SPME-GC-MS and FTIR-ATR Spectroscopic Study as a Tool for Unifloral Common Greek Honeys’ Botanical Origin Identification
Abstract
:1. Introduction
2. Materials and Methods
2.1. Samples
2.2. Physicochemical and Melissopalynological Analysis
2.3. Isolation of Volatile Compounds
2.4. Analysis of the Isolated Volatile Compounds
2.5. ATR-FTIR Spectroscopy
2.6. Statistical Analysis
3. Results and Discussion
3.1. Physicochemical and Melissopalynological Analysis
3.2. Volatile Compounds Analysis
3.3. Spectroscopic Analysis
3.4. Stepwise LDA Based on Volatile Compounds Analysis
3.5. Stepwise LDA Based on ATR-FTIR Spectra
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Greek Statistical Authority. Available online: https://www.statistics.gr/el/statistics/agr (accessed on 20 February 2021).
- Trade Map ITC. Available online: https://www.trademap.org/ (accessed on 20 February 2021).
- Government Gazette B-239/23-2-2005 Annex II Article 67 of Greek Food Code 2005. Available online: http://www.minagric.gr/images/stories/docs/agrotis/MeliMelissokomia/KYATaytopoiisi.pdf (accessed on 20 February 2021).
- Tananaki, C.; Thrasyvoulou, A.; Giraudel, J.; Montury, M. Determination of volatile characteristics of Greek and Turkish pine honey samples and their classification by using Kohonen self organising maps. Food Chem. 2007, 101, 1687–1693. [Google Scholar] [CrossRef]
- Marini, F.; Magrıì, A.L.; Balestrieri, F.; Fabretti, F.; Marini, D. Supervised pattern recognition applied to the discrimination of the floral origin of six types of Italian honey samples. Anal. Chim. Acta. 2004, 515, 117–125. [Google Scholar] [CrossRef]
- León-Ruiz, V.; Vera, S.; González-Porto, A.V.; Andrés, M.P.S. Vitamin C and sugar levels as simple markers for discriminating Spanish honey sources. J. Food Sci. 2011, 76, C356–C361. [Google Scholar] [CrossRef]
- Anjos, O.; Iglesias, C.; Peres, F.; Martínez, J.; García, Á.; Taboada, J. Neural networks applied to discriminate botanical origin of honeys. Food Chem. 2015, 175, 128–136. [Google Scholar] [CrossRef] [PubMed]
- Jandrić, Z.; Haughey, S.A.; Frew, R.D.; McComb, K.; Galvin-King, P.; Elliott, C.T.; Cannavan, A. Discrimination of honey of different floral origins by a combination of various chemical parameters. Food Chem. 2015, 189, 52–59. [Google Scholar] [CrossRef]
- Zhao, J.; Du, X.; Cheng, N.; Chen, L.; Xue, X.; Zhao, J.; Wu, L.; Cao, W. Identification of monofloral honeys using HPLC–ECD and chemometrics. Food Chem. 2016, 194, 167–174. [Google Scholar] [CrossRef] [PubMed]
- Dinca, O.R.; Ionete, R.E.; Popescu, R.; Costinel, D.; Radu, G.L. Geographical and botanical origin discrimination of Romanian honey using complex stable isotope data and chemometrics. Food Anal. Methods 2014, 8, 401–412. [Google Scholar] [CrossRef]
- Zheng, X.; Zhao, Y.; Wu, H.; Dong, J.; Feng, J. Origin Identification and Quantitative analysis of honeys by nuclear magnetic resonance and chemometric techniques. Food Anal. Methods 2015, 9, 1470–1479. [Google Scholar] [CrossRef]
- Gan, Z.; Yang, Y.; Li, J.; Wen, X.; Zhu, M.; Jiang, Y.; Ni, Y. Using sensor and spectral analysis to classify botanical origin and determine adulteration of raw honey. J. Food Eng. 2016, 178, 151–158. [Google Scholar] [CrossRef]
