- Email: [email protected]
Improved flavour acceptability of cherry tomatoes. Target group: Children
Food Quality and Preference 18 (2007) 152–160 www.elsevier.com/locate/foodqual
Improved flavour acceptability of cherry tomatoes. Target group: Children B. Brueckner a
a,*
, I. Schonhof a, R. Schroedter b, C. Kornelson
b
Institute for Vegetable and Ornamental Crops, Theodor-Echtermeyer-Str. 1, 14979 Grossbeeren, Germany b Prosens Inc., Germany Arthur-Scheunert-Allee 40/41, 14558 Nuthetal, Germany Accepted 12 September 2005 Available online 26 October 2005
Abstract Acceptability of tomato fruit flavour was investigated. To vary flavour, contents of glucose, fructose and citric acid were added to diced fruit, resulting a range of 3 to 8 g reducing sugars/100 FM and 430–700 mg titratable acid/100 g FM. Significant sweetness and sourness changes were determined by descriptive analysis, tomato-like flavour remained unchanged. Consumer tests with children aged 7–11 years were used to rate flavour acceptability. Most accepted combinations of acid and sugar were identified (4.5–6.5 g sugar/100 g FM; 540–640 mg acid/100 g FM). Cluster analysis allowed to separate three clusters with different response to sugars and acid concentrations. Forty five percent of the children did not respond, 30% liked low sugar concentrations (<3 g/100 g FM) most, 25% preferred 6.5 g/100 g FM at a wide range of acid concentrations. There was little evidence of differences with respect to gender, age, body weight and length between the cluster members, but the liking of sweet and acidic solutions differed. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Tomato fruit; Reducing sugars; Citric acid; Taste; Flavour; Children; Acceptability; Vegetable
1. Introduction Fruit and vegetable intake of children and teenagers is even lower then the intake of adults. Cognitive information (on health issues) is picked up by children, but effect-less for nutritional behaviour. To increase vegetable consumption, reference to consumersÕ wants and needs must be taken (German Nutrition Report 2000), the role of improved acceptability of flavour of fresh fruit and vegetables is emphasised. The aim of this study was to specify important criteria for flavour quality of cherry tomatoes as an example to improve acceptability of this fruit flavour for children. In a previous study with adults (Malundo, Shewfelt, & Scott, 1995) it was demonstrated, that the liking of tomato flavour could be enhanced by varying sugar and acid content. *
Corresponding author. Fax: +49 33701 55391. E-mail address: [email protected] (B. Brueckner).
0950-3293/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2005.09.011
No upper limit for sugar concentration was found. No similar experiments with children exist. Another important question is not yet answered in the literature: whether segments with respect to flavour preferences exist among children and how attributes must be like to meet the preferences of each segmentsÕ members. 2. Material and methods 2.1. Sample preparation Round, conventional tomato fruit of a single cultivar were picked in November 2002 at uniform size and colour (stage 9 at CBT colour chart) and shipped directly to the institute (experiment 1) by a greenhouse grower near Potsdam, Germany or, as in experiment 2, fruit were picked in December 2003 from a grower in Den Hoorn, The Netherlands and shipped to the EDEKATM distribution centre close to the institute. Fruit were stored at 12 ± 1 °C, until
B. Brueckner et al. / Food Quality and Preference 18 (2007) 152–160
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they were used for preparing the samples within three days. When needed, fruit were cut into dices of an edge length of 1 cm. Fructose and glucose were mixed at the ratio of 14/11 and were dissolved in distilled water to form the stock solution containing 50% of reducing sugars. Citric acid was dissolved in distilled water for a 25% acid stock solution. Stock solutions were kept in the refrigerator at 10 °C for no longer than one day. Three hours before the sensory analysis 150 ml of a solution prepared from the stock solutions and distilled water were given to 850 g of the diced fruit. The mixture was kept at 10 °C for 2.5 h prior to packing into 125 ml closed plastic containers at 20–25 g each. At this time two sub-samples of 50 g each were taken for the chemical analyses.
To evaluate the flavour acceptability of the diced tomato samples, consumer tests with a total of 163 children (experiment 1) and 121 children (experiment 2) were conducted. The age varied from 7–11 years. Body weight and height were recorded. Each child evaluated each of the four (experiment 1) or six (experiment 2) samples. In experiment 2 also 20 ml solutions of 0%, 0.1%, 0.2% and 0.5% citric acid and 0%, 2.0%, 5.0% and 8.0% glucose and fructose (mixture: 11 parts glucose/14 parts fructose) were given to all children for acceptability testing. The trained panel and the consumer panel worked in a sensory laboratory under defined (temperature and light) conditions single cabins with computer equipment. Data acquisition was carried out with the computer program CASA (Computer Aided Sensory Analysis).
2.2. Chemical analyses
2.4. Statistical analyses
The acid and sugar analyses were carried out as double estimations per sample with 50 g of homogenised and frozen (32 °C) tomatoes each. The material thawed quickly and boiled for 5 min with 100 ml deionised water. After cooling, the tomato sample was diluted to 250 ml with deionised water and filtered. The content of titratable acid was determined by a potentiometric titration with 0.1 M NaOH (LMBG, 1983) using 50 ml filtrate. The sugar contents were measured by the enzymatic detection of glucose and fructose, summarised as reducing sugars. The filtrate (5 ml) was diluted to 100 ml with deionised water. A 100 ll sample was assayed with an enzymatic test kit (Boehringer Mannheim, 1986) where reduced nicotinamide-adenine-dinucleotide-phosphate (NADPH) was formed during the reaction of the reducing sugars with hexokinase, adenosine-5-triphosphate, nicotinamideadenine-di-nucleotide-phosphate (NADP), glucose 6-phosphate-dehydrogenase and phosphoglucose-isomerase. The absorbance of NADPH was measured spectrophotometrically (Spekol 221, Carl Zeiss, Jena) at 340 nm. The results were converted to grams of fresh matter.
The data were analysed using the software packages Statistica v.4.1 (Statsoft), and SPSS v.7.5 (SPSS Inc.). Analytical data were subject to ANOVA and Tuckey-Test at the significance level stated. Multiple regression analysis, cluster analysis and response surface analysis were calculated with the corresponding modules of the Statistical package.
2.3. Sensory evaluation The descriptive sensory analysis was conducted to characterise the attributes of the prepared tomato material using a trained panel similar to the method of (Stone & Sidel, 1993). Eight judges were selected who had successfully passed standardised tests for olfactory, taste and colour sensibility as well as for commemoration, verbal abilities and creativity. Approximately 20 h training over a 10-week period for establishing the methodological foundations was followed by another 20 h training with tomato fruit. Fruit dices were presented individually and in random order in closed 125 ml plastic cups. A four digit code was assigned to the samples. The flavour terms sweet, sour and tomato-like were assessed using unstructured line scales with the anchor points 0—not perceptible and 100—strongly perceptible.
