Volatile Profiles of Honeys Using HS-SPME-GC-MS

By: Federica Bianchi, Marilena Musci, Reporter US Vol 28.1

The following was generated with the assistance of an outside source using Sigma-Aldrich products. Technical content was generated and provided by:

Federica Bianchi1 and Marilena Musci1

1. Università degli Studi di Parma, Dipartimento di Chimica Generale ed Inorganica, Chimica Analitica, Chimica Fisica, Viale Usberti 17/A, 43100 Parma, Italy

mike.buchanan@sial.com

Introduction

The assessment of the authenticity of honey is a subject of primary importance both for consumers and industries. Usually, the determination of the botanical origin of honey is carried out by melissopalynological analysis, based on the identification of pollen by microscopic examination (1). However, data interpretation is very difficult and does not always lead to correct identification. The characterization of the volatile profile of honey has proven to be a reliable alternative to pollen analysis for the assessment of its botanical origin (2,3). In fact, the volatile profile represents a chemical fingerprint of honey, since both the nature and the amount of volatile compounds are characteristics of the floral source.

Solid phase microextraction (SPME) (4) is a rapid, solvent-less, and easy-to-use extraction technique widely applied in the determination of volatile compounds in several kinds of food. In this work we evaluate the applicability of headspace SPME (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) for the characterization of the volatile fraction of some honey samples.

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Materials and Methods

Four samples of unifloral honeys (milk thistle, citrus, eucalyptus, and acacia) and a sample of a multifloral honey were analyzed. Dynamic headspace (DHS) extraction was performed following the procedure described in a previous work (2). A brief description of this DHS process can be found in Figure 1. HS-SPME was carried out per the procedure described in Figure 2. GC-MS conditions are listed in both Figures 1 and 2.

Figure 1. Milk Thistle Honey Volatiles Using DHS

 

Figure 2. Milk Thistle Honey Volatiles Using SPME

 

Compounds were identified by comparing the mass spectra obtained with those stored in the National Institute of Standards and Technology (NIST) library. In addition, retention indices (RIs) were calculated for each peak and compared with literature data (5). Table 1 lists the most abundant compounds identified during this work. The chromatograms in Figures 1-6 are shown on the same abundance scale for ease of visual comparison. In order to evaluate quantitative differences in the aromatic profile of the samples investigated, gas chromatographic peak areas were calculated as Total Ion Current (TIC).

Table 1. Most Abundant Compounds Identified in Honey Headspace

 

Figure 3. Milk Thistle Honey Volatiles Using SPME

 

Figure 4. Milk Thistle Honey Volatiles Using SPME

 

Figure 5. Milk Thistle Honey Volatiles Using SPME

 

Figure 6. Milk Thistle Honey Volatiles Using SPME

 

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Results and Discussion

Preliminary experiments were carried out in order to compare the performances of the DHS technique, used in a previous study dealing with the characterization of the volatile profile of honey (2), with the SPME technique. Chromatographic profiles for a milk thistle honey obtained by DHS and SPME are shown in Figure 1 and Figure 2, respectively. As can be seen, the SPME profile not only shows a greater number of peaks with respect to that obtained by DHS, but also presents higher signal intensities. Less volatile compounds were better extracted using SPME, owing to its coating properties, whereas the more volatile compounds were better extracted by DHS. Due to the greater number of peaks observed, SPME was chosen as the extraction technique for the remainder of our study.

Figures 2-6 show the chromatographic profile of five honey samples obtained by the SPME technique. From a qualitative point of view, the chromatographic profiles of honey samples of different botanical origins were quite similar, as some of the same volatile compounds were detected in different samples. So, it was not possible to define specific volatile compounds as markers characteristic for a defined botanical origin.

However, significant differences were observed from a quantitative point of view, since different amounts of the volatile compounds were observed depending upon the floral source. For example, the milk thistle honey (Figure 2) contained a high content of hotrienol (35%), phenylacetaldehyde (16%), and 3-phenyl furan (5%), the last compound being detected only in milk thistle honey. Citrus honey (Figure 3) was characterized by a high content of hotrienol (30%) and phenylacetaldehyde (10%). Alternatively, neither hotrienol nor phenylacetaldehyde were observed in eucalyptus honey (Figure 4), which was characterized by high amounts of nonanol (32%), nonanal (12%), and nonanoic acid (7%). Acacia honey (Figure 5) was characterized by high amounts of benzaldehyde (18%), 􀁁-linalool (11%), nonanal (6%), and hotrienol (6%). The chromatographic profile of multifloral honey (Figure 6) presents a high number of compounds, the most abundant being hotrienol (14%), benzaldehyde (10%), nonanol (10%), nonanal (8%), and furfural (5%).

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Conclusion

Considering both the nature and the relative amount of the volatile compounds extracted by SPME, it was possible to obtain and distinguish the chemical fingerprints of different types of honey. Therefore, it is possible that SPME may prove to be a useful tool for determining the botanical origin of honeys to achieve authenticity assessment.

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References

  1. Loveaux, J., Maurizio, A., & Vorwhohl, G. (1978) Bee World, 59, 139-157.
  2. Radovic, B.S., Careri, M., Mangia, A., Musci, M., Gerboles, M., & Anklam, E. (2001) Food Chemistry, 72 511-520.
  3. Cuevas-Glory, L.F., Pino, J.A., Santiago, L.S., & Sauri-Duch, E. (2007) Food Chemistry, 103, 1032-1043.
  4. J. Pawliszyn, Solid Phase Microextraction; Wiley-VCH: New York, 1997.
  5. Bianchi, F., Careri, M., Mangia, A. & Musci, M. (2007) Journal of Separation Science, 30, 563-572.

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