961 resultados para 3-PHASE JUNCTION
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Natural riversare consisting of various networks as junction andstreams. And sediment and erosion are occurred by specific stream condition. When flood season,large discharge flew in the river and river bed changed by high flow velocity. Especially junction area’s flow characteristics are very complex. The purpose of this study is to analyze the flow characteristics in channel junction, which are most influenced by large discharge like flooding and input water from tributary. We investigate the flow characteristics by using hydrodynamics and transport module in MIKE 3 FM. MIKE 3 FM model was helpful tool to analysis 3D hydrodynamics, erosion and sediment effect from channel bed. We analyze flow characteristics at channel junction. Also we consider hydraulic structures like a bridge pier which is influencing flow characteristics like a flow velocity, water level, erosion and scour depth in channel bed. In the model, we controlled discharge condition according to Froude Number and reflect various grain diameter size and flow ratio change in main stream and tributary. In the result, flow velocity, water level, erosion and sediment depth are analyzed. Additionally, we suggest a these result relationship with equations. This study will help the understand flow characteristics and influence of hydraulic structure in channel junction. Acknowledgments This research was supported by a grant (12-TI-C01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.
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Neste relatório apresentaremos a análise crítica do tema Paradoxos Organizacionais e apresentaremos 3 estudos de caso onde pode compreender a aplicação do conceito de paradoxos organizacionais em situações de mudanças organizacionais. Utilizaremos o paradigma da Sociologia Interpretativa em nossas análises, mais especificamente os trabalhos de Peter Berger e Thomas Luckmann e a metodologia Etnográfica para estudo de caso, conforme apresentado no corpo do trabalho.
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A dynamic headspace solid-phase microextraction (HS-SPME) and gas chromatography coupled to ion trap mass spectrometry (GC–ITMS) method was developed and applied for the qualitative determination of the volatile compounds present in commercial whisky samples which alcoholic content was previously adjusted to 13% (v/v). Headspace SPME experimental conditions, such as fibre coating, extraction temperature and extraction time, were optimized in order to improve the extraction process. Five different SPME fibres were used in this study, namely, poly(dimethylsiloxane)(PDMS),poly(acrylate)(PA),Carboxen-poly(dimethylsiloxane)(CAR/PDMS),Carbowax-divinylbenzene(CW/DVB)and Carboxen-poly(dimethylsiloxane)-divinylbenzene (CAR/PDMS/DVB). The best results were obtained using a 75 m CAR/PDMS fibre during headspace extraction at 40◦C with stirring at 750rpm for 60min, after saturating the samples with salt. The optimised methodology was then appliedtoinvestigatethevolatilecompositionprofileofthreeScotchwhiskysamples—BlackLabel,BallantinesandHighlandClan.Approximately seventy volatile compounds were identified in the these samples, pertaining at several chemical groups, mainly fatty acids ethyl esters, higher alcohols, fatty acids, carbonyl compounds, monoterpenols, C13 norisoprenoids and some volatile phenols. The ethyl esters form an essential group of aroma components in whisky, to which they confer a pleasant aroma, with “fruity” odours. Qualitatively, the isoamyl acetate, with “banana” aroma,wasthemostinteresting.Quantitatively,significantcomponentsareethylestersofcaprilic,capricandlauricacids.Thehighestconcentration of fatty acids, were observed for caprilic and capric acids. From the higher alcohols the fusel oils (3-methylbutan-1-ol and 2.phenyletanol) are the most important ones.
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The volatile composition from four types of multifloral Portuguese (produced in Madeira Island) honeys was investigated by a suitable analytical procedure based on dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography–quadrupole mass spectrometry detection (GC–qMS). The performance of five commercially available SPME fibres: 100 μm polydimethylsiloxane, PDMS; 85 μm polyacrylate, PA; 50/30 μm divinylbenzene/carboxen on polydimethylsiloxane, DVB/CAR/PDMS (StableFlex); 75 μm carboxen/polydimethylsiloxane, CAR/PDMS, and 65 μm carbowax/divinylbenzene, CW/DVB; were evaluated and compared. The highest amounts of extract, in terms of the maximum signal obtained for the total volatile composition, were obtained with a DVB/CAR/PDMS coating fibre at 60 °C during an extraction time of 40 min with a constant stirring at 750 rpm, after saturating the sample with NaCl (30%). Using this methodology more than one hundred volatile compounds, belonging to different biosynthetic pathways were identified, including monoterpenols, C13-norisoprenoids, sesquiterpenes, higher alcohols, ethyl esters and fatty acids. The main components of the HS-SPME samples of honey were in average ethanol, hotrienol, benzeneacetaldehyde, furfural, trans-linalool oxide and 1,3-dihydroxy-2-propanone.