3. Results The chemical analysis of the four treatments in experiment 1 showed, that part of the added reducing sugars and titratable acid was absorbed by the tomato dices (Table 1). In untreated tomato dices, the contents was 2.00 g of reducing sugars/100 g and 411 mg titratable acids/100 g. Between the treatments, the amounts were clearly differentiated, though not statistically significant in case of acid contents between treatment B and C in experiment 1. Also, in experiment 2 the contents of reducing sugars and titratable acids could be increased by adding sugars and acid to the tomato dices (Table 2). The untreated material contained was 2.25 g of reducing sugars/100 g FM and 417 mg titratable acids/100 g FM. The content of absorbed acid was independent from the amount of added sugar, but less sugars were absorbed in the higher acid treatments. The increased sugar contents in diced tomatoes of both experiments increased the intensity of sweetness assessed by the descriptive panel. There was a significant, linear relationship (Table 3). No significant effect of added acidity on perceived sweetness was found. Both, sugar and acid level significantly affected sourness, but had no influence on tomato-like flavour (see Table 3). The consumers clearly distinguished the samples in experiment 1 because of their different flavour acceptability (Fig. 1). High acceptability scores were given to the samples B and C with intermediate sugar and acid levels. Samples A, the sweetest sample wit the lowest amount of acid was liked least, also, the most acidic and least sweet sample D was sub-optimal.
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Table 1 Amount of added reducing sugars and citric acid and measured average contents of reducing sugars and titratable acids in the four treatments (A–D) of experiment 1 Added sugars (g/100 g)/acid (g/100 g) A 6.5/0.1
B 5.0/0.2
C 3.5/0.3
D 2.0/0.4
Reducing sugars 6.01 d+ Titratable acids 433 a
Reducing sugars 4.99 c Titratable acids 512 b
Reducing sugars 3.92 b Titratable acids 565 b
Reducing sugars 3.05 a Titratable acids 641 c
+
Values with different alphabet letters are significantly different at p < 0.05 (separately for sugars and acids).
Table 2 Amount of added reducing sugars and citric acid and measured average contents of reducing sugars and titratable acids in the six treatments (A–F) of experiment 2 Added acid (g/100 g)
Added sugars (g/100 g) 8
5
2
0.2
A Reducing sugars 7.65 e+ Titratable acids 500 b
B Reducing sugars 5.27 c Titratable acids 484 a
C Reducing sugars 3.37 a Titratable acids 499 b
0.5
D Reducing sugars 6.79 d Titratable acids 685 d
E Reducing sugars 4.73 b Titratable acids 675 c
F Reducing sugars 3.09 a Titratable acids 695 e
+
Values with different alphabet letters are significantly different at p < 0.05 (separately for sugars and acids).
Table 3 Multiple regression results of descriptive attributes and sugar and acid content levels Variable Sweet Sour Tomato-like ** ***
R2
Intercept
0.837 0.979 0.230
Sugar level beta **
32.88 24.58 53.06
+0.814 0.634*** 0.387 n.s.
B
Acid level beta
B
7.75 5.16 0.99
0.235 n.s. +0.588*** 0.188 n.s.
0.037 0.078 0.008
Significant at p < 0.01. Significant at p < 0.001.
Table 4 Average physical characteristics of the consumer panelists averaged according to the cluster membership Experiment 1, 2002
Age (years) Weight (kg) Length (cm) Girls (%) Boys (%)
Experiment 2, 2003
Mean
Cluster 1
Cluster 2
Cluster 3
Mean
Cluster 1
Cluster 2
Cluster 3
9.5 36.2 144 50.9 49.1
9.4 35.9 143 51.4 48.6
9.6 35.5 144 60.8 39.2
9.5 37.4 147 36.6 63.4
10.7 43.7 150 53.7 46.3
10.5 42.6 149 41.8 58.2
10.9 45.5 150 71.4 28.6
10.6 43.6 151 54.8 45.2
In experiment 2 again a non-linear relationship between the sugar levels and the flavour acceptability response was found (Fig. 2). At the lowest sugar level (level 1) acceptability was higher, when the acid level was low (level 1). At higher sugar levels (levels 2 and 3) increased acid concentration was accepted. The acceptability curve seemed to be shifted to higher sugar values, when acid was elevated. To visualise the relation between sugar and acid levels and consumer acceptability, a response surface depending
on the sugar and acid concentrations was calculated (Eq. (1)). The best fit with the data was achieved with the quadratic polynomial z ¼ 67:47 þ 471:72x þ 12:9xy þ 2:30y 459:11x2 0:91y 2 ð1Þ where z is the consumer acceptance response; x is the acid concentration and y is the sugar concentration both given in g/100 g FM.
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Flavour acceptability (0-100)
80
70
60
50 A
B
C
D
Diced tomato sample
Fig. 1. Results of the consumer test in experiment 1. Mean acceptability scores of the four tomato samples. The bars indicate the 95% confidence interval.
90
Flavour acceptability (0-100)
80
70
60 95% Conf. interv. Acid level 1 95% Conf. interv. 50
Acid level 2 1.00
2.00
3.00
Added sugar levels
Fig. 2. Results of the consumer test in experiment 2. Mean acceptability scores of the six tomato samples. The bars indicate the 95% confidence interval. The solid line represents the low acid level (level 1), the dotted line acid level 2.
The resulting graph is shown as a contour plot in Fig. 3. Starting from low levels, increased sugar levels and increased acid levels led to higher acceptability until an optimum area (4.5–6.5 g sugar/100 g FM; 540–640 mg acid/100 g FM) is reached. Beyond these values acceptability decreased again.
Despite the clear sample separation by the average of the consumers, there was substantial variation between the consumers. A k-means cluster analysis was applied to identify consumer groups with similar preferences with respect to the samples presented. Fig. 4 shows the cluster means for three clusters found to differ in flavour
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Sugar concentration (g /100g FM)
8.5
7.5 62 6.5
5.5
64 66 68 70 72
74
4.5
76
3.5
2.5 400
440
480
520 560 600 640 Acid concentration (mg /100g FM)
680
720
Fig. 3. Contour plot showing the consumer scores for acceptability on a 0–100 line scale depending on acid and sugar concentrations. Mean of all consumers.
