sensory profile and contribution of major

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7VRTICES, Campos dos Goytacazes/ RJ, v.14, n. Especial 2, p. 7-25, 2012

Sensory prole and contribution of major components of aroma in dry red wine quality

Sensory profle and contribution o majorcomponents o aroma in dry red wine quality

Luisa Costa de Oliveira*Maria Eugnia de Oliveira Mamede**

Key words: Quantitative descriptive analysis. Multivariate Statistics. Quality. Red wine. Volatiles.

Introduction

Although many alternative techniques have been developed, none o them areable to advantageously replace classical descriptive sensory analysis with respect to wine

(DAMSIO e COSELL, 1991). Descriptive analysis is a primary tool used in sensoryanalysis (CAMPO et al., 2010) which provides a complete analysis o complex matrices,such as wine. Cadot et al. (2010) suggested that quantitative descriptive analysis (QDA)is one o the techniques useul or determining the typicality o Cabernet Sauvignonand Cabernet Franc to the French appellation o origin. Te same technique has beenused to evaluate sensory eects o ethanol levels in the perception o aroma attributes inMalbec wines (GOLDNER et al., 2009).

Among the various sensory attributes o wine, aroma is one o the most

important. According to Falco et al. (2008), aromatic compounds can impact andhelp steer the development o wines with higher quality. Over 700 compounds havebeen isolated and identied in the volatile raction o various wines (JACKSON, 2008)at concentrations ranging rom hundreds o mg L-1 to ng L-1.

Te extraction o volatile compounds by headspace solid phase microextraction(HS-SPME) has been widely used in studies o the aroma o alcoholic beverages, such as

Tis study aimed to determine the sensory profle and main volatile compounds o a set o commercialwines rom two major wine regions in Brazil. A total o 28 descriptors were selected by quantitativedescriptive analysis, and red, violet, pungent aroma, vinegary aroma and sotness were themost important descriptors in sample discrimination (p0.05). 42 volatile aroma compounds wereconsidered relevant or the evaluation o red wine samples. Several acetates and esters that contributeto the pleasant aroma in wines were ound in the samples, but other undesirable compounds werealso identifed: acetic acid and octanoic acid may have contributed to the vinegary and sulphur odors

perceived by a trained team.

Artigo Original

* Nutricionista, Mestre em Cincia de Alimentos pela Faculdade de Farmcia da Universidade Federal da Bahia - Brasil. E-mail:[email protected]

**Doutora em Cincia de Alimentos pela Faculdade de Engenharia de Alimentos da Universidade Estadual de Campinas;

Docente do curso de Ps-graduao em Cincia de Alimentos da Universidade Federal da Bahia - Brasil.(nvel MestradoAcadmico). E-mail: [email protected]


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8 VRTICES, Campos dos Goytacazes/ RJ, v.14, n. Especial 2, p. 7-25, 2012

Luisa Costa de Oliveira, Maria Eugnia de Oliveira Mamede

wine, and it is essential or assessing the quality o such products and or optimizationo their production (AUGUSO; LEIE, 2003). Trough this extraction technique,Zhang et al. (2010) identied 11 volatile compounds determining the classication osamples o varietal red wines including Cabernet Sauvignon and Merlot. Cmara et al. (2007) dierentiated and classied samples o Madeira wines according to their region

o origin based on their aromatic composition.Currently, there are two main regions producing ne wines (Vitis viniera) in

Brazil. One area is located in the region o Serra Gacha (Vinhedos Valley, Rio Grandedo Sul), and it has geographical indication certication. Te principal grape varietiescultivated in this wine region are Cabernet Sauvignon and Merlot. Te other area islocated in the So Francisco Valley region, on the states o Bahia and Pernambucoborder, but it does not have geographical indication certication. Te main grapevarieties cultivated in this wine region are Cabernet Sauvignon and Shiraz. Tus, the

aim o this study was to determine the sensory prole and volatile compounds o nedry wines rom the two major wine regions in Brazil.

Materials and methods

Wine samples

Six brands o commercial ne dry red wines (2006 harvest) produced in Brazil

were analyzed. Te samples were rom the regions o So Francisco Valley (Juazeiro,BA, and Petrolina, PE) and Serra Gacha (Bento Gonalves, RS). Tese samples wererepresentatives o wines produced in these regions. A total o 11 bottles o each brand(same batch) were sampled randomly rom supermarkets and used or sensory analysis.Te bottles were stored horizontally in a dark room at 16C until analysis.