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The analysis of volatile compounds in Funchal, Madeira, Mateus and Perry Vidal cultivars of Annona cherimola Mill. (cherimoya) was carried out by headspace solid-phase microextraction (HS-SPME) combined with gas chromatography–quadrupole mass spectrometry detection (GC–qMSD). HS-SPME technique was optimized in terms of fibre selection, extraction time, extraction temperature and sample amount to reach the best extraction efficiency. The best result was obtained with 2 g of sample, using a divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fibre for 30 min at 30 °C under constant magnetic stirring (800 rpm). After optimization of the extraction methodology, all the cherimoya samples were analysed with the best conditions that allowed to identify about 60 volatile compounds. The major compounds identified in the four cherimoya cultivars were methyl butanoate, butyl butanoate, 3-methylbutyl butanoate, 3-methylbutyl 3-methylbutanoate and 5-hydroxymethyl-2-furfural. These compounds represent 69.08 ± 5.22%, 56.56 ± 15.36%, 56.69 ± 9.28% and 71.82 ± 1.29% of the total volatiles for Funchal, Madeira, Mateus and Perry Vidal cultivars, respectively. This study showed that each cherimoya cultivars have 40 common compounds, corresponding to different chemical families, namely terpenes, esters, alcohols, fatty acids and carbonyl compounds and using PCA, the volatile composition in terms of average peak areas, provided a suitable tool to differentiate among the cherimoya cultivars.
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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.
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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.
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This paper reports on the development and optimization of a modified Quick, Easy, Cheap Effective, Rugged and Safe (QuEChERS) based extraction technique coupled with a clean-up dispersive-solid phase extraction (dSPE) as a new, reliable and powerful strategy to enhance the extraction efficiency of free low molecular-weight polyphenols in selected species of dietary vegetables. The process involves two simple steps. First, the homogenized samples are extracted and partitioned using an organic solvent and salt solution. Then, the supernatant is further extracted and cleaned using a dSPE technique. Final clear extracts of vegetables were concentrated under vacuum to near dryness and taken up into initial mobile phase (0.1% formic acid and 20% methanol). The separation and quantification of free low molecular weight polyphenols from the vegetable extracts was achieved by ultrahigh pressure liquid chromatography (UHPLC) equipped with a phodiode array (PDA) detection system and a Trifunctional High Strength Silica capillary analytical column (HSS T3), specially designed for polar compounds. The performance of the method was assessed by studying the selectivity, linear dynamic range, the limit of detection (LOD) and limit of quantification (LOQ), precision, trueness, and matrix effects. The validation parameters of the method showed satisfactory figures of merit. Good linearity (View the MathML sourceRvalues2>0.954; (+)-catechin in carrot samples) was achieved at the studied concentration range. Reproducibility was better than 3%. Consistent recoveries of polyphenols ranging from 78.4 to 99.9% were observed when all target vegetable samples were spiked at two concentration levels, with relative standard deviations (RSDs, n = 5) lower than 2.9%. The LODs and the LOQs ranged from 0.005 μg mL−1 (trans-resveratrol, carrot) to 0.62 μg mL−1 (syringic acid, garlic) and from 0.016 μg mL−1 (trans-resveratrol, carrot) to 0.87 μg mL−1 ((+)-catechin, carrot) depending on the compound. The method was applied for studying the occurrence of free low molecular weight polyphenols in eight selected dietary vegetables (broccoli, tomato, carrot, garlic, onion, red pepper, green pepper and beetroot), providing a valuable and promising tool for food quality evaluation.
