Capillary electrophoresis characterisation of humic acids:application to diverse forest soil samples

Michael Tatzber,A,C Franz Mutsch,B Axel Mentler,A Ernst Leitgeb,B

Michael EnglischB and Martin H. GerzabekA

AInstitute of Soil Research, Department of Forest and Soil Sciences, University of Natural

Resources and Applied Life Sciences, Peter Jordan Strasse 82, A-1190 Vienna, Austria.BFederal Research and Training Centre for Forests, Natural Hazards and Landscape,

Seckendorff-Gudent-Weg 8, A-1131 Vienna, Austria.CCorresponding author. Email: michael.tatzber@boku.ac.at

Environmental context. Analysis of soil organic matter is important for understanding turnover and stabilisa-tion processes of organic carbon in soils. Capillary electrophoresis is used here to investigate humic acids fromsoils of diverse forest sites, and show that the patterns of signals are indicative of soil characteristics. Themethodprovides useful information of soil types and complements the existing set of methods for humic acidcharacterisation.

Abstract. Analyses of humic substances provide very useful information about turnover characteristics and stabilisationprocesses of soil organic matter in environmental soil samples. The present study investigates 113 samples of forest soilsfrom three different layers (undecomposed litter (L), if present, mixed samples of F (intermediate decomposed) and

H (highly decomposed) organic matter (FH) and upper mineral soil layers (Ah horizon) from 0 to 5 cm) by extractinghumic acids (HAs) and recording electropherograms. Five signals of these electropherograms were evaluated andcorrelated with basic parameters from soil (organic carbon, Corg, and total nitrogen, Nt, and extraction yields of HAs)

and HAs (total carbon, Ct, and Nt), and with signals from photometry, mid-infrared and fluorescence spectroscopy. Thedeveloped method was able to separate HAs from different soil layers by calculating a discriminant function based onthe five evaluated electrophoretic signals. The dataset of this work opened the opportunity to correlate the observedelectrophoretic signals with the other determined soil parameters and spectroscopic signals. This can be seen as a very

important step in the direction to assignments of the obtained electrophoretic signals. Soil characteristics were reflectedquite well by this method and, combined with the other approaches, it is suitable for applications in further studies.

Received 22 April 2011, accepted 27 September 2011, published online 23 November 2011

Introduction

Analyses of extracted organic matter help characterise a given

site with respect to soil organic matter (SOM) turnover andstabilisation. Extracted organic matter simplifies the analysis ofmolecular characteristics. For this purpose, humic acids (HAs)

have been proven to be a very indicative fraction of SOMby many different approaches including solid-state 13C-NMRspectroscopy,[1] fluorescence spectroscopy, mid-infrared spec-troscopy, pyrolysis gas chromatography–mass spectroscopy

(pyrolysis GC-MS) and photometry (e.g. Chen et al.,[1] Kangand Xing[2] and Knicker et al.[3]). Hence, their analyses have along and successful history. Capillary electrophoresis has an

advantage over standard characterisation methods for extractedSOM by utilising a very different characterisation principle: itseparates based on the charge of the solvated molecules in a

strong electrical field. This makes it a potentially valuableaddition to traditional methods of SOM analysis.

The applicability of the electrophoretic approach in SOM

analysis has been demonstrated by Schmitt-Kopplin et al.,[4–6]

Schmitt-Kopplin and Junkers,[5] Garrison et al.,[7] Trubetskoj

et al.[8–10] and Trubetskaya et al.[11,12] Concerning capillaryelectrophoresis, several publications compare different buffer-

ing systems[5,7,13] and examine artefacts related to the buffersused for the electrophoretic separations.[5–6] Polyacrylamide gelelectrophoresis (PAGE), in combination with size-exclusion

chromatography (SEC), is another established method of HAanalysis (‘SEC-PAGE’).[8–12] Capillary electrophoresis com-bined with UV-detection has been used to analyse lignin-derived phenolic distribution in the degradation residues after

alkaline CuO oxidation of samples of humic substances.[14]

Finally, the fingerprints of fulvic acids (FAs) and HAs havebeen characterised based on the functionality of these acids.[15]

Fetsch et al.[16] used capillary electrophoresis to investigateaggregation of humic substances. In this context the criticalconcentration for the formation of aggregates was mainly

,30mgL�1.[16]

The complexation behaviour of europium and gadoliniumwith HAs was examined by capillary electrophoresis (CE)

coupled with inductively coupled plasma mass spectrometry(CE-ICP-MS).[17] Other authors evaluated CE for characterising

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Environ. Chem. 2011, 8, 589–601

http://dx.doi.org/10.1071/EN11054

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Research Paper

HAs of different origins without purifying the sample.[18] He

et al. characterised five FAs, six HAs and two unprocessednatural organic matter (obtained from the International HumicSubstance Society, IHSS) samples with CE and a fluorescence

excitation–emission matrix[19]: different capillary electropho-retic fractions were differentiated by the presence of differentfluorophore components. In a study of He et al., different HAfractions from different agricultural soils (Nebraska corn and

Philippine rice soils) were compared.[20] UV radiation haddifferent effects: it apparently disaggregated humic fractionsof the Nebraska soils into their structural subunits and the

Philippine soils by altering the functional groups of the humicfractions.[20]

The above works demonstrate the clear potential of CE to

complement traditional spectroscopic approaches when evalu-ating characteristics of extracted SOM. In a recently completedproject, forest soils were sampled from a great number of sitesthroughout Austria and evaluated using mid-infrared spectros-

copy with bulk soils for carbon determinations.[21] Models forsoil layer identifications were then calculated. In a second step,HAs were extracted from a selection of 113 samples of these

forest soil samples.[22] These HAs were also analysed by mid-infrared spectroscopy followed by photometry and fluorescencespectroscopy. Basic data of the HAs were available, along with

site characteristics and basic data of the forest soil samples. Thisdataset is a valuable support for the information obtained fromCE. The first aim of the present study was to develop a capillary

electrophoretic approach for HAs to provide information aboutthe SOM characteristics of soils. A second aimwas to record thesignals from the HAs from different soil layers of the differentforest sites. Finally, those signals present in all the samples (and

therefore useful for comparisons) should be assigned to soilproperties or their chemical nature based on their correlationswith the signals from othermethods. The hypothesis was that the

electrophoretic signals are correlated with signals connectedwith carboxyl groups, aromatics (connected with phenols) andpossibly alcohol groups.

