Journal of Chromatography A

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1 Journal of Chromatography A, 1200 (2008) Contents lists available at ScienceDirect Journal of Chromatography A journal homepage: Comparative study of Eucalyptus dunnii volatile oil composition using retention indices and comprehensive two-dimensional gas chromatography coupled to time-of-flight and quadrupole mass spectrometry Carin von Mühlen a, Claudia Alcaraz Zini b, Elina Bastos Caramão b, Philip J. Marriott c, a Centro Universitário Feevale - Instituto de Ciências Exatas e Tecnológicas, Novo Hamburgo, RS, Brazil b Universidade Federal do Rio Grande do Sul - Instituto de Química, Porto Alegre, RS, Brazil c Australian Centre for Research on Separation Science, School of Applied Sciences, RMIT University, GPO Box 2476V, Melbourne, Victoria, Australia article info abstract Article history: Available online 29 May 2008 Keywords: Comprehensive two-dimensional gas chromatography Eucalyptus dunnii Retention index Eucalyptus GC GC GC GC/TOFMS GC GC/qMS In the present work, the composition of volatile oil from leaves of Eucalyptus dunnii was studied using comprehensive two-dimensional gas chromatography (GC GC) techniques. Structurally related compounds were found to elute mainly in specific regions of the two-dimensional space, showing orderly distribution with chemical class. Mass spectra of essential oil components were obtained from two different mass spectrometry detection methods: quadrupole (qms) and time-of-flight (TOFMS), using the same GC GC system under the same chromatographic conditions. Higher values of Similarity (average S of 914 with TOFMS compared to 880 with qms) and Reverse (average R of 944 with TOFMS compared to 881 with qms) were obtained with GC GC/TOFMS showing its superior performance, which was most likely due to better sensitivity and resolution arising from the TOFMS system, and lack of spectral bias. Also, the number of compounds found in E. dunnii essential oil was 15% higher when TOFMS was used. Most of these are lower abundance components or exhibit low quality mass spectra; this supports the improved sensitivity obtained with TOFMS. A linear relationship (r 2 = 0.998) between experimental retention indices (LTPRI) of 30 standard compounds obtained with GC GC/TOFMS and GC with flame ionization detection literature retention indices is reported as an aid for compound identification Elsevier B.V. All rights reserved. 1. Introduction Eucalyptus has been prized as a rich source of essential oils. The oils of various species have been valued for pharmaceutical, industrial and perfume uses [1]. In recent years, the attention of forest husbandry towards the Eucalyptus dunnii species has been focused on its adaptation to frost conditions, combined with good wood quality [2]. Several studies on the essential oil composition of E. dunnii leaves [1,3 5] from different countries are available which show considerable differences regarding their volatile composition. Zini et al. [6] presented preliminary research on headspace solid-phase microextraction and comprehensive two-dimensional gas chromatography with flame ionization detection (HS-SPME- GC GC-FID) applied to E. dunnii volatile oil. In that work, 580 peaks were detected, but the authors also stated that 50% of the trace peaks were due to background. In another work [7], 96 compounds were tentatively identified using GC GC/quadrupole mass spec- Corresponding author. Tel.: ; fax: address: philip.marriott@rmit.edu.au (P.J. Marriott). trometry (qms), and another 64 were classified according to their proposed chemical class, based on their mass spectral fragmentation. When GC/qMS was used, only 34 compounds were tentatively identified, using the same algorithm for mass spectral comparison employed for GC GC/qMS. Results obtained for several sesquiterpenic compounds were not easily interpreted, as some of them are isomers which complicate identification due to their similar mass spectra; in the absence of co-injected authentic standard compounds absolute identification is difficult. A high number of isomers in essential oils are not unusual because of their structure, degree of saturation and heteroatomic homogeneity [8,9]. Mass spectra obtained with different mass analyzers offer significant differences as regards to acquisition rates, sensitivity, detection limits, and resolution [10]. Time-of-flight mass spectrometry (TOFMS) systems can readily achieve the required spectral acquisition rates (> Hz) for reliable GC GC peak assignment and quantification [11,12]. The higher cost of such instrumentation is the main reason behind its limited laboratory diffusion [13]. Quadrupole mass spectrometers have been commercially available in their present form for many years; they are found in many laboratories, they are extremely popular, and are less /$ see front matter 2008 Elsevier B.V. All rights reserved. doi: /j.chroma

