Development of a dynamic headspace solid-phase microextraction procedure coupled to GC–qMSD for evaluation the chemical profile in alcoholic beverages

In the present study, a simple and sensitive methodology based on dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography with quadrupole mass detection (GC–qMSD), was developed and optimized for the determination of volatile (VOCs) and semi-volatile (SVOCs) compounds from different alcoholic beverages: wine, beer and whisky. Key experimental factors influencing the equilibrium of the VOCs and SVOCs between the sample and the SPME fibre, as the type of fibre coating, extraction time and temperature, sample stirring and ionic strength, were optimized. The performance of five commercially available SPME fibres was evaluated and compared, namely polydimethylsiloxane (PDMS, 100 μm); polyacrylate (PA, 85 μm); polydimethylsiloxane/divinylbenzene (PDMS/DVB, 65 μm); carboxen™/polydimethylsiloxane (CAR/PDMS, 75 μm) and the divinylbenzene/carboxen on polydimethylsiloxane (DVB/CAR/PDMS, 50/30 μm) (StableFlex). An objective comparison among different alcoholic beverages has been established in terms of qualitative and semi-quantitative differences on volatile and semi-volatile compounds. These compounds belong to several chemical families, including higher alcohols, ethyl esters, fatty acids, higher alcohol acetates, isoamyl esters, carbonyl compounds, furanic compounds, terpenoids, C13-norisoprenoids and volatile phenols. The optimized extraction conditions and GC–qMSD, lead to the successful identification of 44 compounds in white wines, 64 in beers and 104 in whiskys. Some of these compounds were found in all of the examined beverage samples. The main components of the HS-SPME found in white wines were ethyl octanoate (46.9%), ethyl decanoate (30.3%), ethyl 9-decenoate (10.7%), ethyl hexanoate (3.1%), and isoamyl octanoate (2.7%). As for beers, the major compounds were isoamyl alcohol (11.5%), ethyl octanoate (9.1%), isoamyl acetate (8.2%), 2-ethyl-1-hexanol (5.9%), and octanoic acid (5.5%). Ethyl decanoate (58.0%), ethyl octanoate (15.1%), ethyl dodecanoate (13.9%) followed by 3-methyl-1-butanol (1.8%) and isoamyl acetate (1.4%) were found to be the major VOCs in whisky samples.

Effectiveness of different solid-phase microextraction fibres for differentiation of selected Madeira island fruits based on their volatile metabolite profile: identification of novel compounds

A headspace solid-phase microextraction (HS-SPME) procedure based on five commercialised fibres (85 μm polyacrylate – PA, 100 μm polydimethylsiloxane – PDMS, 65 μm polydimethylsiloxane/divinylbenzene – PDMS/DVB, 70 μm carbowax/divinylbenzene – CW/DVB and 85 μm carboxen/polydimethylsiloxane – CAR/PDMS) is presented for the characterization of the volatile metabolite profile of four selected Madeira island fruit species, lemon (Citrus limon), kiwi (Actinidia deliciosa), papaya (Carica papaya L.) and Chickasaw plum (Prunus angustifolia). The isolation of metabolites was followed by thermal desorption gas chromatography–quadrupole mass spectrometry (GC–qMS) methodology. The performance of the target fibres was evaluated and compared. The SPME fibre coated with CW/DVB afforded the highest extraction efficiency in kiwi and papaya pulps, while in lemon and plum the same was achieved with PMDS/DVB fibre. This procedure allowed for the identification of 80 compounds, 41 in kiwi, 24 in plums, 23 in papaya and 20 in lemon. Considering the best extraction conditions, the most abundant volatiles identified in kiwi were the intense aldehydes and ethyl esters such as (E)-2-hexenal and ethyl butyrate, while in Chicasaw plum predominate 2-hexenal, 2-methyl-4-pentenal, hexanal, (Z)-3-hexenol and cyclohexylene oxide. The major compounds identified in the papaya pulp were benzyl isothiocyanate, linalool oxide, furfural, hydroxypropanone, linalool and acetic acid. Finally, lemon was shown to be the most divergent of the four fruits, being its aroma profile composed almost exclusively by terpens, namely limonene, γ-terpinene, o-cymene and α-terpinolene. Thirty two volatiles were identified for the first time in the fruit or close related species analysed and 14 volatiles are reported as novel volatile metabolites in fruits. This includes 5 new compounds in kiwi (2-cyclohexene-1,4-dione, furyl hydroxymethyl ketone, 4-hydroxydihydro-2(3H)-furanone, 5-acetoxymethyl-2-furaldehyde and ethanedioic acid), 4 in plum (4-hydroxydihydro-2(3H)-furanone, 5-methyl-2-pyrazinylmethanol, cyclohexylene oxide and 1-methylcyclohexene), 4 in papaya (octaethyleneglycol, 1,2-cyclopentanedione, 3-methyl-1,2-cyclopentanedione and 2-furyl methyl ketone) and 2 in lemon (geranyl farnesate and safranal). It is noteworthy that among the 15 volatile metabolites identified in papaya, 3-methyl-1,2-cyclopentanedione was previously described as a novel PPARγ (peroxisome proliferator-activated receptor γ) agonist, having a potential to minimize inflammation.

