European Food Research and Technology

, Volume 245, Issue 2, pp 315–324 | Cite as

Checking syrup adulteration of honey using bioluminescent bacteria and chemometrics

  • Dora Melucci
  • Alessandro Zappi
  • Luca Bolelli
  • Francesca Corvucci
  • Giorgia Serra
  • Michela Boi
  • Francesca-Vittoria Grillenzoni
  • Giorgio Fedrizzi
  • Simonetta Menotta
  • Stefano Girotti
Original Paper


Accomplishing the Italian law to verify honey quality is onerous, because it requires measuring many chemical and physical parameters. On the contrary, bioluminescence-based analytical methods allow for rapid and inexpensive analysis. Bioluminescence has never been applied before to verify honey adulteration. The application of chemometrics to analytical methods based on bioluminescence has been here explored for this scope. Several honey samples were prepared, in which sugar syrup was added without exceeding legal limits: in this case, univariate analysis prescribed by the law cannot reveal the fraud. All samples were subjected to measurements of parameters prescribed by the law and also to bioluminescence analysis, executed using the Vibrio fischeri bacterium, one of the most common bioluminescent bacteria. Principal components analysis, linear discriminant analysis, and partial least square regression were applied to discriminate sugar-added honeys with respect to natural honeys, both by regulated physicochemical parameters and by bioluminescence ones. The feasibility of combining bioluminescence and multivariate analysis for a rapid screening of honey authenticity was demonstrated.


Honey Adulteration Bioluminescent bacteria Chemometrics LDA PLS 



The authors wish to thank Lucia Banchetti and Silvio Lipartiti, for carrying out the experimental work; a detailed author contribution summary is provided in Online Resource 4. This investigation was supported by the University of Bologna (Funds for Selected Research Topics).

Compliance with ethical standards

Conflict of interest

Authors declare that no conflict of interest is associated with this publication.

Compliance with ethics requirements

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

217_2018_3163_MOESM1_ESM.csv (4 kb)
EMS_1 LAW variables data set. The first column is sample names, the second the botanical category of each sample, the third the class used for LDA (“natural_honey”, NAT or “counterfeit”, ADU) (CSV 4 KB)
217_2018_3163_MOESM2_ESM.csv (3 kb)
EMS_2 LDA classification table for LAW variables. The first column is sample names, the second the prior class, the third is the posterior class recalculated by LOO-CV. The following columns provide the belonging percentage of each sample to each class, again calculated by LOO-CV (CSV 3 KB)
217_2018_3163_MOESM3_ESM.csv (2 kb)
EMS_3 Numerical visualization of Fig. 4. The first column is sample names, the second the prior class. Third column reports the belonging degree to ADU class, while fourth column reports the degrees recalculated by LOO-CV, which are, respectively, abscissa and ordinate of Fig. 4 (CSV 1 KB)
217_2018_3163_MOESM4_ESM.pdf (275 kb)
EMS_4 Detailed authors contributions summary (PDF 275 KB)


