Relationship Between Chemical Markers and SensoryScore of Traditional Balsamic Vinegars Using a ScreeningApproach Combined with Rapid Assessment Methods

Andrea Versari & Giuseppina Paola Parpinello &

Arianna Ricci & Matteo Meglioli

Received: 16 January 2013 /Accepted: 25 February 2013# Springer Science+Business Media New York 2013

Abstract In this study, 200 samples of traditional balsamicvinegar (TBV) of Reggio-Emilia, a typical Italian “aged dress-ing”with Protected Denomination of Origin, were analyzed tomodel the relationship between sensory scores with some pre-selected compounds/parameters, such as Brix value, wateractivity (aw), titratable acidity, color, polymeric compounds,and electronic nose signal. Statistical techniques, such asnonlinear regression and Principal Component Analysis(PCA) were used to model the relationship among vinegarscomposition. The sensory score of panelists was mainly cor-related with Brix (r=0.85) followed by brown color at 445 nm(r=0.74) and water activity (aw) (r=−0.79), whereas the poly-meric compounds content showed a negative correlation withwater activity (r=–0.73). In particular, the water activity ofTBVs at different Brix values followed a nonlinear trendwith good fitting (r=0.857) with K=3.10 that was consis-tent with the value reported in the literature for fructoseand glucose. Electronic nose (enose) data from TBVs and sixmarker compounds (acetic acid, butyric acid, vanillin, ethyl-phenylacetate, phenylethyl alcohol, and furfural) combinedwith PCA revealed a pattern related to the ageing of TBVs.

Keywords Capillaryelectrophoresis .Enose .Melanoidins .

Norrish model . Sensory . Vinegar .Water activity

Introduction

Traditional balsamic vinegar (TBV) of Reggio-Emilia is adark, creamy, and tasty syrup obtained from the alcoholicfermentation and acetic bio-oxidation of cooked grape mustaged in small wood barrels for at least 12 years (up to 25 or40 years). TBVof Reggio-Emilia is classified as “aged dress-ing” (GURI 1987) and has been recently distinguished withthe “Protected Designation of Origin” (PDO) by the EuropeanUnion (Commission Regulation (EC) No. 813/2000). Theactual PDO certification of TBV is based on sensory evalua-tion together with two simple physical-chemical parameters:total acidity and density (GURI 2000).

However, TBV is a complex mixture of water and numer-ous classes of compounds, including carbohydrates, organicacids (Cocchi et al. 2006), phenolics (Plessi et al. 2006),furans (Masino et al. 2005), melanoidins (Falcone andGiudici 2008; Falcone et al. 2011; Falcone et al. 2012), andvolatiles (Chinnici et al. 2009; Xiao et al. 2011). In particular,melanoidins are colored polymers produced during grapemust heating (Piva et al. 2008) mainly by Maillard condensa-tion reactions of sugar and amino acids (Montevecchi et al.2010) or other mechanisms that lead to nitrogen-freemelanoidins (Falcone et al. 2011).

The composition of TBV is variable and depends on sev-eral factors, mainly the raw material, the acetification systemused, and the ageing in wood barrels during which the productundergoes a further slow concentration process by waterevaporation through the staves of the barrels. Moreover, everyyear, new cooked must is added and aliquots of product aretransferred from barrel to barrel (Fig. 1). This proceduregenerates a blend of vinegars of different ages (Giudici andRinaldi 2007) and composition. In the first barrels, the alco-holic fermentation and a subsequent acetic bio-oxidation

A. Versari (*) :G. P. Parpinello :A. Ricci :M. MeglioliDepartment of Agricultural and Food Sciences,University of Bologna, Piazza Goidanich 60,Cesena, FC 47023, Italye-mail: andrea.versari@unibo.it

Present Address:M. MeglioliMosti Mondiale, 6865 Route 132,Ville Sainte-Catherine, QC J5C 1B6, Canada

Food Anal. MethodsDOI 10.1007/s12161-013-9594-8

occur, whereas in the following barrels, the composition (i.e.,water activity, pH, acetic acid content) gradually prevent anyfurther biological activity.

