Analytical and Bioanalytical Chemistry

, Volume 386, Issue 2, pp 306–312 | Cite as

Quantification of abscisic acid in grapevine leaf (Vitis vinifera) by isotope-dilution liquid chromatography–mass spectrometry

  • Francisca Vilaró
  • Anna Canela-Xandri
  • Ramon Canela
Original Paper

Abstract

A specific, sensitive, precise, and accurate method for the determination of abscisic acid (ABA) in grapevine leaf tissues is described. The method employs high-performance liquid chromatography and electrospray ionization–mass spectrometry (LC-ESI-MS) in selected ion monitoring mode (SIM) to analyze ABA using a stable isotope-labeled ABA as an internal standard. Absolute recoveries ranged from 72% to 79% using methanol/water pH 5.5 (50:50 v/v) as an extraction solvent. The best efficiency was obtained when the chromatographic separation was carried out by using a porous graphitic carbon (PGC) column. The statistical evaluation of the method was satisfactory in the work range. A relative standard deviation (RDS) of < 5.5% and < 6.0% was obtained for intra-batch and inter-batch comparisons, respectively. As for accuracy, the relative error (%Er) was between −2.7 and 4.3%, and the relative recovery ranged from 95% to 107%.

Keywords

Abscisic acid Isotopically labeled internal standard LC-ESI-MS Vitis vinifera Grapevine leaf 

Introduction

Plant hormones are natural products that act at low concentrations and regulate important processes during a plant’s life cycle. Among these, abscisic acid (ABA), a monocyclic sesquiterpenoid, is involved in the regulation of many stress-induced gene-expressions and confers the plant with adaptability towards drought, salinity, cold, and other environmental stresses [1]. In plant cells, ABA is continually synthesized and degraded. Catabolism can then occur by several routes involving oxidation, reduction, and conjugation [2]. The study of the variation of ABA concentration in different plant tissues can therefore provide knowledge on the ABA biosynthesis and degradation pathways and the correlation with different physiological and environmental parameters [3, 4, 5].

In recent years, some studies carried out to increase water efficiency have shown that the rational control of irrigation in grapevine promotes the biosynthesis of ABA. The increase in ABA content reduced vegetative vigor and increased the antocyanin concentration in berries. These phenomena occurred without a significant reduction in crop and berry size [6, 7]. These results suggested that the ABA level in leaf tissue could be used as a quality index for the wine obtained. An accurate and fast analytical method is needed to determine ABA contents in plant tissues.

Numerous analytical techniques have been used to detect and quantify ABA in plant tissues. Although the most commonly used techniques are based on gas chromatography–mass spectrometry (GC-MS), they involve several steps of intense purification and a derivatization step prior to analysis [8, 9, 10]. ELISA tests using anti-ABA monoclonal antibodies have also been used to determine ABA in plant tissues [11]; however, this technique also requires a purification step to avoid cross-reactivity with other plant compounds.

In recent years, liquid chromatography–tandem mass spectrometry (LC-MS/MS) techniques have been developed for the analysis of this phytohormone in some plant tissues, although not in grapevine, that do not require purification and/or derivatization steps [12, 13, 14, 15]. In addition, an easily prepared isotopomer of the analyte has been described as an internal standard (IS) [12]. The use of a stable isotope-labeled internal standard for ABA quantification would provide the necessary precision and accuracy by compensating for both ABA losses in the extraction step and the non-specific matrix effects caused by co-eluting components [16, 17]. However, it is well accepted that the sample preparation for the quantification of ABA is very different depending on the sample matrix and the detection technique applied [12, 13, 14, 15]. For example, Ross et al. [13] showed that extraction and clean-up procedures for two different vegetal matrices should be different to obtain accurate results.

In this study, we present an analytical method developed for specific detection and accurate quantification of ABA in grapevine leaf using LC-MS with negative ion electrospray ionization (ESI−). Hexadeutero-ABA [12] was used as an internal standard. We demonstrated the usefulness of the method by quantifying ABA in several grapevine leaf samples collected under various irrigation conditions.

