Optimal and acceptable levels of sweetness, sourness, firmness, mealiness and banana aroma in dessert banana (Musa sp.)

Scientia Horticulturae 211 (2016) 399–409

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Optimal and acceptable levels of sweetness, sourness, firmness, mealiness and banana aroma in dessert banana (Musa sp.) Christophe Bugaud a,∗ , Isabelle Maraval a , Marie-Odette Daribo b , Nathanaëlle Leclerc c , Frédéric Salmon d a

CIRAD, UMR QUALISUD, 73 rue Jean Franc¸ois Breton, F-34398 Montpellier Cedex 5, France CIRAD, UPR GECO, Campus agro-environnemental Caraïbe, Quartier Petit Morne, F-97285 Lamentin, Martinique, France c Institut Technique Tropical, F-97130 Capesterre-Belle-Eau, Guadeloupe, France d CIRAD, UMR AGAP, Station Neufchateau, Sainte Marie, F-97130 Capesterre-Belle-Eau, Guadeloupe, France b

a r t i c l e

i n f o

Article history: Received 8 July 2016 Received in revised form 12 September 2016 Accepted 14 September 2016 Keywords: Musa Hybrid Sensory attributes Acceptability Variety screening Just-About-Right

a b s t r a c t Acceptability criteria in dessert banana were investigated to enable sensory qualities to be taken into account earlier in the assessment of new banana hybrids in a selection scheme. Twelve banana cultivars were characterized by sensory profiling and physical-chemical analyses at a defined eating stage. The ‘right’ levels of sourness, sweetness, firmness, mealiness, and banana aroma were evaluated by 214 consumers on the ‘Just-About-Right’ scale. Optimal acceptance of a banana means at the most 20% of consumers judged the banana to be e.g. ‘too . . .’ or ‘not . . . enough’. The ideal banana received scores ranging between 6.1 and 6.7 for sweetness, between 2.8 and 3.3 for sourness, above 6.3 for banana aroma, between 3.7 and 4.7 for firmness and between 1.0 and 1.4 for mealiness on a discrete 0–9 scale, by titratable acidity of 5.5 meq 100 g−1 , or a pH of 4.9, and a pulp puncture force between 1.9 and 2.4 N. Acceptability thresholds were calculated when a maximum of 33% of consumers judged bananas to be e.g. ‘too . . .’ or ‘not . . . enough’. Screening new hybrids revealed the advantage of using an acceptability threshold of 33% of unsatisfied consumers as the first step, since after a hybrid has passed the acceptability threshold, crop management can be directed towards being as close as possible to the characteristics of the ideal banana. © 2016 Elsevier B.V. All rights reserved.

1. Introduction For more than half a century, genetic improvement programs have mainly targeted disease and pest resistant varieties (Ortiz et al., 1995). CIRAD (French research center working with developing countries to tackle international agricultural and development issues) has a breeding program that aims at extending the range of varieties that combine disease resistance with new quality characteristics. However, up to now, all the new hybrids have been rejected by breeders, producers and consumers because of either visual or sensorial flaws. It is thus important for breeders to have reliable tools to assess the quality of the hybrid sufficiently early in a selection scheme. A few studies on consumer preferences in dessert banana have compared cultivars at different stages of maturity (Eyabi et al., 2000; Garruti et al., 2013; Salvador et al., 2007), but none trans-

∗ Corresponding author. E-mail address: [email protected] (C. Bugaud). http://dx.doi.org/10.1016/j.scienta.2016.09.016 0304-4238/© 2016 Elsevier B.V. All rights reserved.

formed these preferences into measurable criteria that could be used by breeders. The sensory traits of dessert bananas were described in a previous paper (Bugaud et al., 2011). In that study, sweetness, sourness, firmness, mealiness and banana aroma were found to be the five most relevant attributes to describe the sensory variability of dessert banana cultivars. These sensory attributes are known to be important drivers of consumer preferences for fruits, and can be understood by consumers (Andani et al., 2001; Bonany et al., 2014; Causse et al., 2010; Harker et al., 2008; Jaeger et al., 1998; Lester, 2006; Matsuura et al., 2004). The aim of the present study was thus to identify the optimal and acceptable levels of the sensory traits in dessert bananas based on the relationship between the intensity of the relevant attributes and their degree of acceptance. Among the methods used to assess the sensory characteristics that explain consumer preference, the ‘Just-About-Right’ (JAR) scale gives a reliable indication of the proportion of consumers who appreciate each sample and thus make it possible to define the right level of a given attribute. As CIRAD’s hybrids are intended for both the export market (Europe) and the local market (the Caribbean),

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consumers in the two areas were included in the hedonic sensory tests. Previous works produced mixed results on the preferences of consumers from different European countries, sometimes no differences in consumer preferences could be found (Causse et al., 2010), and sometimes interactions were found between the cultivar and the country (Bonany et al., 2013). All these acceptability criteria were used to screen hybrids produced in the CIRAD banana breeding program with the aim of identifying the most efficient screening criteria. 2. Material and methods 2.1. Identifying acceptability criteria 2.1.1. Material Twelve banana cultivars (Musa spp.) of different genotypes were used in this study (Table 1), four of which were produced by the CIRAD banana breeding program. The CIRAD hybrids were produced by crossing a diploid AA cultivar with a tetraploid (AAAA) (Tomekpe et al., 2004). All the bananas were grown at the Campus Agro-Environnemental Caraïbes (CAEC, Martinique, French West Indies; latitude 14◦ 37 N, longitude 60◦ 58 W, altitude 16 m) on continental alluvial soil. Similar standard agronomic and cropping practices (suckering, bunch management) were used for all cultivars. Bunches destined for descriptive sensory analyses were harvested between June and July 2009 and bananas destined for consumer tests between March and April 2014. Flowering to harvest time, which indicates fruit age, was first calculated for each cultivar as the time required for fruits to have a green life of 25 ± 5 days, measured at 20 ◦ C (Table 1). Three bunches of each cultivar were harvested, except the cv Gros Michel, for which not enough bunches were available at the time of the study. 2.1.2. Preparation of samples The second and the third banana hands on each bunch were reserved for analyses of sensory profiling, and the first fifth proximal hands on each bunch were reserved for the consumer test. All the hands were rinsed and dipped in fungicide (bitertanol, 200 mg L−1 ) for one minute. The fruits were placed in a plastic bag with 20 ␮m respiration holes and stored in boxes for six days at 18 ◦ C. The banana hands were then placed in a room at a temperature of 18 ◦ C for ethylene treatment (1 mL L−1 for 24 h) to trigger the ripening process. After 24 h, the room was ventilated. Bananas were kept at 18 ◦ C until the stage of ripeness chosen for eating (eating stage) was reached (Table 1). The optimal eating stage was assessed using a simple method developed by Daribo et al. (2007) as follows: between March and May 2009, two to three bunches of each cultivar were harvested and prepared as described above. The eating stage selected for each cultivar was the stage among three stages (i.e. the 6th, 9th or 13th day after ethylene treatment) that received the highest acceptability score and the lowest astringency and fermented aroma scores from five consumers. Five consumers may seem too few, but the results showed that for each variety, one of the three stages was always consensual. Four days before the consumer test in Montpellier (France), the boxes of banana were insulated with polystyrene and transported from Martinique to Montpellier by air in less than 24 h. The average temperature during transport was recorded by a temperature sensor placed inside the boxes and was 21 ◦ C. 2.1.3. Sensory analyses Sensory profiling was used for the characterization of 12 cultivars by 10 trained panelists selected among students and employees at the CAEC research station in Martinique. Texture, taste, odor (orthonasal olfaction) and aroma (retronasal olfaction)

