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Data Descriptor

13C NMR Dataset Qualitative Analysis of Grecian Wines

by
Alberto Mannu
1,*,
Ioannis K. Karabagias
2,*,
Salvatore Baldino
1,
Cristina Prandi
1,
Vassilios K. Karabagias
2 and
Anastasia V. Badeka
2
1
Department of Chemistry, University of Turin, via Pietro Giuria 7, 10125 Turin, Italy
2
Laboratory of Food Chemistry, Department of Chemistry, University of Ioannina, 45110 Ioannina, Greece
*
Authors to whom correspondence should be addressed.
Submission received: 7 August 2020 / Revised: 29 August 2020 / Accepted: 3 September 2020 / Published: 5 September 2020

Abstract

:
The development of analytical techniques for characterizing food samples, especially for the wine industry, is a main topic of research. Regarding the classification of wines based on their geographical origin, nuclear magnetic resonance (NMR) spectroscopy represents a fast and effective tool for determining chemical fingerprints. Herein, a 13C NMR dataset, which was acquired for classification of Grecian wines through multivariate statistics, is reported and described. Thus, the main qualitative differences between grapes of the same geographical origin, observable by the visual analysis of the 13C NMR data, are discussed.
Dataset License: CC BY 4.0

1. Summary

The development of new analytical techniques combined with statistics for possible applications in food chemistry and, in particular, in food classification and quality assessment is a topic of interest for many studies [1,2,3,4,5]. The possibility to employ, for such purposes, the raw data extracted from 13C nuclear magnetic resonance (NMR) analysis for the geographical classification of Grecian wines has been recently explored [6]. In that case, selected portions of 13C NMR spectra were extracted by a binning procedure, and the resulting integrals (independently from their physical meaning) were statistically treated. Herein, the original dataset, only partially published in the original manuscript, is reported and qualitatively described. The 13C NMR spectra were grouped by a known geographical origin, and a qualitative discussion about the differences among different wines from the same region is provided. The samples were analyzed in pure form as collected from the original bottles. Additional details are given in the Methods section.

2. Data Description

The 13C NMR analysis of 28 Grecian wine samples is herein described. Samples of different geographical origin and arising from different grapes and processes were considered (Table 1). The samples were grouped by geographical origin, and seven groups were generated: Crete, Samos Island, Ileia, Ioannina, Meteora, Korinthos, and Macedonia. The 13C NMR spectra of each group are described in a dedicated section.

2.1. Crete Samples

The Crete group contains two white (Malvasia di Candia Aromatica–Chardonnay and Vidiano), two red (Syrah and Syrah–Mandilari), and one rosé wine (Syrah–Mandilari). The corresponding 13C NMR spectra are reported in Figure 1.
From the 13C NMR spectra reported in Figure 1, it is possible to notice that the pattern of signals associated with the Crete wines is similar for all the samples considered. As the five wines analyzed are quite different in terms of grapes, procedure, and year of preparation, more differences within the corresponding spectra were expected. This fact suggests that the common geography of these grapes strongly influences their chemical composition, leading to only small differences related to grape and production characteristics. The portions of the spectra most representative for these samples are the aliphatic part (10–40 ppm), as well as the part associated with carbon atoms near multiple bonds or to heteroatoms (40–80 ppm). Looking at the small differences, up to 50 ppm, only the dry rosé protected geographical indication (PGI) Syrah–Mandilari shows a different pattern of signals between 40 and 50 ppm. Looking at lower fields, dry red wine PGI Syrah–Mandilari and dry red wine Syrah reveal a small pattern between 90 and 105 ppm. Small signals just outside the background in the area of the quaternary carbons, around 180 ppm, can be noticed for all the samples.

2.2. Samos Island Samples

From Samos Island, four wines (three white and one rosé) were considered (Figure 2).
The three Muscat wines from Samos Island present a very similar pattern in their 13C NMR spectra. The dry white DPO wine seems to contain fewer minor compounds with respect to the other two wines made by the same grape. Apart from the major pattern, the windows between 20 and 55 ppm, as well as from 110 to 210 ppm, are very clean. The spectrum of the semi-dry rosé wine shows a very similar pattern to the Muscat wines, suggesting (at a qualitative level) that the common geography determines the composition observable at 13C NMR more than the specific type of grape.