  1. 1.
    European Commission DG Agriculture and Rural Development (2013) Evaluation of measures for the apiculture sector. Final ReportGoogle Scholar
  2. 2.
    Esslinger S, Riedl J, Fauhl-Hassek C (2014) Potential and limitations of non-targeted fingerprinting for authentication of food in official control. Food Res Int 60:189–204. CrossRefGoogle Scholar
  3. 3.
    Da Silva PM, Gauche C, Gonzaga LV et al (2016) Honey: chemical composition, stability and authenticity. Food Chem 196:309–323CrossRefGoogle Scholar
  4. 4.
    Bougrini M, Tahri K, Saidi T et al (2016) Classification of honey according to geographical and botanical origins and detection of its adulteration using voltammetric electronic tongue. Food Anal Methods 9:2161–2173. CrossRefGoogle Scholar
  5. 5.
    Wang S, Guo Q, Wang L et al (2015) Detection of honey adulteration with starch syrup by high performance liquid chromatography. Food Chem 172:669–674. CrossRefGoogle Scholar
  6. 6.
    Zhang YN, Chen LZ, Xue XF et al (2015) Discrimination of rice syrup adulterant of Acacia honey based using near-infrared spectroscopy. Guang Pu Xue Yu Guang Pu Fen Xi 35:2536–2539. Google Scholar
  7. 7.
    Zhou J, Qi Y, Ritho J et al (2014) Analysis of maltooligosaccharides in honey samples by ultra-performance liquid chromatography coupled with evaporative light scattering detection. Food Res Int 56:260–265. CrossRefGoogle Scholar
  8. 8.
    Brereton RG (2007) Applied chemometrics for scientists. John Wiley & Sons, Ltd, NJCrossRefGoogle Scholar
  9. 9.
    Corvucci F, Nobili L, Melucci D, Grillenzoni FV (2015) The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis. Food Chem 169:297–304. CrossRefGoogle Scholar
  10. 10.
    Tonello N, Moressi MB, Robledo SN et al (2016) Square wave voltammetry with multivariate calibration tools for determination of eugenol, carvacrol and thymol in honey. Talanta 158:306–314. CrossRefGoogle Scholar
  11. 11.
    Cajka T, Hajslova J, Pudil F, Riddellova K (2009) Traceability of honey origin based on volatiles pattern processing by artificial neural networks. J Chromatogr A 1216:1458–1462. CrossRefGoogle Scholar
  12. 12.
    Karabagias IK, Vavoura MV, Nikolaou C et al (2014) Floral authentication of Greek unifloral honeys based on the combination of phenolic compounds, physicochemical parameters and chemometrics. Food Res Int 62:753–760. CrossRefGoogle Scholar
  13. 13.
    Spiteri M, Jamin E, Thomas F et al (2015) Fast and global authenticity screening of honey using 1H-NMR profiling. Food Chem 189:60–66. CrossRefGoogle Scholar
  14. 14.
    Karabagias IK, Vlasiou M, Kontakos S et al (2018) Geographical discrimination of pine and fir honeys using multivariate analyses of major and minor honey components identified by1H NMR and HPLC along with physicochemical data. Eur Food Res Technol 244:1249–1259. CrossRefGoogle Scholar
  15. 15.
    Campbell AK (1988) Chemiluminescence principles and applications in biology and medicine. J Pharm Sci 78(9):787–797. Google Scholar
  16. 16.
    Björn LO, Ghiradella H (2015) Bioluminescence. In: Photobiology: the science of light and life, 3rd edn. Springer, Berlin, pp 399–413Google Scholar
  17. 17.
    Bolelli L, Ferri EN, Girotti S (2016) The management and exploitation of naturally light-emitting bacteria as a flexible analytical tool: a tutorial. Anal Chim Acta 934:22–35CrossRefGoogle Scholar
  18. 18.
    Girotti S, Ferri EN, Fumo MG, Maiolini E (2008) Monitoring of environmental pollutants by bioluminescent bacteria. Anal Chim Acta 608:2–29CrossRefGoogle Scholar
  19. 19.
    Backhaus T, Grimme LH (1999) The toxicity of antibiotic agents to the luminescent bacterium Vibrio fischeri. Chemosphere 38:3291–3301. CrossRefGoogle Scholar
  20. 20.
    El-Alawi YS, Huang X-D, Dixon DG, Greenberg BM (2002) Quantitative structure-activity relationship for the photoinduced toxicity of polycyclic aromatic hydrocarbons to the luminescent bacteria Vibrio fischeri. Environ Toxicol Chem 21:2225–2232Google Scholar
  21. 21.
    Farré M, Ferrer I, Ginebreda A et al (2001) Determination of drugs in surface water and wastewater samples by liquid chromatography-mass spectrometry: methods and preliminary results including toxicity studies with Vibrio fischeri. J Chromatogr A 938(1–2):187–197CrossRefGoogle Scholar
  22. 22.
    Somasundaram L, Coats JR, Racke KD, Stahr HM (1990) Application of the microtox system to assess the toxicity of pesticides and their hydrolysis metabolites. Bull Environ Contam Toxicol 44:254–259. CrossRefGoogle Scholar
  23. 23.
    Carlson-Ekvall CEA, Morrison GM (1995) Contact toxicity of metals in sewage sludge: evaluation of alternatives to sodium chloride in the microtox® assay. Environ Toxicol Chem 14:17–22. CrossRefGoogle Scholar
  24. 24.
    Newman MC, McCloskey JT (1996) Predicting relative toxicity and interactions of divalent metal ions: microtox(R) bioluminescence assay. Env Toxicol Chem 15:275–281.;2 CrossRefGoogle Scholar
  25. 25.
    Martin EB, Mansfield LP, Smith A, Forsythe SJ (2001) Inhibition of light emission from the bioluminescent bacterium Vibrio fischeri after exposure to triclosan and related hygiene care products. Luminescence 16:29–32. CrossRefGoogle Scholar
  26. 26.
    Burton SA, Petersen RV, Dickman SN, Nelson JR (1986) Comparison of in vitro bacterial bioluminescence and tissue culture bioassays and in vivo tests for evaluating acute toxicity of biomaterials. J Biomed Mater Res 20:827–838. CrossRefGoogle Scholar
  27. 27.
    (2003) Official Gazette of the Italian Republic, no. 185, August 11Google Scholar
  28. 28.
    Sesta G, Lusco L (2008) Refractometric determination of water content in royal jelly. Apidologie 39:225–232. CrossRefGoogle Scholar
  29. 29.
    Mehmood T (2016) Hotelling T2 based variable selection in partial least squares regression. Chemom Intell Lab Syst 154:23–28. CrossRefGoogle Scholar
  30. 30.
    Monago-Maraña O, Galeano-Díaz T, Muñoz de la Peña A (2017) Chemometric discrimination between smoked and non-smoked paprika samples. Quantification of pahs in smoked paprika by fluorescence-U-PLS/RBL. Food Anal Methods 10:1128–1137. CrossRefGoogle Scholar
  31. 31.
    Wold S, Sjöström M, Eriksson L (2001) PLS-regression: a basic tool of chemometrics. Chem Int Lab Syst 59(2):109–130. CrossRefGoogle Scholar
  32. 32.
    Kaškoniene V, Venskutonis PR (2010) Floral markers in honey of various botanical and geographic origins: a review. Compr Rev Food Sci Food Saf 9:620–634. CrossRefGoogle Scholar
  33. 33.
    Persano Oddo L, Piazza MG, Sabatini AG, Accorti M (1995) Characterization of unifloral honeys. Apidologie 26:453–465. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Dora Melucci
    • 1
  • Alessandro Zappi
    • 1
  • Luca Bolelli
    • 2
  • Francesca Corvucci
    • 3
  • Giorgia Serra
    • 3
  • Michela Boi
    • 3
  • Francesca-Vittoria Grillenzoni
    • 3
  • Giorgio Fedrizzi
    • 4
  • Simonetta Menotta
    • 4
  • Stefano Girotti
    • 2
  1. 1.Department of Chemistry CiamicianUniversity of BolognaBolognaItaly
  2. 2.Department of Pharmacy and Biotechnology (FaBiT)University of BolognaBolognaItaly
  3. 3.CREA-API Agricultural Economics Research CouncilHoneybee and Silkworm Research UnitBolognaItaly
  4. 4.IZSLER Zooprophylactic Experimental Institute for Lombardy and Emilia Romagna “Bruno Ubertini”BresciaItaly

Personalised recommendations