Impact of phase ratio, polydimethylsiloxane volume and size, and sampling temperature and time on headspace sorptive extraction recovery of some volatile compounds in the essential oil field

Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino, Italy.
Journal of Chromatography A (Impact Factor: 4.17). 05/2005; 1071(1-2):111-8. DOI: 10.1016/j.chroma.2004.09.054
Source: PubMed


This study evaluates concentration capability of headspace sorptive extraction (HSSE) and the influence of sampling conditions on HSSE recovery of an analyte. A standard mixture in water of six high-to-medium volatility analytes (isobutyl methyl ketone, 3-hexanol, isoamyl acetate, 1,8-cineole, linalool and carvone) was used to sample the headspace by HSSE with stir bars coated with different polydimethylsiloxane (PDMS) volumes (20, 40, 55 and 110 microL, respectively), headspace vial volumes (8, 21.2, 40, 250 and 1000 mL), sampling temperatures (25, 50 and 75 degrees C) and sampling times (30, 60 and 120 min, and 4, 8 and 16 h). The concentration factors (CFs) of HSSE versus static headspace (S-HS) were also determined. Analytes sampled by the PDMS stir bars were recovered by thermal desorption (TDS) and analysed by capillary GC-MS. This study demonstrates how analyte recovery depends on its physico-chemical characteristics and affinity for PDMS (octanol-water partition coefficients), sampling temperatures (50 degrees C) and times (60 min), the volumes of headspace (40 mL) and of PDMS (in particular, for high volatility analytes). HSSE is also shown to be very effective for trace analysis. The HSSE CFs calculated versus S-HS with a 1000 mL headspace volumes at 25 degrees C during 4 h sampling ranged between 10(3) and 10(4) times for all analytes investigated while the limits of quantitation determined under the same conditions were in the nmol/L range.

4 Reads
  • Source
    • "microextraction (SPME) [11] [12] [17] [21] [25] and stir bar sorptive extraction (SBSE) [26], have been successfully applied for PAH quantification. Headspace sorptive extraction (HSSE) is an SBSE-derived microextraction technique [28] [29], in which the polydimethylsiloxane (PDMS) coated stir bar is exposed to the headspace sample vial, trapping the analytes into its extracting phase coating. The retained compounds are later thermodesorbed in a specific injector, composed of a thermal desorption unit (TDU) and a programmed temperature vaporizing (PTV) injector, and submitted to GC separation . "
    [Show abstract] [Hide abstract]
    ABSTRACT: A solvent-free method is described for the determination of 10 volatile polycyclic aromatic hydrocarbons (PAHs), considered as priority pollutants by the EU, in different herbal infusions using headspace sorptive extraction (HSSE) and gas chromatography-mass spectrometry (GC-MS). The parameters affecting both the extraction and thermal desorption steps in the HSSE were optimized by means of Plackett-Burman designs. Ten millilitres of the herbal infusion was submitted to the HSSE preconcentration in the presence of salt for 4h at 88°C. The use of d(10)-phenanthrene as internal standard not only improved the repeatability of the method but allowed quantification of the samples against external aqueous standards. Detection limits ranged between 11 and 26ngL(-1).
    Full-text · Article · Jun 2014 · Journal of Chromatography A
  • Source
    • "VOCs from the Petri dish headspace were passively adsorbed on the PDMS film for a period of 6 h. The time was chosen after testing different sampling durations (6 h, 24 h, 48 h) and had also been demonstrat ed to be an optimum sampling time for trace analysis (Bicchi et al., 2005). Twisters were sealed in their original storage vials after the sampling period and analyzed within two weeks. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Fungi emit a large spectrum of volatile organic compounds (VOCs). In the present study, we characterized and compared the odor profiles of ectomycorrhizal (EM), pathogenic and saprophytic fungal species with the aim to use these patterns as a chemotyping tool. Volatiles were collected from the headspace of eight fungal species including nine strains (four EM, three pathogens and two saprophytes) using the stir bar sorptive extraction method and analyzed by gas chromatography - mass spectrometry (GC-MS). After removal of VOCs released from the growth system, 54 VOCs were detected including 15 novel compounds not reported in fungi before. Principle component and cluster analyses revealed that fungal species differ in their odor profiles, particularly in the pattern of sesquiterpenes. The functional groups and species could be chemotyped by using their specific emission patterns. The different ecological groups could be predicted with probabilities of 90 to 99%, whereas for the individual species the probabilities varied between 55 and 83%. This study strongly supports the concept that the profiling of volatile compounds can be used for non-invasive identification of different functional fungal groups.
    Full-text · Article · Mar 2013 · Fungal Genetics and Biology
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Progress is investigated for a shared-memory distributed system with a weak form of fault tolerance that allows processes to stop and restart functioning without notification. The concept of bounded fairness is introduced to formalize bounded delay under the assumption that each family of related processes continuously contains at least one active member. This is a generalization of wait-freedom, and also of a finitary form of weak fairness. Several useful proof rules are stated and proved. In a system with bounded fairness, a wait-free process can be constructed by forming a new process in which processes from the various families are scheduled in a round robin way. The theory is applied to prove progress within bounded delay for a linearizing concurrent data-object in shared memory. The safety properties of this algorithm have been treated elsewhere. Keywords: bounded fairness, concurrent data object, fault tolerance, memory management, client server architecture. 1 Introduction The...
    Preview · Article · Apr 1999
Show more

We use cookies to give you the best possible experience on ResearchGate. Read our cookies policy to learn more.