Experimental

Chemicals

(±)-Abscisic acid [CAS Registry N° 14375-45-2, 99% purity, ref. A1049] (see Fig. 1), deuterium oxide (isotopic purity 99.96%, ref. 151890), and 30% wt. deuterated sodium hydroxide in deuterium oxide (minimum isotopic purity 99%, ref. 164488) were acquired from Sigma–Aldrich Química S.A (Madrid, Spain). Acetone and acetonitrile (HPLC-grade purity) were purchased from J.T. Baker (Deventer, The Netherlands). Formic acid (98–100% extra pure quality) was purchased from Merck (Barcelona, Spain). Methanol, dichloromethane, and diethyl ether (PA-grade purity) were purchased from Panreac (Barcelona, Spain). Water was prepared using a Milli-Q reagent water system. Specifications for columns used for analysis are cited below.
Fig. 1

Chemical structure of abscisic acid (ABA)

Preparation of deuterated abscisic acid

[2H6]-ABA was synthesized using a base exchange mechanism on (±)-ABA as described elsewhere [12, 18]. We evaluated the purity of the [2H6]-ABA obtained by LC-MS using the conditions indicated below. No unlabeled ABA was detected in the [2H6]-ABA synthesized.

Preparation of standard solutions

Stock standard solutions of ABA (189 nmol mL−1) and [2H6]-ABA (315 nmol mL−1) were prepared by dissolving appropriate amounts of each compound in 30% acetonitrile in water containing 0.1% formic acid (standards solvent). The solutions were stored in the dark at −18 °C and were found to be stable for at least 3 months.

Intermediate standard solutions of ABA and [2H6]-ABA were prepared by tenfold dilution of the stock standard solutions with the standard’s solvent. These solutions were freshly prepared every month and stored in the dark at −18 °C.

The standard levels used for the calibration curve were 800, 400, 200, 100, and 50 ng mL−1. They were prepared by dilution of intermediate standard solutions with the standards solvent. [2H6]-ABA was added as an internal standard to each solution to achieve a concentration of 700 ng mL−1 for the LC-MS analysis. These standard solutions were freshly prepared every month and stored in the dark at −18 °C.

Sample preparation

Grapevine (Vitis vinifera) leaves were collected from vineyards in Lleida, Spain. Each sample was immediately frozen in liquid nitrogen, lyophilized, and milled to obtain a fine powder. The processed samples were stored under dry conditions at room temperature.

Extracting solvent test

Grapevine leaf samples were spiked with [2H6]-ABA at 2 nmol g−1 level and extracted as described below. One of the following solutions was used in each case: water at pH 3, water at pH 5.5, 1% sodium bicarbonate (NaHCO3) solution, or methanol/water pH 5.5 (50:50 v/v). The essays were carried out in triplicate.

Extraction procedure

One hundred milligrams of powder material was placed in a 50-mL glass beaker and mixed with 1.26 nmol of internal standard (40 μL of 31.5 nmol mL−1 intermediate standard solution) using a magnetic stirrer for 5 min. The sample was extracted with 10 mL methanol/water pH 5.5 (50:50 v/v) using a magnetic stirrer for 20 min. The mixture was poured through a polyethylene frit with 20-m pore size (Supelco, Sigma-Aldrich S.A., Madrid, Spain). The remaining solid was extracted by repeating the same procedure. The filtrates were joined and extracted twice with 10 mL dichloromethane. The dichloromethane extracts were joined and evaporated under vacuum conditions at 40 °C. The residue was dissolved in 100 μL acetone and 250 μL water/acetonitrile (70:30 v/v) (0.1% formic acid).

LC-MS conditions

Analyses were performed using an in-line LC-MS system equipped with an ESI ion source. The LC separations were carried out at room temperature and in the isocratic mode using a Waters Alliance 2695 separation module (Waters Corp.). The injection volume was 20 μL. Two columns were tested, a 150×2.1-mm i.d. Symmetry C18 packed with 5-μm particles (Waters Corp., Barcelona, Spain) and a 100×2.1-mm i.d. Hypercarb PGC packed with 5-μm particles (Hypersil division of TermoQuest, Barcelona, Spain). The mobile phase was water/acetonitrile (70:30 v/v) (0.1% formic acid) at a flow rate of 0.2 mL min−1.

