Sensory characterization of dry-cured ham using free-choice profiling

Sensory characterization of dry-cured ham using free-choice profiling

Sensory characterization of dry-cured ham using free-choice profiling

IRTA-Centro de Tecnologia de los Alimentos, Finca Camps i Armet, E-17121 Monells, Spain

Article history:

Received 19 February 2009

Received in revised form 19 August 2009

Accepted 19 August 2009

Available online 23 August 2009

Keywords:

Free-choice profiling

Consumer perception

Dry-cured ham

Sensory properties

a b s t r a c t

In this study, free-choice profiling was carried out to study how consumers perceived and described the sensory properties of dry-cured ham One hundred and nine consumers from three different Spanish regions evaluated the sensory characteristics of four different commercial dry-cured hams aged with age-ing times of 6, 9, 12 and 16 months Data were analysed by means of Generalized Procrustes Analysis In order to understand the sensory consumers’ vocabulary better a Quantitative Descriptive Analysis with seven trained assessors was also performed In general, results showed that consumers used simple terms

to describe the sensory characteristics of the samples, paying special attention to the appearance, espe-cially, the colour and fat content of the dry-curedham There was some disagreement in the case of salty taste and texture descriptors, but, apart from that a consensus in the use of sensory attributes was observed Data from trained assessors proved to be a useful method for understanding and validating consumers’ vocabulary

Ó 2009 Elsevier Ltd All rights reserved

1 Introduction

The sensory quality of dry-cured ham results from the

interac-tions between the characteristics of the fresh matter and the

Guerrero, & Sárraga, 1998; Buscailhon, Gandermer, & Monin,

1994; Parolari, Virgili, & Schivazappa, 1994; Vestegaard,

Schivaz-appa, & Virgili, 2000) The extent of these changes depends on

the initial composition of the raw material and the technological

process (Buscailhon, Berdagué, & Monin, 1993) and the ageing

duration (Guàrdia, Guerrero, Gou, Monfort, & Arnau, 1999) In

addition to these factors affecting sensory properties, there are

fur-ther aspects such as habits of consumption (Mili, Mahlau, &

Furi-tsch, 1996) and socio-cultural characteristics related to the

geographical region (Cilla et al., 2006) that also affect consumers’

quality perception of dry-cured ham

Sensory descriptive tests are among the most sophisticated

tools used by sensory scientists (Lawless & Heymann, 1998) and

involve the discrimination and description of both the qualitative

and quantitative sensory components (Meilgaard, Civille, & Carr,

1991) Several different methods exist within descriptive analysis

that reflect different sensory approaches (Lawless & Heymann,

1998) Quantitative Descriptive Analysis (QDA) is a technique

fre-quently used in sensory characterization of food In this respect,

several authors (Cilla, Martínez, Beltrán, & Roncalés, 2006;

García-González et al., 2006; Guerrero, Gou, Alonso, & Arnau,

1996; Rousset & Martin, 2001) have used trained panels to

describe the sensory properties of different types of dry-cured ham However, QDA is very time-consuming due to the extensive training that assessors must undergo Furthermore,Piggott, Sheen, and Apostolidou (1990)pointed out that trained and experienced assessors normally tend to generate complex and scientifically ori-ented terms in sensory research which may be difficult for non-specialized people to understand

Free-choice profiling (FCP) is a sensory methodology that differs from other descriptive methods because it is not necessary to use a common vocabulary of attributes to describe the samples, nor are the panellists expected to agree on their interpretation of the terms used By means of FCP, each participant produces their own descriptive profiles of the products, without having to explain the exact meaning (Williams & Langron, 1984) This is based on the assumption that panellists do not differ in their perceptions, but merely in the way in which they describe them FCP is similar

to traditional profiling in that assessors must be able to detect dif-ferences between the samples, verbally describe the perceived attributes and quantify them (Oreskovich, Klein, & Sutherland,

1991) The FCP strategy can yield important insights into consumer differentiation of products and establish relationships between consumer preferences and sensory characteristics (Jack & Piggott,

1992) The analysis of the data collected from FCP is normally

1975; Langrom, 1983) This statistical technique allows for the rationalization of the spatial configurations derived from individ-ual profiles The result is a consensus configuration revealing the interrelationships between the samples for the panel as a whole (Williams & Langron, 1984) Regarding the number of attributes generated, this is limited only by the perceptual and descriptive 0950-3293/$ - see front matter Ó 2009 Elsevier Ltd All rights reserved.

