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Rapid Plant Volatiles Screening Using Headspace SPME and Person-Portable Gas Chromatography–Mass Spectrometry
- Wong, Yong Foo, Yan, DanDan, Shellie, Robert A., Sciarrone, Danilo, Marriott, Philip J.
- Chromatographia 2019 v.82 no.1 pp. 297-305
- Asteraceae, Humulus lupulus, Mentha piperita nothosubsp. piperita, Myrtaceae, Pittosporaceae, Rutaceae, botanical gardens, emissions, essential oils, gas chromatography-mass spectrometry, genotype, headspace analysis, hybrids, leaves, multivariate analysis, plant extracts, screening, solid phase microextraction, spectrometers, Australia
- Rapid on-site screening of biogenic volatile emissions from leaves of living plants is demonstrated, using headspace solid-phase microextraction (HS-SPME) with a portable gas chromatograph (PGC), fitted with a low-thermal mass (LTM) column equipped with a miniature toroidal ion trap mass spectrometer (ITMS). For field sampling, the study was conducted at the Royal Botanical Garden, Cranbourne, Australia, with the sampling site located in the Peppermint Garden. Twelve designated plants in the families of Asteraceae, Lamiaceae, Myrtaceae, Pittosporaceae, and Rutaceae were chosen for this field study. A customised SPME syringe was used for headspace sampling and sample introduction; leaves were collected into vials, equilibrated, sampled onto a PDMS/DVB-coated fibre, then desorbed in the GC inlet in split mode. A resistively heated LTM, narrow bore (0.1 mm ID) non-polar capillary column heated at 2 °C s⁻¹ to 270 °C, provided fast GC elution with total run time of 3 min. The miniaturised ITMS was operated over a mass range of 40–500 Da. This provided approximation of near-real-time measurement of leaf volatiles released from the plant. For a second study, PGC–ITMS is employed to profile essential oils from experimental hybrid and commercial Humulus lupulus L. (hop) plant extracts in the laboratory, and contrasted with bench-top data. Results were processed by chromatographic fingerprinting using retention times, and MS fragmentation pattern similarity criteria. Unsupervised multivariate analysis was performed to improve specificity for classification of different plant volatiles, yielding loading variables corresponding to chemical differences of the analysed plants. The combination of HS-SPME and portable GC–ITMS proved effective for rapid chemical expression of the plant volatile genotype in the field.