Sensory characteristics of different cod products related to consumer preferences and attitudes

Food Quality and Preference 20 (2009) 120–132

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Sensory characteristics of different cod products related to consumer preferences and attitudes Kolbrún Sveinsdóttir a,e,*, Emilía Martinsdóttir a, Ditte Green-Petersen b, Grethe Hyldig b, Rian Schelvis c, Conor Delahunty d a

Matís ohf (former Icelandic Fisheries Laboratories), Skúlagata 4, 101 Reykjavík, Iceland Danish Institute for Fisheries Research, Technical University of Denmark, Build. 221, DK-2800 Lyngby, Denmark c Institute for Marine Resources and Ecosystem Studies (former RIVO), Haringkade 1, 1976 CP IJmuiden, Postbus 68, 1970 AB IJmuiden, The Netherlands d Food Science Australia, 11 Julius Avenue, Riverside Corporate Park, North Ryde NSW 2113, Australia P.O. Box 52, North Ryde NSW 1670, Australia e Department of Food Science and Nutrition, University of Iceland, Eiríksgata 29, 101 Reykjavik, Iceland b

a r t i c l e

i n f o

Article history: Received 23 May 2006 Received in revised form 20 June 2008 Accepted 7 September 2008 Available online 13 September 2008 Keywords: Fish Cod products Sensory evaluation Preference mapping Cluster analysis Consumer attitudes

a b s t r a c t Quantitative descriptive analysis (QDA) was used to analyse the sensory quality of eight cod products, different with regard to origin (wild/farmed), storage time (short/extended) and storage method (fresh/ frozen/packed in modified atmosphere). At the same time, 378 consumers in four European countries tasted and scored the cod products on a 9-point hedonic scale. In addition information on the consumers attitudes, motives/barriers and fish purchase behaviour was collected. The aim was to investigate how sensory quality corresponded to consumers liking of different cod products and to study the liking in terms of different consumer attitudes and demographics. The QDA discriminated well between the products. The farmed cod products were considerably different from wild cod, with more light and even colour, meaty texture, odour and flavour. Country differences were considerable with regard to fish consumption, attitudes and preferences of the eight cod products. However, it was demonstrated that within each country, different segments of consumers existed with different preferences, motives/barriers and demographic background. The results indicated various potential to increase fish consumption. Ó 2008 Elsevier Ltd. All rights reserved.

1. Introduction The aims of the present study were to compare and relate sensory quality to consumer acceptability of wild and farmed cod, as well as cod stored under different conditions (fresh, frozen, MA-packed cod fillets) for short and extended storage time. In addition, we wished to determine whether different groups of consumers had different likes and dislikes for these different cod products. Fish purchase behaviour, attitudes in relation to health and food and demographics were studied in terms of explaining liking of the different cod products. Further, consumers across countries were compared with regard to liking, purchase behaviour and attitudes. The products were evaluated using quantitative descriptive analysis (QDA) by a trained sensory panel, and at the same time consumers in Iceland, Denmark, the Netherlands and Ireland rated acceptability of the

* Corresponding author. Address: Matís ohf (former Icelandic Fisheries Laboratories), Skúlagata 4, 101 Reykjavík, Iceland. Tel.: +354 4225000; fax: +354 4225001. E-mail address: [email protected] (K. Sveinsdóttir). 0950-3293/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2008.09.002

products, followed by answering questions about attitudes and fish consumption. 1.1. Health benefits of seafood The health benefits of seafood consumption are well known and have been verified by the number of research studies that show that consuming fish at least 1–2 times per week has a positive effect on health (De Deckere, Korver, Verschuren, & Katan, 1998; Marckmann & Grønbk, 1999; Thorsdottir, Birgisdottir, Halldorsdottir, & Geirsson, 2004). A recent study showed that increased fish consumption decreased undesirable types of blood fat and increased antioxidation activity. In addition, the fish protein facilitated weight loss in overweight young adults (Thorsdottir et al., in press). Public health organisations in various countries recommend that fish should be consumed at least two times per week (Food Standards Agency, 2007; American Heart Association, 2007; Lydheilsustod, 2007; Sundhedsstyrelsen, 2007). However, in many countries the average fish consumption is considerably less frequent (Honkanen et al., 2005). Furthermore, fish consumption is considerably lower among young adults (Steingrímsdóttir,

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Þorgeirsdóttir, & Ólafsdóttir, 2003; Olsen, 2003; Verbeke & Vackier, 2005). 1.2. Attitudes towards fish It has been shown that young adults have more negative attitudes related to fish (Olsen, 2003; Verbeke & Vackier, 2005), and that attitudes towards fish influence fish consumption (Verbeke, Vermeir, & Brunsø, 2007; Olsen, Scholderer, Brunsø, & Verbeke, 2007; Olsen, 2003). High health and food involvement (Olsen, 2003), and convenience (Olsen et al., 2007), can positively influence fish consumption, while price has been found to be one of the main barriers (Verbeke & Vackier, 2005). As habits have significant influences on fish consumption (Trondsen, Braaten, Lund, & Eggen, 2004; Verbeke & Vackier, 2005), it is important to build a foundation for fish consumption early in life to increase the likelihood of future fish consumers. 1.3. Sensory quality and consumer liking Sensory liking is the strongest determinant for fish consumption intention (Verbeke & Vackier, 2005). Though consumers may have strong opinions, they usually find it difficult to explain in detail why they prefer one product to another, and the results may be difficult to interpret. However, descriptive sensory analysis carried out by trained sensory panels provides accurate and detailed description of the sensory properties of the products under study. The consumer acceptance or preference may then be related to the sensory characteristics of products by preference mapping (Greenhoff & MacFie, 1994; McEwan, 1996). Preference mapping has been used to study acceptability of various food products such as meat (Helgesen, Solheim, & Ns, 1997), beverages (Geel, Kinnear, & de Kock, 2005; Guinard, Uotani, & Schlich, 2001), fruits (Thybo, Kühn, & Martens, 2003; Daillant-Spinnler, MacFie, Beyts, & Hedderley, 1996) and cheese (Westad, Hersleth, & Lea, 2004; Murray & Delahunty, 2000). However, few studies comparing consumer acceptability and sensory properties of different cod products have been published. Sveinsdóttir, Thorkelsdóttir, and Martinsdóttir (2003) studied acceptability of Icelandic consumers and the sensory quality of fresh, thawed and MA-packed cod fillets of different storage time. Consumers preferred thawed and MA-packed fillets to fresh fillets. The thawed and MA-packed fillets were determined to be more dry and tough when compared to fresh fillets, according to a trained sensory panel. In addition, the consumers found differences between fresh and stored cod fillets (stored 2 and 10 days), preferring the more fresh fish. Luten et al. (2002) studied preferences of Dutch consumers and the sensory quality of wild and farmed cod. The farmed cod was slightly more appreciated by consumers. Compared to wild cod, the farmed cod received higher scores for white and dull appearance, cod taste and fibrousnesses, but lower scores for juiciness when evaluated by a trained sensory panel. 1.4. Availability of seafood products Eating quality preference decisions are ultimately made during consumption. Eating quality will vary from one species of seafood to another, and then again due to choice of storage, handling, packaging, transportation, etc., made at each point in the chain from seafood catch, or slaughter, to consumption. Consumers in different countries may have different experiences with seafood, related to traditions, availability and frequency of consumption that will determine individual preferences. However, the composition and availability of seafood products on the market has changed considerably during the last few decades. The world wide production of fresh seafood has increased gradually since 1994, from approximately 30,000,000 T to 50,000,000 T

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per year in 2002, while the production of frozen has remained the same (Vannuccini, 2004). The effects of freezing on quality of fish are well documented. Frozen/thawed cod products are generally characterized by lower eating quality compared to fresh, e.g., due to decreased freshness, drier and tougher texture (Magnússon & Martinsdóttir, 1995; Martinsdóttir & Magnússon, 2001; Sveinsdóttir et al., 2003). In order to meet consumer demands for fresh products, food products packed in modified atmosphere (MA) have increased their market share, with the advantage of extended shelf life. The use of modified atmosphere packaging (MAP) has been found to increase the keeping quality of fish products (e.g., Sivertsvik, Jeksrud, & Rosnes, 2002). However, cod fillets packed in MA have less juicy and tender texture (Sveinsdóttir et al., 2003). In the near future, most of the increase in fish production is expected to come from aquaculture (FAO, 2006a). The capture of cod has decreased gradually between 1970 and 2000, from approximately 3,000,000 T to 1,000,000 T per year. A sharp increase has occurred in production of farmed cod between 2000 and 2003, from 200 T to 2600 T (FAO, 2006b). The changing composition of the market for cod products raises questions about consumer preferences for the different products of cod in relation to different sensory characteristics. In this paper, sensory quality is compared to consumer acceptability of different cod products on the market. The consumers fish purchase behaviour, attitudes in relation to health and food are studied in terms of explaining liking of the different cod products. Further, different consumers segments are identified based on different liking on one hand and across different countries on the other hand. Potential to increase fish consumption based on the results is discussed.

