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Sensory characterization of dry-cured ham using free-choice profiling
Sensory characterization of dry-cured ham using free-choice profiling M. Dolors Guàrdia, Ana P.S. Aguiar, Anna Claret, Jacint Arnau, Luis Guerrero * IRTA-Centro de Tecnologia de los Alimentos, Finca Camps i Armet, E-17121 Monells, Spain article info 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 abstract 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 bio- chemical changes occurring during the processing (Arnau, 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 car- ried out by means of Generalized Procrustes Analysis (Gower, 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. doi:10.1016/j.foodqual.2009.08.014 * Corresponding author. Tel.: +34 972 630052; fax: +34 972 630373. E-mail address: lluis.guerrero@irta.es (L. Guerrero). Food Quality and Preference 21 (2010) 148–155 Contents lists available at ScienceDirect Food Quality and Preference journal homepage: www.elsevier.com/locate/foodqual 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 (50 l m polyamide/100 l m polyethylene multilayer; oxygen per- meability: 7 cm 3 /m 2 /24 h at 4 °C and 80% RH; CO 2 permeability: 1150 cm 3 /m 2 /24 h at 23% and 75% RH; water-vapour permeability: 1.5 g/m 2 /24 h; SACOLIVA Ò , S.L., Castellar del Vallès, Spain) under modified atmosphere (99.8 ± 0.1% N 2 and 0.1 ± 0.1% O 2 ) 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 INFRATEC TM 1265 Meat Analyzer (Tecator AB, Sweden). NaCl content was deter- mined by the Charpentier–Volhard method (ISO, 1970). Physico- chemical composition of dry-cured hams used in the study is shown in Table 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 cm 3 /m 2 / 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 consumer study. Table 1 Least square means and RMSE for moisture, fat content and NaCl and each type of dry-cured ham (n = 3). p Samples * RMSE ABCD 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. M.D. Guàrdia et al. / Food Quality and Preference 21 (2010) 148–155 149 24 h; water-vapour transmission rate 2000 g/m 2 /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 sessions. 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 and L -tryptophan), metallic (flavour similar to a solution of FeSO 4 Á7H 2 O), 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 (flavour 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, 2000), adhesiveness (textural property rated by the degree to 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 pastiness were those described by Guerrero, Gou, and Arnau (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 as much as possible according to Macfie et al. (1989). All hams 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 to Arnold 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 was analysed using Simple Correspondence Analysis (Greenacre & 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 by means of the ANOVA test using the GLM procedure of SAS (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 in Table 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, 2001) in Spain shows that employees represented 55.58% of the 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 Male 44.0 Female 56.0 Age 20–35 years 39.4 36–50 years 41.3 >50 years 20.2 Education level Primary school 20.2 Secondary school 45.9 University 33.9 Working situation Employed 67.9 Unemployed or retired 28.4 Student 3.7 Consumption frequency >3 times a week 22.9 2 or 3 times a week 47.7 Once a week 18.3 <Once a week 11.0 150 M.D. Guàrdia et al. / Food Quality and Preference 21 (2010) 148–155 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 con- sumption per capita (4.6 kg per year, MAPA, 2005) and also 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 by Cilla 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 dry-cured ham purchase decisions. Furthermore, Köster (2003) 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 to Köster (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. 3 shows 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 to the number of consumers who agree on their use (Issanchou, 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 dimension con- Table 3 Frequency of occurrence for the most frequently elicited descriptors. Attribute Original words (in 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 Fat content Grasa, tocino 59.6 Matured Curado, curación 34.9 Marbling Veteado, vetas 31.2 Texture Textura 22.0 Dry Seco, sequedad 20.2 Hard (tough) Duro, dureza 20.2 White spots Pintas blancas, puntos blancos 19.3 Tender Tierno, blando 19.3 Juiciness Jugoso, jugosidad 15.6 Brightness Brillo, brillante 13.8 Appearance Aspecto, presencia 13.8 Rancid Rancio 11.9 Soft Suave 11.0 Fat colour Color de la grasa 11.0 Uniform Uniformidad, homogeneidad 9.2 Sinews Nervios 9.2 Slice size Tamaño de la loncha 9.2 Slice shape Forma de la loncha 8.3 Thickness Grosor, espesor 8.3 a Percentage of respondents (n = 109). 0 5 10 15 20 4567891011121314 1 51617181920 number of atributes number of consumers undefined appearance odour taste texture Fig. 2. Frequency of attributes used by consumers to describe dry-cured ham samples. M.D. Guàrdia et al. / Food Quality and Preference 21 (2010) 148–155 151 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 tenderness 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 that could lead to an adaptation in consumer perception. 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 usually much harder than internal ones (biceps femoris)(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 in Table 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 consumers and trained assessors. Guerrero, Gou, and Arnau (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 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 Dimension 2 (26.5%) 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). Attributes Samples * RMSE ABCD Flavour Sweetness 0.3 c 0.8 bc 1.1 ab 1.9 a 0.665 Saltiness 4.9 a 3.0 b 4.2 a 2.4 b 1.168 Bitterness 1.3 1.0 1.2 0.9 0.848 Metallic 3.1 a 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 Hardness 4.0 a 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 Pastiness 1.2 ab 1.8 a 0.5 c 1.1 bc 0.879 Fibrousness 3.4 2.9 3.4 2.8 0.854 a,b,c Within a row, least square means with different superscripts differs signifi- cantly (p < 0.05). RMSE: root mean standard error. * A = 6, B = 9, C = 12 and D = 18 months of ageing time, respectively. 152 M.D. Guàrdia et al. / Food Quality and Preference 21 (2010) 148–155 between Figs. 3 and 4 allows 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 in Fig. 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 to Askegaard 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 C C D D D -1 -0.5 0 0.5 1 -1 -0.5 0 0.5 1 PC2 (23.5%) PC1 (56.1%) Fig. 4. Principal Component Analysis of the sensory profile of four dry-cured ham samples (A, B, C and D). SEVILLA MAD RID GIRONA F3 F2 F1 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 -1 -0.5 0 0.5 1 Dimension 1 (63.7 %) Dimension 2 (36.3 %) 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. M.D. Guàrdia et al. / Food Quality and Preference 21 (2010) 148–155 153 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. 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