12 resultados para SPME-GC-MS
em Reposit
Resumo:
Recently, ethyl carbamate (EC) was reclassified by the International Agency for Research on Cancer (IARC) as "probably carcinogenic to humans" and occurs mainly in fermented beverages. Nowadays many countries have set limit values for EC in alcoholic beverages. In this sense and taking into account the low concentrations found in alcoholic beverages, the scientific community has shown interest for the development of new analytical methods, whereby its simplification plays an important role in the EC control and prevention. Firstly, a simple, rapid and sensitive methodology was developed for the EC quantification in fortified wines by microextraction by packed sorbent (MEPS) with gas chromatography coupled with a mass spectrometer detector (GC-MS). This method showed good linearity (R2 = 0.999) and sensitivity (LOD = 1.5 μg/L). The accuracy of the method was assessed by means of repeatability and reproducibility (RSD < 7%). Moreover, a good recovery has been demonstrated (97 – 106%) as well as its applicability (16 fortified wines). Thus, the developed methodology has proven to be an excellent approach for routine quantification of EC in fortified wines. The EC evolution was also evaluated during a year and half of Madeira wine ageing submitted to two traditional ageing methods, estufagem and canteiro, in order to evaluate the formation kinetic. The results revealed that estufagem process increased the formation kinetic and promoted a linear increase of the EC concentration (R2 ≥ 0.977), proportionally to the ageing time (4 months). However, when the wines are firstly submitted to estufagem and then undergo canteiro ageing, the EC values remain almost constant during the following 14 months. The results suggest that estufagem does not seem to be the critical factor in the EC formation, but instead the amount of precursors in the medium.
Resumo:
In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.
Resumo:
Com este trabalho pretendeu-se estabelecer o perfil metabolómico volátil de amostras de fluidos biológicos, nomeadamente saliva e urina, de pacientes com cancro da mama e do pulmão e de indivíduos saudáveis (grupo controlo), utilizando a Microextração em Fase Sólida em modo headspace (HS-SPME) seguida de Cromatografia Gasosa acoplada à Espectrometria de Massa (GC-MS). Efetuou-se a comparação entre os perfis voláteis dos grupos estudados com o objetivo de identificar metabolitos que possam ser considerados como potenciais biomarcadores dos tipos de cancro em estudo. De modo a otimizar a metodologia extrativa, HS-SPME, foram avaliados os diferentes parâmetros experimentais com influência no processo extrativo. Os melhores resultados foram obtidos com a fibra CAR/PDMS, usando um volume de 2 mL de saliva acidificada, 10% NaCl (m/v) e 45 minutos de extração a uma temperatura de 37±1°C. Para a urina foi utilizada a mesma fibra, 4 mL de urina acidificada, 20% NaCl (m/v) e 60 minutos de extração a 50±1°C. Nas amostras de saliva e urina, foram identificados 243 e 500 metabolitos voláteis respetivamente, sendo estes pertencentes a diferentes famílias químicas. Posteriormente, utilizou-se a análise discriminante por mínimos quadrados parciais (PLS-DA) que permitiu observar uma boa separação entre os grupos controlo e oncológicos. Nas amostras salivares o grupo de pacientes com cancro da mama foi maioritariamente caracterizado pelo metabolito ácido benzeno carboxílico e o grupo de pacientes com cancro do pulmão pelo ácido hexanóico. Na urina o grupo de pacientes com cancro da mama foi maioritariamente caracterizado pelo metabolito 1-[2-(Isobutiriloxi)-1-metiletil]-2,2-dimetilpropil 2-metilpropanoato e o grupo de pacientes com cancro do pulmão pelo o-cimeno. Além da metodologia PLS-DA foi realizada a validação cruzada de monte carlo (MCCV) tendo-se obtido uma elevada taxa de classificação, sensibilidade e especificidade o que demonstra a robustez dos dados obtidos.
Resumo:
The present study was done in collaboration with J. Faria e Filhos company, a Madeira wine producer, and its main goal was to fully characterize three wines produced during 2014 harvest and identify possible improving points in the winemaking process. The winemaking process was followed during 4 weeks, being registered the amounts of grapes received, the fermentation temperatures, the time at which fermentation was stopped and evolution of must densities until the fortification time. The characterization of musts and wines was done in terms of density, total and volatile acidity, alcohol content, pH, total of polyphenol, organic acids composition, sugars concentration and the volatile profile. Also, it was developed and validated an analytical methodology to quantify the volatile fatty acids, namely using SPME-GC-MS. Briefly, the following key features were obtained for the latter methodology: linearity (R2=0.999) e high sensitivity (LOD =0.026-0.068 mg/L), suitable precision (repeatability and reproducibility lower than 8,5%) and good recoveries (103,11-119,46%). The results reveal that fermentation temperatures should be controlled in a more strictly manner, in order to ensure a better balance in proportion of some volatile compounds, namely the esters and higher alcohols and to minimize the concentration of some volatiles, namely hexanoic, octanoic and decanoic acids, that when above their odours threshold are not positive for the wine aroma. Also, regarding the moment to stop the fermentation, it was verified that it can be introduced changes which can also be benefit to guarantee the tipicity of Madeira wine bouquet.