Methods and materials

Sampling sites

The sampling sites are described in a previous work.[22]

Approximately 50% of the Austrian forest soils are Regosols,which cover mainly the silicatic central alps. Further importantforest soil types are Leptosoils (,15%), Luvisols, Umbrisols

and Cambisols (,10% each). As a result of human activities,Austrian forests are dominated by conifers (66.7% of the forestarea); the most important species is Norway spruce (53.6%),

followed by pine (5.6%), European Larch and fir. Red beech(9.6% of the forest land), oak, hornbeam and ash are the mostimportant broadleaves. The Austrian climate is mostly humid,

small parts of the country are boreal or continental. The averagetemperature (30 years mean) of the forest area ranges between2.7 and 8.7 8C for the investigated forest sites, the annual pre-cipitation ranges between 500 and 1800mm.[22]

Soil sampling

Soil samples from 139 Austrian forest sites were available fromthe BioSoil project. Three pits were excavated per location and

the material from the humus and top-mineral-soil layers(undecomposed litter (L), if present, mixed samples of F(intermediate decomposed) and H (highly decomposed) organic

matter (FH) and mineral soil: 0–5 cm) was sampled, air-dried

and sieved (2mm). The samples were stored in airtight bottles.

Some of the ‘mineral soil’ samples had organic carbon contents.20% (the limit for the mineral soil horizons according to theAustrian classification system); these samples were removed

from the sample sets assigned to 0–5 cm (explaining the dif-ferent sample numbers of the investigated soil layers). Somesamples also contained insufficient amounts of soil for HAextraction.

HA extraction

The extraction of HAs with 1M NaOH (Merck, Darmstadt,Germany) was described in detail in previous works.[23,24] An

amount of soil containing 0.8 g of organic carbon was used forthe extraction. After adding 1M NaOH to the soil in a 250-mLplastic bottle, the volume of the suspension was 190mL. This

suspension was shaken overnight and centrifuged (BeckmanJ2-HS Centrifuge, Beckman Instruments, Palo Alto, CA, USA)the next day for 30min at 15 344g at room temperature (storage

of the solutions was in a cooling room, 4 8C) with a Beckmancarbonfibre-rotor having an rmax of 137mm. In the next step, theextraction solution was decanted and this extraction procedurerepeated twice. Especially when extracting soils from organic

layers, particulate organic matter was visible on the surface ofthe extraction mixtures; in such cases these particles wereremoved by passing the solutions through a tea strainer. The

pellets were discarded and the first extraction solution wastransferred into the centrifuge bottle and acidified with 37%HCl (Merck) for precipitation ofHAs and centrifuged for 20min

at 15 344g. The supernatant solutionwas discarded and the sameprocedure was conducted with the second and third extractionsolution; finally, a pellet of all obtained HAs was obtained. Thispellet was dissolved in 20mL of 1MNaOH andwater added to a

volume of,190mL. The sample was centrifuged for 50min at25 931g at room temperature to remove remaining inorganicfine particles from the solution. After careful decantation the

solution was acidified with 3mL of 37%HCl and centrifuged at15 344g for 20min and the supernatant solution discarded. Thesecond washing step was conducted with 10mL of 1M NaOH

and 1.5mL of 37% HCl, and the third washing step involvedelutriating the HAs with water and acidifying with 10 drops of37% HCl from a Pasteur pipette. The purified HAs were

transferred with a small amount of water into 50-mL plasticbottles and freeze-dried. The freeze-dried HAs were stored in adesiccator and subsequently transferred into small airproofplastic vessels for storage.

Ash contents of the obtained HAs were determined by

transferring 15–25mg of HAs into small porcelain cups andheating them in a muffle furnace overnight at 550 8C.[25]

Capillary electrophoresis

For the method for CE measurements of HAs in this work,

fragments of other works were adopted and adapted for the HAsamples of this study: The background electrolyte was a bufferconsisting of 10-mM boric acid and 10-mM sodium tetraborate(boric acid and sodium tetraborate-decahydrate; Merck); a boric

acid–sodium tetraborate buffer was for instance used in thestudy of Garrison et al.[7] A total of 5mg of HAs were dissolvedin 400mL of 1M NaOH, mixed with 3000mL of boric acid and

sodium tetraborate (16.67mM each), 1000 mL of H2O andafterwards 400mL of 1MHCl were added. Finally, 200mL of anelectro-osmotic flow (EOF) marker solution were added (1mg

acetanilidemL�1;Merck). Hence, theHAconcentration in these

M. Tatzber et al.

590

solutions was 1mg mL�1 (e.g. Schmitt-Kopplin et al.[6,13] and

Garrison et al.[7]). These solutions were well mixed and analiquot taken to fill a 1-mL polypropylene vial. The electro-phoretic measurements were performed with a HP 3DCapillary

Electrophoresis System apparatus (Hewlett-Packard,Waldbronn,Germany). The lift offset was 4mm and the temperature of thecassettemaintained at 30 8C.[6,7,20] TheCE capillarieswere fromAgilent (Waldbronn, Germany) (HPCE extended light path cap,

Part Number: G1600-62232, 50-mm inner diameter, 72-cmlength). The position of the detector window was 8.6–8.9 cmbefore the end of the capillary. The capillary was preconditioned

before each measurement by flushing with 1M NaOH, triplydistilled water and background electrolyte buffer, each for aduration of 1min. The sample was injected at a pressure of

5000 Pa for 15 s (yielding an injection volume of 50 mL); themeasurements were made with a stop time of 30min, a voltageof 30 kV[15,20] and a performance of 0.6W. The separatedfractions were detected with a photometer (Agilent interfaces,

Part NumberG1600-60230, alignment interface for 50-mm innerdiameter extended light path capillary) at the following wave-lengths: 240, 254, 280, 320 and 400 nm. The photometer had a

range from 180 to 600 nm and a resolution of 1 nm (which waspossible to calculate to 0.1 nm), the integration time was 0.5 s.As the signal-to-noise ratio decreased with increasing wave-

length, and the signal at 254 nm is known to be reliable for bothelectrophoresis and photometry,[5,7] this wavelength was chosento evaluate peaks and humps. The stability of the pH values (8.6)

of the produced solutions was controlled and affirmed. To verifythe stable conditions in the different measurement series, astandard HA sample (extracted in a past project) was recordedat least once during each series of measurements.

The capillary column had to be changed once which led to an(expected) shift between data measured using the first and thesecond capillary. This problem was solved by calculating a

mean of all acetanilide areas of the measured electropherogramsof the first column (20.4� 1.9 mAU, n¼ 102) and of the secondcolumn (48� 3 mAU, n¼ 11). This yielded a factor of 0.427,

which was multiplied with all values measured by the secondcolumn. Thereafter, the values of both capillaries were compa-rable and used for further correlations.

Elemental analyses

Themethodology for determination of organic carbon (Corg) and

total nitrogen (Nt) was as described earlier.[21,22] Briefly, car-bonate contents were determined gas volumetrically and sub-tracted from the total carbon values to obtain the organic carbon.

Total carbon (Ct) and total nitrogen contents were measured bydry combustion at 1250 8C with a LECO CN 2000 apparatus.