2 C. von Mühlen et al. / J. Chromatogr. A 1200 (2008) expensive than the new generation of TOFMS instruments. Their limited data acquisition speed and interscan duty cycle may restrict their compatibility with fast chromatographic peaks in respect of spectral quality and quantitative analysis [14]. Frysinger and Gaines proposed broadening the chromatographic peak (from 0.2 to 1 s in the second dimension) by increasing the run time [15] which was achieved by slowing the chromatographic elution in GC GC. The acquisition rate can also be improved by limiting the scan range to ca. 200 Da to achieve 20 scan/s [14,16] or more, in modern qms instruments [10,17]. This strategy was adopted by several authors [13,18,19], and was also used in the present work. The primary objective of this research was to discuss differences regarding the quality of analytical information obtained under GC GC conditions, using TOFMS and qms detectors, with the same essential oil sample, under similar experimental conditions, using the same modulation system. Linear temperature programmed retention indices (LTPRI) were obtained in order to tentatively identify compounds in E. dunnii essential oil, using both detector systems. 2. Experimental 2.1. Samples and chemicals Leaves from mature plants were collected from one tree of E. dunnii clone by Aracruz Celulose in Guaiba, Brazil. The fresh leaves (300 g) were submitted to steam distillation for 5 h in 1.2 L water, in a Clevenger apparatus. The oil was passed over anhydrous sodium sulfate to remove any trace of water. Samples were stored at 18 C prior to initial analysis. The samples were sealed under inert atmosphere and stored in the dark for transfer to Australia, for GC GC analysis. The volatile oil samples were obtained via triplicate extractions and then combined into one sample for analysis. A solution of n-alkanes (C 8 C 22 ) was prepared using a standard kit supplied by Alltech Associates (Baulkham Hills, Australia). n- Hexane (pesticide grade) supplied by Merck (Kilsyth, Australia) was used to prepare the 1% standard and volatile oil solutions. Thirty volatile compounds were co-injected for identification purposes, as listed in Table GC GC system GC GC/qMS analyses were carried out on an Agilent Technologies 6890 model GC system (Agilent Technologies, Burwood, Australia). The instrument was equipped with a 5973 mass- Table 1 Linear temperature programmed retention indices (LTPRI) experimentally obtained for a standard mixture, and from reference LTPRI data [9] Compound LTPRI [9] LTPRI Compound LTPRI [9] LTPRI Hexanal Terpinene (Z)-hexenol n-octanol n-hexanol Terpineol Anisole Myrtenal Pinene Citronellol Camphene Verbenone Sabinene Geraniol Pinene Nerol Myrcene Carvacrol n-octanal Cubebene Hexyl acetate Terpinyl acetate Phellandrene (Z)-caryophyllene Limonene Cedrene ,8-Cineole Aromadendrene (E)- -ocimene Humulene selective detector with fast acquisition upgrade, a model 6873 auto sampler and Chemstation software. A conventional split/splitless injector was used at 250 C, with an injection volume of 1.0 L in the splitless mode, a split flow of 100 ml min 1 after 1 min in the splitless condition, and 20 ml min 1 4 min after injection. Temperature program conditions were as follows: initial temperature of 60 C, programmed at 3 Cmin 1 to 240 C (60 min total run). Constant helium carrier gas flow at 0.8 ml min 1, at a linear velocity of 31.9 cm s 1 measured at 60 C, was applied throughout the whole analysis. The MS transfer line temperature was 280 C, detector voltage 1.3 kv, and a reduced mass scan range of Da was used to provide a data acquisition rate of Hz. GC GC/TOFMS analyses were performed using an Agilent 6890GC system with a Pegasus III TOFMS analyser (LECO, St. Joseph, MI, USA). The carrier gas was supplied at 1 ml min 1,inorderto achieve the same linear velocity as in the qms (31.9 cm 1 ). The split/splitless injector conditions and temperature program in the GC oven were the same as in GC GC/qMS. The transfer line temperature was 260 C, and the source temperature was 200 C. Data were collected over a mass range of u at a nominal data acquisition rate of 100 Hz. The detector voltage was 1732 V. LTPRI values were obtained using the