- Aliferis, K.A.; Tarantilis, P.A.; Harizanis, P.C.; Alissandrakis, E. Botanical discrimination and classification of honey samples applying gas chromatography/mass spectrometry fingerprinting of headspace volatile compounds. Food Chem. 2010, 121, 856–862. [Google Scholar] [CrossRef]
- Svečnjak, L.; Biliškov, N.; Bubalo, D.; Barišić, D. Application of infrared spectroscopy in honey analysis. Agric. Conspec. Sci. 2011, 76, 191–195. [Google Scholar]
- Chen, L.; Wang, J.; Ye, Z.; Zhao, J.; Xue, X.; Heyden, Y.V.; Sun, Q. Classification of Chinese honeys according to their floral origin by near infrared spectroscopy. Food Chem. 2012, 135, 338–342. [Google Scholar] [CrossRef] [PubMed]
- Corvucci, F.; Nobili, L.; Melucci, D.; Grillenzoni, F.V. The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis. Food Chem. 2015, 169, 297–304. [Google Scholar] [CrossRef]
- Devi, A.; Jangir, J.; Anu Appaiah, K.A. Chemical characterization complemented with chemometrics for the botanical origin identification of unifloral and multifloral honeys from India. Food Res. Int. 2018, 107, 216–226. [Google Scholar] [CrossRef] [PubMed]
- Gok, S.; Severcan, M.; Goormaghtigh, E.; Kandemir, I.; Severcan, F. Differentiation of Anatolian honey samples from different botanical origins by ATR-FTIR spectroscopy using multivariate analysis. Food Chem. 2015, 170, 234–240. [Google Scholar] [CrossRef]
- Karabagias, I.K.; Badeka, A.V.; Kontakos, S.; Karabournioti, S.; Kontominas, M.G. Botanical discrimination of Greek unifloral honeys with physico-chemical and chemometric analyses. Food Chem. 2014, 165, 181–190. [Google Scholar] [CrossRef]
- Karabagias, I.K.; Karabagias, V.K.; Badeka, A.V. The honey volatile code: A collective study and extended version. Foods 2019, 8, 508. [Google Scholar] [CrossRef] [Green Version]
- Helrich, K. Official Methods of Analysis of Association of Official Analytical Chemists, 15th ed.; Helrich, K., Ed.; Association of Official Analytical Chemists: Arlington, VA, USA, 1990; Volume 1. [Google Scholar]
- International Honey Commission. Harmonides Methods of the International Honey Commission; Bee Product Science; Bogdanov, S., Ed.; Swiss Bee Research Centre FAM: Bern, Switzerland, 2009; Available online: https://www.ihc-platform.net/ihcmethods2009.pdf. (accessed on 20 February 2021).
- Louveaux, J.; Maurizio, A.; Vorwohl, G. Methods of melissopalynology. Bee World 1978, 59, 139–157. [Google Scholar] [CrossRef]
- Alissandrakis, E.; Tarantilis, P.A.; Harizanis, P.C.; Polissiou, M. Aroma investigation of unifloral Greek citrus honey using solid-phase microextraction coupled to gas chromatographic–mass spectrometric analysis. Food Chem. 2007, 100, 396–404. [Google Scholar] [CrossRef]
- Adams, R.P. Identification of Essential Oil Components by Gas Chromatography Quadrupole Mass Spectrometry, 4th ed.; Allured Publishing Corporation: Carol Stream, IL, USA, 2007. [Google Scholar]
- Field, A. Discovering Statistics Using SPSS, 3rd ed.; Sage Publications Ltd: London, UK, 2009. [Google Scholar]