100
Flavour acceptability (0-100)
80
60
40 Cluster No. 1 Cluster No. 2 Cluster No. 3
20
0
A
B C Diced tomato samples
D
Fig. 4. Results of the consumer test for acceptability of samples A–D in experiment 1. The different symbols represent the means of the members of each cluster.
acceptability in experiment 1. The largest cluster (cluster 1) combining 43% of the consumers quoted high acceptability values and did not differentiate between the samples. The second largest cluster (cluster 2, 31%), clearly disliked the sweetest and low acidic samples A and B, whereas cluster members of cluster 3 (25%) disliked the least sweet and most acidic sample. Also in experiment 2 three different consumer clusters were identified. The largest cluster 1 (45%) rated all samples between 86 and 91. Members of cluster 2 (29%) disliked the sweetest samples, whereas members of cluster 3 (26%) disliked the least sweet samples, even more so at the higher acid level (Fig. 5). Instead of the average consumer acceptability response, as presented in Fig. 3, the mean acceptability scores of the
clusters were plotted as a function of sugar and acid concentrations. Because the members of cluster 1 did not respond very much to different sugar and acid levels, no response plot was calculated for this cluster. Fig. 6 shows the response of cluster 2 members, who preferred less sweet tomatoes. The fitted regression equation (Eq. (2)) was z ¼ 143:89 þ 983:68x þ 30:85xy þ 24:60y 964:15x2 0:16y 2
ð2Þ
where z is the consumer acceptance response; x is the acid concentration and y is the sugar concentration both given in g/100 g FM. For a wide range of acid concentrations from approximately 480–630 mg/100 g FM the highest acceptability
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85 lower acid level
Flavour acceptability (0-100)
75 higher acid level 65 higher acid level
55
45 Cl. 3 A1 Cl. 3 A2
lower acid level
35
Cl. 2 A1 Cl. 2 A2
25 C/F
B/E Added sugar level
A/D
Fig. 5. Results of the consumer test for acceptability of samples A–F with low (C, F), intermediate (B, E) and high (A, D) sugar levels in experiment 2. The different symbols represent the means of the members of cluster 2 (circles) and cluster 3 (diamonds) at low (dotted line, A1) and high (solid line, A2) acid level.
Sugar concentration (g /100g FM)
8.5
7.5
31
23
38 46
6.5 54 5.5
62
4.5
69
3.5
2.5 400
77
440
480
520 560 600 640 Acid concentration (mg /100g FM)
680
720
Fig. 6. Contour plot showing the consumer scores for acceptability depending on acid and sugar concentrations. Only members of cluster 2 were included.
was calculated, when the sugar concentrations were in the area of 2.5–3.0 g/100 g. Members of cluster 3 preferred sweet tomatoes with sugar contents of approximately 6.5 g/100 g FM. The response surface was fitted with the (Eq. (3)) and plotted in Fig. 7. Different acid concentrations had almost no effect on the acceptability of the fruit in this consumer cluster. z ¼ 294:97 þ 720:81x 10:12xy þ 58:35y 614:94x2 4:13y 2
ð3Þ
where z is the consumer acceptance response; x is the acid concentration and y is the sugar concentration both given in g/100 g FM. To identify characteristics of the consumers combined in each cluster, the age, weight, body length and gender distri-
bution data were analysed. No significant differences could be found between the cluster means except the higher percentage of boys in cluster 3 in experiment 1 and the higher percentage of girls in cluster 2 in both experiments (Table 4). Solutions, which contained citric acid or the 11/14 glucose/fructose mixture in concentrations, similar to those in the tomato dices were presented to all children in the consumer test of experiment 2. The acceptability scores assigned to the acid concentrations were not significantly different between the consumer clusters, which were set up by tomato acceptability data (Table 5). But the acceptability of sugar solutions clearly differed between the cluster mean scores. For the members of cluster 3, who preferred sweeter tomato samples, also the sugar solutions were significantly more acceptable than for the members of cluster 2.
158
B. Brueckner et al. / Food Quality and Preference 18 (2007) 152–160 8.5
Sugar concentration (g /100g)
7.5
6.5 77
5.5
70 63
4.5
56 49 41
3.5 34 27 2.5 400
440
480
520 560 600 640 Acid concentration (mg /100g FM)
680
720
Fig. 7. Contour plot showing the consumer scores for acceptability depending on acid and sugar concentrations. Only members of cluster 1 were included.
Table 5 Acceptability of acid and sugar solutions within the consumer clusters, which were assigned according to the results of tomato acceptability test Acceptability Cluster 1
Cluster 2
Cluster 3
Citric acid solution 0.1% 0.2% 0.5%
49.9 n.s. 47.4 n.s. 40.7 n.s.
46.9 n.s. 39.0 n.s. 35.5 n.s.
42.1 n.s. 44.0 n.s. 37.0 n.s.
Glucose/fructose solution 2.0% 5.0% 8.0%
65.4 b+ 61.7 b 57.7 b
39.3 a 32.7 a 33.2 a
71.7 b 60.3 b 49.8 ab
+
Values with different alphabet letters in a row are significantly different at p < 0.05.