were described by quantitative and qualitative attributes. Quantitative attributes were rated using a structured discrete scale (0–9) on which 0 corresponded to ‘low intensity’ and 9 to ‘high intensity’. For qualitative attributes, the frequency of detection (number of ‘presence’ responses out of the total number of responses) was calculated for each product. The separation between quantitative and qualitative attributes was decided in a session in which descriptive vocabulary was generated (Bugaud et al., 2011). The panelists were trained to use sensory attributes and to score the intensity of the sample on the scale proposed and seven sessions were held from May to June 2009. Sensory profiling was performed in 11 sessions held from June to July 2009. Before each session, the three to five selected banana hands were stored in the sensory room for one hour. A few minutes before sensory analysis, 10 bananas per hand were selected, cut into 4–5 cm cylinders without peel, and one cylinder was reserved for each panelist. The banana samples were coded with random numbers and were served monadically according to the Williams Latin square design. The panelists rinsed their mouths with mineral water between consecutive samples. Only the attributes for which significant differences were observed among the cultivars and for which the performance of the panel was satisfactory in terms of agreement and reliability are presented here (Table 2). The 12 cultivars were assessed in 11 sessions between June and July 2009. The laboratory met the requirements of the international norm ISO 8589: it was air conditioned with a controlled temperature (22 ◦ C ± 1 ◦ C) and humidity (75% ± 10%). It was equipped with separate boxes and lit with green light. The consumer test was conducted simultaneously at two sites, at CIRAD Montpellier (France) and at Pole Agro-alimentaire Régional de la Martinique in Lamentin (Martinique, French West Indies) in April 2014. The aim of the test was to include both European consumers who are only familiar with one cultivar (Cavendish), and Caribbean consumers who are familiar with a wide range of banana cultivars. Since there were 12 samples, two sessions were held on two consecutive days at each site. The test included 118 consumers in Montpellier and 96 consumers in Lamentin, giving a total of 214 consumers. A few minutes before each session, the skin was removed from six bananas (representing six cultivars), the fruits were cut into 4–5 cm cylinders, and presented to each consumer on a plate. The banana samples were coded with random numbers and were served monadically according to the Williams Latin square design. The consumers rinsed their mouths with mineral water between each sample. Consumers were asked to provide information on their gender (male/female), age (<30/30–49/≥50), frequency of banana consumption (>4 per month/1–4 per month/<1 per month), and the preferred stage of maturity of the most frequently eaten banana cultivar, Cavendish (yellow skin with a green tip/yellow all over/yellow with spots). For each sample, overall liking was scored on a 9-point discrete scale (1 = I don’t like it at all, 9 = I like it very much). The right level of sourness, sweetness, firmness, mealiness, and banana aroma of each sample was evaluated with Just-AboutRight (JAR) five-point bipolar scales. The consumers were asked ‘in your opinion this product is . . .’, rated on the following scale (here for sweetness): 1 = not sweet at all . . ., 2 = not sweet enough . . ., 3 = just about right, 4 = too sweet . . ., 5 = much too sweet. . .. (Lawless and Heymann, 2010). At the end of the questionnaire, consumers were asked what they disliked about the sample. 2.1.4. Physical-chemical analyses Puncture force was measured on two fresh bananas using a TA/XT2 Texture Analyzer according to the method of Bugaud et al. (2013). The other bananas were peeled and frozen in liquid nitrogen and stored at −80 ◦ C for chemical analysis. Total soluble solids were measured by refractometry after dilution of pureed banana in an equal volume of distilled water and filtration of the solution.

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Table 1 Banana cultivars assessed, harvest, and eating stages. Cultivar

Group

Subgroup

Fruit age at harvest (days)

Eating stage (days after ethylene treatment)

Abbreviation

Cirad916 Cirad918 Cirad919 Cirad925 Cavendish Fougamou Gros Michel Mossi Pisang Lilin Pisang Madu Pisang Mas Prata Ana

AAA AAA AAA AAA AAA ABB AAA AAA AA AA AA AAB

hybrid hybrid hybrid hybrid Cavendish Pisang Awak Gros Michel Red – – – Pome

72 79 86 74 91 73 76 67 85 70 42 102

6 13 6 9 9 9 9 9 9 13 9 9

916 918 919 925 CV FOU GM MO PL PU PM PA

Table 2 Definition of sensory attributes used to describe bananas. Definition Quantitative attributes Firmness Melting Mealiness Adhesiveness Heterogeneity Sweetness Sourness Astringency Banana odor Grassy odor Banana aroma Grassy aroma Chemical aroma Fermented aroma

Force required to compress a sample between teeth Ease of masticating a sample and reducing it for swallowing Crumbling during mastication Force required to remove the material that adheres to the mouth Presence of fibrous or grainy particles One of basic tastes (e.g. sucrose) One of basic tastes (e.g. citric acid) One of basic tastes (e.g. potassium sulphate) Odor of banana Odor of freshly cut green grass Flavor of banana Flavor of freshly cut green grass Flavor of candy with synthetic fruity aromas (Arlequin TM ) Flavor of fermentation, alcohol

Attribute scored on a presence/absence scale Flavor of candy with synthetic fruity Chemical odor aroma (Arlequin TM ) Odour of fermentation, alcohol Fermented odor Medicinal odor Odor of medicinal products, ether, soap Flavor of milk, cream Milky aroma Pineapple aroma Flavor of pineapple Flavor of medicinal products, ether, Medicinal aroma soap

trained panel and overall liking assessed by consumers) between banana cultivars with judge/consumer as a random effect and cultivar as a fixed effect. A two-way ANOVA was performed to identify significant differences in physical-chemical parameters between cultivars and between periods of analyses (descriptive sensory analysis vs. consumer test in Martinique vs. consumer test in Montpellier). The comparisons between cultivars were evaluated with a Tukey’s test (p = 0.05). 2.2. Screening of varieties 2.2.1. Material The acceptability criteria were tested by screening 172 hybrids (including the four hybrids used to identify the acceptability criteria) produced by the CIRAD banana breeding program. The hybrids were the product of the first step of the selection scheme, i.e. each hybrid was represented by a single individual of which only the agronomic characteristics (size of the banana plant, bunch appearance, length of the cycle) had been measured (Salmon et al., 2003). All the bananas were grown in the CIRAD experimental station at Neufchateau in Guadeloupe (latitude 16◦ 04 N, longitude 61◦ 36 W, altitude 250 m) on gibbsite andosol soil. Similar standard agronomic and cropping practices (suckering, bunch management) were used for all the hybrids. The hybrids were harvested between January and June 2015 when the first bananas had begun to ripen on standing plants.