Van den Dool and Kratz equation [20], and the total GC GC retention time of peak apexes were used. LTPRI was also calculated using an equivalent first dimension retention time ( 1 t R ) value, obtained by the subtraction of the second dimension retention time ( 2 t R ) from the total retention time (results not shown), which is a more usual procedure for GC GC LTPRI calculations [21,22]. These values differ by less than 3 units of LTPRI when compared with the values obtained when total retention times were employed and therefore the total retention time was chosen for LTPRI calculation Column sets The column set used in all systems consists of a primary capillary column of BPX5 phase (5% phenyl polysilphenylene-siloxane) of dimensions 30 m 0.25 mm I.D., 0.25 m film thickness (d f ), serially coupled with a second capillary column of BP20 (Wax) phase (polyethylene glycol) of dimensions 1.5 m 0.1 mm I.D., 0.1 m d f. Both columns were from SGE International (Ringwood, Australia). In the GC GC/TOFMS system a transfer line with dimensions 0.4 m 0.1 mm I.D. was used, and in the GC GC/qMS system, the second dimension ( 2 D) column was directly inserted into the source Modulation A longitudinally modulated cryogenic system (LMCS) (Chromatography Concepts, Doncaster, Australia) was retrofitted to each GC instrument. The modulation period of 5.0 s was applied in all GC GC analyses, and the thermostatically controlled cryogenic trap was maintained at approximately 20 C for the duration of each analysis Data analysis and presentation Data were acquired by using ChemStation software (Agilent Technologies, Burwood, Australia) which allows raw data to be exported as a comma separated value file in ASCII format. Data were converted into two-dimensional array format according to the modulation time and data acquisition frequency. A contour plot of this two-dimensional data was generated using Transform (Fortner Research, Boulder, CO, USA). The data transformation process for presenting the GC GC results in two-dimensional (2D) contour plots has been described elsewhere [23]. Chromatograms

3 36 C. von Mühlen et al. / J. Chromatogr. A 1200 (2008) Fig. 1. GC GC/TOFMS total ion current chromatogram (TIC) data colour plot of E. dunnii essential oil, showing the distribution of classes of compounds in different regions of the chromatographic space, using a non-polar polar column set, as described in the experimental section. (A) Linear alcohols; (B) aldehydes; (C) acetates; (D) monoterpenic hydrocarbons; (E) monoterpenic alcohols; (F) monoterpenic acetates; (G) sesquiterpenic hydrocarbons; (H) oxygenated sesquiterpenes. were transported to the software AMDIS 32 [US National Institute for Standards and Technology (NIST), Gaithersburg, MD, USA], and selected mass spectra from these chromatograms were applied to MS Search 2.0 software (NIST), for uniform data analysis. The mass spectra were then compared with Adams [9] database and the main library of the software (NIST MS 2.0), using hybrid similarity (normal search + neutral loss logic). GC GC/TOFMS data were processed in the ChromaTOF II software, and mass spectra obtained from peak apexes were directly exported to MS Search Results and discussion The normal column set was chosen based on previous results obtained with different column sets (normal and inverse geometry) [7]. Fig. 1 shows several classes of compounds orderly distributed through the 2D plot of E. dunnii essential oil. Classes were tentatively grouped based on peak retention times and chemical identity (Table 2). It is easy to observe the clusters of compounds and also the higher retention times of oxygenated compounds in the 2 D, as would be expected for a polar column. Monoterpenic alcohols (E) in Fig. 1 were divided in two regions due to wrap-around effect. This effect is undesirable, because it results in greater band broadening on the 2 D column, and overlap may arise. Several strategies were tested to avoid wrap-around in another work [7], however, it was possible to conclude that in some cases, observed wrap-around represents just a visual inconvenience, since the broadening effect can be accepted provided the general separation (resolution) obtained meets the performance criteria of the analysis under the experimental conditions employed. In this work, wrap-around did not affect the separation and identification of the compounds, since the more strongly retained components (those that wrap-around) did not overlap peaks that were weakly retained in the subsequent modulation. A manageable degree of wrap-around also illustrates an interesting maximization of the separation space the lower region of the 2D plot can still accept some wrap-around peaks without overlap with non-wrap-around peaks. E. dunnii surface plots obtained with both detectors (TOFMS and qms) are illustrated in Fig. 2A and B, respectively. It is possible to visually verify a superior peak resolution or definition when TOFMS Fig. 2. 