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Hop(HumuluslupulusL.,Cannabaceaefamily)isprizedforitsessentialoilcontents,usedin beer production and, more recently, in biological and pharmacological applications. In this work,a methodinvolvingheadspace solid-phase microextractionand gas chromatography– mass spectrometry was developed and optimized to establish the terpenoid (monoterpenes and sesquiterpenes) metabolomic pattern of hop-essential oil derived from Saaz variety as a mean to explore this matrix as a powerful biological source for newer, more selective, biodegradable and naturally produced antimicrobial and antioxidant compounds. Different parameters affecting terpenoid metabolites extraction by headspace solid-phase microextraction were considered and optimized: type of fiber coatings, extraction temperature, extraction time, ionic strength, and sample agitation. In the optimized method, analytes were extracted for 30 min at 40 C in the sample headspace with a 50/30 m divinylbenzene/carboxen/polydimethylsiloxane coating fiber. The methodology allowed the identification of a total of 27 terpenoid metabolites, representing 92.5% of the total Saaz hop-essential oil volatile terpenoid composition. The headspace composition was dominated by monoterpenes (56.1%, 13 compounds), sesquiterpenes (34.9%, 10), oxygenated monoterpenes (1.41%, 3), and hemiterpenes (0.04%, 1) some of which can probably contribute to the hop of Saaz variety aroma. Mass spectrometry analysis revealed that the main metabolites are the monoterpene -myrcene (53.0±1.1% of the total volatile fraction), and the cyclic sesquiterpenes, -humulene (16.6 ± 0.8%), and -caryophyllene (14.7 ± 0.4%), which together represent about 80% of the total volatile fraction from the hop-essential oil. Thesefindingssuggestthatthismatrixcanbeexploredasapowerfulbiosourceofterpenoid metabolites.
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In this study the feasibility of different extraction procedures was evaluated in order to test their potential for the extraction of the volatile (VOCs) and semi-volatile constituents (SVOCs) from wines. In this sense, and before they could be analysed by gas chromatography–quadrupole first stage masss spectrometry (GC–qMS), three different high-throughput miniaturized (ad)sorptive extraction techniques, based on solid phase extraction (SPE), microextraction by packed sorbents (MEPS) and solid phase microextraction (SPME), were studied for the first time together, for the extraction step. To achieve the most complete volatile and semi-volatile signature, distinct SPE (LiChrolut EN, Poropak Q, Styrene-Divinylbenzene and Amberlite XAD-2) and MEPS (C2, C8, C18, Silica and M1 (mixed C8-SCX)) sorbent materials, and different SPME fibre coatings (PA, PDMS, PEG, DVB/CAR/PDMS, PDMS/DVB, and CAR/PDMS), were tested and compared. All the extraction techniques were followed by GC–qMS analysis, which allowed the identification of up to 103 VOCs and SVOCs, distributed by distinct chemical families: higher alcohols, esters, fatty acids, carbonyl compounds and furan compounds. Mass spectra, standard compounds and retention index were used for identification purposes. SPE technique, using LiChrolut EN as sorbent (SPELiChrolut EN), was the most efficient method allowing for the identification of 78 VOCs and SVOCs, 63 and 19 more than MEPS and SPME techniques, respectively. In MEPS technique the best results in terms of number of extractable/identified compounds and total peak areas of volatile and semi-volatile fraction, were obtained by using C8 resin whereas DVB/CAR/PDMS was revealed the most efficient SPME coating to extract VOCs and SVOCs from Bual wine. Diethyl malate (18.8 ± 3.2%) was the main component found in wine SPELiChrolut EN extracts followed by ethyl succinate (13.5 ± 5.3%), 3-methyl-1-butanol (13.2 ± 1.7%), and 2-phenylethanol (11.2 ± 9.9%), while in SPMEDVB/CAR/PDMS technique 3-methyl-1-butanol (43.3 ± 0.6%) followed by diethyl succinate (18.9 ± 1.6%), and 2-furfural (10.4 ± 0.4%), are the major compounds. The major VOCs and SVOCs isolated by MEPSC8 were 3-methyl-1-butanol (26.8 ± 0.6%, from wine total volatile fraction), diethyl succinate (24.9 ± 0.8%), and diethyl malate (16.3 ± 0.9%). Regardless of the extraction technique, the highest extraction efficiency corresponds to esters and higher alcohols and the lowest to fatty acids. Despite some drawbacks associated with the SPE procedure such as the use of organic solvents, the time-consuming and tedious sampling procedure, it was observed that SPELiChrolut EN, revealed to be the most effective technique allowing the extraction of a higher number of compounds (78) rather than the other extraction techniques studied.