4. Discussion From this study there is clear evidence that sugar and acid concentration levels affect the taste properties of tomato fruit. It has been shown previously (Malundo et al., 1995; Stevens, Kader, & Albright, 1979), that sugar levels determined the sweetness and acid levels determined sourness in tomatoes. In some studies also acidity (determined as acid content, pH or titratable acid) not only influenced sourness, but also sweetness (Jones & Scott, 1984; Kader, Stevens, Albrightholton, Morris, & Algazi, 1977; Stevens, 1997; Stevens, Kader, Albright-Holton, & Algazi, 1977). Malundo et al. (1995) hypothesised, that panels differ in their ability to discriminate between acidity and sweetness. But reduced sweetness in presence of more acidity may also be caused by mixture suppression, which has been documented for all four classical taste qualities (Lawless & Heymann, 1998). In the present study sweet taste was only affected by sugar level and not by acid level, but sour taste was not only influenced by acid, but also by sugar level. One reason for this one sided masking effect may be the concentration range involved in the experi-
ments, which may have been larger for sugars, than for acid in this work. The intensity of the flavour quality ‘‘tomato-like’’ was not significantly influenced by sugar or acid concentrations. This is consistent with earlier findings, where this flavour quality has been attributed to a complex characteristic (Kader et al., 1977) or to volatile compounds (Krumbein, Peters, & Bruckner, 2004; Stevens et al., 1979). The results of the consumer tests show, that acceptability of the tomato samples could be improved, when the concentration of reducing sugars was increased from 3 g/ 100 g FM to about 4 or 5 g/100 FM. A further augmentation of the sugar concentration led to reduced acceptability. The role of acid concentration could not be assessed independently in experiment 1. The combination of increasing sugar values with decreasing acid concentrations was selected, to uncouple effects of absolute sugar and acid contents from the situation of constant sugar/acid ratio. The ratios implemented in this experiment ranged from 4.8 to 15.0. The intermediate values were the most acceptable. From experiment 2 it can be concluded, that increased acid can affect acceptability negatively at a lower
B. Brueckner et al. / Food Quality and Preference 18 (2007) 152–160
sugar level, whereas no negative effect was seen at intermediate sugar level. In this case the acceptability was assessed at different sugar/acid ratios. The optimal sugar concentration was surpassed at the highest sugar level at both acid concentrations in the tested range. It is important to note, that for both, sugar and acid level a maximum value for acceptability was found; beyond these values acceptability decreased again. This confirms the expected, inverted ‘‘U’’ shaped curve for acceptability as a function of a stimulus (Meilgaard, Civille, & Carr, 1991), which, in this experiment, could be drawn in two dimensions (sugar and acid concentrations). Visualised in Fig. 3, the changing shape of the curve (e.g. over sugar concentration) at different levels of the second factor (e.g. acid concentration) can be seen. The negative effect of high acid concentrations, depending on the sugar level was also emphasised in the study of Malundo et al. (1995) with adults, but they could not identify an ‘‘ideal’’ sugar concentration in their experiment, probably because the tested total sugar contents were lower. When trying to vary food ingredients to optimise acceptability, the target group is important, and even within a target group consumers are considerably diverse with respect to their preferences (Greenhoff & MacFie, 1994; Moskowitz, 2002). Pagliarini, Monteleone, and Ratti (2001) reported two distinct consumer groups among the adult population based on preferences for different tomato cultivars. The first group preferred cultivars, that were red and sweet, while the second group preferred fruit, that were acidic and had certain texture characteristics. Similar results were also found by Bru¨ckner (2000) and Bru¨ckner and Auerswald (2000), but in addition there was a large segment of consumers, which did not respond very much to different sensory magnitudes. In both experiments with children reported here, three consistently different clusters could be separated. It is noticeable, that in both experiments the largest group consisted of children, who reported very high acceptability of the tomato samples, but did not distinguish between the sugar or acid levels. This seems to be not because they were not able to distinguish between the samples. This is indicated by the fact, that there was some differentiation in acceptability between sugar and acid solutions (Table 5), but not in the tomato samples with comparable concentrations of sugars and acids. The second largest cluster of children rated fruit samples less acceptable when sugar contents exceeded approximately 3 g/100 g FM but did respond to changed acidity only at very low or very high concentration. The assumption, that members of this cluster mainly tried to avoid too much sweetness is confirmed by the results from solution testing. The response to the citric acid solutions was not different from response of other cluster members, but acceptability of sugar solutions was significantly lower. The members of the smallest cluster preferred tomato samples with very high sugar concentrations and this inde-
159
pendent from acid levels over a very wide range. Like in the cluster before, the acid solutions were not rated different from the other cluster members, but sweet solutions were liked significantly more. An important result from this study is the finding, that more than half of the tested children (members of cluster 2 and 3) clearly preferred tomatoes of certain sugar acid combinations. Differences in acceptability were caused mainly by the sugar contents. There was no common concentration level for highest acceptability of all clustersÕ members, whereas an optimal acid concentration for all clusters could be found. This study demonstrates, that optimal composition of fresh fruit and vegetables is not a self-runner, but consumer studies can contribute to identify improved compound concentrations and combinations thereof. It also shows that assumption of an optimal quality is delusive, if the target group and its segments are not understood in detail. References Boehringer Mannheim. (1986). Biochemica. Methoden der biochemischen Analytik und Lebensmittelanalytik. 37–38. (GENERIC) Ref Type: Report. Bru¨ckner, B. (2000). Acceptability of tomatoes defined by sensory attributes and consumer segments. In W. J. Forkowski, S. E. Prussia, & R. L. Shewfelt (Eds.), Integrated view of fruit and vegetable quality (pp. 229–240). Lancaster. PA, USA: Technomic Publishing. Bru¨ckner, B., & Auerswald, H. (2000). Instrumental data—consumer acceptance. In R. L. Shewfelt & B. Bru¨ckner (Eds.), Fruit and vegetable quality: An integrated view (pp. 178–198). Lancaster. PA, USA: Technomic Publishing. Greenhoff, K., & MacFie, H. J. H. (1994). Preference mapping in practice. In H. J. H. MacFie & D. M. H. Thomson (Eds.), Measurement of food preferences (pp. 137–166). Glasgow: Chapman & Hall. Jones, R. A., & Scott, S. J. (1984). Genetic potential to improve tomato flavor in commercial F1-hybrids. Journal of the American Society for Horticultural Science, 109, 318–321. Kader, A. A., Stevens, M. A., Albrightholton, M., Morris, L. L., & Algazi, M. (1977). Effect of fruit ripeness when picked on flavor and composition in fresh market tomatoes. Journal of the American Society for Horticultural Science, 102, 724–731. Krumbein, A., Peters, P., & Bruckner, B. (2004). Flavour compounds and a quantitative descriptive analysis of tomatoes (Lycopersicon esculentum Mill) of different cultivars in short-term storage. Postharvest Biology and Technology, 32, 15–28. Lawless, H. T., & Heymann, H. (1998). Psychological and psychophysical foundations of sensory function. In H. T. Lawless & H. Heymann (Eds.), Sensory evaluation of food—principles and practices (pp. 28–82). New York: Chapman & Hall. LMBG. (1983). Bestimmung des Gesamtsa¨uregehaltes von Tomatenmark (potentiometrische Methode) (Amtliche Sammlung von Untersuchungsverfahren nach § 35 LMBG). L26 11, 3–4. (GENERIC). Malundo, T. M. M., Shewfelt, R. L., & Scott, J. W. (1995). Flavour quality of fresh tomato (Lycopersicon esculentum Mill) as affected by sugar and acid levels. Postharvest Biology and Technology, 6, 103–110. Meilgaard, M., Civille, G. E., & Carr, T. (1991). Sensory evaluation techniques. Boca Raton, New York: CRC Press. Moskowitz, H. R. (2002). Sensory drivers of liking and sensory preference segmentation. Chemistry of taste: Mechanisms, behaviors, and mimics, 825, 214–226. Pagliarini, E., Monteleone, E., & Ratti, S. (2001). Sensory profile of eight tomato cultivars (Lycopersicon esculentum) and its relationship to consumer preference. Italian Journal of Food Science, 13, 285–296.
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Stevens, J. C. (1997). Detection of very complex taste mixtures: Generous integration across constituent compounds. Physiology & Behavior, 62, 1137–1143. Stevens, M. A., Kader, A. A., Albright-Holton, M., & Algazi, M. (1977). Genotypic variation for flavor and composition in fresh market tomatoes. Journal of the American Society for Horticultural Science, 102, 680–689.
