traditional testing methods for porearchitecture include the gas adsorption method, mercuryintrusion porosimetry, and permporometry (Churchman andPayne 1983; Gaskin and Raymond 1973; Lipiec et al. 2012).Paradoxically, the majority of the tests destroy or alter the veryparameters they are supposed to measure. Additionally, thetoxicity of mercury is a concern for the wellbeing of theresearcher.

High-resolution X-ray computed tomography (mCT) is atechnique that can provide valuable information in theanalysis of soil pore architecture, and which can reliablydescribe the pore structure and connectivity of an undisturbedsoil entity (Turner et al. 2003). A mCT scan with subsequentthree-dimensional (3D) reconstruction of serial images enablesthe visualisation of isolated pores not visible externally due tothe opaque nature of the soil medium, and therefore can be usedto determine parameters such as total porosity, closed porosity,pore connectivity, and overall 3D micro-architecture (Darlingand Sun 2004; Vergés et al. 2011; Cárdenas et al. 2012). Amongthe pioneers of the use of mCT scans in soil science were JMHainsworth and LAG Aylmore in Australia (Hainsworth andAylmore 1983; Aylmore 1993), and S Crestana in Brazil(Crestana et al. 1986). Principles of mCT operations in soiland plant sciences are comprehensively detailed by Taina et al.(2010), Vogel et al. (2010), Mooney et al. (2012), and Basileet al. (2012).

The present study aimed to investigate structuraldifferences induced by different cations (Na, K, Mg, or Ca) in aRed Chromosol, as indicated by changes in pore-systemarchitecture identified by non-destructive, high-resolution X-rayCT scanning. Further, it aimed to link these observed changes inpore architecture to alterations in physico-chemical parameterssuch as claydispersion andhydraulic conductivity.The study alsoaimed to relate any observed structural differences caused by thecations to the ionic character of the bonds between the cationsand clay particles.

Materials and methods

The 15–45 cm layer of Urrbrae fine sandy loam, a RedChromosol (Isbell 2002), was collected by hand auger, air-dried, and sieved to 2-mm particle diameter.

Soil particle-size distribution (Gee and Bauder 1986), solubleand exchangeable cations (Rayment and Lyons 2011), totalcarbon by Dumas high temperature combustion method(Rayment and Lyons 2011), organic carbon (Walkley andBlack 1934), and clay mineralogy by X-ray diffraction andzeta potential of dispersed clays (Marchuk and Rengasamy2011) were measured and are presented in Table 1. Water-dispersible clay was determined in the same way as particle-sizeanalysis except that the samples were dispersed with water,without any pre-treatment to remove cementing compounds andwithout use of dispersive agents (FAO 2006).

Soil samples were evenly packed into Plexiglas (EvonikIndustries, Essen, Germany) columns (4 cm diameter, 7.6 cmlength) at a bulk density of 1.25Mgm–3. Both column ends werefitted with nylon mesh screens with a double disk of a gauzemesh on the top of the soil to reduce surface disturbance. Fivesoil cation saturation treatments were performed: a control (nocations added), and Na, K, Mg, and Ca (chloride solutions), witheach treatment performed in triplicate. Initially the columns weresaturated from the base by slow capillary rise with the treatmentsolutions for 24 h and drained for 48 h before the flow directionwas reversed. The columns were percolated with three wettingand drying cycles using each of four treatment solutions asdescribed in Speirs et al. (2011). At the end of the last cycle,deionised water was passed through the columns to simulateinfiltration of the soils with rain water. The control columns ofuntreated soil were also set up to measure saturated hydraulicconductivity in order to compare the results of the cation (Na, K,Mg, or Ca) saturated soils. Once wetting and drying cycles andsaturated hydraulic conductivity measurements were complete,the columns were stored at room temperature for 2 months,allowing the moisture to evaporate.