* Corresponding author Tel.: +34 972 630052; fax: +34 972 630373.

E-mail address: lluis.guerrero@irta.es (L Guerrero).

Contents lists available atScienceDirect Food Quality and Preference

j o u r n a l h o m e p a g e : w w w e l s e v i e r c o m / l o c a t e / f o o d q u a l

skills of the consumer (Oreskovich et al., 1991) and, according to

Deliza, MacFie, and Hedderley (2005), terms used by untrained

assessors may vary, based on their individual experience and

familiarity with the product To summarize, FCP offers the

possibil-ity of assisting the demands of marketing and product

develop-ment teams who require information on target consumer’s

perception of products, rather than the more technical descriptions

of the products typically provided by trained sensory panels

(Elmore & Heymann, 1999; Murray, Delahunty, & Baxter, 2001)

The aim of this study was to evaluate how consumers

repre-senting three different Spanish regions perceive and describe

sen-sory characteristics of four different types of commercial dry-cured

ham using FCP Furthermore and, in order to surmount the

incon-venience related to the interpretation of the consumers’

vocabu-lary, a QDA with trained assessors was used to facilitate

comprehension of the terms generated by consumers

2 Materials and methods

2.1 Dry-cured ham sample preparation

Four types of commercial Spanish dry-cured ham from white

pig breeds with aging times 6, 9, 12 and 16 months (samples A,

B, C and D, respectively) were selected to provide a wide range of

sensory variability and to stimulate the generation of attributes

by consumers Three dry-cured hams of each type were boned,

cut at the head of the femur level and then sliced (1.5 ± 0.2

mm-thick) perpendicularly to the femur axis in the distal part direction

(Fig 1) with a vertical slicer Kolossal 350 BVK (Marconi, Italy) So

that the panellists were not distracted by testing cuts from

differ-ent areas of the dry-cured ham (Guerrero, Guàrdia, & Arnau, 2004,

2005), the slices evaluated by each consumer were from the same

anatomical position for each one of the four dry-cured hams

assessed

Slices were placed inside polypropylene trays, packed in bags

per-meability: 7 cm3/m2/24 h at 4 °C and 80% RH; CO2 permeability:

1150 cm3/m2/24 h at 23% and 75% RH; water-vapour permeability:

1.5 g/m2/24 h; SACOLIVAÒ, S.L., Castellar del Vallès, Spain) under

modified atmosphere (99.8 ± 0.1% N2 and 0.1 ± 0.1% O2) with an

oxygen scavenger (Tyvek LH3000, ATCO) and then stored at

2 °C ± 2 °C for a maximum period of 7 days

2.2 Physicochemical description of samples Moisture and fat content of six slices per ham were analysed by near infrared transmittance (NIT) spectroscopy with an INFRATECTM

1265 Meat Analyzer (Tecator AB, Sweden) NaCl content was

Physico-chemical composition of dry-cured hams used in the study is shown inTable 1

2.3 Descriptive sensory analysis 2.3.1 Free-choice profiling (FCP)

A group of 109 consumers aged between 21 and 68, recruited in the Centre (Madrid) (n = 34), South (Sevilla) (n = 37) and North (Girona) (n = 38) of Spain, participated in the study The recruit-ment was randomly made by phone, using a filter questionnaire specifically elaborated for this study, including demographic and socio-economic information (gender, age, education level, and working situation) and frequency of consumption of different food products including dry-cured ham Only consumers who declared eating ham at least once every two weeks, and with no previous experience in sensory analysis, were selected