Stevens, M. A., Kader, A. A., & Albright, M. (1979). Potential for increasing tomato flavor via increased sugar and acid content. Journal of the American Society for Horticultural Science, 104, 40–42. Stone, H., & Sidel, J. L. (1993). Sensory evaluation practices. San Diego: Academic Press.
Improved flavour acceptability of cherry tomatoes. Target group: Children B. Brueckner a
a,*
, I. Schonhof a, R. Schroedter b, C. Kornelson
b
Institute for Vegetable and Ornamental Crops, Theodor-Echtermeyer-Str. 1, 14979 Grossbeeren, Germany b Prosens Inc., Germany Arthur-Scheunert-Allee 40/41, 14558 Nuthetal, Germany Accepted 12 September 2005 Available online 26 October 2005
Abstract Acceptability of tomato fruit flavour was investigated. To vary flavour, contents of glucose, fructose and citric acid were added to diced fruit, resulting a range of 3 to 8 g reducing sugars/100 FM and 430–700 mg titratable acid/100 g FM. Significant sweetness and sourness changes were determined by descriptive analysis, tomato-like flavour remained unchanged. Consumer tests with children aged 7–11 years were used to rate flavour acceptability. Most accepted combinations of acid and sugar were identified (4.5–6.5 g sugar/100 g FM; 540–640 mg acid/100 g FM). Cluster analysis allowed to separate three clusters with different response to sugars and acid concentrations. Forty five percent of the children did not respond, 30% liked low sugar concentrations (<3 g/100 g FM) most, 25% preferred 6.5 g/100 g FM at a wide range of acid concentrations. There was little evidence of differences with respect to gender, age, body weight and length between the cluster members, but the liking of sweet and acidic solutions differed. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Tomato fruit; Reducing sugars; Citric acid; Taste; Flavour; Children; Acceptability; Vegetable
1. Introduction Fruit and vegetable intake of children and teenagers is even lower then the intake of adults. Cognitive information (on health issues) is picked up by children, but effect-less for nutritional behaviour. To increase vegetable consumption, reference to consumersÕ wants and needs must be taken (German Nutrition Report 2000), the role of improved acceptability of flavour of fresh fruit and vegetables is emphasised. The aim of this study was to specify important criteria for flavour quality of cherry tomatoes as an example to improve acceptability of this fruit flavour for children. In a previous study with adults (Malundo, Shewfelt, & Scott, 1995) it was demonstrated, that the liking of tomato flavour could be enhanced by varying sugar and acid content. *
Corresponding author. Fax: +49 33701 55391. E-mail address: [email protected] (B. Brueckner).
0950-3293/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2005.09.011
No upper limit for sugar concentration was found. No similar experiments with children exist. Another important question is not yet answered in the literature: whether segments with respect to flavour preferences exist among children and how attributes must be like to meet the preferences of each segmentsÕ members. 2. Material and methods 2.1. Sample preparation Round, conventional tomato fruit of a single cultivar were picked in November 2002 at uniform size and colour (stage 9 at CBT colour chart) and shipped directly to the institute (experiment 1) by a greenhouse grower near Potsdam, Germany or, as in experiment 2, fruit were picked in December 2003 from a grower in Den Hoorn, The Netherlands and shipped to the EDEKATM distribution centre close to the institute. Fruit were stored at 12 ± 1 °C, until
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they were used for preparing the samples within three days. When needed, fruit were cut into dices of an edge length of 1 cm. Fructose and glucose were mixed at the ratio of 14/11 and were dissolved in distilled water to form the stock solution containing 50% of reducing sugars. Citric acid was dissolved in distilled water for a 25% acid stock solution. Stock solutions were kept in the refrigerator at 10 °C for no longer than one day. Three hours before the sensory analysis 150 ml of a solution prepared from the stock solutions and distilled water were given to 850 g of the diced fruit. The mixture was kept at 10 °C for 2.5 h prior to packing into 125 ml closed plastic containers at 20–25 g each. At this time two sub-samples of 50 g each were taken for the chemical analyses.
To evaluate the flavour acceptability of the diced tomato samples, consumer tests with a total of 163 children (experiment 1) and 121 children (experiment 2) were conducted. The age varied from 7–11 years. Body weight and height were recorded. Each child evaluated each of the four (experiment 1) or six (experiment 2) samples. In experiment 2 also 20 ml solutions of 0%, 0.1%, 0.2% and 0.5% citric acid and 0%, 2.0%, 5.0% and 8.0% glucose and fructose (mixture: 11 parts glucose/14 parts fructose) were given to all children for acceptability testing. The trained panel and the consumer panel worked in a sensory laboratory under defined (temperature and light) conditions single cabins with computer equipment. Data acquisition was carried out with the computer program CASA (Computer Aided Sensory Analysis).
2.2. Chemical analyses
2.4. Statistical analyses
The acid and sugar analyses were carried out as double estimations per sample with 50 g of homogenised and frozen (32 °C) tomatoes each. The material thawed quickly and boiled for 5 min with 100 ml deionised water. After cooling, the tomato sample was diluted to 250 ml with deionised water and filtered. The content of titratable acid was determined by a potentiometric titration with 0.1 M NaOH (LMBG, 1983) using 50 ml filtrate. The sugar contents were measured by the enzymatic detection of glucose and fructose, summarised as reducing sugars. The filtrate (5 ml) was diluted to 100 ml with deionised water. A 100 ll sample was assayed with an enzymatic test kit (Boehringer Mannheim, 1986) where reduced nicotinamide-adenine-dinucleotide-phosphate (NADPH) was formed during the reaction of the reducing sugars with hexokinase, adenosine-5-triphosphate, nicotinamideadenine-di-nucleotide-phosphate (NADP), glucose 6-phosphate-dehydrogenase and phosphoglucose-isomerase. The absorbance of NADPH was measured spectrophotometrically (Spekol 221, Carl Zeiss, Jena) at 340 nm. The results were converted to grams of fresh matter.
The data were analysed using the software packages Statistica v.4.1 (Statsoft), and SPSS v.7.5 (SPSS Inc.). Analytical data were subject to ANOVA and Tuckey-Test at the significance level stated. Multiple regression analysis, cluster analysis and response surface analysis were calculated with the corresponding modules of the Statistical package.
2.3. Sensory evaluation The descriptive sensory analysis was conducted to characterise the attributes of the prepared tomato material using a trained panel similar to the method of (Stone & Sidel, 1993). Eight judges were selected who had successfully passed standardised tests for olfactory, taste and colour sensibility as well as for commemoration, verbal abilities and creativity. Approximately 20 h training over a 10-week period for establishing the methodological foundations was followed by another 20 h training with tomato fruit. Fruit dices were presented individually and in random order in closed 125 ml plastic cups. A four digit code was assigned to the samples. The flavour terms sweet, sour and tomato-like were assessed using unstructured line scales with the anchor points 0—not perceptible and 100—strongly perceptible.
