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Article

Comprehensive 2D Gas Chromatography with TOF-MS Detection Confirms the Matchless Discriminatory Power of Monoterpenes and Provides In-Depth Volatile Profile Information for Highly Efficient White Wine Varietal Differentiation

1
Institute of Agriculture and Tourism, K. Huguesa 8, 52440 Poreč, Croatia
2
Centre of Excellence for Biodiversity and Molecular Plant Breeding, Svetošimunska 25, 10000 Zagreb, Croatia
3
Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), Via E. Mach 1, 38098 San Michele all’Adige, TN, Italy
*
Author to whom correspondence should be addressed.
Foods 2020, 9(12), 1787; https://doi.org/10.3390/foods9121787
Submission received: 26 October 2020 / Revised: 25 November 2020 / Accepted: 28 November 2020 / Published: 2 December 2020
(This article belongs to the Special Issue Flavour Volatiles of Wine)

Abstract

:
To differentiate white wines from Croatian indigenous varieties, volatile aroma compounds were isolated by headspace solid-phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOF-MS) and conventional one-dimensional GC-MS. The data obtained were subjected to uni- and multivariate statistical analysis. The extra separation ability of the GC×GC second dimension provided additional in-depth volatile profile information, with more than 1000 compounds detected, while 350 were identified or tentatively identified in total by both techniques, which allowed highly efficient differentiation. A hundred and sixty one compounds in total were significantly different across monovarietal wines. Monoterpenic compounds, especially α-terpineol, followed by limonene and linalool, emerged as the most powerful differentiators, although particular compounds from other chemical classes were also shown to have notable discriminating ability. In general, Škrlet wine was the most abundant in monoterpenes, Malvazija istarska was dominant in terms of fermentation esters concentration, Pošip contained the highest levels of particular C13-norisoprenoids, benzenoids, acetates, and sulfur containing compounds, Kraljevina was characterized by the highest concentration of a tentatively identified terpene γ-dehydro-ar-himachalene, while Maraština wine did not have specific unambiguous markers. The presented approach could be practically applied to improve defining, understanding, managing, and marketing varietal typicity of monovarietal wines.

1. Introduction

Aroma is among the most important attributes that drive the perception of wine sensory quality and varietal typicity by consumers. It results from the occurrence of many diverse odoriferous volatile compounds of different origin. Primary or varietal aroma compounds originate from grapes, secondary or fermentation aroma compounds are produced in fermentation, while tertiary aromas are formed during maturation [1,2,3]. The three groups mentioned are not so clearly divided: most of the precursors of volatile aroma compounds originate from grapes and are in one way or another affected by fermentation and/or aging [4]. The final wine aroma profile is a result of complex interactive effects between many sources of variability, such as variety [5], geographical position characterized by specific agroecological conditions [6,7], viticultural practices [8], harvest date [9], harvest year [10,11], grape processing, and fermentation parameters [12,13], etc.
Varietal characterization (description) and differentiation (contradistinction from other varieties) is an ever-important field of wine research. Many studies have aimed to identify volatile compounds characteristic for various grape varieties, since they are crucial for the typical varietal attributes of their wines. The knowledge on the volatile aroma compound composition of monovarietal wines is important since it may enable producers to better cope with the phenomena encountered in production and to manage vinification with greater efficiency, all in order to produce high quality wines of accentuated varietal typicity. It may enable detailed and precise description of the aroma of monovarietal wines, which could be used in their marketing, especially towards informed consumers interested in wines of high quality with marked diversity and identity. In addition to often being linked to a given geographical provenance with a corresponding protected designation of origin (PDO), particular monovarietal wines are especially appreciated and demanded because of their typical sensory properties. Such wines often fall within a higher price range and are a target of counterfeiting by mislabeling their varietal origin. Therefore, control in terms of varietal origin authentication is needed: the general strategy used by many research groups includes the (semi)quantification of a large number of volatile compounds in large sets of wines and use of the generated data for the production of multivariate statistical models able to classify wines, as well as to predict and confirm their varietal origin [5].
The analysis of volatile aroma compounds in wine varietal characterization and differentiation studies is commonly performed by conventional one-dimensional gas chromatography mass spectrometry (GC-MS) [14,15,16,17,18,19]. Although the information obtained by this approach is often sufficient to obtain more or less efficient varietal differentiation, a large amount of information is lost due to frequent co-elutions, even when using long GC run times on high-efficiency capillary columns with selective stationary phases and programmed oven temperature conditions [20,21]. In the last few decades, comprehensive two-dimensional gas chromatography-mass spectrometry (2D-GC-MS or GC×GC-MS) stood out as a highly potent technique for in-depth characterization of complex samples [22], where the number of compounds of interest is large and many are present at trace levels, as in wine. This technique utilizes two GC columns of different stationary phases serially connected by a modulator, where the compounds co-eluting in the first column are in most cases separated in the second. GC×GC-MS is therefore characterized by higher efficiency and sensitivity, since the additional separation by a second stationary phase produces clearer mass spectra and much less chromatographic peaks remain unannotated. In this way, GC×GC-MS allows detection and identification of a much larger number of volatile compounds compared to conventional GC-MS [23].
Regardless of the existing great potential, only a few studies have utilized GC×GC to investigate wine volatile aroma profiles, while studies which used GC×GC for varietal characterization and differentiation were extremely rare. Several authors reported more or less detailed GC×GC volatile aroma profiles of particular monovarietal wines, such as Cabernet Sauvignon [24], Sauvignon Blanc [25], Shiraz [9,26] or Syrah [12], Pinotage [21], Chardonnay [27], and Verdicchio [28], but none of them directly compared them to or differentiated them from other monovarietal wines of similar typology. In this way, despite detailed profiles determined in some cases, it still remained unknown which compounds and in which amounts are typical for a given variety and whether they could differentiate it from other monovarietal wines. The only two studies which utilized GC×GC and succeeded in differentiating several monovarietal wines did not report actual concentrations of all the identified volatile compounds [20,29].
The aim of this study was to utilize the potential of two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOF-MS) technique, in combination with headspace solid-phase microextraction (HS-SPME) and multivariate statistical tools, as a more efficient approach to characterize and differentiate monovarietal white wines based on their volatile aroma compound composition. Profiling by GC×GC was combined with conventional GC-MS analysis of major wine volatile compounds to obtain more comprehensive aroma profiles. Special attention was devoted to terpenes, often highlighted as key varietal markers in wine. The approach was applied to characterize and differentiate Croatian wines made from indigenous grape varieties, with each variety represented by a rather heterogeneous group of wines with respect to geographical microlocation and agroecological conditions, viticultural practices, harvest date, and grape processing and wine production parameters. It was expected that GC×GC-TOF-MS would be extremely effective in providing novel in-depth information for efficient white wine varietal differentiation.

2. Materials and Methods

2.1. Wine Samples

A total of 32 wines made from Croatian indigenous white grape varieties (Vitis vinifera L.) Malvazija istarska (MI, 8 samples) Pošip (PO, 7), Maraština (MA, 7), Kraljevina (KR, 7), and Škrlet (SK, 3) were donated by producers from Croatia (EU), more specifically Istria (MI) and Dalmatia (PO and MA) as the coastal regions and continental Croatia (KR and SK). Wines from the same variety were donated by different producers. The selection was representative for Croatian wine production and comprised the majority of the most important Croatian indigenous varieties. Only young wines from harvest 2015 were collected, labelled with a protected designation of origin (PDO) and with a traditional term “Quality or Top quality” wine. Wines were of the same typology and produced by standard white winemaking technology, which included grape harvest at technological maturity, destemming, crushing and mashing of the grapes, no or short pre-fermentative skin-contact (up to 48 h), use of selected commercial yeasts, fermentation at relatively low temperatures (up to 18 °C), and other standard procedures (sulfiting, racking, fining, and stabilization, etc.). Wines were not in contact with wood. During the period from harvest and vinification in September 2015 until the collection and analyses in April and May 2016 the wines were stored in stainless steel tanks and 0.75 L glass bottles with cork stoppers in wine cellars of the producers. The wine samples were selected from a larger set as typical representatives of a given variety by the panel for wine sensory analysis of the Institute of Agriculture and Tourism in Poreč (Croatia), which consisted of highly trained and experienced tasters. Standard physico-chemical parameters of the collected wines determined by OIV methods are reported in Table S1.

2.2. Standards, Chemicals, and Consumables

Chemical standards of volatile aroma compounds were procured from AccuStandard Inc. (New Haven, CT, USA), Fluka (Buchs, Switzerland), Honeywell International Inc. (Morris Plains, NJ, USA), Merck (Darmstadt, Germany), and Sigma-Aldrich (Sigma-Aldrich, St. Louis, MO, USA). A stock solution of major volatile compounds commonly present in wine was prepared in methanol, while standard solutions were prepared in model wine (13 vol.% of ethanol, pH 3.3). Ammonium sulfate and sodium chloride were purchased from Kemika d.d (Zagreb, Croatia).
Divinylbenzene/carboxen/polydimethylsiloxane (DVB-CAR-PDMS, StableFlex, 50/30 μm, 1 cm) SPME fiber used for GC-MS analysis was procured from Supelco, Sigma Aldrich (Bellafonte, PA, USA) and DVB-CAR-PDMS SPME fiber (StableFlex, 50/30 μm, 2 cm) used for GC×GC-TOF-MS analysis was procured from Supelco, Sigma Aldrich (Milan, Italy).

2.3. Analysis of Volatile Aroma Compounds by Conventional One-Dimensional GC-MS

Volatile aroma compounds for GC-MS analysis were isolated by headspace solid-phase microextraction (HS-SPME) according to the modified method proposed by Bubola et al. [30]. Four milliliters of a solution obtained by diluting wine four times with deionized water were pipetted in a 10 mL glass vial. Ammonium sulfate (1 g) and 50 μL of internal standards solution (2-octanol (0.84 mg/L), 1-nonanol (0.82 mg/L), and heptanoic acid (2.57 mg/L)) were added. After 15 min preconditioning at 40 °C, microextraction using a DVB-CAR-PDMS SPME fiber took place for 40 min at 40 °C with stirring (800 rpm). Volatile compounds were desorbed after the insertion of the fiber for 10 min into a GC/MS injector heated at 248 °C, with the first 3 min in splitless mode. Volatile aroma compounds were identified and quantified using a Varian 3900 gas chromatograph (GC) connected to a Varian Saturn 2100T mass spectrometer with an ion trap analyzer (Varian Inc., Harbour City, CA, USA). The column used was a 60 m × 0.25 mm i.d. × 0.25 μm d.f. Rtx-WAX (Restek, Belafonte, PA, USA). Initial temperature of the GC oven was 40 °C, ramped up at 2 °C/min to reach 240 °C, and then kept at this temperature for additional 10 min. Helium was used as a carrier gas at a flow rate of 1.2 mL/min. Mass spectra were acquired in EI mode (70 eV), at 30–350 m/z.
Identification of volatile compounds was conducted by comparison of retention times and mass spectra of the analytes with those of pure standards, and with mass spectra from NIST05 library. Identification by comparison with mass spectra was considered satisfactory if spectra reverse match numbers (RM) higher than 800 were obtained. In the case of less clear spectra (RM < 800) identification was considered satisfactory if the ratios of the relative intensities of a quantifier ion and three characteristic ions with the highest intensity reasonably matched those in the reference spectra of a given compound. Linear retention indices were calculated with respect to the retention times of C10 to C28 n-alkanes and compared to those reported in literature for columns of equal or equivalent polarity. Calibration curves were constructed based on the analysis of standard solutions containing known concentrations of standards at six concentration levels and were used for quantification. Quantification of major volatile compounds was based on total ion current peak area, while quantification of minor compounds was based on quantifier ion peak area. The peak areas and concentrations in standard solutions and in wine samples were normalized with respect to those of the internal standards. Linearity was satisfactory with coefficient of determination higher than 0.99 for all the standards. Relative standard deviation of repeatability (RSD) was determined after repeated analysis (n = 5) of a Malvazija istarska wine sample and was satisfactory, with RSD lower than 13.05% for monoterpenes, 7.38 for β-damasenone, lower than 9.23% for alcohols, 7.34 for ethyl esters, 12.34% for acetate esters, and 11.78% for fatty acids. Method validation parameters were previously published in the study of Bubola et al. [30]. In the cases when pure chemical standards were not available, semi-quantitative analysis was carried out. The concentrations of such compounds were expressed as equivalents of compounds with similar chemical structure which were quantified using calibration curves, assuming a response factor equal to one.

2.4. Analysis of Volatile Aroma Compounds by GC×GC-TOF-MS

A volume of 2.5 mL of wine was transferred to a 20 mL headspace vial and 1.5 g of sodium chloride was added. Wine sample was spiked with 50 μL of internal standard (2-octanol, 1 mg/L). Quality control samples (QC) were prepared by mixing equal proportion of each sample and were analyzed before the samples sequence (n = 5) and after every five samples (n = 1). GC×GC-TOF-MS analysis of wines was performed using a GC Agilent 7890N (Agilent Technologies, Palo Alto, CA, USA) coupled to a LECO Pegasus IV time-of-flight mass spectrometer (TOF-MS) (Leco Corporation, St. Joseph, MI, USA) equipped with a Gerstel MPS autosampler (GERSTEL GmbH & Co. KG, Mülheim an der Ruhr, Germany), as described in previous studies with minor modifications [9,31,32]. Briefly, samples were preconditioned at 35 °C for 5 min and volatile compounds were extracted using a DVB/CAR/PDMS SPME fiber for 20 min. Volatile compounds were desorbed for 3 min at 250 °C in splitless mode. The fiber was reconditioned for 7 min at 270 °C between each extraction. Helium was used as a carrier gas at a flow rate of 1.2 mL/min. The oven was equipped with a 30 m × 0.25 mm × 0.25 μm film thickness VF-WAXms column (Agilent Technologies) in the first dimension (1D) and a 1.5 m × 0.15 mm × 0.15 μm film thickness Rxi 17Sil MS column (Restek) in the second dimension (2D). Initial oven temperature was maintained at 40 °C for 4 min, then raised at 6 °C/min to 250 °C, and then finally maintained at this temperature for additional 5 min. The second oven was maintained at 5 °C above the temperature of the first one throughout the analysis. The modulator was offset by +15 °C in relation to the secondary oven, the modulation time was 7 s with 1.4 s of hot pulse duration, as described previously [31]. Electron ionization at 70 eV was applied, the temperature of ion source was 230 °C, detector voltage was 1317 V, mass range (m/z) was 40–350, acquisition rate was 200 spectra/s, and acquisition delay was 120 s.
Baseline correction, chromatogram deconvolution and peak alignment were performed using LECO ChromaTOF software version 4.32 (Leco Corporation, St. Joseph, MI, USA). The baseline offset was set to 0.8 and signal to noise (S/N) ratio was set at 100. Peak width limits were set to 42 s and 0.1 s in the first and the second dimension, respectively. Traditional, not adaptive integration was used. The required match (similarity) to combine peaks was set to 650. Under these conditions 1025 putative compounds were detected. Volatile compounds were identified by comparing their retention times and mass spectra with those of pure standards and with mass spectra from NIST 2.0, Wiley 8, and FFNSC 2 (Chromaleont, Messina, Italy) mass spectral libraries, with a minimum library similarity match factor of 750 out of 999. For identification of compounds by comparison with pure standards, a mix of 122 compounds was injected under identical GC×GC-TOF-MS conditions. For tentative identification of compounds and/or confirmation of their identities determined as described above, linear retention indices were calculated with respect to the retention times of C10 to C30 n-alkanes and compared to those from literature for conventional one-dimensional GC obtained using columns of equal or equivalent polarity (NIST 2.0, Wiley 8, FFNSC 2, VCF, ChemSpider). Three hundred and seventeen (317) volatile aroma compounds were (tentatively) identified in total. Volatile compounds were semi-quantified and their concentrations in μg/L were calculated relative to the internal standard 2-octanol, assuming a response factor equal to one.
In preliminary tests by principal component analysis (PCA), QC samples were clustered very close and were very well separated from the wine samples, suggesting the repeatability of the method was very good. Relative standard deviation of the internal standard 2-octanol in QC samples was 10.4% which was considered satisfactory for HS-SPME/GC×GC-TOF-MS analysis.