For HAs, carbon and nitrogen were determined by a Carlo

Erba Total Analyzer (Milan, Italy) by combustion at 1050 8Cand subsequent gas-volumetric determination of formed CO2

and N2.

Mid-infrared analyses

Mid-infrared measurements were performed as described pre-viously.[24,26] Pellets (consisting of soil in KBr; Merck) wereprepared for transmission mid-infrared spectroscopy. The full

weight of each pellet was 200 to 201mg. Each pellet included0.5mg of analyte for the L and FH layers and 1.5mg for themineral soil samples from 0 to 5 cm. The exact analyte weights

per pellet were noted for the spectra evaluation. The

mid-infrared spectra of bulk soils were recorded with a Perkin

Elmer Paragon 500 Spectrometer (Baconsfield, Buckingham-shire, UK) in the mid-infrared area (4000 to 400 cm�1). Therecordings were conducted with a resolution of 4 cm�1, weak

apodisation and 16 scans per sample. Background correctionsagainst ambient air and pure KBr were carried out at least every3 h. Band areas were integrated with corrected baselines; theobtained units were absorbance units by wavenumber (A cm�1).

These band areas were normalised by dividing the band area bythe analyte weight in the pellet, yielding absorbance units bywavenumber per milligram (A cm�1mg�1). The signal stability

was verified bymeasuring three almost identical pellets of lignin(Organosolv, Aldrich, Milwaukee, WI, USA) at least once permeasurement series. Detailed band interpretations have been

published for the humus layers and the mineral soils.[21,22]

Humic acids were measured similarly with a Bruker FT-IRspectrometer Tensor 27 (Ettlingen, Germany) apparatus andevaluated with Opus-software. This recently acquired apparatus

was used for HA determinations because of its more uncompli-cated handling for band evaluations. A 0.5-mg sample of HAwas taken for each pellet.

Formeasurements of bothHAs and bulk soils, signal stabilitywas verified by measuring three different pellets containing aknown lignin concentration (organosolv, Aldrich Chemical Co.

Inc.,Milwaukee,WI, USA, catalogue number 37, 101-7) at leastonce during every measurement series.

UV and visible absorbance measurements

UV and visible absorbance measurements were conducted as

previously described,[23] with some modifications. An Agilent8453 UV-visible spectrometer and a HA concentration of200mgL�1 was used. The observed wavelengths were 400 and

600 nm. Dissolving the HAs required dissolving 1mg of HAs in0.5mL of 1M NaOH, adding 4mL of 0.3M Na2CO3 and 0.3MNaHCO3 buffer (Na2CO3 and NaHCO3; Merck), and neu-

tralising the NaOH with 0.5mL of 1M HCl. pH stability (9.5)was controlled along with signal stability of absorbance using aHA sample of a past project. This sample was used as a standardfor the measurements to verify the signal stability of the appa-

ratus and was measured at least once during each measurementseries.

Fluorimetric measurements

Fluorimetric measurements were conducted as described pre-viously (Perkin Elmer LS50B Luminescence Spectrometer,

Norwalk, CT, USA), with certain modifications.[24,27] Similarlyto the UV and visible absorbance measurements, the HAs wereinitially dissolved in a small amount of 1M NaOH; buffer was

added and the NaOH was then neutralised with 1M HCl. Toavoid inner filter effects, a HA concentration of 15mgL�1 waschosen for all measurements.

To make sure that the single scans include the emission

maxima of HAs from different soil layers, three dimensionalscans from HAs were recorded, first, global scans for somesamples of all layers (L, FH and 0–5 cm) with Dl ranging from0 to 180 nm and an excitation wavelength range from 200 to500 nm, the increment was set at 20 nm (see Fig. 3). In a nextstep, scans of smaller wavelength ranges with higher resolutions

were recorded for L and 0–5-cm layers:

1. Dl from 75 to 115 nm and l(excitation) from 300 to 350 nm,

Dl increment of 3 nm.

Capillary electrophoresis with humic acids

591

2. Dl from 115 to 150 nm and l(excitation) from 270 to 300 nm,

Dl increment of 3 nm.3. Dl from 150 to 195 nm and l(excitation) from 225 to 260 nm,

Dl increment of 3 nm.

Based on the observed maxima in the three dimensionalscans, the following scans were recorded for each sample

(l¼wavelength):

� Scan 1: l(extinction)¼ 319 nm, l(emission)¼ 405–450 nm

� Scan 2: l(extinction)¼ 285 nm, l(emission)¼ 405–435 nm� Scan 3: Dl¼ 180 nm, l(extinction)¼ 230–260 nm.

It was unclear which maximum was responding most sensi-tively, so all three maximawere recorded. Relative fluorescenceintensities (RFIs) were taken for the evaluations. As for UV and

visible absorbance measurements, the pH was controlled (also9.5) and a standard HA sample measured at least once duringeach measurement series to verify signal stability.

Statistical analyses

Correlations of signals between the different methods werecalculated with the software PASW statistics 18 (formerlyknown as SPSS). As the data were not always normally dis-

tributed, Spearman correlation coefficients were calculated toevaluate the goodness of correlations. In this context, the para-meters for correlations of a handbook for SPSS 11[28] were

adopted: very low correlations were assigned to Spearmancoefficients (R) ranging from 0 to 0.2, low correlations toR, 0.5, medium correlations to R, 0.7, high correlations

to R, 0.9 and very high correlations to R. 0.9. Significancewas assumed at P, 0.01 (.100 samples) and labelled with anasterisk (*). Outliers were identified by an analysis of extremevalues following David et al.[29]

Results

Ranges of the basic parameters of bulk soils are provided inTable 1, ranges for basic parameters of the extracted HAs inTable 2. A selection of electropherograms for every investigated

soil layer is shown in Fig. 1. Typical electropherograms exhibitfive signals: three peaks (sharp signals) and two humps (com-parably flat signals). All evaluated regions are highlighted in this

figure. A peak deriving from acetanilide at the beginning of the

electropherogram was evaluated as an internal standard. For

signal evaluation, a base-line corrected area was integrated andthe so-called spikes (the very thin signals in the electro-pherograms attributable to small air bubbles) were subtracted if

appearing together with a peak or a hump. Furthermore, the areaof peak 3 was subtracted from hump 1 to separate their signalareas. When comparing the HA electropherograms of the pic-tured forest soil site (Fig. 1) with increasing soil depth, hump 1

changed its shape clearly in the Ah layer (0–5 cm) and seemed todecrease slightly, whereas hump 2 increased constantly. Thenumber of evaluated sampleswas always 113 except for hump 2,

where two obtained values were identified as outliers; hence, forthis signal the number of analysed samples was 111.