To avoid the effect of storage time on the sensory properties of dry-cured ham, sensory evaluation of the samples was carried out

in all three cities in the same week Two FCP sessions with 15–20 consumers each were carried out per city Participants were re-ceived in a conference room and placed at individual tables under white lighting (700 lx ± 150 lx) First of all, consumers were briefed

on the concept of the methodology and the procedure The aim of this was to allow for development of the vocabulary to describe the four types of dry-cured ham Each consumer was given one slice of each of the four dry-cured hams They were instructed to include only objective attributes and not to use hedonic terms During this task, the consumers were first asked to describe the appearance and the odour of the samples After, they were requested to taste the sample and to describe the flavour and texture characteristics writing their personal perception in their own words Then, each consumer once again received one slice of each type and scored the four types of dry-cured ham using his/her own previously gen-erated descriptors In this case, the same hams were presented but with different codes and in a different order All samples were as-sessed in the same tasting session balancing the first-order and carry-over effects (Macfie, Bratchell, Greenhoff, & Vallis, 1989) Sensory attributes were evaluated using an unstructured 100 mm line scale anchored with the words ‘‘absence” and ‘‘intense” at each end

In all sessions, slices of dry-cured ham were evaluated at room temperature (20 °C) and presented on white plastic plates covered with a food grade PVC film (oxygen permeability; 20,000 cm3/m2/

b

a

20 mm 25 mm

c

b

a

20 mm 25 mm

c

Fig 1 Schematic view of the dry-cured ham sampling: (a) sample for

physico-chemical analysis; (b) sample for sensory analysis (QDA) and (c) sample for

Table 1 Least square means and RMSE for moisture, fat content and NaCl and each type of dry-cured ham (n = 3).

Moisture (%) <0.0001 51.34 a

48.17 a 50.71 a 40.65 b 3.035 Fat content (%) 0.0002 6.83 b

12.36 b

7.13 b 19.68 a 4.001 NaCl (%) <0.0001 6.05 a 5.10 b 5.63 a 4.79 b 0.231 a,b

Within a row, least square means with different superscripts differs significantly (p < 0.05).

RMSE: root mean standard error.

* A = 6, B = 9, C = 12 and D = 18 months of ageing time, respectively.

24 h; water-vapour transmission rate 2000 g/m2/24 h; Macopal,

S.L., Lliçà de Vall, Spain) to prevent drying Samples were coded

with three-random numbers and, for each consumer, all the

sam-ple slices came from the same anatomical position Mineral water

and unsalted crisp-bread were provided to rinse consumers’

mouths between samples

2.3.2 Quantitative Descriptive Analysis (QDA)

Seven selected and trained assessors (ASTM, 1981; ISO 8586-1,

1993; ISO 8586-2, 1994) undertook the sensory analysis on 1.5 mm

slices from the same dry-cured hams (n = 12, three dry-cured hams

and four ageing times) previously evaluated by the consumers The

generation of the descriptors had been carried out in open

discus-sion in two previous sesdiscus-sions The descriptors retained were:

