Quantification of polyphenols with potential antioxidant properties in wines using reverse phase HPLC

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 (< 3%) were obtained, as well as relative peak area. Also high recoveries were achieved, over 80.3%. Polyphenols calibration curves showed a good linearity (r(2) >0.994) within test ranges. Detection limits ranged between 0.03 and 11.5 microg/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, rosé 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.     

Aroma composition of red wines by different extraction methods and Gas Chromatography-SIM/MASS spectrometry analysis

One hundred and one volatile compounds, reported in literature as powerful odorants of wine, were quantified by Gas Chromatography-Selective Ion Monitoring/Mass Spectrometry (GC-SIM/MS) in Primitivo, Aglianico, Merlot and Cabernet Sauvignon red wines. Wine samples were extracted by 3 different extraction methods: 1) separation of the alcoholic fraction from the aqueous phase by salting-out and subsequent extraction by liquid-liquid micro-extraction with 1,1,2-trichlorotrifluoroethane (Freon 113); 2) extraction by liquid-liquid micro-extraction with dichloromethane; 3) solid phase extraction (SPE cartridge: 800 mg of LiChrolut EN resin) with pentane-dichloromethane (20:1) and dichloromethane. The selection of the ion fragments used for quantification was directly performed on a red wine sample. For each compound the area of the corresponding peak was normalized respect to the peak of the internal standard and then interpolated in a calibration curve obtained analysing a model wine solution (water, ethanol, tartaric acid and known amounts of analytes and of internal standard). The methods showed a good linearity: r2>0.990, except for farnesol (isomer a and c), octanal, decanal, furaneol and phenylacetic acid with 0.966 < or = r2 < or = 0.990. The 7 most powerful odorants were: beta-damascenone, acetaldehyde, maltol, ethyl 2-methylbutanoate, ethyl 3-methylbutanoate, 3-methylbutanoic acid and acetal; 7 other slightly less important were: ethyl hexanoate, ethyl acetate, 1-octen-3-ol, butanoic acid, rose oxide, furaneol and sotolon. The Aglianico wines were characterised by the major fermentation compounds (esters, fatty acids and 2-phenylethanol), beta-damascenone, beta-ionone and linalool. The Primitivo wines were characterized by furaneol, methoxypyrazine, gamma-nonalactone and acetaldehyde, while Cabernet Sauvignon and Merlot wines principally by cask derivates (vanillin, (Z) 3-methyl-gamma-octalactone [(Z) wiskylactone], maltol and eugenol), some aldehydes and 3-isopropyl-2-methoxypyrazine.     

Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry combined with solid phase microextraction as a powerful tool for quantification of ethyl carbamate in fortified wines. The case study of Madeira wine

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).     

Characterization of volatile substances in apples from Rosaceae family by headspace solid‐phase microextraction followed by GC‐qMS

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, extraction time, sample amount, dilution factor, ionic strength, and desorption time, were optimized and discussed. The SPME fiber coated with 50/30 μm divinylbenzene/carboxen/PDMS (DVB/CAR/PDMS) afforded highest extraction efficiency of volatile compounds, providing the best sensitivity for the target volatiles, particularly when the samples were extracted at 50°C for 30 min with constant magnetic stirring. A qualitative and semi‐quantitative analysis between the investigated apple species has been established. It was possible to identify about 100 of volatile compounds among pulp (46, 45, and 39), peel (64, 60, and 64), and entire fruit (65, 43, and 50) in PP, PS, and SS apples, respectively. Ethyl esters, terpenes, and higher alcohols were found to be the most representative volatiles. α‐Farnesene, hexan‐1‐ol and hexyl 2‐methylbutyrate were the compounds found in the volatile profile of studied apples with the largest GC area, representing, on average, 24.71, 14.06, and 10.80% of the total volatile fraction from PP, PS, and SS apples. In PP entire apple, the most abundant compounds identified were α‐farnesene (30.49%), the unknown compound m/z (69, 101, 157) (21.82%) and hexyl acetate (6.57%). Regarding PS entire apple the major compounds were α‐farnesene (16.87%), estragole (15.43%), hexan‐1‐ol (10.94), and E‐2‐hexenal (10.67). α‐Farnesene (30.3%), hexan‐1‐ol (18.90%), 2‐methylbutanoic acid (4.7%), and pentan‐1‐ol (4.6%) were also found as SS entire apple volatiles present in a higher relative content. 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, p‐ethyl styrene, and E‐2‐hexenal.     