The MS detector (Micromass ZMD 2000) consisted of a single-quadrupole mass spectrometer equipped with a Z-spray API source (Waters Corp.). The MS was operated in the negative ESI mode. The source was operated with N2 (LCMS quality) at a 400 L h−1 gas flow. MS parameter were optimized by flow injection analysis (FIA) of the individual solutions of the ABA and [2H6]-ABA. These compounds gave a response in the ESI interface in the negative mode but not in the positive mode. The capillary voltage was varied from 2.0 to 3.5 kV and the cone voltage from 10 to 80 V. Optimized conditions for MS were: desolvation temperature, 350 °C; source temperature, 120 °C; capillary voltage, 3.0 kV; cone voltage, 30 V; extractor voltage, 5 V.

For the ABA and [2H6]-ABA, the most abundant and characteristic ion was chosen for quantification ([M−C6H6O2]) and two ions ([M−H] and [M−CO2]) were selected for confirmation (Table 1). The fragmentation pathways for the deprotonated molecules were reported by Gómez-Cadenas et al. [12]. Analyses were carried out in SIM mode with a dwell time of 500 ms. Masslynx version 4.0 software (Micromass) was used to process the quantitative data obtained from calibration standards and from samples.
Table 1

Selected ions for the LC-MS determination of ABA and [2H6]-ABA

Compound

Quantification ion

First confirmation ion

Second confirmation ion

m/z

Relative intensity (%)

m/z

Relative intensity (%)

m/z

Relative intensity (%)

ABA

153

100

263

56

219

25

[2H6]-ABA

159

100

269

56

225

25

Validation procedures

Specificity, calibration curve estimation, sensitivity, precision, accuracy, and relative recovery were investigated to evaluate the integrity of the method.

Specificity was based on relative retention time and relative abundance of masses obtained in the SIM mode.

Calibration curves were tested for the linearity, the interday repeatability of the slopes, and the intercept test significance. The linearity was investigated by calculation of the regression curve by the method of least squares and expressed by the determination coefficient (R2). Comparison of the interday slopes was carried out by the application of t-test at significant level α=0.05. The intercept test significance was carried out by means of a t-test at a significance level of α=0.05.

Limits of detection (LODs) and quantification (LOQs) were evaluated from the y-intercept standard deviation (Sb) and the slope (a) of the calibration curve [19, 20, 21].

The precision was estimated by the evaluation of the intra-batch precision (measure repeatability) and the inter-batch precision (preparation process repeatability). The intra-batch precision was determined by a set of six replicate analyses of two samples with different concentration levels of ABA. The inter-batch precision was evaluated by a set of four extracts of four samples with different concentration levels.

Accuracy and relative recovery were evaluated over the linear range at three concentrations. The essays were carried out using five replicates for each concentration.

Statistical analysis

The t-test and F-test were performed by using Microsoft Excel version 2000 (Microsoft Corp.); one-way analysis of variance (ANOVA) and the Duncan test were carried out by using SAS version 8.02 (SAS Institute, Inc.). All statistical tests applied in this work were employed to validate the analytical method.

Results and discussion

LC-MS conditions

Development of the analytical procedure involves the optimization of analytical conditions to obtain the best results. Using FIA of the individual solutions of the ABA and [2H6]-ABA, maximum sensitivity was obtained using a 3.0-kV capillary voltage and a 30-V cone voltage.

Extraction procedure

Effect of extracting solvent on ABA recoveries

Besides affecting the extraction yield of ABA and [2H6]-ABA, the extraction solvent can influence the specificity of the method. Table 2 shows the results obtained when several spiked samples were extracted with water pH 3, water pH 5.5, 1% NaHCO3 aqueous solution, or methanol/water pH 5.5 (50:50 v/v). The extraction yields varied from 50% to 75% with relative standard deviations lower than 5%. The Duncan multiple comparison procedure indicated that recoveries obtained using methanol/water pH 5.5 (50:50 v/v) were significantly different from the other three procedures at the α=0.05 level (Table 2). Furthermore, this procedure gave the best absolute recoveries. Consequently, this solvent was selected for use in all the subsequent essays.
Table 2

Influence of extraction solvents on ABA recoveries. Number of replicates, average recoveries (%), and relative standard deviation (%RSD) are indicated

Solvent

na

Mean recovery

%RSD

Duncan test (α=0.05)

Water pH 3

3

50

3.0

A

Water pH 5.5

3

56

3.8

B

1% NaHCO3aqueous solution

3

53

1.6

AB

Methanol/water pH 5.5 (50:50 v/v)