Fig. 2 provides mid-infrared spectra of HAs from the three

investigated soil layers of an arbitrarily selected forest soil site.In the electropherograms, the clearest differences were visiblebetween the organic layers and mineral soils. A fluorimetricthree-dimensional scan of a HA sample from an FH layer is

shown in Fig. 3, including the labelled investigated regions.Region 3 showed the highest relative fluorescence intensity.During the measurements, this region also showed the highest

sensitivity for correlations with electrophoretic signals.Fig. 4a shows the relation of the electrophoretic peak 1 to the

extraction yield of the HAs. The correlation was significant and

negative. No significant trend was detected for the signal area ofpeak 1 with HA carbon contents (Fig. 4b). The nitrogen contentsof the HAs and the areas of peak 1 showed a positive significant

correlation (Fig. 4c). Organic carbon of the bulk soils wasmedium (but significantly) correlated with peak 1 of theextracted HAs (Fig. 4d). The same was true for soil-nitrogen,although that correlation was low instead of medium (Fig. 4e).

A very similar correlation behaviour was obtained for peak 2(Table 3). The electrophoretic peak 3 showed a low negativecorrelation with the extraction yields, although still significant

(Table 3). Also here, no significant correlation was observedwith HA carbon content (Table 3). Peak 3 was also notsignificantly correlated with HA nitrogen content (Table 3).

Significant negative correlations were detected for peak 3 withsoil organic carbon and soil nitrogen contents, both being low(Table 3).

A high and significant correlation was observed between

hump 1 and the extraction yields of HAs (Fig. 5a). Again, nosignificant correlation behaviour was detectable for carboncontents in HAs (Fig. 5b), but nitrogen contents were negative

and medium and also significantly correlated with hump 1(Fig. 5c). Both soil organic carbon and nitrogen were mediumpositively and significantly correlated with hump 1 (Fig. 5d, e).

Hump 2 showed a low but significant negative correlation withthe extraction yields of HAs (Table 3). There was no significantcorrelation between carbon contents of HAs and hump 2;

nitrogen contents of HAs were correlated positively and low,although significantly with this signal (Table 3). Soil organiccarbon correlated negatively, medium and significantly withhump 2, as did soil nitrogen (Table 3), although the correlation

was weak instead of medium. The acetanilide signal did notshow any significant correlation with one of these basic soilparameters or HAs, including their yields (Table 3).

Table 4 lists correlations between evaluated mid-infraredbands (plus their assignments) and the investigated electropho-retic signals. The following mid-infrared bands showed signifi-

cant correlations with all electrophoretic signals exceptacetanilide: band number (BN) 1, 8, 10, 14, 18 and 22. Allbands with this high number of correlations contained either OH

Table 1. Ranges of basic parameters in the investigated bulk soils and

forest sites

Corg, soil organic carbon; and Nt, total nitrogen

Range Corg Nt Carbonate Mean annual

temperature

Mean annual

precipitation

(g kg�1) (g kg�1) (g kg�1) (8C) (mm)

Minimum 57.0 2.73 0.0 2.7 500

Maximum 555.3 21.87 508.3 6.6 1779

Table 2. Ranges of basic parameters in the extracted humic acids

Ct, total carbon; and Nt, total nitrogen

Range Extraction yields Ct Nt Ash contents

(g g�1) (%) (%) (%)

Minimum 0.006 37.68 1.52 0.00

Maximum 0.240 58.75 5.08 8.04

M. Tatzber et al.

592

Electrophoretic migration time (min)

Peak 3Peak 1

Acet-anilide

Peak 2

Hump 1

50

0

2

Pho

tom

etric

sig

nal (

mA

U)

4

6

8

10

12

14

10 15 20 25 30

Hump 2

Electrophoretic migration time (min)

Peak 3

Peak 1

Peak 2Acet -anilide

Hump 1

50

0

2

Pho

tom

etric

sig

nal (

mA

U)

4

6

8

10

12

14

10 15 20 25 30

Hump 2

Electrophoretic migration time (min)

Peak 3

Peak 1

Peak 2Acet -anilide

Hump 1

50

0

2

Pho

tom

etric

sig

nal (

mA

U)

4

6

8

10

12

14

(a)

(b)

(c)

10 15 20 25 30

Hump 2

Fig. 1. Selection of electropherograms of humic acids (HAs) from the three investigated layers of one of the

investigated forest soil sites. The electropherogram ofHAs from layer L (undecomposed litter) is shown in (a), mixed

samples of intermediate decomposed and highly decomposed organic matter (FH) in (b) and the electropherogram of

HAs from the upper mineral soil layers (Ah horizon) from 0–5 cm in (c). The investigated electrophoretic signals are

highlighted. Note the change in the height and shape of some electrophoretic signals with the different soil layers,

especially hump 1.

Capillary electrophoresis with humic acids

593

groups or groups of aromats or olefins. Three significantcorrelations with electrophoretic signals were observed for

BN 6 and 16, two for BN 7 and 20, and one for BN 3, 11, 17and 21. No significant correlations were obtained for BN 2, 4,5, 12, 13, 15, 19, 13 and 24. When there was significance

between mid-infrared band areas and electrophoretic signals,

most correlations were low (35 cases); a minority of sevencorrelations was medium. None of these correlations was

high. For all significant correlations, hump 1 showed a comple-mentary behaviour compared with the four other electrophoreticsignals. Bands assigned to carboxyl groups showed few or no

significant correlations with peaks or humps.

3500 3000 2500 2000 1500 5001000

L

FH

0–5 cmTran

smis

sion

(ar

bitr

ary

units

)

Wavenumber (cm�1)

Fig. 2. Arbitrarily selectedmid-infrared spectra of humic acids (HAs) from the different layers of an investigated forest

soil site; also here the clearest differences are visible between the organic layers (undecomposed litter, L, and mixed

samples of intermediate decomposed and highly decomposed organic matter, FH) and the mineral soil (0–5 cm).

Dal

ta L

ambd

a (Δ

λ, n

m)

Excitation wavelength (nm)

500.0

2.9336

0.4253

5.4419

7.9502

10.4585

12.9668

15.4751

17.9834

20.4917

23.0000

�2.0830450400350300250200.0

0.0

20

40

60

80

120

140

160

180

195.0

X Region 3

Region 2

Region 1

X

X

100

Fig. 3. Three-dimensional scan of a humic acid (HA) from an FH (mixed samples of intermediate

decomposed and highly decomposed organic matter) layer of a forest soil. The three investigated

fluorimetric regions are highlighted.

