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Food Sci Nutr. 2018;6:27–35. | 27 www.foodscience-nutrition.com Received:17March2017 | Revised:17May2017 | Accepted:22May2017 DOI: 10.1002/fsn3.494 ORIGINAL RESEARCH Internal preference mapping of milk–fruit beverages: Influence of color and appearance on its acceptability Rocío Fernández-Vázquez1 | Carla M. Stinco1 | Dolores Hernanz Vila2 | Francisco J. Heredia1 | Carolina Chaya3 | Isabel M. Vicario1 ThisisanopenaccessarticleunderthetermsoftheCreativeCommonsAttributionLicense,whichpermitsuse,distributionandreproductioninanymedium, providedtheoriginalworkisproperlycited. ©2017TheAuthors.Food Science & NutritionpublishedbyWileyPeriodicals,Inc. 1FoodColour&Quality Laboratory,DepartmentofNutrition&Food Science,FacultaddeFarmaciaUniversidadde Sevilla,Sevilla,Spain 2DepartmentofAnalyticalChemistry,Facultad deFarmacia,Sevilla,Spain 3DepartmentofAgricultural Economics,StatisticsandBusiness Management,UniversidadPolitécnicade Madrid,Spain Correspondence IsabelM.Vicario,FoodColour&Quality Laboratory,DepartmentofNutrition&Food Science,FacultaddeFarmaciaUniversidadde Sevilla,Spain. Email:[email protected] Funding information Thisworkwassupportedbyfundingfromthe ConsejeríadeInnovaciónCienciayEmpresa, JuntadeAndalucíabytheprojectP11- AGR-7783. Abstract Theindividualpreferencesof100consumersbetween20and30yearsoldforthe colorof16milk–fruitjuicebeverages(MFJB)wereinvestigatedbypreferencemappingtechnique.Consumerswereaskedtoevaluate,justbylookingatthesamples, howmuchtheylikedthem(from“Extremelydislike”to“Extremelylike”).Thecolorof thesampleswasanalyzedbytwodifferentinstrumentaltechniques.Resultsobtained fromtheinstrumentalcolormeasurementshowedthewidediversityinhuesofthe beveragesavailableinthemarket,andcorrelationsbetweentechniquesprovedthat bothofthemwereappropriatetoanalyzecolor. Resultsshowedthatparticipantspreferredsampleswithorangishappearanceinstead ofthosewithawhiterlook.Anyway,punctuationsgivenbytheconsumerssuggest thatgenerally,coloroftheseproductsisnothighlyevaluatedbyconsumers,asthe bestmeanpunctuationwas6.6. KEYWORDS acceptance,color,consumersstudy,milk–fruitbeverage 1 | INTRODUCTION Beveragesmadefrommilkandfruitjuice(MFJB)haveproliferatedin theEuropeanmarketduringthelastyearsinresponsetoagrowing demandfornaturalproductsthatareperceivedashealthierbyconsumers.Thesebeveragesareconsideredthemostwidelyconsumed functionalfoods(Pszczola,2005); however,therearelittledatarelatedtoquality,safety,oracceptabilityoftheseproducts(Sampedro, Geveke,Fan,Rodrigo,&Zhang,2009). Fromanutritionalpointofview,theydonotreplaceorarenot equivalenttoaglassofmilkoraportionoffruit.Thus,initscomposition,fruitcontentsrangefrom7%to41%andtheyusuallycomefrom differentconcentratedfruits;milkmeansupto30%,andtheycontain alsovitamins,fiber,andsugars. Instrumentalcolormeasurementsaresimple,accurate,versatile, andobjective.Tocharacterizecolor,therearedifferentinstruments, such as colorimeters, spectrophotometers, and spectroradiometers, andindependentlyoftheinstrumentused,itisveryimportanttodefine measurementsconditionscorrectly.CIE(InternationalCommissionon Illumination) recommends observers (CIE, 1991a), illuminants (CIE, 1991b),andcolorspaces(CIE,1978),inordertonormalizeobjective colormeasurement.Itmustbealsotakenintoaccountsampleposition,systemgeometry,lightsourceintensity,sampledeepness,blank