- Karabagias, I.K.; Dimitriou, E.; Halatsi, E.; Nikolaou, C. Volatile profile, pigment content, and in vitro radical scavenging activity of flower, thyme, and fir honeys produced in Hellas. J. Food Chem. Nanotechnol. 2017, 3, 98–104. [Google Scholar] [CrossRef]
- Karabagias, I.K.; Nikolaou, C.; Karabagias, V.K. Volatile fingerprints of common and rare honeys produced in Greece: In search of PHVMs with implementation of the honey code. Eur. Food Res. Technol. 2018. [Google Scholar] [CrossRef]
- Alissandrakis, E.; Tarantilis, P.A.; Pappas, C.; Harizanis, P.C.; Polissiou, M. Ultrasound-assisted extraction gas chromatography–mass spectrometry analysis of volatile compounds in unifloral thyme honey from Greece. Eur. Food Res. Technol. 2009, 229, 365–373. [Google Scholar] [CrossRef]
- Karabagias, I.K.; Badeka, A.; Kontakos, S.; Karabournioti, S.; Kontominas, M.G. Characterization and classification of Thymus capitatus (L.) honey according to geographical origin based on volatile compounds, physicochemical parameters and chemometrics. Food Res. Int. 2014, 55, 363–372. [Google Scholar] [CrossRef]
- Bayraktar, D.; Onoğur, T.A. Investigation of the aroma impact volatiles in Turkish pine honey samples produced in Marmaris, Datça and Fethiye regions by SPME/GC/MS technique. Int. J. Food Sci. Technol. 2011, 46, 1060–1065. [Google Scholar] [CrossRef]
- De la Fuente, E.; Martínez-Castro, I.; Sanz, J. Characterization of Spanish unifloral honeys by solid phase microextraction and gas chromatography-mass spectrometry. J. Sep. Sci. 2005, 28, 1093–1100. [Google Scholar] [CrossRef]
- Soria, A.C.; Sanz, J.; Martínez-Castro, I. SPME followed by GC–MS: A powerful technique for qualitative analysis of honey volatiles. Eur. Food Res. Technol. 2008, 228, 579–590. [Google Scholar] [CrossRef] [Green Version]
- Anjos, O.; Campos, M.G.; Ruiz, P.C.; Antunes, P. Application of FTIR-ATR spectroscopy to the quantification of sugar in honey. Food Chem. 2015, 169, 218–223. [Google Scholar] [CrossRef]
- Nayik, G.A.; Dar, B.N.; Nanda, V. Physico-chemical, rheological and sugar profile of different unifloral honeys from Kashmir valley of India. Arab. J. Chem. 2015. [Google Scholar] [CrossRef] [Green Version]
- Svečnjak, L.; Prđun, S.; Rogina, J.; Bubalo, D.; Jerković, I. Characterization of Satsuma mandarin (Citrus unshiu Marc.) nectar-to-honey transformation pathway using FTIR-ATR spectroscopy. Food Chem. 2017, 232, 286–294. [Google Scholar] [CrossRef] [PubMed]
- Se, K.W.; Ghoshal, S.K.; Wahab, R.A.; Ibrahim, R.K.R.; Lani, M.N. A simple approach for rapid detection and quantification of adulterants in stingless bees (Heterotrigona itama) honey. Food Res. Int. 2018, 105, 453–460. [Google Scholar] [CrossRef]
- D’Arcy, B.R.; Rintoul, G.B.; Rowland, C.Y.; Blackman, A.J. Composition of Australian honey extractives. 1. Norisoprenoids, monoterpenes, and other natural volatiles from blue gum (Eucalyptus leucoxylon) and yellow box (Eucaliptus melliodora). J. Agric. Food Chem. 1997, 45, 1834–1843. [Google Scholar] [CrossRef]