M. Tatzber et al.

594

Spearman coefficient: �0.656*

0.000.0

0.5

1.0

1.5

2.0

2.5

3.0(a) (b)

0.05 0.10 0.15 0.20 0.25 0.30

Ele

ctro

phor

etic

pea

k 1

(mA

U)

HA yield (g kg�1)

Spearman coefficient: �0.131

HA-C (%)

2.5

3.0

2.0

1.5

1.0

0.5

0.00 10 20 30 40 6050 70

Ele

ctro

phor

etic

pea

k 1

(mA

U)

(c) (d)Spearman coefficient: 0.600*

HA-N (%)

3 4 5 62100.0

0.5

1.0

1.5

Ele

ctro

phor

etic

pea

k 1

(mA

U)

2.0

2.5

3.0 Spearman coefficient: �0.646*3.0

2.5

2.0

1.5

1.0

0.5

0.01000 200 300 400 500 600

Ele

ctro

phor

etic

pea

k 1

(mA

U)

Soil Corg (g kg�1)

(e) Spearman coefficient: �0.451*3.0

2.5

2.0

1.5

1.0

0.5

0.00 5 10 15 20 25

Ele

ctro

phor

etic

pea

k 1

(mA

U)

Soil Nt (g kg�1)

Fig. 4. Correlations of electrophoretic peak 1 with basic humic acid (HA) parameters (extraction yields (a), carbon contents (HA-C) (b), and N contents

(HA-N) (c)) and the respective soil samples (organic carbon (Corg) (d) and total nitrogen (Nt) (e)).

Table 3. Spearman coefficients of basic parameter of soils and humic acids

Significant correlations within rows are labelled with asterisks (*)

Basis parameter Peak 2 Peak 3 Hump 2 Acetanilide (control)

Extraction yield of HAs (g g�1) �0.588* �0.238* �0.405* 0.053

Carbon contents in HAs (%) �0.079 �0.131 �0.122 0.024

Nitrogen contents in HAs (%) 0.545* 0.145 0.278* �0.038

Organic carbon in soils (g kg�1) �0.639* �0.428* �0.575* �0.021

Total nitrogen in soils (g kg�1) �0.391* �0.248* �0.403* 0.027

Capillary electrophoresis with humic acids

595

Table 5 provides correlations of electrophoretic signals andmid-infrared signal intensities of the bulk soil samples, fromwhich the HAs were extracted. Four mid-infrared bands corre-

lated significantly with all investigated electrophoretic signals:BN II, V, VII and IX. BN III correlated significantly with fourelectrophoretic signals, BN VIII with three, and BN I and VI

with two of them. None of these mid-infrared bands showed oneor no significant correlations with evaluated areas from electro-pherograms. Again, hump 1 showed a complementary behav-

iour compared with the other signals, whenever there was

significance. As for mid-infrared spectroscopy of HAs, mostcorrelations were low (23 cases), some were medium (9 cases)and none were high or very low.

Table 6 includes correlations between electrophoretic signalsand UV and visible absorbance and fluorimetric signal intensi-ties. All fluorimetric signals correlated with every electropho-

retic peak and hump. Three electrophoretic signals weresignificantly correlated with the UV and visible absorbance at600 nm and two with the absorbance at 400 nm. None of these

signals correlated significantly with acetanilide and (as in all

Spearman coefficient: 0.708*

00.00

0.05

0.10

0.15

0.20

0.25

0.30(a) (b)

200 400 600

Ele

ctro

phor

etic

hum

p 1

(mA

U)

HA yield (g g�1)

Spearman coefficient: �0.018

HA-C (%)

2.5

3.0

2.0

1.5

1.0

0.5

0.00 100 200 300 400 600500 700

Ele

ctro

phor

etic

hum

p 1

(mA

U)

(c) (d)Spearman coefficient: �0.525*

HA-N (%)

3 4 5 62100

100

200

300

Ele

ctro

phor

etic

hum

p 1

(mA

U)

400

500

700

600

Spearman coefficient: �0.568*700

600

500

400

300

200

100

01000 200 300 400 500 600

Ele

ctro

phor

etic

hum

p 1

(mA

U)

Soil Corg (g kg�1)

(e) Spearman coefficient: 0.579*700

500

600

400

300

200

100

0�10 �5 0 105 15 20 25

Ele

ctro

phor

etic

hum

p 1

(mA

U)

Soil Nt (g kg�1)

Fig. 5. Correlations of electrophoretic hump 1 with basic humic acid (HA) parameters (extraction yields (a), carbon contents (HA-C) (b) and N contents

(HA-N) (c)) and the respective soil samples (organic carbon (Corg) (d) and total nitrogen (Nt) (e)).

M. Tatzber et al.

596

cases before) hump 1 showed, with respect to significance

of correlations, a complementary behaviour compared withthe other electrophoretic signals. Except for hump 1 (wherenegative correlations were obtained), all significant signals

correlated positively with fluorimetric and UV and visibleabsorbance signals.Most of the obtained significant correlationswere low (14 cases), a fewmedium (6 cases), and no high or very

low significant correlations were observed.Table 7 shows the correlations between the electrophoretic

signals amongst each other. Peak 1, peak 2 and hump 2

correlated with four other signals significantly, peak 3 and hump2with three signals. Hump1was only negatively correlatedwithother electrophoretic signals; the remaining signals correlatedpositively. Acetanilide was correlating significantly once, with

peak 3; no other significant correlations were obtained for thissignal. One high correlation was obtained (between peak 1

Table 4. Spearman coefficients of mid-infrared bands of extracted humic acids

Significant correlations within rows are labelled with asterisks (*). For assignments of mid-infrared bands to functional groups see also Tatzber et al.[23]

Integration base

points (cm�1)

Band number Assignments to functional groups Peak 1 Peak 2 Peak 3 Hump 1 Hump 2 Acetanilide

(control)

3119–3015 1 Aromatic groups 0.525* 0.618* 0.434* �0.465* 0.459* 0.056

2991–2866 2 Aliphatic groups 0.022 �0.033 �0.057 �0.175 �0.084 �0.050

2864–2819 3 Aliphatic groups 0.197 0.082 0.186 �0.424* 0.175 �0.054

2664–2393 4 Carboxyl groups, amines 0.068 0.110 0.234 �0.019 0.157 �0.062

1796–1699 5 Carbonyls �0.117 0.071 0.088 0.081 �0.021 �0.010

1699–1684 6 Aryl-aldehydes and -ketones �0.329* �0.341* �0.167 0.113 �0.284* �0.049

1683–1654 7 a,b-unsaturated ketones, amides 0.320* 0.222 0.143 �0.433* 0.157 �0.021

1653–1570 8 –NH2, C=C, carboxylates �0.386* �0.282* �0.295* 0.458* �0.378* 0.057

1559–1541 9 Carboxylates, C–NO2, C=C 0.226 0.207 0.165 �0.270* 0.091 �0.033

1526–1490 10 N–H, C=C �0.343* �0.372* �0.508* 0.242* �0.551* �0.104

1474–1458 11 Aliphatic groups (deformation) �0.141 �0.203 �0.163 �0.120 �0.286* �0.082

1458–1443 12 Aliphatic groups (deformation) �0.242 �0.138 0.065 0.136 �0.199 �0.045