Considering the high commercial value of the product, theclassification of TBVs is important to control the productionprocess and to guarantee the product quality and for regulatorypurposes as well. By tradition, the quality control of TBV isbased on sensory analysis with a trained panel, whereas there isa need for rapid analytical methods to monitor the ageing ofTBV. One method, the electronic nose (enose), is a promisingtechnique that has been recently used for monitoring the ageingof several foods, including wine (Apetrei et al. 2012) and beer(Ghasemi-Varnamkhasti et al. 2011), with good agreementwith chemical analysis and sensory panel evaluations. Thepioneering work of Anklam et al. (1998) showed the abilityof enose with polymer sensors to discriminate between twodifferent groups of balsamic vinegars of Modena (total 21samples). Today, application of enose to vinegars is still limitedto origin classification only (Zhang et al. 2008).

The aim of this study is to model the relationship betweenselected physico-chemical and sensory parameters (Brixvalue, water activity, titratable acidity, color, polymericcompounds, the overall sensory score, enose) of 200 TBVsof Reggio-Emilia using a screening approach and rapidevaluation tool for traditional balsamic vinegars qualitycontrol.

Materials and Methods

Sensory Analysis of Traditional Balsamic Vinegars

Two hundred samples of TBV of Reggio-Emilia werecollected from local producers and evaluated by at leastfive master experts (Confraternita dell’Aceto BalsamicoTradizionale Reggiano, Reggio-Emilia, Italy) trainedaccording to international standards (ISO 8586-1 1993;ISO 8586-2 2008) using a score card based on a total of400 points (Versari et al. 2011). Each sample was tastedby at least five expert panelists, and the mean sensory

score for the panelists was computed. The score cardused for sensory evaluation is based on a total of 400points distributed as follow: visual attributes (56 points),aroma attributes (104 points), taste and texture attributes(200 points), and 40 points for the final overall sensation.The total score used in this study is the aggregate num-ber of different attributes, thus samples with the sametotal score would not necessarily have the same chemicalcomposition.

Analytical Methods

For each TBV sample, the following physico-chemical pa-rameters were measured: titratable acidity (TA) (TIM 900titration manager, Radiometer, Copenhagen, Denmark), totalsoluble solids (TSS) (digital refractometer PAL-1, Atago,Bellevue, WA, USA), turbidity (NTU) (turbidimeter mod.18900, Hach, Milan, Italy) (GURI 1986), and optical densityat 625, 550, 495, and 445 nm (Lambda 45 UV/Vis spectro-photometer, Perkin-Elmer, Milan, Italy) that are useful forestimating color response/difference related to sensory analy-sis (Jackson 2002). Data from spectral analysis wereexpressed as absorbance unit (AU) with 1 cm path lengthand corrected by dilutions (OIV 2007). Water activity (aw)was measured using an electronic dew point water activitymeter AquaLab 3TE (Decagon Devices, Pullman, WA, USA)calibrated with saturated salt solutions in the water activityrange of interest. Measurements were conducted at 20±0.5 °C,and the average of duplicate measurements was reported.

Polymeric compounds were analyzed in Capillary ZoneElectrophoresis (CZE) according to Morales (2002) using aCE P/ACE system 5000 (Beckman, Palo Alto, CA) equippedwith a UV–VIS detector set at 280 and 440 nm, and a P/ACEStation 1.21 data system to record the electropherograms(Fig. 2). An uncoated fused-silica capillary (total length52 cm; effective length to the detector 40 cm; i.d. 50 μm)was conditioned successively with 1 M sodium hydroxide(15 min), CE-grade water (5 min), then rinsed with the run-ning buffer 50 mM sodium tetraborate pH9.3 (15 min). Priorto each hydrodynamic sample, injection carried out at theanode for 5 s the capillary was flushed with 0.1 M NaOH(15 s), and 50 mM sodium tetraborate pH9.3 for 30 s.Analyses were performed at 25 °C and a voltage of 25 kVacross the capillary was applied for 15 min. Due to lack ofcertified standards, the semi-quantitation of polymeric com-pounds was based on peak area, whereas the further chemicalcharacterization of the melanoidins is beyond the scope of thepresent study.