- Wootton, M.; Edwards, R.A.; Faraji-Haremi, R.; Williams, P.J. Effect of accelerated storage conditions on the chemical composition and properties of Australian honeys 3. Changes in volatile components. J. Apic. Res. 1978, 17, 167–172. [Google Scholar] [CrossRef]
- Visser, F.R.; Allen, J.M.; Shaw, G.J. The effect of heat on the volatile flavour fraction from a unifloral honey. J. Apic. Res. 1988, 27, 175–181. [Google Scholar] [CrossRef]
- Castro-Vázquez, L.; Díaz-Maroto, M.C.; González-Viñas, M.A.; de la Fuente, E.; Pérez-Coello, M.S. Influence of storage conditions on chemical composition and sensory properties of citrus honey. J. Agric. Food Chem. 2008, 56, 1999–2006. [Google Scholar] [CrossRef] [PubMed]
- Bouseta, A.; Collin, S.; Dufour, J.P. Characteristic aroma profiles of unifloral honeys obtained with a dynamic headspace GC-MS system. J. Apic. Res. 1992, 31, 96–109. [Google Scholar] [CrossRef]
- Pita-Calvo, C.; Vázquez, M. Differences between honeydew and blossom honeys: A review. Trends Food Sci. Technol. 2017, 59, 79–87. [Google Scholar] [CrossRef]
- Bonnländer, B.; Winterhalter, P. 9-Hydroxypiperitone β-d-Glucopyranoside and Other Polar Constituents from Dill (Anethum graveolens L.) Herb. J. Agric. Food Chem. 2000, 48, 4821–4825. [Google Scholar] [CrossRef]
- Castro-Vázquez, L.; Díaz-Maroto, M.C.; González-Viñas, M.A.; Pérez-Coello, M.S. Differentiation of monofloral citrus, rosemary, eucalyptus, lavender, thyme and heather honeys based on volatile composition and sensory descriptive analysis. Food Chem. 2009, 112, 1022–1030. [Google Scholar] [CrossRef]
- Karabagias, I.K.; Halatsi, E.Z.; Kontakos, S.; Karabournioti, S.; Kontominas, M.G. Volatile fraction of commercial thyme honeys produced in Mediterranean regions and key volatile compounds for geographical discrimination: A chemometric approach. Int. J. Food Prop. 2016, 20, 2699–2710. [Google Scholar] [CrossRef]
- Piasenzotto, L.; Gracco, L.; Conte, L. Solid phase microextraction (SPME) applied to honey quality control. J. Sci. Food Agric. 2003, 83, 1037–1044. [Google Scholar] [CrossRef]
- Ciulu, M.; Oertel, E.; Serra, R.; Farre, R.; Spano, N.; Caredda, M.; Malfatti, L.; Sanna, G. Classification of unifloral honeys from SARDINIA (Italy) by ATR-FTIR spectroscopy and random forest. Molecules 2021, 26, 88. [Google Scholar] [CrossRef] [PubMed]
Wavenumber (cm−1) | Functional Group | Peak Performance | Assignment | Reference |
---|---|---|---|---|
~3270 | O–H | Sugars–Water | Stretching | [34] |
~2927 | C–H and C–N | Carboxylic acids and Amino acids | Stretching | [34] |
~1643 | Ο–Η | Water | Deformation | [34] |
~1414 | C–O–H, –CH2 and C–H | Glucose and Alkene | Stretching | [34,35,36] |
~1341 | O–H (C–OH) | Fructose | Bending | [36] |
~1253 | C–C and –CH2– | Glucose and fructose | Stretching and Bending | [34,35,36] |
~1146 | C–O, C–O–C | Sugars | Bending, Stretching | [36] |
~1044 | C–O (C–OH), C–O | Sugars and fructose | Stretching | [34,35,36,37] |
~1025 | C–O | Glucose | Stretching | [36] |
~918 | C–H | Sugars, Glucose | Bending | [36] |
~865 | C–C | Fructose | Stretching | [36] |
~818 | C–C–H | Fructose | Stretching | [36] |
~777 | C–C–H | Fructose | Deformation | [36] |
Classification Results 1,2 | |||||||
---|---|---|---|---|---|---|---|