measurement, background, and surrounding (Meléndez-Martínez, Vicario,&Heredia,2006;Stincoetal.,2012).Digitalimageanalysis (DIA)isbeingusedincreasinglyforinstrumentalfoodcolorspecificationalthoughmoretraditionaltechniqueslikespectroradiometry(SPE) willalsoprovideanappropriatecharacterizationofcolorinbeverages (Fernández-Vázquez,Stinco,Hernanz,Heredia,&Vicario,2013,2014; Stinco,Fernámdez-Vázquez,Heredia,Meléndez-Martínez,&Vicario, 2014). Furthermore,colorisoneofthemostimportantattributesrelated toquality,affectingchoiceofpurchase(Baker&Günter,2004;Calvo, Salvador, & Fiszman, 2001). For the consumers, color is, alongside
28 | FERNÁNDEZVÁZQUEZ Et al. TABLE1 Compositionofthecommercialbeveragesanalyzed Samples Main ingredients Colorant Fiber Vitamins Jelling agents Sugar added Other S1aSkimmedmilk,concentrateorange 5% B-Carotene 1%inulin – – 7.6%sugar Corndextrose,ascorbicacid,citricacid, aromas,milkproteins,guargum,lactobacillus acidophilus,bifidobacterium,plantsterols, andsterolsesters S2 Water,juicefromconcentrate: pineapple,carob,appleandgrape, orangeandlemon(12%),skimmed milk(4.5%) B-Carotene – – Pectin Sugar,sucralose,acesulfame-K Milkprotein,citricacid,aromas,ascorbicacid S3aPartiallyskimmedmilk,orangejuice fromconcentrate(5%) B-Carotene 1%inulin – – 7.6%sugar Corndextrose,sodiumcitrates,ascorbicacid, guargum,milkproteins,lactobacillus acidophilus,milkenzymes,bifidobacterium S4aSkimmedmilk,6%concentrate (orange,pineapple,mango) B-Carotene GumArabic – – Sugar Bifidobacterium,milkenzymes,aromas S5 Water,fruitjuice:orange,apple, pineappleandlemon(15%), skimmedmilk(10%) – – – Pectin Sugarandsucralose Citricacid,ascorbicacid,aromas S6 Water,fruitjuice:pineapple,orange, appleandlemon(15%),skimmed milk(10%) – – – Pectin Sugar,acesulfame-K,neohesperidinDC Citricacid,ascorbicacid,aromas S7 Water,fruitjuice:orange(25%), apple(18%),pineapple(5%),lemon (1%),skimmedmilk(10%) –Fiber A,C,E Pectin Glucoseandfructose(syrup), sugar Citricacid,aromas S8 Water,fruit,andvegetablejuice: orange,grape,pineapple,carrot, peach,andpassionfruit(25%), skimmedmilk8% B-Carotene – – Pectin Sucralose,acesulfame-K Citricacid,ascorbicacid,aromas S9 Water,fruit,andvegetable concentratejuice:orange(8%), carrot(5%),lemon(2%),pineapple (2%),passionfruit(2%),skimmed milk(10%),pureepeach(4%) B-Carotene Dietaryfibers C,E Pectin,xanthan gum Fructose(syrup),sucralose Citricacid,aromas S10 Water,skimmedmilk(10%), Concentrate:pineapple,mango(7%) B-Carotene –A,C,E Pectin Sugar,sucralose Citricacid,aromas S11 Water,fruit,andvegetablejuices: orange,carrot,peach(15%), skimmedmilk(10%) B-Carotene – – Pectin Saccharose Citricacid,ascorbicacid,aromas S12 Water,concentratefruitjuice: orange,pureepeach,carrot(18%), skimmedmilk(10%) B-Carotene –A,C,E Pectin Sucralose Citricacid,aromas (Continues)
| 29 FERNÁNDEZVÁZQUEZ Et al. freshness,oneofthemaincriteriaforfoodselection,andakeyfactorin sensoryacceptance(Fernández-Vázquez,Stinco,Melendez-Martinez, Heredia,&Vicario, 2011; Quitao-Teixeira,Aguiló-Aguayo, Ramos,& Martín-Belloso, 2008).Traditionally, this kind of products has been oftenconsumedintheirsingle-usepackages,meaningthatconsumers couldnotperceivethecolor,whichmightbethereasonwhyindustries havenotputtoomuchattentiontothischaracteristicofthebeverages. However,currently,duetotheincreasingintheconsumption,manyof