2.3. Ileia Samples

A total of four wines arising from Ileia were analyzed: one white (Albariño) and three red (Augoustiatis, Daphne Nera–Mavrodafni, and Refosco) (Figure 3).
Concerning the wines from Ileia (Figure 3), the three made from red grapes share a very similar 13C spectrum, with no relevant differences. The patterns change for the white Albariño, which has a characteristic group of signals between 90 and 110 ppm.

2.4. Ioannina Samples

Two wines from Ileia were analyzed: one red and one white from, respectively, grapes of the type Vlahiko and Debina (Figure 4).
Vlahiko and Debina wines from Zitsa (Ioannina) look very different in the 13C NMR spectra. A first important difference is represented by the relative concentration of chemicals; as the samples were analyzed in pure form, the richness of signals and their qualitative intensity are indicative of the relative organic compounds’ availability in the wine. In this context, Debina wine is richer in its organic fraction, and important patterns can be observed (Figure 4) especially in the portion ranging from 55 to 82 ppm, and from 90 to 115 ppm.

2.5. Meteora Samples

The three wines considered from Meteora were prepared from grapes Malagouzia and Assyrtiko (white) and Limniona (red). The 13C NMR spectra are reported in Figure 5.
The three analyzed wines from Meteora show different patterns in the 13C NMR spectra. In general, Assyrtiko and Limniona samples seem richer in composition when compared to the Malagouzia wines, suggesting once again that the difference in grapes can be sometimes overwhelmed by the same geographical origin. This qualitative observation sets the basis for a quantitative classification based on geography by means of an appropriate treatment of 13C data with statistics [1].

2.6. Korinthos Samples

Two Agiorgitiko wines (one red and one rosé), and a blended Syrah–Merlot–Cabernet (red) from Korinthos were analyzed (Figure 6).
The 13C NMR spectra of the three samples from Korinthos are different for each sample (Figure 6). Semi-sweet red PGI wine (Agiorgitiko) results are richer in composition, maybe due to the specific preparation process. The 13C pattern registered for the other Agiorgitiko wine (dry rosé PGI) seems a less rich version (in terms of composition) of the sweet red one made from the same grape, as all the relevant signals are common in both samples, with the red sweet wine showing many additional patterns.

2.7. Macedonia Samples

Six samples from Macedonia were considered for analysis: three prepared from mono-varietal grapes (Malagouzia, Syrah, and Xinomavro) and three blended (Syrah–Xinomavro, Xinomavro–Mavroudi–Sefka, Merlot–Xinomavro, Figure 7).
Regarding the Macedonia samples, the monovarietal or the blended nature of the wine does not seem to have been the origin of the differences in their organic composition. Malagouzia, Syrah, Xinomavro, and Merlot–Xinomavro wines show a very similar pattern, which indicates, indeed, a not particularly rich composition. On the contrary, Syrah–Xinomavro and Xinomavro–Mavroudi–Sefka show the presence of several different organic carbons, with comparable patterns.

3. Conclusions

The qualitative analysis of 13C NMR spectra relative to Grecian wines produced from different grapes confirmed the possibility of employing NMR spectroscopy for wine classification. Nevertheless, the different spectral patterns observed can be related to the grape type as well as to the geographical origin. Non-homogeneous trends were observed in samples from the same geographical area. In this context, in order to employ the methodology herein presented to discriminate within different wines, some additional analytical steps need to be performed. More information can be extracted from the 13C NMR spectra by opportune multivariate statistical techniques.

