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ABSTRACTAn Ecuadorian specimen of Ophryosporus peruvianusproduced an essential oil with a yield of 0.4% of the weight of the fresh plant material. A total of thirty-two compounds were detected and quantified. The chemical composition showed the predominance of monoterpene hydrocarbons, with sabinene (22.5%), β-pinene (15.1%), limonene (8.3%), β-phellandrene (29.7%), δ-elemene (2.1%), and epi-α-cadinol (2.7%) being the main components, expressed as mean values on two stationary phases of different polarity. This composition was very different from that reported in the literature for the essential oil of a Peruvian specimen, which was dominated by sesquiterpene hydrocarbons. These results indicate the existence of different chemotypes of O. peruvianus. Moreover, an enantioselective analysis of the major chiral constituents was performed, which revealed (R)-(-)-β-phellandrene, (R)-(-)-β-phellandrene and (1R,9R,E)-(-)-β-caryophylleneas enantiomerically pure compounds. On the other hand, β-thujene, β-pinene, β-pinene, sabinene, limonene, and terpinen-4-ol were scalemic mixtures. Finally, a preliminary screening of enzymatic inhibitory activity was performedin vitro, showing modest but interesting inhibition of both butyrylcholinesterase and lipase.

The volatile fraction of foods and of plant-origin materials provides functional information on sample-related variables, and gas-phase extractions are ideal approaches for its accurate chemical characterization. However, for gas-phase sampling, the usual procedures adopted to standardize results from solvent extraction methods are not appropriate: headspace (HS) composition depends on the intrinsic physicochemical analyte properties (volatility, polarity, partition coefficient(s)) and matrix effects. Method development, design, and expression of the results are therefore challenging. This review article focuses on volatile vapor-phase quantitation methods (internal standard normalization, standard addition, stable isotope dilution assay, multiple headspace extraction) and their suitability in different applications. Because of the analyte informative role, the different ways of expressing results (normalized chromatographic area, percent normalized chromatographic areas, and absolute concentrations) are discussed and critically evaluated with examples of quality markers in chamomile, process contaminants (furan and 2-methylfuran) in roasted coffee, and key-aroma compounds from high-quality cocoa.

Aroma is a primary hedonic aspect of a good coffee. Coffee aroma quality is generally defined by cup tasting, which however is time-consuming in terms of panel training and alignment and too subjective. It is challenging to define a relationship between chemical profile and aroma sensory impact, but it might provide an objective evaluation of industrial products. This study aimed to define the chemical signature of coffee sensory notes, to develop prediction models based on analytical measurements for use at the control level. In particular, the sensory profile was linked with the chemical composition defined by HS-SPME-GC-MS, using a chemometric-driven approach. The strategy was found to be discriminative and informative, identifying aroma compounds characteristic of the selected sensory notes. The predictive ability in defining the sensory scores of each aroma note was used as a validation tool for the chemical signatures characterized. The most reliable models were those obtained for woody, bitter, and acidic properties, whose selected volatiles reliably represented the sensory note fingerprints. Prediction models could be exploited in quality control, but compromises must be determined if they are to become complementary to panel tasting.

The solvent‐enhanced headspace sorptive extraction technique aims at modifying PDMS polarity using a solvent to increase its concentration capability. In solvent‐enhanced headspace sorptive extraction, a PDMS tubing closed at both ends by small glass stoppers and filled with an organic solvent is suspended in the sample headspace for a fixed time. After sampling, the sampled analytes are recovered from the PDMS tubing by thermal desorption and online transferred to a GC–flame ionization detector or GC‐MS system for analysis. Cyclohexane, iso‐octane, ethyl acetate, acetone, acetonitrile and methanol were tested as PDMS modifiers to sample the volatile fractions of sage (Salvia lavandulifoliaVahl.), thyme (Thymus vulgarisL.) and roasted coffee. Ethyl acetate was found to be the most effective PDMS modifier for all matrices investigated; although to a lesser extent, cyclohexane also increased component recoveries with sage and thyme. Acetone, acetonitrile and methanol did not increase PDMS recovery, while isooctane was excluded because of its interaction with the polymer. The results show that solvent‐modified PDMS extends the range of sampled headspace components with different polarities, increases the recovery of many of them, improves sensitivity in trace analysis, speeds up recovery and gives repeatability comparable with that of unmodified PDMS.