sweetness (basic taste sensation elicited by sugar), saltiness (basic

taste sensation elicited by NaCl), bitterness (basic taste sensation

elicited by caffeine andL-tryptophan), metallic (flavour similar to

a solution of FeSO4
7H2O), piquantness (stinging sensation in the

mouth and throat), matured flavour (set of complex nuances

char-acteristic of dry-cured meat products, not described by other

fla-vour attributes), aged (flafla-vour related to aged fat which is

characteristic of long aged Spanish dry-cured ham partially

skinned according to the typical V shape;Gou, Arnau, & Guàrdia,

which the surface of the ham slice adheres to the palate when

com-pressed with the tongue), hardness (amount of pressure required

to completely compress the sample), crumbliness (textural

prop-erty characterized by ease with which a sample can be separated

into smaller particles during chewing), pastiness (feeling of paste

detected in hams with a high proteolytic index), fibrousness

(tex-tural property characterized by the perception of the amount of

muscle fibres detected during chewing) The references used to

illustrate the maximum intensity of hardness, crumbliness and

(1999) A non-structured scoring scale (Amerine, Pangborn, &

Roessler, 1965) was used, where 0 meant absence of the descriptor

and 10 meant high intensity of the descriptor Sensory evaluation

was undertaken in three sessions and a complete block design

was used (Steel & Torrie, 1960–1983), where each taster assessed

the four different types of dry-cured ham in each session Samples

were coded with three-random numbers and were presented to

the assessors balancing the first-order and the carry-over effects

were evaluated in slices from the same anatomical area

2.4 Data analysis

2.4.1 Free-choice profiling data analysis

Data from the FCP was submitted to Generalized Procrustes

Analysis, and a consensus matrix was obtained by using

mathe-matical data operations according toArnold and Williams (1986)

The average of all transformed configurations that shows the

min-imum overall deviation was obtained as a consensus space It

sum-marizes the information on the samples and replaces the panel

mean (Langrom, Williams, & Collins, 1984) Similar terms were

grouped together in order to simplify the map obtained Only

agreed descriptors with correlation coefficients higher than 0.6 in

at least one of the first two dimensions and mentioned by more

than eight consumers were used to visualize the relationships

be-tween samples and attributes

The frequency of descriptors used by consumers in each city

& Belsius, 1994), including gender, age, education level, working

situation and consumption frequency of each consumer as

supple-mentary variables

Statistical analyses were carried out using XLSTAT software (Addinsoft, France)

2.4.2 Quantitative descriptive data analysis Data from the Quantitative Descriptive Analysis was analysed

(2001) The ANOVA test was performed over the mean score (seven assessors) for each dry-cured ham because each dry-cured ham is the experimental unit (when performing sensory analysis all the assessors evaluate the same ham) The model included the type

of dry-cured ham (ageing time) and the taste session as fixed ef-fects The interaction assessor  type of dry-cured ham was tested and dropped from the model since it was not significant (p > 0.05) Differences between treatments were tested by the Tukey test Fur-thermore, a Principal Component Analysis was carried out on the mean score for each dry-cured ham

2.4.3 Physicochemical data analysis Data from physicochemical analysis were submitted to one-way ANOVA (SAS, 2001) including the type of dry-cured ham (age-ing time) as a fixed effect Mean comparisons were carried out using the Tukey test

3 Results and discussion Demographic, socio-economic characteristics and frequency of dry-cured ham consumption of the consumers involved in the present study are shown inTable 2 About 44.0% of the consumers were men and 56.0% women and most of them were aged between

20 and 50 (80.7%) The final age distribution of the consumers who participated in the present study showed a bias when compared with the Spanish population (33.41% of which are older than 50; INE, 2007) This bias may be explained by the additional selection criteria used of consumption frequency – eat ham at least once every two weeks Normally, people aged over 50–55 tend to reduce salt and fat consumption in order to prevent cardiovascular risk factors (Black, 2000) and both are present in dry-cured ham A large percentage of consumers had a medium education level (45.9%) similar to the Spanish average (48.03%,INE, 2001) and, 67.9% of them were employees In this case, the official data (INE,

Table 2 Demographic, socio-economic characteristics and frequency of dry-cured ham consumption of the participants (% of respondents, n = 109).