2. Materials and methods 2.1. Cod products The selection of the cod products chosen was based on several criteria, such as high consumption rate in Europe, and availability. Product variety was investigated in the participating countries, and products were found to differ mainly with regard to storage method (fresh, frozen, packed in MA), storage time (short or long) and origin (wild or farmed). This variety represented the products used in the project. Wild and farmed cod (Gadus morhua) was purchased by the Icelandic Fisheries Laboratories (IFL) from several fish processors in Iceland, depending on who could provide acceptable raw material each time. The cod was trimmed, with skin, tail and bones removed (loins) and packed fresh, MAP, or frozen. The samples were then packed in plastic bags with diapers in the bottom and placed in polystyrene boxes (unfrozen products with ice mats) and stored in a cold store. The boxes were transported from IFL by airfreight to other partners involved in the consumer study. The overall transport time was within 24 h, and samples were kept in cold stores before and after airfreight (temperature during transport was below 1 °C). Information about each cod product is shown in Table 1. 2.2. Descriptive sensory evaluation Quantitative Descriptive Analysis (QDAÒ), described by Stone and Sidel (2004), was used to assess cooked samples of cod. An unstructured scale (left end = 0%, increasing intensity to the right end = 100%) was used with a defined sensory attribute vocabulary, describing appearance, odour, flavour, and texture. The vocabulary for the products was previously developed and tested for comparable products.

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Table 1 Detailed sample description of cod samples used in the consumer study Sample name

W-fresh-S W-fresh-L W-MAP-S W-MAP-L W-froz-S W-froz-L F-fresh-S F-fresh-L a b c

Type

Wild Wild Wild Wild Wild Wild Farmed Farmed

Storage Condition

Storage timea

Supplier

0–1 °C 0–1 °C 0–1 °Cb 0–1 °Cb 24 °Cc 24 °Cc 0–1 °C 0–1 °C

3 days 10 days 3 days 10 days 9 days 5 months 3 days 6 days

Solbakki ehf, via Fiskverslun Haflida Bodvarsonar ehf, Iceland Solbakki ehf, via Fiskverslun Haflida Bodvarsonar ehf, Iceland HB-Grandi, Iceland HB-Grandi, Iceland HB-Grandi, Iceland HB-Grandi, Iceland Fish farming Thoroddur, Thorsberg ehf, Iceland Fish farming Thoroddur, Thorsberg ehf, Iceland

Storage time was calculated from day of filleting. From slaughter/catch cod was stored whole in ice, and storage time until filleting was 3 ± 1 days. Samples stored in 500 g packs with modified atmosphere, gas mixture: 50%CO2/6.4% O2/43.6% N2. The frozen cod samples were IQF packed, and thawed over night at 4 °C before analysis the following day.

Nine panellists of the Icelandic Fisheries Laboratories’ sensory panel participated in the QDA of the cooked cod. They were all trained according to international standards (ISO, 1993); including detection and recognition of tastes and odours, training in the use of scales, and in the development and use of descriptors. The members of the panel were familiar with the QDA method, and were experienced in sensory analysis of cod. The panel was trained using different samples of cod (farmed, wild, fresh, thawed, packed in MA) of different freshness categories in three sessions. The vocabulary described appearance, odour, flavour and texture of cod (Table 2), and the panel was trained to describe the intensity of each attribute for a given sample using the unstructured scale. All sample observations were conducted according to international standards (ISO, 1988). Samples weighing 40–50 g were taken

from the loin part of the fillets and placed in aluminium boxes coded with three-digit random numbers. The samples were cooked for 7 min in a pre-warmed oven (Convotherm Elektrogeräte GmbH, Eglfing, Germany) at 95–100 °C with air circulation and steam, and then served to the panel. Each panellist evaluated duplicates of each sample in a random order in four sessions (four samples per session). A computerized system (FIZZ, Version 2.0, 1994–2000, Biosystémes) was used for data recording. The descriptive analysis was carried out the day before the consumer test. 2.3. Consumer tests Altogether 378 consumers completed the test, recruited in four European countries; Iceland (30%), Denmark (28%), the Nether-

Table 2 Sensory attributes (n = 33) evaluated in cod product using an unstructured scale Short name

Sensory attribute

Description of attribute

Odour O-Sweet O-BoilMilk O-BoilPot O-Butter O-Vanilla O-Meat O-FrozSt O-TCloth O-TMA O-Sour O-Sulphur O-Putrid

Sweet Boiled milk Boiled potatoes Butter Vanilla Meaty Frozen storage Table cloth TMA Sour Sulphur Putrid

Sweet odour Boiled milk, fruity/mushy odour Odour of boiled potatoes Butter odour, popcorn Vanilla odour, sawdust, timber Meaty odour, reminds of boiled meat Reminds of odour found in refrigerator and/or freezing compartment Reminds of a table cloth (damp cloth to clean kitchen table, left for 36 h) TMA odour, reminds of dried salted fish, amine Sour odour, spoilage sour, acetic acid Sulphur, matchstick Putrid odour

Appearance A-DarkCol A-DisCol A-WhPrec

Light/dark colour Homogenous/heterogeneous White precipitation

Left end: light, white colour. Right end: dark, yellowish, brownish, grey Left end: homogenous, even colour. Right end: discoloured, heterogeneous, stains White precipitation in the broth or on the fish

Flavour F-Salt F-Sweet F-Metallic F-Sour F-Butter F-Meat F-FrozSt F-Pungent F-TMA F-Putrid

Salt Sweet Metallic Sour taste Butter Meaty Frozen storage Pungent TMA Putrid

Salt taste Sweet flavour Metallic flavour Sour taste, spoilage sour Butter flavour, popcorn Meaty flavour, reminds of boiled meat, meat sour, farmed fish Reminds of food which has soaked in refrigerator/freezing odour Pungent flavour, bitter TMA flavour, reminds of dried salted fish, amine Putrid flavour

Texture T-Flakes T-Soft T-Juicy T-Tender T-Mushy T-Meaty T-Clammy T-Rubber

Flakiness Firm/soft Dry/juicy Tough/tender Mushy Meaty Clammy Rubbery

The fish portion slides into flakes when pressed with the fork Left end: firm. Right end: soft. Evaluate how firm or soft the fish is during the first bite Left end: dry. Right end: Juicy. Evaluated after chewing several times: dry - pulls juice from the mouth Left end: tough. Right end: tender. Evaluated after chewing several times Mushy texture Meaty texture, meaty mouth feel Clammy texture, tannin Rubbery texture, chewing gum