3. Results The chemical analysis of the four treatments in experiment 1 showed, that part of the added reducing sugars and titratable acid was absorbed by the tomato dices (Table 1). In untreated tomato dices, the contents was 2.00 g of reducing sugars/100 g and 411 mg titratable acids/100 g. Between the treatments, the amounts were clearly differentiated, though not statistically significant in case of acid contents between treatment B and C in experiment 1. Also, in experiment 2 the contents of reducing sugars and titratable acids could be increased by adding sugars and acid to the tomato dices (Table 2). The untreated material contained was 2.25 g of reducing sugars/100 g FM and 417 mg titratable acids/100 g FM. The content of absorbed acid was independent from the amount of added sugar, but less sugars were absorbed in the higher acid treatments. The increased sugar contents in diced tomatoes of both experiments increased the intensity of sweetness assessed by the descriptive panel. There was a significant, linear relationship (Table 3). No significant effect of added acidity on perceived sweetness was found. Both, sugar and acid level significantly affected sourness, but had no influence on tomato-like flavour (see Table 3). The consumers clearly distinguished the samples in experiment 1 because of their different flavour acceptability (Fig. 1). High acceptability scores were given to the samples B and C with intermediate sugar and acid levels. Samples A, the sweetest sample wit the lowest amount of acid was liked least, also, the most acidic and least sweet sample D was sub-optimal.
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Table 1 Amount of added reducing sugars and citric acid and measured average contents of reducing sugars and titratable acids in the four treatments (A–D) of experiment 1 Added sugars (g/100 g)/acid (g/100 g) A 6.5/0.1
B 5.0/0.2
C 3.5/0.3
D 2.0/0.4
Reducing sugars 6.01 d+ Titratable acids 433 a
Reducing sugars 4.99 c Titratable acids 512 b
Reducing sugars 3.92 b Titratable acids 565 b
Reducing sugars 3.05 a Titratable acids 641 c
+
Values with different alphabet letters are significantly different at p < 0.05 (separately for sugars and acids).
Table 2 Amount of added reducing sugars and citric acid and measured average contents of reducing sugars and titratable acids in the six treatments (A–F) of experiment 2 Added acid (g/100 g)
Added sugars (g/100 g) 8
5
2
0.2
A Reducing sugars 7.65 e+ Titratable acids 500 b
B Reducing sugars 5.27 c Titratable acids 484 a
C Reducing sugars 3.37 a Titratable acids 499 b
0.5
D Reducing sugars 6.79 d Titratable acids 685 d
E Reducing sugars 4.73 b Titratable acids 675 c
F Reducing sugars 3.09 a Titratable acids 695 e
+
Values with different alphabet letters are significantly different at p < 0.05 (separately for sugars and acids).
Table 3 Multiple regression results of descriptive attributes and sugar and acid content levels Variable Sweet Sour Tomato-like ** ***
R2
Intercept
0.837 0.979 0.230
Sugar level beta **
32.88 24.58 53.06
+0.814 0.634*** 0.387 n.s.
B
Acid level beta
B
7.75 5.16 0.99
0.235 n.s. +0.588*** 0.188 n.s.
0.037 0.078 0.008
Significant at p < 0.01. Significant at p < 0.001.
Table 4 Average physical characteristics of the consumer panelists averaged according to the cluster membership Experiment 1, 2002
Age (years) Weight (kg) Length (cm) Girls (%) Boys (%)
Experiment 2, 2003
Mean
Cluster 1
Cluster 2
Cluster 3
Mean
Cluster 1
Cluster 2
Cluster 3
9.5 36.2 144 50.9 49.1
9.4 35.9 143 51.4 48.6
9.6 35.5 144 60.8 39.2
9.5 37.4 147 36.6 63.4
10.7 43.7 150 53.7 46.3
10.5 42.6 149 41.8 58.2
10.9 45.5 150 71.4 28.6
10.6 43.6 151 54.8 45.2
In experiment 2 again a non-linear relationship between the sugar levels and the flavour acceptability response was found (Fig. 2). At the lowest sugar level (level 1) acceptability was higher, when the acid level was low (level 1). At higher sugar levels (levels 2 and 3) increased acid concentration was accepted. The acceptability curve seemed to be shifted to higher sugar values, when acid was elevated. To visualise the relation between sugar and acid levels and consumer acceptability, a response surface depending
on the sugar and acid concentrations was calculated (Eq. (1)). The best fit with the data was achieved with the quadratic polynomial z ¼ 67:47 þ 471:72x þ 12:9xy þ 2:30y 459:11x2 0:91y 2 ð1Þ where z is the consumer acceptance response; x is the acid concentration and y is the sugar concentration both given in g/100 g FM.
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Flavour acceptability (0-100)
80
70
60
50 A
B
C
D
Diced tomato sample
Fig. 1. Results of the consumer test in experiment 1. Mean acceptability scores of the four tomato samples. The bars indicate the 95% confidence interval.
90
Flavour acceptability (0-100)
80
70
60 95% Conf. interv. Acid level 1 95% Conf. interv. 50
Acid level 2 1.00
2.00
3.00
Added sugar levels
Fig. 2. Results of the consumer test in experiment 2. Mean acceptability scores of the six tomato samples. The bars indicate the 95% confidence interval. The solid line represents the low acid level (level 1), the dotted line acid level 2.
The resulting graph is shown as a contour plot in Fig. 3. Starting from low levels, increased sugar levels and increased acid levels led to higher acceptability until an optimum area (4.5–6.5 g sugar/100 g FM; 540–640 mg acid/100 g FM) is reached. Beyond these values acceptability decreased again.
Despite the clear sample separation by the average of the consumers, there was substantial variation between the consumers. A k-means cluster analysis was applied to identify consumer groups with similar preferences with respect to the samples presented. Fig. 4 shows the cluster means for three clusters found to differ in flavour
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Sugar concentration (g /100g FM)
8.5
7.5 62 6.5
5.5
64 66 68 70 72
74
4.5
76
3.5
2.5 400
440
480
520 560 600 640 Acid concentration (mg /100g FM)
680
720
Fig. 3. Contour plot showing the consumer scores for acceptability on a 0–100 line scale depending on acid and sugar concentrations. Mean of all consumers.