Socio-demographic characteristic % of respondents Gender

Age

Education level

Working situation

Consumption frequency

population aged over 16 and in this sense our sample was also

slightly biased

Almost half of the respondents (47.7%) stated that they

con-sumed dry-cured ham two or three times a week, 22.9% more than

three times a week, 18.3% once a week and 11.0% less than once a

week These results may be explained by the high Spanish

be-cause the consumption of dry-cured ham (higher than once every

two weeks) was one of the criteria of recruitment These results are

in agreement with those obtained byCilla et al (2006), Resano,

Sanjuán, and Albisu (2007) and Morales, Guerrero, Claret, Guàrdia,

and Gou (2008)

The results obtained that each consumer in FCP used 10

attri-butes, on average, to describe differences between samples The

number of attributes ranged from 4 to 20 (Fig 2) Most of the terms

used by consumers (39.7%) referred to appearance, 26.5% to

fla-vour, 17.9% to texture and 15.9% to odour The high number of

con-sumers’ words dealing with appearance (n = 431) agrees with

Guerrero, Aguiar, Guàrdia, Claret, and Arnau (2007)which stated

that this is the most important factor for Spanish consumers in

pointed out that visual attributes are easier to describe than the

oronasal senses, because vision and hearing are an inborn

mecha-nism, whereas the other senses rely largely on learning

Table 3 shows the frequency of occurrence for the most

fre-quent attributes mentioned by consumers Colour, intensity of

dry-cured ham odour, saltiness, intensity of dry-cured ham flavour

and fat content were mentioned by more than 59% of the

respon-dents On taking into account the consumer response, it can be

sta-ted that the aforementioned descriptors probably represent the

most important sensory attributes in dry-cured ham or, according

toKöster (2003), the easiest to elicit In a similar way,Resano et al

(2007)observed that 90% of consumers from the central Spanish

region considered colour, fat and salty taste as very or quite

impor-tant in dry-cured ham selection Also,Morales et al (2008)found

that more than 70% of consumers from Catalonia (Northeast part

of Spain) pointed out that colour, salty taste, aged flavour and

tex-ture were the most important parameters affecting the purchase of

dry-cured ham

Fig 3shows the graphic results of GPA over the consumer

sen-sory profiles The variance accounting for the first two components

was 83.7% Similar descriptors used by different assessors and

lo-cated in the same area in the first two dimensions have been

grouped In these cases the size of the descriptor is proportional

Schlich, & Lesschaeve, 1992) The results obtained revealed that

sample D (with the highest ageing time) located in the negative area of the first dimension was mainly defined by colour, dry-cured ham odour and flavour and fat content and, to a lesser degree (the smaller letter size) by marbling, saltiness, texture, matured flavour, juiciness and appearance Conversely, sample A (with the least age-ing time) located in the positive direction of the first axis was char-acterized by hardness, dryness, saltiness and atypical flavour/ odour attributes Ageing is referred to as one of the main factors responsible for developing sensory characteristics of dry-cured ham due to biochemical reactions that occur throughout this pro-cess (Flores, Ingram, Bett, Toldrá, & Spanier, 1997) In this study, another consideration to explain the differences observed between samples A and D is their different physicochemical composition, particularly in fat and moisture content (Table 1) Dry-cured hams

B and C show intermediate characteristics within this first dimen-sion of the consensus space However, the second dimendimen-sion

con-Table 3 Frequency of occurrence for the most frequently elicited descriptors.

Spanish)

Frequency a (%) Colour (dark, red) Color, color oscuro, rojo 87.2 Odour intensity (dry-cured ham

odour)

Olor, olor a jamón 75.2 Saltiness, amount of salt Salado, cantidad de sal 72.5 Flavour intensity (dry-cured ham

flavour)

Sabor, intensidad, a jamón

66.1

White spots Pintas blancas, puntos

blancos

19.3

homogeneidad

9.2

a Percentage of respondents (n = 109).