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lands (13%) and Ireland (29%). These countries were chosen based on differences in fish consumption. In addition, as the study included fresh fish, which is a very perishable product, the short distances and direct flight from the airport in Iceland to each location were necessary to insure products of comparable sensory quality, which was extremely important for the study. Consumers were recruited using ads in newspapers, leaflets, and through e-mail lists of workplaces and universities near the institutes where the test was conducted. Consumers who had attended consumer tests before were contacted by telephone to participate. Consumers were selected on the criteria of being 18 years or older, and who consumed fish at least one time per month. The consumer group included 40% males and 60% females. The average age was 44 years; divided over age ranges: 18–29 years (31%), 30– 44 years (19%), 45–59 years (23%) and 60 years or older (27%). Consumers evaluated the eight cod samples during two sessions at research institutes in each of the participating countries, with a time interval of 7 days. Each day of assessment included four to six consumer test sessions, with up to 30 consumers in each session. Each consumer selected a session time beforehand from 10 am to 8 pm and evaluated the samples at the same time each of the test days. Samples weighing 40–50 g were taken from the loin part of the fillets. All samples were prepared and placed in aluminium boxes approximately 2–3 h before being cooked and served to consumers. Uncooked samples in aluminium boxes were stored at 4 °C. The samples were cooked until their core temperature had reached 70 °C, with slightly a different method in each country. However, the differences were kept to a minimum, and the cooking procedure was pre-tested in each country to reach the same core temperature. The samples were cooked using steam or covered with aluminium paper to avoid vaporisation and assure comparable moisture in the samples during cooking. In Iceland, samples were cooked at 95–100 °C for 7 min in a pre-warmed oven (Convotherm Elektrogeräte GmbH, Eglfing, Germany) with air circulation and steam. In Denmark, samples were covered with aluminium paper and cooked for 12 min in a 100 °C pre-warmed oven (Ratinal, Großküchentechnik GmbH, D-86899 Landsberg a. Lach). In Ireland and the Netherlands, au bain marie cooking was used. The boxes were placed on a tray filled with water (100 °C, 1 and 2 cm, respectively) and placed in a pre-heated oven (Hotpoint electric single oven with ‘‘circulaire” fan cooking, model ‘‘Nouvelle 6102”, Indesit Co., Peterborough, UK (Ireland), the Miele H 216 (The Netherlands)) set at 200 °C (actual temperature was 100 °C due to water vapour from bain marie evaporation) and cooked for 7.5 and 12 min, respectively. The samples were served directly from the oven to the consumers. The procedure was repeated with all four samples. Cooking and serving was done according to a balanced serving plan that was designed for all four countries and all sessions. Serving order was randomised between sessions and countries. Consumers in each country completed the same questionnaire translated into their own language. The consumers were asked to answer one question about overall liking on a 9-point hedonic scale: dislike extremely (0), neither like nor dislike (4), like extremely (8). After the final tasting session, an additional questionnaire was handed out. Statements and questions about fish consumption behaviour were selected from an extensive European questionnaire, designed and validated within the Integrated Research Project SEAFOODplus, RTD pillar 2 Project 2.1. CONSUMERSURVEY (http://www.seafoodplus.org). The questionnaire included; (i) statements about food and health attitudes, and fish consumption motives and barriers, measured on a 7-point scale: totally disagree (0), Neither agree nor disagree (3), Totally agree (6); (ii) questions about fish consumption frequency (in general and on cod product level), and questions about purchase frequency and place (mea-

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sured on a 9-point category scale): never (0), less frequently than once every 6 months (1), 1–5 times every 6 months (2), once a month (3), 2–3 times a month (4), once a week (5), two times a week (6), 3–4 times a week (7), daily or almost every day (8); (iii) demographics (gender, age, family size, children, income and education). For data treatment, the 9-point category scales dealing with fish consumption (in general and on cod product level) and fish purchase frequency and place of fish purchase were converted to continues scales according to Honkanen et al. (2005): never = 0.0; less frequently than once every 6 months = 0.05; 1–5 times every 6 months = 0.12; once a month = 0.25; 2–3 times a month = 0.625; once a week = 1.0; two times a week = 2.0; 3–4 times a week = 3.5; daily or almost every day = 6.5 (times per week). 2.4. Data analysis QDA data was corrected for level effects (effects caused by level differences between assessors and replicates) by the method of Thybo and Martens (2000). From a partial least squares regression (PLS) model, the initial variance (signal) at zero PC’s and the residual variance (noise) after optimal PC’s were plotted as a signal to noise (S/N) ratio for each panellist, each sample and each sensory attribute (Martens & Martens, 2000; Thybo & Martens, 2000). Principal component analysis (PCA) on mean level corrected values of different sensory attributes and samples were performed. A hierarchical clustering using Ward’s method was performed with inspection of the dissimilarity plot and dendrogram, which showed that a five cluster solution would be optimal. After having identified the groups, the consumers were segmented by the kmeans clustering method. This method divides consumers into K clusters so that the within-cluster sum of squares is minimized. The chosen number of clusters showed interaction between the clusters with regard to liking, similarity of sensory characteristics liked by consumers within each cluster, and differences in demographics and attitudes between clusters. The results were then viewed with PCA. Secondly, external preference mapping was applied, using PLS. The sensory data was used as the explanatory variables (X-matrix) and the average preference data within each cluster as the response data (Y-matrix). All multivariate analysis was performed using the statistical program UnscramblerÒ (Version 8.0, CAMO, Trondheim, Norway). Analysis of variance (ANOVA) was carried out on QDA data corrected for level effects in the statistical program NCSS 2000 (NCSS, Utah, USA). The program calculates multiple comparisons using Duncan’s multiple comparison test. In addition to the study of liking of each consumer cluster, the differences between clusters in terms of consumer attitudes, fish consumption, purchase behaviour, motives and barriers and demographics were analysed. For categorical data (demographics, gender, age group), the chi-square test was applied, but for consumer line scale data, General Linear Modelling ANOVA and Duncan’s multiple comparison test was used. The data were adjusted for age, by using age as a covariant when testing for country differences. Principal axis analysis with oblimn rotation (Fabrigar, Wegener, MacCallum, & Strahan, 1999) was applied on consumer attitudes towards food and health, and fish consumption motives and barriers. The two criteria used to extract numbers of factors were Eigen value > 1 and scree plots. Five factors were identified (Table 3); (1) problem to prepare fish, (2) health and food involvement, (3) fish is wholesome, (4) insecurity regarding fish purchase and (5) fish liking. Statements about finding it a problem to clean and prepare fish, buying fish only without bones, inability to recognize if fish is fresh and finding the smell of fish unpleasant loaded on problem to prepare fish, implying that consumers scoring high on those

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Table 3 Final factor loadings from principal axis analysis with oblimn rotation; statements about attitudes, motives and barriers for fish consumption Factor (1) Problem to prepare fish It is a problem for me to clean and prepare fish I only buy fish without bones Fish has an unpleasant smell I can not recognize if fish is fresh I appreciate healthy food very much I appreciate food very much Health is very important to me I appreciate cooking very much Eating fish is healthy Eating fish is safe I never know if I make the right choice of fish I feel lost when having to choose fish Fish has a good taste I can say that I actually do not like to eat fish I enjoy a meal with fish more than a meal without fish

0.74 0.60 0.41 0.36 0.01 0.10 0.07 0.15 0.08 0.05 0.06 0.11 0.02 0.03 0.10

(2) Health and food involvement 0.03 0.01 0.11 0.06 0.78 0.73 0.59 0.47 0.13 0.01 0.07 0.06 0.01 0.02 0.08

statements found preparing fish and recognizing fish freshness problematic. Statements about appreciation of healthy food, appreciation of food, health importance and appreciation of cooking loaded on health and food involvement. Statements about that eating fish is safe and eating fish is healthy loaded on fish are wholesome (health beliefs). Statements about feeling lost when having to choose fish and not knowing if the right choice of fish is made loaded on insecurity regarding fish purchase. Statements about fish having a good taste, liking to eat fish, enjoying a meal with fish more than a meal without fish loaded on fish liking. Previously, the following statements were eliminated one at a time during the factor analysis due to low factor loadings: My household members do not like fish, I have easy access to buy fish, I find it easy to prepare delicious and tasty meals with fish, eating fish is expensive, shelf life of fish is too short and I appreciate fish very much. The significance level was set at 5%, if not stated elsewhere.