100
Flavour acceptability (0-100)
80
60
40 Cluster No. 1 Cluster No. 2 Cluster No. 3
20
0
A
B C Diced tomato samples
D
Fig. 4. Results of the consumer test for acceptability of samples A–D in experiment 1. The different symbols represent the means of the members of each cluster.
acceptability in experiment 1. The largest cluster (cluster 1) combining 43% of the consumers quoted high acceptability values and did not differentiate between the samples. The second largest cluster (cluster 2, 31%), clearly disliked the sweetest and low acidic samples A and B, whereas cluster members of cluster 3 (25%) disliked the least sweet and most acidic sample. Also in experiment 2 three different consumer clusters were identified. The largest cluster 1 (45%) rated all samples between 86 and 91. Members of cluster 2 (29%) disliked the sweetest samples, whereas members of cluster 3 (26%) disliked the least sweet samples, even more so at the higher acid level (Fig. 5). Instead of the average consumer acceptability response, as presented in Fig. 3, the mean acceptability scores of the
clusters were plotted as a function of sugar and acid concentrations. Because the members of cluster 1 did not respond very much to different sugar and acid levels, no response plot was calculated for this cluster. Fig. 6 shows the response of cluster 2 members, who preferred less sweet tomatoes. The fitted regression equation (Eq. (2)) was z ¼ 143:89 þ 983:68x þ 30:85xy þ 24:60y 964:15x2 0:16y 2
ð2Þ
where z is the consumer acceptance response; x is the acid concentration and y is the sugar concentration both given in g/100 g FM. For a wide range of acid concentrations from approximately 480–630 mg/100 g FM the highest acceptability
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85 lower acid level
Flavour acceptability (0-100)
75 higher acid level 65 higher acid level
55
45 Cl. 3 A1 Cl. 3 A2
lower acid level
35
Cl. 2 A1 Cl. 2 A2
25 C/F
B/E Added sugar level
A/D
Fig. 5. Results of the consumer test for acceptability of samples A–F with low (C, F), intermediate (B, E) and high (A, D) sugar levels in experiment 2. The different symbols represent the means of the members of cluster 2 (circles) and cluster 3 (diamonds) at low (dotted line, A1) and high (solid line, A2) acid level.
Sugar concentration (g /100g FM)
8.5
7.5
31
23
38 46
6.5 54 5.5
62
4.5
69
3.5
2.5 400
77
440
480
520 560 600 640 Acid concentration (mg /100g FM)
680
720
Fig. 6. Contour plot showing the consumer scores for acceptability depending on acid and sugar concentrations. Only members of cluster 2 were included.
was calculated, when the sugar concentrations were in the area of 2.5–3.0 g/100 g. Members of cluster 3 preferred sweet tomatoes with sugar contents of approximately 6.5 g/100 g FM. The response surface was fitted with the (Eq. (3)) and plotted in Fig. 7. Different acid concentrations had almost no effect on the acceptability of the fruit in this consumer cluster. z ¼ 294:97 þ 720:81x 10:12xy þ 58:35y 614:94x2 4:13y 2
ð3Þ
where z is the consumer acceptance response; x is the acid concentration and y is the sugar concentration both given in g/100 g FM. To identify characteristics of the consumers combined in each cluster, the age, weight, body length and gender distri-
bution data were analysed. No significant differences could be found between the cluster means except the higher percentage of boys in cluster 3 in experiment 1 and the higher percentage of girls in cluster 2 in both experiments (Table 4). Solutions, which contained citric acid or the 11/14 glucose/fructose mixture in concentrations, similar to those in the tomato dices were presented to all children in the consumer test of experiment 2. The acceptability scores assigned to the acid concentrations were not significantly different between the consumer clusters, which were set up by tomato acceptability data (Table 5). But the acceptability of sugar solutions clearly differed between the cluster mean scores. For the members of cluster 3, who preferred sweeter tomato samples, also the sugar solutions were significantly more acceptable than for the members of cluster 2.
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Sugar concentration (g /100g)
7.5
6.5 77
5.5
70 63
4.5
56 49 41
3.5 34 27 2.5 400
440
480
520 560 600 640 Acid concentration (mg /100g FM)
680
720
Fig. 7. Contour plot showing the consumer scores for acceptability depending on acid and sugar concentrations. Only members of cluster 1 were included.
Table 5 Acceptability of acid and sugar solutions within the consumer clusters, which were assigned according to the results of tomato acceptability test Acceptability Cluster 1
Cluster 2
Cluster 3
Citric acid solution 0.1% 0.2% 0.5%
49.9 n.s. 47.4 n.s. 40.7 n.s.
46.9 n.s. 39.0 n.s. 35.5 n.s.
42.1 n.s. 44.0 n.s. 37.0 n.s.
Glucose/fructose solution 2.0% 5.0% 8.0%
65.4 b+ 61.7 b 57.7 b
39.3 a 32.7 a 33.2 a
71.7 b 60.3 b 49.8 ab
+
Values with different alphabet letters in a row are significantly different at p < 0.05.
4. Discussion From this study there is clear evidence that sugar and acid concentration levels affect the taste properties of tomato fruit. It has been shown previously (Malundo et al., 1995; Stevens, Kader, & Albright, 1979), that sugar levels determined the sweetness and acid levels determined sourness in tomatoes. In some studies also acidity (determined as acid content, pH or titratable acid) not only influenced sourness, but also sweetness (Jones & Scott, 1984; Kader, Stevens, Albrightholton, Morris, & Algazi, 1977; Stevens, 1997; Stevens, Kader, Albright-Holton, & Algazi, 1977). Malundo et al. (1995) hypothesised, that panels differ in their ability to discriminate between acidity and sweetness. But reduced sweetness in presence of more acidity may also be caused by mixture suppression, which has been documented for all four classical taste qualities (Lawless & Heymann, 1998). In the present study sweet taste was only affected by sugar level and not by acid level, but sour taste was not only influenced by acid, but also by sugar level. One reason for this one sided masking effect may be the concentration range involved in the experi-
ments, which may have been larger for sugars, than for acid in this work. The intensity of the flavour quality ‘‘tomato-like’’ was not significantly influenced by sugar or acid concentrations. This is consistent with earlier findings, where this flavour quality has been attributed to a complex characteristic (Kader et al., 1977) or to volatile compounds (Krumbein, Peters, & Bruckner, 2004; Stevens et al., 1979). The results of the consumer tests show, that acceptability of the tomato samples could be improved, when the concentration of reducing sugars was increased from 3 g/ 100 g FM to about 4 or 5 g/100 FM. A further augmentation of the sugar concentration led to reduced acceptability. The role of acid concentration could not be assessed independently in experiment 1. The combination of increasing sugar values with decreasing acid concentrations was selected, to uncouple effects of absolute sugar and acid contents from the situation of constant sugar/acid ratio. The ratios implemented in this experiment ranged from 4.8 to 15.0. The intermediate values were the most acceptable. From experiment 2 it can be concluded, that increased acid can affect acceptability negatively at a lower
B. Brueckner et al. / Food Quality and Preference 18 (2007) 152–160