Electronic Nose (e-Nose)

The electronic nose is a device composed of an array of gassensors, with non-specific responses, having pattern

Fig. 1 Example of typical barrel set for TBV production. The changeof color during ageing is indicative only. The procedure of refilling thebarrels with the vinegar from the previous barrel is called “rincalzo”

Food Anal. Methods

recognition ability based on the multivariate data analysis ofthe whole set of responses (Gardner and Bartlett 1994).Each TBV was placed into a glass vial (capacity 10 ml), with gas inlet and outlet tubes fitted through the lid,and vials were sealed and held at 25 °C for 60 min forheadspace equilibration. After this period, the headspacewas analyzed with a commercial electronic nose PEN2(Airsense Analytics, Milan, Italy) composed of an arrayof ten temperature-moderated metal-oxide sensors(MOS), a sampling system and a data acquisition de-vice. The signal output of the sensors is digitized byrecording and normalized to a value of 1.0 prior tosampling; this arbitrary baseline value was subtractedfrom the sensor responses prior to enhancement deter-mination. The signal output was measured at 1 sintervals for 120 s, long enough for most of the sensorsto reach a steady-state. For each sensor, the value at120 s was used for the pattern recognition studies bymeans of principal component analysis (PCA). Besidesthe TBVs, six standard solutions of marker compoundsof ageing (acetic acid, butyric acid, vanillin, ethyl-phenylacetate, phenylethyl alcohol, and furfural) wereanalyzed with the same procedure.

Statistical Analysis

The relationship between the water activity of TBV and theBrix values was fitted with nonlinear regression by theNorrish equation (Norrish 1966): aw=Xw exp (−KXs

2),where Xw is the molar fraction of water, Xs is the molarfraction of sugar, and K the constant to be determined.Besides, the experimental approach included the use ofprincipal component analysis (PCA), a descriptive non-parametric method commonly used to examine the relation-ships among the variables and grouping among samples(Lewi 1992). Statistics calculations (mean, SD, CV%) andPCA for the sensory and physico-chemical parameters of tra-ditional balsamic vinegars of Reggio-Emilia were performedusing MINITAB software (MINITAB v. 15.0, Minitab Inc.,State College, PA, USA).

Results and Discussion

Composition of TBV

A preliminary physico-chemical and sensory characteriza-tion of 200 samples was carried out and Table 1 shows themean, SD, and coefficient of variation of TBV samples forsensory score, total soluble solids, titratable acidity, wateractivity, and color parameters. The TSS of TBV samplesranged from 17.9° to 79.2° Brix, and the titratable acidityvaried from 1.1 % to 8.9 % showing values in agreementwith a previous study (Masino et al. 2005; Lemmetti andGiudici 2011). Titratable acidity of TBV is mainly due toacetic acid, originating from the acetic fermentation,followed by other carboxylic acids including citric, malic,succinic, tartaric, and gluconic acid (Sanarico et al. 2003).Several samples were below a minimum value of titratableacidity 5 % (w/w) fixed for TBV of Reggio-Emilia by law(GURI 2000). This limit of 5 % titratable acidity was fixedonly recently in 2000; therefore, the samples analyzed inthis study and produced before the year 2000 most likelyused different production protocols. The acidity of TBVsdepends on several factors (e.g., grape maturity, concentra-tion process, fermentation, bio-oxidation) and the value can

Fig. 2 Electropherogram ofpolymeric pigments (gray area)found in traditional balsamicvinegar

