In Search of the Ideal Pear (pyrus spp.): Results of a Multidisciplinary Exploration S.R. JAEGER, C.M. LUND, K. LAU, AND F.R.

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1 JFS: In Search of the Ideal Pear (pyrus spp.): Results of a Multidisciplinary Exploration S.R. JAEGER, C.M. LUND, K. LAU, AND F.R. HARKER ABSTRACT: Preference mapping with 10 pears identified 3 segments among New Zealand consumers. While 1 segment preferred ripe European cultivars, another rejected only the seedling with strong off-flavors. A 3rd segment combined the 2 former segments, but also rejected 2 hybrid samples. Survey responses to the question To me, the ideal pear is... from a 2nd consumer sample confirmed the general preference for juicy and sweet pears, the key characteristics of ripeness. A separate appearance evaluation revealed 4 segments based on color and shape. Combining information from several sources resulted in suggestions for new breeding directions for pears, while highlighting the importance of appearance and the need for more extensive measurements. Keywords: preference mapping, sensory profiling, consumer acceptability, product innovation Introduction RECENTLY, THE FRUIT INDUSTRY HAS BEGUN A TRANSFORMATION similar to that previously experienced in the manufactured foods sector. Dictated by the growing competitiveness of the marketplace, this has resulted in vertical integration of supply chains and branding initiatives and a stronger focus on the needs and wants of end-consumers. In particular, the multiple retailers have placed greater pressure on breeders and growers to continuously develop new cultivars that meet the evolving needs of the marketplace (McKenna and others 1998; Weil 1998; Jaeger 2003). To do so successfully, fruit industries are turning increasingly towards the tools used by R&D and marketing personnel in the manufactured foods sector. Preference mapping is one is these techniques. The term preference mapping (Carroll 1972) refers to a group of statistical techniques aimed at the analysis of preference data by taking account of individual differences in consumers perception of preference. The literature contains many examples of applications with products as different as potato crisps (Schlich and McEwan 1992; Schlich 1995), low sugar beverages (Pastor and others 1996), lamb sausages (Helgesen and others 1997), salad dressings (Yackinous and others 1999), and apples (Daillant- Spinnler and others 1996; Jaeger and others 1998). From the early days of preference mapping, a distinction between internal and external analysis has been made. Internal preference mapping (Greenhoff and MacFie 1994) refers to the analysis of preference data only and provides a summary of the main preference directions and the associated consumer segments. Information about the sensory properties driving preference can be obtained by projecting sensory attributes onto the sample map spanned by the key internal preference dimensions (MacFie and Hedderley 1993). In comparison, external analysis refers to the analysis where differences between products found in external data (typically sensory profiles) are used as a basis for interpreting consumer preferences. While the 2 types of preference mapping make use of the same information sources, their philosophical basis differs. When, as in the present research, the aim of a study is to uncover directions for consumer-driven new product development (NPD), we believe it is more appropriate to use the preference data as the basis of the analysis. While the authors work with kiwifruit (Jaeger and others 2003) demonstrated the usefulness of preference mapping in directing fresh fruit NPD, scope for improvements exist. One area pertains to the lack of using objective measures of fruit quality (for example, ph, Brix, flesh firmness, titratable acids, and so on) as an additional source of external data. Given the importance of these measurements in horticultural NPD, including such measures in preference mapping applications is one way of incorporating information that is immediately meaningful and highly relevant to horticultural scientists. In terms of guiding NPD, the key benefit of preference mapping is the ability to uncover the sensory attributes driving preference. With fresh fruit, however, it is not uncommon that the sensory profiles include only internal appearance, odor, flavor, and texture attributes (Morel and others 1999; Zerbini and others 1999; Andani and others 2001; Kuhn and Thybo 2001). Only sometimes is information related to external appearance such as skin smoothness, skin and flesh color, fruit size and shape included. Probably, the difficulty in developing standardized references for such attributes is a contributing factor. Yet, in the supermarket, at the point-of-purchase, a consumer is likely to use appearance to inform his or her choice. Unless a cultivar is purchased with which the consumer has previous experience, appearance, together with aroma and tactile cues, are the only sensory attributes available upon which to form a decision. The steps taken by the fruit industry to ensure that fruit in retail outlets are of standardized appearance is one indication of the importance of appearance. The aim of the study was 2-fold: (1) improving the usefulness of preference mapping to guide fruit NPD; (2) identifying directions for future breeding programs by uncovering desirable and undesirable features of pears. To achieve this, information from several sources was collected and brought together. These included: (i) a preference mapping application with 10 pear samples; (ii) a consumer appearance evaluation with 7 pear samples; and (iii) a survey of consumer perceptions of the ideal pear. The latter was intended as an independent validation of the outcomes of the preference mapping and appearance acceptability evaluations. Sentence completion, an approach grounded in marketing research, was used to collect consumer descriptions of an ideal pear. In the preference mapping application, the sensory profiles of samples were supplemented with some physiochemical measures JOURNAL OF FOOD SCIENCE Vol. 68, Nr. 3, Institute of Food Technologists Further reproduction prohibited without permission