2.5. Statistical Data Elaboration

Data obtained by GC-MS and GC×GC-TOF-MS were processed by analysis of variance (one-way ANOVA). Least significant difference (LSD) post-hoc test was used to compare the mean values of concentrations at p < 0.05. Multivariate analysis of data was performed by PCA and forward stepwise linear discriminant analysis (SLDA). The original dataset which included 32 wines and 350 volatile aroma compounds (33 determined by GC-MS + 317 determined by GC×GC-TOF-MS analysis; in the case of compounds determined by both techniques GC×GC-TOF-MS data were used), was reduced based on Fisher ratios (F-ratios). Multivariate techniques were applied on the variables (mean-centered concentrations of volatile compounds) with the highest F-ratios. PCA was performed with 40 variables with the highest F-ratio, while SLDA and hierarchical clustering were performed with 60 variables with the highest F-ratio, in both cases with GC-MS and GC×GC-TOF-MS data combined. Two additional SLDA models were built with the concentrations of terpenes which were significantly different between wines, using GC-MS and GC×GC-TOF-MS data separately. In SLDA, variables were selected based on Wilk’s lambda, with F to enter = 1 and F to remove = 0.5. Cross-validation was applied to check the prediction capacity of the developed SLDA models. ANOVA, PCA, and SLDA were performed by Statistica v. 13.2 software (StatSoft Inc., Tulsa, OK, USA). Hierarchical clustering was conducted and a heatmap was generated by Ward algorithm and Euclidean distance analysis using MetaboAnalyst v. 4.0 (http://www.metaboanalyst.ca), created at the University of Alberta, Canada [33].

3. Results and Discussion

3.1. GC-MS

Major volatile aroma compounds are highly abundant in wines and for this reason GC-MS was considered appropriate for their analysis. It was considered that their quantitation by GC-MS was not significantly affected by co-eluting compounds. As well, the analysis of major volatiles by GC×GC-TOF-MS would require a rather different setup than that applied in this study, with much larger modulation time and hot pulse duration, not applicable for minor and trace compounds. Major volatile aroma compounds determined by GC-MS are listed in Table 1, grouped according to chemical class, and sorted within each class in order of decreasing F-ratio obtained by one-way ANOVA. Twenty-one monoterpenoids and a sesquiterpenoid trans-nerolidol, eight C13-norisoprenoids, two benzenoids, four alcohols, four acids, and 11 esters were quantified. Table S2 reports the concentrations of the identified volatile compounds in each of the investigated wines.
Among terpenes, major monoterpenols such as linalool, geraniol, α-terpineol, and nerol were found in the highest concentration, which was generally in agreement with previous findings on white wines [34,35,36]. The mentioned are among the most influential monoterpenoids to wine aroma, to which they significantly contribute with specific floral and fruity nuances due to their relatively low odor perception thresholds, such as, for example, 15 μg/L for linalool [35,37]. The highest F-ratio among all the compounds identified by GC-MS was determined for α-terpineol, followed by an unidentified monoterpene and linalool, confirming the importance of terpenes for wine varietal differentiation [35]. Many other (mono)terpenes also turned out to be important in this sense, while other compound classes exhibited lower F-ratios, with the exception of 1-hexanol. Such an outcome was expected to some extent, since terpenes are primary aroma compounds originating from grapes, both as free volatile molecules or released from glycosidic precursors. Their composition and amounts are genetically pre-determined: genetic variation in aroma biosynthesis genes cause differences in terpene concentrations between grapevine varieties. For example, a variant of 1-deoxy-D-xylulose-5-phosphate synthase, a gene responsible for the biosynthesis of terpenoids, causes pronounced increase in terpene concentration in Muscat and Gewürztraminer grapes, which gives wines of these varieties a recognizable floral aroma [4,38,39]. Monoterpenes are generally known to be responsible for varietal aroma of muscats and non-muscat aromatic varieties, such as Gewürtztraminer, Riesling, Müller-Thurgau, etc. [36,40,41], but were also found useful for the differentiation of wines of other, so-called semi-aromatic and neutral grape varieties [41,42,43,44,45]. Márquez, Castro, Natera, and García-Barroso [46] characterized the volatile fraction of Andalusian sweet wines made from Muscat and Pedro Ximenez varieties and, interestingly, also found that α-terpineol was the most powerful differentiator with the highest F-ratio, followed closely by linalool and limonene, similar as in this case.
In this study, the ratios of terpene concentrations in different monovarietal wines varied from compound to compound, but it was generally observed that wines from Škrlet, a relatively unexplored Croatian grape variety, were characterized by the highest concentrations of many important monoterpenes (Table 1), while the concentrations of other monoterpenes were also among the highest in the investigated wines. The concentrations of monoterpenes in Malvazija istarska wines were notable and generally in fair agreement with those reported previously for this variety, with linalool followed by geraniol as the most abundant [43,47,48,49]. Malvazija was followed by Pošip wine with intermediate concentrations, while Maraština and especially Kraljevina wines had the lowest terpene concentrations.
Although the content and composition of terpenes in grapes and wines is principally pre-determined by variety, they are susceptible to modulation in response to many factors, such as viticultural parameters including soil characteristics, exposure to sunlight, water status, defoliation, crop thinning, etc. [34,50], as well as pre-fermentation and fermentation practices and conditions [35,36]. Except the effect of variety, the differences between the investigated monovarietal wines were probably partly caused by different geographical origin (Istria, Dalmatia, continental Croatia), so the effects of variety and location probably acted in synergy. It is indeed known that low temperatures favor the production of aroma compounds in grapes [51], so it is possible that the highest concentration of monoterpenes in Škrlet wines from continental Croatia characterized by lower temperatures was at least partly due to the effect of climate. The same could be deduced for Malvazija wines coming from the northern, somewhat colder part of the Adriatic coast. Conversely, elevated temperatures have potential to reduce the aromatic potential of grapes [52], which is possibly a reason for somewhat lower concentrations of monoterpenes in Dalmatian Pošip and Maraština wines. Kraljevina wines, which had the lowest concentrations of terpenes despite originating from the continental part, could be an exception that confirms the rule.
C13-Norisoprenoids are also secondary metabolites in grapes, present in both aromatic and neutral varieties. They are formed as biodegradation products of carotenoid molecules, such as lutein, β-carotene, violaxanthin, and neoxanthin, via numerous formation mechanisms and intermediates during pre-fermentative steps, fermentation, and aging [53,54]. Four of them, β-damascenone, β-ionone, 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN), and trans-1-(2,3,6-trimethylphenyl)buta-1,3-diene (TPB), were commonly found in wine at concentrations surpassing their odor perception thresholds, meaning they can have a direct impact on wine aroma [34]. Especially important is β-damascenone with its pleasant odor reminiscent of honey, dried plum and stewed apple, and a very low perception threshold, which ranks it among the most important wine odorants [37]. β-Ionone, characterized by a threshold of the similar order of magnitude, also significantly contributes to wine aroma with an odor reminiscent of violets, while the contribution of TDN and TPB becomes relevant mostly in aged wines [34]. The concentrations of the majority of C13-norisoprenoids were generally higher in Dalmatian Pošip and Maraština, and the lowest in Kraljevina wines, although in particular cases with no statistical significance (Table 1). According to Marais and van Wyk [54] the concentration of β-damascenone is principally dependent on viticultural and winemaking conditions, while variety has less influence. Nevertheless, particular differences were observed: Malvazija wines were found to contain the highest concentration, although not different from that found in Pošip, while Škrlet had the lowest, not different from that found in Maraština wine. Malvazija was also characterized by the lowest concentration of vitispiranes together with Kraljevina wine. Among benzenoids, ethyl cinnamate emerged as a prominent marker of Pošip varietal origin, since it was found in the highest concentration in this wine.
C6-alcohols are formed mainly in pre-fermentation vinification steps by degradation of unsaturated fatty acids by the action of enzymes, as well as by liberation from glycosidic precursors. They may have an effect on wine aroma with their so-called green and herbal odors, but luckily have relatively high odor perception thresholds, such as 8000 μg/L for 1-hexanol [37], so only very high concentration can produce negative effects. Certain authors include C6-compounds among varietal aromas [16] and their concentrations were found useful in differentiation of particular wines based on variety [43,55]. The highest concentration of 1-hexanol was found in Škrlet, while Kraljevina contained the lowest amount (Table 1). Maraština, and especially Pošip wines were characterized by the highest concentration of unsaturated C6-alcohols. It is possible that the mentioned differences were a consequence of different enzymatic potentials and fatty acid precursor loads in grapes of these varieties [55].
Concentrations and the composition of fermentation aroma compounds are mainly affected by fermentation conditions, but may also be influenced by grape composition [56]. Many studies proved that the composition of volatile compounds formed in fermentation can be useful in differentiating wines of mostly neutral varieties equally or even more successful than by using, e.g., monoterpene concentrations [11,14,20,29]. This is more characteristic for C6–C10 fatty acids and the corresponding ethyl esters which, in contrast to acetates, are more dependent on the concentration of precursors and therefore on variety and conditions in vineyard, and less on the activity of yeast [57]. The average concentration of 2-phenylethanol was higher than the corresponding odor perception threshold of 10,000 μg/L in all the studied monovarietal wines, meaning this alcohol contributed significantly with its odor reminiscent of roses [37]. Pošip and Maraština had approximately 50% higher concentration of 2-phenylethanol in relation to the other investigated wines (Table 1). The concentrations of major volatile fatty acids (C6–C10) surpassed the corresponding odor perception thresholds of 420, 500, and 1000 μg/L, respectively [58], in all the investigated wines. Fatty acid production is determined in part by the initial composition of must [59] and therefore possibly by varietal origin. Malvazija istarska wines stood out with low concentrations of decanoic and octanoic acid. Among esters, Pošip was clearly differentiated from the other monovarietal wines by the highest concentration of 2-phenethyl acetate, which could have been related to the higher concentration of its precursor 2-phenylethanol found in this wine. However, it was stated previously that precursor concentrations do not significantly determine the concentrations of acetate esters formed by Saccharomyces cerevisiae, with the expression of alcohol acetyl transferase gene in yeast as a limiting factor [60]. Concentration of 2-phenethyl acetate in all the investigated wines was higher than the corresponding threshold of 250 μg/L [37], suggesting its floral odor participated in the aroma of all the wines. The major ethyl and acetate esters are among the most important volatile compounds for the fresh fruity aroma of young white wines to which they significantly contribute by commonly multiply surpassing their rather low odor perception thresholds, such as 30 μg/L for isoamyl acetate, 20 μg/L for ethyl butyrate, 5 μg/L for ethyl hexanoate, and 2 μg/L for ethyl octanoate [37]. The highest concentration of linear middle-chain ethyl esters and acetates other than 2-phenylethyl acetate, although in some cases without statistical significance, was noted in Malvazija istarska wines. Pošip was also relatively abundant in these esters, except for ethyl hexanoate which was found in the lowest concentration in this and in Maraština wines. Although hexanoic acid is mainly formed in fermentation, grapes also contain non-negligible concentration. This means that the concentration of ethyl hexanoate in wine is probably partly influenced by the concentration of its precursor, hexanoic acid, in grapes [4], so the lower concentration of ethyl hexanoate in Pošip and Maraština could have been influenced by a genotype.

3.2. GC×GC-TOF-MS

A characteristic HS-SPME/GC×GC-TOF-MS analysis 2D chromatogram of volatile compounds in Malvazija istarska wine is shown in Figure S1. It can be seen that many compounds which were separated by the second dimension column had the same retention times on the first, meaning these compounds would not be adequately separated by the conventional GC-MS. The average concentrations of volatile compounds (tentatively) identified in the investigated wines after GC×GC-TOF-MS analysis are reported in Table 2, while the concentrations found in each of the investigated wines are reported in Table S3. Compounds were grouped according to chemical class, and sorted within each class in order of decreasing F-ratio determined by one-way ANOVA. Three hundred and seventeen (317) volatile aroma compounds were identified, including 53 terpenes, 10 norisoprenoids, 50 benzenoids, 5 hydrocarbons, 7 aldehydes, 24 ketones, 32 alcohols, 16 acids, 73 esters, 5 volatile phenols, 17 furanoids and lactones, 19 sulfur containing compounds, and 6 other compounds. GC×GC-TOF-MS exhibited superior peak annotation ability than GC-MS which enabled the identification of a much larger number of compounds, as a consequence of higher separation efficiency, enhanced sensitivity, and clearer mass spectra allowed by separation on two different phases [23]. Other factors which could have affected the differences between the results obtained by the two techniques/methods were the absolute sensitivity of the analyzers, SPME conditions (sample volume and dilution, duration and temperature of extraction, fiber length, etc.), and others. To our knowledge, with 350 compounds identified by GC-MS and GC×GC-TOF-MS combined, this study reported one of the most detailed volatile aroma profiles in wine to date. It has to be noted that for particular compounds which were analyzed and reported by both the techniques applied the obtained absolute concentrations differed due to different quantification methods used: quantitative analysis with the use of standards solutions and calibration curves in GC-MS, and semi-quantification relative to internal standard 1-octanol concentration, assuming a response factor equal to one, in GC×GC-TOF-MS analysis, respectively. The concentrations of many volatile compounds were found to be significantly different between wines (161), but relatively few were found to be exclusive markers of particular variety.
In order to compare the techniques applied, the GC×GC-TOF-MS results for the major monoterpenols and some other compounds already quantified by GC-MS and reported in Table 1 were also reported in Table 2. It was observed that the results, in relative terms, were mostly in fair agreement. α-Terpineol was confirmed as a monoterpene and a volatile aroma compound in general with the highest discriminative power, with an F-ratio even higher than that obtained after GC-MS data elaboration. α-Terpineol was followed by limonene and linalool, as well as some other monoterpenes which were also among the most potent volatiles according to this criterion as determined by GC-MS, such as nerol, ho-trienol, 4-terpineol, and trans-β-ocimene. On the other hand, some discrepancies were observed; for example, in the case of geraniol, α-terpinolene, and geranyl ethyl ether, with a high F-ratio obtained by GC×GC-TOF-MS and a relatively low F-ratio obtained by GC-MS data elaboration. The opposite was observed for citronellol. It is possible that the discrepancies observed derived from the co-elution of the mentioned monoterpenes with particular unidentified compounds having mass spectra with ions of equal mass to those used for quantification of terpenes during GC-MS analysis, although strict measures have been taken to ensure the quality of the results.
Similar as in the case of GC-MS results (Table 1), Škrlet wines were the most abundant in monoterpenes, followed by Malvazija istarska, then Pošip, and finally Maraština and Kraljevina wines with the lowest concentrations (Table 2). Only a few exceptions were noted: Škrlet wines contained the lowest concentration of β-calacorene, while Malvazija wine was deficient in cis-Z-α-bisabolene epoxide. Although Kraljevina wine was generally poor in terpenes, several sesquiterpenes, such as cadalene, β-calacorene, and especially tentatively identified γ-dehydro-ar-himachalene, emerged as potential markers of the varietal origin of this wine.
All the other classes of compounds were confirmed to be far less efficient in differentiating the investigated monovarietal wines than terpenes, with few exceptions. The number of C13-norisoprenoids identified by the two techniques applied was similar, but their identities differed in most cases. The relative results for β-damascenone obtained by GC-MS and GC×GC-TOF-MS were in a fair agreement, with the highest concentration found in Malvazija istarska and the lowest in Škrlet wines (Table 2). A similar degree of correspondence between GC-MS and GC×GC-TOF-MS results and the corresponding F-ratios was observed for a vitispirane isomer. Kraljevina wines contained the highest concentration of tentatively identified 1,2-dihydro-1,4,6-trimethylnaphthalene.
Superiority of GC×GC-TOF-MS over GC-MS in terms of compound separation and identification was demonstrated well in the analysis of benzenoids, with a much larger number of compounds identified by the former technique. Several benzenoids were found to be relatively efficient discriminators between monovarietal wines, and some of them were exclusive differentiators for particular varieties. High ethyl benzene concentration was specific for Pošip, while 1,1′-oxybisbenzene was most abundant in Malvazija istarska wines, in both cases supported by rather high F-ratios. In addition to the highest concentration of 1,1′-oxybisbenzene, Malvazija istarska wine was characterized by most varietal markers among benzenoids, including octylbenzene, a non-identified benzenoid, azulene, 2-methylnaphthalene, and methyl 2-(benzyloxy)propanoate. Pošip was characterized by the highest ethyl benzene and trans-edulan concentration, Kraljevina was the most abundant in 6-[1-(hydroxymethyl)vinyl]-4,8a-dimethyl-1,2,4a,5,6,7,8,8a-octahydro-2-naphthalenol, while Škrlet wine was the richest in m-methoxyanisole and α,α-dimethylbenzenemethanol (Table 2).
No significant differences were found between the concentrations of hydrocarbons, while aldehydes also turned out to be poor varietal differentiators, with significant differences found only for decanal (Table 2). On the other hand, several ketones were found useful for this purpose: the highest concentration of 2-undecanone and 3-undecanone was specific for Malvazija istarska, 1,4,7,10,13-pentaoxacyclononadecane-14,19-dione and cyclohexylideneacetone were characteristic for Škrlet, while the lowest concentration of isophorone was found in Maraština wines.
4-Methyl-1-heptanol was the most useful among alcohols in differentiating monovarietal wines with a rather high F-ratio (Table 2). It was found in the highest concentration in Škrlet, followed by Malvazija istarska wines, while the other wines contained lower concentrations. The results for cis-3-hexen-1-ol were in accordance with those obtained by GC-MS, with the highest concentration found in Dalmatian Pošip and Maraština wines. 3-Octanol and 1-octen-3-ol were exclusive markers for Pošip, 2-decanol for Škrlet, while the lowest concentration of an isomer of 2-penten-1-ol was characteristic for Kraljevina wine. F-ratios determined for fatty acids were relatively low and significant differences were found only for five of them.
A very large number of minor esters was identified by GC×GC-TOF-MS analysis (Table 2). In accordance with the GC-MS data, the concentrations of the majority of esters of aliphatic higher alcohols and fatty acids were the highest in Malvazija istarska wines. Despite the thesis that precursor concentrations do not significantly determine the concentrations of acetate esters formed by Saccharomyces cerevisiae [60], the highest concentration of cis-3-hexen-1-yl acetate corresponded to the highest concentration of its precursor, cis-3-hexen-1-ol, found in Pošip wine. Pošip wine was the most abundant in particular esters of ethanol and hydroxyl keto acids, such as diethyl glutarate and ethyl pyruvate. Although without a statistically significant difference, the concentrations of the related esters, such as ethyl lactate and diethyl succinate, determined by GC-MS, also had a tendency to be higher in Pošip wines.
Pošip wines contained the highest concentration of volatile phenols, such as 2-methoxyphenol and 4-vinylguaiacol. Significant differences were found for particular furanoids and lactones. A number of sulfur containing compounds was identified, with many of them found in the highest concentration in Pošip wines, some with relatively high F-ratios, such as methional. Kraljevina and Škrlet wines were generally the least abundant in these compounds (Table 2).

