International Journal of Food Studies IJFS April 2017 Volume 6 pages 95–112

Rheological Properties of Traditional Balsamic Vinegar: NewInsights and Markers for Objective and Perceived Quality

Pasquale M. Falconea*, Elisa Sabatinellia, Federico Lemmettib, and PaoloGiudicib

a University Polytechnical of Marche - Department of Agricultural, Food and Environmental Sciences, BrecceBianche 2 – 60128 Ancona, Italy

b University of Modena and Reggio Emilia, Unimore Microbial Culture Collection – Department of LifeSciences – Via Giovanni Amendola 2 - 42122 Reggio Emilia, Italy

*Corresponding authorpm.falcone@univpm.itTel: +39 0712204138

Received: 24 October 2016; Published online: 18 April 2017

Abstract

The molecular structure of Traditional Balsamic Vinegar (TBV) undergoes shear-induced and time-dependent jamming transitions due to the high solute concentration and self-assembling phenomena ofhigh molecular size melanoidins with very-long relaxation times (12 years at least or more than 25).The purpose of this work was to perform a descriptive and quantitative evaluation of relationshipsbetween rheological properties, vinegar composition, and perceptual assessment of sensory propertiesaccording to the official sensory procedure. With this aim, vinegars having quality traits matching legalrequirements for the PDO designation were analyzed for their reducing sugars (glucose and fructose),volatile acidity, fixed acidity, pH, Brix degree, and density as well as for their flow behaviour anddynamic viscosity over a wide range of shear rates. Results showed that flow behaviour of TBV wasaffected by jamming properties over wide-scale ranges of shear rate producing flow instability belowa shear rate of 60 s−1. Homogeneous, continuous flow was found at medium-high shear rates withthickening and/or thinning traits. A common onset for the structure scaling was mathematicallyestimated to occur close to when the density was 1.32 gmL−1. Comparative analysis of rheological,compositional and sensory properties suggested that the colloidal jamming of the vinegar melanoidinsdominated the total olfactive and gustative stimuli, and determined the classification of the vinegarsthat had a higher dynamic viscosity but more homogeneous flow as being of the highest commercialquality category. A robust statistical model was proposed encoding for the top-down decision-makingprocess for quality assignment according to the official sensory procedure, using composition and flowproperties as predictor variables.

Keywords: Jamming transition; Melanoidins; Flow properties; Viscosity; Perceptual assessment ofsensory properties; POD disciplinary

1 Introduction

Traditional Balsamic Vinegar (TVB) of Mod-ena (TBVM) and Traditional Balsamic Vinegarof Reggio Emilia (TBVRE) are two high-valueItalian aged vinegars produced in the Modena

and Reggio Emilia provinces (northern Italy), forwhich the European Council has granted PDOstatus, i.e. protected geographical origin anddesignation (Gazzetta Ufficiale della RepubblicaItaliana 124/2000; Regulation EC 813/2000).Two independent authorities certify the age and

Copyright ©2017 ISEKI-Food Association (IFA) 10.7455/ijfs/6.1.2017.a9

96 Falcone et al.

quality requirements imposed by the regulationaccording to the official taste procedure, whichis based on the sensorial ranking of a series ofcoded visual, olfactory, gustatory and olfactory-gustatory attributes and on the instrumentalmeasurement of density and titratable acidity.Originally, these artisanal products were onlyavailable to Italians on higher incomes, but nowboth TBVs are gaining worldwide great recogni-tion for their sensorial, nutritional, health prop-erties (Tagliazucchi, Verzelloni, & Conte, 2010;Lemmetti, Falcone, & Giudici, 2013; Lemmetti,Solieri, Bonciani, Zanichelli, & Giudici, 2014).TBV is very labour-intensive to produce andit is the only vinegar around the world thatis produced starting from cooked grape juiceonly. The historical procedure requires thatthe grapes must be cooked with a direct flamein open vessels, then the cooked must is fer-mented and oxidized by autochthonous microor-ganisms and, finally, the resulting vinegar ageswithin casks of decreasing volumes made of dif-ferent woods (oak, mulberry, chestnut, cherry,juniper, ash, and acacia). While it ages overdecades and gradually evaporates under seasonaltemperature and relative humidity, the vinegaris transferred to successively smaller casks be-coming sweet, concentrated, flavoured and vis-cous. Time plays a central role in the overallproduction of TBV, requiring a legal minimumfor the aging period of 12 to 25 years at least,which promotes profound changes in composi-tion (Plessi, Monzani, & Coppini, 1988; Cocchiet al., 2006), volatile compounds (Duran Guer-rero, Chinnici, Natali, Natera Marin, & Riponi,2008), rheological (Falcone, Chillo, Giudici, &Del Nobile, 2007, 2008) and sensory properties(Giudici, Falcone, Scacco, & Lanza, 2009). Theclasses of the major components in TBV in-clude glucose, fructose, acetic, gluconic, malic,tartaric, and succinic acids. The classes of theminor compounds refer mainly to volatile com-pounds, polyphenols and melanoidins, a compo-sitionally and structurally heterogeneous blendof sugar/phenol-derived polymeric melanoidinsshowing antioxidant and radical scavenging prop-erties (Verzelloni, Tagliazucchi, & Conte, 2007).From a physical perspective, TBV has beenrecognized as a soft material showing differ-ent flow behaviours spanning from Newtonian