3. Results and discussion 3.1. Descriptive sensory evaluation of cod products Signal (S) to noise (N) analysis showed that all samples and 24 of the 33 evaluated sensory attributes had a S/N ratio greater than 1 and therefore a good descriptive power (Table 4). The samples W-froz-S (short frozen storage) and W-MAP-S (short storage in modified atmosphere) had a relatively low S/N ratio compared to other samples evaluated. This could be due to a rather neutral sensory description, with neither having a very high nor low intensity of any of the sensory attributes (Table 5). Texture and appearance attributes, such as meaty, tender and soft texture, dark colour and white precipitation had a relatively high S/N ratio. This indicated that the samples were more different with regard to texture and appearance than odour and flavour. Fig. 1 illustrates how the different samples of cod were described by the sensory attributes. The first two principal components (PC1 and PC2) show the main structured information in the data and explain 89% (73% and 16%, respectively) of the sensory variation between the samples. The predominant difference between the samples was due to texture, mainly meaty, tender and soft texture. Differences in appearance, odour and flavour were also apparent, as attributes characteristic for cod at the beginning of storage, such as sweet odour and flavour, and metallic flavour were located in the right and lower corner, and attributes characteristic at the end of shelf life, such as sour and TMA odour and fla-

(3) Fish is wholesome 0.03 0.10 0.13 0.03 0.09 0.01 0.17 0.15 0.64 0.63 0.00 0.05 0.08 0.06 0.01

(4) Insecurity regarding fish purchase 0.08 0.06 0.10 0.15 0.08 0.05 0.13 0.01 0.13 0.10 0.74 0.74 0.09 0.24 0.02

(5) Fish liking 0.11 0.02 0.16 0.10 0.05 0.19 0.04 0.01 0.15 0.05 0.02 0.01 0.65 0.43 0.39

Table 4 Signal to noise (S/N-ratio) for cod products and sensory attributes, evaluated by a trained sensory panel Sample

S/N

Attribute

S/N

Attribute

S/N

W-fresh-L W-fresh-S F-fresh-L F-fresh-S W-froz-L W-froz-S W-MAP-L W-MAP-S

1.19 1.34 1.36 1.34 1.42 1.06 1.23 1.03

O-Sweet O-BoilPotat O-Meat O-FrozSt O-TCloth O-TMA A-Colour A-Discol A-WhPrec F-Salt F-Sweet

1.06 1.10 1.11 1.00 1.09 1.06 1.31 1.11 1.24 1.16 1.06

F-Metallic F-Meat F-TMA T-Flakes T-Soft T-Juicy T-Tender T-Mushy T-Meaty T-Clammy T-Rubber

1.04 1.14 1.05 1.01 1.51 1.21 1.87 1.08 1.97 1.42 1.35

vour, dark colour and discoloured appearance were in the left and upper corner. The sample groups spanned the sensory space quite well. Wfroz-L (extended frozen storage) and W-fresh-L (extended fresh storage) were similar, mainly described with dark colour and discoloration and a hint of storage odour and flavour, such as boiled potato and frozen storage odours, and TMA flavour. However, those samples were not beyond the end of shelf life, as the sensory attributes related to spoilage, such as TMA and sour odours and flavours were below the QDA score 20 (Bonilla, Sveinsdottir, & Martinsdottir, 2007; Magnússon, Sveinsdóttir, Lauzon, Thorkelsdóttir, & Martinsdóttir, 2006). The W-froz-L and W-fresh-L samples were the least described by freshness odours and flavours, such as metallic flavour and sweet flavour and odour. Similarly, the W-froz-S (short frozen storage) and W-MAP-L (extended storage in modified atmosphere), were rather dark and discoloured, with dry, tough and firm texture (opposite to juicy, tender and soft texture), but those samples were less described by storage attributes, such as sour odour and TMA odour and flavour. W-fresh-S (short fresh storage) was the juiciest, soft and tender sample. Though WMAP-S (short storage in modified atmosphere) was located close to W-fresh-S, although it was less described by those texture attributes, and more with sweet flavour. The farmed cod, F-fresh-S (short fresh storage) and F-fresh-L (extended fresh storage) were described by meaty, clammy and rubber texture, meaty odour and flavour. The appearance of the farmed cod was different from the wild cod samples: with a very high degree of white precipitation, the lightest colour and the most even colour (opposite to dark and discoloured appearance).

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K. Sveinsdóttir et al. / Food Quality and Preference 20 (2009) 120–132 Table 5 Average sensory scores for the 8 cod products Attribute Odour Sweet BoilPotat Meat FrozSt TCloth TMA Sour Appearance DarkCol DisCol WhPrec Flavour Salt Sweet Metallic Sour Meat TMA Texture Flakes Soft Juicy Tender Mushy Meaty Clammy Rubber

W-fresh-L ** * ** * ** *** **

*** *** ***

*** **

* *** **

*** *** *** *** *** *** ***

W-fresh-S

F-fresh-L

F-fresh-S

W-froz-L

W-froz-S

W-MAP-L

W-MAP-S

23b 34 9 21 16ab 10ab 9a

29 25 7 7 3ce 1ce 0b

32 24 16a 6 3ce 2ce 5

38a 18b 16a 10 5ce 3ce 2b

22b 36a 3b 17 14bd 7bd 3b

33 32 10 10 6cd 3cd 3b

33 25 11 15 8ac 3cd 2b

30 27 5 8 3ce 1ce 1b

47ab 43a 22cd

34cd 32a 14d

19e 22b 36ab

21e 20b 31bc

47ab 42a 16d

44bc 41a 28

38cd 34a 31bc

31d 35a 19cd

7b 15d 19 11a 6df 15ab

3b 24 27 2 7df cd 5

10b 27 30 8 31a 6

7b 32ab 25 6 28ab cd 5

27a 21cd 15 7 12cef bd 13

7b 19cd 22 4 22ac 6

7b 24 26 7 17bcde 7cd

3b 33bc 29 1b 18 2c

44 60bc 52 60a 39ab 20cd 18b 9d

49 66ab 64ab 66a 41ab 14d 13b 6d

36 40d 50cd 33b 21cd 55a 33a 34ab

44 43d 50 32b 16d 55a 38a 19cd

47 57be 60bc 60a 36bc 13d 14b 5d

44 42d 43d 33b 24 32bc 33a 28bc

40 36d 41d 30b 20cd 45a 40a 28bc

43 54c 61bc 60a 30 23cd 18b 8d

Different letters show significant differences within a line; O = odour; A = appearance; F = flavour; T = texture. * p < 0.05. ** p < 0.01. *** p < 0.001.

3.2. Consumer differences by countries and age The majority of consumers (71%) consumed fish once per week or more often. The average consumption frequency was different between countries (Table 6). Age distribution was different between the countries. In addition, fish consumption behaviour and attitudes were different in different age groups as shown in Table 7. Therefore the results were adjusted for age. The fish consumption was highest among Icelandic consumers (1.8 times per week), but the lowest in Denmark and the Netherlands or c.a. one time per week (Table 6). In 2002, close to 90% of Icelandic consumers consumed fish once per week or more often, however, the consumption has decreased considerably between 1990 and 2002 (Steingrímsdóttir et al., 2003). Our findings indicated a further decrease among Icelandic consumers. The average fish consumption in Denmark and the Netherlands was 1.4 and one times per week (respectively) in 2004 (Honkanen et al., 2005). Research on variability of fish consumption in 10 European countries (Welch et al., 2002) showed that the fish consumption was higher in Denmark compared to the Netherlands, but the present study showed similar fish consumption among the participants in those countries. The Irish participants consumed fish 1.4 times per week on average, but slightly higher when corrected for age. This is in accordance with the fish consumption reported earlier among Irish adults. In 1997–1999, the fish consumption among Irish consumers was 30–40 g per day (Hearty, McCarthy, Kearney, & Gibney, 2007), indicating that the fish consumption frequency was on average 1.2–1.6 times per week, calculated from validated average fish serving size (Einarsdóttir et al., 2007). Fish consumption was considerably lower among the youngest consumers (Table 7) in accordance with other recent studies (Steingrímsdóttir et al., 2003; Verbeke & Vackier, 2005; Olsen, 2003).

Our findings showed that consumption of different cod products was different in the four participating countries (Table 6). Recorded consumption of various cod products indicated that the Danish consumers consumed cod least frequently and the Dutch most frequently. Our findings are in accordance with Welch et al. (2002), who showed that consumption of fat fish species is more characteristic of Denmark, but white fish products are more common in the Netherlands. The Dutch consumers had the highest consumption frequency of fresh cod, nearly two times per month on average. The Dutch and Irish consumers consumed frozen cod three times more often than Icelandic and Danish consumers. Icelandic consumers consumed wild and salted cod more frequently than consumers in the other three countries. Frozen ready to eat meals with cod were more frequently consumed by Irish consumer, however, little less than one time per month on average. Icelandic and Danish consumers claimed they hardly ever consumed farmed cod or frozen ready to eat meals with cod and the Danish did not consume chilled ready to eat meals with cod. Salted cod, and chilled or frozen ready to eat meals with cod, had a very low consumption rate, each product consumed less frequently than one time per month on average. Recorded consumption of wild or farmed cod was very low. This could be due to the consumer’s lack of knowledge about the origin of the cod; only 84% and 79% of the consumers responded to the question about the consumption frequency of wild or farmed cod (respectively), compared to 97% about the fresh cod products. The place of purchase varied considerably between the countries (Table 6). Icelandic and Dutch consumers purchased their fish most frequently from fish mongers, while Danish and Irish consumers purchased their fish most frequently in supermarkets. In addition, the Dutch and Irish consumers purchased their fish more often at markets, which could be explained by very low number of fish markets in Iceland and Denmark.