Sensory analysis

QDA, as described by Stone and Sidel (2004), was used to determine the sensoryprole o wine samples. Te analysis was carried out in the Laboratory o SensoryAnalysis in individual booths under white light and in a temperature controlled room(22C) throughout the day.

Te recruitment o judges was done by lling out a questionnaire based onhabits o red wine consumption, interest and availability to participate. Candidateswith better discriminatory ability were selected in three sessions o a triangular test.Samples were tested in the ollowing pairs: AXD, BXC and EXF. Te test result wasanalysed by a specic table test (minimum number o replies rom the triangular test)

at 5% signicance (MEILGAARD et al., 2007). Only those candidates who correctly


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discriminated three pairs o sample combinations were selected.o prevent recruitment o judges with little or no experience in sensory analysis

o wines, odor recognition and basic taste tests (MEILGAARD et al., 2007) werealso applied only at training level beore the QDA. In the odor recognition test, eachsubstance was introduced in porcelain cups covered with perorated aluminum oil to

prevent the display o reerences. o test the basic tastes, aqueous solutions containingdierent concentrations o substances representing the basic tastes (sweet, sour andbitter) and astringency were prepared as ollows: solutions o sucrose (0.4% and 0.8%);solutions o ood grade citric acid (0.02%, 0.03% and 0.04%), solutions o ood gradecaeine (0.02% and 0.04%) and juice o unripe grape skins.

Te descriptive terminology was generated by Repertory Grid Kellys Method(MOSKOWIZ, 1983). ests were carried out to select the subjects that wouldcompose the denitive sensory team. Te subjects chose the reerences that indicated

the maximum and minimum intensity o each attribute by their own consensus underthe supervision o a team leader (able 1).Selection o the nal sensory panel was perormed according to Damsio and

Costell (1991) based on discrimination abilities on (Fpsample0.05) o each attribute veried by a two-actor analysis o variance (ANOVA:

sample and repetition), and agreement o the averages o each judge with the team orat least 75% o all descriptors collected or samples o red wine.

Te sensory panel was composed o 10 judges (seven women and three men, 21to 55 years old) who were submitted to 9 training sessions. Each judge evaluated three

samples per analytical session (about 1 hour long) with three replications on dierentdays. For each repetition, a dierent bottle o wine was tested. Te samples (50 mL)were served at 16C in clear glass bowls suitable or red wine, and properly coded. Tesamples were presented in balanced incomplete blocks, in order to control the contrasteect amongst the samples. Order o presentation o the samples in each session wasbalanced or the rst-order eect. Te number o times that each sample appeared ineach block () was calculated according to Equation 1 or the experimental design, asollows:

=r(k - 1)/a -1 (1)where r is the number o repetitions per sample, k is the number o samples per

analysis session, and a is the total number o treatments (samples).Panelists were asked to rinse their palate with room temperature mineral water

and to ingest unsalted roast between samples. Reerences were provided in a separateroom during all examination sessions. Tus, i a question was raised, each judge couldtry the reerences o the attributes to be analyzed at any time. Te quantication odescriptors was perormed on 9cm unstructured line scales with the terms o intensityanchored at its let and right extremes.


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Table 1. Descriptive terminology and respective references of intensity developed bysensorial team to the red wine samples


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Cont. Table 1. Descriptive terminology and respective references of intensitydeveloped by sensorial team to the red wine samples


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Extraction, separation and identifcation o volatile compounds

Te volatile compounds were isolated by using HS-SPME. Te ber usedwas 100-m polydimethylsiloxane (PDMS) (Supelco, USA). Approximately 3 mLo each sample were placed in amber sealed vials, and the PDMS ber was exposed

to the headspace at 30C 30 min-1. Te separations were conducted on a ShimadzuQP5000 gas chromatograph with detector quadrupole mass spectrometry. A capillarycolumn (HP-5; Hewllett-Packard, USA) 30m x 0.32mm x 0.25mm (5% diphenyl and95% dimethylpolysiloxane) was used. Te carrier gas was helium (1 mL min-1). Tecolumn temperature had the ollowing schedule: initial temperature o 60C with anincreasing temperature gradient (3C min-1) to reach the nal temperature o 246C.Te temperature o the detector and injector was 250C, and the orm o injectionused was splitless. Desorption time was 2 min. An ionization voltage o 70eV wasused, and the mass spectrum was obtained in a scan interval o 30m/z to 350m/z.Te identication o volatile compounds was perormed using the Automated MassSpectral Deconvolution System (AMDIS v.2.62) and was compared with the NISlibrary using the Mass Spectral Search Program (NIS v.2.0, Washington D.C., USA).

