Comparison of two extraction methods for evaluation of volatile constituents patterns in commercial whiskeys: Elucidation of the main odour-active compounds

An analytical procedure based on manual dynamic headspace solid-phase microextraction (HS-SPME) method and the conventional extraction method by liquid–liquid extraction (LLE), were compared for their effectiveness in the extraction and quantification of volatile compounds from commercial whiskey samples. Seven extraction solvents covering a wide range of polarities and two SPME fibres coatings, has been evaluated. The highest amounts extracted, were achieved using dichloromethane (CH2Cl2) by LLE method (LLECH2Cl2)(LLECH2Cl2) and using a CAR/PDMS fibre (SPMECAR/PDMS) in HS-SPME. Each method was used to determine the responses of 25 analytes from whiskeys and calibration standards, in order to provide sensitivity comparisons between the two methods. Calibration curves were established in a synthetic whiskey and linear correlation coefficient (r ) were greater than 0.9929 for LLECH2Cl2LLECH2Cl2 and 0.9935 for SPMECAR/PDMS, for all target compounds. Recoveries greater than 80% were achieved. For most compounds, precision (expressed by relative standard deviation, R.S.D.) are very good, with R.S.D. values lower than 14.78% for HS-SPME method and than 19.42% for LLE method. The detection limits ranged from 0.13 to 19.03 μg L−1 for SPME procedure and from 0.50 to 12.48 μg L−1 for LLE. A tentative study to estimate the contribution of a specific compound to the aroma of a whiskey, on the basis of their odour activity values (OAV) was made. Ethyl octanoate followed by isoamyl acetate and isobutyl alcohol, were found the most potent odour-active compounds.

A sensitive microextraction by packed sorbent-based methodology combined with ultra-high pressure liquid chromatography as a powerful technique for analysis of biologically active flavonols in wines

A new approach based on microextraction by packed sorbent (MEPS) and reversed-phase high-throughput ultra high pressure liquid chromatography (UHPLC) method that uses a gradient elution and diode array detection to quantitate three biologically active flavonols in wines, myricetin, quercetin, and kaempferol, is described. In addition to performing routine experiments to establish the validity of the assay to internationally accepted criteria (selectivity, linearity, sensitivity, precision, accuracy), experiments are included to assess the effect of the important experimental parameters such as the type of sorbent material (C2, C8, C18, SIL, and C8/SCX), number of extraction cycles (extract-discard), elution volume, sample volume, and ethanol content, on the MEPS performance. The optimal conditions of MEPS extraction were obtained using C8 sorbent and small sample volumes (250 μL) in five extraction cycle and in a short time period (about 5 min for the entire sample preparation step). Under optimized conditions, excellent linearity View the MathML source(Rvalues2>0.9963), limits of detection of 0.006 μg mL−1 (quercetin) to 0.013 μg mL−1 (myricetin) and precision within 0.5–3.1% were observed for the target flavonols. The average recoveries of myricetin, quercetin and kaempferol for real samples were 83.0–97.7% with relative standard deviation (RSD, %) lower than 1.6%. The results obtained showed that the most abundant flavonol in the analyzed samples was myricetin (5.8 ± 3.7 μg mL−1). Quercetin (0.97 ± 0.41 μg mL−1) and kaempferol (0.66 ± 0.24 μg mL−1) were found in a lower concentration. The optimized MEPSC8 method was compared with a reverse-phase solid-phase extraction (SPE) procedure using as sorbent a macroporous copolymer made from a balanced ratio of two monomers, the lipophilic divinylbenzene and the hydrophilic N-vinylpyrrolidone (Oasis HLB) were used as reference. MEPSC8 approach offers an attractive alternative for analysis of flavonols in wines, providing a number of advantages including highest extraction efficiency (from 85.9 ± 0.9% to 92.1 ± 0.5%) in the shortest extraction time with low solvent consumption, fast sample throughput, more environmentally friendly and easy to perform.