Quantitation of adulterated honey by three-dimensional fluorescence

Lin Cong; Hua Bai; Fangdi Cong

doi:10.1515/ijfe-2024-0196

Abstract

Honey products adulterated with syrup need to be availably distinguished from the true ones and quantified by modern method, for instance three-dimensional fluorescence spectroscopy. The spectra from eight types of honey showed that a linear relationship existed between fluorescence intensity and honey solution concentration in two excitation wavelength ranges of 240–320 nm and 320–360 nm when honey was diluted to 1 % (V:V) or less. Based on the linearity, a way was proposed to estimate the purity of adulterated honey by employing the least squares model to compare the spectra of adulterated honey with honey and syrup on a computer, after they were properly diluted. Honey artificially mixed with syrup in a ratio of 3:7 (V:V) was evaluate to be 31.6 % and the error was only 1.6 %. The method of quantitation on adulterated honey has the characteristics of convenience and accuracy.

Keywords: honey; adulteration; three-dimensional fluorescence; quantitative analysis; fluorescence quenching effect

Corresponding authors: Hua Bai, School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China, E-mail: baihua@tiangong.edu.cn; and Fangdi Cong, College of Basic Sciences, Tianjin Agricultural University, Tianjin 300392, China, E-mail: congfangdi@163.com

Acknowledgments

We would like to thank the Tianjin Bokang Tianmi Technology Development Co., Ltd., for the support in this research.

Research ethics: Not applicable.
Informed consent: Not applicable.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Use of Large Language Models, AI and Machine Learning Tools: None declared.
Conflict of interest: All other authors state no conflict of interest.
Research funding: None declared.
Data availability: Not applicable.

References

1. Ji, L, Qi, S, Zheng, H, Chen, S, Yan, W, Hu, Y. Research progress on nutritional composition and functional activity of honey. Food Ferment Sci Technol 2024;60:101–7.Search in Google Scholar

2. Zhang, Y, Wang, Q, Wang, H, Du, Y, Zhang, H, Zhang, G. Research progress on techniques for identification of honey authenticity. Food Sci (N Y) 2024;45:374–82.Search in Google Scholar

3. Koroec, M, Kropf, U, Golob, T, Bertoncelj, J. Functional and nutritional properties of different types of Slovenian honey. In: Functional properties of traditional foods. Boston, MA: Springer US; 2016:323–38 pp.10.1007/978-1-4899-7662-8_23Search in Google Scholar

4. Kumar, D, Hazra, K, Prasad, PVV, Bulleddu, R. Honey: an important nutrient and adjuvant for maintenance of health and management of diseases. J Ethn Food 2024;11:19. https://doi.org/10.1186/s42779-024-00229-3.Search in Google Scholar

5. Knoll, S, Fadda, V, Ahmed, F, Cappai, MG. The nutritional year-cycle of Italian honey bees (Apis mellifera ligustica) in a southern temperate climate. Agriculture 2024;14:1–20. https://doi.org/10.3390/agriculture14050730.Search in Google Scholar

6. Brar, DS, Pant, K, Krishnan, R, Kaur, S, Rasane, P, Nanda, V, et al.. A comprehensive review on unethical honey: validation by emerging techniques. Food Control 2023;145:109482. https://doi.org/10.1016/j.foodcont.2022.109482.Search in Google Scholar

7. Robert, IIO, Birech, Z, Kaniu, MI. Rapid assessment of molasses adulterated honey using laser Raman spectroscopy and principal component analysis. Food Anal Methods 2023;16:1702–10. https://doi.org/10.1007/s12161-023-02538-w.Search in Google Scholar

8. Siano, DB, Abdullakasim, W, Terdwongworakul, A, Phuangsombut, K. Improving the performance of the model developed from the classification of adulterated honey with different botanical origins based on near-infrared hyperspectral imaging system and supervised classification algorithms. Infrared Phys Technol 2023;131:104692. https://doi.org/10.1016/j.infrared.2023.104692.Search in Google Scholar

9. Damto, T, Zewdu, A, Birhanu, T. Impact of different adulterants on honey quality properties and evaluating different analytical approaches for adulteration detection. J Food Protect 2024;87:100241. https://doi.org/10.1016/j.jfp.2024.100241.Search in Google Scholar PubMed

10. Xue, X, Wang, Q, Li, Y, Wu, L, Chen, L, Zhao, J, et al.. 2-acetylfuran-3-glucopyranoside as a novel marker for the detection of honey adulterated with rice syrup. J Agric Food Chem 2013;61:7488–93. https://doi.org/10.1021/jf401912u.Search in Google Scholar PubMed