Resumo:
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.
Resumo:
Madeira wine is a fortified wine with impact in the Madeira Island’s economy. Similarly to other wines, its acidity should be well controlled in order to ensure Madeira wine quality, mostly the volatile acidity. Due to Madeira wine complex flavour, it is crucial to get a better knowledge about the volatile acidity impact in its features, namely determine the perception limit of acetic acid and ethyl acetate, as both are the main contributors for volatile acidity. Firstly, the olfactory perception threshold of volatile acidity was assessed by a trained and an untrained panel, using 5 and 10 years-old Sercial and Malvasia wines. Moreover, the current work also presents the evolution of organic acids, acetic acid and ethyl acetate during 540 days of ageing of Madeira wines (Malvasia, Bual, Verdelho and Sercial), comparing the same wines aged by both traditional ageing processes: canteiro and estufagem. Other wine samples, aged in wood casks (canteiro) for at least 5 years, were also evaluated. HS-SPME followed by GC-MS analysis was used to determine ethyl acetate concentration and IEC-HPLC-DAD was used for the organic acids determination, including acetic acid. The results indicated that acetic acid and ethyl acetate olfactory perception threshold depends essentially on wine’s age. Concerning acetic acid, the untrained panel was in average 5.45 g/L (5 years-old) and 6.22 g/L (10 years-old). Training the expert panel to recognize acetic acid odour, the values decreased for 1.44 g/L (5 years-old) and 1.87 g/L (10 years-old), but still remained higher than the established volatile acidity legal limits. Ethyl acetate threshold was similar for both panels (in average 327.97 mg/L). Both compounds tend to increase exponentially with age, being more evident in sweet wines. Organic acids in young Madeira wines depend mostly on the nature of grape varieties, but this difference is minimized with wine ageing.
Resumo:
BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.
Resumo:
Com a realização deste trabalho, pretendeu-se traçar o perfil padrão da composição volátil típico de fluidos biológicos (urina) de indivíduos sem patologia oncológica (grupo de controlo) comparando-os com os de pacientes (grupo com patologia oncológica). As amostras de urina de ambos os grupos foram analisadas por microextracção em fase sólida em modo de headspace acoplada à espectrometria de massa (HS-SPME-GC/qMS). Com o intuito de aumentar a eficiência de extracção da SPME, foram optimizados alguns parâmetros com influência no processo extractivo, nomeadamente o tipo de fibra, o tempo e a temperatura de extracção. Assim sendo, foram testadas e comparadas seis fibras comercialmente disponíveis, polidimetilsiloxano (PDMS, 100 m), poliacrilato (PA, 85 m), carboxeno-polidimetilsiloxano (CAR/PDMS, 75 m), carbowax-divinilbenzeno (CW/DVB, 65 m), divinilbenzeno-carboxen-polidimetilsiloxano (DVB/CAR/PDMS, 50/30 m) e polidimetilsiloxano-divinilbenzeno (PDMS/DVB, 65 m). A influência do tempo (30, 45, 60 e 75 min) e temperatura (30, 50 e 60 ºC) de extracção foram optimizados de modo a obter uma melhor eficiência de extracção dos compostos voláteis presentes nas amostras de urina. Os melhores resultados foram obtidos usando a fibra carboxeno-polidimetilsiloxano (CAR/PDMS, 75 m), com uma velocidade de agitação de 800 rpm durante 75 min a uma temperatura de 50 ºC. Para os dois grupos em estudo, foram identificados 80 compostos voláteis pertencentes a diversas famílias químicas, nomeadamente, aldeídos, cetonas, derivados benzénicos, compostos terpénicos, ácidos orgânicos, compostos furânicos, compostos sulfurados, fenóis voláteis, ésteres, álcoois superiores e derivados do naftaleno. Os compostos maioritários pertencentes aos grupos analisados foram a 4-heptanona, a 2-pentanona, a acetona, a 2-butanona, o 1(2- furanil)etanona, o 3-metil-3-fenil-2-propenal, o 3,4-dimetilbenzaldeído, o decanal, o dissulfureto de dimetilo, o metanotiol, o 2-metoxitiofeno, o 4-metil-fenol, o p-tert-butil-fenol, o 2,4-bis(1,1- dimetiletil)fenol, o fenol, o m-cimeno, o p-cimeno, o tolueno, o 1-etil-3,5-diisopropilbenzeno, o 2,6-dimetil-7-octen-2-ol, a D-carvona, o vitispirano I e o vitispirano II. O teste One-Way ANOVA foi aplicado aos resultados com o intuito de verificar se existiam diferenças significativas entre os grupos avaliados (Controlo e Oncológico), sendo o dissulfureto de dimetilo, o 2-metoxitiofeno, e o p-cimeno estatisticamente significativos. A aplicação da análise multivariável às amostras de urina das diferentes patologias permitiu diferenciá-las no qual se obteve 81,02% da variância total.A aplicação da análise multivariável às amostras de urina das diferentes patologias permitiu diferenciá-las no qual se obteve 81,02% da variância total. A patologia de Hodgkin é influenciada pelas variáveis heptanal e o 2-metil-3-fenil-2-propenal. O Controlo é afectado essencialmente pelas variáveis p-cimeno, 1,4,5-trimetilnaftaleno e o dissulfureto de dimetilo. O Cólon é influenciado pelo 4-metilfenol, anisole e 1,2-dihidro-1,1,6-trimetil-naftaleno. O 1-octanol e a 3-heptanona influenciam, essencialmente as patologias da Mama e Leucemia.