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a 50

PC2

40 30 20

• W-froz-S • W-MAP-L

• W-fresh-L

• W-froz-L

10 0

F-fresh-L • F-fresh-S •

-10

•W-MAP-S • W-fresh-S

-20 -30 -40

PC1

-50 -40

-50

b 1.0

-30

-20

-10

0

10

20

30

40

50

PC 2

• • •

0.5

• • • •

• F-Sour • O-Sour

• F-Salt

A-DarkCol O-BoilPot A-DisCol 0

O-FrozSt O-TCloth F-TMA O-TMA

• T-Mushy •

T-Flakes

•• T-Tender T-Soft

-0.5

• T-Juic y

T-Rubber • T-Clammy • A-WhPrec • O-Meat • T-Meaty • F-Meat • O-Sweet •

• F-Metallic • F-Sweet

-1.0

PC1 -1.0

-0.5

0

0.5

1.0

Fig. 1. PCA describing sensory quality of the cod products as evaluated by a trained sensory panel. (a) Scores and (b) correlation loadings. PC1 vs PC2 (X-expl.: 73% and 16%). Ellipses mark the 50% and 100% explained variance limits. O = odour; A = appearance; F = flavour; T = texture.

The attitudes, motives and barriers were different between the countries (Table 6) and could explain the higher fish consumption among Icelandic and Irish consumers. The Irish participants scored the highest on the factor health and food involvement, which might have positively influenced their fish consumption (Olsen, 2003). Icelanders were the most convinced that fish is wholesome, were the least insecure regarding fish purchase and had easy access to fish. Easy access to purchase fish might encourage fish consumption as convenience has been found to have a positive correlation with fish consumption frequency (Olsen et al., 2007). Icelandic consumers did not find fish expensive, opposite to Danish and Dutch consumers, but price has been found to be one of the main barriers for fish consumption (Verbeke & Vackier, 2005) and this could partly explain the differences in fish consumption between the countries. However, the consumers perception of fish price was not in accordance with the relative price level in the four countries (Statistics Iceland, 2007). Statistical information showed that fish was cheap in Denmark and the Netherlands compared to Iceland. However, compared to the other countries, fish in Iceland was relatively cheaper in comparison to other food.

Young consumers in the age group 18–29 years were considerably less health and food involved in comparison to other age groups, especially 60 years and older (Table 7). In addition the younger consumers were more insecure regarding fish purchase, found fish preparation problematic and scored low on the fish liking factor. Verbeke and Vackier (2005) showed that younger consumers had more negative attitudes related to bones in fish, which was included in the factor of problem to prepare fish. The young participants in Verbeke and Vackier (2005) bought their own food less frequently than the older, indicating that the young consumers lacked experience, resulting in their insecurity towards fish purchase. In addition, according to Olsen (2003), young consumers are less health involved, and scored lower on perceived convenience related to lack of time for seafood meal preparation. Liking differences were observed between countries (Table 8). Overall, Icelandic and Irish consumers had higher liking for the cod products. However, Irish consumers liked cod after extended frozen storage (5 months at 24 °C), while Icelandic and Dutch consumers liked cod after short frozen storage (9 days at 24 °C). These differences might be explained by different fish consumption patterns within the countries. The cod after extended frozen storage was more characterized by frozen storage sensory characteristics. The Irish participants consumed frozen cod products more frequently and purchased their fish more frequently at supermarkets. In addition, Irish consumers have a tradition of consuming much more frozen fish compared to fresh fish (National Statistics, 2001). The Icelandic consumers generally liked cod products after short storage (frozen (9 days at 24 °C), fresh and stored in modified atmosphere (3 days at 0–1 °C)) more than consumers in the other countries. There are clear differences in liking between countries that appear to be related to availability and familiarity. The easier access, high frequency of purchase in fishmonger shops and tradition of high fish consumption could indicate that Icelandic consumers were more familiar with and thereby have higher liking of the sensory attributes characterising very fresh cod. Between country differences have been demonstrated for various other food products, such as coffee (Heidema & de Jong, 1997), chocolate (Januszewska & Viaene, 2001) and meat (Prescott, Young, & O’Neill, 2001). Bryhni et al. (2002) demonstrated that consumers from countries with high pork consumption were more positive towards pork quality when compared with consumers in countries with lower pork consumption. This supports the higher liking of the cod products by Icelandic and Irish consumers, considering their higher fish consumption. Further, Sañudo et al. (2007) showed higher liking of lamb meat among consumers in countries with high traditional lamb meat consumption, and association between country and liking of different lamb types, presumably due to different culinary backgrounds. Séménou, Courcoux, Cardinal, Nicod, and Ouisse (2007) were able to show to some degree a link between the preferences of consumers from different countries and sensory characteristics of smoked salmon within their country. This indicates that the tradition of fresh fish in Iceland, but frozen in Ireland might explain the different preferences within the two countries. It is clear that consumers like the products they have as most available and are therefore the most familiar with. 3.3. Consumer cluster analysis and internal preference mapping PCA of the consumer preferences for the eight different cod products (Fig. 2) showed that 57% of the variance was explained by the first three principal components (PC). PC 1 separated consumers with low preferences from consumers with high preferences. PC 2 seemed to separate consumers who preferred farmed cod from consumers who had higher preferences for wild cod products after an extended storage period (Fig. 2a). PC 3 appeared to separate consumers with high preference for wild cod products

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Table 6 Country differences; average age, age groups (n), gender (n), fish consumption and purchase (frequency per week), attitudes, motives and barriers (average factor loadings) and average scores for fish is expensive and easy access Country

IS

DK

IR

NL

Total

n Age

112 41c

107 51b

109 35d

50 58a

378 375

36 30 28 18

22 14 26 45

58 22 16 13

1 6 16 27

117 72 86 103

40 72

48 59

39 70

26 24

153 225

1.8a 1.8a 0.2b 0.2 0.3a 0.0b 0.2a 0.1 0.0b

1.3b 1.1b 0.1b 0.1b 0.1b 0.0b 0.0c 0.0 0.0b

1.4b 1.5a 0.3a 0.3a 0.1b 0.1a 0.1b 0.1 0.2a

1.3b 1.0b 0.3a 0.3a 0.1 0.1a 0.0c 0.1 0.1a

378 378 365 350 319 298 346 359 356

0.7a 0.5a 0.1b

0.2b 0.6a 0.1b

0.4b 0.8a 0.4a

0.6a 0.3b 0.3a

354 359 324

0.1bc 0.2b 0.1bc 0.1 0.4a 3.3d 5.4a

0.3cd 0.2a 0.0ab 0.1 0.6c 4.2ac 4.7b

0.3a 0.0 0.2a 0.0 0.2a 3.6cd 4.8b

0.1ab 0.0 0.3cd 0.1 0.1b 4.2ab 5.0

341 341 341 341 341 368 366

***

Age group 18–29 years 30–44 years 45–59 years 60 years or older

***

Gender Male Female

ns

Consumption frequency per week Fish as main course (crude)A Fish as main course Fresh cod Frozen cod Wild cod Farmed cod Salted cod Chilled ready to eat meals with cod Frozen ready to eat meals with cod

** *** *** ** ** *** *** * ***

Purchase frequency per week Fish monger Retailer/supermarket Market

*** ** ***

Attitudes, motives/barriers Health and food involvement Insecurity regarding fish purchase Fish liking Problem to prepare fish Fish is wholesome Fish is expensive Easy access

*** * **

ns *** ** **

IS = Iceland, DK = Denmark, IR = Ireland, NL = The Netherlands. Values with different letters within a line are significantly different. ns = not significant. A Crude mean not corrected for age. * p < 0.05. ** p < 0.01. *** p < 0.001.

