Improved sample storage, preparation and extraction of blueberry aroma volatile organic compounds for gas chromatography
•HS-SPME and DHS extractions yield sufficient analyte recovery of blueberry VOCs.•GC×GC-TOFMS analysis enhances identification of aroma compounds in VOC profiles.•Proper storage and preparation of blueberries is crucial for VOC preservation.•Selection of an appropriate quality control matrix assures...
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Veröffentlicht in: | Journal of Chromatography Open 2023-11, Vol.3, p.100075, Article 100075 |
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Sprache: | eng |
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Zusammenfassung: | •HS-SPME and DHS extractions yield sufficient analyte recovery of blueberry VOCs.•GC×GC-TOFMS analysis enhances identification of aroma compounds in VOC profiles.•Proper storage and preparation of blueberries is crucial for VOC preservation.•Selection of an appropriate quality control matrix assures significant results.
Aroma profiles of blueberries contain a heterogeneous mixture of volatile organic compounds (VOCs), and headspace sampling is the most efficient approach to VOC extraction from berries. Typically, headspace solid-phase microextraction (HS-SPME) has been applied to blueberry VOCs. Though HS-SPME has been the most common choice for headspace sampling, the fiber chemistry introduces selectivity to the extraction: preferential sorption may skew aroma profiles. Dynamic headspace (DHS) is an attractive substitute for HS-SPME, given its improved sensitivity and lessened bias imparted due to extraction phase selectivity. DHS extractions tend to yield a larger number of compounds and require even less sample than HS-SPME. These two extraction techniques were applied to homogenized blueberries and extracts were subjected to analysis by comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS). Major chemical classes were identified with filtering scripts for GC×GC-TOFMS data. The HS-SPME and DHS methods were assessed for reproducibility and chemical diversity (i.e., recovered chemical classes).
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ISSN: | 2772-3917 2772-3917 |
DOI: | 10.1016/j.jcoa.2022.100075 |