Statistical analysis

Te results o the descriptive analysis were subjected to ANOVA with ukeys testat 5% signicance using the SAS statistical sotware (version 8.2; SAS institute, Cary,

NC). Te graphics o the principal component analysis (PCA), hierarchical clusteranalysis (HCA) and Pearsons correlation were perormed with Minitab statisticalsotware (version 15.1; Minitab Inc.).

Results and discussion

All selected judges correctly identied at least 60% o the aromas presented in the

odor recognition test. Te eucalyptus aroma was the most easily detected by the judges(100% correct), and paprika was the aroma with the lowest rate o recognition (7%correct). In the test o basic tastes, all o the judges were able to recognize at least oneconcentration o each basic taste in addition to astringency. Most participants (77%)acknowledged at least 75% o the taste solutions presented with the lowest recognitionrate (54%) assigned to the sour taste at the 0.02% concentration.

A total o 28 descriptors were raised or samples o red wine (able 2). In previoussensory study involving Brazilian red wines (FALCO et al., 2007), descriptors werealso raised that were common to those developed in this work, demonstrating its

importance in the development o the sensory prole o Brazilian red wines. At least


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two samples diered signicantly in all attributes. Te most important descriptorsin determining wine samples by variance analysis were red, violet, pungent aroma,vinegary aroma and sotness.

Table 2. Results of Analysis of Variance (ANOVA) for sensory attributes of red wine

samples

With respect to appearance, samples B and C (Cabernet Sauvignon, So FranciscoValley) signicantly diered rom the other samples with the lowest averages or red andviolet. Tese samples were considered to have the most reddish-orange color. SamplesA, E and F had the highest average or the red and violet.

Aroma descriptors, such as vanilla, ripe ruit, and foral were considered positivein red wines. Te highest averages o vanilla aroma were observed in compositesamples with a blend o Cabernet Sauvignon and Shiraz (able2) without signicantdierences between them. Moreover, sample D did not dier rom sample F (Merlot).

Furthermore, no signicant dierence in the vanilla aroma was ound between samples


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F and E (Cabernet Sauvignon), which were produced in the same geographical region.Te aroma similarity between Merlot and Cabernet Sauvignon varieties, produced indierent localities, has also been described (GRBZ et al., 2006). Wines rom thesevarieties have many favor compounds in common, and dier only by their caramelaroma (higher in Merlot).

Several studies have described the aromas o certain wine varietals. Aromas ogooseberry, green pepper, smoke, hay, vanilla, blueberry and cinnamon are consideredtypical in Cabernet Sauvignon wines produced in China (AO et al., 2009). In anotherstudy, the aroma o Merlot wine was described as vegetation, resh caramel, quince,gooseberry, butter, grass, liquorice, and oak (GAMBARO et al., 2003). Te pungentaroma was important to dierentiate signicantly sample C (Cabernet Sauvignon, SoFrancisco Valley) rom the others samples, and it was perceived by the sensory panel withgreater intensity in this sample (able2). Higher scores or the dried ruit aroma were

obtained rom samples A and D. Te addition o Shiraz grapes may have contributedto this. During a comparison o the Shiraz and Cabernet Sauvignon varietal wines byLattey et al. (2010), Shiraz wines were associated with the aroma o cooked dark ruitsin addition to being classied with a greater purple colour and sweet taste.

Negative aromas were also perceived by judges. Samples B and C (CabernetSauvignon) achieved the highest averages or the ermented and sulphur aromas(able2). Regarding vinegary aroma, samples B and C had high scores but didnot signicantly dier rom the Serra Gacha region wines, which had the highestaverages. Te vinegary aroma was important to dierentiate signicantly samples A

and D (Cabernet Sauvignon/Shiraz, So Francisco Valley) rom the other samples. Byolactometry, Falco et al. (2008) related vinegar odor to acetic acid. Small amountso acetic acid (0.2 to 0.4g/L) in wine can be produced by the action oSaccharomycescerevisiae during the ermentation process (FALCO et al., 2007). However, highconcentrations o acetic acid are related to a ailure in the drink sanity.