Following dilution of 5 g of pureed banana in 50 mL distilled water, titratable acidity was determined by titration with 0.1 N NaOH to an endpoint at pH 8.1. The pH of the macerate was recorded before the start of titration. For the measurement of dry matter content, 2 g of pureed banana were oven dried at 70 ◦ C for 24 h and then weighed. For titratable acidity and dry matter content, the results are expressed on a fresh weight basis.

2.2.2. Preparation of samples The third hand on each bunch (corresponding to each hybrid), with no banana in the climacteric crisis, were rinsed, placed in a plastic bag with 20 ␮m respiration holes and stored in boxes for one day at 20 ◦ C. The banana hands were then placed in a room at 20 ◦ C and treated with ethylene (1 mL L−1 for 24 h) to trigger the ripening process. After 16 h of treatment, the room was ventilated. The bananas were stored at 20 ◦ C until the 8th day after ethylene treatment.

2.1.5. Statistical analyses The high-dimensional data in the sensory traits of cultivars were analyzed by principal component analysis using XLSTAT software (Version 2015.1.01). Hierarchical ascendant cluster analysis was applied to the overall liking scores to identify groups of consumers with similar preference patterns. Dissimilarities among samples were calculated on the basis of the squared Euclidean distance, and the Ward hierarchical agglomerative method was used to establish clusters. For each socio-demographic variable (gender, origin, age, frequency of banana consumption, and preferred stage of maturity) a Fisher’s test was used to examine differences between groups of consumers. A two-way ANOVA was performed to determine significant differences in sensory traits (attributes assessed by the

2.2.3. Sensory analyses The sensory traits of the 172 hybrids were characterized by three experienced panelists between January and July 2015 at the Neuchateau research station (Guadeloupe). Like for the first panel, the selected panelists were trained to use and to score the five sensory attributes (sweetness, sourness, banana aroma, firmness, and mealiness). They had previously rated cultivars that were assessed by the first panel and the results of the two panels were similar. The five attributes (sweetness, sourness, banana aroma, firmness, and mealiness) were rated using a structured discrete scale (0–9), 0 corresponded to ‘low intensity’ and 9 to ‘high intensity’. The method used to organize sensory profiling sessions is described in paragraph 2.1.3 above.

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3. Results and discussion 3.1. Characteristics of cultivars 3.1.1. Sensory characteristics of dessert bananas The sensory traits of the cultivars were described by principal component analysis (Fig. 1). The first principal component (39% of total variability) contrasted firmness, grassy aroma and astringency with melting, fermented and banana odor and aroma, and chemical odor. This axis indicates the degree of ripeness perceived by panelists. The second principal component (23%) separated fruits with a mealy texture from the sourest fruits with chemical and pineapple aroma. Cavendish fruits, which had the highest banana score (5.7/9), were considered by panelists as having a typical banana aroma. Cavendish fruits were also characterized by the most adhesive texture and the highest milky aroma. Cavendish fruits were among the sweetest and the least sour fruits. Among the four banana hybrids, marked contrasts were observed in Cirad919 bananas with the highest sourness score and Cirad918 bananas with the highest sweetness and fermented aroma, and the lowest firmness scores. Cirad916 bananas differed in medicinal odor, whereas Cirad925 bananas did not differ in any particular sensory attribute. Prata Ana, widely eaten in Brazil, was among the firmest and sourest bananas with a grassy odor and a pineapple aroma. Pisang Mas, exported by Columbian producers to Europe under the name ‘Figue sucrée’ or ‘Frayssinette’, were slightly sweet and astringent. Mossi bananas, produced in the French West Indies (FWI) and mainly exported to France at Christmas under the name ‘Figue Rose’ were one of the most melting bananas. Gros Michel, one of the most popular bananas in banana production areas, was characterized by the highest mealiness. Among less well-known cultivars, Pisang Lilin was among the sourest and had a high chemical aroma and the highest medicinal note. Fougamou bananas were among the most heterogeneous. Pisang Madu bananas had the highest score for firmness and heterogeneity, and the lowest score for sourness and banana aroma. 3.1.2. Physical-chemical characteristics of dessert banana Physical-chemical analyses were conducted to (1) check the homogeneity of the samples assessed at different locations (Martinique, Montpellier) and at different dates (2009, 2014), (2) describe the characteristics of the cultivars linked with their sensory traits, and (3) identify relevant instrumental indicators of acceptability. Precautions were taken to limit the heterogeneity of batches by harvesting the cultivars at the same age, and by ripening the banana fruits in the same conditions. Although the bananas sampled for sensory profiling (in 2009) presented a significant mean value lower than that of the bananas sampled for consumer tests (in 2014) in titratable acidity (−0.6 meq 100 g−1 ) and total soluble solids (−1.7◦ Brix) (Table 3), overall, the cultivars were ranked in the same way. Moreover, differences in titratable acidity (average of 0.6 meq 100 g−1 ) were well below the differences required to ensure a detectable difference (3.6 meq 100 g−1 ) perceived by panelists (Bugaud et al., 2013). The ripeness of bananas shipped from Martinique to Montpellier for consumer tests in 2014 does not appear to have been affected by air transport, based on the absence of significant differences between the samples tested in Martinique and Montpellier. We can therefore assume that the batches of banana assessed in Martinique and Montpellier in 2009 and 2014 were representative for sensory analyses. Pulp puncture force ranged from 1.5 to 4.1 N. As expected, this rheological parameter was correlated with the firmness evaluated by trained panelists (R = 0.73). Pisang Madu and Cirad919 had the highest pulp puncture force values, and Cirad918, Mossi, Cavendish, and Pisang Mas had the lowest. High variability in titratable acidity at the eating stage was observed with val-