2D plot of total ion current chromatogram (TIC) data from E. dunnii volatile oil using (A) GC GC/TOFMS and (B) GC GC/qMS. As a further point of reference, the oval region compares equivalent peaks in the two plots. detection was employed (Fig. 2A), especially in the region where 1 t R is close to 40 min, where an enlargement is shown circled. This difference can be expressed in terms of peak width. Two modulated peaks of peak 98 (tentatively identified as viridiflorol, see later) produced apparent peak widths at base of 420 ms and 480 ms, respectively, in the qms system, while in the TOFMS, these values were 240 ms and 300 ms. The S/N ratios for the highest modulated peak were 69 and 4033, using qms and TOFMS, respectively. In another region of Fig. 2 close to 1 t R 18 min, two peaks were selected: 25 and 30 (tentatively identified as terpinolene and isopentyl-2- methyl butanoate, respectively). While peak 25 has a width at base of 300 ms and a S/N 15 in qms, the same peak width was 240 ms and S/N 271 in TOFMS (S/N 16 times higher when TOFMS was used). For peak 30 this S/N difference was correspondingly greater, with the same base width as peak 25, S/N was 151 in qms, and 2691 in TOFMS (S/N almost 18 times higher when TOFMS was used). Selected modulated peaks obtained by GC GC using both MS detectors are presented in Fig. 3, where both chromatograms were transferred to AMDIS software. The first peak, in both chromatograms, is the unique modulated peak obtained for compound 42 (tentatively identified as (Z)- -terpineol), and the second peak, is one of the modulations of compound 39 (tentatively identified as(e)-pinocarveol). The higher sensitivity observed for the TOFMS response was anticipated, based on its operational principle. However, not only was the S/N ratio higher (for (Z)- -terpineol peak (approximately 37 times when comparing GC GC/TOFMS and GC GC/qMS), but also the peak resolution increased for GC GC/TOFMS due to the wider peaks found for qms; the tentative identification of peak 42 (the minor component) was only possible for TOFMS. If the two chromatographic systems are capable of producing peaks of the same widths i.e. that they are matched then it must be proposed that the MS system is responsible for the apparent different peak widths and is due to scan rate effects (slow scanning proportional to peak broadening) or some other sourcedependent effects that serve to broaden the peaks. Note that in Fig. 3, the two peaks for 39 and 42 appear to have similar heights for the TIC data, whereas in Fig. 2, peak 39 has a much larger TIC

4 C. von Mühlen et al. / J. Chromatogr. A 1200 (2008) Table 2 Tentative identification of E. dunnii volatile oil compounds using GC GC/qMS and GC GC/TOFMS No. Compound Ref. [9] GC GC-FID GC GC/qMS LTPRI GC GC/TOFMS LTPRI LTPRI 2 t R S R 2 t R S R 1 Pentanol (Z)-pentenol (Z)-hexenal Hexanal a Ethyl isovalerate (E)-hexenal (Z)-hexenol a Pinene a Camphene a (10)-Thujadiene Pinene a Myrcene a (E)-dehydroxy linalool oxide Dehydro-1.8-cineole (Z)-hexenyl acetate (Z)-dehydroxy linalool oxide p-Menthatriene Phellandrene a p-cymene Limonene a (Z)- -ocimene Cineole a (E)- -ocimene a Terpinene a Terpinolene (Z)-linalool oxide Campholenal m-cymenene Linalool Isopentyl-2-methyl butanoate Pinene oxide Camphenol p-Menthatriene Endo-Fenchol (E)-p-mentha-2.8-dienol Campholenal (Z)-p-mentha-2.8-dienol Ipsdienol (E)-pinocarveol Nerol oxide Nopinone (Z)- -terpineol Camphene hydrate (E)-pinocamphone Pinocarvone Terpineol p-mentha-1.5-dienol Borneol (Z)-pinocamphone Terpineol Cryptone (E)-p-mentha-1.[7].8-dien-2-ol p-cymen-8-ol Terpineol a Myrtenol (E)-dihydrocarvone Myrtenal a (Z)-sabinol endo-fenchyl acetate Verbenone a (E)-carveol Isobornyl formate Neral (Z)-carveol (Z)-p-mentha-1.[7].8-dien-2-ol Carvone Carvotanacetone Geranial (E)-linalyl oxide acetate Bornyl acetate (Z)-pinocarvyl acetate Isoledene