Although all the wines were dry, sweet taste was detected, with sample E havingthe highest average. Te amount o residual sugar in this sample, and the sensitivityo each individual judge may have allowed this perception. Moreover, the alcohol and

glycerol contents also reinorce a perception o sweetness in wine (JACKSON, 2008).As or the sour taste, samples C and A had the highest mean ,and the sample D hadthe lowest average or this attribute, with no signicant dierence being ound betweensample D and the samples produced in the South. Te lowest score or bitter taste wasobserved in sample F (Merlot) (able2).

Te samples rom the So Francisco Valley region had the highest mean oastringency (able 2). Astringency in red wines is usually related to phenol compounds.Lucena et al. (2010) ound high levels o phenol compounds in samples o red winesproduced in the So Francisco Valley (3.2 to 5.9gGAE/L). Tey suggest that climate,

high levels o sunshine, and use o controlled irrigation typical o this region may


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contribute to the higher phenol content o wines. Wines that had high polyphenol levelswere characterized as astringent, bitter, sour and pungent (GOLDNER; ZAMORA,2010).

Body and sotness were also two important descriptors to discriminate winesamples. Body attribute was dened by the sensory panel as a sense o opulence or

density o the red wine perceived in mouth, while the sotness attribute was describedas the harmony between the amounts o sugar and alcohol in the samples perceived bythe mouth. Samples A and D (So Francisco Valley) presented the highest body (5.44and 5.21, respectively). Possibly, this increased sense o body is related to its alcoholcontent since, at high concentrations, alcohol may contribute to the eeling o weight orbody, especially in dry wines (JACKSON, 2008). Tese same samples (A and D) wereconsidered as the sotest along with samples o the Serra Gacha region (E and F), thusmore balanced in sugar and alcohol content. Sotness was important to signicantly

dierentiate samples B and C (Cabernet Sauvignon, So Francisco Valley) rom theothers.Pearsons correlation showed that among the ollowing sensory attributes there

were strong positive correlations (able 3): sweet taste and sotness (r=0.78); bodyand sotness (r=0.76); bitter taste and astringency (r=0.74); sweet taste and red color(r=0.68); sour taste and astringency (r=0.67). Te positive association between red colorand intensity o sweet taste in a variety o drinks was cited by Durn and Costell (1999)to demonstrate the infuence o color on perceived sweetness. According to Delwice(2003), color has a proound eect on the perception o ood and drink aromas, and

the techniques used by winemakers to enhance the color o red and white wines canoten distort the perception o their real favor.

Te ollowing strong negative correlations also were observed: sweet taste andastringency (r=-0.98); astringency and sotness (r=-0.73); sweet and acid tastes (r=-0.68); sweet and bitter tastes (r=-0.63). Some authors have suggested that sweetnesscan have a dampening eect on the perception o acidity, bitterness and astringencywith the opposite also being true (BEHRENS; SILVA, 2000), explaining the negativecorrelations obtained between these attributes in the current study.

Tere were negative correlations between astringency and the ruity aroma andbitter taste attributes; as well as a positive correlation between ruity aroma and sweettaste (able3). Tese results agree with those obtained by Senz-Navajas et al. (2010),who ound that sweetness o dry wines is closely related to the ruity aroma, and thatperceptions o astringency and bitterness are inversely related to this aroma.


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Table 3 - Pearson correlation coefficient (r) between means of sensory attributes


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Most analytical methods tend to generate a lot o inormation. Te use omultivariate techniques has helped in the interpretation o results obtained withwines. Campo et al. (2008) suggest that the use o HCA can be an interestingtool to dierentiate the quality o Spanish monovarietal white wines. Tus, HCAwas perormed to veriy the grouping o samples (Figure 1). Tere were two major

clusters at level 9.17 (y-axis). Samples B and C were clearly separated in a smallercluster, and another larger cluster was associated with samples A, D, E and F. Tedendrogram showed that samples A and D (Cabernet Sauvignon and Shiraz) romthe So Francisco Valley had a higher degree o similarity with samples E (CabernetSauvignon) and F (Merlot) rom Serra Gacha. Tese same samples were perceived asthe sotest by the sensory team (able 2). Even though the wines E and F were maderom dierent grape varieties, their similarity can be justied by the same soil andclimatic conditions during the cultivation o grapes and preparation o the beverage,

demonstrating the infuence o conditions resulting rom a geographical region in thenal sensory characteristics o red wine. Although there was some dierentiation othe samples by HCA, no inormation about the importance o sensory attributes wasindicated by it.