to shear thinning, shear thickening and vis-coelastic regimes under controlled shearing con-ditions. Using different and complementary tech-niques, the major contribution of the polymericmelanoidins to local jamming phenomena form-ing metastable structures has been recently rec-ognized throughout the entire aging process (Fal-cone & Giudici, 2008; Falcone, 2010; Falcone,Boselli, & Frega, 2011, 2012). “Jamming” is aterm widely used in the science of food structurefor soft materials (Mezzenga, Schurtenberger,Burbidge, & Michel, 2005; Ubbink, Burbidge,& Mezzenga, 2008) in order to describe howtheir constituents may result metastable struc-tures that reach a minimum free energy as well ashow some external parameters including density,temperature, and mechanical stress can influencesuch out-of-equilibrium structures by enhancing,reducing or eliminating the ability to flow (Liu& Nagel, 1998; Cates, Wittmer, Bouchaud, &Claudin, 1998; Trappe, Prasad, Cipelletti, Segre,& Weitz, 2001; Liu & Nagel, 2001). Falcone etal. (2012) attributed vinegar jamming to the self-assembly properties of vinegar melanoidins dueto their molecular properties: (i) the wide rangeof molecular size distribution that spreads from200Da to beyond 2000kDa (ii) the distribution onthe chain backbone of attractive net charges andbulky aromatic phenolic residues. Other compo-sitional factors were also hypothesized to play arole in the extent of colloidal jamming in long-aged vinegars: Fe and Mg content were higherand pH was lower in jammed fractions of thevinegar rather than flowing ones.From a sensory perspective, the personal abilityof trained judges to classify vinegars according totheir sensing and perceptual assessment of vine-gar properties is first to develop a codified con-cept of the visual, taste, olfactory, and trigeminalproperties. Then they are required to evaluatesuch vinegar properties in an independent wayunder a series of mechanical stimuli the most ofwhich arise into the mouth before, during andafter swallowing. However, the independence ofthe stimuli assessment is not realistic in literalsense due to the simultaneous nature of humanperceptions of chemical and flavour resulting insynergistic or masking effects depending on me-chanical stimuli. In other food beverages of sim-ilar composition and at the same temperature,

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New Quality Markers for Traditional Balsamic Vinegar 97

the viscosity affects flavour release (Cook, Hol-lowood, Linforth, & Taylor, 2003; Hollowood,Linforth, & Taylor, 2002; Vingerhoeds, de Wijk,Zoet, Nixdorf, & van Aken, 2008), and deter-mines threshold for sweetness and creaminessperception (Zahn, Hoppert, Ullrich, & Rohm,2013). Thickness is the texture attribute world-wide used to describe perceptual assessment ofthe flow behaviour of a food beverage. Thick-ness can be assessed in the mouth by judgingthe resistance of the sample to flow, the rate offlow, or the amount of force needed to translocatethe fluid in the mouth (Akhtar, Stenzel, Murray,& Dickinson, 2005). For a more objective eval-uation, the simple approach of considering thetongue-palate as two plates has been used for along time as a basis for attempting to associatethe thickness of food materials to the dynamicviscosity measured in the cone-plate or cylindri-cal geometry of a rheometer (Chen & Engelen,2012). Thus, the dynamic viscosity of a homoge-neous fluid can be interpreted as a macroscopicexpression of the friction of the constituents op-posing the flow under controlled shearing condi-tions. However, it is important to have knowl-edge about the smallest differences in dynamicviscosity that the human senses can discriminate:the same thickness does not necessarily meanthe same dynamic viscosity (Camacho, Dop, deGraaf, & Stieger, 2015).The purpose of this work was to perform adescriptive and quantitative evaluation of rela-tionships between rheological properties, vinegarcomposition, and perceptual assessment accord-ing to the official taste procedure.

2 Materials and Methods

2.1 Sourcing of vinegar samples

In order to characterize vinegars for their rheo-logical properties, all vinegar samples were ran-domly collected from different vinegar farms withthe aim of having a broad distribution of productcomposition, structure and flow behaviour. How-ever, only vinegars having quality traits match-ing legal requirements for the PDO designationwere analysed for their composition and rheolog-ical properties. Besides the requirements for the