Table 1 Statistics for the sensory and physico-chemical parameters oftraditional balsamic vinegars of Reggio-Emilia (N=200 samples)

Parameter Mean±SD (CV%) Min–max

Sensory score 253±31 (12) 133–306

Total Soluble Solids (Brix) 65±10 (16) 18–79

Water activity (aw) 0.91±0.08 (9) 0.62–0.98

Turbidity (NTU) 1451±1178 (81) 61–8649

Titratable acidity (% w/w) 5.1±1.2 (24) 1.1–8.9

625 nm (AU) 0.08±0.07 (86) 0.001–0.56

550 nm (AU) 0.05±0.05 (92) 0.001–0.43

495 nm (AU) 0.17±0.08 (47) 0.009–0.44

445 nm (AU) 0.28±0.12 (45) 0.022–0.67

Food Anal. Methods

change with time during processing and storage. Inparticular, following the bio-oxidation of acetic duringageing, the total acidity increases significantly due tothe production of acetic acid by ethyl alcohol and canreach levels well above 12 %. Taking into account theseveral variables of the vinegar production, it is a matter offact that products with different characteristics are available atproduction stage. When all the parameters fit the regulatoryrequirements, the product is ready for the market as certifiedTBV.

The water activity of TBVs (aw range, 0.62–0.98) wascompared to their Brix values (range, 18–79) and the data werefitted with nonlinear regression (Fig. 3). The fermentation ofcooked must involves the growth of different species of yeasts,whereas increasing Brix values resulted in a noticeable reduc-tion in water activity which implies a decreased risk of con-taminant yeast growth. In this view, the aw value of 0.62 isconsidered the lower limit for microbial growth (Fontana 2007)referred to Zygosaccharomyces rouxii, a yeast involved invelum formation during biological ageing of sherry wine(Esteve-Zarzoso et al. 2004).

Once in solution the sugars can bind water, thus reducingthe partial pressure of water vapor. Consequently, as thesesugars content increases during ageing of traditional balsamicvinegar the resulting aw decreased. Water activity decreasessignificantly during aging, and it progressively becomes thelimiting driving factor for the evaporation (Solieri et al. 2012).The water activity is usually described by the Norrish equation(Norrish 1966): aw=Xw exp (−KXs2) that considers the wateractivity to be a function of the mole fraction of each solublesolute present in the system and K values have been reportedin literature for a range of aw value for solutions of fructose(K=2.25), sucrose (K=6.47), glycerol (K=1.16) , xylitol (K=1.66), sorbitol (K=1.65), and polyethylene glycols 400 (K=26.6) and 600 (K=56) (Baeza et al. 2010). The experimental

K value (3.10) found in this study for TBV samplesshowed a good fit to the model (r=0.857) and was similar tothe literature value (K=2.25) reported for fructose and glu-cose. These two carbohydrates make up for approximately91 % on a dry matter basis of grape juice (Chirife et al. 2011),whereas they represent on average approx. 70–77 % on a drymatter basis of traditional balsamic vinegars (Masino et al.2008). Minor discrepancies from theoreticalK values reportedin the literature with standard solutions can be attributed to theinteractions among dissolved solutes and surface effects be-tween solutes and polymeric compounds present in TBVssuch as melanoidins.

Electronic Nose and PCA

A subset of twenty samples (Table 2), representative of theentire range of Brix and water activity values found in thisstudy (Fig. 3), was selected for further analysis by enose andexamined with PCA analysis looking for the hidden contri-bution of the volatile compounds linked to product ageing.In fact, TBVs contain a considerable number of volatilecomponents, including alcohols, acids, aldehydes, and estersthat contribute to both the aroma of the product (Chinnici etal. 2009; Cirlini et al. 2011), and the signal can be detectedby the enose sensors (Anklam et al. 1998).