Label | Predicted Group Membership | Total | |||||
Fir Honey | Thyme Honey | Pine Honey | Citrus Honey | ||||
Original | Count | Fir honey | 11 | 0 | 3 | 0 | 14 |
Thyme honey | 1 | 18 | 1 | 0 | 20 | ||
Pine honey | 2 | 0 | 12 | 0 | 14 | ||
Citrus honey | 0 | 2 | 0 | 12 | 14 | ||
% | Fir Honey | 78.6 | 0.0 | 21.4 | 0.0 | 100.0 | |
Thyme honey | 5.0 | 90.0 | 5.0 | 0.0 | 100.0 | ||
Pine honey | 14.3 | 0.0 | 85.7 | 0.0 | 100.0 | ||
Citrus honey | 0.0 | 14.3 | 0.0 | 85.7 | 100.0 | ||
Cross-validated 3 | Count | Fir honey | 11 | 0 | 3 | 0 | 14 |
Thyme honey | 1 | 18 | 1 | 0 | 20 | ||
Pine honey | 3 | 1 | 10 | 0 | 14 | ||
Citrus honey | 0 | 2 | 0 | 12 | 14 | ||
% | Fir honey | 78.6 | 0.0 | 21.4 | 0.0 | 100.0 | |
Thyme honey | 5.0 | 90.0 | 5.0 | 0.0 | 100.0 | ||
Pine honey | 21.4 | 7.1 | 71.4 | 0.0 | 100.0 | ||
Citrus honey | 0.0 | 14.3 | 0.0 | 85.7 | 100.0 |
Classification Results 1,2 | |||||||
---|---|---|---|---|---|---|---|
Label | Predicted Group Membership | Total | |||||
Fir Honey | Thyme Honey | Pine Honey | Citrus Honey | ||||
Original | Count | Fir honey | 12 | 0 | 2 | 0 | 14 |
Thyme honey | 0 | 20 | 0 | 0 | 20 | ||
Pine honey | 0 | 0 | 12 | 2 | 14 | ||
Citrus honey | 0 | 0 | 0 | 14 | 14 | ||
% | Fir honey | 85.7 | 0.0 | 14.3 | 0.0 | 100.0 | |
Thyme honey | 0.0 | 100.0 | 0.0 | 0.0 | 100.0 | ||
Pine honey | 0.0 | 0.0 | 85.7 | 14.3 | 100.0 | ||
Citrus honey | 0.0 | 0.0 | 0.0 | 100.0 | 100.0 | ||
Cross-validated 3 | Count | Fir honey | 12 | 0 | 2 | 0 | 14 |
Thyme honey | 2 | 17 | 0 | 1 | 20 | ||
Pine honey | 0 | 0 | 12 | 2 | 14 | ||
Citrus honey | 0 | 3 | 1 | 10 | 14 | ||
% | Fir honey | 85.7 | 0.0 | 14.3 | 0.0 | 100.0 | |
Thyme honey | 10.0 | 85.0 | 0.0 | 5.0 | 100.0 | ||
Pine honey | 0.0 | 0.0 | 85.7 | 14.3 | 100.0 | ||
Citrus honey | 0.0 | 21.4 | 7.1 | 71.4 | 100.0 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Xagoraris, M.; Revelou, P.-K.; Dedegkika, S.; Kanakis, C.D.; Papadopoulos, G.K.; Pappas, C.S.; Tarantilis, P.A. SPME-GC-MS and FTIR-ATR Spectroscopic Study as a Tool for Unifloral Common Greek Honeys’ Botanical Origin Identification. Appl. Sci. 2021, 11, 3159. https://doi.org/10.3390/app11073159
Xagoraris M, Revelou P-K, Dedegkika S, Kanakis CD, Papadopoulos GK, Pappas CS, Tarantilis PA. SPME-GC-MS and FTIR-ATR Spectroscopic Study as a Tool for Unifloral Common Greek Honeys’ Botanical Origin Identification. Applied Sciences. 2021; 11(7):3159. https://doi.org/10.3390/app11073159
Chicago/Turabian StyleXagoraris, Marinos, Panagiota-Kyriaki Revelou, Stela Dedegkika, Charalabos D. Kanakis, George K. Papadopoulos, Christos S. Pappas, and Petros A. Tarantilis. 2021. "SPME-GC-MS and FTIR-ATR Spectroscopic Study as a Tool for Unifloral Common Greek Honeys’ Botanical Origin Identification" Applied Sciences 11, no. 7: 3159. https://doi.org/10.3390/app11073159
APA StyleXagoraris, M., Revelou, P. -K., Dedegkika, S., Kanakis, C. D., Papadopoulos, G. K., Pappas, C. S., & Tarantilis, P. A. (2021). SPME-GC-MS and FTIR-ATR Spectroscopic Study as a Tool for Unifloral Common Greek Honeys’ Botanical Origin Identification. Applied Sciences, 11(7), 3159. https://doi.org/10.3390/app11073159