production process, the regulation specifies thechemical-physical parameters and sensory traits,indicating as compulsory their perceptual assess-ment before submitting vinegar lots for PDOauthorization. The official sensory procedureimposes firstly the trained evaluation of visualtraits, followed by olfactory perception and fi-nally tasting, i.e. viscosity, colour and clearnessfor the “visual traits”; delicacy, defectiveness,persistence and acidity for “olfactory traits”; full-ness, maturity, harmony and acidity for “gusta-tory traits”. Perceptual discrimination and clas-sification of all these organoleptic properties arisefrom a human complex decision-making processdriven by sensory and psychological factors thatare expressed by the judges as quantitative andcumulative scores. Official sensory panels awarda final score, which determines the commercialquality and price categories: the Consortiumof the ABTRE discriminate three quality lev-els (“aragosta”, “argento”, and “oro”). Trainedjudges individually taste and express their eval-uation filling a structured questionnaire: eachsensory descriptor has a pre-printed ranking ofscores and the panellist has to indicate the scorethat best matches his or her perception of inten-sity.In this work a trained panel composed of fivemembers from the official list of “ABTRE experttasters” registered in the Chamber of Commerceof Reggio Emilia was asked to analyse more thanone thousand TBVRE vinegars for their visual,gustatory and tasting traits according to the of-ficial sensory procedure as well as for rankingthem on the basis of their perceptual intensity.For these vinegars the producers claimed an ag-ing period ranging from 12 to 25 years, whichgranted them the participation in the historicalpublic competition known as “Palio Matildico”held at 2014 in Arcevia (Reggio Emilia, Italy).Only 100 vinegars received the judgment “vine-gar matching law requirements for the PDO des-ignation” from which a subsets of 20 vinegarswas assigned to the quality level “oro”, whilethe remaining 80 vinegars were assigned to the“aragosta” or “argento” ones. In this work “F”is the label assigned to those vinegars that judgesrecognized as to “aged vinegars of very-high sen-sory quality” and corresponding to the qualitylevel “oro”; while “R” is the label assigned to

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those vinegars that judges recognized as to “agedvinegars of acceptable sensory quality” and cor-responding to the quality level “aragosta” or “ar-gento”. All of samples were further coded usingrandom alpha numeric labels “F[n]” or “R[n]”with [n] the three digit part of the code.

2.2 Composition properties

Vinegars samples were analysed for glucose andfructose (the sum of which is indicated as “sug-ars”), volatile acidity (AcVol), titratable acid-ity (AcTit), fixed acidity (AcFix), pH, specificweight (density) and Brix degree (Brix). Densitywas measured with a hydrostatic balance (Den-simat, Gibertini, Italy) and Brix with a refrac-tometer (2WA, Alessandrini, Italy); they wereused to cumulatively estimate the overall concen-tration of the vinegar. Enzymatic kits (RochesCo. Darmstad, Germany) coupled with a spec-trophotometer UV-Vis (V-550, Jasco, Japan)were used to determine the sugars and acetic acidconcentration (% w/w), the latter was assumedequivalent to the AcVol. AcTit was determinedwith titration method using NaOH and phenoph-thalein indicator to stop neutralization at pH 7.AcFix was calculated as difference between Ac-Tit and AcVol. A digital pH-meter (model 8417,Hanna Instruments, Padova, Italy) was used tomeasure the pH value after dilution with HPLC-grade water in the ratio 1 to 10 by weight.

2.3 Rheological experiments

Flow behaviour was investigated with a rheome-ter (Rheomat RM180, Maple Instruments)equipped with concentric cylinders complying tothe size requirements of DIN 53019 (or ISO 2555)as the measuring system. Shear stress datawere acquired by performing steady-state shear-ing tests based on the step changes of single pointmeasurements, i.e. torque required to hold fora given time the vinegar sample under shearingat a given shear rate (with an accuracy of therotation speed was ± 0.5% of the actual value).The dynamic viscosity was calculated as the ratiobetween the shear stress and steady-state shearrate. Flow experiments were carried out withinmeasuring tubes immersed in a water bath for

temperature control (25±0.5 °C). Samples wereloaded into the system, allowing them to comeout gently from a vial reservoir. The waitingtime required establishing a baseline shear his-tory was fixed at 5 minutes.

2.4 Flow curve analysis andmodelling

Stress data were analysed as a function of shearrate by means of a theoretical model. Softwarepackage Pro Fit ver. 6.2.16. (Quantum Soft Inc.2015, Uetikon am See, Switzerland) was used torun the robust algorithm for non-linear regres-sion of the models. For comparative purposes,fitting parameters were estimated together withtheir confidence limits (95%, p<0.05). Erroranalysis was performed accounting for 0.5% onthe actual value of shear rate and running thefitting procedure 500 times so that descriptivestatistics were finally calculated from the distri-butions of the parameters. The goodness-of-fitwas evaluated by calculating the mean relativeerror according to Boquet, Chirife, and Iglesias(1978), using expression (1).

E =100

N×

N∑i=1

|(yobsi − ycalc|ycalc

(1)

Where yobs are the experimental data, ycalc arethe predicted data; N is the number of datapoints

2.5 Statistical Analysis

Descriptive, principal component and tree classi-fication analyses were performed using the soft-ware package STATISTICA ver. 10 (StatSoftInc. 2011, Tulusa, USA) accounting for com-position and rheological data as input variableswith and without a grouping variable in order toperform supervised and unsupervised analysis ofdata structure.Unsupervised recognition methods are helpfulwhen the researcher wishes to discover the classmembership of a sample, while supervised pat-tern recognition methods are helpful to discoverthe sample properties that distinguish sampleclasses. In this case, the algorithm requires