Two PCAs were used for looking at trends and groups inthe normalized data (mean=0; SD=1). Based on response

Fig. 3 Relationship between water activity (aw) and total solublesolids (Brix value) of TBV at 20 °C. Samples (N=20) that match theregression line were selected for further analysis (red dot)

Table 2 Statistics for the sensory and physico-chemical parameters ofa subset of traditional balsamic vinegars of Reggio-Emilia (N=20samples)

Parameter Mean±SD (CV%) Min–max

enose sensor 1 (S1) 0.52±0.08 (15) ―

enose sensor 2 (S2) 2.15±0.62 (29) ―

enose sensor 3 (S3) 0.61±0.07 (11) ―

enose sensor 4 (S4) 1.01±0.04 (4) ―

enose sensor 5 (S5) 0.72±0.06 (8) ―

enose sensor 6 (S6) 1.46±0.21 (14) ―

enose sensor 7 (S7) 1.03±0.01 (1) ―

enose sensor 8 (S8) 1.65±0.30 (18) ―

enose sensor 9 (S9) 1.05±0.03 (2) ―

enose sensor 10 (S10) 1.00±0.03 (3) ―

Sensory score 218±33 (15) 133–263

Total Soluble Solids (°Brix) 56±15 (27) 18–79

Water activity (aw) 0.83±0.10 (12) 0.62–0.98

Turbidity (NTU) 1480±2090 (141) 61–8649

Titratable acidity (% w/w) 4.63±1.68 (36) 2.5–8.9

625 nm (AU) 0.07±0.05 (80) 0.003–0.211

550 nm (AU) 0.04±0.04 (83) 0.001–0.125

495 nm (AU) 0.15±0.10 (63) 0.031–0.331

445 nm (AU) 0.25±0.15 (62) 0.064–0.583

Food Anal. Methods

variability, only five sensors (S1, S2, S3, S6, and S8) out of tenwere used for PCA analysis. The S1, S2, S3, S6, and S8sensors were associated with aromatic, broad range, aromatic,broad-methane, and broad-alcohol attributes, respectively. Apreliminary PCA analysis was carried out using, in combina-tion with the 20 TBVs, six selected standards: acetic acid,butyric acid, vanillin, ethyl-phenylacetate, phenylethyl alco-hol, and furfural (Fig. 4). In particular, S2 was associated withacetic and butyric acid, whereas S1 and S3 were associatedwith ethyl-phenylacetate and furfural. Even with the lack ofvisible clusters among samples due to large within-groupvariation in the data, the position of the volatile standards onthe PCA plot revealed the presence of a trend starting fromacetic acid (bottom right) to ethyl-phenylacetate (upper left)that reflected the importance of the TBV compositionalchange with time.

In fact, according to the literature, butyric acid and van-illin are expected to increase with ageing (Chinnici et al.2009), whereas the balance of acetic acid during aging ofTBV is the result of its initial production via the bio-oxidation phenomena and the slow evaporation during theageing phase. However, it is a matter of fact that TBVs get ahigh sensory score when acetic acid is low (Masino et al.2008). Regarding the ethyl-phenylacetate, this compoundhas a strong and sweet fragrance of honey (Tat et al. 2007)and, like many other volatile esters, is most likely synthe-sized during both alcoholic and acetic fermentation andageing (Cirlini et al. 2011). Also, phenylethyl alcohol iscommonly used in the flavor industry and is considered animportant flavor component of wine vinegar (Xiao et al.2011). Furfural confers a caramel or vanilla-like odor(Reazin 1981) and together with 5-hydroxymethyl-furfuralincreases with time during the ageing period of TBV mostlydue to water evaporation, as well as the degradation(hydrolysis) of sugars (Cocchi et al. 2011).