5 38 C. von Mühlen et al. / J. Chromatogr. A 1200 (2008) Table 2 (Continued ). No. Compound Ref. [9] GC GC-FID GC GC/qMS LTPRI GC GC/TOFMS LTPRI LTPRI 2 t R S R 2 t R S R 73 -Copaene (Z)-jasmonene Gurjunene (Z)-caryophyllene a (E)-caryophyllene Calarene Aromadendrene a (Z)-eudesma-6.11-diene Dehydro-aromadendrene Humulene a epi-(E)-caryophyllene Gurjunene Amorphene Viridiflorene Selinene Phenylethyl-3-methylbutanoate Selinene Cadinene (E)-cyclo-isolongifol-5-ol (Z)-calamenene Viridiflorol isomer Ledol Spathulenol Gleenol Caryophyllene oxide Viridiflorol Eudesmol neo-intermedeol Kusinol epi-Cubenol Eremoligenol Muurolol epi- -Muurolol Cadinol Eudesmol neo-intermedeol LTPRI Linear Temperature Programmed Retention Indices. TABS similarity factor. R reverse factor. a Identity confirmation with external standard injection. Fig. 3. Modulated peaks of tentatively identified (Z)- -terpineol (peak 42, Table 2), and (E)-pinocarveol (peak 39, Table 2), obtained using GC GC/qMS and GC GC/TOFMS. response (as shown by the more intense zone for peak 39). In this case, peaks in Fig. 3 do not necessarily exhibit the same relative peak responses of Fig. 2 due to modulation phase effects. A similar phenomenon can be observed, related to peaks with higher S/N ratio, as illustrated in Fig. 4. A viridiflorol isomer and ledol (tentative identification of peaks 93 and 94, respectively) are two oxygenated sesquiterpenes with very similar mass spectra. Two modulated peaks of these two compounds where chosen to show that a full separation was achieved in the TOFMS system, but some modulated peaks could not be clearly assigned in the qms, due to lack of separation. In that case, modulations were identified based on 2 t R differences. In the last prominent modulation (40.48 min) of peak 94, another minor peak was resolved on the shoulder of peak 94 only when TOFMS was used. This peak was neither detected nor resolved by qms, unless characteristic ions could be selected, although in this case it was only apparent from the TOFMS data that the choice of characteristic ion was possible (panel B, Fig. 4). A full spectrum for this peak was obtained by GC GC/TOFMS, which showed a fragmentation pattern typical of an oxygenated sesquiterpene, although the compound was not present in the library and so identification could neither be proposed nor confirmed. The superior performance of TOFMS in terms of sensitivity and resolution improved the quality of mass spectra obtained and also expanded the number of compounds found in the essential oil. Tentative identification of compounds was performed using LTPRI values obtained with GC GC/qMS and GC GC/TOFMS, retention time in both dimensions, mass spectral comparison of

6 C. von Mühlen et al. / J. Chromatogr. A 1200 (2008) Fig. 4. Modulated peaks of tentatively identified viridiflorol isomer (peak 93) and ledol (peak 94) obtained using GC GC/qMS and GC GC/TOFMS. Number of each peak according to Table 2. the unknown compounds with data from MS libraries using Similarity (S) and Reverse (R) values [24], and co-injection of standards where available, as presented in Table 2. Similarity and Reverse values are mass spectral match factors reported in the range of 0 999, with a higher value corresponding to a better fit. Similarity describes how well the library hit matches the peak when using all masses, and reverse how well the library hit matches the peak when using only the masses present in the library spectrum [24]. S and R values that are higher than 800, in conjunction with consistent LTPRI values (see below), were employed as criteria for tentative identification of compounds [24,25]. As a result, 94 compounds were tentatively identified using GC GC/qMS associated with GC GC-FID and 108 compounds using GC GC/TOFMS. The experimental LTPRI of E. dunnii essential oil compounds obtained under GC GC conditions were plotted against 1D reference LTPRI from Adams [9], as illustrated in Fig. 5. This procedure was previously presented with GC GC-FID results [7]. In this work the linear relation formerly observed between LTPRI values calcu Retention indices In order to compare mono-dimensional (1D) reference LTPRI with experimental LTPRI obtained in this work, a solution of 30 typical volatile oil standard compounds listed in Table 1 and a solution of n-alkanes were co-injected in the GC GC/TOFMS, and LTPRI were calculated. These LTPRI were generated directly from the ChromaTOF II software for these compounds, using the Van den Dool and Kratz formula [20]. LTPRI and 2 t R presented in Table 2 for the GC GC/qMS system, were obtained with a GC GC-FID in another work, and are presented here for comparison purposes [7]. Fig. 5. Comparison between LTPRI obtained with a standard solution of 30 compounds, with LTPRI of the same components obtained from E. dunnii volatile oil sample, using GC GC/TOFMS data, and reference 1D LTPRI [9].