thecompaniesarechangingthepackagesofthebeveragestosome withmorevolume,whichmeansconsumerswilldrinktheminglasses, andtherefore,theywillperceiveandevaluatetheircolor. Despitetherelevanceofmilk–fruitbeveragesMFJBinthemarket, uptonowthereisalackofinformationaboutthecolorpreferences fortheseproductsandits consumeracceptance.Thus,the aimsof thisstudywere(1)tocharacterizethecolorofMFJBbeveragesusing differenttechniques,(2)tostudytheconsumers’acceptanceoftheir color,and(3)to identifyand characterizedifferent consumerssegmentsintermsofcoloracceptancebymeansofinternalpreference mapping. 2 | MATERIALS AND METHODS 2.1 | Samples SixteencommerciallyavailableMFJB formulatedwithmilk or dairy products and fruit juice were purchased in different supermarkets inSpain,andtheircompositionsareshowninTable1.Threeofthe samplesaresoldatrefrigerationtemperature(4±2°C)astheywere pasteurized,whiletheother13samplesaresoldatroomtemperature (20±2°C)sincetheyweresubmittedtoaUHTprocess. 2.2 | Color measurements 2.2.1 | Spectrophotometry (SPE) The color of the beverages was measured in a spectrophotometer CM5(KonicaMinoltaSensingAmericas,Inc.,NY).Eachsamplewas containedin75-mlcapacitytransparentplasticbottles.ThecolorparametersoftheuniformcolorspaceCIELABL*; a*; and b*wereobtaineddirectlyfromtheapparatus.Colordataobtainedwereaverages of three measurements. 2.2.2 | Digital image analysis (DIA) TheDigiEyeimagingsystemwasusedtocapturethedigitalimages (Luo,CUI,&LI,2001).Thelattersystemincludesacalibrateddigital camerawith10.2-megapixelNikonD80(NikonCorporation,Tokyo, Japan)andanobjectiveNikkor35-mmf/2D(NikonCorporation),a colorsensorfordisplaycalibration,andanilluminationboxdesigned byVeriVideLtd.(Leicester,UK). Thesampleswereplacedin75-mlcapacitytransparentplasticbottles,illuminatedbyadiffuseD65simulator,andmeasuredagainsta graysurround(L*=50)andwhitebackground. Samples Main ingredients Colorant Fiber Vitamins Jelling agents Sugar added Other S13 Water,fruit,andvegetablejuice: orange,carrot,pineapple,passion fruit,mango,guava,papaya,and apricot(25%),skimmedmilk(10%) –Fiber A,C,E Pectin Sugar Water,citricacid,aromas S14 Water,juicefromconcentrate: orange,pineapple,apple,papaya, carrot,mango,guava(20%), skimmedmilk(10%) B-Carotene –C,E Pectin Sugar,glucose,andfructose (syrup),sucralose Citricacid S15 Water,juicefromconcentrate: orange,apple,andmango, skimmedmilk(10%) B-Carotene –A,C,E Pectin Sucralose,acesulfame-K Citricacid,aromas S16 Water,juicefromconcentrate:8% orange,1%mango,1%pineapple, skimmedmilk(10%) B-Carotene – E Pectin Sugar Citricacid,sodiumcitrates aSamplesstoredunderrefrigeration. TABLE1 (Continued)
30 | FERNÁNDEZVÁZQUEZ Et al. TocalculatetheCIELABcoordinatesfromRGBcolorspace,the DigiFood software was used (Heredia, González-Miret, Álvarez, & Ramírez,2006). FromtheCIELABuniformcolorspace,thepsychophysicalparameterschroma(C*ab)andhue(hab)aredefinedasfollows: Chroma( C∗ab )isusedtodeterminethedegreeofdifferenceofa hueincomparisonwithagraycolorwiththesamelightnessandis consideredthequantitativeattributeofcolorfulness.Hue(hab)isthe attribute according to which colors are usually defined as reddish, greenish,etc.andisusedtodefinethedifferenceofacolorwithreferencetoagraycolorwiththesamelightness.Thisattributeisrelatedto thedifferencesinreflectanceatdifferentwavelengthsandisconsideredthequalitativeattributeofcolor. 