Acta Vet. Brno 2025, 94: 251-259
https://doi.org/10.2754/avb202594030251
Raman spectroscopy and NIR as a method of comparing monofloral and honeydew honeys
References
1. 2018: Honey as a potential natural antioxidant medicine: an insight into its molecular mechanisms of action. Oxid Med Cell Longev 2018: 1-19
AS, Sulaiman SA, Baig AA, Ibrahim M, Liaqat S, Fatima S, Jabeen S, Shamim N, Othman NH
2. 2018: Physicochemical characterization of Lavandula spp. honey with FT-Raman spectroscopy. Talanta 178: 43-48
< O, Santos AJA, Paixao V, Estevinho LM https://doi.org/10.1016/j.talanta.2017.08.099>
3. 2005: Novel quality control methods in conjunction with chemometrics (multivariate analysis) for detecting honey authenticity. Crit Rev Food Sci Nutr 45: 193-203
< IS, Chalhoub C, Gotsiou P, Lydakis-Simantiris N, Kefalas P https://doi.org/10.1080/10408690590956369>
4. 2020: Authentication of commercial honeys based on Raman fingerprinting and pattern recognition analysis. Food Control 117: 107346
< DP, Shotts ML, Rodriguez-Saona LE https://doi.org/10.1016/j.foodcont.2020.107346>
5. 2008: Honey for nutrition and health: a review. J Am Coll Nutr 27: 677-689
< S, Jurendic T, Sieber R, Gallmann P https://doi.org/10.1080/07315724.2008.10719745>
6. 2018: Phenolic compounds in honey and their associated health benefits: a review. Molecules 23: 2322
< D, Forbes-Hernández TY, Gasparrini SAM, Redo-Rodriguez P, Manna PP, Zhang J, Lamas LB, Florez SM, Toyos PA, Quiles JL, Giampieri F, Battino M https://doi.org/10.3390/molecules23092322>
7. 2020: Honey: Another alternative in the fight against antibiotic-resistant bacteria? Antibiotics 9: 1-21
< P, Fresno JM, Estevinho MM, Sousa-Pimenta M, Tornadijo ME, Estevinho LM https://doi.org/10.3390/antibiotics9110774>
8. 2015: The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis. Food Chem 169: 487-494
< F, Nobili L, Melucci D, Grillenzoni FV https://doi.org/10.1016/j.foodchem.2014.07.122>
9. 2011: Quality control of honey using infrared spectroscopy: a review. Appl Spectrosc Rev 46: 523-538
< D, Corbella E, Smyth HE https://doi.org/10.1080/05704928.2011.587857>
10. 2002: Fourier transform Raman spectroscopy of honey. Appl Spectrosc 56: 306-311
< LFC, Colombara R, Edwards HGM https://doi.org/10.1366/0003702021954881>
11. 2015: Physicochemical characteristics of honey from different origins. Ann Agric Sci 60: 279-287
< SA, Masry SHD, Shehata MG https://doi.org/10.1016/j.aoas.2015.10.015>
12. 2025: The complexity of honey fraud detection. Bee World 102: 8-14
< NL, Amadei Enghelmayer M https://doi.org/10.1080/0005772X.2025.2467474>
13. 2014: Terpenes in honey: Occurrence, origin and their role as chemical biomarkers. RSC Adv 4: 31710-31728
< I, Kuś PM https://doi.org/10.1039/C4RA04791E>
14. 2024: Domain decomposed classification algorithms based on linear discriminant analysis: An optimality theory and applications. Neurocomputing 575: 127261
< J, Cai XC https://doi.org/10.1016/j.neucom.2024.127261>
15. 2023: Botanical honey recognition and quantitative mixture detection based on Raman spectroscopy and machine learning. Acta A Mol Biomol Spectrosc 293: 122433
< DA, Berghian-Grosan C https://doi.org/10.1016/j.saa.2023.122433>
16. 2011: Honey: its medicinal property and antibacterial activity. Asian Pac J Trop Biomed 1: 154-160
< MD, Mandal S https://doi.org/10.1016/S2221-1691(11)60016-6>
17. 2014: Physicochemical characteristics of minor monofloral honeys from Tenerife, Spain. LWT Food Sci Technol 55: 572-578
< AB, Garcia ZH, Galdon BR, Rodriguez ER, Romero CD https://doi.org/10.1016/j.lwt.2013.09.024>
18. 1980: Laser-Raman spectra of d-fructose in aqueous solution. Carbohydr Res 78: 225-233
< M, Luu DV https://doi.org/10.1016/0008-6215(80)90002-6>
19. 2013: Rapid analysis of sugars in honey by processing Raman spectrum using chemometric methods and artificial neural networks. Food Chem 136: 1444-1452
< B, Boyaci IH, Topcu A, Kadilar C, Tamer U https://doi.org/10.1016/j.foodchem.2012.09.064>
20. 2024: Use of a factor analysis to assess biomechanical factors of American Sign Language in native and non-native signers. J Biomech 165: 112011
< J, Demalis EC, Shelly J, Miller K, Moore ZM, Vidt ME https://doi.org/10.1016/j.jbiomech.2024.112011>
21. 2011: Discrimination of Corsican honey by FT-Raman spectroscopy and chemometrics. Biotechnol Agron Soc Environ 15: 75-84
JAF, Abbas O, Dardenne P, Baeten V
22. 2001: Rapid analysis of sugars in fruit juices by FT-NIR spectroscopy. Carbohydr Res 336: 63-74
< LE, Fry FS, McLaughlin MA, Calvey EM https://doi.org/10.1016/S0008-6215(01)00244-0>
23. 2006: Authentication of the botanical origin of honey by near-infrared spectroscopy. J Agric Food Chem 54: 6867-6872
< K, Luginbühl W, Bogdanov S, Bosset JO, Estermann B, Ziolko T, Amado R https://doi.org/10.1021/jf060770f>
24. 2007: Quantitative determination of physical and chemical measurands in honey by near-infrared spectrometry. Eur Food Res Technol 225: 415-423
< K, Luginbühl W, Bogdanov S, Bosset JO, Estermann B, Ziolko T, Kheradmandan S, Amado R https://doi.org/10.1007/s00217-006-0432-8>
25. 2017: Honey and health: a review of recent clinical research. Pharmacogn Res 9: 121-127
S, Farkhondeh T, Samini F
26. Smith BC 2011: Fundamentals of Fourier Transform Infrared Spectroscopy. 2nd edn. Boca Raton: CRC Press, 207 p.
27. 2021: Honey authenticity: analytical techniques, state of the art and challenges. RSC Adv 11: 11273-11294
< AS, Koulis GA, Danezis GP, Martakos I, Dasenaki M, Georgiou CA, Thomaidis NS https://doi.org/10.1039/D1RA00069A>
28. 2022: Botanical origin identification and adulteration quantification of honey based on Raman spectroscopy combined with convolutional neural network. Vib Spectrosc 123: 103439
< X, Xu B, Ma R, Gao S, Niu Y, Zhang X, Du Z, Liu H, Zhang Y https://doi.org/10.1016/j.vibspec.2022.103439>
29. 2013: A beginner’s guide to factor analysis: focusing on exploratory factor analysis. Tutor Quant Methods Psychol 9: 79-94
< AG, Pearce S https://doi.org/10.20982/tqmp.09.2.p079>