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New Quality Markers for Traditional Balsamic Vinegar 99

class information to be input. It is well knownthat conventional principal component analysis(PCA) can be performed as a classical data anal-ysis method providing a dimensionality reductioninto data set able to capture the maximum vari-ability in the data, and can be viewed as mod-elling the covariance structure of the data. How-ever, the effectiveness of conventional PCA islimited to unsupervised problems, making it im-possible to guide the algorithm toward the modesof variability that are of particular interest. Inthe present work, we were interested to classifyvinegars on the basis of their composition andrheological properties, attempting to project theexplanatory variables along directions that wererelated to a desired response variable, i.e. R andF quality category. This goal is not achieved byusing the directions that have maximum vari-ation. Thus, in order to discover compositionand rheological properties able to classify vine-gars belonging the quality categories (i.e. F orR), we performed a “supervised principal com-ponent analysis” using quality category as group-ing variable and all composition and rheologicalproperties as independent variables. The latterwere used as input for supervised PCA and cho-sen from those showing the most statistical sig-nificance in the Kolmogorov-Smirnov two-sampletest. The latter test was compared to standarddescriptive statistics based on theoretical sym-metrical distribution of data.Without any a priori hypotheses about howmany independent quality categories as well asabout what and how many vinegars may havebelonged to each of them, unsupervised classifi-cation of the vinegars was performed by meansof tree classification analysis (TCA) for whichall composition and rheological properties wereused as predictor variables. Classification, split-ting and validation rules were used to examinetheir effects one at a time, rather than just allat once. The unsupervised top-down classifica-tion process started by dividing the initial set ofvinegars into subsets in a hierarchical manner,using the best splitting value test for one com-position or rheological property at time used astarget variable. Such recursive partitioning wascompleted when splitting no longer added valueto the predictions. The classification rule was toassign membership of vinegars to the F or R cat-

egory with the same accuracy regardless of thefrequency really assigned by the judges. Vinegarmisclassification was evaluated by comparing theunsupervised vinegar classification and the as-signment of them into the two quality categoriesby trained judges based on their perceptual as-sessment of their sensory properties. In orderto minimize misclassification error, only one case(one vinegar sample) was imposed as a stoppingrule at terminal nodes. The initial data set wasdivided into the training and validation datasetand a V-fold cross validation algorithm (with Vequal to 60) was used for validation purposes.

3 Results and Discussion

3.1 Theoretical analysis of sheardependence of the flow

The molecular size and molecular size distribu-tion as well as the self-assembling and jammingproperties of melanoidins present in long-agedtraditional balsamic vinegars were discussedin previous works (Falcone & Giudici, 2008;Falcone et al., 2012). To get a fundamentalinsight about the effect of jamming propertieson the overall flow behaviour for the vinegarsamples, flow curves were analyzed using amodified Krieger-Dougherty equation (Krieger& Dougherty, 1959) for relative viscosity. Sucha model provided valuable guidelines for under-standing the role of the colloidal structure inflow behaviour as a function of the concentrationof the attractive colloidal melanoidins dispersedinto the vinegar bulk. The functions (2) and(3) were fitted to the experimental data. Thegoodness-of-fit for eq. 2 and eq. 3 (E% < 9.75%)indicated that TBVRE behaved as a colloidaldispersion of attractive melanoidins for whichthe onset for the structure scaling signing thetransition from Newtonian to non-Newtonianflow regime was close to the relative density of1.32 gmL−1 (Figure 1).As indicated by the apparent discontinuityof the shear stress profiles, TBVRE showedintermittent flow at low shear rates (mainlyunder 60) followed by continuous flow at highershear rates. Figure 2a and 2b show the two flowregimes for the vinegar samples “R376” and

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100 Falcone et al.

“F227” as examples for quality categories R andF, respectively. According to a scheme generallyrecognized for other soft jammed systems suchas colloidal, micellar and polymeric suspensionsthat show typical intermittent flow behaviour(Coussot & Ovarlez, 2010; Holmes, Callaghan,Vlassopoulos, & Roovers, 2004; Schall &van Hecke, 2010; Princen & Kiss, 1989), weattempted to interpret the flow instability in thevinegars from a physical perspective. With thisaim, we attributed the observed intermittentflow to the progressive evolution of the viscoelas-tic structure of colloidal melanoidins undermechanical shearing. Recent studies showedthat long-aged traditional balsamic vinegarswith high Brix values (over 75°Bx) show yieldstress and viscoelastic behaviour under sweepexperiments from 10 to 200Hz (Falcone et al.,2012). With this in mind, two structuring,competing phenomena were hypothesized, oneon them becoming dominant depending on theflow conditions: (i) reversible restructurationat long-range scales of the locally-discontinuousnetwork of colloidal melanoidins due to theinter-chain entanglements (elastic contributionto colloidal jamming), that may oppose thestarting flow (yield stress) and/or the flow atlower shear rates (intermittent flow behaviour)and (ii) irreversible restructuration at short-range scales of viscous local bonds through localreptation of the chain backbone of polymericmelanoidins(viscous contribution to sub-colloidaljamming), that may result in homogeneous flowregime with shear-thinning or shear-thickeningbehaviour depending on the effective hydro-dynamic interactions. Discontinuous colloidalnetworks deform under shear until they breakrapidly when the elastic stress reaches maximumcritical values. As elastic bonds are broken andreformed reversibly, stress changes abruptly.As there is no more elastic interaction amongdispersed colloids, the stress needed to maintainflow is only the simple viscous one and changesmay occur due only to the shear-thinning orshear-thickening phenomena.