Resumo:
The maturation of Madeira wines usually involves exposure to relatively high temperatures and humidity levels >70%, which affect the aroma and flavor composition and lead to the formation of the typical and characteristic bouquet of these wines. To estimate the levels of sotolon [3-hydroxy4,5-dimethyl-2(5 H )-furanone] and their behavior over time, 86 aged Madeira wines samples (1-25 years old), with different sugar concentrations, respectively, 90 g L-1 for Boal, 110 g L-1 for Malvazia, 25 g L -1 for Sercial, and 65 g L-1 for Verdelho varieties, were analyzed. Isolation was performed by liquid-liquid extraction with dichloromethane followed by chromatographic analysis by GC-MS. The reproducibility of the method was found to be 4.9%. The detection and quantification limits were 1.2 and 2.0 µgL-1, respectively. The levels of sotolon found ranged from not detected to 2000 µgL-1 for wines between 1 and 25 years old. It was observed that during aging, the concentration of sotolon increased with time in a linear fashion ( r ) 0.917). The highest concentration of sotolon was found in wines with the highest residual sugar contents, considering the same time of storage. The results show that there is a strong correlation between sotolon and sugar derivatives: furfural, 5-methylfurfural, 5-hydroxymethylfurfural, and 5-ethoxymethylfurfural. These compounds are also well correlated with wine aging. These findings indicate that the kinetics of sotolon formation is closely related with residual sugar contents, suggesting that this molecule may come from a component like sugar.
Resumo:
The aim of this study was to determine the optimal temperature and baking time to obtain a Madeira wine considered typical by an expert panel. For this purpose simultaneous descriptive analyses of typical Madeira wines were performed, and seven descriptors were selected: “dried fruit”, “nutty”, “musty”, “baked”, “oak”, “mushroom”, and “brown sugar”. Up to 10 odor-active zones were the most frequently cited by the members of the GC-olfactometry panel as corresponding to the panel’s descriptors. The odor importance of each of the zones reported by the GC-O analysis was ranked by AEDA. Three odor zones were identified as common to both Malvasia and Sercial wines and had retention indices (RI) of 1993 (“brown sugar” and “toasted”), 2151 (“brown sugar”), and 2174 (“nutty”, “driedfruits”);sotolonwasidentifiedasresponsibleforthislastaroma.Severalmoleculeswereselected to be quantified on baked wines on the basis of AEDA results and expected Maillard volatiles, such as sotolon, furfural, 5-methylfurfural, 5-ethoximethylfurfural, methional, and phenylacetaldehyde. It was observed that typicity scores were positively correlated with the concentrations of sotolon and sugar and baking time and negatively with the fermentation length.
Resumo:
An analytical methodology based on headspace solid phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (GC × GC–ToFMS) was developed for the identification and quantification of the toxic contaminant ethyl carbamate (EC) directly in fortified wines. The method performance was assessed for dry/medium dry and sweet/medium sweet model wines, and for quantification purposes, calibration plots were performed for both matrices using the ion extraction chromatography (IEC) mode (m/z 62). Good linearity was obtained with a regression coefficient (r2) higher than 0.981. A good precision was attained (R.S.D. <20%) and low detection limits (LOD) were achieved for dry (4.31 μg/L) and sweet (2.75 μg/L) model wines. The quantification limits (LOQ) and recovery for dry wines were 14.38 μg/L and 88.6%, whereas for sweet wines were 9.16 μg/L and 99.4%, respectively. The higher performance was attainted with sweet model wine, as increasing of glucose content improves the volatile compound in headspace, and a better linearity, recovery and precision were achieved. The analytical methodology was applied to analyse 20 fortified Madeira wines including different types of wine (dry, medium dry, sweet, and medium sweet) obtained from several harvests in Madeira Island (Portugal). The EC levels ranged from 54.1 μg/L (medium dry) to 162.5 μg/L (medium sweet).
Resumo:
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.