3.3. Multivariate Statistical Analysis

PCA allowed a good separation of the investigated monovarietal wines according to variety when applied on a dataset reduced to 40 variables with the highest F-values, obtained by both GC-MS and GC×GC-TOF-MS analysis. Monovarietal wines were clearly separated from each other in two-dimensional space despite a relatively high number of varieties (Figure 1). Škrlet wine was clearly differentiated from the others along the direction of PC1 and was characterized by higher amounts of terpenes. A part of Malvazija istarska wines also gravitated towards higher positive PC1 values, but the wines of this variety were also separated from the others along the direction of PC2, mostly due to higher concentrations of particular esters with positive PC2 values. Volatile aroma compounds located in the second quadrant of Cartesian system with negative PC1 and positive PC2 coordinates, 2,3-dihydro-1,1,5,6-tetramethyl-1H-indene and γ-dehydro-ar-himachalene, contributed most to the separation of Kraljevina wines, while the location of Pošip wines was obviously conditioned by the loadings of cis-3-hexen-1-ol, vitispirane II, ethyl benzoate, methional, cis-3-hexen-1-yl acetate, 2-phenethyl acetate, and 2-(methylthio)ethanol. Maraština wines were apparently not linked to any particular compound class, probably due to lower concentrations of the 40 volatile compounds used for PCA.
Hierarchical clustering analysis according to variety, performed using the amounts of the 60 volatile aroma compounds with the highest F-ratio, confirmed that each monovarietal wine had a distinct volatile profile (Figure 2). Most of the conclusions were similar to those obtained by the PCA. Škrlet and Malvazija Istarska wines were clearly separated from each other mostly due to higher concentrations of particular esters in the latter, but were clustered together by high terpene concentrations. The generated heatmap probably offered the clearest insight into the intra-varietal diversity of particular wines, especially Malvazija with two evident clusters with different terpene content. Pošip formed a distinct cluster mostly due to high concentrations of particular compounds from several classes, some of them already mentioned in the PCA, including vitispirane II, trans-edulan, methional, 2-phenyletahnol, cis-3-hexen-1-ol and its acetate, ethyl benzoate, 2-heptanol, 2-phenethyl acetate, ethyl cinnamate, and others. Kraljevina wines were clearly the least abundant in the majority of the 60 pre-selected compounds, except for γ-dehydro-ar-himachalene, 1,2-dihydro-1,4,6-trimethylnaphthalene and particular benzenoids, which were confirmed as its markers.
SLDA was applied on a dataset reduced to 60 most significant volatile aroma compounds according to F-ratio from both GC-MS and GC×GC-TOF-MS original datasets. All the monovarietal wines were classified correctly according to variety by this model, and 24 most significant variables were extracted (Figure 3), with rather high squared Mahalanobis distances from group centroids. A 100% correct classification was obtained after including only seven variables. α-Terpineol was confirmed once again as the most powerful varietal marker, since the SLDA model classified correctly 68.75% of all the wines and 100.00% of Škrlet wines by using only this variable. After including β-pinene and ethyl benzoate the total percentage of correctly classified wines increased to 93.75%. For achieving a 100.00% correct classification, 1,1′-oxybisbenzene, γ-dehydro-ar-himachalene, vitispirane II, and 2,6,10,10-tetramethyl-1-oxaspiro[4.5]deca-3,6-diene were included in the SLDA model. The following 17 volatile aroma compounds were also included: 2-phenethyl acetate, isophorone, monoterpenyl acetate (n.i.; m/z 93, 69, 121), 2,3-dihydro-1,1,5,6-tetramethyl-1H-indene II, cis-3-hexen-1-ol, methyl hexanoate, trans-rose oxide, methyl decanoate, cis-3-hexen-1-yl acetate, monoterpene (n.i.; m/z 93, 69, 41), β-myrcene, limonene, 3-methyl-2(5H)-furanone, 2-phenylethanol, 1,2-dihydro-1,4,6-trimethylnaphthalene, nerol, and nerol oxide.
Apparently, SLDA has extracted volatile aroma compounds which were most useful for the differentiation of the five investigated monovarietal wines between each other, which only partly coincided with the compounds with the highest F-ratios obtained by ANOVA. Monoterpenes had a key role again, especially α-terpineol. The ability of the SLDA model to predict a correct variety was checked by “leave-one-out” cross-validation, where each wine sample was excluded and classified by the functions derived from all the other wine samples. The correct prediction rate achieved was 100.00%.
To compare the usefulness of the information contained in the composition of terpenes alone obtained by GC-MS and GC×GC-TOF-MS analysis for differentiating monovarietal wines, SLDA was applied separately on the two datasets containing 20 and 31 terpenes, respectively, found significant by ANOVA. Both GC-MS and GC×GC-TOF-MS dataset based models succeeded in achieving 100.00% correct classification (Figure 4). α-Terpineol was again confirmed as a key differentiator, since both models included it as the first, which classified correctly 59.38% and 68.75% monovarietal wines, respectively. For achieving 100.00% correct classification, the GC-MS model further included trans-ocimene, cis-linalool furan oxide, β-pinene, citronellol, trans-nerolidol, ho-trienol, trans-rose oxide, and limonene, while the GC×GC-TOF-MS model extracted γ-dehydro-ar-himachalene, ho-trienol, nerol, o-cymene, isogeraniol, a non-identified sesquiterpene (n.i.; m/z 119, 93, 69), neryl ethyl ether, and cis-α-ocimene. The classification efficacy of the models was improved by including further eight and nine terpenes, respectively. The GC×GC-TOF-MS model exhibited a superior efficacy judging from the degree of the overlapping of the corresponding 95% confidence areas, as well as higher squared Mahalanobis distances on the average, especially for Škrlet wines.
The volatile aroma compounds which were found to be most useful for the differentiation of the investigated wines in this study were only partly in accordance with the ones highlighted in previous studies which applied a similar multivariate statistical approach. For example, Welke et al. [29] characterized and differentiated wines from Chardonnay, Sauvignon Blanc, Pinot Noir, Merlot, and Cabernet Sauvignon based on volatile aroma composition obtained by GC×GC-TOF-MS analysis and extracted the following 12 volatile compounds as the most useful for their differentiation: diethyl succinate, 2,3-butanediol, nerol, 3-penten-2-one, diethyl malonate, β-santalol, ethyl 9-decenoate, alcohol-C9, 4-carene, tetrahydro-2(2H)-pyranone, dihydro-2(3H)-thiophenone, and 3-methyl-2(5H)-furanone. It is probable that the main reason for such discrepancy between this and the study from Welke et al. [29] was the fact that the mentioned authors mutually compared wines from white and red varieties, which greatly differ with respect to the production technology, which, besides variety, certainly greatly contributed to the differences between wines. Welke et al. [29] also obtained a SLDA model that differentiated wines according to variety with a 100% correct recognition ability, while some other authors who applied conventional GC-MS for the same purpose, such as Zhang et al. [61] and Câmara, Alves and Marques [14], did not succeed completely. Fabani, Ravera, and Wunderlin [15] obtained a 100% correct discrimination among Syrah, Malbec, and Bonarda red wines by the application of SLDA on GC-MS data with ethyl hexanoate, ethyl octanoate, 1-hexanol, benzyl alcohol, and isoamyl acetate as the most useful differentiators. Terpenes were not analyzed. Ziółkowska, Wąsowicz, and Jeleń [19] obtained a relatively good differentiation of red wines, with the ability of the LDA model to correctly classify and predict their varietal origin based on HS-SPME/GC-MS data of 95%, while the model built for white wines was not that successful. The compounds most useful for the differentiation of white wines (Chardonnay, Sauvignon Blanc, and Muscat) were isoamyl acetate, furfural, ethyl octanoate, ethyl decanoate, and ethyl dodecanoate, while red wines (Cabernet Sauvignon and Merlot) were differentiated mainly by 1-hexanol, ethyl decanoate, and 2-phenylethanol. It should be noted that the samples of the same variety were collected across several countries, which was certainly a factor that introduced large variability.

4. Conclusions

HS-SPME/GC×GC-TOF-MS analysis, alone or combined with conventional HS-SPME/GC-MS, was shown to be an excellent analytical tool for differentiation of wines according to variety based on volatile aroma compound composition. It has also been proven that the additional separation efficiency enabled by the second chromatographic column in GC×GC-TOF-MS analysis was crucial for the separation and identification of a very large number of volatile compounds, which would otherwise remain undetected by conventional GC-MS. This feature provided additional in-depth volatile profile information which was exploited for highly efficient white wine varietal differentiation. Such an outcome can be considered even more successful knowing that the number of varieties was relatively high while that of wine samples of each variety was relatively small, and that the investigated wines were characterized by high intra-varietal heterogeneity in terms of micro-locations and grape cultivation and winemaking parameters. The results of this study confirmed the unmatched power of monoterpenes to discriminate wines according to variety, which was robust enough to be captured by uni- and multivariate statistics based on both GC-MS and GC×GC-TOF-MS analysis data separately.

Supplementary Materials

The following are available online at https://www.mdpi.com/2304-8158/9/12/1787/s1, Figure S1: Example of a contour plot obtained for Malvazija istarska monovarietal wine using HS-SPME/GC×GC-TOF-MS. Colored areas represent more abundant volatile aroma compounds and black dots represent less abundant and trace volatile aroma compounds, Table S1: Physico-chemical parameters in in Croatian monovarietal wines, Table S2: Concentrations (μg/L) of volatile aroma compounds found in individual Croatian monovarietal wines after headspace solid-phase microextraction followed by gas chromatography-mass spectrometry (HS-SPME/GC–MS) sorted by compound class, Table S3: Concentrations (μg/L relative to internal standard 2-octanol) of volatile aroma compounds found in individual Croatian monovarietal wines obtained by headspace solid-phase microextraction combined with comprehensive two-dimensional gas chromatography-mass spectrometry with time-of-flight mass spectrometric detection (HS-SPME/GC×GC-TOF-MS) sorted by compound class.

Author Contributions

Conceptualization, I.L.; methodology, I.L. and U.V.; formal analysis, I.L. and S.C.; investigation, I.L. and S.C.; resources, I.L. and U.V.; data curation, I.L. and U.V.; writing—original draft preparation, I.L.; writing—review and editing, I.L. and U.V.; supervision, I.L. and U.V.; project administration, I.L. and U.V.; funding acquisition, I.L. and U.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Croatian Science Foundation grant number UIP-2014-09-1194 and by the ADP 2017 project funded by the Autonomous Province of Trento.