2 Table 1 Physiochemical measures of samples included in preference mapping application Firmness Brix Weight Sample Species Availability [KgF] [%] [g] Shape Yellow Green Ripe Buerre Bosc P. communis L. Cultivar 1.7 (0.2) ef 12.3 (0.6) abc (16.3) c 4.3 (0.3) c 0.0 (0.0) e 0.0 (0.0) c Not-Ripe Buerre P. communis L. Cultivar 4.6 (0.5) b 12.3 (0.5) abc (14.0) bc 4.3 (0.3) c 0.0 (0.0) e 0.0 (0.0) d Bosc Ripe Packham s P. communis L. Cultivar 0.8 (0.2) g 12.4 (0.8) abc (7.1) a 4.8 (0.3) a 12.5 (0.9) b 7.7 (2.8) b Triumph Not-Ripe Pack- P. communis L. Cultivar 5.4 (0.9) a 12.8 (0.8) ab (7.8) a 4.9 (0.3) a 6.2 (3.0) d 12.1 (0.8) a ham s Triumph Ripe Doyene du P. communis L. Cultivar 0.6 (0.3) g 13.0 (0.7) a (8.6) bc 3.4 (0.3) b 16.3 (1.9) a 4.4 (4.5) d Comice Not-Ripe Doyene P. communis L. Cultivar 4.4 (1.5) b 13.0 (1.2) a (12.7) b 3.4 (0.4) b 10.0 (3.0) c 11.9 (1.9) a du Comice Ripe Pear A P. Hybrid Seedling 1.2 (0.4) fg 10.1 (0.4) d (22.7) bc 3.0 (0.2) d 16.0 (2.4) a 1.3 (2.0) d Not-Ripe Pear A P. Hybrid Seedling 3.5 (0.6) c 10.2 (0.4) d (22.6) c 3.0 (0.2) d 12.5 (2.3) b 6.4 (3.7) bc Pear B P. pyrifolia Seedling 2.6 (0.3) d 12.0 (0.7) bc (60.7) a 2.2 (0.3) e 14.3 (2.5) b 5.3 (2.7) c Nashi P. pyrifolia Cultivar 2.0 (0.2) e 10.5 (0.8) c (13.6) bc 1.5 (0.2) f 0.0 (0.0) e 0.0 (0.0) d Note: Values are averages across the samples presented to the sensory panellists (with standard deviations given in brackets). See text for description of shape and color measurements. In Figures 1 to 3, prefix R denotes ripe genotypes, NR denotes Not-Ripe. For the sake of brevity the following abbreviations are used throughout: Bosc for Buerre Bosc, Packham for Packham s Triumph and Comice for Doyene du Comice. If letters differ within a column Student-Newman-Keuls multiple range test is significant at the 5%-level. Materials and Methods Samples In accordance with the aim of identifying directions for NPD, the pear samples (pyrus spp.) used in the preference mapping application were selected to span the pyrus genus and provide variation with respect to degree of ripeness. Specifically, 10 samples from 6 genotypes were evaluated (Table 1). The term genotype was used to indicate the plants from which the different fruits came. Four genotypes were commercially available pear cultivars. The remaining 2 were seedlings that had been nominated by plant breeders for market screening. Note that in the U.S., Nashi is also referred to as Asian Pear. The fruit from seedlings was grown at research orchards in Nelson, New Zealand. Immediately following harvest, the fruit was placed in coolstores held at 0 ºC. Two wk prior to sensory evaluation, the fruit were transferred to post-harvest facilities at the Mt. Albert Research Center. Immediately prior to this transfer, fruit from the 4 commercial cultivars was obtained from commercial coolstores in the Hawkes Bay area. Two samples of each of the European cultivars and the P. communis L + P. pyrifolia hybrid were included in the preference mapping application. For these 4 genotypes, the 2 samples varied with respect to degree of ripeness. The ripening treatment consisted of removing samples from coolstores to a temperature controlled maturation room (20 C) 1 wk prior to commencing sensory evaluation. In comparison, not-ripe samples were removed from coolstores 24 h prior to commencing testing. The ripening treatment was not applied to the 2 Asian genotypes, which were also removed from coolstores 24 h prior to commencing testing. Seven genotypes were selected for consumer evaluation of appearance. With the exception of 2 genotypes, these were seedlings selected by breeders for market screening. In most cases it was impossible to obtain sufficient fruit numbers to include these seedlings in the preference mapping application. Therefore, only 3 of the 7 genotypes included in appearance acceptability evaluation also featured in the preference mapping application, namely Bosc, Nashi and Pear B. The 4 seedlings that did not feature in the preference mapping application were Pear C, Pear D, Pear E and Pear F (see Figure 3). Physiochemical Measures Firmness and Brix (soluble solids) were measured by a single operator using conventional protocols in which juice expressed during puncture measurements (hand-held Effegi penetrometer with an 8 mm dia probe; Facchini Srl; Alfonsine, Italy) was transferred onto a digital refractometer (Harker and others 1996, 1999). Intensity of green and yellow was assessed using commercial color chips as used to assess apple harvest maturity (Harker and others 1999). For green color, readings on the ENZA 1996 Braeburn chart were transformed into values on a 14-point scale anchored at 0 = not green and 14 = intensely green. Readings on the ENZA 1996 Gala/Royal Gala chart for yellow were transformed into values on a 20-point scale anchored at 0 = not yellow and 20 = intensely yellow. The transformations allowed projection of these 2 color variables onto the preference map. Although 2 genotypes ( Bosc and Nashi ) were brown, variation in brown color was not measured. The same applied to the intensity of red color (Pear B and Comice ). Shape was judged using a 5-point scale from round (1) through elongated (3) to pyriform (5) [the scale is reproduced in Appendix A]. The weight of samples was used as a proxy for size. For the samples included in the appearance evaluation, length (excluding stem) and diameter was measured to the nearest 0.01 cm using manual calipers. All physiochemical measurements were made on whole fruit, which were halved when presented to panelists and consumers. Immediately prior to doing so a slice of fruit tissue containing the penetrometer hole was removed. A tracking system was used to match physiochemical measures of individual fruits with samples presented to individual panelists and consumers. Sensory profiling For the samples included in the preference mapping application, descriptive profiling was performed by a panel of 10 trained female panelists. All were experienced panelists who had previous- Vol. 68, Nr. 3, 2003 JOURNAL OF FOOD SCIENCE 1109

3 ly been involved in sensory evaluation of fresh fruit and none were research employees. Vocabulary development and training took place over a period of 5 d. The vocabulary was developed and refined during the first 2 d of training. In addition to exposing panelists to genotypes included in the study, reference standards previously used by the authors in sensory profiling of pears (Harker and others 1999) were also used. The subsequent training sessions focused on reaching agreement among panelists on the meaning and evaluation of the attributes. During this training period, the performance of each panelist with regard to descriptive ability and sensitivity was strictly monitored. To ensure consistency within the panel, daily feedback was given. The final vocabulary consisted of 25 attributes of which 6 pertained to odor, 11 to flavor, and 8 to texture (Table 2). The intensity of attributes was recorded on 150 mm unstructured lines scales anchored at the ends with the words absent and extreme. The position of reference standards was marked on each attribute linescale. Samples, which were presented monadically, were assessed in replicate over the course of 4 consecutive days. Panelists evaluated 5 samples each day using a randomized and balanced complete block design. Evaluations were performed on just less than half a fruit (cut lengthwise) at room temperature. Microlene (TM) filtered water and plain water crackers were provided as palate cleansers. Testing was carried out in sensory booths at the Mt. Albert Research Center using automated data collection (Compusense Five software). The sensory evaluation booth area was held at 20 C and a positive airflow removed odors from the testing area. All fruit presented to panelists and consumers was room temperature. Consumer evaluations In parallel with sensory profiling, consumers