0 5 10 15 20

number of atributes

undefined appearance odour taste texture

trasts sample B in the positive direction, with sample C in the

neg-ative Sample C is described as having white spots, matured,

salti-ness and tendersalti-ness attributes

Some discrepancies were observed among consumers regarding

perception of saltiness in this study Conversely, Parolari (1994)

did not observe these differences in a similar investigation

per-formed on Italian Parma hams Saltiness was located in the four

areas defined by the first two dimensions, which means that they

were not used in the same way by the participants Saltiness is a

basic taste and a well-known sensory attribute, so agreement

among consumers would be expected This apparent contradiction

detected in saltiness can be explained by the fact that salt content

(NaCl) in Spanish dry-cured ham is very heterogeneous,

particu-larly when there are important differences in moisture content

be-tween muscles (Arnau, Guerrero, Casademont, & Gou, 1995) Since

several consumers only tasted a portion of the slices provided, this

could have contributed to the discrepancies in saltiness perception

among them Another possible explanation for this contradictory

result is that dry-cured ham is a product with high salt content

O’Mah-ony (1986)explains that when a stimulus is experienced (i.e., a

product is tasted), some residue remains in the mouth The taste

system adapts to such residual stimuli rendering it less sensitive

to such stimuli, and when tasted subsequently the high salt

con-tent will taste less intense In order to reduce any desensitization

due to adaptation, unsalted crisp-bread and mineral water were

provided to rinse the mouth at the beginning of the session and

be-tween samples However, it is probable that all the consumers did

not follow these recommendations fully Conversely, the trained

assessors always tasted the central part of each slice containing a

portion of semimembranosus and biceps femoris muscles in order

to block differences in salt content between them Furthermore,

trained panellists are aware of the fact that the taste system adapts

to residual stimuli when dry-cured ham is tasted and they follow

the abovementioned instructions In our opinion these are the

main reasons for explaining why the problems observed in the

consumer study were not observed in the QDA study

Hardness, fibrousness and tenderness attributes also showed a

slight disagreement (Fig 3) Some consumers described sample A

as hard in the positive direction of the first dimension However,

fibrousness, hardness and tenderness descriptors were also placed

in the negative area of this first dimension, close to sample D Fur-thermore, tenderness was also explained by the second dimension and related with sample C in the negative direction of this axis Again, this discrepancy could be due to the slice portion tasted

by each consumer, since external muscles (semimembranosus) are

Ruiz-Ramírez, Arnau, Serra, & Gou, 2006) The meaning of the term tex-ture (located in the negative area of the first dimension) is not eas-ily interpreted, as it is of a multidimensional concept and therefore

a number of confusing attributes come together In this sense, Szc-zesniak (2002)stated that consumers have difficulty in describing texture due to its complex nature, since there are no single and specific receptors for it, in contrast to other sensory attributes, such as colour and taste Therefore, the apparent discrepancy ob-served in our results could be due to the fact that consumers have different ways of describing their perceptions, depending on indi-vidual experiences, preferences and familiarity with the product (Deliza et al., 2005) In addition, they may also differ considerably

in their ability to express themselves (Lachnit, Busch-Stockfisch, Kunert, & Krahl, 2003)

Dry-cured ham samples were also sensory evaluated by a trained panel to clarify and understand the consumer vocabulary better Least square means corresponding to the sensory descrip-tors are shown inTable 4 (in this table, n = 3 means that three dry-cured hams of each ageing time were sensory evaluated) The total number of different descriptors generated by the trained panel was slightly higher than those from the consumers Con-versely,Moskowitz (1983)stated that trained panellists use fewer descriptors than those untrained, because it seems that the effort expended in accurate description replaces the effort used to cap-ture all attributes Ten of the selected descriptors by the expert pa-nel were discriminant (p < 0.05) between dry-cured hams Samples

A and D were different in eight of the twelve descriptors used, however, B and C only differed in five of them (Table 4) Fig 4 shows the graphic results of PCA over the sensory descriptors from the trained panel and dry-cured ham samples

The results obtained with GPA (Fig 3) and PCA (Fig 4) are com-plementary to each other and sample location was similar among

(1997)also obtained similar results when they compared sensory profiles from expert and semi-trained assessors In this study, sam-ples A and D were differentiated by the first dimension, whereas B and C were separated by the second dimension The comparison

D

B

C

A

colour

fat

odour

flavour

saltiness

marbling

odour

flavour

texture

hard

cured

white spots

atypical flavour/odour juiceness

saltiness tender

cured

tender

appearance

saltiness

saltiness

dry

soft

brightness

fibrous/hard

shape

rancid

-1

-0.5

0

0.5

1

Dimension 1 (57.2%)

Fig 3 Consensus space obtained using Generalised Procrustes Analysis over the

sensory consumer profile of dry-cured ham (the letters represent the dry-cured ham

samples) The size of each descriptor is proportional to the number of assessors who

agree on their use Only those descriptors having a correlation coefficient higher or

equal 0.06 with one of the two first dimensions of the consensus space are shown.