1438–1402 13 Amides, carboxylates 0.114 0.161 0.164 �0.120 0.152 �0.085

1402–1348 14 Acetyl groups, –C(CH3)2, –C(CH3)3, OH �0.302* �0.324* �0.317* 0.294* �0.397* 0.068

1343–1313 15 OH, sulfones, esters 0.102 0.040 �0.155 �0.043 �0.152 �0.117

1305–1250 16 OH, nitrates, =C–O–C, phenols �0.374* �0.279* �0.141 0.348* �0.165 0.016

1241–1181 17 COOH, aryl ethers, phenols, =C–O–C 0.044 �0.001 �0.245* 0.011 �0.221 �0.022

1168–1105 18 Aliphatic OH, ethers �0.611* �0.555* �0.294* 0.582* �0.474* 0.034

1080–1001 19 Silicates, polysaccharides, aliphatic

ethers, alcohols, =C–O–C

0.094 0.149 �0.005 �0.223 0.020 �0.026

992–912 20 RCH=CH2; RCH=CHR �0.212 �0.257* �0.058 0.378* �0.131 0.138

910–879 21 R2C=CH2 0.205 0.145 0.030 �0.302* 0.053 0.021

875–802 22 aromatic systems, R2C=CRH �0.263* �0.379* �0.356* 0.187 �0.430* �0.005

798–781 23 aromatic systems �0.060 �0.176 �0.076 0.161 �0.111 0.031

779–712 24 sp3-CH2, benzene rings �0.111 �0.060 0.197 0.125 0.092 0.168

Table 5. Spearman coefficients of mid-infrared bands of bulk soils from which humic acids were extracted

Significant correlations within rows are labelled with asterisks (*). For assignments of mid-infrared bands to functional groups see also Tatzber et al.[21]

Integration base

points (cm�1)

Band number Assignments to functional groups Peak 1 Peak 2 Peak 3 Hump 1 Hump 2 Acetanilide (control)

3107–3042 I Aryl-H, alkenes �0.200 �0.254* �0.146 0.380* �0.189 0.043

2989–2877 II Aliphats �0.512* �0.523* �0.331* 0.459* �0.500* �0.084

2873–2836 III Alpihats �0.474* �0.474* �0.203 0.416* �0.383* �0.057

2562–2480 IV Carbonate �0.228 �0.155 �0.290* 0.164 �0.169 �0.080

1185–1144 V Aliphatic OH, ethers �0.460* �0.512* �0.415* 0.389* �0.562* �0.137

1136–1070 VI Quartz, polysaccharides, alcohols, alkyl ethers 0.267* 0.189 0.144 �0.315* 0.167 �0.021

945–887 VII Alkenes, pyranose rings in carbohydrates,

malonic or benzoic acids

0.539* 0.549* 0.504* �0.426* 0.598* 0.089

887–866 VIII Carbonate 0.174 0.310* 0.085 �0.255* 0.251* �0.040

820–752 IX Alkenes, phenyls with three adjacent H’s 0.448* 0.446* 0.465* �0.459* 0.430* 0.059

Table 6. Spearman coefficients for correlations of electrophoretic

signals with photometric signals at 400 and 600 nm and fluorescence

Significant correlations within rows are labelled with asterisks (*)

Signals Peak 1 Peak 2 Peak 3 Hump 1 Hump 2 Acetanilide

(control)

Photometry at

400 nm

0.008 0.121 0.386* �0.048 0.357* 0.085

Photometry at

600 nm

0.158 0.314* 0.608* �0.195 0.544* 0.116

Fluorescence

(Region 1)

0.301* 0.377* 0.464* �0.395* 0.516* 0.017

Fluorescence

(Region 2)

0.321* 0.418* 0.488* �0.461* 0.511* �0.161

Fluorescence

(Region 3)

0.440* 0.498* 0.500* �0.484* 0.620* 0.023

Capillary electrophoresis with humic acids

597

and 2), two medium and seven low correlations. A calculateddiscriminant function for testing the potential of differentiation

into groups of soil layers is shown in Fig. 6. Function 1 had aneigenvalue of 2.166, explained 97.6% of the variance andshowed a canonical correlation of 0.827. This function was

dominated by peak 3, hump 1 and peak 1; Wilks–Lambdashowed a highly significant difference (P, 0.001) betweenthe mean values of the discriminant function in the differentgroups. Function 2 had an eigenvalue of 0.052, explained 2.4%

of the variance and included a canonical correlation of 0.223.Dominating signals were hump 1, peak 3 and peak 2. Wilks–Lambda of function 2 showed no significant difference between

mean values of the discriminant function in the different groups(0.241).

Discussion

The electropherograms shown in Fig. 1 were typical for HAs, as

other earlier published works show, especially for the appliedbuffer milieu.[5–6] This supports the procedure developed andused for capillary electrophoretic measurements with HAs in

this study. The third peak of the spectra (see Fig. 1) is a wellknown artefact reflecting the borate buffering systems, where

borate ions form complexes with for example 1,2-doils, 1,3-diols or both.[5–6] The spectra for fluorescence and mid-infraredmeasurements were also expected for HAs (Figs 2, 3) based on

earlier studies.[24,27] The high diversity of the investigatedextracted HAs is reflected by both basic data of soils and HAs(Tables 1, 2). This diversity can be explained by the high vari-

ability of the 139 investigated forest sites regarding soil type, sealevel, vegetation, tree species etc.

The potential of the electrophoretic signals to reflect soil

characteristics is quite remarkable, as shown by the significantcorrelations with soil Corg and Nt as well as the extraction yieldsof HAs, representing the pool size of this soil fraction (see Figs4, 6a, d, e, Table 3). This was true for all electrophoretic signals;

the highest correlations were obtained for hump 1 and peak 1when referring to yields, for peak 1, 2, hump 1 and 2with respectto Corg, and for hump 1 and peak 1 regarding soil Nt. Note also

that the electrophoretic signals reflect Corg and extraction yieldsbetter than soil Nt. A completely different picture was obtainedwhen relating signals to the carbon and nitrogen contents in the

HA fractions (Figs 4, 6a, d, e, Table 3). Here, not a singlecorrelation was significant between electrophoretic signals andcarbon contents in HAs, showing that the carbon in soils isclearly better reflected in extraction yields than in HA carbon

contents. The good correlations of the electrophoretic signalswith both soil carbon and extraction yields of HAs showed thatelectrophoretic signals represented quite selective parts of SOM

inside the HA fractions; these parts were indicative for both thepool size of HAs as well as the size of the bulk organic carbonpool in soils.