2.3 | Consumer study OnehundredSpanishconsumerswererecruitedfromstaffandstudents at the University of Sevilla. Information regarding demographics and consumptionhabitswascollectedviaaquestionnairepriortothesensoryassessmentofthesamples.Alltheconsumerswere20–30yearsold (30%malesand70%females),whichisespeciallyinterestingasitisthe groupofpopulationwhicharepotentialconsumersoftheseproducts. Thetestwascarriedoutindesignedindividualsensorybooths, underNorthernHemispherelightingconditions.Samples(75ml)were presentedmonadicallyinthesamebottlesusedfortheothermeasurements,labeledwiththreedigitsrandomcodes,inarandomizedorder. Consumers were asked to evaluate how much they liked the appearance of the beverages (from “Dislike extremely” to “Like extremely”)usingthe9-pointhedonicscale,justbylookingatthesamples.Theratingdecisionwasbasedonlyontheappearance,without further information. 2.4 | Data analysis Thestatisticalanalysisofinstrumentalcolordatawasperformedby one-way analysis of variance (ANOVA), and statistically significant differences(p < 0.05)weredeterminedusingtheTukeymultiplecomparisontest.Correlationanalysiswasdonebetweenthecolorimetric parametersmeasuredbybothinstrumentaltechniquesandbetween instrumentalanalysisandconsumerstudyresults. Consumer data first underwent normality testing (Shapiro–Wilk test) and were subsequently analyzed using nonparametric tests (Kruskal–Wallis)toidentifydifferencesamongsamples.Then,these datawere further examined using hierarchal cluster analysis, using SquaredEuclideanDistancesandWardscriterion,andinternalpreferencemapping. Independence between demographic variables and consumer clusterswereanalyzedbyχ2 test. AllstatisticalanalyseswereperformedusingtheprogramStatistica 8 for Windows (StatSoft, 2007) and XLStat (Version 2009.6.03, Addinsoft,USA). C ∗ ab = √ (a∗)2+(b∗)2,hab =arctan(b∗∕a∗ ) TABLE2 Colorcoordinatesofthebeveragesmeasuredbythedifferenttechniques:spectroradiometer(SPE)andbydigitalimageanalysis (DIA) Sample Spectrophotometry Digital image analysis L*C*hab L*C*ab hab S1* 85.75±0.02a21.53±0.02a75.01±0.03a90.91±0.12a22.05±0.20a77.90±0.40a S2 54.67±0.09b9.73±0.04b99.56±0.08b73.31±0.13b21.97±0.20a87.91±0.18b S3* 81.19±0.01c27.60±0.03c74.44±0.03c86.67±0.07c27.69±0.11b75.38±0.09c S4* 83.06±0.02d28.64±0.08c80.34±0.03d89.57±0.09d30.55±0.12c81.80±0.22d S5 55.64±0.12e21.69±0.83a86.48±0.47e72.31±0.05e30.66±0.31c78.59±0.13ae S6 49.03±0.08f14.63±0.06d94.14±0.08f70.40±0.65f28.80±1.09b86.83±0.41f S7 60.08±0.07g25.90±0.09e88.67±0.14g68.79±0.11g33.10±0.14d84.10±0.06g S8 50.86±0.02h51.84±0.04f62.08±0.09h61.75±0.22h50.48±0.19e54.24±0.07h S9 51.73±0.18i43.50±0.10g68.40±0.03i67.53±0.02ik 51.40±0.07e62.47±0.12i S10 58.25±0.02j26.66±0.12ce 83.12±0.04j76.15±0.00j42.93±0.00f79.21±0.00e S11 53.45±0.14k37.40±0.15h64.31±0.05k66.95±0.00i45.86±0.00g59.75±0.00j S12 53.04±0.19l36.36±0.44h61.95±0.08h67.76±0.08kl 45.18±0.08g57.40±0.15k S13 48.69±0.06f43.91±0.12g61.79±0.06h62.01±0.05h51.54±0.08e52.59±0.15l S14 49.64±0.01m39.93±0.11i63.10±0.06l64.97±0.22m47.58±0.22h56.20±0.14m S15 57.28±0.04n53.97±0.09j81.28±0.05m65.71±0.4m57.87±0.14i81.69±0.12d S16 58.30±0.00j40.03±0.04i76.09±0.03n68.49±0.03gl 57.52±0.08i70.63±0.06n a–oDifferentsuperscriptswithincolumnsforeachparameterindicatestatisticallysignificantdifferences(p < 0.05). *Samplesstoredunderrefrigeration.