Accurate discrimination of Gastrodia elata from different geographical origins using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis

Gastrodia elata from different geographical origins varies in quality and pharmacological activity. This study focused on the classification and identification of Gastrodia elata from six producing areas using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis. Before recognition analysis, a principal component analysis was applied to ascertain the discrimination possibility with high‐performance liquid chromatography fingerprints. And then, boosting partial least‐squares discriminant analysis and conventional partial least‐squares discriminant analysis were applied in this study. Experimental results indicated that the adaptive iteratively reweighted penalized least‐squares algorithm could eliminate the baseline drift of high‐performance liquid chromatography chromatograms effectively. And compared with partial least‐squares discriminant analysis, the total recognition rates using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis for the calibration sets and prediction sets were improved from 94 to 100% and 86 to 97%, respectively. In conclusion, high‐performance liquid chromatography combined with boosting partial least‐squares discriminant analysis, which has such advantages as effective, specific, accurate, non‐polluting, has an edge for discrimination of traditional Chinese medicine from different geographical origins. And the proposed methodology is a useful tool to classify and identify Gastrodia elata from different geographical origins.     

Metabolic fingerprinting based on high-resolution tandem mass spectrometry: a reliable tool for wine authentication?

Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (MS) and an alternative technology represented by direct analysis in real time coupled with quadrupole time-of-flight MS were investigated for metabolic fingerprinting of 343 red and white wine samples. Direct injection of pure wine and an extraction procedure optimized for isolation of polyphenols were used to compare different analytical and data handling strategies. After data processing and data pretreatment, principal component analysis was initially used to explore the data structure. Initially, the unsupervised models revealed a notable clustering according to the grape varieties, and therefore supervised orthogonal partial least squares discriminant analysis models were created and validated for separation of red and white wines according to the grape variety. The validated orthogonal partial least squares discriminant analysis models based on data (ions) recorded in positive ionization mode were able to classify correctly 95 % of samples. In parallel, authentication parameters, such as origin and vintage, were evaluated, and they are discussed. A tentative identification of markers was performed using accurate mass measurement of MS and MS/MS spectra, different software packages and different online libraries. In this way, different flavonol glucosides and polyphenols were identified as wine markers according to the grape varieties.     

Direct immersion solid‐phase microextraction with gas chromatography and mass spectrometry for the determination of specific biomarkers of human sweat in melted snow

To provide a reliable tool for investigating diffusion processes of the specific components of the human odor 3‐hydroxy‐3‐methylhexanoic acid and 3‐methyl‐3‐sulfanylhexan‐1‐ol through the snowpack, we developed and optimized an analytical method based on direct immersion solid‐phase microextraction followed by gas chromatography with mass spectrometry. Direct immersion solid‐phase microextraction was performed using polyacrylate fibers placed in aqueous solutions containing 3‐hydroxy‐3‐methylhexanoic acid and 3‐methyl‐3‐sulfanylhexan‐1‐ol. After optimization, absorption times of 120 min provided a good balance to shorten the analysis time and to obtain suitable amounts of extractable analytes. The extraction efficiency was improved by increasing the ionic strength of the solution. Although the absolute extraction efficiency ranged between 10 and 12% for 3‐hydroxy‐3‐methylhexanoic acid and 2–3% for 3‐methyl‐3‐sulfanylhexan‐1‐ol, this method was suitable for analyzing 3‐hydroxy‐3‐methylhexanoic acid and 3‐methyl‐3‐sulfanylhexan‐1‐ol concentrations of at least 0.04 and 0.20 ng/mL, respectively. The precision of the direct immersion solid‐phase microextraction method ranged between 8 and 16%. The variability within a batch of six fibers was 10–18%. The accuracy of the method provided values of 88–95 and 86–101% for 3‐hydroxy‐3‐methylhexanoic acid and 3‐methyl‐3‐sulfanylhexan‐1‐ol, respectively. The limit of detection (and quantification) was 0.01 ng/mL (0.04 ng/mL) for 3‐hydroxy‐3‐methylhexanoic acid and 0.06 ng/mL (0.20 ng/mL) for 3‐methyl‐3‐sulfanylhexan‐1‐ol. The signal versus concentration was linear for both compounds (r² = 0.973–0.979). The stability of these two compounds showed that 3‐hydroxy‐3‐methylhexanoic acid was more stable in water than 3‐methyl‐3‐sulfanylhexan‐1‐ol. We applied the method to environmental samples in correspondence with an olfactory target buried previously.     