Figure 1. Multivariate analysis demonstrated in the form of hierarchical clustering of samples of red wine.

Tus, PCA was perormed ater HCA. PCA was divided into categories oattributes as represented in Figures 2, 3 and 4 (correlation matrix). Te rst twoprincipal components o the category o appearance attributes, explained 95.8% othe total variation o the data, and they showed that the turbidity, amount o tears and


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visual viscosity were important to characterize samples A and D. Te red color wasmore important to characterize samples E and F, and the reddish-orange characterizedsamples B and C (Figure 2). It was possible to discriminate samples based in theproduction region by means o Component I o PCA with regard to the attributes oappearance (Figure 2).

Figure 2. Two-dimensional projection of the results obtained from the principal components analysis Iand II for the class of attributes that include the appearance.

With regard to the attributes o aroma (Figure 3), components I and II accountedor 83.2% o the explanation or variability. Te axis o component I objected to theterms o ruity aromas related to the terms o ermented, olive and sulphur aromasvectors that had long and near to the axis, indicating the relevance o this attributesin the characterization o samples. Te vanilla aroma, ripe ruit aroma and ruityaroma were important in characterizing sample A. Te buttery aroma characterized

sample E. Te samples D and F were characterized by a foral aroma in addition toa dried ruit aroma and alcoholic aroma. Te pungent aroma, olive aroma, sulphuraroma, vinegary aroma and ermented aroma (correlated positively with Component I)diered the samples B and C rom the others. Tus, these aromas were responsible orthe characterizing o these samples. It was possible to discriminate the samples based ingrape variety only by means o Component II o PCA with regard to the attributes oaroma (Figure 3).


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Regarding the attributes o mouth perceptions (Figure 4), components I andII totaled 83.3%. Alcoholic favor was important in characterizing sample A, andsample D was mainly characterized by body, sotness and ruity favor. Sample Cwas characterized by a higher intensity o astringency, sour taste and bitter taste. Tevinegary and ermented favors were important to characterize sample B while samples

E and F were characterized by higher intensity o sweet taste, although all the sampleswere dry red wine and probably contained a low content o total sugars.

Figure 3. Two-dimensional projection of the results obtained from the principal components analysis I

and II for the class of attributes that include aroma.

Figure 4. Two-dimensional projection of the results obtained from the principal components analysis Iand II for the class of attributes that include mouth sensations.


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A qualitative study o volatile compounds or the six brands o red wines analyzedwas conducted. 42 volatile compounds were identied, including 8 alcohols, 8 acids, 11ethyl esters, 4 acetates and 11 compounds belonging to other chemical classes (able 4).

Table 4. Volatiles compounds identified in red wine samples

*So Francisco Valley; **Serra Gacha; Rt=retention time (min); (+) identied compound. Identication

considering only similarity > 90%; 1Grbz et al. (2006); 2 Guarrera et al. (2005); 3 Vilanova et al. (2010); 4Falco et al. (2008); 5 Goldner et al. (2009); 6 Antalick et al. (2010); 7 ao et al. (2008).


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Identication o each aromatic compound may help in understanding theindividual contribution o each volatile compound in the aroma o wine. In allsamples, 1-propanol, 2-methyl-1-butanol and 3-methyl-1-butanol were detected.Tese compounds are among the quantitatively most important higher alcohols in wine(JACKSON, 2008). Phenethyl alcohol (ound in all samples) may have contributed to

the perception o a foral aroma during the QDA (able 1).Te increased intensity o the ermented aroma or sample C (able2) may be

associated with the presence o decanoic acid (able 4). Hexanoic acid was ound onlyin sample A , in agreement with the sensory analysis (able 2) which indicated thatsample A had the highest average or the buttery aroma. Octanoic acid was observedonly in sample C and is associated with unpleasant odors (able 4). Octanoic acid maybe related to a more intense aroma o sulphur (characteristic o rotten egg), which wasperceived by the sensory panel or sample C (able 2).