ues ranging from 2.6 meq 100 g−1 (Cavendish, Pisang Madu) to 11.1 meq 100 g−1 (Cirad919), and pH from 4.1 (Cirad919) to 5.8 (Pisang Madu). As expected, titratable acidity and pH were correlated with sourness (R = 0.93, R = −0.83) and sweetness (R = −0.76, R = 0.62), respectively. Total soluble solids did not vary much among cultivars (10% coefficient of variation). Pisang Mas and Pisang Madu fruits had the highest total soluble solids (24–25◦ Brix), and Cirad919 and Mossi fruits had the lowest (19–21◦ Brix). Dry matter content ranged from 22% in Mossi pulp to 31% in Fougamou pulp. Using the regression equation proposed by Bugaud et al. (2013), which predicted sweetness from titratable acidity (TA), total soluble solids (TSS) and dry matter content (DM) (sweetness = 2.3–0.36 × TA + 0.32 × TSS − 9.7 × 10−2 × DM), 54% of sweetness was explained. This regression equation was used for the identification of instrumental indicators of acceptable sweetness.

3.1.3. Overall liking and clustering of consumers The consumer panel included 60% women, 25% were aged under 30, and 36% aged 50 or more (Table 4). Forty-two percent ate bananas every week, 36% ate one to four bananas per month, and 22% ate a banana less than once a month. Based on Cavendish, the preferred stage of banana fruit ripeness was when the banana skin was completely yellow with a green tip for 16% of the consumers, yellow all over for 55% of consumers, and yellow with spots for 29% of the consumers. The cultivar most liked by consumers was Cavendish with an overall liking score of 6.9 on a 1–9 scale (Table 5). Among the top four were Prata Ana and Gros Michel, which were the most popular in banana production areas. Interestingly, the hybrid Cirad925 which is currently being tested by French Caribbean producers ranked well, with an overall liking score of 5.8. The firmest (Pisang Madu) and the sourest (Cirad919) cultivars were the least liked by consumers with an overall liking score of 3.4 and 4.1, respectively. Their sensory characteristics, which are rarely encountered in popular bananas, were disqualified by consumers. The other cultivars had an overall liking score of around 5, i.e. they were neither particularly liked nor disliked. Hierarchical cluster analysis was performed on the overall liking data and resulted in four groups (data not shown). The consumers in group 1 (18% of consumers) liked bananas since except for Pisang Madu, they scored cultivars between 6 and 8 (Table 5). They scored cultivars at least one point above the mean value. They praised Prata Ana fruits. This was the only group that did not select Cavendish as favorite. With a score of 8.0, Prata Ana was the highest rated cultivar of all. The cultivars with a sour taste (Prata Ana, Pisang Lilin, Cirad919) were scored higher by this group than by the other groups. The consumers in group 1 were mostly under 50 years old and did not like overripe bananas with spotted skin (Table 4). In contrast, consumers in group 4 (27%) did not like bananas at all, since, except for Cavendish, they gave a mean score below 5 to all the cultivars. Half the consumers in group 4 were aged 50 or more, two-thirds came from Montpellier, and almost half preferred overripe bananas. As suggested for kiwifruits (Jaeger et al., 2003), consumers in group 1 should be referred to as ‘accepting’ and consumers in group 4 as ‘demanding’. It is also likely that the bananas used for this study were not sufficiently ripe for demanding consumers, who prefer overripe bananas. The consumers in group 2 gave cultivars a score close to the mean value given by all the consumers. More people in group 2 came from Montpellier than from Martinique. The consumers in group 3 praised the Cavendish cultivar (to which they gave a score of 7.9). Unlike the consumers in group 1, they disliked cultivars with a strong sour taste (Pisang Lilin and Cirad919). Clustering consumers thus highlighted two contrasting consumer segments, one who like sourer bananas, and one who prefer sweet bananas, as already demonstrated for other fruits

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403

Fig. 1. Principal component analysis of the sensory traits of dessert bananas. Abbreviations; for the cultivars are given in Table 1. Descriptors followed by ‘a’ refer to aroma; descriptors followed by ‘o’ refer to odor.

Table 3 Physical-chemical characteristics of dessert bananas at the eating stage. Locations and years of analyses Martinique (2009)

Montpellier (2014)

a

Puncture force (N) Titratable acidity (meq 100 g−1 ) pH Total soluble solids (◦ Brix) Dry matter content (g 100 g−1 )

Martinique (2014)

a

2.3 5.1b 4.9a 21.4b 26.7a

2.2a 5.6ab 5.0a 23.1a 26.7a

2.2 5.8a 4.9a 23.1a 26.5a

Two-way ANOVA was applied to the cultivar factor (12 cultivars) and to the location/year of analyses factor, values are the mean of the 12 cultivars, superscripts a,b are the results of Tukey’s test.

Table 4 Socio-demographic details of consumers within preference subgroups. Total sample in%

p in number

Gender Male Female

40 60

86 128

Origin Martinique Montpellier

45 55

96 118

Age <30 30–49 ≥50

25 39 36

54 83 77

Frequency of banana consumption >4 per month 1–4 per month <1 per month

42 36 22

91 76 47

Preferred stage of maturity Yellow skin with green tip Yellow skin Spotted yellow skin

16 55 29

35 118 61

Group 1a

Group 2

Group 3

Group 4

(18%)

(30%)

(25%)

(27%)

16 23

32 32

17 36

21 37

18 21

22 42

36 17

20 38

15 17 7

16 22 26

14 23 16

9 21 28

17 16 6

23 23 18

24 19 10

27 18 13

11 23 5

12 36 16

6 34 13

6 25 27

0.22

0.001

0.048

0.708

0.005

The values in bold are significant at alpha = 0.05 with Fisher’s test per case. a Hierarchical cluster analysis was performed on the overall liking data and resulted in four groups.

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Table 5 Overall liking expressed by each group of consumers for the 12 cultivars assessed on a 1–9 scale of acceptability. Cultivar

Overall consumer(mean)

Standard deviation

Group 1*

Group 2

Group 3

Group 4

Cavendish Prata Ana Cirad925 Gros Michel Cirad918 Fougamou Mossi Pisang Mas Cirad916 Pisang Lilin Cirad919 Pisang Madu

6.9a 5.9b 5.8b 5.7b 5.6bc 5.6b–d 5.4b–d 5.0c–e 5.0de 4.7ef 4.1f 3.4g

1.7 2.2 2.0 1.8 2.1 2.0 1.9 2.0 2.2 2.2 2.2 2.0

7.3ab 8.0a 7.3ab 7.4ab 6.1cd 7.1a–c 6.8b–d 6.6b–d 6.1cd 6.8b–d 6.0d 4.3e

6.9a 6.0ab 5.7b 5.7b 6.0b 6.1ab 5.8b 5.4bc 5.4bc 5.6b 4.5cd 4.1d

7.9a 5.7bc 6.2b 6.0b 6.1b 5.4b–d 5.8bc 4.7cd 4.4d 2.7e 3.0e 2.7e

5.6a 4.5ab 4.5ab 4.3b 4.5b 4.1b 3.8bc 3.9b 4.2b 4.2b 3.5bc 2.7c

*Hierarchical cluster analysis was performed on the overall liking data and resulted in four groups. Superscripts a−g are the results of Tukey’s test.