Usefulness of chemometrics and mass spectrometry-based electronic nose to classify Australian white wines by their varietal origin

A combination of mass spectrometry-based electronic nose (MS e_nose) and chemometrics was explored to classify two Australian white wines according to their varietal origin namely Riesling and unwooded Chardonnay. The MS e_nose data were analysed using principal components analysis (PCA), discriminant partial least squares (DPLS) and linear discriminant analysis (LDA) applied to principal components scores and validated using full cross validation (leave one out). DPLS gave the highest levels of correct classification for both varieties (>90%). LDA classified correctly 73% of unwooded Chardonnay and 82% of Riesling wines. Even though the conventional analysis provides fundamental information about the volatile compounds present in the wine, the MS e_nose method has a series of advantages over conventional analytical techniques due to simplicity of the sample-preparation and reduced time of analysis and might be considered as a more convenient choice for routine process control in an industrial environment. The work reported here is a feasibility study and requires further development with considerably more commercial samples of different varieties. Further studies are needed in order to improve the calibration specificity, accuracy and robustness, and to extend the discrimination to other wine varieties or blends.     

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

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.     

Preparation and selective recognition of a novel solid‐phase microextraction fiber combined with molecularly imprinted polymers for the extraction of parabens in soy sample

A prepared molecularly imprinted polymer with ethyl p‐hydroxybenzoate as template molecule was applied for the first time to a homemade solid‐phase microextraction fiber. The molecularly imprinted polymer‐coated solid‐phase microextraction fiber was characterized by scanning electron microscopy and thermogravimetric analysis. Various parameters were investigated, including extraction temperature, extraction time, and desorption time. Under the optimum extraction conditions, the molecularly imprinted polymer‐coated solid‐phase microextraction fiber exhibited higher selectivity with greater extraction capacity toward parabens compared with the nonimprinted polymer‐coated solid‐phase microextraction fiber and commercial fibers. The molecularly imprinted polymer‐coated solid‐phase microextraction fiber was tested using gas chromatography to determine parabens, including methyl p‐hydroxybenzoate, ethyl p‐hydroxybenzoate, and propyl p‐hydroxybenzoate. The linear ranges were 0.01–10 μg/mL with a correlation coefficient above 0.9943. The detection limits (under signal‐to‐noise ratio of 3) were below 0.30 μg/L. The fiber was successfully applied to the simultaneous analysis of three parabens in spiked soy samples with satisfactory recoveries of 95.48, 97.86, and 92.17%, respectively. The relative standard deviations (n=6) were within 2.83–3.91%. The proposed molecularly imprinted polymer‐coated solid‐phase microextraction method is suitable for selective extraction and determination of trace parabens in food samples.     

猕猴桃果酒香气成分的气相色谱/质谱分析

采用溶液萃取法提取猕猴桃果酒中的香气成分，经气相色谱－质谱联机分析，分离出44个峰，鉴定出42种化合物，占总峰面积的94．51％。其中主要为3－甲基丁醇、2－甲基丙醇、苯乙醇、乙酸乙酯、四氢化2－甲基噻吩、辛酸、二氢化－2（3H）－呋喃酮、乙酸3－甲基丁酯、己酸、1H－吲哚－3－乙醇等。     

In‐tube extraction for the determination of the main volatile compounds in Physalis peruviana L