ηlowηm

=

[1− d

dmax

]−ηin×dmax

(2)

ηhighηm

=

[1− d

dmax

]−ηin×dmax

(3)

Where ηlow and ηhigh are the apparent viscos-ity measured at 60 s−1 (where the intermittentflow starts to disappear) and at 600 s−1 (whereNewtonian flow starts to be recovered); ηm isthe vinegar bulk viscosity which was calculatedusing the 2th-order equation provided by Fal-cone et al. (2007) for aqueous solutions of glu-cose, fructose and acetic acid (the main vinegarconstituents simulating the TBV composition);d is the relative density used here to representthe overall concentration of structure-formingconstituents including isolated/discontinuous ag-gregates of colloidal melanoidins; dmax repre-sents the maximum packing fraction of structure-forming constituents due to the formation of acontinuous network structure among attractivecolloidal melanoidins; ηin is the intrinsic viscos-ity, a measure of the extent of jamming at acolloidal scale (dmax and ηin were treated as afitting parameter). When the vinegar viscosityis equal to that of its bulk medium, then rela-tive viscosity (ηlow/ηm or ηhigh/ηm) is equal to1; an increase of relative viscosity must be at-tributed to an increase of the colloids concentra-tion and/or to the strength of their interactions.

3.2 Perceptual probing ofjamming properties

The visual perception of the characteristic flowbehaviour under gravity is considered historicallya key point to meet quality requirements in termsof vinegar thickness as imposed by the officialregulations for TBVRE. The term adopted to in-dicate the optimal thickness is “syrup flowiness”or “flow syrupiness”, both resembling the flowof concentrated syrups. Trained judges evalu-ated the vinegar thickness by inspecting visu-ally the pouring speed from a glass bottle andthe ability to leave a film transparent to thelight of a candle. It is worth noting that sucha visual method cannot discriminate small dif-ferences in kinematic viscosity, i.e. the resis-tance to flow per unit of specific weight. Smalldifferences in pouring speed and time of obser-vation strongly affect visual perception of vine-

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New Quality Markers for Traditional Balsamic Vinegar 101

Figure 1: Shear-limited viscosity data fitted with the modified Krieger-Daugherty model. TBVREbehaved as a colloidal dispersion of melanoidins with the onset for solute concentration signing transitionfrom Newtonian to non-Newtonian flow regime

(A) (B)

Figure 2: Shear-induced transition from intermittent to homogeneous flow regime: (a) the vinegar R376belonged to the quality category R, i.e. “aged vinegars of acceptable sensory quality”; (b) the vinegarF227 belonged to the quality category F, i.e. “aged vinegars of very-high sensory quality”

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102 Falcone et al.

gar thickness. Moreover, kinematic viscosity mayvary with the flow rate for vinegars showing jam-ming properties and non-Newtonian behaviour,dynamically affecting the strength of the film andtransparency to light. Differences in concentra-tion of visible light-absorbing molecules in vine-gar bulk may also affect transparency at the samevinegar thickness or kinematic viscosity.With this in mind, it was reasonably hypothe-sized that colloidal and jamming properties to-gether with the non-Newtonian behaviour mightaffect in a synergistic or masking way not onlyvinegar thickness under gravity as evaluated byvisual inspection but also stress stimuli and theway they are perceived during vinegar sensing sodetermining the final quality score. As a con-sequence, in this work we decided to examinethe shear stress developed over a wide range ofcontrolled shear rates, i.e. 1-1000 s−1 againstthe overall perceptual score used to assign vine-gars along with two different commercial cate-gories. The shear rate ranging from 50 s−1 to200 s−1 includes those experienced by a New-tonian liquid pouring from a bottle (Gebhard,2000). However the vinegars under investigationshowed Newtonian behaviour only after 600 s−1

thus the kinematic viscosity was evaluated at thistargeted shear rate with the purpose of simulat-ing mechanical stimuli probed by visual inspec-tion of the Newtonian flow under gravity. Theshear rates ranging between 1 s−1 and 60 s−1 arelong-term, even though they are the most fre-quent shear rate condition experienced by manyfluid foods in the mouth during tasting (Wood,1968; Shama, Parkinson, & Sherman, 1973). Fal-cone et al. (2012) showed that the size of thecolloids of vinegar melanoidins spreads in a widerange (from sub-colloidal to macroscopic) withthe most frequent around 50 - 100 microns. Ithappens that this size is similar to the size thathumans can sense with the tongue, and thus theyare expected to affect the stress stimuli duringvinegar tasting.As far as the shear forces experienced in thisstudy are concerned, they varied between about90mN and 500mN within the range of shear ratesfrom 10 s−1 to 60 s−1 (Table 1). Such a rangeof shear forces includes force stimuli the humantongue can probe by mechanoreceptive afferents.Trulsson and Essick (1997) found that the lin-

gual nerve contains 33 single mechanoreceptiveafferents particularly innervating the tip of thetongue. Of these afferents, 22 were located atsurface of the tongue and respond to extremelylow mechanical forces, with force threshold rangebetween 300mN and 2mN. The remaining 11 af-ferent units are located in the tongue musclemass and responded to high force threshold, i.e.> 4 mN. The superficial units were classified asrapidly adapting afferents to the stress stimuli:they respond both during the application and re-moval of, but not during maintenance of, stressstimuli on the receptive field. Among the deepafferent units, two type of slowly adapting re-sponses were observed: one type was character-ized by a pronounced sensitivity to force changesduring the application and removal of the stressstimuli and an irregular static discharge duringmaintenance of the stimulus on the receptivefield. In contrast, the other afferent units exhibita weak sensitivity to force change, a highly reg-ular static discharge, and spontaneous activity.Finally, these authors concluded that the super-ficial units encode vigorously when the tongue ismoved to bring the receptive field into physicalcontact with other intraoral structures.