Table 1. Selected physical and chemical properties, main clayminerals, classification, and location of Urrbrae soil, Waite Institute,

Adelaide

Soil properties Units Description

Depth cm 15–40pH (1 : 5 soil–water solution) 6.7EC (1 : 5 soil–water solution) dS m–1 0.061Cation ratio of structural stability(CROSS)

mol0.5 m–1.5 0.24

Sodium adsorption ratio (SAR) mol0.5 m–1.5 0.12Total carbon % 1.5Organic carbon % 1.4Cation exchange capacity (CEC) cmol kg–1 7Zeta potential mV –38Dominant clay minerals Illite, kaoliniteAustralian Soil Classification (Isbell 2002) Red ChromosolTexture Sandy loamClay content (Gee and Bauder 1986) % 40Water dispersible clay % 26Location in South Australia 34858000.4100S,

138838003.2900E;elevation 109m

Nature of the clay–cation bond affects soil structure Soil Research 639

After the storage period, soil samples from the first andsecond columns of each treatment were removed, air-dried,crushed, and passed through a 2-mm sieve before beinganalysed for selected properties such as EC1:5 (electricalconductivity, 1 : 5 soil–water), pH 1:5 (1 : 5 soil–water),CROSS (cation ratio of structural stability) of soil solutions(CROSSss), and ECR (exchangeable cation ratio, %).Spontaneous dispersion was determined and zeta potentialwas measured on soil clay particles, using the methods givenin Marchuk and Rengasamy (2011). The third set of columnswas used for X-ray CT scanning. Soluble cation (Na, K, Mg, Ca)concentrations (mmolc/L) were determined in the 1 : 5 extractsby ICP method, and CROSSss of the soil solutions werecalculated using the following equation:

CROSSss ¼ðNaþ 0:56KÞ=½ðCaþ 0:6MgÞ=2�0:5ðmol0:5m�1:5Þ ð1Þ

where the concentrations of the corresponding ions areexpressed in mmolc/L. Exchangeable cations were estimatedby the method described in Rayment and Lyons (2011). Theeffective cation exchange capacity (CECeff) and ECR% werecalculated as:

CECeff ¼ sum of exchangeable cations Na; K; Mg; and Ca

ECR% ¼ ½ððNaþ þ KþÞ=CECeff Þ� � 100% ð2Þwith quantities of exchangeable cations expressed in cmolc kg

–1.

Non-destructive, high-resolution, X-ray CT scanningmethod

The X-ray CT scanning method is a non-invasive imagingtechnique that allows the 3D, non-destructive examination ofopaque, heterogeneous material including soil, whereby largenumbers of transmission measurements of an X-ray beam areused to reconstruct an image of a scanned object, such as aportion or block of soil. Using digital image processing, it ispossible to create 3D visualisations derived from 2D scans, andhence examine the undisturbed soil pore network of a soil entityin 3D.

Micro-CT analysis

Four soil samples representing each cation used for saturationwere prepared from the third set of replicated columns. Due tosize limitations for samples in the CT scanner, the specimenswere cut into a small parallelepiped piece of 30 by 20 by 10mmeach with the intensity of 16 bits per pixel. The prepared soilspecimens were designated as Na, K, Mg, and Ca. The sampleswere scanned using a SkyScan-1076 in vivo micro-CT scanner(Adelaide Microscopy, The University of Adelaide) set at100 kV and 100mA with a 1.0-mm aluminium filter inserted.The scans were performed at a voxel resolution of 17.3mm andthe duration of each scan was 48min. During data acquisition,the sample was rotated over 1808 at the step size of 0.58.Horizontal overlap was 64 pixels to ensure full coverage ofthe entire sample.

The output format for each sample was, on average, 676serial images, 3936 by 1014 pixels each. These slices wereviewed and reconstructed into 2D slices using NRecon software

Version 1.6.3.2 (SkyScan, now Bruker-microCT, Kontich,Belgium). The 3D models of the soil specimen and porespace were reconstructed and visualised using CTVolsoftware Version1.10.10.2 (Bruker-microCT).

Soil structure parameters of interest, total porositypercentage, closed porosity percentage, and pore connectivity,were calculated by a SkyScan CT-analyser program (CTAn).Illustrative 3D visualisation of half-reconstructed pore space(coloured in white) was produced by applying a visual cutawayof the solid region that occluded the pores.

Morphometric parameters are calculated by the CT-analysersoftware either directly in 3D based on a surface-renderedvolume model or in 2D from individual binarised cross-section images (Morphometric Parameters in CT-analyser,available at: www.skyscan.be/next/CTAn03.pdf; Pender et al.2009). Two types of analysis were performed for both 2D and3D measurements. First, all objects in the selected region wereanalysed together, and the integrated results calculated, such astotal volume of surface of all the objects, or mean thickness ofall the objects. Second, individual objects were categorised,on the basis of being entirely surrounded by space either in2D (on a single selection only) or in 3D (for selected volumecomprising many cross-sectional levels). Morphometricparameters in 3D and 2D were carried out on all of theseindividual objects (Bruker-micro CT, SkyScan1076 Manual,