7 40 C. von Mühlen et al. / J. Chromatogr. A 1200 (2008) lated from both systems GC GC-FID and GC-FID, and Adams LTPRI values is confirmed using experimental LTPRI data from 30 standard compounds obtained in GC GC/TOFMS. Both data sets (experimental LTPRI values obtained from GC GC/TOFMS for standards and for the E. dunnii sample) show a clear linear trend when correlated with Adams LTPRI, as the determination coefficient (r 2 ) of the linear equations describing the relation between LTPRI of standard compounds and compounds of the essential oil versus Adams LTPRI are and 0.997, respectively. The advantages of these linear relations have been already described for GC GC-FID and GC-FID systems [7] regarding identification of the outliers: peak numbers 17 (1,3,8-p-menthatriene) and 58 (sabinol). Hexenal isomers (peaks 3 and 6) were only detected in the GC GC/TOFMS system and one of them was also found to be an outlier in Fig. 5. The detection of these compounds only in this system clearly shows the superior sensitivity of TOFMS detector compared to qms, since the same modulation system and column set were employed in both experiments. The use of the LTPRI linear relationships in the GC GC/TOFMS for peak identification may also be exemplified using the peaks of hexenal isomers. Both isomers exhibit similar mass spectra, but only the (E)-isomer has its LTPRI reported by Adams. In this case, the (Z)-hexenal was wrongly identified as the (E)-isomer. However, the linear relationship between LTPRI from GC GC/TOFMS system and literature LTPRI presented in Fig. 5 shows this misidentification as an outlier. These positional isomers are separated by boiling point in the first dimension ( 1 D) column, and their interaction with the short 2 D polar column is quite similar. Considering 2 t R of peaks 3 and 6 (2.03 and 2.45 s, respectively), the higher 1 D elution temperature of peak 6 would have been responsible for a smaller retention time for 2 t R, if the same interaction with the polar second dimension column was to be expected. Ruther [26] presented a retention index database with non-polar and polar mono-dimensional columns. In that work, the RI difference from (Z)- to (E)-hexenal was 7 units in a DB-5 column, and 14 units in a DB-Wax column. This difference may explain the higher interaction of (E)-isomer with the short second dimension wax column. This example clearly demonstrates that whenever isomer identification is necessary, the use of linear relationships between experimental GC GC and reference 1D-LTPRI may render this task easier. Some effort was taken to find correlations (results not shown) between the LTPRI difference ( LTPRI = experimental LTPRI Adams LTPRI [9]) and molecular structural characteristics, such as molecular weight, number of double bonds, number of cyclic rings, presence of oxygen, etc., however, no specific trend was observed. Even though thirty compounds were enough to show the linear trend between experimental GC GC/TOFMS LTPRI and Adams LTPRI, they were insufficient to investigate correlations between LTPRI and molecular structural features, although with a sufficiently large database and correlations with molecular descriptors this should be possible. Variations in 1 D linear flow velocity due to second column diameter restriction and vacuum may possibly impair such type of correlation, but if retentions could be informed by these data, it would be very useful for prediction purposes Mass spectrometry information The high number of isomers present in volatile oils, especially within sesquiterpene compounds, is one of the major difficulties for characterization of essential oil samples. Even small variations in mass spectra are sufficient to misidentify a compound. More analytical information can be obtained when GC GC data are associated with MS detection, provided that limitations of each MS system are well understood [7,27]. Mass spectra obtained in quadrupole and time-of-flight systems were transferred to NIST MS Search 2.0 software to obtain S and R values after performing library searching, and these data are presented in Table 2. The identity of all compounds was confirmed using the mass spectral deconvolution feature of ChromaTOF software, although all the R and S values were obtained without this deconvolution procedure (results not shown). Higher