4. Methods

Wine samples were collected from their original bottles and analyzed in pure form (0.4 mL). Proton-decoupled 13C NMR analysis, in the presence of 30 mL of D2O containing 10% of tetramethylsilane (TMS, internal reference) (Sigma-Aldrich Italy) was then conducted. As TMS is almost insoluble in D2O, when this reference was not used, the typical signal at 60.1 ppm of glucose, common to all the samples, was taken as an internal reference for scale adjustment [7]. The NMR measurements were taken using a Bruker NEO 500 spectrometer equipped with a 5 mm pulsed-field z-gradient broadband BBFO probe and a variable-temperature unit operating at 125 MHz for the carbon nucleus. The following acquisition parameters were applied for each measurement: time domain 32K, 2500 scans, and a spectral width of 240 ppm. The spectral data from the 13C NMR analysis were processed as follows: Fourier transformation was applied and apodization with an exponent = 0.1 was performed, followed by an automatic baseline and phase corrections. The resulting spectra were studied in the range between 0 and 210 ppm. Spectral manipulation was performed using the Bruker Top Spin software [8].

Author Contributions

Conceptualization, I.K.K. and A.M.; methodology, A.M.; validation, A.M.; investigation, A.M.; resources, A.M., I.K.K. and A.V.B.; data curation, A.M.; writing—original draft preparation, I.K.K. and A.M.; writing—review and editing, I.K.K., C.P. and S.B.; visualization, I.K.K., V.K.K., A.M.; supervision A.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

The authors are grateful to the following wineries/estates: Zoinos Winery Zitsa, Ioannina; Papagiannakos Domaine, Markopoulo, Athens; I. Papadopoulos-I.Kalaitzidis Co., Drama; Theopetra Estate, Meteora, Tsililis K. S.A; Ktima Biblia Chora, Paggaio, Kavala; Ktima Gerovassiliou, Epanomi, Macedonia; Merkouri Estate, Korakochori, Ileia, Peloponnese; UWC SAMOS, Malagari, Samos Island; Diamantakis Winery, Heraklion, Crete; SEMÉLI ESTATE, Nemea, Korinthos; VAENI Naoussa-Agricultural Viticultural Winemaking Co. of Naoussa, for the supply of the wine samples. The technical assistance of Dionysia Sykalia during the collection of wine samples is greatly acknowledged.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Son, H.S.; Kim, K.M.; Frans, V.D.B.; Hwang, G.S.; Park, W.M.; Lee, C.H. 1H NMR nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas. J. Agric. Food Chem. 2008, 56, 8007–8016. [Google Scholar] [CrossRef] [PubMed]
  2. Karabagias, I.K.; Sykalia, D.; Mannu, A.; Badeka, A.V. Physico-chemical parameters complemented with aroma compounds fired up the varietal discrimination of wine using statistics. Eur. Food Res. Technol. 2020, 1–16. [Google Scholar] [CrossRef]
  3. Mandrile, L.; Zeppa, G.; Giovannozzi, A.M.; Rossi, A.M. Controlling protected designation of origin of wine by Raman spectroscopy. Food Chem. 2016, 211, 260–267. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Amargianitaki, M.; Spyros, A. NMR-based metabolomics in wine quality control and authentication. Chem. Biol. Technol. Agric. 2017, 4, 9. [Google Scholar] [CrossRef] [Green Version]
  5. Hu, B.; Cao, Y.; Zhu, J.; Xu, W.; Wu, W. Analysis of metabolites in chardonnay dry white wine with various inactive yeasts by 1H NMR spectroscopy combined with pattern recognition analysis. AMB Express 2019, 9, 140. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Mannu, A.; Karabagias, I.K.; Di Pietro, M.E.; Baldino, S.; Karabagias, V.K.; Badeka, A.V. 13C NMR-Based Chemical Fingerprint for the Varietal and Geographical Discrimination of Wines. Foods 2020, 9, 1040. [Google Scholar] [CrossRef] [PubMed]
  7. Bagno, A.; Rastrelli, F.; Saielli, G. Prediction of the 1H and 13C NMR Spectra of r-D-Glucose in Water by DFT Methods and MD Simulations. J. Org. Chem. 2007, 72, 7373–7381. [Google Scholar] [CrossRef] [PubMed]