Table 2. Structural differences in a Red Chromosol induced bydominance of different cations (Na, K, Mg, or Ca) as indicated bythe changes in pore system architecture (total porosity, closed porosity,and pore connectivity) identified by non-destructive, high-resolution

X-ray CT scanning

Treatment cations: Na K Mg Ca Control

Number of values 702 633 764 645 637Total porosity (%) 37.1 39.4 42.3 49.3 40.6Std deviation 1.303 2.14 0.85 1.02 1.03Std error 0.058 0.08 0.03 0.04 0.04

Closed porosity (%) 34.5 31.0 24.4 10.7 31.1Std deviation 1.2 2.6 5.0 2.9 2.5Std error 0.11 0.20 0.10 0.05 0.10

Pore connectivity (106) 1.3 1.43 4.0 5.1 1.5

Ca Mg K Na Control0

10

20

30

40

50

38.6%

17.9%

8.4%

2.6%

9.5%

Pac

t%

Fig. 1. Active porosity (Pact) in a soil dominated by a single cation (Na, K,Mg, or Ca) and an untreated control soil.

640 Soil Research A. Marchuk et al.

Belgium). Therefore, four categories of analysis wereperformed, comprising both integrated analysis of all selectedobjects (with a single result output for all objects collectively)

and individual analysis of all discrete objects (with a separateresult output for each object), and both of these were calculatedin 2D and 3D.

(d ) NaCl treated soil. Total porosity 37.07%, closed porosity 34.5%

(c ) KCl treated soil. Total porosity 39.4%, closed porosity 31.0%

(b ) MgCl2 treated soil. Total porosity 42.3%, closed porosity 24.4%

(a ) CaCl2 treated soil. Total porosity 49.26%, closed porosity 10.7%

Ca 2D

Mg 2D

K 2D

Na 2D Na 3D Na 3D half

K 3D K 3D half

Mg 3D Mg 3D half

Ca 3D Ca 3D half

Fig. 2. The 2D, 3D, and 3D half-cut reconstructed sections of pore visualisation from X-ray mCT imagery of Ca, Mg,K, and Na treated soils. Pore space is shown as white colour (contrast and brightness have been enhanced for visualisationusing Photoshop 5.5). The 3D model is 15.5mm by 15.5mm by 8mm in size and the images are coronal.

Nature of the clay–cation bond affects soil structure Soil Research 641

Statistical analyses

Statistical calculations and linear regression analysis wereperformed with the program GraphPad Prism Instat version5.01 (GraphPad Software, Inc., San Diego, CA).

Results and discussion

The percentage of dominant exchangeable cation of Ca, Mg, K,and Na soils was 82.1, 44.2, 39.2, and 31.2, respectively, withother cations being present in smaller proportions as detailed(see Table 3).

Evaluation of mCT results

Soil structure responds morphologically to changes effected bythe different cations in soil solution and on the exchange sites.The differences in porosity values of different cationic soilshighlighted the changes in soil structure induced by thedominant cation (Table 2). Values for active porosity andpore connectivity were the highest in Ca-dominant soil, butclosed porosity values were the highest in Na-dominant soil.Values for active porosity and pore connectivity were in theorder Na <K <Mg <Ca. Several studies have indicated thedeteriorative effect of Na and the beneficial effects of Ca onsoil structure, whereas the effects of K and Mg have generallybeen overlooked. The results in this study clearly indicate thatthe deleterious effect of K is smaller than of Na; and thebeneficial effect of Mg is smaller than of Ca.

The direction of fluid flow in soil depends upon thearchitecture of the pores, and only a part of the pore phaseparticipates in fluid conductivity. In particular, the closed pores,even those connected to each other, do not participate actively inhydraulic conductivity processes, and it is preferable to excludethem from any analysis of soil structure, particularly related tosoil water function (Matrecano 2012). Total porosity includesthe percentage of the pores that actively transmit water, referredto as the ‘active porosity’, Pact, and the relatively small, inactivepores, known as closed porosity, Pcl (Hoag and Price 1997). Theeffect of cation treatments on Pact in the soil, calculated as thedifference between mCT results for total (Ptot) and closed (Pcl)porosity, is shown in Fig. 1. Active porosity was higher in Ca-dominated soil (38.6%) than in Mg-dominated soil (17.9%) andlower in Na-dominated soil (2.6%) than in K-dominated soil(8.4%), and porosity is generally lower for soils with dominantlymonovalent cations than for those with dominantly divalent

cations. Active porosity and pore connectivity of untreatedcontrol soil was higher than K and Na soils (Table 2, Fig. 1).