similarity values may be expected for experimental mass spectra provided by qms than for the ones obtained from TOFMS when comparing them with the reference mass spectra library, as these latter spectra may be expected to be derived predominantly by using qms systems [9]. However, results in Table 2 demonstrate the opposite. Similarity values found with the TOFMS system were, on average, 4% higher than the ones with qms. Also, on average, R values were approximately 7% higher when the TOFMS system was employed. Thus, for qms, the average S and R values were 879 and 880, and for TOFMS were 917 and 951, respectively. Note that this was for the same match algorithm, since both sets of data were exported to the same search software. In a previous work, a comparison between S and R values from 1D-GC/qMS and GC GC/qMS was performed, and an increased mass spectral distortion (bias) arising from the qms signal over a single GC GC peak, in comparison with a 1D-GC peak, was observed. These results are in agreement with data presented by different authors [14,18]. However, some authors presented opposite results when using fast-qms systems associated [13] or not [17] with broadening effects, as for example the use of polar columns and lower temperature ramp in the first dimension, achieving a total run time twice the one presented here, for perfume analysis [13]. These different results show that deterioration of spectra in qms systems depends on the acquisition speed employed and on the system used (conventional or fast-qms). Some authors have stated that it also depends on analytical conditions such as interscan delay, m/z range, and acquisition frequency [17,28]. However, one may anticipate that the spectrum taken at exactly the peak apex, as opposed to at the shoulder or inflexion point, may reduce the scanning bias for qms. Even considering that TOFMS mass spectra are not exactly the same as qms mass spectra (the EI fragmentation should be consistent, but quadrupole mass analyzers and TOFMS operate by different principles), in GC GC experiments TOFMS demonstrated higher similarity with the library than qms spectra. Some reasons may be offered to explain these results. The first is that TOFMS is less affected by mass spectral distortion effects associated with quadrupole scanning instruments [18]. Another reason is that the higher acquisition frequency needed to perform GC GC is better achieved with TOFMS, since it is suitable for acquisition rates up to 500 Hz. As an example, mass spectra obtained on the top of two peaks (S/N 10) with both GC GC instruments are shown in Fig. 6: tentatively identified as (E)-carveol peak (number 61 in Table 2) and -eudesmol peak (number 99 in Table 2). The mass spectra from the Adams library (a) are very similar to those obtained by GC GC/TOFMS for compounds of the real sample (b), whereas the qms results (c) show a few differences. This is demonstrated with S and R values obtained with TOFMS data for (E)-carveol (S =974;R = 974) and for -eudesmol (S =915;R = 920). Similarity and Reverse data obtained for the same peaks using GC GC/qMS were lower: (E)-carveol (S = 884; R = 884) and for eudesmol (S = 865; R = 865). Differences among spectra obtained with GC GC/qMS and the Adams library does not seem to show a trend as it is possible to find m/z fragments that are more intense in the qms spectrum such as m/z 149 for -eudesmol than in the Adams spectrum, and also missing minor peaks, such as m/z 135 and 136 for (E)-carveol. Shellie et al. [14,17,21] have already pointed out similar limitations in the use of a GC GC/qMS system with a

8 C. von Mühlen et al. / J. Chromatogr. A 1200 (2008) Fig. 6. Mass spectra of tentatively identified (E)-carveol (peak 61) and -eudesmol (peak 99): (a) from Adams library; (b) from E. dunnii oil sample using GC GC/TOFMS; and (c) GC GC/qMS. Number of each peak is according to Table 2. low acquisition rate, for characterization of essential oil samples, although comparisons with TOFMS systems were not presented. 