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A sensitive assay to identify volatile organic metabolites (VOMs) as biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. Therefore the aim of this study was to establish the urinary metabolomic profile of breast cancer patients and healthy individuals (control group) and to explore the VOMs as potential biomarkers in breast cancer diagnosis at early stage. Solid-phase microextraction (SPME) using CAR/PDMS sorbent combined with gas chromatography–mass spectrometry was applied to obtain metabolomic information patterns of 26 breast cancer patients and 21 healthy individuals (controls). A total of seventy-nine VOMs, belonging to distinct chemical classes, were detected and identified in control and breast cancer groups. Ketones and sulfur compounds were the chemical classes with highest contribution for both groups. Results showed that excretion values of 6 VOMs among the total of 79 detected were found to be statistically different (p < 0.05). A significant increase in the peak area of (−)-4-carene, 3-heptanone, 1,2,4-trimethylbenzene, 2-methoxythiophene and phenol, in VOMs of cancer patients relatively to controls was observed. Statiscally significant lower abundances of dimethyl disulfide were found in cancer patients. Bioanalytical data were submitted to multivariate statistics [principal component analysis (PCA)], in order to visualize clusters of cases and to detect the VOMs that are able to differentiate cancer patients from healthy individuals. Very good discrimination within breast cancer and control groups was achieved. Nevertheless, a deep study using a larger number of patients must be carried out to confirm the results.
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The volatile composition of different apple varieties of Malus domestica Borkh. species from different geographic regions at Madeira Islands, namely Ponta do Pargo (PP), Porto Santo (PS), and Santo da Serra (SS) was established by headspace solid-phase microextraction (HS-SPME) procedure followed by GC-MS (GC-qMS) analysis. Significant parameters affecting sorption process such as fiber coating, extraction temperature,extractiontime,sampleamount,dilutionfactor,ionicstrength,anddesorption time,wereoptimizedanddiscussed.TheSPMEfibercoatedwith50/30 lmdivinylbenzene/carboxen/PDMS (DVB/CAR/PDMS) afforded highest extraction efficiency of volatile compounds, providing the best sensitivity for the target volatiles, particularly whenthesampleswereextractedat508Cfor30 minwithconstantmagneticstirring. A qualitative and semi-quantitative analysis between the investigated apple species has been established. It was possible to identify about 100 of volatile compounds amongpulp(46,45,and39),peel(64,60,and64),andentirefruit(65,43,and50)inPP, PS,andSSapples,respectively.Ethylesters,terpenes,andhigheralcoholswerefound tobethemostrepresentativevolatiles. a-Farnesene,hexan-1-olandhexyl2-methylbutyratewerethecompoundsfoundinthevolatileprofileofstudiedappleswiththelargestGCarea,representing,onaverage,24.71,14.06,and10.80%ofthetotalvolatilefractionfromPP,PS,andSSapples.InPPentireapple,themostabundantcompoundsidentified were a-farnesene (30.49%), the unknown compound m/z (69, 101, 157) (21.82%) andhexylacetate(6.57%).RegardingPSentireapplethemajorcompoundswere a-farnesene(16.87%),estragole(15.43%),hexan-1-ol(10.94),andE-2-hexenal(10.67).a-Farnesene(30.3%),hexan-1-ol(18.90%),2-methylbutanoicacid(4.7%),andpentan-1-ol(4.6%) werealsofoundasSSentireapplevolatilespresentinahigherrelativecontent.Principal component analysis (PCA) of the results clustered the apples into three groups according to geographic origin. Linear discriminant analysis (LDA) was performed in order to detect the volatile compounds able to differentiate the three kinds of apples investigated. The most important contributions to the differentiation of the PP, PS, and SS apples were ethyl hexanoate, hexyl 2-methylbutyrate, E,E-2,4-heptadienal, pethylstyrene,andE-2-hexenal.