3.3 Flow behaviour vs perceptionof colloidal jamming

With the purpose of simulating key force stim-uli experienced by tongue during vinegar tasting,the following two rheological descriptors were ob-tained from flow curves. The ratio R(1,2) wascalculated by dividing the shear forces measuredat 10 s−1 and 60 s−1, so that levels with a differ-ence greater than 1 indicated changes in densityheterogeneities at colloidal scale as induced bylow-shear rates (yield stress or intermittent flowregime). Thus R(1,2) was associated to the in-mouth mechanical stimuli encoding for probing ofthe extent of jamming at colloidal scale. Further-more, the ratio R(2,3) was calculated by dividingthe shear forces measured at 60 s−1 and 600 s−1

so that levels greater than 1 indicated decreasingin density heterogeneities at sub-colloidal scaleas induced by medium-high shear rates (homoge-neous flow with shear-thinning effects). Levels ofR(2,3) lower than 1 indicated increasing of local

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New Quality Markers for Traditional Balsamic Vinegar 103

Table 1: Distribution of shear stress values measured at 10 s−1, 60 s−1 and 600 s−1

Mean(*) Std.Dev.

Stress [mN] at 10s−1 5,65 [0.95 – 10.35]a 4,7Stress [mN] at 60s−1 28,90 [2.82 – 54.98]a 26,08Stress [mN] at 600s−1 282,47 [34.44 – 530.5]b 248,03

(*)Different letters indicate statistically significance difference between confidence limits

density heterogeneities as induced by medium-high shear rates (homogeneous flow with shear-thickening effects). Thus R(2,3) was associatedto the in-mouth mechanical stimuli encoding forprobing of the extent of jamming at sub-colloidalscale. A clear picture of vinegar distribution(Figure 3a and 3b) was obtained as a functionof perceptual classification of sensory properties,accounting for kinematic viscosity measured at600 s−1 (V600/Density) and the associated jam-ming descriptors R(1,2) and R(2,3). As can beinferred from data, the scale length of jammingclearly affected both the Newtonian flow undergravity and perceptual classification of the sen-sory properties. The closer the colloidal jam-ming extent, i.e. the value of R(1,2) was to 1,the greater the kinematic viscosity. The greaterthe extent of jamming at sub-colloidal scale, i.e.the value of R(2,3) was far from 1, the lowerthe kinematic viscosity. The box plots in Figure3c show that more than 90% of the vinegars as-signed to the quality category F were character-ized by lowest levels of yield stress and more ho-mogeneous flow, i.e. R(1,2) was on average veryclose to 1, so that it must be concluded that col-loidal jamming negatively affected the decision ofthe judges prevailing on the overall olfactive andgustative properties. Judges assigned the bestscores to the vinegars with higher shear-thinningtraits at the sub-colloidal scale rather than shear-thickening ones (Figure 3d).

Supervised Analysis of Data

A descriptive analysis of the results from per-ceptual assessment of the sensory properties wasinvestigated accounting for both the compositionand rheological properties following a supervisedapproach, i.e. assuming the prior knowledgeabout which vinegar samples belonged to one of

the two quality categories, F and R. Since stan-dard descriptive statistics from Shapiro-Wilks’W and Lilliefors tests highlighted asymmetricdistribution for the most of the vinegar proper-ties (data not shown), the Kolmogorov-Smirnovtwo-sample test, which is based on cumulativedistribution, was preferred to summarize differ-ences among the vinegars. The most significantdifferences between F and R quality categorieswere calculated at p < 0.05 for the dynamic vis-cosities measured at 10 s−1, 60 s−1, 600 s−1,V600/Density as well as for Brix degree, titrat-able acidity, and volatile acidity (Table 2). Vine-gar samples belonging to the quality category Fwere characterized on average by viscosity levelsmore than double those of vinegars assigned tothe category R. No significant differences wereobserved for sugars, density and fixed acidity.Composition and rheological properties were alsoused as independent variables, while quality cate-gory (F and F) as grouping variable for the prin-cipal component analysis (PCA). Results fromPCA are summarized using the plot of scoresand variables (Figure 4). A scree plot was usedto graphically determine the optimal number offactors to retain. The original variables clusteredin two new meaningful, independent variablesthat could be described respectively as “Homoge-neous vs Heterogeneous Flow” according to thefactor loading on Factor 1 and as “Overall so-lute concentration to volatile compounds Bal-ances” according to the factor loading on Fac-tor 2. Factor 1 accounted for the 61.73% of theexperimental variance, with the dynamic viscosi-ties and kinematic viscosity oppositely related tocolloidal jamming property. Factor 2 accountedfor about 23.05% of the experimental variance,with the ratio between Brix degree and titrat-able acidity oppositely related to the ratio be-tween the volatile acidity and titratable acidity.

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104 Falcone et al.