4. Conclusions The application of TOFMS and qms detectors to an E. dunnii essential oil sample, using the same GC GC system, column sets, sample and modulation system showed an improvement in sensitivity and resolution when TOFMS was employed. As a result, the Similarity and Reverse values were higher for TOFMS than with qms, showing a superior mass spectral quality, even though the mass spectra usually found in the reference libraries (NIST and Adams) employed are mainly obtained from qms detectors. Another consequence of this higher sensitivity and resolution was the gain in terms of number of peaks tentatively identified in the volatile oil of E. dunnii when a GC GC/TOFMS technique was employed in comparison with a GC GC/qMS system (15% more compounds identified by GC GC/TOFMS), using the same mass spectral identification algorithm. GC GC/TOFMS experimental retention indices of a mixture of thirty volatile compounds presented a linear relationship with conventional GC indices reported in the literature and the same was observed with the E. dunnii essential oil components. This provides simple and powerful supporting information for peak identification, which can be associated with 2 t R for a correct peak assignment, even if an unknown compound is not listed in a mass spectra reference library, especially in the case of isomers. It also provides a faster identification process for essential oil compounds, as the knowledge of experimental GC GC-FID retention indices will not be necessary, whilst GC GC retention indices have been described using a novel method, the process is still not routine [22]. Acknowledgements C.v.M. thanks the Conselho Nacional de Desenvolvimento Científico e Tecnológico CNPq, a Brazilian governmental institution, that promotes scientific and technological development and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior CAPES for Ph.D. grants. The technical assistance of Mr. Paul Morrisonisgratefullyacknowledged. Eucalyptus samples provided by Aracruz Celulose Unidade Guaíba are also acknowledged. References [1] D.J. Boland, J.J. Brophy, A.P.N. House, Eucalyptus Leaf Oils, Inkata Press, Melbourne, [2] T.F. de Assis, Personal communication, Porto Alegre, [3] C.M. Bignell, P.J. Dunlop, J.J. Brophy, Flavour Fragr. J. 12 (1997) 277. [4] C.A. Zini, K.D. Zanin, E. Christensen, E.B. Caramão, J. Pawliszyn, J. Agric. Food Chem. 51 (2003) [5] I. Mizrahi, J.R. Traverso, M.A. Juarez, A.L. Bandoni, L. Muschietti, C. van Baren, J. Essent. Oil Res. 9 (1997) 715. [6] C.A. Zini, T.F. De Assis, E.B. Ledford Jr., C. Dariva, J. Fachel, E. Christensen, J. Pawliszyn, J. Agric. Food Chem. 51 (2003) [7] C. Von Muhlen, C.A. Zini, E.B. Caramão, P.J. Marriott, J. Sep. Sci., submitted for publication. [8] R.J. Western, P.J. Marriott, J. Chromatogr. A 1019 (2003) 3. [9] R.P. Adams, Identification of Essential Oil Components by Gas Chromatography/Quadrupole Mass Spectroscopy, Allured Publ. Co, Carol Stream, IL, [10] M. Adahchour, M. Brandt, H.U. Baier, R.J.J. Vreuls, A.M. Batenburg, U.A.T. Brinkman, J. Chromatogr. A 1067 (2005) 245. [11] B.A. Mamyrin, Int. J. Mass Spectrom. 206 (2001) 251. [12] J. Dallüge, R.J.J. Vreuls, J. Beens, U.A.T. Brinkman, J. Sep. Sci. 25 (2002) 201. [13] L. Mondello, A. Casilli, P.Q. Tranchida, G. Dugo, P. Dugo, J. Chromatogr. A 1067 (2005) 235. [14] R. Shellie, P.J. Marriott, C.W. Huie, J. Sep. Sci. 26 (2003) [15] G.S. Frysinger, R.B. Gaines, J. High Resolut. Chromatogr. 22 (1999) 251.

9 42 C. von Mühlen et al. / J. Chromatogr. A 1200 (2008) [16] M. Kallio, T. Hyötyläinen, M. Lehtonen, M. Jussila, K. Hartonen, M. Shimmo, M.L. Riekkola, J. Chromatogr. A 1019 (2003) 251. [17] P. Korytár, J. Parera, P.E.G. Leonards, J. Boer, U.A.T. Brinkman, J. Chromatogr. A 1067 (2005) 255. [18] S.M. Song, P. Marriott, P. Wynne, J. Chromatogr. A 1058 (2004) 223. [19] D. Ryan, R. Shellie, P.Q. Tranchida, A. Casilli, L. Mondello, P.J. Marriott, J. Chromatogr. A 1054 (2004) 57. [20] H. van den Dool, P.D. Kratz, J. Chromatogr. A 11 (1963) 463. [21] R. Shellie, P.J. Marriott, Analyst (Cambridge, United Kingdom) 128 (2003) 879. [22] S. Bieri, P.J. Marriott, Anal. Chem. 78 (2006) [23] P.J. Marriott, L. Mondello, A.C. Lewis, K.D. Bartle, Multidimensional Chromatography, Wiley, Chichester, [24] J. Dallüge, L.L.P. Stee, X.B. Xu, J. Williams, J. Beens, R.J.J. Vreuls, U.A.T. Brinkman, J. Chromatogr. A 974 (2002) 169. [25] S. Zhu, X. Lu, L. Dong, J. Xing, X. Su, H. Kong, G. Xu, C. Wu, Anal. Chim. Acta 545 (2005) 224. [26] J. Ruther, J. Chromatogr. A 890 (2000) 313. [27] G.B. Lockwood, J. Chromatogr. A 936 (2001) 23. [28] M. Adahchour, J. Beens, R.J.J. Vreuls, U.A.T. Brinkman, Trends Anal. Chem. 25 (2006) 540.