3

75

4.6

C

aNumber of replicates

The spiking level is 2 nmol g−1

Effect of LC column on method specificity

Chromatographic separation of the different compounds of the matrix sample is an important factor for obtaining a good specificity because this separation influences the method’s efficiency. Figure 2 shows the chromatograms and their respective spectra obtained from grapevine leaf extracts using a C18 column (Symmetry C18 150×2.1-mm i.d., 5 μm) and a porous graphitic carbon (PGC) column (Hypercarb PGC 100×2.0-mm i.d., 5 μm). The relative intensity obtained with each column and compound demonstrated which chromatographic column should be chosen. The PGC column made it possible to obtain a series of chromatographic peaks presenting a relative intensity of ions that were closer to the desired pure standards (Table 1). Consequently, the PGC column was selected for all subsequent essays. The total time needed for one LCMS analysis was 15 min.
Fig. 2

LC-ESI-MS composite mass chromatograms and the corresponding spectra resulting from the analysis of a grapevine leaf extract with a PGC column (A SIM for ABA and B [2H6]-ABA) and with a C18 column (C SIM for ABA and D [2H6]-ABA). Retention times (RTs) for both compounds are indicated in each chromatogram

Method validation

Calibration integrity

Calibration curves were obtained by least-squares linear regression analysis of the peak area ratio of analyte to internal standard (y) versus analyte concentration (x). Five standard solutions were employed to determine the calibration curve. Two replicate measurements were made for each standard solution. The interday calibration behavior was linear with determination coefficients (R2) between 0.9990 and 0.9997. The calibration curve was expressed by:
$$ y = {\left( {2.652 \pm 0.015} \right)} \cdot x + {\left( {2.835 \pm 6.268} \right)} $$
(1)
Two Student’s t-test was performed to determine the calibration curve quality. The interday slopes comparison was carried out by using three calibration curves obtained on three different days. For all cases tcalculated value<tcritical value for 16 degrees of freedom at the α=0.05 level (Table 3). The second t-test (9 degrees of freedom) was used to compare the y-intercept values of the three calibration curves with zero. Table 3 shows that for all cases tcalculated value<tcritical value. Consequently, there were no significant differences between y-intercept and zero at α=0.05. These results suggest that the calibration curve presented good linearity and interday stability.
Table 3

t-Test values for the comparison of three calibration curves obtained on three different days at α=0.05

 

Interday slope comparison (16 dfa)

y-intercept comparison with zero (9 df)

Curve

tcalculated value

tcritical value

tcalculated value

tcritical value

1

0.06

 

1.43

 

2

0.40

2.12

1.28

2.26

3

0.29

 

0.43

 

aDegrees of freedom

Lower limits

The sensitivity was evaluated by determining the LODs and LOQs. Both parameters were respectively calculated by using the equations LOD=3.3·Sb/a and LOQ=10·Sb/a, where a is the slope and Sb is the standard deviation of the y-intercept [17]. Values of 0.2 nmol g−1 and 0.6 nmol g−1 dry grapevine leaves were calculated for LODs and LOQs, respectively.

Precision

The intra-batch precision of the method based on measurement repeatability was assessed by replicate injections (n=6) of two sample extracts with different concentration levels, i.e., 3.89 and 6.24 nmol g−1 dry sample. The ANOVA test was used to estimate significant differences at α=0.05 among the different instrumental measures. The results demonstrated that the instrument did not influenced the response obtained (Fcalculated value (0.03) < Fcritical value (4.39)). Table 4 shows that the intra-batch precision, calculated by relative standard deviation, did not exceed 5.5%.
Table 4

Repeatability results for ABA in grapevine leaf samples

Precision data

 

Intra-batchc

Inter-batchd

Level

Low

High

Low

Medium1

Medium2

High

Meana

3.89

6.24

3.17

3.44

4.18

6.53

SDb

0.21

0.22

0.13

0.20

0.13

0.16

%RSD

5.40

3.53

4.10

5.81

3.11

2.45

aConcentration (nmol g−1 lyophilized sample)

bStandard deviation

cSix replicate analysis of two real samples

dFour replicate extractions of four real samples

The inter-batch precision of the method based on extraction repeatability was assessed by replicate extraction (n=4) of four samples with different concentration levels, i.e., 3.17, 3.44, 4.18, and 6.53 nmol g−1 dry sample. The ANOVA test was used to estimate significant differences at α=0.05 among the different extracts of the sample. Results demonstrated that the extraction procedure did not influence the concentration value obtained (Fcalculated value (0.00) < Fcritical value (3.49)). Table 4 shows that the inter-batch precision, calculated by relative standard deviation, was less than 6.0%.