(A) (B)

(C) (D)

Figure 3: Distribution of TBVRE samples as function of kinematic viscosity measured at 600 s−1 againstthe extent of colloidal (a) and sub-colloidal jamming (b). Membership of the vinegars to the two qualitycategories F, i.e. “aged vinegars of very-high sensory quality” and R, i.e. “aged vinegars of acceptablesensory quality” was affected by the colloidal (c) and sub-colloidal jamming (d). The rheological markerR(1,2) was associated with the mechanical stimuli of the in-mouth perception of colloidal jamming, whileR(2,3) to the mechanical stimuli of the in-mouth perception of sub-colloidal jamming

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(A)

(B)

Figure 4: Results from supervised Principal Component Analysis showing distribution of the vinegarswith respect to their rheological and composition properties (a). (b) the visual perception of the flowregime under gravity as perceived according to the official sensory method for vinegars belonging to thequality category “R” (intermittent flow) or to the quality category “F” (homogeneous flow)

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Table 2: Results from Kolmogorov-Smirnov two-sample test used to assess the differences between thetwo quality categories of vinegars R, i.e. the “aged vinegars of acceptable sensory quality” and F i.e. the“aged vinegars of very-high sensory quality” in terms of composition and rheological properties. Markedtests are significant at p < 0.005

VAR Max Negative Max Positive p-value Mean Mean Std. Dev. Std. Dev.Difference Difference F R F R

Sugars -0.105 0.268 P > 0.100 43.302 41.961 2.037 3.351Brix 0.000 0.391 P < 0.050 71.817 67.945 3.076 4.961Density 0.000 0.341 P < 0.100 1.359 1.339 0.021 0.030AcTit -0.471 0.155 P < 0.005 5.027 6.116 0.473 1.772AcFix 0.000 0.335 P < 0.100 1.505 1.280 0.295 0.323AcVol -0.506 0.052 P < 0.005 3.522 4.836 0.612 1.822V10 0.000 0.536 P < 0,001 1010.000 426.579 623.411 303.806V60 0.000 0.536 P < 0.001 883.648 356.979 559.863 296.951V600 0.000 0.584 P < 0.001 848.493 353.573 522.643 290.431R(1,2) -0.423 0.068 P < 0.025 1.187 1.327 0.165 0.296R(2,3) -0.155 0.331 P < 0.100 1.032 1.011 0.063 0.125R(1,3) -0.341 0.094 P < 0.100 1.225 1.341 0.184 0.359ViscBlukPredicted -0.105 0.268 P < 0.100 0.002 0.002 0.000 0.000Brix/AcTit -0.068 0.506 P < 0.005 14.430 12.034 1.731 3.533V600/Density 0.000 0.584 P < 0.001 620.888 260.888 378.291 210.395

As can be inferred from PCA results, flow prop-erties dominated over the composition ones un-derpinning the perceptual classification of sen-sory properties by judges towards vinegars show-ing lower but more homogeneous flowiness witha very narrow distribution centered on the meanlevel for the compositional balance (where theFactor 2 is equal to 0), i.e. with respect for boththe overall solute concentration (including sugarsand titratable acidity) and volatile acidity (in-cluding acetic acid). Such a compositional bal-ance was thought as an optimum for such agedvinegars. It is worth noting that the official tast-ing procedure for TBVRE imposes different co-efficients for weight contribution from visual, ol-factive, and gustative perceptions, reserving thelower one (i.e. 15%) for the visual perception ofthe vinegar flowiness and light transparency. Asa consequence, it was concluded that the extentof jamming at the colloidal scale plays a strongmasking effect on the perceptual intensity of botholfactory and gustatory sensing.

Unsupervised Analysis of Data

An important key point is the fact that the sen-sory score assigned by the panellists were theresult of a top-down decision process consistingof a series of judgments related to their per-ception of more than one sensory attribute ata time. The official tasting procedure, in fact,imposes a series of ordered, stepwise evaluationtests for coded visual, olfactory and taste at-tributes. Without any a priori hypotheses abouthow many independent quality categories as wellas about which vinegar sample may belong toeach of them, tree classification analysis (TCA)was carried out based on classification, splittingand validation rules examining the effects of thepredictor variables one at a time, rather thanjust all at once. The top-down induction processstarted by dividing the initial set of vinegars intosubsets in a hierarchical manner, using a split-ting value test for one composition or one rheo-logical property at time as target variable. Suchrecursive partitioning was completed when split-ting no longer added value to the predictions,i.e. when no further vinegar was assigned to thesame cluster of the tree. The classification rule

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Table 3: Tree structure from unsupervised classification tree analysis for composition and rheologicalrelated properties as predictor variables one at once, encoding for the top-down decision process followedfor vinegar classification according to the official sensory procedure

NODE Left Right Size of N in N in Selected Split SplitBranch Branch Node class F class R Category Variable Constant

1 2 3 75 18 57 R V600/Density 426.52 4 5 54 5 49 R R(1,2) 1,14 6 7 42 2 40 R Brix/AcTit 12.56 24 0 24 R7 8 9 18 2 16 R AcVol/AcTit 0.88 10 11 17 1 16 R V600/Density 349.610 13 0 13 R11 12 13 4 1 3 R V600/Density 376.212 1 1 0 F13 3 0 3 R9 1 1 0 F5 14 15 12 3 9 R V600/Density 152.714 9 0 9 F15 3 3 0 F3 16 17 21 13 8 F AcVol/AcTit 0.716 18 19 12 11 1 F Brix/AcTit 18.118 11 11 0 F19 1 0 1 R17 20 23 3 2 1 F R(1,2) 1.120 6 0 6 R21 22 23 3 2 1 F Brix/AcTit 14.322 2 2 0 F23 1 0 1 R