Another interesting relation of electrophoretic signals con-cerns the behaviour of nitrogen contents in HAs. This behaviourwas significantly connected with all electrophoretic signals

except peak 3 (that peak being an artefact[6]) and behavedinversely to total soil nitrogen. The inverse correlation HAnitrogen content with hump 1, which in turn correlated positivelywith extraction yields, Corg and soil Nt (as also supported by the

other electrophoretic signals) points towards a stabilised frac-tion of soil organic nitrogen (Fig. 5, Table 3). In their review,Sutton and Sposito describe soil humic substances as ‘collec-

tions of diverse, relatively low molecular mass componentsforming dynamic associations stabilised by hydrophobic inter-actions and hydrogen bonds’.[30] The detailed discussion

on the nature of nitrogen in HAs there concludes that amideN in peptides is usually the dominant chemical form of N inhumic substances.[30] In an important concept paper, protein N

in soils is described as ‘usually considered labile’.[31] Thatpaper includes two studies in which stability in soils is eitherconnected with preservation as cross-linked melanoidin-like

Table 7. Spearman coefficients for correlations of electrophoretic signals among themselves

Significant correlations within rows are labelled with asterisks (*)

Signals Peak 1 Peak 2 Peak 3 Hump 1 Hump 2 Acetanilide (control)

Peak 1 1.000 0.710* 0.284* �0.519* 0.442* 0.036

Peak 2 0.710* 1.000 0.356* �0.471* 0.440* 0.015

Peak 3 0.284* 0.356* 1.000 �0.185 0.588* 0.306*

Hump 1 �0.519* �0.471* �0.185 1.000 �0.327* 0.126

Hump 2 0.442* 0.440* 0.588* �0.327* 1.000 0.145

Acetanilide (control) 0.036 0.015 0.306* 0.126 0.145 1.000

Function 1

5.02.50.0�2.5�5.0

Fun

ctio

n 2

5.0

2.5

0.0

�2.5

�5.0

3

2

1

Centres of groups3 � Ah, 0–5 cm

2 � FH1 � L

Layer

Fig. 6. A discriminant function based on the five evaluated electrophoretic

signals. Function 1 of this analysis successfully and significantly separated

humic acids (HAs) from organic layers from those of mineral soils.

M. Tatzber et al.

598

materials[32] (also explaining the dark colour of stabilised SOM)

or with stabilisation by association with mineral surfaces.[33]

The important role of melanoidin-like substances (formed bycatalysedMaillard reactions) in the genesis of humic substances

is also supported by Jokic et al.[34] andHuang.[35] Combining theoutcome of these studies suggests protected protein structures ormelanoidin-like fragments in associations of low molecularweight in the HA fraction, which were correlated with electro-

phoretically separated fractions. The expectation is that thesefractionswere connectedwith the respective charged groups andelectrophoretically separated together with them. This interpre-

tation would agree with the stabilised nature of nitrogen in HAs,which is also expressed by the C/N ratios. For C/N in HAs, thecorrelations were �0.693* with peak 1, �0.596* with peak 2,

�0.205 with peak 3, 0.539* with hump 1 and �0.335* withhump 2. Correlating electrophoretic signals with C/N in therespective bulk soil samples yielded coefficients of�0.629* forpeak 1, �0.663* for peak 2, �0.453* for peak 3, 0.472* for

hump 1 and �0.593* for hump 2.The analysis of the electrophoretic signals demonstrates that

hump 1 represents a different SOM fraction than the rest of the

electrophoretic signals: whenever there was a significant rela-tion to independent data, it showed an inverse behaviour. Thefact that hump 1 increased with carbon and nitrogen in soils and

that it decreased with the HA nitrogen suggests that this fractionrepresents younger components in the HAs. An earlier studybased on 14C labelled material showed that HAs extracted with

1M NaOH consisted largely of younger materials and a clearlysmaller (but constantly present) proportion of older compo-nents.[24] Accordingly, hump 1 represented the highest signalarea compared with the other signals. As mentioned above,

peak 3 was identified as an artefact related to the bufferingsystem.[5–6] Its significant correlations show that it is stillreflecting certain basic soil properties. Schmitt-Kopplin et al.[6]

conclude that borate complexation can be used as a probe toprovide structural information about polyols in HAs. This agreeswith the significant behaviour of peak 3with the extraction yields

of HAs, soil Corg and soil Nt, given that these parameters areconnected with polyols. The fact that the reference signal ofadded acetanilide did not correlate significantly with any of thesoil or HA parameters shown in Figs 4 and 5 and Table 3 further

supports the reliability of the obtained electrophoretic results.This reliability was also valid for the evaluated and correlated

mid-infrared signals (Tables 4, 5): the acetanilide signal showed

no significance for any of the mid-infrared signals, neither forHAs nor for soils. Many significant correlations were obtainedfor mid-infrared bands and the other evaluated electrophoretic

signals. An overview of Tables 4 and 5 reveals a clearly highernumber of significant correlations of mid-infrared signals fromsoils v. HAs. This reflects the basic parameters of soils and HAs

in Figs 4, 5 and Table 3. There, the correlations were also higherwith the bulk soil parameters than with HA characteristics. Theelectrophoretically separated fractions from HAs are clearlyindicative not only for basic parameters in bulk soils, but also for

characteristics of at least some functional groups. This makesthis methodology very promising for further investigations.Mid-infrared signals in HAs assignable largely to aromatic

characteristics (BN 1, 8 and 20–21) and alcohols (14, 16 and18, see Table 4) showed significant correlations with electro-phoretic signals. The area of stretching vibrations was more

reliable and the focus was therefore on the bands located there.Here, two additional aspects deserve mention: First, there wereno correlations with the very broad and undisturbed band 4

assignable to carboxyl groups. This bandwas expected to show a

very strong correlation with electrophoretic signals becausethese groups are negatively charged in the borate–tetraboratebuffer milieu. Schmitt-Kopplin et al. described three regions for

assignments: an aldehydes’ region, a phenolic acids’ region anda dicarboxylic region.[13] As we found no correlations ofelectrophoretic signal intensities with BN 4 (Table 4), weconcluded that the number of carboxylic groups was responsible

only for the position in the electropherogram, not for the signalintensities. This is plausible when considering the UV andvisible absorbance detection of the electrophoretically separated

fractions at 254 nm. This detection principle is correlated only toaromatic information and underlines the need for advanceddetection principles to recognise and evaluate capillary electro-

phoretically separated fractions. Against this background, how-ever, the correlation behaviour of infrared BN 4 appearsplausible and suggests that some fractions were simply notdetected with the present electrophoretic arrangement. The

second interesting aspect was that there was no correlationbetween aliphatic groups of the HAs themselves, but definitelywith aliphatic signals from the soils. This shows that the

compounds which were electrophoretically separated anddetected by UV and visible absorbance measurements wereindicative for aliphaticity in the bulk soils. In the context with

mid-infrared signals from soils, we declined to draw conclusionsabout aromaticity. This was because BN I (Table 5) wasassumed to be overlaid by the other bands, especially the OH

band, or BN I was modified by band interactions. Nonetheless,the comparison of electrophoretic results with mid-infraredsignals did affirm the indicative potential of electrophoreticsignals for soil characteristics (included in HAs).