Acknowledgments

The authors would like to thank wine producers from Croatia for donating wine samples, Irena Budić-Leto, Sanja Radeka, and the panel for sensory analysis of wine from the Institute of Agriculture and Tourism in Poreč, Croatia, for assistance in collecting and selection of wine samples, Ivana Puhelek for assistance in collecting wine samples, and Ivana Horvat for technical assistance.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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Figure 1. (a) Separation of Croatian monovarietal wines according to variety in two-dimensional space defined by the first two principal components, PC1 and PC2; (b) Factor loadings of selected variables (40 volatile aroma compounds with the highest F-ratios), as determined by gas chromatography mass spectrometry (GC-MS) and two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOF-MS) analysis, on PC1 and PC2.
Figure 1. (a) Separation of Croatian monovarietal wines according to variety in two-dimensional space defined by the first two principal components, PC1 and PC2; (b) Factor loadings of selected variables (40 volatile aroma compounds with the highest F-ratios), as determined by gas chromatography mass spectrometry (GC-MS) and two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOF-MS) analysis, on PC1 and PC2.
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Figure 2. Hierarchical clustering analysis performed using volatile aroma compound profiles of Croatian monovarietal wines obtained by GC-MS and GC×GC-TOF-MS analysis. The heatmap was generated using 60 most significant compounds (the highest F-ratios). The rows in the heatmap represent compounds and the columns indicate samples. Compounds are designated by numbers which correspond to those in Table 1 (GC, i.e., GC-MS) or in Table 2 (GCGC, i.e., GC×GC-TOF-MS). The colors of heatmap cells indicate the abundance of compounds across different samples. The color gradient, ranging from dark blue through white to dark red, represents low, middle, and high abundance of a compound.
Figure 2. Hierarchical clustering analysis performed using volatile aroma compound profiles of Croatian monovarietal wines obtained by GC-MS and GC×GC-TOF-MS analysis. The heatmap was generated using 60 most significant compounds (the highest F-ratios). The rows in the heatmap represent compounds and the columns indicate samples. Compounds are designated by numbers which correspond to those in Table 1 (GC, i.e., GC-MS) or in Table 2 (GCGC, i.e., GC×GC-TOF-MS). The colors of heatmap cells indicate the abundance of compounds across different samples. The color gradient, ranging from dark blue through white to dark red, represents low, middle, and high abundance of a compound.
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Figure 3. Separation of Croatian monovarietal wines according to variety defined by the first three discriminant functions (roots) obtained by forward stepwise discriminant analysis (SLDA) on the basis of volatile aroma compound composition determined by GC-MS and GC×GC-TOF-MS analysis. (a) root 1 vs root 2; (b) root 1 vs root 3; (c) root 2 vs root 3.
Figure 3. Separation of Croatian monovarietal wines according to variety defined by the first three discriminant functions (roots) obtained by forward stepwise discriminant analysis (SLDA) on the basis of volatile aroma compound composition determined by GC-MS and GC×GC-TOF-MS analysis. (a) root 1 vs root 2; (b) root 1 vs root 3; (c) root 2 vs root 3.
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Figure 4. Separation of Croatian monovarietal wines according to variety defined by the first three discriminant functions (roots) obtained by forward stepwise discriminant analysis (SLDA) on the basis of volatile terpene composition determined by GC-MS (ac) and GC×GC-TOF-MS (df) analysis.
Figure 4. Separation of Croatian monovarietal wines according to variety defined by the first three discriminant functions (roots) obtained by forward stepwise discriminant analysis (SLDA) on the basis of volatile terpene composition determined by GC-MS (ac) and GC×GC-TOF-MS (df) analysis.
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Table 1. Concentrations (μg/L) of volatile aroma compounds found in Croatian monovarietal wines after headspace solid-phase microextraction followed by gas chromatography-mass spectrometry (HS-SPME/GC–MS) sorted by compound class and descending Fisher F-ratio.
Table 1. Concentrations (μg/L) of volatile aroma compounds found in Croatian monovarietal wines after headspace solid-phase microextraction followed by gas chromatography-mass spectrometry (HS-SPME/GC–MS) sorted by compound class and descending Fisher F-ratio.
No.Volatile CompoundstRIDLRIexpLRIlitF-RatioVariety
(min:s) MIPOMAKRSK
Terpenes
1α-Terpineol39:59S, MS, LRI1684168435.0715.65 ± 7.04 b10.92 ± 3.16 bc5.50 ± 2.10 cd1.98 ± 0.89 d40.49 ± 11.05 a
2Monoterpene
(n.i.; m/z 59, 93, 121)
28:29MS1441-27.681.03 ± 0.50 b0.64 ± 0.24 bc0.27 ± 0.24 cd0.02 ± 0.04 d2.79 ± 1.01 a
3Linalool33:10S, MS, LRI1542154224.7168.00 ± 27.76 b38.17 ± 8.05 c18.52 ± 8.28 d7.64 ± 2.56 d90.75 ± 15.48 a
4Limonene15:17MS, LRI1191119618.911.33 ± 0.68 b0.98 ± 0.28 b0.19 ± 0.05 c0.36 ± 0.11 c2.66 ± 1.01 a
5Nerol44:35S, MS, LRI1791179116.3113.38 ± 6.72 a6.49 ± 1.96 b4.55 ± 1.58 bc1.06 ± 0.46 c17.36 ± 3.74 a
6cis-Linalool furan oxide29:24MS, LRI1464146412.570.08 ± 0.03 b0.18 ± 0.06 a0.06 ± 0.05 b0.02 ± 0.01 b0.20 ± 0.11 a
7Monoterpenyl acetate
(n.i.; m/z 93, 69, 121)
21:55MS1302-12.503.12 ± 1.85 a1.11 ± 0.27 b0.59 ± 0.36 b0.12 ± 0.06 b3.16 ± 0.84 a
84-Terpineol35:37MS, LRI1594159611.600.24 ± 0.10 b0.24 ± 0.06 b0.23 ± 0.11 b0.11 ± 0.03 c0.51 ± 0.08 a
9β-Pinene13:45MS, LRI1146114511.464.40 ± 2.41 a2.43 ± 0.75 bc0.40 ± 0.15 d1.16 ± 0.37 cd4.17 ± 1.06 ab
10Ho-Trienol36:02MS, LRI1601160110.447.45 ± 3.95 a6.95 ± 2.01 ab1.71 ± 1.14 c1.60 ± 0.76 c4.18 ± 0.79 bc
11trans-Rose oxide23:23MS, LRI1352134110.320.27 ± 0.08 b0.21 ± 0.04 bc0.15 ± 0.07 c0.16 ± 0.03 bc0.59 ± 0.34 a
12Monoterpene
(n.i.; m/z 93, 69, 41)
29:56MS1476-8.510.49 ± 0.28 b0.25 ± 0.07 c0.24 ± 0.17 c0.12 ± 0.13 c0.77 ± 0.24 a
13trans-Ocimene18:03MS, LRI125212508.451.58 ± 0.92 a1.27 ± 0.41 ab0.17 ± 0.07 c0.55 ± 0.18 bc1.30 ± 0.50 ab
14Citronellol43:11S, MS, LRI175817588.345.02 ± 0.61 a5.09 ± 0.69 a5.30 ± 1.78 a2.56 ± 0.30 b5.60 ± 1.75 a
15Nerol oxide29:18MS, LRI145914647.013.04 ± 1.12 a3.74 ± 1.82 a1.35 ± 1.17 b1.11 ± 0.40 b4.11 ± 1.44 a
16Geranyl acetone47:01MS, LRI184518455.382.93 ± 0.58 b3.58 ± 0.99 b7.58 ± 4.80 a2.64 ± 0.39 b2.55 ± 1.14 b
17trans-Linalool pyran oxide41:49MS, LRI172617524.850.08 ± 0.02 b0.13 ± 0.05 a0.07 ± 0.05 b0.04 ± 0.03 b0.06 ± 0.02 b
18trans-Nerolidol54:39MS, LRI203120314.612.89 ± 0.50 a3.17 ± 0.59 a2.66 ± 1.58 ab1.59 ± 0.22 b1.53 ± 0.35 b
19Monoterpene
(n.i.; m/z 121, 93, 136)
31:30MS1509-3.092.45 ± 0.49 a2.41 ± 0.56 a2.11 ± 0.73 a1.11 ± 0.16 b2.88 ± 2.79 a
20Geraniol46:35S, MS, LRI183818382.9340.64 ± 21.59 ab24.23 ± 8.96 ab39.96 ± 48.27 ab2.73 ± 1.56 b46.19 ± 10.53 ab
21Geranyl ethyl ether31:54MS, LRI151114992.690.53 ± 0.330.86 ± 0.971.08 ± 0.840.05 ± 0.020.82 ± 0.25
22α-Terpinolene19:34MS, LRI128712812.320.49 ± 0.290.73 ± 0.920.07 ± 0.040.14 ± 0.070.33 ± 0.26
C13-norisoprenoids
23Vitispirane II31:16MS, LRI152315299.850.07 ± 0.02 c0.34 ± 0.16 a0.20 ± 0.10 b0.09 ± 0.01 c0.14 ± 0.06 bc
24β-Damascenone45:26MS, LRI180918097.093.52 ± 0.69 a2.81 ± 1.42 ab1.99 ± 0.58 bc2.28 ± 0.25 b0.89 ± 0.29 c
25Actinidol I49:55MS, LRI191419145.590.12 ± 0.05 a0.16 ± 0.06 a0.13 ± 0.07 a0.04 ± 0.01 b0.09 ± 0.03 ab
26Actinidol II50:27MS, LRI192719275.100.20 ± 0.08 a0.23 ± 0.07 a0.23 ± 0.10 a0.08 ± 0.01 b0.16 ± 0.04 ab
27Vitispirane I32:08MS, LRI152115265.030.09 ± 0.04 c0.46 ± 0.24 a0.33 ± 0.24 ab0.19 ± 0.05 bc0.32 ± 0.18 abc
28β-Ionone50:17S, MS, LRI192319233.890.06 ± 0.01 ab0.05 ± 0.01 b0.07 ± 0.01 a0.05 ± 0.01 b0.07 ± 0.01 a
29Actinidol ethyl ether I40:25MS, LRI169016903.370.25 ± 0.12 bc0.43 ± 0.24 a0.34 ± 0.25 ab0.11 ± 0.02 c0.24 ± 0.06 bc
30Actinidol ethyl ether II41:49MS, LRI172317232.760.15 ± 0.07 ab0.25 ± 0.16 a0.20 ± 0.15 a0.06 ± 0.01 b0.15 ± 0.04 ab
Benzenoids
31Ethyl cinnamate57:33S, MS, LRI211121226.960.41 ± 0.19 b1.16 ± 0.78 a0.39 ± 0.08 b0.21 ± 0.10 b0.16 ± 0.10 b
32Benzaldehyde31:26S, MS, LRI150815090.841.66 ± 1.253.48 ± 5.401.17 ± 0.542.56 ± 0.813.11 ± 1.57
Alcohols
331-Hexanol23:35S, MS, LRI1356135725.56792.14 ± 264.44 b949.93 ± 179.86 b859.15 ± 171.18 b321.89 ± 32.90 c1544.09 ± 146.31 a
34cis-3-Hexen-1-ol25:03S, MS, LRI1379137912.7377.49 ± 40.64 c299.33 ± 113.23 a193.20 ± 123.23 b26.16 ± 4.63 c54.67 ± 23.77 c
352-Phenylethanol48:52S, MS, LRI189118937.1620,047.0 ± 4767.1 b33,176.1 ± 4679.3 a32,117.2 ± 10,870.7 a20,712.5 ± 6134.8 b17,665.9 ± 1061.0 b
36trans-3-Hexen-1-ol24:03S, MS, LRI136113611.7361.38 ± 24.0945.64 ± 17.9946.57 ± 10.2843.09 ± 10.2663.87 ± 22.80
Acids
37Decanoic acid62:49S, MS, LRI225722585.05646.02 ± 179.70 b1627.60 ± 659.33 a1062.71 ± 505.33 b994.33 ± 67.19 b1090.36 ± 494.95 ab
38Octanoic acid54:56S, MS, LRI204320424.034294.07 ± 796.78 b6239.74 ± 1532.91 a5147.23 ± 1562.12 ab6219.42 ± 455.69 a6359.73 ± 1152.33 a
39Hexanoic acid46:10S, MS, LRI183018283.055715.09 ± 552.13 ab5184.65 ± 722.46 b5284.54 ± 1710.50 b6487.89 ± 603.01 a7025.45 ± 1103.35 a
40Butyric acid36:28S, MS, LRI161216120.541766.10 ± 323.751607.09 ± 231.341685.41 ± 407.861581.53 ± 184.631788.32 ± 346.09
Esters
412-Phenethyl acetate45:03S, MS, LRI180318019.022230.06 ± 481.79 b4731.20 ± 1467.85 a2359.08 ± 1289.62 b2579.92 ± 287.25 b1750.70 ± 284.91 b
42Ethyl octanoate28:06S, MS, LRI143514358.881211.04 ± 239.22 a1086.51 ± 223.88 a817.08 ± 231.10 b701.64 ± 160.66 b544.02 ± 243.59 b
43Ethyl hexanoate17:35S, MS, LRI123612366.80721.60 ± 172.38 a379.34 ± 86.89 c463.42 ± 153.50 bc580.60 ± 120.60 ab474.95 ± 108.08 bc
44Hexyl acetate19:26S, MS, LRI127212726.10216.64 ± 52.04 a204.45 ± 73.60 a123.25 ± 54.35 b107.91 ± 34.65 b207.09 ± 40.86 a
45Ethyl decanoate37:43S, MS, LRI163716385.61302.58 ± 46.92 a279.95 ± 69.24 ab179.10 ± 81.94 c220.08 ± 29.45 bc199.26 ± 29.89 bc
46Isoamyl acetate12:29S, MS, LRI112011223.973299.12 ± 1092.74 a3321.37 ± 1674.71 a1460.92 ± 566.57 b2397.45 ± 774.95 ab1879.81 ± 562.20 ab
47Ethyl butyrate09:27S, MS, LRI103010303.09456.83 ± 69.21 a415.44 ± 50.58 ab363.29 ± 80.70 b367.30 ± 47.60 b350.99 ± 74.33 b
48Ethyl 3-methylbutyrate10:31S, MS, LRI106510652.588.51 ± 1.9814.79 ± 5.5712.86 ± 5.2611.34 ± 4.398.39 ± 0.88
49Ethyl 2-methylbutyrate10:00S, MS, LRI104910492.174.19 ± 1.136.57 ± 2.316.57 ± 2.706.25 ± 2.484.01 ± 0.62
50Diethyl succinate39:04S, MS, LRI166716691.531634.59 ± 398.331917.40 ± 1362.671665.03 ± 858.64997.49 ± 290.901064.55 ± 106.44
51Ethyl lactate22:56S, MS, LRI134113410.5825,943.4 ± 13,586.845,815.9 ± 55,981.734,462.1 ± 16,552.625,359.5 ± 12,701.832654.3 ± 7282.3