sugar level, whereas no negative effect was seen at intermediate sugar level. In this case the acceptability was assessed at different sugar/acid ratios. The optimal sugar concentration was surpassed at the highest sugar level at both acid concentrations in the tested range. It is important to note, that for both, sugar and acid level a maximum value for acceptability was found; beyond these values acceptability decreased again. This confirms the expected, inverted ‘‘U’’ shaped curve for acceptability as a function of a stimulus (Meilgaard, Civille, & Carr, 1991), which, in this experiment, could be drawn in two dimensions (sugar and acid concentrations). Visualised in Fig. 3, the changing shape of the curve (e.g. over sugar concentration) at different levels of the second factor (e.g. acid concentration) can be seen. The negative effect of high acid concentrations, depending on the sugar level was also emphasised in the study of Malundo et al. (1995) with adults, but they could not identify an ‘‘ideal’’ sugar concentration in their experiment, probably because the tested total sugar contents were lower. When trying to vary food ingredients to optimise acceptability, the target group is important, and even within a target group consumers are considerably diverse with respect to their preferences (Greenhoff & MacFie, 1994; Moskowitz, 2002). Pagliarini, Monteleone, and Ratti (2001) reported two distinct consumer groups among the adult population based on preferences for different tomato cultivars. The first group preferred cultivars, that were red and sweet, while the second group preferred fruit, that were acidic and had certain texture characteristics. Similar results were also found by Bru¨ckner (2000) and Bru¨ckner and Auerswald (2000), but in addition there was a large segment of consumers, which did not respond very much to different sensory magnitudes. In both experiments with children reported here, three consistently different clusters could be separated. It is noticeable, that in both experiments the largest group consisted of children, who reported very high acceptability of the tomato samples, but did not distinguish between the sugar or acid levels. This seems to be not because they were not able to distinguish between the samples. This is indicated by the fact, that there was some differentiation in acceptability between sugar and acid solutions (Table 5), but not in the tomato samples with comparable concentrations of sugars and acids. The second largest cluster of children rated fruit samples less acceptable when sugar contents exceeded approximately 3 g/100 g FM but did respond to changed acidity only at very low or very high concentration. The assumption, that members of this cluster mainly tried to avoid too much sweetness is confirmed by the results from solution testing. The response to the citric acid solutions was not different from response of other cluster members, but acceptability of sugar solutions was significantly lower. The members of the smallest cluster preferred tomato samples with very high sugar concentrations and this inde-
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pendent from acid levels over a very wide range. Like in the cluster before, the acid solutions were not rated different from the other cluster members, but sweet solutions were liked significantly more. An important result from this study is the finding, that more than half of the tested children (members of cluster 2 and 3) clearly preferred tomatoes of certain sugar acid combinations. Differences in acceptability were caused mainly by the sugar contents. There was no common concentration level for highest acceptability of all clustersÕ members, whereas an optimal acid concentration for all clusters could be found. This study demonstrates, that optimal composition of fresh fruit and vegetables is not a self-runner, but consumer studies can contribute to identify improved compound concentrations and combinations thereof. It also shows that assumption of an optimal quality is delusive, if the target group and its segments are not understood in detail. References Boehringer Mannheim. (1986). Biochemica. Methoden der biochemischen Analytik und Lebensmittelanalytik. 37–38. (GENERIC) Ref Type: Report. Bru¨ckner, B. (2000). Acceptability of tomatoes defined by sensory attributes and consumer segments. In W. J. Forkowski, S. E. Prussia, & R. L. Shewfelt (Eds.), Integrated view of fruit and vegetable quality (pp. 229–240). Lancaster. PA, USA: Technomic Publishing. Bru¨ckner, B., & Auerswald, H. (2000). Instrumental data—consumer acceptance. In R. L. Shewfelt & B. Bru¨ckner (Eds.), Fruit and vegetable quality: An integrated view (pp. 178–198). Lancaster. PA, USA: Technomic Publishing. Greenhoff, K., & MacFie, H. J. H. (1994). Preference mapping in practice. In H. J. H. MacFie & D. M. H. Thomson (Eds.), Measurement of food preferences (pp. 137–166). Glasgow: Chapman & Hall. Jones, R. A., & Scott, S. J. (1984). Genetic potential to improve tomato flavor in commercial F1-hybrids. Journal of the American Society for Horticultural Science, 109, 318–321. Kader, A. A., Stevens, M. A., Albrightholton, M., Morris, L. L., & Algazi, M. (1977). Effect of fruit ripeness when picked on flavor and composition in fresh market tomatoes. Journal of the American Society for Horticultural Science, 102, 724–731. Krumbein, A., Peters, P., & Bruckner, B. (2004). Flavour compounds and a quantitative descriptive analysis of tomatoes (Lycopersicon esculentum Mill) of different cultivars in short-term storage. Postharvest Biology and Technology, 32, 15–28. Lawless, H. T., & Heymann, H. (1998). Psychological and psychophysical foundations of sensory function. In H. T. Lawless & H. Heymann (Eds.), Sensory evaluation of food—principles and practices (pp. 28–82). New York: Chapman & Hall. LMBG. (1983). Bestimmung des Gesamtsa¨uregehaltes von Tomatenmark (potentiometrische Methode) (Amtliche Sammlung von Untersuchungsverfahren nach § 35 LMBG). L26 11, 3–4. (GENERIC). Malundo, T. M. M., Shewfelt, R. L., & Scott, J. W. (1995). Flavour quality of fresh tomato (Lycopersicon esculentum Mill) as affected by sugar and acid levels. Postharvest Biology and Technology, 6, 103–110. Meilgaard, M., Civille, G. E., & Carr, T. (1991). Sensory evaluation techniques. Boca Raton, New York: CRC Press. Moskowitz, H. R. (2002). Sensory drivers of liking and sensory preference segmentation. Chemistry of taste: Mechanisms, behaviors, and mimics, 825, 214–226. Pagliarini, E., Monteleone, E., & Ratti, S. (2001). Sensory profile of eight tomato cultivars (Lycopersicon esculentum) and its relationship to consumer preference. Italian Journal of Food Science, 13, 285–296.
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Stevens, J. C. (1997). Detection of very complex taste mixtures: Generous integration across constituent compounds. Physiology & Behavior, 62, 1137–1143. Stevens, M. A., Kader, A. A., Albright-Holton, M., & Algazi, M. (1977). Genotypic variation for flavor and composition in fresh market tomatoes. Journal of the American Society for Horticultural Science, 102, 680–689.
Stevens, M. A., Kader, A. A., & Albright, M. (1979). Potential for increasing tomato flavor via increased sugar and acid content. Journal of the American Society for Horticultural Science, 104, 40–42. Stone, H., & Sidel, J. L. (1993). Sensory evaluation practices. San Diego: Academic Press.