Table 7 Age group differences; fish consumption (frequency per week), attitudes, motives and barriers (average factor loadings) and average scores for fish is expensive and easy access Age groups (years) Consumption frequency per week Fish as main course Attitudes, motives/barriers Health and food involvement Insecurity regarding fish purchase Fish liking Problem to prepare fish Fish is wholesome Fish is expensive Easy access

18–29

30–44

45–59

***

1.1b

1.4

1.6a

1.7a

***

0.2cd 0.3a 0.2b 0.3a 0.1 3.7 4.9

0.1bc 0.1b 0.1b 0.0b 0.1 3.7 4.8

0.1ab -0.1b 0.2a 0.1b 0.1 3.7 5.3

0.3a 0.3b 0.2a 0.3c 0.1 4.0 4.8

*** *** ***

ns ns ns

60+

Values with different letters within a line are significantly different. ns = not significant. *** p < 0.001.

of short storage time from consumers with preferences for farmed cod and cod products of extended storage time (Fig. 2b). Although consumers liking differed somewhat between countries, segments of consumers with even greater liking differences may be found within each country that are comparable to segments found in other countries. The use of this approach may pro-

vide important information for marketing of seafood and for authorities intending to increase fish consumption. Consumers were segmented by hierarchical clustering, followed by the kmeans clustering method to analyse if groups of consumers with similar preferences existed. The cluster analysis of the hedonic data identified five distinct groups of consumers, presented in Fig. 2. Cluster 1 (K1) appeared to have high preferences for farmed cod products, while cluster 4 (K4) had low preferences for farmed cod but preferred wild cod after extended fresh storage (W-freshL). Cluster 5 (K5) had high preferences, while cluster 3 (K3) had low preferences in general (Fig. 2a). The third component (Fig. 2b) showed that cluster 2 (K2) had high preferences for wild cod products after short storage. Overall, frozen cod products, either after long or short frozen storage were most preferred, whereas fresh cod after long storage was least preferred (Table 9). On average, none of the eight cod products had very high or low acceptability. The differences in liking were more prominent between the clusters identified by the kmeans clustering method (Table 9). Between clusters, consumers differed with regard to age, attitudes, motives and barriers (Table 10). Marginal significance (p = 0.05–0.10) was observed for test location/country and consumption frequency of wild cod. K1 represented 23% of the consumers with high preferences for farmed cod products, but low for wild cod products after short and extended storage, and extended storage in MAP. Relatively many Danish and Icelandic consumers were within this cluster, and

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Table 8 By country consumer liking of the eight cod products (0 = Dislike extremely; 4 = neither like nor dislike; 8 = like extremely) Country

n

Average

W-fresh-L

**

IS DK IR NL

112 107 109 50

W-fresh-S

ns 4.8 4.3 5.0 4.5

5.3ac 4.9d 5.3ab 4.9cd

ns 5.1 4.9 5.5 5.4

F-fresh-L

F-fresh-S

W-froz-L

W-froz-S

W-MAP-L

ns 4.9 4.9 5.0 4.3

*

*

**

**

W-MAP-S *

5.4a 5.0 5.3a 4.4b

5.3b 5.1b 6.0a 4.8b

5.7ab 5.1cd 5.0d 5.7ac

5.5a 4.5b 5.2a 5.0

5.6a 4.9b 5.3 5.3

IS = Iceland, DK = Denmark, IR = Ireland, NL = The Netherlands. Values with different letters within a column are significantly different. ns = not significant. * p < 0.05. ** p < 0.01.

a 1.0

PC2 4

• W-fresh-L

4

4 4 44 4 4 4 4 4 44 4 4 4 4 4 4 44 44 2 34 2 2 4 5 5 3 44 4 4 4 44 4 5 33 22 33 5 4 44 33 2 4 4 2 4 5 4 44 55 5 4 4 2 5 3 2 44 5 5 55 55 5 5 44 4 2 2 4 2 4 2 3 4 55 5 55 4 4 4 3 4 5 5 5 5 3 55 4 22 4 4 4 55 5 5 5 3 2 44444 2 44 44442 2 2 2 5 5 5 5 55 55 5 2 2 3 4 3 34 425 5 55 5 5 555 555 5 5 55 4 4 22424422 14255 2 5 2 55 5 5 5 4 3 5 41 2 5 55 5 5 5 5 1 1 15 5 5 3 55 5 5 12 111121 1 3 3 31 1 1 1 1 1 125 5 5 552 5 3 5 5 5 1 5 2 12 1 1 5 5 55 5 5 1 5 5555 2 1 12 2121 1 2 255 3 3 1 5 1 15 3 3 5 5 5 3 3 3 33 1 1 11 1 1121 1 3 5 3 112 5 1 2 1 1 2 5 55 5 3 11 2121 11 11 1 1 1 3 1 111 1 1 1 5 1111 11 1 12 1 1 1 11 1 1 1 1 1 1

• W-MAP-L • W-fresh-S

0.5

3

0

• W-froz-L

• W-froz-S

• W-MAP-S

-0.5

-1.0

1

-1.0

b 1.0

-0.5

0

PC3

• F-fresh-S • F-fresh-L

PC1

0.5

1.0

• W-froz-L 1 4

4 4

4 4

5

1 1 1 3 4 11 41 4 1 33 41 1 1 1 4 4 4 3 1 4 55 43 1 5 3 4 14 1 4 14 1 5 5 1 34 41 5 545 555 111 4 444 11414141 4 4 1 3 5 5 344 1444414144111 44 4 1 5 5 3 55 5555 5 55555 1 4 4 5 1 3 4 1 33 1 1 41 5 555 55 4 4141 11 55 3 4 1 3 55 5 1 1144 14 55555 1 1 1 4544515555 5 5 5 5 5 5 4 4111 4 41 4112 1 5 5 55 5 4 5 12 2 5 5 5555555555 41 5 5 5 141 41 5 5 5 3 1 44 4 1 4 1 211 22 25 54 5 55 55 5 5 5 5 1 41 34 55 5 3 4 1 1 1 1142 2 2 22 225 55 55 3 5 5 4 12 51 5 3 3 2 5 5 4 4 4 3 1 222 2 2 5 5 5 5 2 3 2 1 1 2 1 2 25 2 5 5 5 332 2 3 3 3 2 55 3 22 2 2 21 2 2 2 2 3 2 3 2 2 3 2 2 2 2 22 3 3

0.5

• F-fresh-L

3

0

• W-fresh-L

•F-fresh-S • W-MAP-L

-0.5

•

••

W-froz-S W-fresh-S W-MAP-S

2 2

-1.0

22 2

-1.0

0.5

0

PC1 0.5

1.0

Fig. 2. Internal preference map of consumer preference scores. Scores (consumers) and loadings (cod products). (a) PC1 vs PC2 (X-expl.: 28% and 16%) (b) PC1 vs PC3 (X-expl.: 28% and 13%). The five numbers represent the consumers in the five different clusters.

many 18–29 and 45–59 years. A second cluster, K2 included 14% of the consumers. They had very high preference for wild cod after short storage (W-fresh-S (3 days at 0–1 °C), W-froz-S (9 days at 24 °C) and W-MAP-S (3 days at 0–1 °C)), but low for cod after extended storage (W-fresh-L (10 days at 0–1 °C), F-fresh-L (6 days at 0–1 °C) and W-froz-L (5 months at 24 °C)). Relatively many Icelandic and Dutch consumers were within this cluster, but few Danish. The highest proportion of people in the 45–59 years range was