Accuracy and relative recovery

These parameters describe the closeness of mean test results to the true concentration of the analyte obtained by the method. Although the absolute recovery of the method was around 75%, the use of an isotopically labeled internal standard enabled relative recovery values adjusted to the theoretical value to be obtained. The standard addition method was used to compare the difference between the results obtained in the sample with addition and the sample with no addition (real value). The theoretical value of the addition was considered as a reference value through the relative error (%Er) or t test [22, 23]. Spiked grapevine leaf samples at three different concentrations of ABA (1, 3.5, and 7.5 nmol g−1) were processed (five replicates) and analyzed (two replicates). The results are shown in Table 5. %Er lays in the range of −2.7 to 4.3% showing a high level of accuracy. Moreover, the assayed mean values are not statistically different from the theoretical values using a t test at α=0.05, suggesting a good level of accuracy in the method. An additional parameter to validate the analytical methods is the relative recovery. This parameter ranged from 95% to 107% at the levels tested, owing to the compensation of the analyte loss by the isotope-labeled internal standard.
Table 5

Method accuracy and ABA relative recoveries in grapevine leaf samples (nmol g−1 lyophilized sample)

 

Accuracy

Recovery

Level

Spiked ABA

Na

nb

Means of measured conc

SD

%RSD

Theoretical conc

tcalculated (tcritical=2.78)

Test result

%Erd

Mean

SD

%RSD

Blank

0.0

5

2

3.17

0.09

2.84

       

Low

1.0

5

2

4.14

0.16

3.86

4.17

0.47

NSDc

−0.7

100.3

7.19

7.17

Medium

3.5

5

2

6.49

0.19

2.93

6.67

2.23

NSD

−2.7

95.2

5.43

5.71

High

7.5

5

2

11.13

0.44

3.95

10.67

2.29

NSD

4.3

106.6

6.09

5.72

aExtraction replicates

bInjection replicates

cNo statistical differences between mean of measured concentration and theoretical concentration (tcalculated< tcritical)

dRelative error calculated by %Er=[(Mean of measured conc-theoretical conc)/theoretical conc]×100

Application

Twenty five lyophilized grapevine leaf samples were processed and analyzed according to the optimized methodology in order to demonstrate their feasibility. The grapevine crops were subjected to six different irrigation conditions in order to obtain a large range of ABA content in the leaf samples. A total of 24 samples (three extractions for sample and two injections for extract), four samples in each irrigation condition, were investigated for application of the analytical method. The ABA concentration showed levels between 2.5 and 10 nmol g−1 dry sample between the calibration range. %RSD levels between 1 and 10 demonstrate that the method is very precise.

A certain tendency towards an increase in ABA content was observed when the cultivar was submitted to a certain hydric stress. Nevertheless, the content of this phytohormone also depended on factors like salt, stress damage, and low temperature adaptations [3, 24], data which were not available in our study.

Conclusions

This work shows that isotope-dilution LC-ESI-MS under negative ionization could be a valuable tool for quantitative determination of ABA in grapevine leaf. Although most of the LC-MS ABA analytical procedures reported use tandem mass spectrometry (MS/MS) in multiple reaction monitoring (MRM) mode, the use of LC-MS in ABA analysis presents advantages in terms of instrumental cost and availability. The method developed is fast and easy to handle, and the instrumental equipment needed is present in most routine laboratories nowadays. The method includes an extraction step with mean recovery around the 75% and is specific because it permits a good separation of the matrix compounds. Moreover, the calibration curve presents good linearity (R2>0.9990) and interday stability. The method has been validated and has been shown to be sensitive (LOD=0.2 nmol g−1 dry sample and LOQ=0.6 nmol g−1 dry sample), accurate (%Er between −2.7 and 4.3%), and intra-batch and inter-batch precise (%RSD 5.5 and 6.0% respectively). Finally, it presents excellent relative recoveries (ranging from 95% to 107%). The method is at least as specific, sensitive, precise, and accurate as the LC-MS/MS methods described for other plant tissues. Consequently, this analytical method could be a useful tool for the grapevine growers and wine-making industry.