evaluated the 10 preference mapping samples over 2 consecutive d. Participating adults (N = 103, 50% on d 1) from the Auckland region were regular consumers of pears (eating pears once a week or more frequently when in season). The sample was 82% female and aged between 18 and 65 y of age with 67% being 45 y or younger. Sensory acceptability was measured on a vertical 9-point category scale from 1 = dislike extremely to 9 = like extremely. The samples were presented sequentially according to a design balanced for presentation order and 1st-order carry over effects (MacFie and others 1989). To reduce the 1st-sample effect (Meilgaard and others 1991) a warm-up sample was always presented first ( Nashi cultivar). Samples of just less than half a fruit (cut lengthwise) were presented (with the cut surface facing down) on white paper plates labeled with 3-digit random numbers. Testing took place in the sensory booths used for profiling; water and crackers were available. A 5-min break was enforced after evaluation of the first 6 samples. For the 51 consumers participating on the 2nd d of testing, all samples were weighed before and after being evaluated by individual consumers. Once consumers had completed the taste evaluations, they were presented with a set of 7 pears and asked to rank these from the least to most preferred in terms of appearance. As a further source of information, consumer survey responses were used to uncover attributes of fruit that in the eyes of consumers are ideal. Specifically, as part of a separate study conducted 1 wk later, 3 sentence-completion questions were added to the end of a survey instrument. These asked participants to describe their ideal pear, apple, and kiwifruit ( To me, the ideal xxx is... ). The order of the 3 questions was randomized among participants. These were 100 adults (18 to 65 y old, 57% female) from the Auckland region JOURNAL OF FOOD SCIENCE Vol. 68, Nr. 3, 2003 Statistical analysis The sensory profiling data from each sensory attribute was subjected to 2-way analysis of variance using samples and panelists as factors. Averaging across panelists and replicates, mean values for each attribute were input to principal components analysis (PCA; Krzanowski 1988) of the correlation matrix. The preference data was analyzed using preference mapping methodology and cluster analysis. In the present study, preference mapping was performed in the SAS system (SAS 1990) by submitting the preference data to an internal analysis of the correlation matrix. Two types of significance testing were performed. Testing of whether differences between product preferences are significant was carried out at the 5% level, while the test of how well individual consumers are fitted by the preference model was conducted at the 10% level. The means of the sensory attributes were correlated (r 2 > 0.5) with the 2-dimensional internal preference space to interpret this in terms of the sensory variation driving preference. These procedures were based upon recent developments in internal preference methodology (Daillant-Spinnler and others 1996; Jaeger and others 1998; Monteleone and others 1998). Increasingly, cluster analysis (Chatfield and Collins 1980; Everitt 1993) is being used as a supplement to or substitute for preference mapping. In accord with the underlying premise of grouping people who think alike, the application of cluster analysis is intuitively appealing. Examples from the consumer acceptance literature include Schlich (1995), the European Sensory Network (ESN 1996) and Helgesen and others (1997). In the present study, cluster analysis was performed in the SPSS system (SPSS 1997). Three genotypes ( Bosc, Nashi, and Pear B) featured in both the preference mapping application and the appearance evaluation. Unfortunately, the appearance evaluation data were collected without recording the individual consumers ID. Thus, it was not possible to compare these 2 types of acceptance data. Results and Discussion Physiochemical measures of pears One-way analysis of variance revealed a significant sample effect (p < ) for all measures. Among the 4 genotypes for which ripe and not-ripe samples were included, there was a significant effect of genotype (p < ) but not of ripening (p > 0.70) for Brix, weight, and shape. For firmness and yellow and green color, the effects of ripeness and genotype, as well as their interaction, were highly significant (p < 0.005). It was not unexpected that ripe samples were less firm, more yellow and less green than not-ripe samples. The presence of significant interaction effects indicated that the changes in these attributes were complex and occurring at different rates between genotypes. Sensory profiles of pears Analysis of variance revealed significant differences between samples (p < 0.05) for all attributes except apple odor. With the exception of ease of breakdown, the repetition effect was nonsignificant at the 5% level for all attributes. While the effect of panelists was highly significant for all attributes, the panelist-by-sample interaction was nonsignificant for 8 of the 25 attributes, primarily those pertaining to texture. Prior to performing principal components analysis, the averages across panelist and repetition were computed for all attributes except apple odor and the ease of breakdown. The 2 latter attributes were not considered further. Further ANOVA was performed among the 4 genotypes for which both ripe and not-ripe samples were included in the preference mapping application. For odor attributes, the effect of ripening was

4 significant (p < 0.05) for artificial pear, cooked pear, and grassy/green in a manner where ripe samples had more artificial and cooked pear odor but less grassy/green odor. Among the 4 genotypes, Pear A had highest levels of artificial pear and fermented odor. Comice was highest in stemmy/woody odor; Packham lowest. The ripeness-bygenotype interaction effect was nonsignificant for all odor attributes. With respect to flavor, the effect of ripening was significant (p < 0.05) for cooked pear, fermented, sweet, and bitter (skin on). Ripe samples had higher intensity levels. The effect of genotype was significant for artificial pear, fermented, stemmy/woody, sweet, acid, and bitter (skin on and skin off). With the exception of sweet flavor, Pear A had the highest intensity levels. The interaction effect was nonsignificant for all flavor attributes. In terms of crisp, firm, juicy, and crunchy texture, the sensory data mirror the complex relationships found in the physiochemical data with significant effects of ripening, genotype and ripening-by-genotype. A detailed picture of sample similarities and differences were established by combining the ANOVA and PCA results. For the latter, PCA of the correlation matrix of the sample means resulted in a 3-factor solution accounting for 78.7% of the variation in the data Table 2 Vocabulary terms, definitions and references for sensory profiling of pears Reference standards Term Definition (intensity on 150 mm linescale) Artificial Pear (odor and