within this cluster. More consumers within this cluster claimed they consumed wild cod two times per month or more often. In addition, they were more convinced that eating fish was healthy and safe, were the least insecure regarding fish purchase and had easier access to buy fish. The third cluster, K3 included 10% of the consumers, who generally had very low preferences for cod, but preferred W-MAP-S to other products. The highest proportion of Danish consumers were within this cluster, but lowest of Icelandic and Irish. A relatively high proportion of 18–29 and 30–44 years were within K3. Consumers within K3 consumed wild cod less frequently when compared to consumers within other clusters. In addition they did not think that fish was wholesome and did not have easy access to buy fish. K3 scored very low on the attitude factor ‘‘fish liking”. The fourth cluster, K4, included 22% of the consumers and had in general low preferences for cod, especially farmed cod and MAP after short storage. Their highest preference was for wild cod after extended frozen storage. This cluster had a relatively high proportion of Irish consumers, and people 18–29 and 30–44 years, but the lowest of people 60 years or older. The high proportion of young people in this cluster might be due to the relatively low average age of the Irish participants. The fifth cluster, K5, included 32% of the consumers, who had high preferences for all the cod products indiscriminately. This cluster included a high proportion of Irish consumers and people 60 years and older. The consumers within K5 thought that fish was healthy and had easy access to buy fish. In addition, they scored high on the attitude factor dealing with fish liking. To some degree, the factor fish liking (Table 10) was reflected in the liking scores of the different clusters (Table 9). The average liking of the cod products was generally high within K5, as was the score on the fish liking factor, but both the cod liking and the factor score were low within K3. In this case, age differences between the two clusters may be an important determinant for these liking differences as the different age groups scored very differently on the factor fish liking (Table 7). However, it is not age alone or the factor fish liking factor explaining the liking differences between the clusters. The age distribution is very similar within K3 and K4, though the consumers within these clusters clearly have different preferences for the cod products. The factor scores on fish liking were not different between clusters K1, K2 and K4 but these clusters had very different preferences for the cod products. The differences between the clusters with regard to the fish consumption motives; fish is wholesome and easy access was not caused by the age differences as these factors did not differ between age groups. There will always be consumers who rate all products equally acceptable, regardless of sensory differences, those who would have responded to other sensory differences or those who are for other reasons unable to complete the task of rating their acceptance of products (Greenhoff & MacFie, 1994). In the present study, most of the people who did not discriminate between products, rated all products high, and were found within K5.

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K. Sveinsdóttir et al. / Food Quality and Preference 20 (2009) 120–132 Table 9 By cluster consumer liking of the eight cod products (0 = Dislike extremely; 4 = Neither like nor dislike; 8 = Like extremely) Cluster All K1 K2 K3 K4 K5

n 378 86 53 36 82 121

W-fresh-L *** *** *** *** ***

ms

W-fresh-S

g

bc

4.7 3.4c 3.7f 2.8b 5.3b 6.1

5.2 3.8c 6.8a 3.0b 5.2b 6.2

F-fresh-L f

4.8 6.1a 4.0f 2.7b 3.5d 6.0

F-fresh-S d

W-froz-L

W-froz-S

a

5.1 6.0a 4.9de 3.0b 3.5d 6.3

a

5.4 5.2b 3.6f 3.2b 5.9a 6.5

5.3 5.3b 6.0bc 3.3b 4.3c 6.3

W-MAP-L de

5.1 3.9c 5.4cd 2.8b 5.2b 6.3

W-MAP-S 5.3ab 4.9b 6.5ab 4.6a 3.8d 6.2

K1 to K5 are the 5 clusters segmented by k-means clustering. Values with different letters within a line are significantly different. ms = marginal significance (p = 0.05–0.10). *** p < 0.001.

Table 10 Cluster differences; average age, age groups (n), gender (n), country (n), fish consumption and purchase (frequency per week), attitudes, motives and barriers (average factor loadings) and average scores for fish is expensive and easy access Cluster

K1

K2

K3

K4

K5

n Age

86 43

53 44

36 41

82 40

121 48

30 12 26 18

15 11 15 12

12 10 6 8

28 23 16 15

32 16 23 50

33 53

21 32

17 19

26 56

56 65

28 28 21 9

20 12 9 12

8 15 7 6

22 23 28 9

34 29 44 14

ns ns ns ms ns ns ns ns

1.3 0.2 0.2 0.2 0.1 0.1 0.1 0.1

1.5 0.3 0.2 0.3a 0.0 0.1 0.1 0.1

1.3 0.2 0.1 0.1b 0.0 0.0 0.1 0.1

1.4 0.2 0.2 0.2 0.1 0.0 0.1 0.1

1.6 0.2 0.2 0.1 0.0 0.1 0.1 0.1

ns ns ns

0.4 0.5 0.2

0.6 0.6 0.2

0.5 0.5 0.2

0.5 0.6 0.2

0.5 0.7 0.2

ns ms

0.0 0.2 0.1 0.1 0.0a 3.8 5.0

0.1 0.2 0.0 0.0 0.2a 3.9 5.3a

0.0 0.0 0.3b 0.0 0.4b 4.3 4.6b

0.2 0.1 0.0 0.0 0.1a 3.8 4.7

0.1 0.1 0.2a 0.1 0.1a 3.5 5.0

*

Age group 18–29 years (n = 117) 30–44 years (n = 72) 45–59 years (n = 86) 60 years or older (n = 103)

**

Gender Male (n = 153) Female (n = 225)

ns

Country Iceland (n = 112) Denmark (n = 107) Ireland (n = 109) The Netherlands (n = 50)

ms

Consumption frequency per week Fish as main course Fresh cod Frozen cod Wild cod Farmed cod Salted cod Chilled ready to eat meals with cod Frozen ready to eat meals with cod Purchase frequency per week Fish monger Retailer/supermarket Market Attitudes, motives/barriers Health and food involvement Insecurity regarding fish purchase Fish liking Problem to prepare fish Fish is wholesome Fish is expensive Easy access

*

ns ns ms

K1 to K5 are the 5 clusters segmented by k-means clustering. Values with different letters within a line are significantly different. ns = not significant. ms = marginal significance (p = 0.05–0.10). * p < 0.05. ** p < 0.01.

3.4. External preference mapping An overall view of the consumer preferences in relation to sensory characteristics was obtained by external preference mapping, using the average preference scores of each cluster (Fig. 3). The main position of preferences of the 5 clusters is distinct in Fig. 3, and the first two PC’s explained 67% of the liking variation and 88% of the sensory variation. The farmed cod particularly appealed to consumers in K1, which could be explained by its meaty texture, flavour and odour, and light colour. The consumers within

this cluster could be considered as ‘‘farmed cod lovers”. K2 and K3 appeared to be positively influenced by similar sensory characteristics, such as sweet and metallic flavour, and the absence of sensory attributes present in cod products after extended storage time, such as table cloth odour, TMA odour and flavour. However, those clusters were quite different with regard to liking scores. K2 discriminated much more between the products, with clear dislikes for products with extended storage and high preferences for products of short storage time. K2 could therefore be considered as ‘‘freshness lovers”. K3 scored all products low, with the excep-

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1.0

K. Sveinsdóttir et al. / Food Quality and Preference 20 (2009) 120–132

PC2

• K2

• F-Metallic • F-Sweet 0.5

0

-0.5

•T-Juicy

• K3

• O-Sweet • F-Meat •T-Meaty O-Meat •• K1 •T-Clammy • T-Rubber • A-WhPrec

• T-Tender • T-Soft •T-Flakes • T-Mushy

• K5

-1.0

-1.0

-0.5

• K4

A-Discol • A-Colour • • o-BoilPotat • F-Salt • O-FrozSt • O-TCloth • O-TMA • F-TMA

0

0.5

PC1 1.0

Fig. 3. External preference mapping. PLS with X as the sensory data and mean preference scores of each cluster as Y. Correlation loadings in X and Y. PC 1 and PC2 explain 74% and 14% of the variation in X and 34% and 33% of the variation in Y. Ellipses mark the 50% and 100% explained variance limits. K1 to K5 are the five clusters segmented by k-means clustering.

tion of frozen cod after short storage which had rather neutral sensory characteristics. K3 might be considered as ‘‘negative consumers”. Attributes characteristic for cod products approaching the end of their shelf life could be considered very repellent for both K2 and K3. Consumers within K4 had high preferences for products after extended storage, which could be accredited to attributes such as dark colour, frozen storage, table cloth and TMA odour. These sensory attributes are more characteristic for cod products after extended storage time. On the contrary, attributes characteristic for very fresh and farmed cod appeared not to appeal to K4. This cluster could be considered as ‘‘storage lovers”. K5 has some trend towards storage attributes as K4. However, considering the high and similar scores given within K5, it could as well be assumed that all the products evaluated within the present study would by appreciated by this cluster. Therefore, this cluster could be considered as the ‘‘positive consumers”. 3.5. Potential to increase fish consumption It has been shown possible to affect people’s consumption and lifestyles. Efforts to increase fish consumption of a whole population have resulted in some success. Increased emphasis on fish consumption in dietary recommendations in the United States, resulted in increased the consumption by about 15% in 5 years thereafter (Simopoulos, 1991). However, it may be more effective to approach different groups of people using means adjusted to each group (Buttriss et al., 2004). An intervention study targeted at adolescents (13–18 years) showed very positive results in improving knowledge and positive lifestyle changes, and the results were more positive using computer-based education compared to traditional education via lectures and pamphlets (Casazza & Ciccazzo, 2007). Younger children (8–12 years) increased their fruit, juice and vegetable consumption after participation in an intervention using multimedia game with the theme fun with consumption (Baranowski et al., 2003). In-store based intervention using computer tailored nutrition information influenced adults to improve their eating behaviours (Anderson, Winett, Wojcik, Winett, & Bowden, 2001). Increased access has proven to increase fruit and vegetable consumption in work place canteens (Lassen, Thorsen, Ellen, Mette, & Ovesen, 2004).