| 31 FERNÁNDEZVÁZQUEZ Et al. 3 | RESULTS AND DISCUSSION 3.1 | Instrumental color measurements Table2showsthecolorcoordinatesofthebeveragesmeasuredby thetwotechniques.Lightness(L*)valuesrangedfrom61.75to90.91 inDIAandfrom48.69to85.75inSPE,thussamplesseemedlighter whenSPEwasconsidered.Chroma(C*ab)valuesrangedfrom21.55 to57.52inDIAbutfrom9.73to53.97inSPE,showingagainlower values,andwiderrangewhenSPEisconsidered.Finally,hue(hab)valuesrangedfrom52.58to87.91inDIAandfrom61.79to99.56in SPE,whichmeansthat,whenDIAisconsidered,samplesseemedmore reddish. Zulueta, Esteve, and Frígola (2007) reported similar values, rangingfrom53.05to80.62;17.67to63.59;and35.47to115.57;forL*, C*ab and hab,respectively,indifferentcommercialMFJBanalyzedwith a Hunter Labscan II Colorimeter (Hunter Associates Laboratory, Inc., Reston,VA,USA). Thesewiderangesinthevaluesshowthebroadvarietyofcolorin thebeveragesavailableinthemarket.Thus,ANOVA(Table2)showed thatmostofthesamplesweresignificantlydifferentinallthecolorimetricparameters. Thefruit/milkcompositionofthebeveragesisrelatedtothecolor andthustothecolorimetricparametersandcouldexplaincolordifferencesamongsamples.Inthissense,samplesstoredunderrefrigeration(S1,S3,andS4),whichwerethesampleswiththehighestvalues oflightness,hadasmainingredientmilkanditsproportionoffruit wasminor(5%–6%ofconcentratedfruit).Thiscouldexplainthehigh valuesoflightnessinthosesamples. However, generally, beverages which contain mayor proportion of fruits with reddish-yellowish colorations, such as orange, peach, mango, or carrot, presented hue values minor of 70°, while fruits with yellowish-greenish colorations, such as apple,pineapple,orlemon,areassociatedwithvaluesofhueabove 90°. Regardingchrome,nosignificantrelationbetweenthecompositionandthecolorimetricparameterscouldbeargued. 3.1.1 | Relationship between instrumental techniques Figure1 shows the samples in the CIELAB space (Diagram a*b*) measuredbySPE(Figure1a)andDIA(Figure1b).Itcanbeobserved thatsamplesweresituatedinthesameareaoftheCIELabdiagram, independentlyofthetechniqueusedalthoughwithslightmodificationsinthepositions.Theseslightvariationsobservedinthecolor coordinatesvaluesmeasuredbydifferenttechniqueswerealsofound inapreviousstudy(Fernández-Vázquezetal.,2011),wherecolorof differentorangejuiceswasmeasuredbyDIAandSPE. Instrumentalmeasurementsareconsideredanaccurateandsuitablemethodforevaluatingcolorinfood,asithasalreadybeenreported for wine and orange juice (Fernández-Vázquez etal., 2011; Martínez,Melgosa,Pérez,Hita,&Negueruela,2001).However,there might be differences among the measurements, depending on the technique used. They may be related mainly to differences in the thicknessofthemeasuredsample,othersecondaryfactorssuchas illuminationconditions,orthegeometryofthesystem.Inthissense,it isinterestingtocheckifallthetechniquesaresignificantlycorrelated. Inthiscase,allthecorrelationcoefficientswerehigh(>0.85)and statisticallysignificant(α=0.05).Thus,itconfirmedtherelationship betweenbothtechniquesinthe measurementsofthe colorofthis kindofbeverages. 