Table 4 Least square means and RMSE for each sensory descriptor and for each type of dry-cured ham obtained from the sensory analysis (n = 3).

Flavour Sweetness 0.3 c

0.8 bc

1.1 ab

1.9 a

0.665

2.2 ab

2.0 bc

1.0 c

0.975 Piquantness 2.1 a

1.4 ab

1.7 ab

0.9 b

1.242 Matured flavour 2.4 b

3.0 b

4.7 a

5.6 a

1.168 Aged flavour 0.3 c

0.7 c

2.3 b

4.2 a

1.110 Texture

Adhesiveness 1.1 b

1.8 a

1.0 ab

1.6 ab

0.999

3.0 b

4.0 a

3.2 b

0.615 Crumbliness 4.2 b

4.7 ab

5.1 a

5.3 a

0.855

a,b,c Within a row, least square means with different superscripts differs signifi-cantly (p < 0.05).

RMSE: root mean standard error.

*

betweenFigs 3 and 4allows us to ascertain the sensory attributes

behind consumer vocabulary Dry-cured ham sample A, defined as

bitter, piquant and metallic in PCA was described as having an

atypical flavour/odour in GPA Atypical flavour/odour is a

compila-tion of several words such as feed, male, acid and different

off-odour or off-flavour attributes used by consumers that had similar

location on the consensus space Hardness and fibrousness as

re-ferred mainly to sample A by the trained panel, could mean hard

and dry texture in consumer words The crumbliest dry-cured

ham sample D is characterized by juiciness, texture, tender and

soft in the GPA consensus space Likewise, odour, flavour and

ma-tured terms mentioned by consumers (GPA) could be interpreted

as sweetness, matured and aged flavour in the trained panel

vocab-ulary (PCA) Samples D were also the dry-cured hams with the

highest fat content (Table 1), which accordingly have been related

to higher sweetness and juiciness (Guàrdia, Guerrero, Gispert,

Gar-nier, & de Vries, 1999) and matured flavour (Bolzoni, Barbieri, &

Virgili, 1996; Flores et al., 1997)