11. Ajlouni, S, Sujirapinyokul, P. Hydroxymethylfurfuraldehyde and amylase contents in Australian honey. Food Chem 2010;119:1000–5. https://doi.org/10.1016/j.foodchem.2009.07.057.Search in Google Scholar

12. Elenany, YE, Sharaf, H. Detection and identification of novel bacterial strains isolated from fresh clover bee honey. J Plant Protect Pathol 2019;10:49–52.10.21608/jppp.2019.40580Search in Google Scholar

13. Lestari, LA, Triyana, K, Hanifah, AK, Wildiana, RA. The use of electronic tongue (e-tongue) as a simple and rapid method for honey\nauthentication. Food Res 2021;5:453–60. https://doi.org/10.26656/fr.2017.5(3).615.Search in Google Scholar

14. Tiwari, K, Tudu, B, Bandyopadhyay, R, Chatterjee, A. Identification of monofloral honey using voltammetric electronic tongue. J Food Eng 2013;117:205–10. https://doi.org/10.1016/j.jfoodeng.2013.02.023.Search in Google Scholar

15. Qi, J, Zhaozong, M, Zhen, ZL, Li, Z. Review of scientific instruments: evaluation of adulteration in honey using a microwave planar resonator sensor. Rev Sci Instrum 2023;94:104706. https://doi.org/10.1063/5.0166005.Search in Google Scholar PubMed

16. Tomaszewskagras, J, Bakier, S, Goderska, K, Mansfeld, K. Differential scanning calorimetry for determining the thermodynamic properties of selected honeys. J Apicult Sci 2015;59:109–18. https://doi.org/10.1515/jas-2015-0012.Search in Google Scholar

17. Chen, G, Wu, W, Chen, K. Analysis of adulterated oilseed rape honey using differential scanning calorimetry combined with principal component analysis and two-dimensional correlation analysis. Food Sci (N Y) 2017;38:310–15.Search in Google Scholar

18. Peña, RM, Barciela, J, Herrero, C, García-Martín, S. Solid-phase microextraction gas chromatography-mass spectrometry determination of monoterpenes in honey. J Separ Sci 2015;27:1540–4. https://doi.org/10.1002/jssc.200301705.Search in Google Scholar PubMed

19. Wang, J, Xue, X, Du, X, Cheng, N, Chen, L, Zhao, J, et al.. Identification of acacia honey adulteration with rape honey using liquid chromatography – electrochemical detection and chemometrics. Food Anal Methods 2014;7:2003–12. https://doi.org/10.1007/s12161-014-9833-7.Search in Google Scholar

20. Chen, L, Xue, X, Ye, Z, Zhou, J, Chen, F, Jing, Z. Determination of Chinese honey adulterated with high fructose corn syrup by near infrared spectroscopy. Food Chem 2011;128:1110–14. https://doi.org/10.1016/j.foodchem.2010.10.027.Search in Google Scholar

21. Ruoff, K, Luginbühl, W, Künzli, R, Iglesias, MT, Amado, R. Authentication of the botanical and geographical origin of honey by mid-infrared spectroscopy. J Agric Food Chem 2006;54:6873–80. https://doi.org/10.1021/jf060838r.Search in Google Scholar PubMed

22. Wu, X, Xu, B, Ma, R, Niu, Y, Gao, S, Liu, H, et al.. Identification and quantification of adulterated honey by Raman spectroscopy combined with convolutional neural network and chemometrics. Spectrochim Acta 2022;274:121133. https://doi.org/10.1016/j.saa.2022.121133.Search in Google Scholar PubMed

23. Bertelli, D, Lolli, M, Papotti, G, Bortolotti, L, Serra, G, Plessi, M. Detection of honey adulteration by sugar syrups using one-dimensional and two-dimensional high-resolution nuclear magnetic resonance. J Agric Food Chem 2010;58:8495–501. https://doi.org/10.1021/jf101460t.Search in Google Scholar PubMed

24. Gauthier, JR, Burns, D, Sheng, J, D’Eon, JC. Exploring the composition and authenticity of honey and syrup samples using quantitative nmr spectroscopy and principal component analysis in an upper-year undergraduate analytical environmental course. J Chem Educ 2023;100:161–9. https://doi.org/10.1021/acs.jchemed.2c00501.Search in Google Scholar

25. Ropciuc, S, Dranca, F, Pauliuc, D, Oroian, M. Honey authentication and adulteration detection using emission – excitation spectra combined with chemometrics. Spectrochim Acta 2023;293:122459. https://doi.org/10.1016/j.saa.2023.122459.Search in Google Scholar PubMed