ID—identification of compounds; S—retention time and mass spectrum consistent with that of the pure standard and with NIST05 mass spectra electronic library; LRI—linear retention index consistent with that found in literature; MS—mass spectra consistent with that from NIST05 mass spectra electronic library or literature; n.i.—not identified. The compounds with only MS symbol in ID column were tentatively identified. The compounds for which pure standards were not available (without symbol S in the ID column) were quantified semi-quantitatively and their concentrations were expressed as equivalents of compounds with similar chemical structure assuming a response factor = 1. LRIexp—linear retention index obtained experimentally. Varieties: MI—Malvazija istarska, PO—Pošip, MA—Maraština, KR—Kraljevina, SK—Škrlet. Different superscript lowercase letters in a row represent statistically significant differences between mean values at p < 0.05 obtained by one-way ANOVA and least significant difference (LSD) test.
Table 2. Concentrations (μg/L relative to internal standard 2-octanol) of volatile aroma compounds found in Croatian monovarietal wines obtained by headspace solid-phase microextraction followed by comprehensive two-dimensional gas chromatography-mass spectrometry with time-of-flight mass spectrometric detection (HS-SPME/GC×GC-TOF-MS) sorted by compound class and descending Fisher F-ratio.
Table 2. Concentrations (μg/L relative to internal standard 2-octanol) of volatile aroma compounds found in Croatian monovarietal wines obtained by headspace solid-phase microextraction followed by comprehensive two-dimensional gas chromatography-mass spectrometry with time-of-flight mass spectrometric detection (HS-SPME/GC×GC-TOF-MS) sorted by compound class and descending Fisher F-ratio.
No.Volatile CompoundstR (1D)tR (2D)IDLRIexpLRIlitF-RatioVariety
(min:s)(min:s) MIPOMAKRSK
Terpenes
1α-Terpineol18:47.200:01.2MS, LRI17101709112.9043.683 ± 1.391 b2.440 ± 0.424 c1.256 ± 0.455 d0.712 ± 0.369 d11.628 ± 0.495 a
2Limonene08:01.000:01.8S, MS, LRI1191119454.2311.401 ± 0.746 b0.429 ± 0.261 c0.360 ± 0.105 c0.191 ± 0.114 c3.956 ± 0.291 a
3Linalool15:50.000:01.1S, MS, LRI1541154123.27216.664 ± 7.072 b10.757 ± 1.712 c5.318 ± 1.567 d2.857 ± 0.970 d23.674 ± 3.494 a
4trans-Alloocimene12:13.000:01.6MS, LRI1384138822.0800.362 ± 0.189 b0.137 ± 0.032 c0.088 ± 0.044 c0.040 ± 0.022 c0.753 ± 0.282 a
5o-Cymene09:49.900:01.6S, MS, LRI1273126820.7451.305 ± 0.436 b0.631 ± 0.353 c0.441 ± 0.268 c0.278 ± 0.142 c2.613 ± 1.042 a
6γ-Dehydro-ar-himachalene25:10.000:01.7MS2046-18.7200.003 ± 0.003 b0.003 ± 0.003 b0.003 ± 0.002 b0.016 ± 0.006 a0.004 ± 0.004 b
7β-Myrcene07:18.800:01.6S, MS, LRI1159115917.2442.351 ± 1.293 b0.885 ± 0.539 c0.331 ± 0.070 c0.183 ± 0.094 c4.353 ± 1.916 a
8Nerol20:43.500:01.0S, MS, LRI1812181116.9440.568 ± 0.277 b0.220 ± 0.118 c0.225 ± 0.070 c0.077 ± 0.038 c0.810 ± 0.139 a
9cis-α-Ocimene09:24.800:01.6MS, LRI1254125514.7242.278 ± 0.937 a0.754 ± 0.205 b0.459 ± 0.087 b0.337 ± 0.170 b3.070 ± 1.903 a
10trans-Linalool furan oxide13:39.900:01.2S, MS, LRI1445145014.6010.444 ± 0.117 b0.480 ± 0.160 b0.221 ± 0.144 c0.157 ± 0.138 c0.872 ± 0.264 a
11Ho-trienol17:07.000:01.0MS, LRI1607161213.9452.843 ± 1.206 a2.307 ± 0.568 a0.669 ± 0.405 b0.712 ± 0.395 b2.510 ± 0.219 a
12Geraniol21:33.000:01.0S, MS, LRI1856185711.7610.432 ± 0.254 a0.225 ± 0.091 b0.124 ± 0.041 b0.084 ± 0.020 b0.589 ± 0.079 a
13Carvomenthenal17:14.000:01.5MS, LRI1615162911.3210.381 ± 0.215 a0.193 ± 0.088 b0.142 ± 0.052 b0.057 ± 0.034 b0.525 ± 0.132 a
14Linalool ethyl ether11:02.800:01.9MS, LRI1329133110.9005.419 ± 2.787 a1.744 ± 0.925 b0.998 ± 0.204 b0.444 ± 0.219 b6.365 ± 4.476 a
154-Terpineol17:00.000:01.3S, MS, LRI1600159710.8950.464 ± 0.097 b0.363 ± 0.069 cd0.418 ± 0.116 bc0.289 ± 0.083 d0.676 ± 0.045 a
16α-Terpinolene10:03.700:01.9S, MS, LRI1284128210.8461.630 ± 0.872 b0.520 ± 0.288 c0.387 ± 0.217 c0.173 ± 0.085 c3.391 ± 2.459 a
17Geranyl ethyl ether15:08.000:01.8MS, LRI1506150610.3912.042 ± 0.965 a0.710 ± 0.328 b0.500 ± 0.186 b0.222 ± 0.161 b2.960 ± 2.199 a
18Monoterpene (n.i.; m/z 93, 121, 136)13:54.100:01.9MS1455-9.89910.628 ± 4.686 a4.420 ± 1.974 b2.737 ± 1.576 b1.104 ± 0.702 b16.227 ± 12.511 a
19Neryl ethyl ether14:26.500:01.8MS, LRI147714688.9180.334 ± 0.175 b0.143 ± 0.065 bc0.100 ± 0.067 bc0.023 ± 0.021 c0.863 ± 0.729 a
20Monoterpene (n.i.; m/z 68, 93, 121)08:15.200:01.8MS1202-8.9010.252 ± 0.272 b0.126 ± 0.077 bc0.047± 0.021 c0.020 ± 0.015 c0.575 ± 0.180 a
21p-Cymenene13:30.200:01.5MS, LRI143914387.4091.332 ± 0.236 a0.899 ± 0.190 b0.918 ± 0.307 b0.733 ± 0.210 b1.711 ± 0.786 a
22trans-β-Ocimene09:01.700:01.7S, MS, LRI123712416.8330.078 ± 0.148 b0.067 ± 0.087 b0.099 ± 0.109 b0.014 ± 0.019 b0.919 ± 0.926 a
23β-Calacorene22:43.000:01.8MS, LRI191919185.4950.108 ± 0.018 ab0.075 ± 0.011 c0.078 ± 0.011 c0.131 ± 0.044 a0.072 ± 0.052 c
24cis-Z-α-Bisabolene epoxide24:28.000:01.3MS, LRI201020075.3290.002 ± 0.003 c0.008 ± 0.004 bc0.010 ± 0.009 b0.013 ± 0.006 ab0.023 ± 0.016 a
25trans-Linalool pyran oxide19:34.000:01.1MS, LRI175117524.3460.059 ± 0.018 ab0.082 ± 0.049 a0.029 ± 0.031 b0.031 ± 0.019 b0.086 ± 0.025 a
26Cadalene27:46.200:01.6MS, LRI>210021913.9560.047 ± 0.010 b0.039 ± 0.017 b0.035 ± 0.011 b0.064 ± 0.022 a0.032 ± 0.021 b
27Isogeraniol20:55.400:01.0MS, LRI182218283.4570.036 ± 0.030 a0.018 ± 0.014 ab0.005 ± 0.006 b0.010 ± 0.011 b0.015 ± 0.007 ab
28α-Terpinene07:33.600:01.8S, MS, LRI117011753.2250.033 ± 0.061 b0.006 ± 0.010 b0.006 ± 0.010 b0.007 ± 0.015 b0.106 ± 0.120 a
29Sesquiterpene (n.i.; m/z 119, 93, 69)19:48.000:01.8MS1763-2.8090.064 ± 0.010 a0.038 ± 0.020 b0.040 ± 0.014 b0.045 ± 0.012 b0.042 ± 0.038 b
30Menthol17:42.000:01.1MS, LRI164416412.7460.129 ± 0.050 b0.222 ± 0.283 b0.115 ± 0.032 b0.099 ± 0.023 b1.177 ± 1.847 a
31Citronellol20:02.900:01.1S, MS, LRI177617772.7240.303 ± 0.037 ab0.250 ± 0.089 ab0.260 ± 0.089 ab0.154 ± 0.074 b0.309 ± 0.229 ab
32α-Farnesene II19:48.000:01.9S, MS, LRI176317622.1180.053 ± 0.0180.029 ± 0.0160.026 ± 0.0230.039 ± 0.0210.047 ± 0.026
33Monoterpene (n.i.; m/z 93, 121, 94)20:48.100:01.7MS1816-2.0540.056 ± 0.0340.067 ± 0.0270.041 ± 0.0410.028 ± 0.0150.028 ± 0.009
34γ-Cadinene19:55.000:02.1MS, LRI176917741.8950.020 ± 0.0030.013 ± 0.0070.016 ± 0.0040.014 ± 0.0070.012 ± 0.011
35(+)-Cuparene21:05.000:02.0MS, LRI183118301.8470.020 ± 0.0010.014 ± 0.0100.017 ± 0.0040.012 ± 0.0070.012 ± 0.010
36trans-Calamenene21:19.000:01.9MS, LRI184418371.7800.063 ± 0.0190.056 ± 0.0200.049 ± 0.0110.077 ± 0.0280.056 ± 0.023
37Citronellyl acetate18:10.000:01.5MS, LRI167316681.6520.056 ± 0.0310.082 ± 0.0590.041 ± 0.0220.035 ± 0.0170.063 ± 0.060
38α-Calacorene22:29.000:01.8MS, LRI190619161.5330.020 ± 0.0030.014 ± 0.0080.015 ± 0.0050.019 ± 0.0090.012 ± 0.010
39Dehydroaromadendrene28:20.900:01.4MS>2100-1.3060.001 ± 0.0020.014 ± 0.0360.001 ± 0.0020.012 ± 0.0150.028 ± 0.034
40Terpene (n.i.; m/z 121, 93, 136)15:08.000:01.8MS1506-1.2760.891 ± 0.2020.784 ± 0.3280.788 ± 0.3570.458 ± 0.1720.836 ± 1.082
41β-Cyclocitral17:21.000:01.5S, MS, LRI162216291.1950.067 ± 0.0160.071 ± 0.0170.066 ± 0.0300.051 ± 0.0140.052 ± 0.028
42α-Farnesene I18:17.000:01.9S, MS, LRI168116971.1240.126 ± 0.0430.074 ± 0.0340.102 ± 0.0580.115 ± 0.0610.113 ± 0.046
432-Acetyl-2-carene23:11.000:01.3MS1943-1.0880.030 ± 0.0480.037 ± 0.0390.047 ± 0.0500.010 ± 0.0130.054 ± 0.013
44γ-Isogeraniol20:29.200:01.0MS, LRI179918001.0710.148 ± 0.1340.123 ± 0.0830.087 ± 0.0640.061 ± 0.0460.087 ± 0.078
45Cosmene13:41.600:01.4MS, LRI144614600.9900.109 ± 0.1170.056 ± 0.0560.106 ± 0.0680.080 ± 0.0540.027 ± 0.011
46α-Curcumene20:16.000:01.8MS, LRI178717820.7360.026 ± 0.0140.019 ± 0.0070.021 ± 0.0070.029 ± 0.0170.022 ± 0.011
47trans-Geranyl acetone21:40.000:01.5MS, LRI186318680.7340.409 ± 0.4370.228 ± 0.0710.206 ± 0.0600.422 ± 0.5680.152 ± 0.036
48α-Bergamotene16:18.000:02.4MS, LRI156515850.6750.027 ± 0.0110.037 ± 0.0270.058 ± 0.0710.041 ± 0.0200.043 ± 0.024
49Sesquiterpene (n.i.; m/z 93, 80, 121)20:16.000:02.0MS1787-0.5960.021 ± 0.0070.014 ± 0.0080.020 ± 0.0130.022 ± 0.0140.022 ± 0.021
50Neryl acetate19:20.700:01.5MS, LRI173917420.5760.085 ± 0.0210.060 ± 0.0500.058 ± 0.0380.078 ± 0.0540.092 ± 0.083
514-Thujanol15:20.100:01.7MS1516-0.4440.055 ± 0.0400.051 ± 0.0290.067 ± 0.0430.068 ± 0.0240.046 ± 0.012
52Nerolidol24:56.200:01.3S, MS, LRI203420340.4340.114 ± 0.0490.102 ± 0.0400.124 ± 0.0870.142 ± 0.0580.131 ± 0.064
53Geranyl acetate19:55.000:01.5S, MS, LRI176917680.4130.037 ± 0.0150.048 ± 0.0380.035 ± 0.0180.034 ± 0.0130.034 ± 0.033
C13-norisoprenoids
541,2-Dihydro-1,4,6-trimethylnaphthalene25:38.300:01.5MS2071-7.1480.001 ± 0.001 b0.000 ± 0.000 b0.009 ± 0.008 b0.023 ± 0.018 a0.002 ± 0.001 b
55β-Damascenone21:05.000:01.5S, MS, LRI183118326.7368.245 ± 2.169 a5.770 ± 2.963 bc4.338 ± 1.563 cd6.981 ± 1.067 ab2.336 ± 0.303 d
56α-Ionene14:28.900:02.0MS1479-5.3790.045 ± 0.017 bc0.017 ± 0.023 c0.069 ± 0.047 ab0.085 ± 0.031 a0.032 ± 0.017 bc
57Norisoprenoid (n.i.; m/z 69, 121, 105)20:00.500:01.6MS1774-5.0610.248 ± 0.076 a0.163 ± 0.101 b0.127 ± 0.060 bc0.202 ± 0.058 ab0.055 ± 0.025 c
583,4-Dehydro-β-ionone18:38.000:01.8MS1702-4.9200.032 ± 0.009 a0.011 ± 0.010 b0.036 ± 0.017 a0.040 ± 0.020 a0.020 ± 0.004 ab
59Vitispirane I15:29.000:01.9MS, LRI152415243.4701.155 ± 0.481 c3.501 ± 1.555 ab4.058 ± 2.588 a2.200 ± 0.966 bc3.007 ± 2.552 abc
601,2-Dihydro-1,5,8-trimethylnaphthalene19:41.000:01.6MS1757-2.5790.360 ± 0.1090.363 ± 0.1860.682 ± 0.3990.770 ± 0.4511.085 ± 1.062
61Actinidol ethyl ether II18:52.000:01.9MS, LRI171417232.1790.099 ± 0.0820.181 ± 0.1060.167 ± 0.1300.055 ± 0.0300.133 ± 0.067
621,2-Dihydro-1,1,6-trimethylnaphthalene (TDN)19:06.000:01.6S, MS, LRI172717290.8850.021 ± 0.0120.019 ± 0.0100.031 ± 0.0210.026 ± 0.0180.015 ± 0.015
63trans-1-(2,3,6-Trimethylphenyl)buta-1,3-diene (TPB)21:12.000:01.5MS, LRI183718320.4330.065 ± 0.0290.057 ± 0.0360.076 ± 0.0480.057 ± 0.0310.050 ± 0.025
Benzenoids
64Ethyl benzoate18:17.000:01.2MS, LRI1681167820.1940.759 ± 0.232 b1.493 ± 0.366 a0.653 ± 0.128 b0.533 ± 0.118 b0.570 ± 0.115 b
651,1’-Oxybisbenzene24:20.100:01.3MS, LRI2003201718.9560.011 ± 0.002 a0.004 ± 0.002 b0.004 ± 0.003 b0.003 ± 0.001 b0.003 ± 0.001 b
662,3-Dihydro-1,1,5,6-tetramethyl-1H-indene I18:17.000:01.7MS1681-9.8420.076 ± 0.019 bc0.027 ± 0.030 d0.105 ± 0.039 ab0.139 ± 0.054 a0.050 ± 0.013 cd
67Octylbenzene19:27.000:01.8MS, LRI174517468.6380.109 ± 0.011 a0.065 ± 0.022 b0.074 ± 0.010 b0.072 ± 0.012 b0.070 ± 0.032 b
68trans-Edulan17:07.000:01.8MS, LRI160716027.9380.039 ± 0.016 b0.084 ± 0.018 a0.056 ± 0.019 b0.042 ± 0.010 b0.035 ± 0.031 b
692,3-Dihydro-1,1,5,6-tetramethyl-1H-indene II17:28.000:01.7MS1629-7.6710.023 ± 0.006 bc0.007 ± 0.010 c0.038 ± 0.020 ab0.056 ± 0.030 a0.016 ± 0.004 bc
703-Methylphenylacetylene14:33.000:01.3MS, LRI14811450.97.4380.012 ± 0.002 b0.016 ± 0.006 b0.013 ± 0.007 b0.032 ± 0.013 a0.028 ± 0.012 a
71Benzoic acid30:48.900:00.8S, MS, LRI>210024386.9520.269 ± 0.021 bc0.412 ± 0.064 a0.350 ± 0.047 a0.233 ± 0.107 c0.334 ± 0.111 ab
72Azulene19:34.000:01.3MS, LRI175117466.8910.240 ± 0.058 a0.181 ± 0.044 b0.165 ± 0.042 bc0.130 ± 0.039 c0.117 ± 0.039 c
73Trimethyl-tetrahydronaphthalene13:12.100:01.8MS1426-6.8300.007 ± 0.012 c0.002 ± 0.004 c0.056 ± 0.056 ab0.102 ± 0.070 a0.007 ± 0.008 c
74Benzeneacetaldehyde17:49.000:01.1S, MS, LRI165116486.8275.920 ± 1.513 c10.269 ± 2.174 a8.487 ± 2.065 ab5.884 ± 2.053 c6.501 ± 1.630 bc