As expected, consumers in general used a large number of

unspecific descriptors (colour, taste, odour, appearance and

tex-ture) compared to the trained assessors Some attributes used by

the trained panel i.e., metallic, aged, pastiness, crumbliness,

adhe-siveness were not elicited by more than three consumers, probably

due to the fact that most consumers were either not familiar with

these attributes or did not know their meaning On the other hand,

consumers showed great ability in describing appearance,

high-lighting several features like colour, fat content, marbling,

bright-ness, white spot presence, size and shape In contrast,Hersleth,

Berggren, Westad, and Martens (2005)found in a study on bread

that Norwegian consumers were more efficient in describing

tex-ture attributes than other sensory characteristics These different

results could be due to the fact that consumer sensory perception

tends to be specific for a product, since it provides a different

de-gree of importance to different sensory attributes depending on

the particularities of each food product, and texture seems to be

a more important aspect in bread than ham It is important to

no-tice as well that these differences may be due to the existence of a

different awareness of descriptive terms between Norwegian and

Spanish consumers and the lack of defective texture in the

dry-cured ham samples tasted

Fig 5 shows the results obtained by means of Simple

Corre-spondence Analysis over the contingency table of the different

descriptors elicited by consumers for each city and gender Since age, education level and work situation (supplementary variables) did not show significant differences, these variables were not rep-resented inFig 5 Attributes such as brightness, uniform, colour or appearance were most frequently mentioned in Sevilla; juiciness, hardness, matured flavour, white spots and slice size in Madrid; and fat colour, rancid flavour, sinews, dry and tenderness in Girona This last result may be explained by some differences in habits of meat products consumption at home between geographical areas (Mili et al., 1996) According toAskegaard and Madsen (1998) Eur-ope cannot be regarded as a homogeneous sensory culture since important differences exist in consumption patterns, behaviour and attitudes not only between countries but also between regions within the same country In Spain, dry-cured ham consumption patterns differ clearly between regions If we analyze it by geo-graphical areas, the region of greatest consumption is Catalonia, the Basque Country and Madrid, which represent 70% of the con-sumption, followed by Andalucía and Extremadura (in the South-west), and then Cantabria, Navarra, La Rioja, Galicia and Asturias (Comunidad de Madrid, 2006)

Regarding consumers ‘gender and consumption frequency, sig-nificant differences were found Men and more frequent consum-ers (F1 and F2: 2 or more times a week) described dry-cured ham samples by means of colour, marbling, brightness, hardness, matured flavour and juiciness, whereas women and less frequent consumers (F3: once a week or less) tended to use more recurrent descriptors such as sinews, uniformity, fat colour, rancidity, white spots and saltiness Differences between genders in sensory evalu-ation of food products have been described in scientific literature and may be mainly explained by the different sensitivity of men and women (Chauban, 1989; Prodi et al., 2004; Ullrich & Tepper,

2000) or by a different attitude towards different food related as-pects that are frequent between genders (Aaron, Mela, & Evans, 1994; Dennison & Sheperd, 1995; Guerrero et al., 1999; Guàrdia, Guerrero, Gelabert, Gou, & Arnau, 2006; Kähkönen, Tourila, & Rita, 1996; Sheperd, 1988)

4 Conclusions This study indicates the applicability of FCP methodology in or-der to find out how consumers describe dry-cured ham sensorially

metallic

sweetness

saltiness piquantness

bitterness

aged flavour

matured flavour

adhesiveness

hardness crumbliness

pastiness

fibrousness

A A A

B B B

C

D

D

D

-1

-0.5

0

0.5

1

PC1 (56.1%)

Fig 4 Principal Component Analysis of the sensory profile of four dry-cured ham

samples (A, B, C and D).

SEVILLA

MADRID GIRONA

F3

F2F1 WOMEN

MEN

nerves

size

uniform

fat colour

aspect soft rancid

brightness

juiciness white spots

tender

tough dry texture

marbling cured fat flavour saltiness odour colour

-1 -0.5 0 0.5 1

Dimension 1 (63.7 %)

Fig 5 Graphical distribution of dry-cured samples (A, B, C and D) and descriptors for each city obtained using Simple Correspondence Analysis over the contingency table of the generic descriptors of the consumer sensory profile, including gender (men and women) and consumption frequency (F1 = more than three times a week; F2 = two or three times a week; F3 = once a week or less) as supplementary variables.

Consumers paid more attention to the appearance of the product.

Most of the attributes selected by participants were elementary,

thus reflecting their simplicity when compared with those

ob-tained from the trained panel Consumers showed a high level of

agreement in the use of sensory attributes, except for saltiness

and texture descriptors The little agreement in these key

dry-cured ham attributes could be a limitation in FCP applied to ham

Our results indicate that the consumer sensory description of

dry-cured ham depends on the geographical region where the

con-sumer lives Trained assessors and concon-sumers describe sensory

attributes of dry-cured ham in a similar way and, in both cases,

they are able to differentiate the ageing times of dry-cured ham

The sensory descriptive profile obtained by means of trained

asses-sors proves to be a useful tool to understand consumers’

vocabu-lary regarding dry-cured ham better

Acknowledgments

The authors would like to acknowledge the Spanish Ministry of

Education and Science/INIA (Project RTA 2006-00060-00-00) for

supporting this research work

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