3.2 | Consumer study Results from the demographic and consumption questionnaire are showninTable3.Resultsindicatethat85%ofconsumersconsidered theseproducts as beneficial,and 70% consumedthem quite often (39%didsotwoormoretimesperweek).Participantswhodidnot usetoconsumethesebeveragesstatedthattheydidnotlikethem (63%),ortheypreferredotherbeverages,suchasnaturaljuices(20%). Figure2 shows mean values given by consumers to the beverageappearances.Itisworthytohighlightthatthepunctuations suggestedthatcoloroftheseproductswasnothighlyevaluated,as thebestmeanpunctuationwas6.6.Anyway,generally,participants FIGURE1 a*b*colordiagramfor juice–milkbeveragesmeasuredby spectrophotometer(a)anddigitalimage analysis(b) 10 20 30 40 50 60 0º 10º 20º 30º 40º 50º 60º 70º 80º 90º a* 0102030405060 0 a* 0102030405060 0 10 20 30 40 50 60 0º 10º 20º 30º 40º 50º 60º 70º 80º 90º (a) (b)
32 | FERNÁNDEZVÁZQUEZ Et al. significantlypreferredsampleswithorangishandmorevividappearanceinsteadofthosewithmorewhitishlook(Table4).Thiscould beduetothefactthatconsumersexpectedtofindcolorfulbeveragesastheyaresupposedtobemadewithfruits,andwhenthey observedbeverageswithwhitishcolor,theymayassociateitwith alowerfruitcontent.Thisapparentlylowerpreferencecouldalso beduetothelowmeanconsumptiononthegroup.However,the consumerssegmentwith highest rateofdislikers (Cluster1, 32% dislikers,seeTable3)arethebestdiscriminatorsbetweensamples intermsofcolorappearance,reachingthehighestmeanscoresin somesamples. Relationbetweenconsumeracceptanceandcolorparameterswas explored, andtheyshowedthathue andchromaweresignificantly (p<0.05)correlatedwithconsumeracceptance,withthehighestcorrelation coefficientfor consumeracceptance and huemeasuredby DIA(r=0.97). 3.2.1 | Cluster analysis Tofindoutifthereweregroupsofconsumersdifferingintheirpreferencesforcolor,asegmentationofthepanelgroupwasdoneby Cluster analysis (Vigneau, Qannari, Punter, & Knoops, 2007). The Frequency response (%) p- Value (χ2)a Cluster 1, n = 19 Cluster 2, n = 29 Cluster 3, n = 52 Gender 0.107 Male 11 38 33 Female 89 62 67 Consumption 0.202 Yes 63 83 67 Frequency 0.300 <Onceaweek 42 28 29 Onceaweek – 14 14 Twiceaweek 5 10 16 >Twiceaweek 16 31 8 No 37 17 35 Reasons – Highprice – 3 – Itisnotbeneficial – – 1 Don’tlike 32 3 22 Other 5 11 12 Opinionaboutiftheseproductsarebeneficial – Yes 84 93 80 No 16 7 20 aWhen suitable, χ2 test was applied to test independence between clusters and demographic characteristics. TABLE3 Demographiccharacteristics andconsumptionhabitsforeachcluster and χ2testresults FIGURE2 Meanvaluesappearance scoresgivenbyconsumersandsignificant differencesidentifiedbyKruskal–Wallis test
| 33 FERNÁNDEZVÁZQUEZ Et al. threegroupsofconsumersclearlyidentified,andtheirdemography andconsumptionhabitsareshowninTable3.Resultsfromχ2 test showed that there were no significant differences in demographic characteristics or consumption frequency among clusters, indicatingthatthesevariablesdidnotinfluencecoloracceptancepatterns. Previousstudiesonconsumer’scoloracceptanceofdifferentproducts like strawberry nectar from puree and orange juices showed similarresults,whereneithergendernorageorconsumptionhabits hadsignificantimpactoncoloracceptance(Fernández-Vázquezetal., 2011;Gossingeretal.,2009). Mean appearance scores given by the clusters are shown in Figure3.Thefirstcluster(19%)showedaclearpreferenceforthose sampleswithorangishappearance,givingaveragepunctuationseven higherthan7(“Likemoderately”)andalsoadeeplydislikingforthose with a whiter look, with punctuations lower than 2 (“Dislike very much”). TABLE4 Meanacceptancescoresandappearanceofthesamples(picturestakenwithDigiEyeSystem) Samples Acceptance scores Samples Acceptance scores Samples Acceptance scores Samples Acceptance scores S1 3.5 S2 3.7 S3 3.9 S4 4.0 S5 4.2 S6 4.5 S7 4.7 S8 4.9 S9 5.3 S10 5.4 S11 6.1 S12 6.2 S13 6.3 S14 6.4 S15 6.4 S16 6.6 FIGURE3 Meanappearancescoresgivenbyeachoftheclusters
