4.4 Article

Determination of Biomarkers in Multifloral Honey by Vacuum-Assisted Headspace Solid-Phase Microextraction

期刊

FOOD ANALYTICAL METHODS
卷 16, 期 7, 页码 1180-1190

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SPRINGER
DOI: 10.1007/s12161-023-02499-0

关键词

Biomarkers; Botanical origin; Geographical origin; Gas chromatography; Mass spectrometry

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This study focused on the analysis of volatile and semi-volatile compounds in honey using vacuum-assisted solid-phase microextraction and gas chromatography-mass spectrometry (Vac-SPME/GC-MS) for the first time. The Vac-SPME method was compared with the conventional HS-SPME method, and its application in characterizing the volatile and semi-volatile profile of honey was explored. Analysis of ten multiflower honey samples from mountainous and steppe regions revealed significant geographical variation in honey composition, highlighting the importance of differentiation.
This paper focuses on the study of volatile and semi-volatile compounds of honey, using for the first-time vacuum-assisted solid-phase microextraction and gas chromatography-mass spectrometry (Vac-SPME/GC-MS) to reaffirm the geographical features of honey. An emphasis was put on the Vac-SPME method, and its comparison with HS- SPME method, and its application to characterize the volatile and semi-volatile profile of honey. Ten multiflower honey samples from mountainous and steppe regions were taken for the analysis. Determination of volatiles and semi-volatile was conducted using gas chromatograph with mass spectrometric detector. Chromatographic data processing was conducted through chemometrics tools. The extraction parameters were optimized using design of the experiments based on the protocol of SPME. The optimal parameters of vacuum-assisted solid-phase microextraction to characterize the volatile and semi-volatile profile of honey sample were 30 min for extraction time, 60 degrees C for extraction temperature, and 30 min for the incubation time. Geographical location influences on the composition of honey, so it is important to differentiate them. Hence, pattern recognition method principal component analysis (PCA) was conducted to reaffirm the geographical origin of mountain and steppe honey samples. Analysis revealed a considerable variation in the composition of mountain and steppe honey. Results suggest the developed methodology to be accurate and reliable for the geographical classification of honey.

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