  8. TopSpinsoftware from Bruker. Available online: https://www.bruker.com/service/support-upgrades/software-downloads/nmr.html (accessed on 6 August 2020).
Figure 1. 13C nuclear magnetic resonance (NMR) spectra of Crete wines.
Figure 1. 13C nuclear magnetic resonance (NMR) spectra of Crete wines.
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Figure 2. 13C NMR spectra of Samos Island wines.
Figure 2. 13C NMR spectra of Samos Island wines.
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Figure 3. 13C NMR spectra of Ileia wines.
Figure 3. 13C NMR spectra of Ileia wines.
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Figure 4. 13C NMR spectra of Zitsa (Ioannina) wines.
Figure 4. 13C NMR spectra of Zitsa (Ioannina) wines.
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Figure 5. 13C NMR spectra of Meteora wines.
Figure 5. 13C NMR spectra of Meteora wines.
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Figure 6. 13C NMR spectra of Korinthos wines.
Figure 6. 13C NMR spectra of Korinthos wines.
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Figure 7. 13C NMR spectra of Macedonia wines.
Figure 7. 13C NMR spectra of Macedonia wines.
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Table 1. The wine samples considered in the study.
Table 1. The wine samples considered in the study.
ID YearTypeOriginVariety
12017Dry white wine—PDOZitsa, IoanninaDebina
22017Dry white wine—PGICreteMalvasia di Candia Aromatica–Chardonnay
32016Dry red wine—PGICreteSyrah–Mandilari
42017Dry rosé wine—PGI CreteSyrah–Mandilari
52017Dry red wine—PGI CreteSyrah
62017Dry white wine—PGICreteVidiano
72017Dry white wine—PDOSamos IslandMuscat
82017Dry white wineSamos IslandMuscat
92018Semi-dry rosé wineSamos IslandSamos red grapes
102011Nectar, white wine naturally sweet—PDOSamos IslandMuscat
112016Dry red wine—PGI Letrinoi, IleiaRefosco
122015Dry red wine—PGILetrinoi, IleiaDaphne Nera–Mavrodafni
132016Dry red wine—PGIIleiaAugoustiatis
142017Dry white wineIleiaAlbariño
152017 Demi-sec white wineZitsa, IoanninaDebina
162016Dry red wine—PGIMeteoraLimniona
172017Dry white wine—PGIMeteoraAssyrtiko
182018Dry white wine—PGIMeteoraMalagouzia
192018Dry white wine—PGIMacedoniaMalagouzia
202016Dry red wine—PGI Zitsa, IoanninaVlahiko
212017Dry rosé wine—PGI KorinthosAgiorgitiko
222017Semi-sweet red wine—PGIKorinthosAgiorgitiko
232015Dry red wineKorinthosSyrah/Merlot/Cabernet
242015Dry red wine—PGINaoussa, MacedoniaSyrah–Xinomavro
252015Dry red wine—PGINaoussa, MacedoniaSyrah
262015Dry red wine—Table wineNaoussa, MacedoniaXinomavro–Mavroudi–Sefka
272016Dry red wine—PDO Naoussa, MacedoniaXinomavro
282015Dry red wine—PGI MacedoniaMerlot–Xinomavro
PDO: protected designation of origin, PGI: protected geographical indication.

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MDPI and ACS Style

Mannu, A.; Karabagias, I.K.; Baldino, S.; Prandi, C.; Karabagias, V.K.; Badeka, A.V. 13C NMR Dataset Qualitative Analysis of Grecian Wines. Data 2020, 5, 78. https://doi.org/10.3390/data5030078

AMA Style

Mannu A, Karabagias IK, Baldino S, Prandi C, Karabagias VK, Badeka AV. 13C NMR Dataset Qualitative Analysis of Grecian Wines. Data. 2020; 5(3):78. https://doi.org/10.3390/data5030078

Chicago/Turabian Style

Mannu, Alberto, Ioannis K. Karabagias, Salvatore Baldino, Cristina Prandi, Vassilios K. Karabagias, and Anastasia V. Badeka. 2020. "13C NMR Dataset Qualitative Analysis of Grecian Wines" Data 5, no. 3: 78. https://doi.org/10.3390/data5030078

APA Style

Mannu, A., Karabagias, I. K., Baldino, S., Prandi, C., Karabagias, V. K., & Badeka, A. V. (2020). 13C NMR Dataset Qualitative Analysis of Grecian Wines. Data, 5(3), 78. https://doi.org/10.3390/data5030078

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