26. Shiddiq, M, Zulkarnain, AV, Aliyah, H. Identification of pure and adulterated honey using two spectroscopic methods. J Phys Conf Series 2019;1351:012022.10.1088/1742-6596/1351/1/012022Search in Google Scholar

27. Lanjewar, MG, Panchbhai, KG, Patle, LB. Sugar detection in adulterated honey using hyper-spectral imaging with stacking generalization method. Food Chem 2024;450:139322. https://doi.org/10.1016/j.foodchem.2024.139322.Search in Google Scholar PubMed

28. Kunpeng, Z, Zhiyang, L, Menglong, C, Shanxin, M. Analysis on influencing factors of detecting chemical oxygen demand in water by three-dimensional spectroscopy. Optoelectron Lett 2024;20:42–7. https://doi.org/10.1007/s11801-024-3082-9.Search in Google Scholar

29. Xu, RZ, Cao, JS, Feng, G. Fast identification of fluorescent components in three-dimensional excitation-emission matrix fluorescence spectra via deep learning. Chem Eng J 2022;430P2:132893. https://doi.org/10.1016/j.cej.2021.132893.Search in Google Scholar

30. Sun, G, Liu, S, Shi, C, Liu, X, Guo, Q. 3DCNAS: a universal method for predicting the location of fluorescent organelles in living cells in three-dimensional space. Exp Cell Res 2023;433:113807. https://doi.org/10.1016/j.yexcr.2023.113807.Search in Google Scholar PubMed

31. Karasawa, K, Takakura, M, Kato, S, Akatsuka, M, Kato, M. Simple and rapid evaluation of the unique manuka factor in manuka honey using fluorescence fingerprints and principal component analysis. Chem Pharm Bull 2020;68:762–5. https://doi.org/10.1248/cpb.c20-00208.Search in Google Scholar PubMed

32. Zhu, SH, Wu, HL, Li, BR, Xia, AL, Han, QJ, Zhang, Y, et al.. Determination of pesticides in honey using excitation–emission matrix fluorescence coupled with second-order calibration and second-order standard addition methods. Anal Chim Acta 2008;619:165–72. https://doi.org/10.1016/j.aca.2008.05.005.Search in Google Scholar PubMed

33. Zhao, J, Han, X, Chen, Q, Ouyang, Q. Identification of adulterated honey based on three-dimensional fluorescence spectral technology. Spectrosc Spectr Anal 2013;033:1626–30.Search in Google Scholar

34. Li, S, Zhang, X, Shan, Y, Su, D, Ma, Q, Wen, R, et al.. Qualitative and quantitative detection of honey adulterated with high-fructose corn syrup and maltose syrup by using near-infrared spectroscopy. Food Chem 2017;218:231–6. https://doi.org/10.1016/j.foodchem.2016.08.105.Search in Google Scholar PubMed

35. Egido, C, Saurina, J, Sentellas, S, Nunez, O. Honey fraud detection based on sugar syrup adulterations by HPLC-UV fingerprinting and chemometrics. Food Chem 2024;436:137758. https://doi.org/10.1016/j.foodchem.2023.137758.Search in Google Scholar PubMed

36. Fakhlaei, R, Babadi, AA, Ariffin, NM, Xiaobo, Z. Development of FTIR-ATR spectra and PLS regression combination model for discrimination of pure and adulterated acacia honey. Food Control 2025;169:110996. https://doi.org/10.1016/j.foodcont.2024.110996.Search in Google Scholar

37. Tong, Y, Li, Y, Wu, Y, Pang, M. Absorption, metabolism and effect on health of high fructose corn syrup. Food Sci Technol 2018;43:54–8.Search in Google Scholar

38. Ren, XM, Hu, M, Zhou, CJ, Wang, WT, Wu, YJ. Determination on different types of high fructose corn syrup (HFCS) adulterated in honey. Shandong Agr Sci 2013;45:117–19.Search in Google Scholar

39. Ali, HM. Efficient and sensitive determination of storage time-temperature marker 5-hydroxy methyl furfural in bee honey based on fluorescence quenching of human serum albumin. Microchem J 2024;200:110427. https://doi.org/10.1016/j.microc.2024.110427.Search in Google Scholar

40. Somogyi, B, Lakos, Z, Damjanovich, S, Rosenberg, A. Steady – state fluorescence quenching as a tool to study protein dynamics. J Mol Liq 2015;42:45–58. https://doi.org/10.1016/0167-7322(89)80024-8.Search in Google Scholar