Notes

Acknowledgement

The authors are grateful to the Departament de Tecnologia Frutícola of the Institut de Recerca i Tecnología Agroalimentàries (IRTA) for providing grapevine leaf samples.

References

  1. 1.
    Bray EA (2002) Plant Cell Environ 25:153–161CrossRefGoogle Scholar
  2. 2.
    Cutler AJ, Krochko JE (1999) Trends Plant Sci 4:472–478CrossRefGoogle Scholar
  3. 3.
    Xiong LM, Zhu JK (2003) Plant Physiol 133:29–36CrossRefGoogle Scholar
  4. 4.
    Soar CJ, Speirs J, Maffei SM, Loveys BR (2004) Funct Plant Biol 31:659–669CrossRefGoogle Scholar
  5. 5.
    Koussa T, Colin L, Broquedis M (2004) J Int Sci Vigne Vin 38:141–146Google Scholar
  6. 6.
    McCarthy MG (1997) Aust J Grape Wine Res 3:102–108Google Scholar
  7. 7.
    Stoll M, Loveys B, Dry P (2000) J Exp Bot 51:1627–1634CrossRefGoogle Scholar
  8. 8.
    Kamboj JS, Browning G, Blake PS, Quinlan JD, Baker DA (1999) Plant Growth Regul 28:21–27CrossRefGoogle Scholar
  9. 9.
    Muller A, Duchting P, Weiler EW (2002) Planta 216:44–56CrossRefGoogle Scholar
  10. 10.
    Birkemeyer C, Kolasa A, Kopka J (2003) J Chromatogr A 993:89–102CrossRefGoogle Scholar
  11. 11.
    Gomez-Cadenas A, Tadeo FR, Talon M, Primo-Millo E (1996) Plant Physiol 112:401–408Google Scholar
  12. 12.
    Gomez-Cadenas A, Pozo OJ, Garcia-Augustin P, Sancho JV (2002) Phytochem Analysis 13:228–234CrossRefGoogle Scholar
  13. 13.
    Ross ARS, Ambrose SJ, Cutler AJ, Feurtado JA, Kermode AR, Nelson K, Zhou R, Abrams SR (2004) Anal Biochem 329:324–333CrossRefGoogle Scholar
  14. 14.
    Lopez-Carbonell M, Jauregui O (2005) Plant Physiol Bioch 43:407–411Google Scholar
  15. 15.
    Zhou R, Squires TM, Ambrose SJ, Abrams SR, Ross ARS, Cutler AJ (2003) J Chromatogr A 1010:75–85CrossRefGoogle Scholar
  16. 16.
    Jemal M, Schuster A, Whigan DB (2003) Rapid Commun Mass Spectrom 17:1723–1734CrossRefGoogle Scholar
  17. 17.
    Liu RH, Lin DL, Chang WT, Liu CR, Tsay WI, Li JH, Kuo TL (2002) Anal Chem 74:618A–626AGoogle Scholar
  18. 18.
    Abrams SR, Nelson K, Ambrose SJ (2003) J Label Compd Radiopharm 46:273–283CrossRefGoogle Scholar
  19. 19.
    Food and Drug Administration (1995) International Conference on Harmonisation [ICH]. Validation of analytical procedures: definitions and terminology, Q2A. Federal Register 60:11260Google Scholar
  20. 20.
    Food and Drug Administration (1997) International Conference on Harmonisation [ICH]. Validation of analytical procedures: methodology, Q2B. Federal Register 62:27464Google Scholar
  21. 21.
    Baker SE, Olsson AO, Needham LL, Barr DB (2005) Anal Bioanal Chem 383:963–976CrossRefGoogle Scholar
  22. 22.
    Garcia I, Ortiz MC, Sarabia L, Vilches C, Gredilla E (2003) J Chromatogr A 992:11–27CrossRefGoogle Scholar
  23. 23.
    Feinberg M, Boulanger B, Dewe W, Hubert P (2004) Anal Bioanal Chem 380:502–514CrossRefGoogle Scholar
  24. 24.
    Mauch-Mani B, Mauch F (2005) Curr Opin Plant Biol 8:409–414CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Francisca Vilaró
    • 1
  • Anna Canela-Xandri
    • 2
  • Ramon Canela
    • 2
  1. 1.Centre UdL-IRTALleidaSpain
  2. 2.Chemistry DepartmentLleida UniversityLleidaSpain

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