Table 6 Quadratic functions to model relationships between intensity of sourness (IS) and percentage of consumers who judged bananas to be much too sour (Y1) or not sour enough (Y2). Quadratic function

R2

Percentage of consumers who judged bananas to be much too sour overall consumers Y1all = 1.6 × IS2 − 2.4 × IS + 10.4 Y1G1 = 1.4 × IS2 − 3.4 × IS + 11.8 consumers in group 1 Y1G2 = 1.2 × IS2 + 1.5 × IS + 2.2 consumers in group 2 Y1G3 = 2.6 × IS2 − 8.1 × IS + 20.0 consumers in group 3 Y1G4 = 1.3 × IS2 − 1.0 × IS + 9.8 consumers in group 4

0.96 0.91 0.97 0.93 0.96

Percentage of consumers who judged bananas to be not sour enough overall consumers Y2all = 0.6 × IS2 − 9.7 × IS + 42.7 Y2G1 = 1.1 × IS2 − 13.7 × IS + 44.8 consumers in group 1 consumers in group 2 Y2G2 = 0.1 × IS2 − 5.5 × IS + 34.6 consumers in group 3 Y2G3 = 0.7 × IS2 − 9.8 × IS + 37.0 consumers in group 4 Y2G4 = 0.6 × IS2 − 11.7 × IS + 55.5

0.80 0.75 0.59 0.56 0.76

(Bonany et al., 2014; Daillant-Spinnler et al., 1996; Sinesio et al., 2010). Curiously, the consumers in group 3 who praised Cavendish fruits were mainly from Martinique, whereas their preferences were previously thought to be for local cultivars (Frayssinette, Gros Michel, Figue Pomme, Figue Rose). A survey currently underway in Guadeloupe (French West Indies like Martinique) apparently confirms the preferential consumption of Cavendish in Guadeloupe. 3.2. Acceptability criteria 3.2.1. Sensory indicators of acceptability Acceptability criteria for sourness, sweetness, firmness, mealiness, and banana aroma were computed by combining the sensory profile and JAR test results. The acceptability criteria were assessed as follows. First, the percentage of consumers who judged bananas to be much too sour (corresponding to 4 or 5 on the JAR scale) was linked to the intensity of sourness of the bananas, which had previously been scored by trained panelists. This relationship was fitted for all consumers and for each group with a quadratic function (Fig. 2a). The quadratic parameters are listed in Table 6. Second, the percentage of consumers who judged the bananas to be not sour enough (corresponding to 1 or 2 on the JAR scale) was linked to the intensity of sourness and the relationship was also fitted with a quadratic function (Fig. 2b, Table 6). The sourer the banana, the more likely they were found to be ‘much too sour’ by consumers. Inversely, the less sour the bananas, the more they were likely to be found to be ‘not sour enough’ by consumers. Third, the intensity of sourness at which the percentage of consumers who judged the bananas to be ‘much too sour’ or ‘not sour enough’ was below 20% or 33%, was assessed by a quadratic function. The threshold of 20% of unsatisfied consumers was chosen because an attribute is considered to be optimal when – at the most – 20% of consumers choose the ‘much too sour’ or ‘not sour enough’ categories (Meullenet et al.,

2007). The threshold of 33% of unsatisfied consumers was arbitrarily chosen as the threshold of acceptance and corresponded to two thirds of satisfied consumers. For all consumers, optimal sourness was the interval within which Y1all and Y2all were below 20%, i.e. between 2.8 and 3.3 on a 0–9 scale (Fig. 3). Acceptability at a threshold of 33% was the interval within which Y1all and Y2all were below 33%, i.e. between 1.1 and 4.6. The optimal and acceptable levels of sourness were assessed for each group (Fig. 4A). The optimal sourness was less restrictive for group 2 (between 2.8 and 3.3) than for group 1 (between 2.2 and 3.9), and lower for group 3 (between 2.1 and 3.2). No optimal sourness was identified for group 4 since together, Y1all and Y2all did not fall below 20%. Acceptable sourness covered about four points on the 0–9 scale of sourness. Acceptability criteria for sweetness, banana aroma, firmness and mealiness were calculated in the same way. Relationships between the intensity of these attributes and the level judged by consumers to be right in banana were fitted with linear or quadratic functions (data not shown). To our knowledge, this is the first time these relationships have been revealed in banana. Using a range of cultivars whose rates for the five attributes were distributed evenly from 1 to 7 on a 0–9 scale, we were able to establish relationships with high determination coefficients (generally R2 > 0.70). The ideal banana was characterized by scores between 6.1 and 6.7 for sweetness, between 2.8 and 3.3 for sourness, above 6.3 for banana aroma, between 3.7 and 4.7 for firmness and between 1.0 and 1.4 for mealiness (Fig. 4). A high sweetness score is preferred in banana, as already reported for other fruit species (Bonany et al., 2014; Lester, 2006). The optimal sweetness value was close to that of ripe Cavendish fruits (i.e. when the skin was yellow). Consumers in group 3 preferred banana to be sweeter than consumers in group 1 and vice versa for sourness, confirming the existence of consumer segments for banana sweetness/sourness. The optimal interval for banana aroma (above a score of 6.3) should be interpreted with caution, because the intensity of banana aroma did not exceed a score of 6 in any of the 12 cultivars. However, the values for optimal banana aroma must be at least that of the Cavendish fruits. In contrast to apple (Harker et al., 2008), firmness is not a segmentation criterion, since no great differences were observed between groups of consumers. Optimal firmness is expected to be close to the median value 4.5. Although low mealiness scores are clearly expected in banana, its degree of acceptance varied from one group of consumers to another, as already observed in apple (Jaeger et al., 1998). With its high scores, mealiness is certainly the sensory trait that penalized the Cavendish cultivar. Consumers were also asked what they disliked. Beyond the five previous attributes, heterogeneity and off-flavors were the most frequently mentioned. Heterogeneity referred to the presence of fibrous or grainy particles. Heterogeneity was especially prevalent in Fougamou and Pisang Madu (with respectively 20 and 15 citations versus less than 3 for the other cultivars). Scored by trained