The young consumers and in general the Danish consumers in this study had in common low fish consumption, low health and food involvement and more negative attitudes towards fish. The sensory characteristics of farmed cod in particular appealed to them, and in addition they constituted a rather large proportion of the ‘‘negative” cluster that preferred cod with neutral sensory characteristics. Verbeke and Vackier (2005) concluded that sensory liking is the strongest determinant for fish consumption intention. Therefore, these consumers might be appealed to by emphasising the different sensory characteristics of farmed cod products or the less characteristic sensory attributes of products such as after short frozen storage time. However, the negative attitudes need to be overcome towards increased fish consumption. Trondsen et al. (2004) suggested that promotion and information related to health effects of seafood should increase fish consumption. New information on weight loss related to fish consumption (Thorsdottir et al., in press) might also be emphasised in this relation, as most consumers already believe that fish is healthy. However, not only health effects should be emphasised, but also safety of seafood. This might be particularly important in the case of the negative consumers, as they scored low on wholesomeness of fish. Further, nutritional and origin/catching ground information should be included on the packaging especially targeted at the negative consumers. Easier access and more availability of seafood could contribute to increased fish consumption of this cluster, for example in canteens and restaurants. Ways to prepare fish, and how to evaluate fish freshness could be promoted at the same time, as this appeared to be one of the main barriers of fish consumption for younger consumers. This could include emphasises on how easy fish meal preparation can be, recipes on seafood packaging, or web links to easy but appetizing recipes with additional information on how to recognize fresh fish and easy to prepare meals. Irish consumers constituted a relatively high proportion of ‘‘storage lovers” and ‘‘positive consumers”, and cod products with a hint of storage odours and flavours appealed to them in particular, presumably based on tradition for consumption of frozen fish. Therefore, availability and familiarity appear to play an important role in consumer attitudes and preferences for fish products. This is important when looking into ways to increase fish consumption. By far the highest proportion of consumers 60 years or older had high liking for all the products, regardless of sensory differences. The fact that sense of odour and taste decreases with age (Mojet, 2004) may have affected the preferences of this cluster. However, this age group had by far the most positive attitudes, including fish liking. Icelandic and Dutch consumers and the age group 45–59 had in particular high liking of the freshness sensory characteristics. It appeared that with easier access to buy fish, consumers became more critical toward freshness, and assuring freshness of the fish is very important for this group of consumers. Marketing possibilities or ways to increase the fish consumption of fish lovers might consist in emphasising appetizing pictures, recipes, good flavour or appetizing descriptions of freshness characteristics of the seafood, or new or untraditional fish species.

4. Conclusions Sensory evaluation showed that cod products present in the market differed significantly with regard to different sensory attributes. The consumers in Iceland, Denmark, Ireland and The Netherlands differed considerably with regard to average fish consumption, consumption of different types of cod products and fish purchase habits. In addition, they had different attitudes that could be related to their fish consumption and the different liking of the cod products between countries. However, liking of cod products was different within the countries, and clustering consumers by

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the k-means clustering method, taking into account similarity of scores within each cluster, resulted in five separate clusters, which were different with regard to preferences. Each cluster was constituted with consumers from all four countries. However, the clusters were different with regard to demographic factors, in addition to consumption frequency and attitudes. The clusters could be described as ‘‘farmed cod lovers”, ‘‘freshness lovers”, ‘‘negative consumers”, ‘‘storage lovers” and ‘‘positive consumers”, depending on different liking of the products within clusters. Considering the profile of the consumers in this study, it is worth deliberation upon what comes first: easy access to buy high quality (fresh) fish, the ability to differentiate fish of different freshness quality, positive attitudes towards fish, or higher preferences of fish in general. Availability of products is clearly very important. This is highly relevant for seafood and can be seen in the fish liking and in the frequency of consumption. This is an important point regarding the promotion of seafood consumption, both for seafood industry, and for public health benefit. Despite the increase in production of fresh, but not frozen fish products (Vannuccini, 2004), the overall highest preference within this study were for frozen cod products of both short and extended storage time. This indicates that there are good marketing possibilities for frozen cod products, presented as frozen/thawed. In addition, production of frozen fish products is expected to increase in near future (Agriculture and Agri-Food Canada, 2005). Acknowledgements This work was performed within the Integrated Research Project SEAFOODplus, Contract No. FOOD-CT-2004-506359. The financing of the work by the European Union is gratefully acknowledged. The authors would like to thank Saskia Van Ruth and Stephane Fayoux for their contribution, Gunnþórunn Einarsdóttir and Ása Þorkelsdóttir for their extensive assistance during the consumer study, Fanney Þórsdóttir for advice on statistical analysis, the sensory panel at the Icelandic Fisheries Laboratories and the consumers for their participation. References Agriculture and Agri-Food Canada (2005). Fish and seafood sector profile, The Netherlands, March 2003. Canadian Embassy in the Hague, Netherlands. Accessed 28.03.2007. American Heart Association (2007). Accessed 19.03.2007. Anderson, E. S., Winett, R. A., Wojcik, J. R., Winett, S. G., & Bowden, T. (2001). A computerized social cognitive intervention for nutrition behavior: Direct and mediated effects on fat, fiber, fruits, and vegetables, self-efficacy, and outcome expectations among food shoppers. Annals of Behavioral Medicine, 23(2), 88–100. Baranowski, T., Baranowski, J., Cullen, K. W., Marsh, T., Islam, N., Zakeri, I., et al. (2003). Squire’s quest!: Dietary outcome evaluation of a multimedia game. American Journal of Preventive Medicine, 24(1), 52–61. Bonilla, A. C., Sveinsdottir, K., & Martinsdottir, E. (2007). Development of quality index method (QIM) scheme for fresh cod (Gadus morhua) fillets and application in shelf life study. Food Control, 18(4), 352–358. Bryhni, E. A., Byrne, D. V., Rødbotten, M., Claudi-Magnussen, C., Agerhem, H., Johansson, M., et al. (2002). Consumer perceptions of pork in Denmark, Norway and Sweden. Food Quality and Preference, 13, 257–266. Buttriss, J., Stanner, S., McKevith, B., Nugent, A. P., Kelly, C., Phillips, F., et al. (2004). British Nutrition Foundation Nutrition Bulletin, 29, 333–343. Casazza, K., & Ciccazzo, M. (2007). The method of delivery of nutrition and physical activity information may play a role in eliciting behavior changes in adolescents. Eating Behaviors, 8, 73–82. Daillant-Spinnler, B., MacFie, H. J. H., Beyts, P. K., & Hedderley, D. (1996). Relationships between perceived sensory properties and major preference directions of 12 varieties of apples from the Southern Hemisphere. Food Quality and Preference, 7(2), 113–126. De Deckere, E. A. M., Korver, O., Verschuren, P. M., & Katan, M. B. (1998). Health aspects of fish and n 3 polyunsaturated fatty acids from plant and marine origin. European Journal of Clinical Nutrition, 52, 749–753. Einarsdóttir, G., Sveinsdóttir, K., Martinsdóttir, E., Jónsson, F. H., Þórsdóttir, I., & Þórsdóttir, F. (2007) Viłhorf og fiskneysla ungs folks á aldrinum 18 til 25 ára –

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