The spectroscopic signals listed in Table 6 were availableonly for HAs (because soils are not completely soluble andhence not determinable with these methods). Each fluorimetric

signal showed significant correlations with each electrophoreticsignal. However, region 3 always had the highest correlationcoefficients. The finding that the fractions detected with 254 nm

correlated better with the UV and visible absorbance at 600 v.400 nm was unexpected. Furthermore, the correlations of theelectrophoretic with fluorimetric and UV and visible detected(Table 6) signals agreedwith the behaviour of the aromatic BN1

(Table 4) in the area of stretching vibrations. This, however,appeared explainable when considering the difference betweenthe overall UV and visible absorbance and the absorbance of the

fractions. Accordingly, we conclude that the electrophoreticfractions were connected with the overall aromaticity of theHAs. Garrison et al.[7] investigated the potential of high perfor-

mance CE (especially in the free solution mode) in measuringHAs and FAs. For the latter, a series of sharp and early elutingpeaks was obtained, which were anionic in nature and had a UV

absorptivity at 254 nm.[7] The authors suggested an aromaticcharacter of these peaks which could derive from e.g. ligninmonomers or biomolecules adsorbed or entrapped on the basichumic polymeric network.[7] The HAs extracted with 1M

NaOH are clearly the fraction of brown HAs, which are moreclosely related to FAs than to grey HAs (which are usually betterextracted by sodium pyrophosphate). Combining this informa-

tion suggests that peaks 1 and 2 could be similar to theinterpreted FA peaks obtained in Garrison et al.[7] The signifi-cant positive correlations with fluorescence signals (Table 6)

and band 1 of mid-infrared spectroscopy (Table 4) support thisinterpretation. In a study of He et al. CE and fluorescenceexcitation–emission matrix spectroscopy were performed in

Capillary electrophoresis with humic acids

599

parallel for characterisations of humic substances.[19] Excitation–

emission matrix fluorescence spectroscopy on capillary electro-phoretically collected fractions revealed that each of the 13investigated humic substance samples contained four fluoro-

phore components, whose relative abundance varied among thethree CE fractions.[19] They concluded that ‘quasi-particles orgroups of compounds in the investigated humic samples wereseparated at least partly by CE’.[19] This is in line with the

correlation behaviour of the single CE signals with the fluori-metric signals (Table 6). This would indicate that fluorophorecomponents were preferably depleted with increasing signal

intensity in the hump 1 fraction and enriched with increasingsignal intensity for the other fractions (peaks 1–3 and hump 2),especially for region 3.

Comparing the electrophoretic signals amongst each otherconfirmed the special behaviour of hump 1. Here, one signifi-cant low positive correlation of the acetanilide signal wasobserved with peak 3. This would suggest at least some affinity

of acetanilide with the complexes between the polyalcohols andthe HAs. Referring to the other signals, peaks 1, 2, 3 and hump 2seemed to be more closely related to each other than to hump 1,

because they exhibited only positive correlations. The suitabilityof the electrophoretic method was further supported by thewell separated groups of HAs from organic soils (centres 1

and 2 in Fig. 6) and mineral soils (centre 3 in Fig. 6). Thiscalculation was carried out solely with electrophoretic signalsand showed once again that electrophoresis ofHAs reflected soil

characteristics quite well. Furthermore, this outcome agreeswith the electrophoretically derived ‘fingerprint’ informationreported by other studies.[15,20] The ability for fingerprinting ofCE measurements is further supported by other studies[6,13] and

a review,[5] and all of these works mention the buffer milieuas the key question for handling of the obtained signals. Intwo works of Schmitt-Kopplin et al. fingerprinting of HAs in

borate buffer milieus is reported and the formation of peaks isattributed to formation of complexes with the borate buffer.[6,13]

Furthermore, CE is described as particularly useful when

comparing series of humic fractions involved in processes suchas degradations or pollutant interactions.[13] 11B NMR signalswere used to find the origin of variations in borate complexationin differences of structures of various humic substances[6] and

hence pointed to the direction that HAs were involved in thesecomplexes.

This study achieved its aims: the electrophoretic approach

was applied successfully to a highly diverse set of HA samplesfrom different forest sites. Important characteristics of SOMwere reflected by the electrophoretic signals. The discriminant

function further showed that this approach was able to differen-tiate between HAs from organic layers andmineral soils. Globalassignments were possible, especially for hump 1, which proba-

bly represented a ‘younger’ fraction compared with the otherelectrophoretic fractions. Further investigations would be need-ed to improve assignments. The hypothesis that electrophoreticsignals were connected with carboxyl groups determined by

mid-infrared spectroscopy could not be confirmed; however, arelation to alcohols and clearly to aromatic information wasderived. There is significant potential for improvement of this

method if the detection principle is further developed. Detectionprinciples registering aliphatic components for example woulddeliver valuable additional information because fractions other

than aromatic ones are no doubt separated electrophoretically.This aspect opens another interesting perspective for furtherstudies in this field.

Conclusions

1. An electrophoretic approach for the analysis of HAsextracted with 1M NaOH was successfully developed in

this study.2. The signals were reliable because the EOF marker acetani-

lide showed only one significant correlation, which could be

explained by an association with the borate artefact peak inthe electropherograms.

3. The signals of the electropherograms reflected soil character-isticswell; thiswas evident in a significant separation of groups

of HAs from soil layers by a calculated discriminant function.4. The overall correlations of the electrophoretic signals were

sometimes even higher for bulk soil parameters than for HA

parameters. This shows that the approach developed hereclearly separated HA fractions that were more indicative forsoil characteristics than the bulk fraction of extracted HAs.

5. This method was applicable to a very diverse set of soilsamples, suggesting it be applied to more special questionsincluding soil samples with less variable characteristics.

6. A detection method for electrophoretic fractions is neededthat detects not only overall aromatic information but alsonon-aromatic electrophoretically separated groups (whichare expected to be more aliphatic).

Acknowledgements

This work was financed by the Austrian Federal Ministry of Agriculture,

Forestry, Environment andWater Management. The authors are grateful for

valuable technical support by Walter Frank and helpful suggestions by

Leonhard Jaitz, Maria Furhacker and Astrid Hobel during the capillary

electrophoretic measurements. The authors appreciated the elemental

analyses of the bulk soils, which were conducted by Raffaela Wettl and

Eugenie Fink, as well as of HAs, conducted by Elisabeth Cuncl and Ewald

Brauner. The authors also thankKerstin Petrautzki for extracting the HAs, to

Johanna Vilsmaier for the spectroscopic measurements of the HAs, and to

Andrea Fuhrmann for preparing the pellets for the mid-infrared measure-

ments of the bulk soil samples. The authors are much obliged to Michael

Stachowitsch for valuable linguistic support.

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