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Fig. 2. Relationships between the intensity of sourness measured by trained panelists and the percentage of consumers who judged the bananas to be ‘much too sour’ (A) or ‘not sour enough’ (B). Each number represents a cultivar judged by a group of consumers: 1 for group 1, 2 for group 2, 3 for group 3, and 4 for group 4. Grey dots represent cultivars judged by all consumers. To make the figure easier to read, only the quadratic function fitted to the grey dots (all the consumers) is shown.

panelists on a 0–9 scale, Pisang Madu was scored 6.3, Fougamou 5.7, and the other cultivars less than 3.3 (Bugaud et al., 2011), so a score of 3.3 can be used as the upper threshold of acceptability. When defined, off-flavors were described as fermented, chemical, or medicinal aroma or odor. Among the cultivars whose off-flavors were the most frequently cited, Cirad916 and Pisang Lilin were described as having a chemical and medicinal odor and aroma. Fermented aroma was mainly cited for Mossi. It was clear that the most appreciated cultivars (Cavendish, Prata Ana, Cirad925) were characterized by the almost absence of off-flavors (with respectively 0, 3, and 7 citations versus between 17 and 34 citations for the other cultivars, except Fougamou, which was cited 3 times).

Table 7 Quadratic functions to model relationships between physical-chemical parameters and percentage of consumers who judged bananas to be much too sour or much too firm or not sour enough or not firm enough. Quadratic function

R2

Percentage of consumers who judged bananas to be much too: Y1so = 0.69 × TA2 − 0.73 × TA + 2.39 sour Y1so = 71.4 × pH2 − 750 × pH + 1980 sour Y1fi = 14.8 × Fp2 − 40.8 × Fp + 34 firm

0.91 0.78 0.78

Percentage of consumers who judged bananas to be insufficiently: sour Y2so = 0.22 × TA2 − 7.19 × TA + 52.6 Y2so = −5.6 × pH2 + 83 × pH − 254 sour Y2fi = 23.4 × Fp2 − 128 × Fp + 180 firm

0.77 0.87 0.67

TA: titratable acidity in meq.100 g−1 of fresh weight, Fp: pulp puncture force in N.

3.2.2. Physical-chemical indicators of acceptability Physical-chemical indicators of banana acceptability were identified using the same method as that used for sensory indicators. Relationships between the percentages of consumers who judged bananas to be much too sour or not sour enough and titratable acidity or pH were fitted with quadratic functions (Table 7). The higher the titratable acidity or the lower the pH, the more the banana was considered by consumers to be much too sour. Inversely, the lower the titratable acidity or the higher the pH, the more the banana was considered by consumers to be not sour enough. Similar relationships were found between pulp puncture force and the percentage of consumers who judged bananas to be much too firm or not firm

enough. High determination coefficients (R2 > 0.75) were found for sourness or firmness, pointing to a strong link between the degree of acceptance of these attributes by consumers and their associated physical-chemical parameters. Finally, based on the results obtained from all the consumers, an ideal banana was characterized as having titratable acidity of 5.5 meq 100 g−1 , or a pH of 4.9, and a pulp puncture force between 1.9 and 2.4 N (Fig. 5A, 5B, 5C). Below a titratable acidity of 3.0 meq 100 g−1 or above a pH of 5.4, more than 33% of consumers judged the bananas to be ‘not sour enough’. Above a titratable acidity of 7.2 meq 100 g−1 or below a pH of 4.6, more than 33% of consumers judged the bananas to be ‘much too

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Fig. 3. Sourness acceptability criteria for all consumers. The dashed line represents the quadratic function that fitted the relationship between the intensity of sourness and the percentage of consumers who judged bananas to be ‘much too sour’. The dotted line represents the quadratic function that fitted the relationship between the intensity of sourness and the percentage of consumers who judged bananas to be ‘not sour enough’.

sour’. The acceptable levels of firmness measured by rheology were respectively 1.6 N and 2.8 N. Like for the sensory indicators, differences were observed among the groups of consumers. Thanks to these results, it should be possible to test any cultural or postharvest practice to improve the sourness or firmness of a cultivar. For example, Pisang Lilin bananas were characterized by a titratable acidity above the acceptability threshold (8.3 meq 100 g−1 ). Knowing that titratable acidity is mainly driven by citrate and malate, it should be possible to reduce it by increasing the ripening temperature (which has a negative effect on citrate and malate) or by harvesting bananas earlier (which has a greater negative effect on citrate than its positive effect on malate) (Etienne et al., 2014). Inversely, increasing ripening temperature and harvesting bananas later should improve the sourness of Cavendish fruits whose titratable acidity was the optimal value (3.7–4.1 meq 100 g−1 ). Concerning sweetness, the regression equation established by Bugaud et al. (2013), sweetness = 2.3 − 0.36 × titratable acidity + 0.32 × total soluble solids − 0.097 × dry matter content, was used to link these chemical parameters to the percentage of consumers who judged bananas to be ‘much too sweet’ or ‘not sweet enough’. For a titratable acidity arbitrarily set at 4, 5.5 or 7 meq 100 g−1 and a dry matter content of 22% or 26%, total soluble solids were in the range of values usually met for this parameter in ripe bananas (16–28◦ Brix). As optimal sourness was determined for a titratable acidity of 5.5 meq 100 g−1 , if dry matter content was 22%, total soluble solids of 26.4◦ Brix would be needed to achieve

optimal sweetness (Fig. 5D). The higher the titratable acidity and dry matter content, the more total soluble solids are required to achieve optimal sweetness. No physical-chemical indicators were found for mealiness and banana aroma acceptability. For mealiness, no instrumental predictors have been found in banana, in contrast to apple (Harker et al., 2002). Given its low degree of acceptance by consumers, mealiness thus requires further investigation. Concerning banana aroma, two butanoate esters, 3-methylbutyl butanoate and 2methylpropyl butanoate were recently identified as contributing to this aroma (Bugaud and Alter, 2016). In addition, two other esters, 3-methylbutyl acetate and ethyl 3-methylbutanoate appear to contribute to the fermented, chemical, and medicinal aromas described by consumers as off-flavors. At this point, it appears that concentrations of the first two esters should be high, whereas concentrations of the last two esters should be low in banana fruit. 3.3. Applications: using acceptability criteria for variety screening The acceptability criteria were used to screen the 172 hybrids produced by the CIRAD banana breeding program. Three experienced panelists scored the five attributes (sweetness, sourness, firmness, mealiness, and banana aroma) of each hybrid on a 0–9 scale. It is clear that the required number of panelists for sensory profiling was not met. However, in practice, this small number of panelists is the situation the breeders face when they have to