An analytical procedure based on in‐tube extraction followed by gas chromatography with mass spectrometry has been developed for the analysis of 24 of the main volatile components in cape gooseberry (Physalis peruviana L.) samples. According to their chemical structure, the compounds were organized into different groups: one hydrocarbon, one aldehyde, four alcohols, four esters, and 14 monoterpenes. By single‐factor experiments, incubation temperature, incubation time, extraction volume, extraction strokes, extraction speed, desorption temperature, and desorption speed were determined as 60°C, 20 min, 1000 μL, 20, 50:50 μL/s, 280°C, 100 μL/s, respectively. Quantitative analysis using authentic standards and external calibration curves was performed. The limit of detection and limit of quantification for the analytical procedure were calculated. Results shown the benzaldehyde, ethyl butanoate, 2‐methyl‐1‐butanol, 1‐hexanol, 1‐butanol, α‐terpineol, and terpinen‐4‐ol were the most abundant volatile compounds in analyzed fruits (68.6–585 μg/kg). The obtained data may contribute to qualify cape gooseberry to the group of superfruits and, therefore, increase its popularity.     

Combination of supercritical fluid extraction with counter‐current chromatography to isolate anthocyanidins from the petals of Chaenomeles sinensis based on mathematical calculations

Supercritical fluid extraction (SFE) coupled with high‐speed counter‐current chromatography (HSCCC) was successfully used for the extraction and on‐line isolation of the anthocyanidins from the petals of Chaenomeles sinensis in two stages. The SFE parameters were optimized by an orthogonal test, and the solvent systems of SFE and HSCCC were calculated and optimized with the help of a multiexponential function model. In the first stage, the lower phase of the solvent system of n‐butanol/tert‐butyl methyl ether/acetonitrile/0.1% aqueous TFA (0.715:1.0:0.134:1.592, v/v/v/v) was used as both the SFE modifier and the HSCCC stationary phase, after extraction, the extractants were pumped into HSCCC column, and then eluted with the corresponding upper phase to isolate the moderately hydrophobic compounds. In the second stage, the upper phase of the solvent system of n‐butanol/ethyl acetate/acetonitrile/0.1% aqueous TFA (1.348:1.0:0.605:2.156, v/v/v/v) was used as both the SFE modifier and the HSCCC stationary phase, followed by elution with the corresponding lower phase to separate the hydrophobic compounds. With the help of two‐stage SFE/HSCCC, six compounds including delphinidin‐3‐O‐glucoside (Dp3G), cyanidin‐3‐O‐glucoside (Cy3G), peonidin‐3‐O‐glucoside (Pn3G), delphinidin (Dp), peonidin (Pn), and malvidin (Mv) were successfully separated within 300 min. The targeted compounds were identified by UV spectrophotometry, MS, and NMR spectroscopy. This research has opened up great prospects for the industrial application of SFE–HSCCC for the automatic extraction and separation of unstable compounds.     

Chemotaxonomic study of Chrysobalanus icaco Linnaeus (Chrysobalanaceae) using ultra‐high performance liquid chromatography coupled with diode array detection fingerprint in combination with multivariate analysis

We investigated a strategy for the chemotaxonomy study of Chrysobalanus icaco Linnaeus (Chrysobalanaceae) based on ultra‐high performance liquid chromatography coupled with diode array detection fingerprint in combination with multivariate analysis. Two models using principal component analysis and partial least squares discriminant analysis were developed, and the samples could be successfully classified into two classes: Class 1 (red morphotype) and Class 2 (white and black morphotypes). Furthermore, ultra‐high performance liquid chromatography coupled with diode array and electrospray ionization tandem mass spectrometry was used to identify the main compounds responsible for class separation. The partial least squares discriminant analysis model accurately classified the C. icaco samples using an external validation subset with prediction ability of 100% and revealed the existence of two chemotypes. The most important finding obtained in this study is that the three morphotypes distinguished by the mature fruit color (white, red, and black) are not all phytoequivalent to each other.     

Differentiation of Mint (Mentha haplocalyx Briq.) from different regions in China using gas and liquid chromatography

In this study, complex substances such as Mint (Mentha haplocalyx Briq.) samples from different growing regions in China were analyzed for phenolic compounds by high‐performance liquid chromatography with diode array detection and for the volatile aroma compounds by gas chromatography with mass spectrometry. Chemometrics methods, e.g. principal component analysis, back‐propagation artificial neural networks, and partial least squares discriminant analysis, were applied to resolve complex chromatographic profiles of Mint samples. A total of 49 aroma components and 23 phenolic compounds were identified in 79 Mint samples. Principal component analysis score plots from gas chromatography with mass spectrometry and high‐performance liquid chromatography with diode array detection data sets showed a clear distinction among Mint from three different regions in China. Classification results showed that satisfactory performance of prediction ability for back‐propagation artificial neural networks and partial least squares discriminant analysis. The major compounds that contributed to the discrimination were chlorogenic acid, unknown 3, kaempherol 7‐O‐rutinoside, salvianolic acid L, hesperidin, diosmetin, unknown 6 and pebrellin in Mint according to regression coefficients of the partial least squares discriminant analysis model. This study indicated that the proposed strategy could provide a simple and rapid technique to distinguish clearly complex profiles from samples such as Mint.     