34 | FERNÁNDEZVÁZQUEZ Et al. However,cluster2(29%)didnotdifferentiatesomuchthesamples.Thus,theworstvaluatedbythisgroupofconsumerswasSample 2(averageof4.7)andthebestvaluatedwasSample14(averageof 7.6),whichimpliedaminorrangethantheothertwosegments. Finally,thethirdcluster(52%)wasthemostnumerous.Theseconsumersgavepunctuationslowerforallthesamples,andonlySample 16,withanaverageof6.2,wasvaluatedabove6(“Likeslightly”). These observations give additional information to the general resultsdiscussedearlier.Forinstance,itseemsthatwhileforsome consumers(Cluster1),colorofthesamplesisimportant,sincethey are capable of differentiating samples in terms of acceptance, just bylookingatthem;otherconsumers(Cluster2)didnotfounddifferencesamongthe beverageswhen theyonlyevaluated theirappearances.Moreover,fromthisanalysisitcanbeobservedthatfor agroupofconsumers(Cluster3),noneofthecolorsofthesamples wereappreciated. 3.2.2 | Internal preference mapping Internalpreferencemappingreferstotheanalysisofpreferencedata only,anditwasconductedtovisualizethegeneralbehaviorofthe clusters of consumers (Figure4). Two preference dimensions accountedfor95.18%ofthetotalvariance,sothethirdpreferencedimension was not considered. Alltheclustersappearrepresentedinthepositivevaluesofthe firstdimension.Cluster2issituatedinthehigherhalfofthesecond dimension,clearlyseparatedfromtheothersclustersandoppositeto samplesS2,S6,S7,andS8,indicatingarelativelylowerpreferencefor them(asconfirmedinFigure3).However,clusters1and3arelocated inthelowerhalfoftheseconddimension,oppositetosamplesS1,S3, S4,andS5,indicatingarelativelylowerpreferenceforthosesamples inbothclusters.Inaddition,cluster1ismuchclosertosamples12,13, and14,indicatingahigheracceptanceofthosesamplesascompared withcluster3(Figure3). Furthermore,samplesaredividedbythe first dimensionintwo well-defined groups. In the part of negative values, samples with slightlywhite and gray appearancearelocatedclearlyfar fromthe threeclusters.However,alltheorangishandreddishsamples(with theexceptionofonesample,S8)appearedinthepositivevaluesofthe firstdimension.Thisfactshowedgraphicallytheconsumertendency togivehigherpunctuationstothesampleswithmorevividcolors. 4 | CONCLUSIONS Inthisstudy,colorofcommercialMFJBwasmeasuredbytwodifferenttechniquesconfirmingthatboth,SPEandDIA,areappropriateto analyzetheappearanceoftheseproducts.However,consumerstudy showedthatthoughgenerallyparticipantssignificantlypreferredsampleswithorangishappearanceinsteadofthosewithawhiterlook,the lowpunctuationsgiventothesamples(mean=5.1)suggestedthat coloroftheseproductswasnothighlyevaluated.Thisfactshouldbe takenintoaccountbyindustriesastheappearanceoffoodproducts hasademonstratedinfluenceinfoodacceptance. ACKNOWLEDGMENTS ThisworkwassupportedbyfundingfromtheConsejeríadeInnovación CienciayEmpresa,JuntadeAndalucíabytheprojectP11-AGR-7783. CONFLICT OF INTEREST Nonedeclared. REFERENCES Baker,R.,&Günter,C.(2004).Theroleofcarotenoidsinconsumerchoice andthelikelybenefitsfromtheirinclusionintoproductsforhuman consumption.Trends in Food Science & Technology,15,484–488. FIGURE4 Internalpreferencemapping definedbythetwofirstpreference dimensionsfromtheconsumers’cluster
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