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Fig. 4. Acceptability criteria for sourness (A), sweetness (B), banana aroma (C), firmness (D) and mealiness (E) calculated for each group of consumers using sensory indicators. Optimum acceptability is in black, acceptability at 33% of unsatisfied consumers is in grey.

phenotype many varieties continuously over several years. So, for sensory screening, we preferred to choose three panelists who were available throughout the experiment and were willing to make assessments twice or three times a week. We first made sure they scored like the first panel. Despite these limitations, the results presented below clearly illustrate the advantage of the acceptability criteria for banana breeding. Hybrids were screened for the previously calculated acceptability criteria. None of the groups of consumers identified any hybrid that had the characteristics of the ideal banana, i.e. when all five attributes were at their optimal level (Table 8). Acceptability criteria based on the degree of acceptance by consumers in group 1 allowed screeners to extract nine hybrids close to the ideal banana, since these bananas presented optimal

levels for at least four of the five attributes. At the other end of the scale, acceptability criteria based on the degree of acceptance by consumers in group 4 were such that 83% of the hybrids did not reach the optimal level for any of the five attributes. Analysis of the results of screening by consumers in group 1 who liked sourer bananas and by consumers in group 3 who more specifically preferred sweeter bananas, 68 hybrids had optimal sourness levels according to the consumers in group 1, whereas 27 hybrids did not have optimal sourness for consumers in group 3 (data not shown). Inversely, 41 hybrids had optimal sweetness for group 3, whereas 17 of them did not have optimal sweetness for group 1. This implies that fruit breeders should not only target ‘the ideal fruit’, but also special fruit that create major new flavor niches, as

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Fig. 5. Acceptability criteria for sourness (A and B), firmness (C) and sweetness (D) using physical-chemical indicators (titratable acidity and pH for sourness, pulp puncture force for firmness, and titratable acidity, dry matter content and total soluble solids for sweetness). Optimum acceptability is in black, acceptability at 33% of unsatisfied consumers is in grey. TA: titratable, DM: dry matter content.

Table 8 Number of hybrids that matched acceptability criteria for the five sensory attributes (sourness, sweetness, banana aroma, firmness, and mealiness). Acceptability criteria

Overall consumers

Group 1

Group 2

Group 3

Group 4

At optimal level none at least one at least two at least three at least four all five (ideal banana)

102 ␲ 55 ␣␤␮ 11 4 0 0

26 56 46 ␤␲ 35 ␣ 9␮ 0

68 64 ␤␮␲ 29 ␤ 10 1 0

97 ␲ 58 ␣ ␤ 14␮ 3 0 0

143 ␤␲␮ 27 ␣ 2 0 0 0

At acceptable level none at least one at least two at least three at least four all five (acceptable banana)

7 24 48 ␲ 46 40 ␣␤␮ 7

1 6 30 ␲ 52 50 ␤ 33 ␣␮

4 22 37 ␲ 50 49 ␣␤␮ 10

4 18 49 ␲ 51 43 ␣␤␮ 7

20 39 46 ␤␲ 48 ␣ 19 ␮ 0

The four hybrids used to define the acceptability criteria (Cirad916␣, Cirad918␤, Cirad919␲ , Cirad925 ␮ ) were screened and placed in the corresponding category.

already pointed out in the case of kiwifruit by Harker et al. (2007). It is interesting to analyze the positioning of the four hybrids used to define the acceptability criteria, i.e. Cirad916, Cirad918, Cirad919,

and Cirad925. As expected, Cirad919, which was not liked by consumers, had few traits at the optimal level. The hybrid Cirad925 was the closest to the ideal banana defined by group 1.

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As expected, the number of hybrids that matched the acceptability criteria increased when the screening parameters were set to acceptability thresholds at 33% of unsatisfied consumers. Thirtythree hybrids (in particular Cirad925 and Cirad916) matched group 1’s acceptability criteria for the five attributes. Among these 33, 10 hybrids (6% of the total screened hybrids) matched group 2’s acceptability criteria, and among these 10 hybrids, seven matched group 3’s acceptability criteria. When 33% acceptability thresholds were used, no hybrid matched group 4’s acceptability criteria. Like Russian dolls, several screening levels exist based on the banana ‘accepting – demanding’ scale. Quality specialists and breeders are currently reflecting on the best screening strategy to be used in the CIRAD banana breeding program. We have seen that defining screening parameters on the basis of the ideal fruit is too restrictive. It would be better to screen using parameters representing acceptability criteria at 33% of unsatisfied consumers. The choice of basing the screening parameters on acceptability criteria obtained for any particular consumer group will depend on the means used: basing the parameters on the preferences of ‘accepting’ consumers will lead to the selection of more hybrids, which will subsequently require more analytical resources to test them in the final steps of the selection scheme. Once a hybrid is selected, crop management can be optimized to get closer to the ideal fruit, as discussed in paragraph 3.2.2 above. From a methodological point of view, we are aware of the difficulty involved in implementing high-throughput phenotyping with only three trained panelists, however, in the short term, the number of panelists is expected to be increased to six to cope with the gradual increase in the number of cultivars to be evaluated. 4. Conclusion This is the first time acceptability criteria have been quantified for dessert banana. Criteria were defined for the five main sensory attributes: sweetness, sourness, banana aroma, firmness and mealiness. It was possible to identify the sensory traits of both the ideal and of an acceptable banana by demonstrating relationships between the intensity of these attributes and their ‘right’ level in banana. The number and the choice of banana samples are crucial for identifying these relations. Using a dozen samples (cultivars) whose rating for the five attributes was evenly distributed along a scale of intensity allowed us to identify relationships, and hence acceptability criteria, with good accuracy. We have shown the advantages of using these acceptability criteria for breeders to screen new hybrids. The identification of physical-chemical indicators of acceptability criteria (mainly titratable acidity and pulp puncture force) will allow quality experts and agronomists to improve fruit through crop management. As we included a wide range of banana consumers, some of whom were familiar with the sensory diversity of banana, and some not, we now have a good grasp of consumer preferences. Segmentation mainly appears to be possible for the intensity of sweetness/sourness and for the degree of acceptance of a particular banana by (accepting vs. demanding) consumers. Acknowledgements This study was supported by the project ‘West Indies Sustainable Banana’ from E.U. INTERREG (grant PRESAGE no. 2/229721108R65ALP111). References Andani, Z., Jaeger, S.R., Wakeling, I., MacFie, H.J.H., 2001. Mealiness in apples: towards a multilingual consumer vocabulary. J. Food Sci. 66, 872–879.