One important organic acid present in Vitis vinierawines is lactic acid, whichwas identied only in sample C. Lee et al. (2006) ound negative correlation betweenthe lactic acid content in red wines and their intensity o ripe ruit aroma. Tus, presenceo lactic acid may have contributed to the lower ripe ruit aroma scores in sample C(able 2). Acetic acid, in turn, was detected in samples B, C, E and F, which was also inagreement with the sensory perception o the vinegary aroma (able 2).

Among all the aroma compounds identied, the group o esters was one o themost abundant (able 4). Ethyl octanoate, ethyl decanoate and ethyl hexanoate wereound in all samples. ao et al. (2008) ound ethyl hexanoate, ethyl octanoate and ethyl

lactate in their wine samples, which gave a nice positive foral and ruity odor withhints o ripe ruits. In the current study, ethyl lactate was detected in samples B, D andE. Te highest intensity o ruity aroma, which was perceived in sample D (able 2),may also be related to the presence o ethyl isovalerate, ound only in this sample. Te9-ethyl decenoate may have avored high scores o foral aroma in the samples producedin Southern Brazil (able 2).

Ethyl acetate and isoamyl acetate were observed in all samples. Phenethyl acetatewas ound only in sample C, and it may have contributed to a greater perception o an

olive aroma by the judges (able 2), and to the characterization o this sample (Figure 3).With regard to the compounds belonging to other chemical classes, the onlyvolatile phenol identied was 2,4-di-tert-butyl-phenol (A and F). ao et al. (2008) alsoidentied this compound, but they did not report a specic aromatic description.

ao and Zhang (2010) ound that ethyl acetate, ethyl isovalerate, ethyl hexanoate,ethyl lactate, 1-hexanol, ethyl octanoate, hexanoic acid and octanoic acid among othercompounds have intense odors. Te 2,4-di-tert-butyl-phenol and phenyl ethyl acetatecompounds have been identied with moderate aromatic impact.

Many atypical compounds in red ne wines were detected in sample C (able

4) as toluene. Goldner et al. (2009) also detected toluene in samples o wine, but


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they did not discuss this compound. Te presence o these compounds may contributeto aromas and favors in sample C indicating a possible contamination o the wine.According to Comuzzo et al. (2006), derivatives o benzene (toluene, alkyl benzenes)are among the contaminants commonly detected in various oodstus including wine.Although sample C presented several favor compounds that gave ruity notes, such as

various esters and acetates, it may be possible that the aromatic eect was masked dueto compounds, such as acetic acid, octanoic acid and the atypical compounds describedabove (able 4).

Tis study helped to identiy the aromatic components o the red wine samplesproduced in the So Francisco Valley and Serra Gacha regions. Moreover, it is alsoimportant to explain the descriptors o aroma o red wine as ollows: a synergisticinteraction between volatile components, the association between wine compoundsand the chemical composition o wine.

Conclusions

Te ANOVA method o investigation showed that color attributes, pungentaroma, vinegary aroma and sotness were important attributes to discriminatesamples B and C (So Francisco Valley) rom sample E (Serra Gacha) produced romthe same grape variety (Cabernet Sauvignon). Te multivariate analysis (HCA and PCA)collaborated or the interpretation o sample discrimination, as it was possible to veriy

the ormation o two groups o samples rom dierent regions, characterized mainly bythe attributes o color, in the case o PCA. Te 9-ethyl decenoate was identied only insamples rom the Southern region and it may have contributed to the higher intensityo foral aroma in these wines.

Acknowledgments

Fundings rom Fundao de Amparo Pesquisa do Estado da Bahia (FAPESB)

are grateully acknowledged. Te authors would like to thank the Miolo, Botticelli,Bianchetti and Rio Sol wineries, the Laboratory o Analytical Chemistry (UNICAMP),especially Proessor Fabio Augusto, and all the judges who participated in the sensoryanalysis.

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Artigo recebido em: 31 jul. 2012

Aceito para publicao em: 28 ago. 2012

sensory profile and contribution of major

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