flavor) The estery aromatics/taste of Odor: Crushed pear Jelly Bellys pear jelly beans jellybeans (120) Flavor: Pear Jelly Bellys jellybeans (130) Canned Pear (odor and flavor) The aromatics/taste of canned Odor: 100 ml syrup from Southern Cross Bartlett pears canned Bartlett pears in 1L water (80) Flavor: Watties canned pears in light syrup (50) Grassy / Green (odor) The aromatics of unripe or green 25 ml cis-3-hexen-1-ol in 1L water (120) fruit that is similar to grass/leaves Apple (odor and flavor) The aromatics/taste of apples 500ml Fresh Up apple juice in 500 ml water (odor = 120; flavor = 100) Fermented (odor and flavor) The aromatics/taste of fermented fruit Brightstone classic cider (odor = flavor = 100) Stemmy/Woody (odor, flavor of flesh The aromatics/taste associated with 25 ml cis-3-hexen-1-ol in 500ml Fresh Up apple without skin [skin off] and flavor of fruit stalks/cores juice and 500ml water (odor = 120, flavor skin flesh with skin [skin on]) off = flavor skin on = 150) Astringency (Mouthfeel) The sensation associated with Ocean Spray Cranberry juice (130) drying of the mouth. Sour/Acid (Taste) The basic taste on the tongue 0.5g malic acid in 1L water (75) stimulated by acids Characteristic of acids Sweet (Taste) The basic taste on the tongue 20g sucrose in 1L water (30) and 60g sucrose in stimulated by sugar and high 1L water (120) potency sweeteners Bitter (flavor of flesh without skin The basic taste on the tongue 0.35g caffeine in 1L water (flavor skin off = flavor [skin off] and flavor of flesh with skin stimulated by solutions or skin on = 100) [skin on]) substances such as quinine or certain other alkaloids Crispness (texture) The amount and pitch of sound 1 cm 3 banana (0), 1 cm 3 cucumber (50) and 1 cm 3 generated when sample is first celery (150) bitten with the front teeth Firmness (texture) The force required to compress the 1 cm 3 banana (10), 1 cm 3 celery (110) and 1 cm 3 sample between the back teeth carrot (150) Juiciness(texture) The amount of juice released by the 1 cm 3 banana (0) and 1 Trident canned sample during the 1st 3 chews mandarin segment (150) Crunchiness (texture) The amount of noise generated when 1 cm 3 banana (10) and 1 cm 3 carrot (150) chewing with the back teeth Ease of Breakdown (texture) The ease with which the flesh breaks 1 cm 3 banana (10) and 1 cm 3 carrot (140) down during chewing so that it can be swallowed (do not include skin in evaluation) Skin Toughness (texture) The amount of chewing required to cut Granny Smith apple with skin on (110) through and breakdown the skin with the back teeth Graininess (texture) The degree to which the flesh breaks ¼ cup Flemmings Semolina in 2 ¼ cup water down into a mass containing soft (100) particles (similar to fine porridge) Grittiness (texture) The presence of small hard particles Southern Cross canned guava flesh halves (no in the flesh seeds) (60) Vol. 68, Nr. 3, 2003 JOURNAL OF FOOD SCIENCE 1111

5 (Figure 1). In part as a result of stemmy/woody and bitter flavor of its skin, Pear B was separated from the remaining samples. Pear B was also characterized by high levels of apple flavor, stemmy/ woody flavor, astringency, and juicy and crunchy texture (Figure 1b). The ripe Pear A was characterized by high levels of fermented odor and flavor, and was more astringent and juicy and less firm than the not-ripe Pear A sample. The 3 ripe European pears (that is, Comice, Packham, and Bosc ) were grouped together and separated from a grouping of the corresponding not-ripe samples. The ripe European pears had high levels of sweetness and cooked pear odor and flavor. With respect to texture, they were soft and juicy. Ripe Bosc was less juicy, more firm, crunchy, and grainy than the ripe Comice and ripe Packham. For these 3 ripe samples, grittiness was lowest in Packham, and skin toughness was lowest in Comice. Among the 3 not-ripe European samples, not-ripe Bosc had the lowest level of grassy/green odor. Not-ripe Comice had the highest level of artificial pear odor and flavor and acid flavor. Not-ripe Packham was the least juicy, grainy, and gritty of the 3. Nashi had low to medium intensity of all attributes. The spaces spanned by the 2nd and 3rd principal components are shown in Figures 1c and 1d. Consumer liking of pears The preference data was subjected to internal preference mapping of the correlation matrix. This resulted in a 3-factor solution accounting for 63.9% of the total variation in the data of which 31.6% was accounted for by the 1st preference dimension, 19.6% by the 2nd and 12.7% by the 3rd. The 1st dimension separated the well-liked Figure 1 Results of principal components analysis of sensory profiling data. (a) plot of the 2 first principal component scores; (b) plot of the 2 first principal component loadings; (c) plot of the 2nd and 3rd principal component scores; and (d) plot of the 2nd and 3rd principal component loadings. For sensory attributes, prefix o = odor, f = flavor and t = texture JOURNAL OF FOOD SCIENCE Vol. 68, Nr. 3, 2003

6 ripe Comice, Packham, and Bosc pears from the 2 disliked Pear A samples (Figure 2a). The 2nd dimension separated the not-ripe Comice, Packham, and Bosc pears from the remaining samples. The 3rd dimension separated the 2 Asian genotypes ( Nashi and Pear B) from the remaining samples. Similar to their relative positioning in the space spanned by the 2 first preference dimensions, Nashi and Pear B were positioned close together with negative loadings on the 3rd dimension (not shown). Significance testing at the 10% level revealed that 67 consumers (65%) were significantly fitted in the space spanned by the 2 first preference dimensions. The grouping of consumers in Figure 2b suggested differential acceptance of ripe and not-ripe pears. Using K-means cluster analysis this segmentation pattern was explored further. In the 5-cluster solution that resulted, 1 cluster separated a single outlying person (positioned with the most negative loading on preference dimension 1 in Figure 2a), and another (Segment D) contained only 7 people. These 7 consumers favored the not-ripe Packham but rejected the ripe Bosc sample, which at the aggregate level was highly accepted (Table 3). It was not possible to interpret this preference profile in terms of the physiochemical or sensory attributes driving preference. The dominant characteristic of Segment A (n = 28, 27%) was the rejection of the Pear A genotype in comparison to the remaining 8 samples, which were equally well-liked (> 6.5). In terms of the sensory characteristics driving preference, consumers Figure 2 Results of extended internal preference mapping analysis of consumer liking of pears. (a) plot of the 2 first preference dimension loadings with product confidence ellipses shown at the 5% level; (b) projection of sensory attributes (r 2 > 0.5) on to the preference space; (c) plot of the 2 first preference dimension scores with consumer confidence ellipse shown at the 10% level; and (d) segments identified from cluster analysis of consumer preference scores. Refer to Table 1 for sample legends and to Figure 1 for sensory attribute legends. Vol. 68, Nr. 3, 2003 JOURNAL OF FOOD SCIENCE 1113