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Bonany, J., Buehler, A., Carbó, J., Codarin, S., Donati, F., Echeverria, G., Egger, S., Guerra, W., Hilaire, C., Höller, I., Iglesias, I., Jesionkowska, K., Konopacka, D., ´ D., Martinelli, A., Pitiot, C., Sansavini, S., Stehr, R., Schoorl, F., 2013. Kruczynska, Consumer eating quality acceptance of new apple varieties in different European countries. Food Qual. Preference 30, 250–259. Bonany, J., Brugger, C., Buehler, A., Carbó, J., Codarin, S., Donati, F., Echeverria, G., Egger, S., Guerra, W., Hilaire, C., Höller, I., Iglesias, I., Jesionkowska, K., ´ Konopacka, D., Kruczynska, D., Martinelli, A., Petiot, C., Sansavini, S., Stehr, R., Schoorl, F., 2014. Preference mapping of apple varieties in Europe. Food Qual. Preference 32, 317–329. Bugaud, C., Alter, P., 2016. Volatile and non-volatile compounds as odour and aroma predictors in dessert banana (Musa spp.). Postharvest Biol. Technol. 112, 14–23. Bugaud, C., Deverge, E., Daribo, M.-O., Ribeyre, F., Fils-Lycaon, B., Mbéguié-A-Mbéguié, D., 2011. Sensory characterisation enabled the first classification of dessert bananas. J. Sci. Food Agric. 91, 992–1000. Bugaud, C., Cazevieille, P., Daribo, M.-O., Telle, N., Julianus, P., Fils-Lycaon, B., Mbéguié-A-Mbéguié, D., 2013. Rheological and chemical predictors of texture and taste in dessert banana (Musa spp.). Postharvest Biol. Technol. 84, 1–8. Causse, M., Friguet, C., Coiret, C., Lépicier, M., Navez, B., Lee, M., Holthuysen, N., Sinesio, F., Moneta, E., Grandillo, S., 2010. Consumer preferences for fresh tomato at the European scale: a common segmentation on taste and firmness. J. Food Sci. 75, S531–S541. Daillant-Spinnler, B., MacFie, H.J.H., Beyts, P.K., Hedderley, D., 1996. Relationships between perceived sensory properties and major preference directions of 12 varieties of apples from the southern hemisphere. Food Qual. Preference 7, 113–126. Daribo, M.O., Paget, B., Bugaud, C., 2007. Simple methods to evaluate the saleable life and edible life of new varieties of banana. In: Wanda, Lugo, Wilfredo, Colon (Eds.), Marketing Opportunities for Agriculture and Forestry Products in the Greater Caribbean—A Challenge for the 21st Century. Caribbean Food Crops Society, Costa Rica, pp. 194–198. Etienne, A., Génard, M., Bancel, D., Benoit, S., Lemire, G., Bugaud, C., 2014. Citrate and malate accumulation in banana fruit (Musa sp. AA) is highly affected by genotype and fruit age, but not by cultural practices. Sci. Hort. 169, 99–110. Eyabi, G., Samalang, P., Ehabe, E., Numfor, F.A., 2000. Chemical and organoleptic quality of figs from selected sweet bananas (Musa Spp.). J Food Technol. Afr. 5, 70–72. Garruti, D., Pereira, G., Weber, O., da Costa, J., Facundo, H., 2013. Acceptance of banana cultivars resistant to Black Leaf Streak by consumers of the Brazilian Northeast region. Acta Hort. 986, 345–351. Harker, F.R., Maindonald, J., Murray, S.H., Gunson, F.A., Hallett, I.C., Walker, S.B., 2002. Sensory interpretation of instrumental measurements 1: texture of apple fruit. Postharvest Biol. Technol. 24, 225–239. Harker, F.R., Jaeger, S.R., Lau, K., Rossiter, K., 2007. Consumer perceptions and preferences for kiwifruit: a review. Acta Hort. 753, 81–88. Harker, F.R., Kupferman, E.M., Marin, A.B., Gunson, F.A., Triggs, C.M., 2008. Eating quality standards for apples based on consumer preferences. Postharvest Biol. Technol. 50, 70–78. Jaeger, S.R., Andani, Z., Wakeling, I.N., MacFie, H.J.H., 1998. Consumer preferences for fresh and aged apples: a cross-cultural comparison. Food Qual. Preference 9, 355–366. Jaeger, S.R., Rossiter, K.L., Wismer, W.V., Harker, F.R., 2003. Consumer-driven product development in the kiwifruit industry. Food Qual. Preference 14, 187–198. Lawless, H.T., Heymann, H., 2010. Acceptance testing. In: Lawless, H.T., Heymann, H. (Eds.), Sensory Evaluation of Food: Principles and Practices. Chapman & Hall, New York, pp. 325–344. Lester, G.E., 2006. Consumer preference quality attributes of melon fruits. Acta Hort. 712, 175–182. Matsuura, F.C.A.U., Da Costa, J.I.P., Da Silveira Folegatti, M.I., 2004. Marketing of banana: consumer preferences relating to fruit quality attributes. Rev. Bras. Frutic. 26, 48–52. Meullenet, J.F., Xiong, R., Findlay, C.J., 2007. Analysis of just about right data. In: Meullenet, J.F., Xiong, R., Findlay, C.J. (Eds.), Multivariate and Probabilistic Analyses of Sensory Science Problems. Blackwell Publishing, Iowa, USA, pp. 207–235. Ortiz, R., Ferris, R.S.B., Vuylsteke, D., 1995. Banana and plantain breeding. In: Gowen, S. (Ed.), Bananas and Plantains. Chapman & Hall, London, pp. 110–146. Salmon, F., Bugaud, C., Chillet, M., Dorel, M., Risède, J.M., Jenny, C., Cote, F.X., 2003. Development of a new promising banana hybrid: flhorban 920. In: Farant, M., Anais, G., Ozier Lafontaine, H., Zebus, M.F., Diman, J.L., Hammouya, D. (Eds.), Alternatives to High Input Agriculture in the Caribbean: Towards the Elaboration of Innovative Systems. Caribbean Food Crops Society, Guadeloupe, pp. 274–283. Salvador, A., Sanz, T., Fiszman, S.M., 2007. Changes in colour and texture and their relationship with eating quality during storage of two different dessert bananas. Postharvest Biol. Technol. 43, 319–325. Sinesio, F., Cammareri, M., Moneta, E., Navez, B., Peparaio, M., Causse, M., Grandillo, S., 2010. Sensory quality of fresh French and Dutch market tomatoes: a preference mapping study with Italian consumers. J. Food Sci. 75, S55–S67. Tomekpe, K., Jenny, C., Escalant, J.V., 2004. A review of conventional improvement strategies for Musa. InfoMusa 13, 2–6.