This study reports on the compatibility of a conventional quadrupole MS (qMS) as detector for Fast‐GC in terms of separation, identification, and quantitation when applied to the analysis of peppermint essential oil (e.o.), adopted as representative of this field. The influence of Fast‐GC carried out on a 10 m×0.1 mm id narrow bore column with temperature programmes from 20 to 60°C/min on the results of a qMS in total ion chromatograms (TIC) at different speeds (from 999 and 11 111 amu/s) and SIM modes was evaluated on ten differently abundant components characterizing peppermint e.o. Separation measure (S), peak capacity (n), and half height peak width were taken as separation parameters; match quality, number of scans per peak (NP), spectral skewing, and TIC area repeatability were used for identification. Quantitation was in SIM mode and NP, dwell time, SIM area repeatability and calibration curves, LOD, and LOQ of the selected components were measured. The results show that the peppermint e.o. markers can successfully be analysed qualitatively and quantitatively by F‐GC–qMS up to temperature programmes of 60°/min provided that a suitable scan speed is applied. Fast‐GC–qMS reduces analysis time by a factor greater than ten and gives results that are qualitatively reliable and quantitatively comparable to those obtained by conventional GC–qMS.

AbstractThe essential oil composition of seven Namibian Eriocephalusspecies (E. dinteri, E. ericoidessubsp. ericoides, E. klinghardtensis, E. luederitzianus, E. merxmuelleri, E. pinnatus, E. scariosus) were determined by GC and GC/MS. The oils of E. ericoidessubsp. ericoides(sample 1), E. merxmuelleriand E. scariosuswere found to be rich in 1,8-cineole and camphor. Eriocephalus scariosusoil contained santolina alcohol (14.8%). The highest levels of camphor (38.4%) was found in E. dinterioil. The major component of E. ericoidessubsp. ericoides(sample 2) was linalool (10.4%). A chemical similarity between E. luederitzianusand E. klinghardtensiswas observed which both accumulated high levels of α-pinene, β-pinene, p-cymene and γ-terpinene. Eriocephalus luederitzianusoil contained α-longipinene (10.3%) and β-caryophyllene (13.3%). The morphologically anomalous E. pinnatuswas very different in oil composition when compared to the other taxa and is characterized by isoamyl 2-methylbutyrate (7.9%) and isoamyl valerate (6.5%). Antimicrobial disc diffusion assays and minimum inhibitory concentrations (MIC) were performed on all seven species. Good antifungal activity was noted for E. ericoidessubsp. ericoides.Highest activities were noted for E. merxmuelleriagainst the Gram-positive test organisms and generally poor activity was noted against the Gram-negative test organisms for all species. The anti-inflammatory activity of the oils were assessed using the 5-lipoxygenase (5-LOX) enzyme and E. dinteridisplayed the most promising inhibition (IC50= 35 μg/ml).

Fruit and vegetable fibres resulting as by-products of the fruit juice industry have won popularity because they can be valorised as food ingredients. In this regard, bioactive compounds have already been studied but little attention has been paid to their remaining volatiles. Considering all the samples, 57 volatiles were identified. Composition greatly differed between citrus and noncitrus fibres. The former presented over 90% of terpenoids, with limonene being the most abundant and ranging from 52.7% in lemon to 94.0% in tangerine flesh. Noncitrus fibres showed more variable compositions, with the predominant classes being aldehydes in apple (57.5%) and peach (69.7%), esters (54.0%) in pear, and terpenoids (35.3%) in carrot fibres. In addition, enantioselective analysis of some of the chiral terpenoids present in the fibre revealed that the enantiomeric ratio for selected compounds was similar to the corresponding volatile composition of raw fruits and vegetables and some derivatives, with the exception of terpinen-4-ol and α-terpineol, which showed variation, probably due to the drying process. The processing to which fruit residues were submitted produced fibres with low volatile content for noncitrus products. Otherwise, citrus fibres analysed still presented a high volatile composition when compared with noncitrus ones.

Headspace (HS)-solid-phase microextraction (SPME) has assumed an ever increasing importance as a technique for HS sampling to study the composition of the HS of medicinal and aromatic plants. HS-SPME has mainly been applied for (a) studying the composition of the volatile fraction, including in addition to or as an alternative to other sampling techniques; (b) monitoring the biological phenomena involved with the volatile fraction of a plant; (c) discriminating between species, subspecies, varieties, cultivars, or chemotypes; and (d) quality control of plant samples. A review of 108 articles published during 2000–2005 is presented covering the use of HS-SPME in the field of aromatic and medicinal plants, selection of the most effective fiber and sampling conditions, comparison of HS-SPME and other volatile fraction sample preparation techniques, and the advantages and limits of HS-SPME when applied to medicinal and aromatic plants.