7 Table 3 Mean acceptability for overall consumer sample and by segment for samples in preference mapping application Name Overall Acceptability Segment A Segment B Segment C Segment D Ripe Bosc 7.3 (1.4) a 6.9 (1.2) a 8.0 (0.9) a 7.2 (1.4) a 2.9 (0.7) ab Not-Ripe Bosc 6.4 (1.6) b 7.7 (0.9) b 5.8 (1.6) bc 5.1 (1.8) a 5.3 (2.0) ab Ripe Packham 7.6 (1.4) a 7.6 (1.3) a 8.0 (0.7) a 7.6 (1.5) a 6.1 (2.0) ab Not-Ripe Packham 6.0 (1.9) bc 7.3 (1.1) bc 5.3 (1.8) c 5.2 (2.0) a 7.0 (0.8) a Ripe Comice 7.1 (1.7) a 7.0 (1.1) a 7.9 (0.9) a 7.1 (1.7) a 6.3 (2.2) c Not-Ripe Comice 6.0 (1.9) bc 7.5 (0.8) bc 5.8 (1.7) bc 6.0 (1.6) a 6.4 (2.0) ab Ripe Pear A 4.8 (2.3) d 4.3 (2.1) de 6.4 (1.9) b 3.6 (1.9) b 3.9 (1.9) bc Not-Ripe Pear A 4.8 (2.3) d 4.4 (1.9) e 6.4 (1.6) b 2.7 (1.5) b 6.0 (1.3) ab Pear B 5.9 (2.1) bc 7.0 (1.6) cd 6.4 (1.6) b 4.4 (2.4) a 6.1 (1.2) ab Nashi 5.7 (1.9) c 6.8 (1.2) cd 6.0 (1.7) bc 4.7 (2.2) a 3.7 (1.6) bc Note: N = 103 [Segment A = 29 (28%), Segment B = 38 (37%), Segment = 28 (27%), Segment D = 7 (7%) and 1 outlying consumer]. Acceptability was measured on 9-point scale from 1 = dislike extremely to 9 = like extremely. If letters differ within a column Student-Newman-Keuls multiple range test is significant at the 5% level. in this segment disliked the acid and bitter flavors of Pear A, as well as the artificial pear odor and flavor and stemmy/woody odor (Figure 2c). In this segment, Brix seemed to be an indicator of consumer acceptance (r = 0.75, p = 0.12, n = 10). However, we cannot be certain that Brix is a driver of preference for this segment since the relationship was driven by 1 poor quality genotype that happened to be low in Brix and disliked by consumers. Consumers in Segment B (n = 38, 37%) responded strongly to the degree of ripening. Thus, among the 3 European cultivars, ripe samples were strongly preferred to not-ripe samples. The remaining samples were all relatively well-liked (6 to 6.5). This segment s profile was driven by acceptance of sweet flavor, cooked pear flavor and odor, and juicy texture. Conversely, firm, crisp, crunchy, and grainy textures were disliked. A significant negative correlation with flesh firmness as measured by puncture force (r = 0.82, p = 0.004, n = 10) confirmed this ripeness-related pattern. Consumers in Segment C (n = 29, 28%) exhibited preferences that reflected a combination of the responses that drove Segments A and B. They responded strongly to degree of ripeness with a preference for ripe over not-ripe samples. While acceptance of Pear A was low, ripe Pear A remained more preferred than not-ripe Pear A. In comparison to the 2 other segments, acceptance of Pear B and Nashi was low. This preference profile was related to a liking for sweet flavor but rejection of acid, bitter, fermented, and stemmy/ woody flavor, as well as grainy texture. Within the 3 main clusters, 1-way ANOVA revealed significant differences in acceptance (p < 0.01) for all samples but ripe Packham. This sample was highly liked in all 3 segments. No differences between consumers in the 3 main clusters with respect to frequency of eating pears was established [Chi-square = 3.85, df = 2, p = 0.43, n = 95]. However, there were more consumers aged 45 y old or younger, in comparison to 46 y or older, in Segment C than Segments A and B [Chisquare = 13.87, df = 2, p = 0.001, n = 95]. When identifying consumers with respect to cluster membership in the 2-dimensional internal preference space (Figure 2d), the positioning of members of Segment A (who accepted all genotypes except Pear A) with high negative loadings on dimension 1 and around zero on dimension 2 had face validity. Similarly, the positioning of Segment C in the lower right-hand corner was expected due to the moderate preference of ripe over not-ripe samples and the rejection of Pear A. Segmentation of the consumer sample enabled a clearer interpretation of the 2 first preference dimensions. Specifically, the 1st dimension pertained to acceptance/rejection of Pear A, while the 2nd related to the overall acceptance of ripe compared with not-ripe samples. Recall that on the 2nd d of consumer testing, all fruit were 1114 JOURNAL OF FOOD SCIENCE Vol. 68, Nr. 3, 2003 weighed before and after being evaluated by consumers (n = 51). The amount of fruit eaten varied significantly among samples (p < ). Ripe Packham, which at the aggregate level was the most preferred sample, was also the sample consumers ate most [weight of sample eaten = 27.1g (std = 20.2)]. For the 4 cultivars where both ripe and not-ripe samples were evaluated, consumers ate more of the ripe samples [p = 0.013, ripe = 20.9g (std = 15.3), not-ripe = 17.5g (std = 12.6)]. An analysis of relative amount of sample eaten (weight of sample eaten/initial sample weight) gave similar results. When analyzing the eating data at the level of individual consumers, it was apparent that consumers belonging to Segment A (acceptance of all genotypes except Pear A), in comparison to Segments C and D, were more likely to be those for whom the correlation coefficient between sample liking and weight of sample eaten was significant at the 5% level [Chi-square = 5.17, df = 1, p = 0.023, n = 46]. Further, consumers who were significantly fitted by the 2-dimensional preference space were more likely to be those for whom the correlation coefficient between sample liking and weight of sample eaten was significant at the 5% level [Chisquare = 8.45, df = 1, p = 0.004, n = 51]. Tentatively, if consumers evaluate appearance and odor before tasting samples, then negative cues experienced at this stage may lead to sampling a smaller piece of fruit. In the preference mapping application, Brix and flesh firmness was measured for all fruit given to consumers. Within genotypes, the variation in Brix was not related to liking and only for 1 sample was variation in firmness related to liking. Specifically, for not-ripe Packham consumer acceptance decreased with increasing firmness [r = 0.31, p = 0.015, n = 103]. Similar results were established when exploring the relationships between the weight of eaten sample and Brix and firmness. That is, no effect of Brix, but a lower amount of sample eaten the firmer the not-ripe Packham sample was. Consumer acceptance of appearance and descriptions of an ideal pear To explore the existence of segmentation patterns with respect to acceptance of appearance of pears, the ranking data was subjected to hierarchical cluster analysis using Ward s minimal-variance method (Ward 1963). Four segments were established [N = 103; Segment I = 23 (22%), Segment II = 32 (31%), Segment III = 24 (23%) and Segment IV = 24 (23%)]. For each sample, the mean ranks (Figure 3) differed significantly across the 4 segments (p < ). With the exception of Pear C, preferences for appearance were broadly similar in Segments I and II, and appeared to be driven by a liking for elongated and/or pyriform rather than round shapes. This tendency was most pronounced in Segment I as con-