75m-Methoxyanisole19:48.000:01.2MS, LRI176317616.7150.009 ± 0.013 c0.035 ± 0.021 b0.009 ± 0.011 c0.013 ± 0.013 bc0.070 ± 0.052 a
76Benzenoid (n.i.; m/z 115, 130, 129)16:37.200:01.4MS1581-5.7640.007 ± 0.003 b0.005 ± 0.004 b0.005 ± 0.004 b0.014 ± 0.005 a0.009 ± 0.003 ab
776-[1-(Hydroxymethyl)vinyl]-4,8a-dimethyl-1,2,4a,5,6,7,8,8a-octahydro-2-naphthalenol19:54.700:02.0MS1769-5.5870.010 ± 0.014 b0.010 ± 0.011 b0.009 ± 0.010 b0.041 ± 0.023 a0.013 ± 0.011 b
78Prehnitene14:40.000:01.5MS, LRI148614765.5160.198 ± 0.035 ab0.160 ± 0.052 bc0.249 ± 0.080 a0.124 ± 0.034 c0.124 ± 0.089 c
792-Methylnaphthalene22:15.000:01.3MS, LRI189418724.3210.021 ± 0.004 a0.015 ± 0.003 b0.014 ± 0.004 b0.015 ± 0.005 b0.012 ± 0.003 b
80meso-2,3-Diphenylbutane17:07.000:01.3MS1607-4.2910.025 ± 0.017 b0.050 ± 0.016 a0.037 ± 0.009 ab0.027 ± 0.010 b0.032 ± 0.007 ab
814-Ethylbenzaldehyde19:34.000:01.2MS, LRI175117474.1680.059 ± 0.010 ab0.067 ± 0.014 a0.060 ± 0.015 ab0.043 ± 0.010 c0.048 ± 0.008 bc
82Styrene09:27.400:05.0MS, LRI125612573.5782.067 ± 0.516 ab2.462 ± 0.859 a2.161 ± 0.275 ab1.701 ± 0.419 bc1.223 ± 0.083 c
83Ethyl o-methylbenzoate19:34.200:01.3MS1751-3.1480.039 ± 0.005 ab0.041 ± 0.005 a0.034 ± 0.005 abc0.028 ± 0.013 c0.027 ± 0.015 c
842,3-Dihydrobenzofuran16:46.000:01.2MS1588-3.1220.025 ± 0.011 b0.046 ± 0.014 a0.039 ± 0.013 ab0.029 ± 0.014 b0.029 ± 0.001 b
85Benzofuran15:01.000:01.1MS, LRI150014963.1210.040 ± 0.013 b0.061 ± 0.022 a0.047 ± 0.015 ab0.040 ± 0.013 b0.030 ± 0.005 b
86Benzonitrile17:00.000:01.0MS, LRI160015913.0410.033 ± 0.015 b0.064 ± 0.026 a0.052 ± 0.021 ab0.038 ± 0.016 b0.039 ± 0.005 ab
87α,α-Dimethylbenzenemethanol19:55.200:01.0MS, LRI176917702.9810.021 ± 0.009 b0.033 ± 0.018 b0.024 ± 0.008 b0.027 ± 0.007 b0.203 ± 0.309 a
88Methyl 2-(benzyloxy)propanoate23:18.000:01.3MS1949-2.9580.825 ± 0.861 a0.144 ± 0.151 b0.107 ± 0.138 b0.211 ± 0.456 b0.018 ± 0.017 b
89α-Methylstyrene11:10.800:01.3MS, LRI133613252.7270.006 ± 0.0070.014 ± 0.0060.015 ± 0.0070.017 ± 0.0080.118 ± 0.192
903-Ethylbenzaldehyde18:59.400:01.2MS, LRI172117322.6310.088 ± 0.0130.092 ± 0.0160.086 ± 0.0230.065 ± 0.0210.075 ± 0.004
913-Methylbenzofuran21:19.000:01.1MS1844-2.5940.027 ± 0.0060.046 ± 0.0120.034 ± 0.0160.032 ± 0.0140.034 ± 0.006
92Styralyl isobutyrate23:31.800:01.4MS1961-2.4620.065 ± 0.0220.191 ± 0.1210.166 ± 0.1150.149 ± 0.0690.097 ± 0.023
932’,5’-Dimethylcrotonophenone24:00.000:01.3MS1985-2.3620.045 ± 0.0170.040 ± 0.0290.026 ± 0.0190.040 ± 0.0110.010 ± 0.009
94Ethyl benzenepropanoate22:15.000:01.3MS, LRI189418922.3280.404 ± 0.2560.509 ± 0.3530.314 ± 0.1800.206 ± 0.0520.131 ± 0.079
951-Methylnapthalene21:40.000:01.3MS, LRI186318782.3190.017 ± 0.0050.016 ± 0.0070.014 ± 0.0030.011 ± 0.0030.010 ± 0.001
96Ethyl salicylate21:35.800:01.1S, MS, LRI185918372.2880.037 ± 0.0540.005 ± 0.0080.027 ± 0.0490.011 ± 0.0120.177 ± 0.296
97Methyl salicylate20:16.000:01.2S, MS, LRI178717892.1513.457 ± 1.5764.548 ± 6.3572.447 ± 1.4351.979 ± 0.98514.629 ± 21.656
982-Methylbenzaldehyde17:27.800:01.1MS, LRI162916222.1450.041 ± 0.0140.057 ± 0.0230.034 ± 0.0230.032 ± 0.0120.051 ± 0.025
99Durene13:16.000:01.5MS, LRI142914352.0380.085 ± 0.0330.084 ± 0.0400.080 ± 0.0270.056 ± 0.0340.034 ± 0.028
100Butylated hydroxytoluene22:43.000:01.5MS, LRI191919201.5580.314 ± 0.0730.351 ± 0.1630.295 ± 0.1070.228 ± 0.0670.210 ± 0.146
101Ethyl benzeneacetate20:30.000:01.2MS, LRI179917881.4741.334 ± 0.3103.173 ± 0.8632.503 ± 1.2453.294 ± 3.1863.112 ± 2.566
102p-Methoxyanisole19:34.200:01.2MS, LRI175117521.3090.153 ± 0.0410.184 ± 0.0740.141 ± 0.0440.197 ± 0.0520.191 ± 0.075
103Benzeneacetic acid32:45.200:00.8MS, LRI>210025191.2430.002 ± 0.0000.005 ± 0.0050.008 ± 0.0070.004 ± 0.0070.009 ± 0.013
104Benzyl alcohol22:01.000:00.9S, MS, LRI188118771.2430.914 ± 1.4132.007 ± 2.9530.468 ± 0.2430.354 ± 0.0790.565 ± 0.297
1052-Hydroxybenzeneacetic acid23:11.000:01.0MS1943-1.2380.003 ± 0.0080.008 ± 0.0040.003 ± 0.0030.005 ± 0.0010.005 ± 0.002
1062-Ethyl-m-xylene11:58.500:01.6MS, LRI137313721.2240.106 ± 0.0640.112 ± 0.0590.082 ± 0.0430.094 ± 0.0400.040 ± 0.035
107Benzaldehyde15:16.800:05.8S, MS, LRI151415091.0941.935 ± 0.9784.662 ± 6.4751.479 ± 0.3772.161 ± 0.5352.934 ± 2.144
1082-(1,1-Dimethylethyl)-1,4-dimethoxybenzene22:29.000:01.4MS, LRI190618700.9960.069 ± 0.0100.061 ± 0.0140.066 ± 0.0170.075 ± 0.0210.051 ± 0.044
109trans-1,2-Diphenylcyclobutane20:58.000:01.3MS1825-0.6740.003 ± 0.0020.003 ± 0.0020.004 ± 0.0070.002 ± 0.0030.000 ± 0.000
1103,3-Dimethoxy-1-phenylpropan-1-one09:56.800:05.6MS1278-0.5690.037 ± 0.0320.048 ± 0.0540.052 ± 0.0590.025 ± 0.0270.062 ± 0.031
111trans-Anethole21:12.000:01.3S, MS, LRI183718340.5020.423 ± 0.2230.449 ± 0.1990.390 ± 0.2130.395 ± 0.3090.613 ± 0.344
112cis-Anethole19:55.000:01.3S, MS, LRI176917800.3220.013 ± 0.0050.015 ± 0.0070.014 ± 0.0040.014 ± 0.0070.017 ± 0.010
1131,2-Dimethylbenzene07:41.000:05.1MS, LRI117611750.1760.468 ± 0.3330.412 ± 0.4020.503 ± 0.3550.356 ± 0.3120.432 ± 0.375
Hydrocarbons
114Pentadecane14:54.000:02.7S, MS, LRI149615001.6990.251 ± 0.0550.195 ± 0.0660.222 ± 0.1040.205 ± 0.0340.140 ± 0.045
1152,3,3-Trimethyl-cis-4-nonene10:42.000:01.6MS1313-1.5850.078 ± 0.0950.052 ± 0.0340.031 ± 0.0080.016 ± 0.0090.026 ± 0.031
116Hexadecane17:00.000:02.7S, MS, LRI160016001.3320.170 ± 0.0250.140 ± 0.0510.162 ± 0.0820.134 ± 0.0380.100 ± 0.031
117cis,trans-1,3,5-Octatriene08:08.400:00.7MS1196-1.0870.376 ± 0.1460.364 ± 0.1250.315 ± 0.1400.245 ± 0.1370.329 ± 0.029
1182,6,8-Trimethyl-trans-4-nonene11:13.500:02.5MS1338-0.4640.048 ± 0.0830.029 ± 0.0520.019 ± 0.0390.032 ± 0.0430.002 ± 0.002
Aldehydes
119Decanal14:54.000:01.5S, MS, LRI149614973.1490.068 ± 0.041 a0.068 ± 0.035 a0.051 ± 0.040 ab0.014 ±0.011 b0.060 ± 0.008 ab
120trans-2-Decenal17:49.000:01.4MS, LRI165116472.5530.116 ± 0.0300.131 ± 0.0430.109 ± 0.0300.071 ± 0.0340.094 ± 0.065
121trans-2-Octenal13:25.300:01.3S, MS, LRI143514322.3070.249 ± 0.3010.017 ± 0.0230.120 ± 0.0380.105 ± 0.0920.021 ± 0.020
122Undecanal17:07.000:01.5S, MS, LRI160716061.9670.061 ± 0.0200.053 ± 0.0160.040 ± 0.0100.041 ± 0.0100.051 ± 0.031
123Dodecanal19:06.000:01.6MS, LRI172717221.4710.066 ± 0.0150.062 ± 0.0190.050 ± 0.0140.056 ± 0.0220.043 ± 0.011
1243,3-Dimethyl-2-oxobutanal11:24.800:01.9MS1347-0.2790.108 ± 0.0910.158 ± 0.1780.106 ± 0.1040.226 ± 0.5220.078 ± 0.082
125Nonanal12:40.600:01.5S, MS, LRI140514040.20610.699 ± 7.68912.183 ± 7.41011.470 ± 8.4818.722 ± 6.66810.800 ± 6.868
Ketones
1261,4,7,10,13-Pentaoxacyclononadecane-14,19-dione27:35.000:01.3MS>2100-9.7210.027 ± 0.038 b0.013 ± 0.014 b0.005 ± 0.003 b0.022 ± 0.020 b0.107 ± 0.038 a
127α-Isophorone16:46.000:01.3S, MS, LRI158815937.3800.116 ± 0.022 a0.101 ± 0.032 a0.047 ± 0.024 b0.093 ± 0.021 a0.093 ± 0.029 a
128Cyclohexylideneacetone17:35.000:01.8MS1637-6.9670.097 ± 0.097 c0.671 ± 0.428 b0.424 ± 0.259 bc0.546 ± 0.254 b1.194 ± 0.691 a
129Acetophenone17:56.000:01.1S, MS, LRI165916606.0360.297 ± 0.048 cd0.557 ± 0.116 a0.415 ± 0.107 bc0.271 ± 0.078 d0.487 ± 0.348 ab
1302-Undecanone16:53.400:01.5MS, LRI159415984.0270.755 ± 0.471 a0.320 ± 0.097 b0.294 ± 0.104 b0.347 ± 0.246 b0.215 ± 0.162 b
1314,4-(Ethylenedioxy)-2-pentanone19:20.000:01.1MS1739-3.7870.166 ± 0.053 ab0.245 ± 0.111 a0.145 ± 0.089 b0.102 ± 0.020 b0.102 ± 0.067 b
132Unsaturated diketone
(n.i.; m/z 43, 99, 71)
14:26.000:01.1MS1477-3.2130.137 ± 0.151 b0.361 ± 0.123 a0.269 ± 0.095 ab0.170 ± 0.174 b0.150 ± 0.114 b
1333-Undecanone16:20.300:01.6MS, LRI156715713.1760.455 ± 0.440 a0.075 ± 0.051 b0.081 ± 0.040 b0.123 ± 0.265 b0.025 ± 0.021 b
1343-Tridecanone20:16.000:01.7MS, LRI178717553.1200.036 ± 0.023 a0.010 ± 0.008 b0.008 ± 0.009 b0.018 ± 0.026 ab0.006 ± 0.005 b
1351b,5,5,6a-Tetramethyl-octahydro-1-oxa-cyclopropa[a]inden-6-one18:31.000:02.1MS1695-2.5700.016 ± 0.0190.042 ± 0.0380.047 ± 0.0540.088 ± 0.0680.123 ± 0.138
1363-(Acetoxy)-4-methyl-2-pentanone14:07.300:01.3MS1464-2.5280.012 ± 0.0210.055 ± 0.0550.073 ± 0.0570.025 ± 0.0250.031 ± 0.027
137trans-5-Methyl-2-(1-methylethyl)-cyclohexanone14:08.100:01.6MS, LRI146414732.2820.041 ± 0.0450.312 ± 0.6570.077 ± 0.0500.058 ± 0.0301.167 ± 1.900
1384-(1,1-Dimethylethyl)-cyclohexanone17:35.000:01.5MS, LRI163716452.0320.057 ± 0.0950.124 ± 0.1220.025 ± 0.0330.011 ± 0.0110.092 ± 0.125
1391-Phenyl-1-propanone19:20.200:01.2MS, LRI173917441.7450.019 ± 0.0180.030 ± 0.0130.015 ± 0.0070.015 ± 0.0040.021 ± 0.005
1402-Nonanone12:34.000:01.4S, MS, LRI140114021.68910.162 ± 9.3464.449 ± 3.7376.475 ± 7.1233.195 ± 1.1032.225 ± 2.037
1412H-Pyran-2,6(3H)-dione24:10.500:00.8MS1995-1.5990.485 ± 0.1900.661 ± 0.3260.564 ± 0.2260.397 ± 0.1380.394 ± 0.069
1422-Heptanone07:46.500:05.2S, MS, LRI118011801.4450.692 ± 0.4060.605 ± 0.4161.117 ± 1.1970.301 ± 0.2650.502 ± 0.401
1432,2-Dimethyl-1,3-dioxane-4,6-dione18:17.000:01.1MS1681-1.1670.032 ± 0.0140.022 ± 0.0210.037 ± 0.0100.035 ± 0.0060.026 ± 0.023
1442-Decanone14:47.000:01.5MS, LRI149114910.9900.502 ± 0.2980.457 ± 0.1280.377 ± 0.1750.432 ± 0.1590.255 ± 0.107
145Acetoin10:07.900:00.8S, MS, LRI128712870.7320.054 ± 0.0170.071 ± 0.0480.061 ± 0.0260.093 ± 0.0830.058 ± 0.024
1462,6-Di(tert-butyl)-4-hydroxy-4-methyl-2,5-cyclohexadien-1-one25:45.000:01.1MS, LRI207720940.6940.009 ± 0.0030.010 ± 0.0060.010 ± 0.0070.014 ± 0.0110.013 ± 0.008
1472-Cyclohexene-1,4-dione19:33.700:01.0MS1751-0.6690.006 ± 0.0100.027 ± 0.0310.093 ± 0.2140.031 ± 0.0600.055 ± 0.078
1483,4-Dihydroxy-cyclobutene-1,2-dione18:10.000:01.1MS1673-0.4090.089 ± 0.0310.075 ± 0.0370.060 ± 0.0530.078 ± 0.0590.073 ± 0.022
1495-Methyl-5-hepten-2-one11:24.000:01.3MS, LRI134613430.2150.147 ± 0.1600.113 ± 0.0850.125 ± 0.0230.116 ± 0.1120.170 ± 0.130
Alcohols
1504-Methyl-1-heptanol12:42.100:01.6MS, LRI1406140923.0560.313 ± 0.161 b0.115 ± 0.060 c0.056 ± 0.047 c0.033 ± 0.031 c0.638 ± 0.209 a
151cis-3-Hexen-1-ol12:20.000:00.9S, MS, LRI1390138615.6117.191 ± 2.621 c15.988 ± 3.409 a11.216 ± 4.880 b3.383 ± 0.607 d5.727 ± 3.198 cd
1522-Heptanol10:56.000:01.0S, MS, LRI132413207.2900.943 ± 0.327 bc1.984 ± 0.923 a1.044 ± 0.321 bc0.601 ± 0.251 c1.571 ± 0.480 ab
1532-Penten-1-ol10:56.200:00.8MS, LRI132413215.5880.044 ± 0.021 a0.045 ± 0.014 a0.044 ± 0.017 a0.012 ± 0.002 b0.040 ± 0.012 a
1543-Octanol12:36.400:01.1MS, LRI140214065.1080.082 ± 0.068 b0.185 ± 0.070 a0.062 ± 0.053 b0.072 ± 0.050 b0.054 ± 0.054 b
1551-Undecanol21:49.400:01.1MS, LRI187118835.0520.004 ± 0.006 b0.023 ± 0.015 a0.007 ± 0.012 b0.022 ± 0.010 a0.022 ± 0.007 a
156Alcohol (n.i.; m/z 69, 41, 84)15:02.300:01.0MS1501-4.2780.491 ± 0.778 bc0.848 ± 0.393 ab1.178 ± 0.637 a0.192 ± 0.081 c0.079 ± 0.036 c
1571-Octen-3-ol13:51.000:01.0S, MS, LRI145314523.8323.494 ± 2.869 b5.797 ± 1.668 a2.467 ± 0.654 b2.597 ± 1.254 b3.015 ± 1.251 b
1582-Decanol17:20.300:01.1MS, LRI162116213.0580.023 ± 0.011 b0.047 ± 0.025 b0.021 ± 0.015 b0.024 ± 0.013 b0.212 ± 0.318 a
1592,3-Butanediol II16:25.200:00.8S, MS, LRI157115672.7081.964 ± 0.4502.601 ± 0.5802.586 ± 1.2761.421 ± 0.7802.007 ± 0.180
1604-Hepten-1-ol14:54.500:00.9MS, LRI149615022.6350.105 ± 0.0650.093 ± 0.0900.125 ± 0.0600.044 ± 0.0250.172 ± 0.057
1616-Methyl-5-hepten-2-ol14:05.800:01.0S, MS, LRI146314662.4650.034 ± 0.0060.050 ± 0.0150.042 ± 0.0130.037 ± 0.0110.030 ± 0.012