Micro-CT scanning visual results

The 2D and 3D visualisations of the volumes of interest frommCT images of the Urrbrae soil after cation treatments andhydraulic conductivity measurements suggest significantdifference in the amount of pores and their architecture (Fig. 2).Further evidence of this is seen in the 3D visualisation of half-reconstructed pore space (coloured in white), produced byapplying a visual cutaway of the solid region that occluded thepores (Fig. 2, right column).

Effect of cations on saturated hydraulic conductivity,soil clay dispersion, and zeta potential

Values of soluble and exchangeable cations, relative saturatedhydraulic conductivity (Ksr) (given as relative to the value for theCa-dominant soil, which is taken as unity), turbidity, and zetapotential are presented in Table 3. Hydraulic conductivity foreach of the cationic soils decreased in the order Ca >Mg >K >Na (Table 3). Turbidity (a measure of clay dispersion) ofthe cationic soils decreased in the order Na>K >Mg >Ca(Table 3). Turbidity was also highly related to CROSS(Rengasamy and Marchuk 2011), increasing CROSS leadingto increased turbidity.

The values of these two parameters, usually used to measuresoil structural stability, reflected the same trends observed forpore architecture in these soils, as discussed in the previoussection. The hydraulic conductivity was influenced by activeporosity and pore connectivity. Pore connectivity or the spatialconnectivity is important because the total macroscopic flowcan be dominated by a relatively small fraction of the pore spacethat provides the majority of conductivity pathways for flow(Bhattad et al. 2011). Highly significant correlations betweenKsr

and active porosity (R2 = 0.76) or pore connectivity (R2 = 0.97)were obtained (Fig. 3a, b).

Values of zeta potential (Table 3) show that the net charge ofdispersed clays depends on the dominant exchangeable cation.The Na-clay had the highest negative charge and Ca-clay thelowest, reflecting the influence of cations on the degree ofaggregation of clay particles. Marchuk and Rengasamy(2011) reported from their studies on homoionic clays thatthe monovalent cations led to smaller particle size of clays,whereas divalent cations induced larger particle size, and thisaffected the zeta potential values of these clays.

Table 3. Influence of the dominance of different cations (Ca, Mg, K, Na) in a Red Chromosol on saturated hydraulic conductivity (Ksr), turbidity,zeta potential, cation ratio of structural stability (CROSS), and exchangeable cation ratio (ECR)

ESP, Exchangeable sodium percentage; CEC, cation exchange capacity

Treat. Ksr Turbidity Zeta Soluble cations CROSS Exchang. cations ECR ESP CEC(NTU) (mV) Ca Mg K Na Ca Mg K Na (%) (cmol kg–1)

(meq L–1) (cmol kg–1)

Control 0.10 1780 –36.1 0.29 0.12 0.19 0.26 0.9 4.7 0.93 0.06 0.75 12.45 0.8 6.5Ca 1.00 500 –32.3 1.84 0.20 0.54 0.07 0.4 5.19 0.40 0.67 0.06 11.55 1.0 6.3Mg 0.92 970 –36.5 0.50 1.53 0.54 0.11 1.9 2.79 2.74 0.63 0.06 11.04 0.9 6.2K 0.14 1540 –46.5 0.23 0.11 2.74 0.10 4.3 2.72 0.61 2.19 0.06 40.44 1.2 5.6Na 0.08 2800 –48.7 0.31 0.24 0.60 12.61 27.4 3.13 0.71 0.76 2.06 42.33 30.9 6.6

642 Soil Research A. Marchuk et al.

Soil structural parameters in relation to the ionicityof clay–cation bonds

The effect on soil structural stability when aggregates interactwith water depends on the degree of ionicity of clay–cationbonds (Rengasamy and Sumner 1998). Thus, highly ionic bondsof monovalent cations with clay lead to the easy separation ofclay particles (dispersion) by water molecules. Based on thishypothesis, Marchuk and Rengasamy (2011) derived theionicity indices of clay–cation bonds for monovalent anddivalent cations and showed that the behaviour of pure andsoil clays in aqueous suspensions, such as clay dispersion, zetapotential of dispersed clays, and the mean clay particle size in the

dispersed suspension, was dependent on the ionicity index of thecations. In the present study, clays with a dominance of a singlecation, Ca, Mg, K or Na, were used. The ionicity indices for Ca,Mg, K, and Na bonds with clays are, respectively, 0.67, 0.73,0.86, and 0.89. All of the structural parameters studied,including active porosity, pore connectivity, Ksr, turbidity,zeta potential of the dispersed clay, CROSS, and ECR% werehighly correlated with the ionicity indices of the dominantcations (Table 4).