8 firmed by strong associations between the mean ranks and the physiochemical measure of shape [Spearman rho = 0.77, p = 0.04, n = 7], as well as between mean ranks and sample height [Spearman rho = 0.68, p = 0.09, n = 7]. In Segment II, the rejection of the appearance of Pear C appeared to be driven primarily by color through dislike for earthy, green, and brown shades. Segment III comprised consumers who preferred a round to elongated/pyriform shape [Spearman rho (mean rank, height) = 0.68, p = 0.09, n = 7.] Thus, it was unexpected that Bosc was relatively well accepted. It appeared this acceptance was driven by a liking for warm, red, and golden colors. Segment IV similarly favored round shapes [Spearman rho (mean rank, width) = 0.71, p = 0.07, n = 7] but rejected brown colors. The sentence-completion responses were analyzed by recording the frequency with which different characteristics of pears were mentioned. As expected when collecting information using this approach, a few responses were not directly helpful in relation to NPD (for example, the ideal pear is covered in custard and cream or there is no such thing as an ideal pear ). However, the majority of responses pertained to desirable sensory characteristics. Among the 100 responses, the most frequently mentioned attributes were juicy (43%), sweet (38%), firm (24%), soft (17%), and crispy/crunchy (15%). In addition, 11 responses pertained to size (large or medium), 17 to color (green, yellow, or golden brown) and 18 to skin (not bruised, smooth, thin, soft). Specific cultivars were named 11 times [ Nashi (4), Packham (3), Chretien (2) and Winter Cole (2)]. Figure 3 Mean ranks for overall consumer sample and by segment for samples in appearance evaluation ranking test. Tabular data presents shape, weight and color of samples. Fruit color matched to color chips by Royal Horticultural Society (1966). Improving preference mapping methodology as a tool for guiding fresh fruit NPD The value of preference mapping in the NPD process is broadly acknowledged (Schlich 1995; McEwan 1996; Harker and others 2002). Yet it is also evident that room for improvements exists. Author Jaeger previously sought to improve preference mapping methodology by considering behavioral aspects of preference formation (Jaeger and others 2000). To this end, an information processing model of preference formation was proposed. Within this model, the process of synthesis, which is the way sensory information about product similarities and differences is analyzed and processed, was considered in detail. The authors demonstrated that small performance gains could be achieved through more extensive statistical analysis. In the present study, other avenues for improving the preference mapping methodology were considered. One was validation of the key findings using survey responses from an independent consumer sample. The other pertained to the use of physiochemical measures as an additional source of external data with respect to which consumer preferences could be interpreted. The potential benefits of including physiochemical measures in preference mapping applications are twofold. The first pertains to the frame of reference such measures provide to food-and horticultural scientists due to their widespread usage. The other, which is more tangible, pertains to improvements in the interpretation of results. Among the 3 main clusters established in the preference mapping application, variation in Brix between samples was significantly correlated with mean preferences in the Segments A and C [r , p , n = 10]. In comparison, flesh firmness was negatively correlated with mean preferences in Segment B [r = 0.82, p = 0.004, n = 10]. To the authors these results were key to the realization that in terms of a top-line interpretation of the preference mapping segmentation patterns, Segment A was driven primarily by negative flavor attributes whereas Segment B was primarily driven by ripeness. The appearance evaluation revealed that current consumers of pears have well-formed preferences with respect to shape and color. Further, it was suggested that an individual s acceptance of the appearance of any given fruit may not correspond to his or her liking of it (see later). As a first glance it may, therefore, seem a little odd that the shape and color measures were not useful in interpreting the preference mapping segmentation pattern. We speculate that differences in the signals perceived by consumers about the aim/ focus of a study is of importance. In the appearance evaluation, this signal was clearly a focus on appearance. There was no opportunity to taste and the response sheet asked participants to consider appearance only. On the other hand, when introducing participants in the preference mapping application to the study, they were informed that they would be tasting pears and asked to give an overall evaluation of their liking of each sample. Tentatively, when subsequently seated in sensory tasting booths and presented with samples of half fruit, consumers may have interpreted the somewhat diffuse signal of overall evaluation as a focus on taste and texture rather than appearance. In a preference mapping application, unless specifically instructed to take appearance into consideration, we speculate that many consumers may not automatically do so when not presented with a whole fruit. Perhaps instructing consumers specifically (both during the study introduction and in the tasting booths when presented with each sample) to give an overall evaluation on the basis of appearance, odor, taste, and texture would send a clearer signal as to the intended focus. However, it is likely that taste is dominant over appearance in real-life choice situations. Apple preference maps constructed by Daillant-Spinnler and others (1996) did not markedly change between peeled and unpeeled samples. Furthermore, in studies on orange juice, it was demonstrated that visual cues were less important than taste in determining value (Lange and others 2000). The 5-point scale for shape worked well, but it would have been helpful to supplement with the length and diameter measures also used in the appearance evaluation. Together with weight, these measures are frequently used (Hampson and Quamme 2000; Kappel and others 1995). The work by Hampson and Quamme (2000) Vol. 68, Nr. 3, 2003 JOURNAL OF FOOD SCIENCE 1115