1623-Methyl-1-pentanol11:03.700:00.9S, MS, LRI133013322.3875.790 ± 1.4215.799 ± 1.5046.404 ± 2.9373.575 ± 1.8204.453 ± 0.203
1632,3-Butanediol I15:36.000:02.1S, MS, LRI153015422.2913.399 ± 1.7794.339 ± 1.8123.931 ± 2.2791.744 ± 1.0273.597 ± 0.875
164Alcohol (n.i.; m/z 45, 55, 43)14:17.600:01.0MS1471-2.1570.137 ± 0.1200.012 ± 0.0220.096 ± 0.1140.093 ± 0.0420.054 ± 0.043
1651-Decanol20:02.000:01.1S, MS, LRI177517782.0860.710 ± 0.2190.625 ± 0.1000.597 ± 0.1380.812 ± 0.0970.642 ± 0.209
1663,5-Dimethyl-4-heptanol19:35.200:00.8MS1752-2.0330.043 ± 0.0310.104 ± 0.0630.098 ± 0.0580.053 ± 0.0560.068 ± 0.002
1672-Ethylhexanol14:40.000:01.0MS, LRI148614841.7564.569 ± 0.7354.664 ± 0.5374.826 ± 0.4814.169 ± 0.4654.122 ± 0.201
1688-Methyl-1,8-nonanediol10:56.200:01.1MS1324-1.4540.123 ± 0.0790.199 ± 0.0840.223 ± 0.1220.206 ± 0.0840.133 ± 0.116
1693,4-Nonadienol19:48.000:01.0MS, LRI176317541.4450.017 ± 0.0250.016 ± 0.0130.007 ± 0.0050.003 ± 0.0020.005 ± 0.001
1701-Pentanol08:53.500:00.5S, MS, LRI123112421.2720.082 ± 0.0910.135 ± 0.1000.112 ± 0.0760.058 ± 0.0600.039 ± 0.014
1713-Ethyl-4-octanol18:24.900:01.3MS1689-1.2250.364 ± 0.2080.304 ± 0.1890.479 ± 0.1980.471 ± 0.1080.331 ± 0.229
1722-Octen-1-ol17:14.000:01.0S, MS, LRI161516221.1150.151 ± 0.2060.114 ± 0.0600.077 ± 0.0330.041 ± 0.0150.057 ± 0.020
1732-Undecanol19:13.000:01.2MS, LRI173317380.8410.173 ± 0.2180.330 ± 0.1840.226 ± 0.1370.241 ± 0.0940.278 ± 0.205
1744-Methyl-1-pentanol10:49.000:00.9MS, LRI131913190.8192.297 ± 1.0832.626 ± 0.8003.318 ± 2.0102.130 ± 2.1011.782 ± 0.130
1754-Ethyl-3-octanol15:08.000:01.2MS1506-0.7210.400 ± 0.0590.374 ± 0.0670.430 ± 0.2320.389 ± 0.2020.245 ± 0.213
1762-Nonanol15:15.000:01.1S, MS, LRI151215180.7150.512 ± 0.1870.581 ± 0.3440.429 ± 0.1270.398 ± 0.1690.468 ± 0.272
1771-Nonanol18:03.300:01.0S, MS, LRI166616610.5801.420 ± 1.6350.776 ± 0.5382.515 ± 3.6791.557 ± 2.2681.018 ± 1.218
1781-Heptanol13:58.200:00.9S, MS, LRI145814570.5601.238 ± 0.7211.394 ± 0.6571.120 ± 0.9040.875 ± 0.3811.183 ± 0.341
1792-Methyl-1-pentanol10:28.500:00.9S, MS, LRI130312970.2290.262 ± 0.3260.200 ± 0.2480.323 ± 0.4340.312 ± 0.1450.199 ± 0.124
180trans-4-tert-Butylcyclohexanol19:43.300:01.1MS, LRI175917300.1890.136 ± 0.3260.149 ± 0.2830.267 ± 0.4470.204 ± 0.1810.216 ± 0.332
1812-Octanol (internal standard)13:09.000:01.0S, MS, LRI14241418 40.000 ± 0.00040.000 ± 0.00040.000 ± 0.00040.000 ± 0.00040.000 ± 0.000
Acids
182Propionic acid15:43.000:00.7S, MS, LRI153615404.3651.294 ± 0.324 ab1.631 ± 0.472 a1.159 ± 0.294 b0.946 ± 0.158 b0.991 ± 0.348 b
183Acid (n.i.; m/z 74, 45, 73)14:33.000:01.1MS, LRI148114914.0410.018 ± 0.015 b0.038 ± 0.020 a0.016 ± 0.013 b0.009 ± 0.006 b0.013 ± 0.008 b
184trans-2-Hexenoic acid23:39.000:00.8MS, LRI196719673.6510.081 ± 0.047 b0.205 ± 0.094 a0.159 ± 0.107 ab0.083 ± 0.045 b0.266 ± 0.213 a
185Nonanoic acid26:51.500:00.8S, MS, LRI>210021193.6410.096 ± 0.049 b0.169 ± 0.095 b0.094 ± 0.043 b0.166 ± 0.156 b0.313 ± 0.078 a
186trans-3-Hexenoic acid22:49.800:00.8MS, LRI192419293.1900.031 ± 0.033 a0.006 ± 0.005 b0.007 ± 0.003 b0.005 ± 0.003 b0.011 ± 0.005 ab
187Formic acid15:10.400:00.7MS, LRI150815012.5261.442 ± 0.4652.092 ± 0.8491.523 ± 0.3931.176 ± 0.5071.306 ± 0.515
1883,5,5-Trimethylhexanoic acid23:46.000:00.8MS1973-2.1940.330 ± 0.0530.347 ± 0.1150.370 ± 0.1130.437 ± 0.0940.479 ± 0.101
1892-Propenoic acid17:42.700:00.7MS1645-2.1180.245 ± 0.0730.262 ± 0.1010.266 ± 0.0420.214 ± 0.0390.146 ± 0.055
190Heptanoic acid23:22.200:00.8S, MS, LRI195319551.4230.071 ± 0.0220.075 ± 0.0440.083 ± 0.0760.060 ± 0.0210.152 ± 0.139
1912-Decenoic acid15:43.700:00.8MS, LRI153615401.2890.021 ± 0.0220.012 ± 0.0240.005 ± 0.0100.025 ± 0.0110.022 ± 0.025
192Pentanoic acid19:34.000:00.8S, MS, LRI175117511.0060.408 ± 0.0740.490 ± 0.1470.395 ± 0.0740.394 ± 0.0630.513 ± 0.338
193Isobutyric acid16:18.000:00.7S, MS, LRI156515550.8323.347 ± 0.9884.725 ± 1.5184.212 ± 2.1073.795 ± 1.7573.200 ± 2.305
194trans,trans-2,4-Hexadienoic acid26:51.600:00.8MS, LRI>210021500.7530.188 ± 0.1450.053 ± 0.06618.360 ± 48.1724.350 ± 10.5632.236 ± 3.744
195Isovaleric acid18:18.800:00.7S, MS, LRI168316800.7455.833 ± 1.4823.926 ± 3.9165.923 ± 2.8426.130 ± 2.2085.222 ± 2.990
1962-Ethylhexanoic acid23:18.000:00.8MS, LRI194919600.5680.602 ± 1.2560.232 ± 0.2240.312 ± 0.2710.144 ± 0.0610.151 ± 0.019
197Butyric acid17:28.000:00.7S, MS, LRI162916260.54618.241 ± 2.60819.305 ± 5.11817.622 ± 2.37216.638 ± 0.90518.144 ± 6.443
Esters
198Methyl octanoate12:34.000:01.5MS, LRI1401140412.56851.242 ± 14.675 a14.588 ± 8.497 b25.349 ± 13.750 b21.407 ± 4.375 b12.261 ± 13.962 b
199cis-3-Hexen-1-yl acetate10:56.000:01.3MS, LRI1324130012.06820.041 ± 8.968 b39.339 ± 11.050 a22.891 ± 14.489 b6.372 ± 2.659 c4.576 ± 3.341 c
200Methyl hexanoate07:51.100:05.4S, MS, LRI1183118810.4556.240 ± 2.416 a2.417 ± 1.319 b3.001 ± 1.098 b2.216 ± 0.469 b1.222 ± 1.089 b
201Butyl hexanoate13:05.200:01.7S, MS, LRI1422142810.4230.059 ± 0.026 a0.015 ± 0.014 b0.017 ± 0.016 b0.015 ± 0.008 b0.008 ± 0.007 b
202Isoamyl hexanoate14:05.000:01.8S, MS, LRI146214589.8887.130 ± 1.573 a1.804 ± 1.100 c3.941 ± 3.105 b3.323 ± 0.756 bc1.537 ± 1.597 c
203Ethyl 3-nonenoate16:44.200:01.6MS1587-7.4810.067 ± 0.040 a0.021 ± 0.020 b0.011 ± 0.005 b0.017 ± 0.015 b0.006 ± 0.007 b
204Hexanodibutyrin12:20.000:01.7MS1390-7.4720.444 ± 0.181 a0.571 ± 0.245 a0.180 ± 0.173 b0.179 ± 0.103 b0.705 ± 0.336 a
205Methyl decanoate16:53.000:01.6MS, LRI159415937.1311.375 ± 0.608 a0.552 ± 0.226 b0.741 ± 0.248 b0.599 ± 0.132 b0.426 ± 0.345 b
206Phenethyl formate20:29.800:01.1MS, LRI179918066.7180.088 ± 0.035 c0.211 ± 0.070 a0.156 ± 0.046 b0.119 ± 0.043 bc0.112 ± 0.032 bc
207Ethyl trans-4-octenoate15:15.000:01.5MS1512-6.2560.031 ± 0.003 a0.017 ± 0.009 b0.023 ± 0.006 b0.016 ± 0.007 b0.017 ± 0.006 b
208Ethyl methyl succinate17:36.400:01.1MS, LRI163816316.0260.347 ± 0.156 a0.306 ± 0.126 a0.242 ± 0.078 a0.079 ± 0.067 b0.254 ± 0.070 a
209Octyl formate16:04.200:01.0MS, LRI155315605.9096.604 ± 0.947 b6.267 ± 1.160 b6.531 ± 1.465 b9.177 ± 1.345 a6.050 ± 2.280 b
210trans-3-Hexen-1-yl acetate10:42.000:01.3MS, LRI131313165.67520.322 ± 7.276 a10.073 ± 8.187 b5.922 ± 3.176 b10.530 ± 4.255 b7.388 ± 8.444 b
211Ethyl hexadecanoate30:13.700:01.5MS, LRI>210022615.5860.560 ± 0.414 a0.051 ± 0.082 b0.119 ± 0.222 b0.091 ± 0.149 b0.052 ± 0.064 b
212Ethyl 2-hydroxy-4-methylpentanoate15:49.300:01.0MS1541-5.5430.380 ± 0.161 c0.829 ± 0.571 bc1.875 ± 0.999 a1.625 ± 1.112 ab0.266 ± 0.231 c
2132-Phenylethyl isobutyrate22:45.700:01.1MS, LRI192119165.4193.788 ± 1.880 a1.824 ± 1.708 b1.421 ± 1.243 b0.816 ± 0.397 b0.769 ± 0.245 b
214Propyl hexanoate10:56.200:01.7MS, LRI132413194.9820.760 ± 0.330 a0.339 ± 0.286 b0.286 ± 0.227 b0.379 ± 0.143 b0.170 ± 0.180 b
215Diethyl glutarate20:23.000:01.2MS, LRI179317804.7060.028 ± 0.012 c0.105 ± 0.061 a0.064 ± 0.043 bc0.059 ± 0.013 bc0.092 ± 0.020 ab
2163-Ethoxypropyl acetate11:52.000:01.2MS1368-4.4230.754 ± 0.514 b2.176 ± 1.442 a0.638 ± 0.941 b0.442 ± 0.365 b0.454 ± 0.707 b
217Isoamyl octanoate18:06.100:01.9MS, LRI166916574.0334.133 ± 0.747 a2.340 ± 0.822 b3.155 ± 1.362 ab3.789 ± 0.950 a2.125 ± 1.656 b
218Ethyl heptanoate11:17.000:01.6MS, LRI134113423.7623.007 ± 1.131 a1.591 ± 1.355 b1.701 ± 0.709 b1.498 ± 0.355 b0.938 ± 1.126 b
219Ethyl pyruvate09:53.400:01.0MS, LRI127612763.7171.711 ± 0.693 b3.025 ± 0.908 a1.931 ± 1.095 b1.496 ± 0.650 b1.685 ± 0.421 b
220Isoamyl decanoate21:58.000:01.9MS, LRI187918713.6850.039 ± 0.093 b0.191 ± 0.114 ab0.180 ± 0.153 ab0.239 ± 0.042 ab0.178 ± 0.115 ab
221Propyl octanoate15:22.000:01.8MS, LRI151815043.6370.893 ± 0.277 a0.428 ± 0.431 b0.384 ± 0.269 b0.577 ± 0.297 ab0.270 ± 0.261 b
222Ethyl 4-pyrazolecarboxylate14:33.000:01.1MS1481-3.2910.016 ± 0.002 b0.026 ± 0.011 a0.014 ± 0.010 b0.012 ± 0.008 b0.010 ± 0.009 b
223Methyl 2-methyllactate16:39.000:01.2MS1582-3.0490.116 ± 0.015 a0.088 ± 0.013 bc0.102 ± 0.017 ab0.109 ± 0.024 ab0.068 ± 0.059 c
2243-Hydroxy-2,4,4-trimethylpentyl isobutyrate21:54.700:01.2MS1876-3.0460.089 ± 0.019 b0.191 ± 0.051 a0.124 ± 0.108 b0.104 ± 0.035 b0.112 ± 0.044 b
225Isobutyl hexanoate11:45.000:01.8MS, LRI136213572.9191.039 ± 0.567 a0.392 ± 0.297 b0.767 ± 0.580 ab0.595 ± 0.202 ab0.259 ± 0.272 b
226Hydroxyl acid ester
(n.i.; m/z 143, 115, 75)
17:49.000:01.3MS1651-2.6800.005 ± 0.0050.012 ± 0.0050.009 ± 0.0060.007 ± 0.0040.014 ± 0.005
227Ethyl 4-hydroxybutyrate20:47.700:00.9MS, LRI181518192.5180.955 ± 0.7171.134 ± 0.6771.141 ± 0.6950.315 ± 0.1710.536 ± 0.197
228Octyl acetate14:24.400:01.5MS, LRI147514752.4540.408 ± 0.8571.601 ± 1.1411.423 ± 1.4163.153 ± 1.6396.579 ± 10.545
2293-Methyl-3-buten-1-yl acetate08:07.800:01.2MS, LRI119611902.4480.072 ± 0.0370.066 ± 0.0360.032 ± 0.0280.049 ± 0.0210.025 ± 0.026
230Ethyl 2-octenoate16:04.000:01.5MS, LRI155315572.3860.031 ± 0.0050.027 ± 0.0090.024 ± 0.0080.019 ± 0.0030.027 ± 0.015
231Ethyl undecanoate18:45.200:01.0MS, LRI170917252.3520.539 ± 0.7490.198 ± 0.1110.319 ± 0.3911.006 ± 0.7770.166 ± 0.169
232Pentyl acetate07:36.100:01.3S, MS, LRI117211612.3340.123 ± 0.1990.088 ± 0.2040.037 ± 0.0560.282 ± 0.1740.053 ± 0.057
233Isobutyl octanoate15:57.700:01.9MS, LRI154815512.2260.217 ± 0.0710.119 ± 0.0830.185 ± 0.1140.213 ± 0.1090.074 ± 0.069
234Ethyl 4-hexenoate10:21.300:01.4MS, LRI129712922.2117.705 ± 10.2362.044 ± 1.3641.287 ± 0.6500.784 ± 0.4581.363 ± 1.374
235Ethyl trans-2-butenoate07:19.000:05.0MS, LRI115911612.1278.551 ± 4.3825.204 ± 3.1857.463 ± 2.8414.376 ± 2.7104.293 ± 2.995
236trans,trans-2,4-Octadien-1-yl acetate16:18.000:01.4MS1565-1.9560.017 ± 0.0170.024 ± 0.0180.006 ± 0.0100.007 ± 0.0090.017 ± 0.017
2372-Phenylethyl octanoate32:17.500:01.3MS, LRI>210023731.7620.032 ± 0.0360.006 ± 0.0050.009 ± 0.0040.024 ± 0.0300.004 ± 0.004
238Isoamyl butyrate09:45.800:01.7S, MS, LRI127012661.7562.573 ± 0.9192.131 ± 0.9572.055 ± 0.8921.912 ± 0.3581.089 ± 1.161
239Di-isobutyl acetate20:02.000:01.2MS1775-1.7240.206 ± 0.0650.243 ± 0.2110.139 ± 0.1060.112 ± 0.0370.094 ± 0.032
2403-Methylheptyl acetate12:26.500:01.6MS1395-1.6650.367 ± 0.3470.236 ± 0.2160.182 ± 0.0860.112 ± 0.0500.124 ± 0.077
241Diethyl malonate16:32.000:01.1MS, LRI157715741.6480.174 ± 0.0520.188 ± 0.0790.148 ± 0.0500.126 ± 0.0330.197 ± 0.034
242Heptyl acetate12:13.400:01.5MS, LRI138513851.4870.236 ± 0.1330.249 ± 0.1790.151 ± 0.0910.120 ± 0.0440.143 ± 0.145
243Ethyl hydrogen succinate30:16.200:00.8MS, LRI>210023501.4433.279 ± 0.9207.386 ± 6.5735.875 ± 1.7854.985 ± 2.4704.242 ± 1.226
244Methyl 2-isopropoxypropanoate20:30.000:01.3MS1799-1.2880.030 ± 0.0420.076 ± 0.0360.061 ± 0.0430.065 ± 0.0450.053 ± 0.047
245Vinyl decanoate19:27.200:01.4MS1745-1.2580.224 ± 0.3570.086 ± 0.0650.044 ± 0.0380.038 ± 0.0340.130 ± 0.062
246Diethyl malate25:29.400:00.9MS, LRI206320651.2100.227 ± 0.1440.462 ± 0.5020.399 ± 0.2200.360 ± 0.2310.629 ± 0.235
247trans-Penten-1-yl acetate08:50.000:01.2MS1228-1.1320.050 ± 0.0490.039 ± 0.0490.024 ± 0.0310.011 ± 0.0110.024 ± 0.023
248Phenylmethyl acetate19:27.000:01.2MS, LRI174517471.1190.042 ± 0.0260.211 ± 0.3940.035 ± 0.0180.046 ± 0.0180.054 ± 0.021
249Ethyl 3-hydroxybutyrate15:15.500:00.9MS, LRI151215121.0450.398 ± 0.2780.407 ± 0.2020.430 ± 0.1950.233 ± 0.1570.430 ± 0.093