These results confirm the principle that the degree of ionicityof the clay–cation bond determines soil structural stability and,hence, that CROSS is a better indicator of soil structural stabilityin water than sodium adsorption ratio (SAR), which is applicableonly to Na-dominant soils. It should be noted that CROSS wasderived from the ionicity of the different cations.

Conclusions

Soil structural changes induced by the dominant exchangeablecation in this Urrbrae soil, as shown by mCT scanning analysis,are dependent on the type of cation used for saturation. Porearchitectural parameters such as total porosity, closed porosity,and pore connectivity were influenced by the dominant cation,and all these values decreased in the order Ca >Mg >K >Na.Soils with a dominance of Ca or Mg exhibited a well-developedpore structure and pore interconnectedness, whereas thosedominated by Na or K soil showed a large number ofisolated pore clusters surrounded by a solid matrix where thepores were filled with dispersed clay particles. Saturatedhydraulic conductivities of the cation-treated soils weredependent on the observed pore structural parameters, asshown by the highly significant correlations between Ksr andactive porosity (R2 = 0.76) or pore connectivity (R2 = 0.97).Hydraulic conductivity of cation-treated soils decreased in theorder Ca >Mg >K>Na, whereas clay dispersion, as measuredby turbidity, decreased in the order Na >K>Mg >Ca. Thenegative charge of the dispersed clays from these soils,measured as zeta potentials, decreased in the orderNa >K >Mg >Ca.

The results obtained in the present study confirm an earlierhypothesis (Marchuk and Rengasamy 2011) that structuralchanges during soil–water interaction depend on the ionicityof clay–cation bonding. All of the structural parameters studied,including active porosity, pore connectivity, saturated hydraulicconductivity, clay dispersion, zeta potential of dispersed clays,and CROSS, were highly correlated with the ionicity indices ofdominant cations.

The highly ionic bonding of monovalent cations with claysleads to the separation of clay particles from aggregates by watermolecules, whereas divalent cations of low ionicity lead to moreaggregation of clay particles. The difference in the degree ofionicity between Na and K explains the difference in claydispersion influenced by these cations. Similarly, thedifference between Ca and Mg in the aggregation of clayparticles is explained by their different ionicity indices.

While SAR as a measure of soil structural stability is onlyapplicable to Na-dominant soils, CROSS, derived from theionicity of the different cations, is better suited to soilscontaining different cations in various proportions.

NaK

MgCa

(a)

y = 0.0272x + 0.0741R2 = 0.76p = 0.005

0.0

0.2

0.4

0.6

0.8

1.0

1.2

40

Active porosity Pact %

Na

K

Mg

Ca(b)

y = 0.255x – 0.22R2 = 0.97p = 0.0001

0.0

0.2

0.4

0.6

0.8

1.0

1.2

6

Ks

rel

Pore connectivity 1060 2 4

0 20

Fig. 3. Relationships between mCT pore characteristics and relativesaturated hydraulic conductivity (Ksr).

Table 4. Linear regression analysis between the dependent variables(y: active porosity, pore connectivity, hydraulic conductivity, turbidity,zeta potential, CROSS, and ECR%) and ionicity index of clay-cation

bonds (x)

Regression R2 P

Active porosity y= –142x – 128.8 R2 = 0.89 0.0004Pore connectivity y= –18.08x+ 17.2 R2 = 0.99 <0.0001Ksr y= –4.6251x+ 4.2 R2 = 0.97 <0.0001Turbidity y= 8642.6x – 5353.5 R2 = 0.83 0.0017Zeta potential y= –75.10x – 18.1 R2 = 0.98 <0.0001CROSS y= 90.16x – 62.5 R2 = 0.68 0.0300ECR% y= 160.6x – 100.1 R2 = 0.95 <0.0001

Nature of the clay–cation bond affects soil structure Soil Research 643

Acknowledgments

We are grateful to Dr Jock Churchman of the University of Adelaide forhelpful comments on the manuscript. The authors thank the Grape and WineResearch and Development Corporation (GWRDC) of Australia for financialsupport for the project (CSL 1002). Ms Aoife McFadden of the AdelaideMicroscopy is thanked for the help with CT scanning.

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