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.

Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography–mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile

In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.

Development of a novel microextraction by packed sorbent-based approach followed by ultrahigh pressure liquid chromatography as a powerful technique for quantification phenolic constituents of biological interest in wines

A novel analytical approach, based on a miniaturized extraction technique, the microextraction by packed sorbent (MEPS), followed by ultrahigh pressure liquid chromatography (UHPLC) separation combined with a photodiode array (PDA) detection, has been developed and validated for the quantitative determination of sixteen biologically active phenolic constituents of wine. In addition to performing routine experiments to establish the validity of the assay to internationally accepted criteria (linearity, sensitivity, selectivity, precision, accuracy), experiments are included to assess the effect of the important experimental parameters on the MEPS performance such as the type of sorbent material (C2, C8, C18, SIL, and M1), number of extraction cycles (extract-discard), elution volume, sample volume, and ethanol content, were studied. 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). The wine bioactive phenolics were eluted by 250 μL of the mixture containing 95% methanol and 5% water, and the separation was carried out on a HSS T3 analytical column (100 mm × 2.1 mm, 1.8 μm particle size) using a binary mobile phase composed of aqueous 0.1% formic acid (eluent A) and methanol (eluent B) in the gradient elution mode (10 min of total analysis). The method gave satisfactory results in terms of linearity with r2-values > 0.9986 within the established concentration range. The LOD varied from 85 ng mL−1 (ferulic acid) to 0.32 μg mL−1 ((+)-catechin), whereas the LOQ values from 0.028 μg mL−1 (ferulic acid) to 1.08 μg mL−1 ((+)-catechin). Typical recoveries ranged between 81.1 and 99.6% for red wines and between 77.1 and 99.3% for white wines, with relative standard deviations (RSD) no larger than 10%. The extraction yields of the MEPSC8/UHPLC–PDA methodology were found between 78.1 (syringic acid) and 99.6% (o-coumaric acid) for red wines and between 76.2 and 99.1% for white wines. The inter-day precision, expressed as the relative standard deviation (RSD%), varied between 0.2% (p-coumaric and o-coumaric acids) and 7.5% (gentisic acid) while the intra-day precision between 0.2% (o-coumaric and cinnamic acids) and 4.7% (gallic acid and (−)-epicatechin). On the basis of analytical validation, it is shown that the MEPSC8/UHPLC–PDA methodology proves to be an improved, reliable, and ultra-fast approach for wine bioactive phenolics analysis, because of its capability for determining simultaneously in a single chromatographic run several bioactive metabolites with high sensitivity, selectivity and resolving power within only 10 min. Preliminary studies have been carried out on 34 real whole wine samples, in order to assess the performance of the described procedure. The new approach offers decreased sample preparation and analysis time, and moreover is cheaper, more environmentally friendly and easier to perform as compared to traditional methodologies.

Simultaneous analysis of free amino acids and biogenic amines in honey and wine samples using in loop orthophthalaldeyde derivatization procedure

This work presents a RP-HPLC method for the simultaneous quantification of free amino acids and biogenic amines in liquid food matrices and the results of the application to honey and wine samples obtained from different production processes and geographic origins. The developed methodology is based on a pre-column derivatization with o-phthaldialdehyde carried out in the sample injection loop. The compounds were separated in a Nova-Pack RP-C18 column (150 mm × 3.9 mm, 4 μm) at 35 °C. The mobile phase used was a mixture of phase A: 10 mM sodium phosphate buffer (pH 7.3), methanol and tetrahydrofuran (91:8:1); and phase B: methanol and phosphate buffer (80:20), with a flow rate of 1.0 ml/min. Fluorescence detection was used at an excitation wavelength of 335 nm and an emission wavelength of 440 nm. The separation and quantification of 19 amino acids and 6 amines was carried out in a single run as their OPA/MCE derivatives elute within 80 min, ensuring a reproducible quantification. The method showed to be adequate for the purpose, with an average RSD of 2% for the different amino acids; detection limits varying between 0.71 mg/l (Asn) and 8.26 mg/l (Lys) and recovery rates between 63.0% (Cad) and 98.0% (Asp). The amino acids present at the highest concentration in honey and wine samples were phenylalanine and arginine, respectively. Only residual levels of biogenic amines were detected in the analysed samples.