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A stir bar sorptive extraction with liquid desorption followed by large volume injection coupled to gas chromatography–quadrupole mass spectrometry (SBSE-LD/LVI-GC–qMS) was evaluated for the simultaneous determination of higher alcohol acetates (HAA), isoamyl esters (IsoE) and ethyl esters (EE) of fatty acids. The method performance was assessed and compared with other solventless technique, the solid-phase microextraction (SPME) in headspace mode (HS). For both techniques, influential experimental parameters were optimised to provide sensitive and robust methods. The SBSE-LD/LVI methodology was previously optimised in terms of extraction time, influence of ethanol in the matrix, liquid desorption (LD) conditions and instrumental settings. Higher extraction efficiency was obtained using 60 min of extraction time, 10% ethanol content, n-pentane as desorption solvent, 15 min for the back-extraction period, 10 mL min−1 for the solvent vent flow rate and 10 °C for the inlet temperature. For HS-SPME, the fibre coated with 50/30 μm divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) afforded highest extraction efficiency, providing the best sensitivity for the target volatiles, particularly when the samples were extracted at 25 °C for 60 min under continuous stirring in the presence of sodium chloride (10% (w/v)). Both methodologies showed good linearity over the concentration range tested, with correlation coefficients higher than 0.984 for HS-SPME and 0.982 for SBES-LD approach, for all analytes. A good reproducibility was attained and low detection limits were achieved using both SBSE-LD (0.03–28.96 μg L−1) and HS-SPME (0.02–20.29 μg L−1) methodologies. The quantification limits for SBSE-LD approach ranging from 0.11 to 96.56 μg L−and from 0.06 to 67.63 μg L−1 for HS-SPME. Using the HS-SPME approach an average recovery of about 70% was obtained whilst by using SBSE-LD obtained average recovery were close to 80%. The analytical and procedural advantages and disadvantages of these two methods have been compared. Both analytical methods were used to determine the HAA, IsoE and EE fatty acids content in “Terras Madeirenses” table wines. A total of 16 esters were identified and quantified from the wine extracts by HS-SPME whereas by SBSE-LD technique were found 25 esters which include 2 higher alcohol acetates, 4 isoamyl esters and 19 ethyl esters of fatty acids. Generally SBSE-LD provided higher sensitivity with decreased analysis time.
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A RP-HPLC method with photodiode array detection (DAD) was developed to separate, identify and quantify simultaneously the most representative phenolic compounds present in Madeira and Canary Islands wines. The optimized chromatographic method was carefully validated in terms of linearity, precision, accuracy and sensitivity. A high repeatability and a good stability of phenolics retention times (a3%) were obtained, as well as relative peak area. Also high recoveries were achieved, over 80.3%. Polyphenols calibration curves showed a good linearity (r2 A0.994) within test ranges. Detection limits ranged between 0.03 and 11.5 lg/mL for the different polyphenols. A good repeatability was obtained, with intra-day variations less than 7.9%. The described method was successfully applied to quantify several polyphenols in 26 samples of different kinds of wine (red, ros and white wines) from Madeira and Canary Islands. Gallic acid was by far the most predominant acid. It represents more than 65% of all phenolics, followed by p-coumaric and caffeic acids. The major flavonoid found in Madeira wines was trans-resveratrol. In some wines, (–)-epicatechin was also found in highest amount. Canary wines were shown to be rich in gallic, caffeic and p-coumaric acids and quercetin.
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The establishment of potential age markers of Madeira wine is of paramount significance as it may contribute to detect frauds and to ensure the authenticity of wine. Considering the chemical groups of furans, lactones, volatile phenols, and acetals, 103 volatile compounds were tentatively identified; among these, 71 have been reported for the first time in Madeira wines. The chemical groups that could be used as potential age markers were predominantly acetals, namely, diethoxymethane, 1,1-diethoxyethane, 1,1-diethoxy-2-methyl-propane, 1-(1-ethoxyethoxy)-pentane, trans-dioxane and 2-propyl-1,3-dioxolane, and from the other chemical groups, 5-methylfurfural and cis-oak-lactone, independently of the variety and the type of wine. GC × GC-ToFMS system offers a more useful approach to identify these compounds compared to previous studies using GC−qMS, due to the orthogonal systems, that reduce coelution, increase peak capacity and mass selectivity, contributing to the establishment of new potential Madeira wine age markers. Remarkable results were also obtained in terms of compound identification based on the organized structure of the peaks of structurally related compounds in the GC × GC peak apex plots. This information represents a valuable approach for future studies, as the ordered-structure principle can considerably help the establishment of the composition of samples. This new approach provides data that can be extended to determine age markers of other types of wines.