With regards to the sensory quality of TBVs evaluated bythe expert panelists, the first two principal componentsaccounted for 66 % of the score’s plot total variance (PC1and PC2 accounted for 39 % and 27 % of the variance,respectively) (Fig. 4). The limited clustering can be explainedtaking onto account the periodically refilling of barrels usuallycarried out result in a blending of vinegars of different ages.The variation in PC1 and PC2 can to some extent be ascribedto the volatile composition of the TBV that provided comple-mentary information to the other selected parameters. In par-ticular, the sensory score of panelists was mainly driven byBrix values (r=0.85) followed by brown color at 445 nm (r=0.74) and aw (r=−0.79), whereas little contribution was foundfor the enose sensors (r<0.27). We have formulated the hy-pothesis that the presence in this study of many TBV samplesevaluated below 240 points (the minimum value to get theorange certification) could have affected the performance ofthe judges that are usually trained to taste TBV samples readyfor marketing.

Our results are consistent with the finding of Masino etal. (2008) who reported a correlation of 0.901 betweensensory quality score and Brix values of TBVs. Despitethe detailed knowledge available of the chemistry of thevolatile components of TBVs, research into the relationshipbetween volatiles and the sensory profile (i.e., aroma) ofTBVs is still in progress. Recently, Chirife et al. (2011)found that samples with the highest Brix values (i.e., 71.8–76.0) were associated with increased sweetness, caramelflavor, visual viscosity, and reduced sourness and aceticaroma, all of which are desirable from the sensory point ofview. In particular, it is well known that a high level ofacetic acid commonly found in TBV is responsible for thepungent sensation which tends to mask the aroma percep-tion and causes a feeling of fatigue in the sensory receptors.

Fig. 4 PCA plot of scores (black dot) and loading of the first two PCsof traditional balsamic vinegars of Reggio-Emilia. TBVs samples(black dot) and selected standard compounds (red dot) are plottedtogether with the loading of the enose sensors (S1, S2, S3, S6, and S8)

Fig. 5 Relationship between water activity (aw) and polymeric com-pounds of TBV

Food Anal. Methods

Capillary Electrophoresis of Polymeric Compounds

Although water activity play an important role in the Maillardreaction (Labuza and Saltmarch 1981), there is a lack ofliterature with regard to the relationship between the wateractivity and the polymeric compounds content of TBVs thatshowed a negative correlation (r=–0.73) (Fig. 5), whereas theircorrelationwith brown color of TBVsmeasured at 440 nmwaspositive (r=0.65). With respect to moisture level, the polymer-ic compound content is minimum at high aw level as a result ofdilution of the reactant species. The effect of water activity onchemical reactions in TBVs is difficult to link to a singlemechanism because the reaction mechanisms are complex.Besides chemical reaction, the physical changes and structuretransitions of melanoidins can also play an important role invinegar jamming, i.e., the decrease of the vinegar viscosity,that can be predicted through three simple parameters: refrac-tive index, the sum of glucose and fructose, and shear viscosity(Falcone et al. 2012). Similarly to our approach, Falcone andGiudici (2008) analyzed TBVs with high performance liquidsize exclusion chromatography (SEC) using the signal at420 nm to quantify the products of polymerization reactionsthat were found good descriptors of TBVaging.

Conclusions

Understanding the evolution-related changes in the physico-chemical composition and sensory profile is critical to improvethe identification and classification of TBVs obtained bymixing samples belonging to casks of different ageing. PCAapproach allowed to visualize the relationships between sensorresponses and the chemical composition of TBV highlightingthe parameters and the trend most likely related to the ageingprocess. Assuming the existence of common patterns forchanges in volatile composition of TBV with time, to improvethe ability of the PCA model to cluster the samples, there is aneed for certified samples with known origin (e.g., type ofcooked grape musts and wine vinegars, processing and storageconditions, age, etc.) keeping in mind the minimum periodrequired by law for TBV certification, i.e., 12 years.

Conflict of Interest Andrea Versari declares that he has no conflictof interest. Giuseppina Paola Parpinello declares that he has no conflictof interest. Arianna Ricci declares that he has no conflict of interest.Matteo Meglioli declares that he has no conflict of interest. This articledoes not contain any studies with human or animal subjects.

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