Table 4: Misclassification matrix from unsupervised classification tree analysis accounting for composi-tion and composition related properties as predictor variables one at once, encoding for the top-downdecision process followed for vinegar classification according to the official sensory procedure

OBSERVED PREDICTED F PREDICTED R Row Total

Number F 18 18Column Percentage 100.00% 0.00%Row Percentage 100.00% 0.00%Total percentage 23.68% 0.00% 23.68%Number R 58 58Column percentage 0.00% 100.00%Row Percentage 0.00% 100.00%Total percentage 0.00% 76.32% 76.32%Count All Group 18 58 76TOTAL PERCENT 2 2

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Figure 5: Tree graph showing results from unsupervised classification tree analysis accounting for rheolog-ical and composition properties as predictor variables one at a time, encoding for the top-down decisionprocess followed for vinegar classification according to the official sensory procedure. The number ofterminal nodes was 12

was to assign membership of vinegars to the For R category with the same accuracy, regardlessof the frequency really assigned by the judgesfor the same categories. Corroborating resultsfrom PCA, results from TCA suggest a patternof recognition for vinegar quality relying mostlyon V600/Density and R(1,2) but with a minorcontribution, it relies on the balance betweenthe overall solute concentration and volatile com-pounds. Figure 5 shows the tree graph from un-supervised tree analysis accounting for structureand composition properties as predictor variablesone at a time, obtained without misclassificationcosts. Tree structure data are shown in Table3, while misclassification costs are given in Ta-ble 4. Data reported in Figure 6 together withthose from the misclassification matrix (Table 4)

are evidence of the goodness-of-fit of the clas-sification tree. As can be inferred from Table3, V600/Density was the best parameter to splitlocally the starting set of vinegar samples (426.5Pa.s was the split value test). The first majorsub-group consisted of 54 vinegars, the 90% ofwhich were vinegars belonging to the R category,and could be divided into two subsets, where theR(2,3) was the locally optimal decision predic-tor and 1.10 the split value test. The secondmajor sub-group, consisting of 21 vinegars, 60%of which vinegars belonging to the F category,could be divided in two subsets, based on the ra-tio between volatile acidity and titratable acidity(0.73 split value test). This could be continuedthroughout the entire tree decision process untilthe terminal nodes were reached where one could

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Figure 6: Importance plot from unsupervised classification tree analysis accounting for structure- andcomposition properties as predictor variables one at a time, encoding for the top-down decision processfollowed for vinegar classification according to the official sensory procedure

observe the final membership predictions of thevinegars within one of the two quality categories.As can be inferred from data, the relative impor-tance of prediction variables that could be asso-ciated to the judges assignation followed a de-creasing order for the descriptor of sub-colloidaljamming, i.e. R(2,3), the ratio between Brix de-gree and total acidity, and the kinematic viscos-ity. Such results suggested that the final scoreassigned by the panellists may have been the re-sult of “reverse type” top-down decision process,where they provided a series of judgments aimingunconsciously to classify vinegars with respect totheir perception of jamming properties and thenwith respect for their composition-related per-ception.

4 Conclusions

It is our strong belief that before the assignmentof the Traditional Balsamic Vinegar designation,the official regulations must require compliancewith the dynamic viscosity as a new characteris-tic marker of the quality of the vinegar togetherwith the corresponding instrumental method tobe followed for its measurement under controlledshearing conditions.In this work, two different flow regimes wereclearly detected among the vinegars: (i) an inter-mittent or heterogeneous flow at the lowest shearrates; (ii) a homogeneous and continuous flowregime at medium-high shear rates showing someshear thickening and/or thinning traits. Physicaland structural insights of colloidal jamming onflow behaviour were gained, while the physicalorigin of the flow intermittency was attributedto a change in nature of the interactions between

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vinegar melanoidins at a colloidal scale due tothe mechanical shear. Over a critical shear rate,the apparent shear stress induced phase transi-tion from the intermittent to homogeneous flowregime. Our study provided evidence that theextent of jamming at sub-colloidal scale plays astrong masking effect on the overall olfactory andgustatory perceptions. Jamming properties atsub-colloidal scale affected the perceptual clas-sification of sensory properties towards vinegarsshowing lower but more homogeneous flow, witha very narrow distribution against the optimumof balance between the total solute concentra-tion (including sugars and acidity) and volatilecompounds. A classification tree model able todescribe the top-down decision process for mem-bership assignment according to the official tast-ing procedure was developed and validated ac-counting for composition and rheological proper-ties separately, rather than just all at once. Re-sults suggested that the perceptual assessmentof the sensorial properties of the vinegar, as per-formed by the trained judges according to theofficial sensory procedure, relies mostly on col-loidal jamming and kinematic viscosity measuredat 600 s−1 and less so on the balance betweentotal solids and volatile acidity as well as on thebalance between volatile acidity and total acid-ity.

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