250Isoamyl propanoate07:56.800:01.5MS, LRI118811881.0170.638 ± 0.2640.677 ± 0.4360.740 ± 0.4900.543 ± 0.3410.250 ± 0.186
251Ethyl hydroxyacetate13:09.000:00.8MS, LRI142414360.9870.032 ± 0.0450.097 ± 0.0790.058 ± 0.0760.085 ± 0.1440.163 ± 0.215
252Ethyl nonanoate15:43.000:01.7MS, LRI153615350.9281.843 ± 0.5030.984 ± 0.3940.971 ± 0.3452.321 ± 3.3551.116 ± 0.807
2532-(1,1-Dimethylethyl)-cyclohexen-1-yl acetate16:11.000:01.8MS1559-0.8480.046 ± 0.0260.024 ± 0.0150.045 ± 0.0310.040 ± 0.0320.034 ± 0.004
254Ethyl 2-hydroxy-3-phenylpropanoate29:11.100:01.0MS, LRI>210022730.8460.001 ± 0.0010.001 ± 0.0010.009 ± 0.0190.007 ± 0.0140.001 ± 0.000
255Ethyl 3-methylbutylbutanedioate22:29.700:01.3MS, LRI190719070.8352.315 ± 0.8063.353 ± 2.3242.743 ± 1.8142.843 ± 0.9081.639 ± 0.545
256Ethyl 9-decenoate18:45.000:01.6S, MS, LRI170817080.8010.133 ± 0.1890.177 ± 0.2270.280 ± 0.3470.101 ± 0.0860.067 ± 0.058
257Ethyl 3-ethoxy-trans-2-propenoate15:43.000:01.2MS1536-0.7851.418 ± 0.0961.363 ± 0.2051.480 ± 0.1361.542 ± 0.3171.360 ± 0.353
258Butyl ethyl succinate20:37.000:01.3MS, LRI180618200.7760.245 ± 0.1120.295 ± 0.1950.294 ± 0.1820.220 ± 0.1390.136 ± 0.063
259Ethyl 2,4-hexadienoate I14:35.000:01.3MS, LRI148315010.6730.033 ± 0.0340.019 ± 0.0110.869 ± 2.2690.343 ± 0.8550.097 ± 0.153
260Ethyl 2,4-hexadienoate II15:08.000:01.3MS, LRI150615010.6450.290 ± 0.3280.038 ± 0.0166.200 ± 16.2893.473 ± 8.6850.353 ± 0.515
261Isobutyl acetate04:23.800:04.7S, MS, LRI101510090.5310.726 ± 0.3710.774 ± 0.2800.728 ± 0.4350.534 ± 0.1750.658 ± 0.405
2622-Phenylethyl isovalerate24:00.000:01.4MS, LRI198519880.5300.015 ± 0.0120.014 ± 0.0140.013 ± 0.0100.020 ± 0.0060.011 ± 0.010
263Methyl 2-hydroxybutanoate11:45.000:01.1MS, LRI136213820.5290.274 ± 0.0560.217 ± 0.1550.208 ± 0.1560.280 ± 0.0400.225 ± 0.197
264Isopropyl lactate15:36.000:01.6MS1530-0.5120.032 ± 0.0070.027 ± 0.0040.029 ± 0.0160.026 ± 0.0070.023 ± 0.024
265Ethyl cis-4-decenoate18:17.400:01.6MS, LRI168116800.5100.017 ± 0.0190.012 ± 0.0100.008 ± 0.0140.015 ± 0.0110.011 ± 0.009
266Ethyl cis-4-octenoate14:39.600:01.5MS1486-0.5030.127 ± 0.0730.094 ± 0.0540.123 ± 0.0530.098 ± 0.0150.101 ± 0.094
267Ethyl 2-hexenoate11:31.700:01.5S, MS, LRI135213570.4691.626 ± 0.9841.864 ± 0.7592.107 ± 1.2131.408 ± 0.8061.721 ± 1.542
268Isoamyl lactate16:18.000:01.0MS, LRI156515720.3760.449 ± 0.3040.829 ± 1.0620.597 ± 0.3800.703 ± 0.5810.596 ± 0.341
269Ethyl 2-propynoate09:11.000:01.8MS1244-0.3684.550 ± 1.0654.324 ± 1.4444.768 ± 1.5044.322 ± 1.5653.562 ± 2.475
270Diethyl fumarate17:56.000:01.2MS, LRI165916600.1550.055 ± 0.0270.047 ± 0.0180.048 ± 0.0310.050 ± 0.0140.045 ± 0.014
Volatile phenols
2712-Methoxyphenol21:47.000:00.9MS, LRI186918695.0840.023 ± 0.016 b0.052 ± 0.034 a0.019 ± 0.011 b0.010 ± 0.001 b0.011 ± 0.003 b
2724-Vinylguaiacol27:33.500:00.9S, MS, LRI>210021682.9700.563 ± 0.266 ab0.762 ± 0.426 a0.373 ± 0.170 b0.377 ± 0.330 b0.163 ± 0.069 b
273Phenol24:14.000:00.8S, MS, LRI199819951.6070.701 ± 0.0490.856 ± 0.1310.804 ± 0.3090.601 ± 0.1300.886 ± 0.541
2744-Ethylguaiacol24:44.700:01.0S, MS, LRI202420241.5140.011 ± 0.0200.024 ± 0.0340.004 ± 0.0040.002 ± 0.0050.003 ± 0.003
2752,4-Bis(1,1-dimethylethyl)phenol29:01.000:01.0MS, LRI>210022701.3280.923 ± 0.4170.821 ± 0.2471.133 ± 0.5830.667 ± 0.2800.810 ± 0.189
Furanoids and lactones
2763-Methyl-2(5H)-furanone19:13.300:01.0MS, LRI173317267.7760.029 ± 0.012 a0.024 ± 0.011 ab0.017 ± 0.009 b0.004 ± 0.004 c0.017 ± 0.006 ab
277Acetylfuran15:01.200:01.0MS, LRI150115014.9580.092 ± 0.054 b0.416 ± 0.326 a0.201 ± 0.104 b0.086 ± 0.040 b0.092 ± 0.031 b
278γ-Butyrolactone17:28.000:01.0MS, LRI162916264.4913.839 ± 1.256 a4.284 ± 1.527 a4.055 ± 0.852 a1.918 ± 1.271 b2.661 ± 0.844 ab
2792-(5-Methyl-5-vinyltetrahydro-2-furanyl)-2-propanol14:16.100:01.2MS1470-4.2930.050 ± 0.089 b0.106 ± 0.063 b0.053 ± 0.063 b0.100 ± 0.084 b0.305 ± 0.233 a
280γ-Nonalactone24:42.600:01.2S, MS, LRI202220183.9090.037 ± 0.072 c0.311 ± 0.222 a0.152 ± 0.123 bc0.200 ± 0.100 ab0.191 ± 0.089 abc
281Lactone (n.i.; m/z 85, 57, 100)23:39.000:01.1MS1967-2.4500.057 ± 0.0590.013 ± 0.0140.039 ± 0.0370.010 ± 0.0060.009 ± 0.001
282Pantolactone24:42.000:00.8MS, LRI202220292.2200.091 ± 0.0180.184 ± 0.0750.174 ± 0.1010.156 ± 0.0670.123 ± 0.046
283Furfuryl ether10:14.000:01.1MS1292-2.1380.159 ± 0.1870.242 ± 0.1170.245 ± 0.1000.091 ± 0.0330.116 ± 0.071
284Furfural14:05.200:00.9S, MS, LRI146214602.0871.122 ± 0.38116.951 ± 26.8402.258 ± 1.0440.857 ± 0.1681.010 ± 0.306
285Ethyl 2-furoate17:21.000:01.1MS, LRI162216241.8234.805 ± 1.2887.089 ± 2.5134.929 ± 2.1195.484 ± 1.3754.786 ± 1.742
286γ-Octalactone22:49.800:01.1S, MS, LRI192419231.7220.533 ± 0.2080.907 ± 0.3090.708 ± 0.3250.723 ± 0.2990.730 ± 0.048
2872(5H)-furanone19:59.400:00.9S, MS, LRI177317871.2660.079 ± 0.0130.151 ± 0.1720.078 ± 0.0130.060 ± 0.0100.079 ± 0.046
2885-Methyl-2-furfural16:25.800:01.0S, MS, LRI157115701.2630.014 ± 0.0141.971 ± 4.2780.055 ± 0.0530.033 ± 0.0130.027 ± 0.033
289Lactone (n.i.; m/z 99, 71, 87)23:41.800:01.2MS1970-1.2060.012 ± 0.0220.121 ± 0.2230.022 ± 0.0360.025 ± 0.0220.040 ± 0.034
290γ-Hydroxymethyl-γ-butyrolactone28:33.000:00.9MS>2100-0.7251.594 ± 1.0451.857 ± 1.1702.753 ± 1.8132.442 ± 1.9121.735 ± 1.520
2915-Ethoxydihydro-2(3H)-furanone19:20.000:01.0MS, LRI173917280.6660.054 ± 0.0240.059 ± 0.0310.071 ± 0.0320.046 ± 0.0270.062 ± 0.039
292δ-Caprolactone20:37.400:01.1MS, LRI180618180.1210.344 ± 0.2250.332 ± 0.1810.357 ± 0.1600.305 ± 0.1740.288 ± 0.108
Sulfur containing compounds
293Methional14:02.700:01.0MS, LRI1461146111.8210.018 ± 0.014 c0.116 ± 0.047 a0.060 ± 0.043 b0.017 ± 0.005 c0.027 ± 0.031 bc
2942-(Methylthio)ethanol15:29.000:00.8S, MS, LRI152415319.5010.261 ± 0.063 b0.356 ± 0.069 a0.290 ± 0.094 ab0.133 ± 0.020 c0.237 ± 0.103 b
295Methionol19:08.800:00.9S, MS, LRI172917335.6472.344 ± 0.660 bc4.022 ± 1.550 a3.056 ± 1.076 ab1.741 ± 0.881 c1.465 ± 0.676 c
296Ethyl thiophene-2-carboxylate20:02.000:01.2MS1775-4.8830.024 ± 0.006 a0.020 ± 0.003 ab0.018 ± 0.005 bc0.017 ± 0.004 bc0.012 ± 0.002 c
2974-(Methylthio)-1-butanol21:26.000:00.9MS1850-4.6720.011 ± 0.005 bc0.022 ± 0.010 a0.018 ± 0.009 ab0.009 ± 0.004 c0.007 ± 0.003 c
298S-(3-hydroxypropyl) thioacetate14:47.000:01.1MS1491-4.3200.052 ± 0.015 b0.083 ± 0.032 a0.062 ± 0.016 b0.048 ± 0.006 b0.042 ± 0.020 b
2992-Thiophenecarboxaldehyde18:45.000:01.0S, MS, LRI170817013.7960.039 ± 0.017 b0.087 ± 0.046 a0.063 ± 0.036 ab0.032 ± 0.013 b0.069 ± 0.020 ab
300Ethyl methanesulfonate18:31.000:00.9MS1695-3.6380.177 ± 0.028 a0.157 ± 0.037 a0.159 ± 0.030 a0.120 ± 0.023 b0.163 ± 0.029 a
301Ethyl 3-(methylthio)-trans-2-propenoate19:41.000:01.2MS, LRI175717332.9150.013 ± 0.007 b0.021 ± 0.008 a0.012 ± 0.004 b0.018 ± 0.003 ab0.010 ± 0.007 b
3023-(Methylthio)propyl acetate17:28.700:01.2MS, LRI163016272.8320.589 ± 0.319 ab0.731 ± 0.337 a0.385 ± 0.305 bc0.427 ± 0.061 bc0.202 ± 0.087 c
303Ethyl 3-(methylthio)-trans-2-propenoate21:33.000:01.2MS, LRI185618372.7950.002 ± 0.004 b0.011 ± 0.006 a0.006 ± 0.005 ab0.010 ± 0.006 a0.005 ± 0.006 ab
304Diethyl sulfate17:21.000:01.0MS1622-2.4960.013 ± 0.0030.010 ± 0.0040.011 ± 0.0030.009 ± 0.0020.011 ± 0.002
305Ethyl thiocyanate21:05.200:01.2MS1831-2.3990.250 ± 0.0900.299 ± 0.1190.279 ± 0.0860.251 ± 0.0730.112 ± 0.045
3063-Ethoxythiophene14:19.000:01.2MS1472-1.6560.030 ± 0.0150.042 ± 0.0350.054 ± 0.0390.023 ± 0.0050.020 ± 0.018
307S-[(2,5-dihydro-4-hydroxy-5-oxo-3-furanyl)methyl] ethanethioate23:09.700:00.8MS1942-1.3760.113 ± 0.1490.032 ± 0.0550.048 ± 0.0570.030 ± 0.0240.016 ± 0.020
3081-(tert-Butylsulfonyl)-2-octanol19:14.900:02.2MS1734-0.9960.182 ± 0.1250.193 ± 0.1160.220 ± 0.0780.160 ± 0.0860.086 ± 0.078
309Cyclohexyl isothiocyanate18:17.000:01.6MS, LRI168116670.7800.014 ± 0.0110.017 ± 0.0110.017 ± 0.0090.014 ± 0.0080.006 ± 0.005
3103-[(2-Hydroxyethyl)thio]-1-propanol20:58.000:00.9MS1825-0.5150.020 ± 0.0040.019 ± 0.0060.027 ± 0.0230.029 ± 0.0260.022 ± 0.009
3112-Methyldihydro-3(2H)-thiophenone15:28.600:01.1MS, LRI152315380.5101.630 ± 0.5561.418 ± 0.6731.130± 0.9111.449 ± 0.7521.235 ± 0.462
Other compounds
3122,6,10,10-Tetramethyl-1-oxaspiro[4.5]deca-3,6-diene15:50.000:01.9MS1541-7.9950.139 ± 0.058 a0.025 ± 0.012 c0.076 ± 0.036 b0.054 ± 0.020 bc0.075 ± 0.072 bc
313Ethylene diglycol monoethyl ether17:19.000:00.9MS, LRI162016225.6880.081 ± 0.031 b0.238 ± 0.114 a0.175 ± 0.095 a0.227 ± 0.062 a0.261 ± 0.017 a
314Acetic formic anhydride15:59.600:00.7MS1549-1.8650.065 ± 0.0900.159 ± 0.1320.151 ± 0.1020.059 ± 0.0840.040 ± 0.053
315Crotonic anhydride21:25.800:01.5MS1850-1.5570.077 ± 0.0600.063 ± 0.0420.043 ± 0.0230.065 ± 0.0180.020 ± 0.017
3161H-indole31:00.200:00.9MS, LRI>210024201.0360.044 ± 0.0120.041 ± 0.0190.037 ± 0.0210.027 ± 0.0050.035 ± 0.026
317Methylsuccinic anhydride18:59.000:00.9MS1720-0.5170.013 ± 0.0210.051 ± 0.1120.038 ± 0.0280.029 ± 0.0260.053 ± 0.009
ID—identification of compounds; S—retention time and mass spectrum consistent with that of the pure standard and with NIST05 mass spectra electronic library; LRI—linear retention index consistent with that found in literature; MS—mass spectra consistent with that from NIST 2.0, Wiley 8, and FFNSC 2 mass spectra electronic libraries or literature; n.i.—not identified. The compounds with only MS symbol in ID column were tentatively identified. LRIlit—linear retention index from the literature, LRIexp—linear retention index obtained experimentally. Varieties: MI—Malvazija istarska, PO—Pošip, MA—Maraština, KR—Kraljevina, SK—Škrlet. Different superscript lowercase letters in a row represent statistically significant differences between mean values at p < 0.05 obtained by one-way ANOVA and least significant difference (LSD) test.
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Lukić, I.; Carlin, S.; Vrhovsek, U. Comprehensive 2D Gas Chromatography with TOF-MS Detection Confirms the Matchless Discriminatory Power of Monoterpenes and Provides In-Depth Volatile Profile Information for Highly Efficient White Wine Varietal Differentiation. Foods 2020, 9, 1787. https://doi.org/10.3390/foods9121787

AMA Style

Lukić I, Carlin S, Vrhovsek U. Comprehensive 2D Gas Chromatography with TOF-MS Detection Confirms the Matchless Discriminatory Power of Monoterpenes and Provides In-Depth Volatile Profile Information for Highly Efficient White Wine Varietal Differentiation. Foods. 2020; 9(12):1787. https://doi.org/10.3390/foods9121787

Chicago/Turabian Style

Lukić, Igor, Silvia Carlin, and Urska Vrhovsek. 2020. "Comprehensive 2D Gas Chromatography with TOF-MS Detection Confirms the Matchless Discriminatory Power of Monoterpenes and Provides In-Depth Volatile Profile Information for Highly Efficient White Wine Varietal Differentiation" Foods 9, no. 12: 1787. https://doi.org/10.3390/foods9121787

APA Style

Lukić, I., Carlin, S., & Vrhovsek, U. (2020). Comprehensive 2D Gas Chromatography with TOF-MS Detection Confirms the Matchless Discriminatory Power of Monoterpenes and Provides In-Depth Volatile Profile Information for Highly Efficient White Wine Varietal Differentiation. Foods, 9(12), 1787. https://doi.org/10.3390/foods9121787

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