Screening of key odorants and anthocyanin compounds of cv. Okuzgozu (Vitis vinifera L.) red wines with a free run and pressed pomace using GC‐MS‐Olfactometry and LC‐MS‐MS

The principal purpose of the present work is to characterize the aroma, aroma‐active, and anthocyanin profiles of Okuzgozu wines and to observe the effect of the pomace pressing technique on these parameters. A total of 58 and 59 volatile compounds were identified and quantified in free‐run juice wine (FRW) and pressed pomace wine (PW). Alcohols were found as the most dominant group among aroma compounds followed by esters and acids. However, among all these compounds, only 11 and 13 of them could be considered as key odorants in aromatic extracts of FRW and PW, respectively. According to GC‐MS‐O analysis, ethyl octanoate (fruity), phenyl ethyl acetate (fruity), and 2‐phenyl ethanol (flowery) were found as the main contributors to the overall scent of both wines. Beyond the aroma profiles, anthocyanin contents of both types of wines were also investigated, and total 14 and 15 anthocyanins were identified and quantified in FRW and PW. Malvidin‐3‐glycoside and its acetyl and coumaroyl forms were identified as the dominant anthocyanins in both wines. It is worth noting the pressing application (2.0 atm) led to an increase of some unpleasant notes in the aroma providing chemical, pharmacy, and fermented aromas in wine. On the other hand, the wines produced with pressed pomace presented higher amounts of anthocyanins.     

Metabolite profiling to discriminate different species and genus from thistles in Korea using liquid chromatography with quadrupole time‐of‐flight mass spectrometry

This study was designed to classify and identify closely related thistle species in the genus Cirsium, as well as Carduus and Cephalonoplos species, which are also thistles. The comprehensive and untargeted metabolite profiles of nine Korean thistles were determined using ultra high performance liquid chromatography combined with hybrid quadrupole time‐of‐flight mass spectrometry. The difference in metabolite profiles among species was explored using principal component analysis and hierarchical clustering analysis. The significantly different metabolites (Bonferroni‐corrected P‐value < 0.001) were used to construct a partial least squares discriminant analysis model to predict the species of thistle. Nine species were successfully classified using a partial least squares discriminant analysis model and confirmed using a cross‐validation method. Species with similar features were grouped based on unique patterns in variable clusters. The present study suggests that liquid chromatography with quadrupole time‐of‐flight mass spectrometry untargeted metabolomic profiling with chemometric analysis is an efficient and powerful tool for discriminating between different species of medicinal herbs.     

Classification of wines from five Spanish origin denominations by aromatic compound analysis

Wine is a complex matrix in which aroma compounds play an important role in the characterization of the flavor pattern of a given wine. Twelve volatile compounds were determined in 244 samples of Spanish red wines from different denominations of origin: Rioja, Navarra, Valdepe?as, La Mancha, and Cari?ena. The samples were analyzed by GC using headspace solid-phase microextraction. The concentration (mg/mL) intervals obtained were 3-methyl-butyl acetate (3.9 to 116), 3-methyl-1-butanol (93 to 724), ethyl hexanoate (0.8 to 39), 1-hexanol (0.3 to 6.7), ethyl octanoate (1.4 to 41), diethyl succinate (0.2 to 13), 2-phenyl ethyl acetate (0 to 5.3), hexanoic acid (0 to 8.3), geraniol (0 to 3.0), 2-phenylethanol (1.5 to 56), octanoic acid (0 to 20), and decanoic acid (0 to 3.3). Wines were classified by multivariate statistical methods: principal component analysis, and lineal discriminant analysis. A correct differentiation among wines according to their origin was obtained by lineal discriminant analysis.