41. Wang, L, Liang, YS, Wu, ZB, Liu, YS, Wu, AP. Exploring the interaction between cry1ac protein and Zn2+, Cd2+ metal ions by fluorescence quenching and molecular docking approaches. Chemosphere 2022;297:134105. https://doi.org/10.1016/j.chemosphere.2022.134105.Search in Google Scholar PubMed

42. Chen, Q, Qi, S, Li, H, Han, X, Ouyang, Q, Zhao, J. Determination of rice syrup adulterant concentration in honey using three-dimensional fluorescence spectra and multivariate calibrations. Spectrochim Acta 2014;131:177–82. https://doi.org/10.1016/j.saa.2014.04.071.Search in Google Scholar PubMed

43. Maulana, H, Purwanto, YA, Wijaya, SH, Sukoco, H, Suhandy, D. Prediction of the purity of stingless bee honey using fluorescence-based UV-visible spectrum data with a generative model approach. IOP Conf Ser Earth Environ Sci 2024;1386:012026. https://doi.org/10.1088/1755-1315/1386/1/012026.Search in Google Scholar

44. Yin, S. Fluorescence detecting of protein and DNA based on metallic-capillary [Master, thesis]. Dalian University of Technology; 2019.Search in Google Scholar

45. Zhu, SH, Wu, HL, Li, BR, Xia, AL, Han, QJ, Zhang, Y, et al.. Determination of pesticides in honey using excitation – emission matrix fluorescence coupled with second-order calibration and second-order standard addition methods. Anal Chim Acta 2008;619:165–72. https://doi.org/10.1016/j.aca.2008.05.005.Search in Google Scholar PubMed

46. Sun, Y, Kuang, J, Cheng, Y, Lin, C, Zhang, H, Zhang, M, et al.. Determination of trace fluoroquinolones in honey and milk based on cyclodextrin modified magnetic metal-organic frameworks solid phase extraction coupled with ultra-high performance liquid chromatography. J Chromatogr A 2024;1713:464521. https://doi.org/10.1016/j.chroma.2023.464521.Search in Google Scholar PubMed

47. Eremin, SA, Mukhametova, LI, Arutyunyan, DA, Tereshchenkov, AG, Sumbatyan, NV, Priima, AD, et al.. Development of a fluorescence polarization immunoassay for the quantification of tylosin in honey. J Anal Chem 2024;79:154–61. https://doi.org/10.1134/s1061934824020096.Search in Google Scholar

48. Ruoff, K, Luginbühl, W, Künzli, R, Bogdanov, S, Bosset, JO, Ohe, K, et al.. Authentication of the botanical and geographical origin of honey by front-face fluorescence spectroscopy. J Agric Food Chem 2006;54:6858–66. https://doi.org/10.1021/jf060697t.Search in Google Scholar PubMed

49. Ruoff, K, Karoui, R, Dufour, E, Luginbühl, W, Bosset, JO, Bogdanov, S, et al.. Authentication of the botanical origin of honey by front-face fluorescence spectroscopy. a preliminary study. J Agric Food Chem 2005;53:1343–7. https://doi.org/10.1021/jf048384q.Search in Google Scholar PubMed

50. Lakowicz, JR. Quenching of fluorescence. In: Lakowicz, JR, editor. Principles of fluorescence spectroscopy. Boston, MA: Springer; 1983.10.1007/978-1-4615-7658-7Search in Google Scholar

51. Hao, S, Li, J, Liu, X, Yuan, J, Xuan, H. Authentication of acacia honey using fluorescence spectroscopy. Food Control 2021;130:108327. https://doi.org/10.1016/j.foodcont.2021.108327.Search in Google Scholar

52. Karasawa, K, Takakura, M, Kato, S, Akatsuka, M, Kato, M. Simple and rapid evaluation of the unique manuka factor in manuka honey using fluorescence fingerprints and principal component analysis. Chem Pharm Bull 2020;68:762–5. https://doi.org/10.1248/cpb.c20-00208.Search in Google Scholar PubMed

53. Chen, H, Xu, Q, Jia, Y, Siying, C, Wu, H. Improved ks-gmm algorithm applied in classification and recognition of honey based on laser-induced fluorescence spectra. Appl Opt 2021;60:6140–6. https://doi.org/10.1364/ao.428292.Search in Google Scholar

54. Santana, JEG, Coutinho, HDM, Costa, JGMD, Menezes, JMC, Teixeira, RNP. Fluorescent characteristics of bee honey constituents: a brief review. Food Chem 2021;362:130174. https://doi.org/10.1016/j.foodchem.2021.130174.Search in Google Scholar PubMed

Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/ijfe-2024-0196).

Received: 2024-08-31

Accepted: 2025-02-20

Published Online: 2025-03-11

You are currently not able to access this content.

Supplementary Material