9 on the use of preference testing to identify tolerance limits for fruit visual attributes in apple breeding is helpful in suggesting other external appearance attributes to consider in future studies including lenticels and russet. The consumer survey responses suggested attributes such as skin smoothness, cleanliness, and toughness. The sentence completion data was helpful in getting an independent confirmation of the key outcomes of the preference mapping application and appearance evaluation. Consideration should be given to other brief questions that may aid this validation approach. Characteristics of an ideal pear It is clear from the preference mapping application that the strong dislike for the Pear A genotype was driven by its fermented, bitter, stemmy/woody, and acid attributes. To some extent, the sentence completion responses validated this finding. Although consumers did not use highly specific attributes when describing the ideal pear with respect to flavor, they used terms like tasty, flavorful, and not overripe. When odors such as fermented, bitter, stemmy/woody, and artificial pear become too strong, they are, in effect, off-flavors and have a strong negative impact on acceptance. A similar strong and negative effect of off-flavors in fresh fruit has been reported elsewhere (Daillant-Spinnler and others 1996, Jaeger and others 1998, 2003). Previously Bruhn and others (1991) suggested that the difficulty pears have faced in the marketplace relates predominantly to ripeness. According to these authors, consumers complain that a lot of fruit is too firm and has too little flavor. The issue of ripeness was also key to interpretation of the present results. At the aggregate level, ripe samples were favored over not-ripe samples. Compared to not-ripe samples, ripe samples were less firm and crispy but more juicy and sweet. The descriptions of ideal pears collected among an independent consumer confirmed this result. Juicy and sweet were the terms mentioned most frequently in the survey responses (38% and 43%, respectively). However, firm was mentioned in 24% of survey responses, soft in 17% of cases and crispy/crunchy in 15% of cases. This suggests that degree of firmness, and to a lesser extent crispness, are characteristics that are also very important to consumers. However, as ripening results in a softening of the flesh and a loss of crispness, it seems a possibility that consumers must trade-off characteristics such as juiciness and firmness against each other. Overall, fruit that is not too soft and still juicy and crisp is suggested as one avenue for NPD. The appearance evaluation revealed a complex segmentation pattern among consumers. While some preferred big and elongated/pyriform shape, others rejected dark green and brown colors and others again preferred a round shape and warm golden colors. This variability in color preference was confirmed by the sentence-completion responses where ideal colors included green, yellow, and golden brown. Tentatively, the reason red was not mentioned by consumers is that pears with red coloring are generally not available in the New Zealand marketplace. Thus, if consumers answer the sentence-completion question using their previous experiences as a reference, red is unlikely to be mentioned. However, this does not imply that red fruit will be rejected, as indicated by the appearance evaluation findings. One color it appeared that most consumers did reject was that the dark brown and greens of Pear C. With respect to size, the sentence completion data suggested a preference for medium to large pears. However, it appears that shape rather than size was a key determinant in the appearance evaluation data. In the survey data, 36% of responses mentioned external appearance. In terms of frequency this is just below juicy (43%) and sweet (38%). Overall, it is clear that appearance is a critical aspect of acceptance. We 1116 JOURNAL OF FOOD SCIENCE Vol. 68, Nr. 3, 2003 suggest a greater focus on appearance as one avenue for further exploration in the search for the ideal pear. We previously conducted a preference mapping study with NZ pears (3 cultivars and 5 seedlings; summarized in Harker and others 2002). The internal preference space spanned by the 2 first preference dimensions revealed a number of groupings. While some consumers responded positively to flavors and odors usually associated with unripe pears, others responded positively to flavors and odors usually associated with overripe pears. In addition to the segmentation driven by unripe-overripe characteristics, consumers also differed in their acceptance of flavor and texture properties. A minority responded to crisp and acid-tasting pears. The majority, however, preferred softer and sweeter pears. Overall, the findings from the above study mirrored the key outcomes of the present preference mapping application. Further, the similarity of these 2 preference maps give some indication of the stability of the key attributes driving sensory acceptance for pears and their associated consumer segments. The more extensive work conducted with apples confirm that the key sensory attributes driving consumer acceptance remain stable across studies (MacFie and Beyts 1995, Daillant-Spinnler and others 1996, Jaeger and others 1998, Kuhn and Thybo 2001). One limitation of the present preference mapping application was the dominance of Caucasian female consumers. This convenience sample is not representative of the Auckland or New Zealand population. The extent of the limitation is unknown. The results from our previous pear study suggest that the limitation in terms of culture may not be highly significant. Specifically, in the previous study the consumer sample (n = 120) was 60% New Zealand and 40% recent immigrants from Taiwan (who had lived in NZ less than 1 y). Segmentation between the 2 ethnicities was not evident. Also, recall that the sentence completion findings were similar to those from the preference mapping application. This independent Auckland consumer sample was 43% male. On the other hand, one may err on the side of caution with respect to the influence of gender and culture. Even in this case we believe the preference mapping results remain valuable. A majority of NZ horticultural exports go to the U.S. and E.U. Also, women continue to be responsible for the lion s share of food shopping. In view of the known complex relationships between sensory acceptance, culture, and demographics, further studies are required. The work by Kappel and others (1995) clearly emphasize this need. For example, many of the fruit preferred by consumers in the current study exhibited characteristics outside those considered optimal for appearance in the Canadian study by Kappel and others (1995). Conclusions IN THIS SAMPLE OF NEW ZEALAND CONSUMERS, THE PREFERENCE mapping application revealed a preference for European over Asian or hybrid genotypes and, further, a preference for ripe over not-ripe samples. The latter finding concurred with questionnaire responses from an independent consumer sample that described their ideal pears as sweet and juicy. These 2 attributes were the distinguishing differences between ripe and not-ripe samples. Attempts to improve the usefulness of preference mapping as a tool in guiding fresh fruit NPD was partly successful. The sentence-completion responses were useful as an independent confirmation of the key findings. However, the need to find ways of quantifying external appearance remains. The appearance evaluation highlighted the existence of distinct consumer segments based on appearance. References Andani Z, Jaeger SR, Wakeling IN, MacFie HJH Mealiness in apples: towards a multilingual consumer vocabulary. J Food Sci 66:872-9.

10 Bruhn CM, Feldman N, Garlitz C, Harwood J, Ivans E, Marshall M, Riley Alpha, Thurber D, Williamson E Consumer perceptions of quality: apricots, cantaloupes, peaches, pears, strawberries and tomatoes. J Food Qual 14: Carroll JD Individual differences and multidimensional scaling. In: Shepard RN, Romney AK, Nerlove SB, editors. Multidimensional Scaling: Theory and Applications in the Behavioral Sciences, Vol 1. New York: Seminar Press. p Chatfield C, Collins AJ Introduction to Multivariate Analysis London: Chapman Hall. Dalliant-Spinnler B, MacFie HJH, Beyts PK, Hedderley D Relationships between perceived sensory properties and major preference directions of 12 varieties of apples from the southern hemisphere. Food Qual Pref 72: ESN A European Sensory and Consumer Study A Case Study on Coffee. In: McEwan JA, editor. European Sensory Network. Campden, Gloustershire, U.K.: Campden Chorleywood Food Research Association Chipping. Everitt B Cluster Analysis. 3rd ed. London: Edward Arnold. Greenhoff K, MacFie HJH Preference mapping in practice. In: MacFie HJH, Thomson DMH, editors. Measurement of Food Preferences. Glasgow: Blackie Academic & Professional. p Hampson CR, Quamme HA Use of preference testing to identify tolerance limits for fruit visual attributes in apple breeding. Hort Sci 35: Harker FR, Gamble J, Gunson FA, Jaeger SR, Petley M, Rossiter K, Walker S, White A Consumer preferences for apples and pears. Confidential Client Report 2000/170. New Zealand: Hort Research. Harker FR, Maindonald JH, Jackson PJ Penetrometer measurement of apple and kiwifruit firmness: Operator and instrumental differences. J Am Soc Hortic Sci 121: Harker FR, Watkins CB, Brookfield PL, Miller MJ, Reid S, Jackson PJ, Bieleski RL, Bartley T Maturity and regional influences on watercore development and its postharvest disappearance in Fuji apples. J Am Soc Hortic Sci 124: Harker FR, Gunson FA, Jaeger SR The case for fruit quality: an interpretative review of consumer attitudes, and preferences for apples. Postharvest Biology Technol (In press). Harker FR, Redgwell RJ, Hallett IC, Murray SH, Carter G Texture of fresh fruit. Hort Rev 20: Helgesen H, Solheim R, Næs T Consumer preference mapping of dry fermented lamb sausages. Food Qual Pref 8: Jaeger SR, Andani Z, Wakeling IN, MacFie HJH Consumer preferences for fresh and aged apples: a cross-cultural comparison. Food Qual Pref 9: Jaeger SR, Rossiter KL, Wismer WV, Harker FR Consumer-driven product development in the kiwifruit industry. Food Qual Pref 14(3): Jaeger SR, Wakeling IN, MacFie, HJH Behavioral extensions to preference mapping: the role of synthesis. Food Qual Pref 11: Jaeger SR Convenience is king: product innovation in the horticultural industry. Food Australia (In press). Kappel F, Fisher-Fleming R, Hogue EJ Ideal pear sensory attributes and fruit characteristics. Hort Sci 30: Krzanowski WJ Principles of Multivariate Analysis: A Users Perspective. Oxford Statistical Series 3. Oxford: Oxford Science. Kuhn BF, Thybo AK The influence of sensory and physiochemical quality on Danish children s preferences for apples. Food Qual Pref 12: Lange C, Issanchou S, Combris P Expected versus experienced quality: tradeoff with price. Food Qual Pref 11: MacFie HJH, Bratchell N, Greenhoff K, Vallis LV Designs to balance the effects of order of presentation and 1st order carry-over effects in hall tests. J Sens Stud 4:41-9. MacFie, HJH, Beyts, P Consumer preference and sensory studies on southern and northern hemisphere dessert apples. Eur Apple 3:12-3. MacFie HJH, Hedderley D Current practice in relating sensory perception to instrumental measurements. Food Qual Pref 4:41-9. McEwan JA Preference mapping for product optimization. In: Næs T, Risvik E, editors. Multivariate Analysis of Data in Sensory Science. Amsterdam: Elsevier. p McKenna M, Roche M, Le Heron R Sustaining the fruits of labor: a comparative localities analysis of the integrated fruit production programme in New Zealand s apple industry. J Rural Stud 14: Meilgaard M, Civille GV, Carr TB Sensory Evaluation Techniques. 2nd ed. Boca Ranton, FL: CRC Press. Monteleone E, Frewer L, Wakeling IN, Mela DJ Individual differences in starchy food consumption: the application of preference mapping. Food Qual Pref 9: Morel S, Harrison RE, Muir DD Genotype, location, and hardest date effects on the sensory character of fresh and frozen rasberries. J Am Soc Hort Sci 124: Pastor MV, Costell E, Izquierdo L, Duran L Optimizing acceptability of a high fruit-low sugar pectin peach nectar using aspartame and guar gum. J Food Sci 61: R.H.S R.H.S. Color Chart. The Royal Horticultural Society, London (reprinted). SAS SAS/STAT User s Guide, Version 6, 4th ed. SAS Institute Inc, Cary, N.C. Schlich P, McEwan JA Cartographie des preferences Un outil statistique pour l industrie agro-alimentaire. Sciences Des Alimentes 12: Schlich P Preference mapping: relating consumer preferences to sensory or instrumental measurements. In: Etievant P, Schreier P, editors. Bioflavor 95: Analysis/Precusor Studies/ Biotechnology. Versailles, France: INRA Editions. SPSS for Windows SPSS Professional Software, release 800 SPSS Inc, Chicago. Available online at Ward JH Jr Hierarchical grouping to optimize an objective function. J Am Stat Assn 58: Weil D The needs of the fruit industry in the US for the important testing and release of new cultivars: an industry perspective. Fruit Var J 52: Yackinous C, Wee C, Guinard J-X Internal preference mapping of hedonic ratings for Ranch salad dressings varying in fat and garlic flavor. Food Qual Pref 10: Zerbini PE, Pianezzola A, Grassi M Poststorage sensory profiles of fruit of 5 apple cultivars harvested at different maturity stages. J Food Qual 22:1-17. MS Submitted 9/3/02, Revised 10/17/02, Accepted 11/12/02, Received 11/20/02 The authors are with the Horticulture and Food Research Institute of New Zealand Ltd, Mt Albert Research Center, Private Bag , Auckland, New Zealand. Author Jaeger is now with The Univ. of Aukland, Dept. of Marketing, Private Bag 92019, Aukland, NZ. Direct inquiries to author Jaeger ( sjaeger@hortresearch.co.nz). Vol. 68, Nr. 3, 2003 JOURNAL OF FOOD SCIENCE 1117