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Development of a sensory quality index for strawberries based on correlation between sensory data and consumer perception
Postharvest Biology and Technology 52 (2009) 97–102
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Postharvest Biology and Technology journal homepage: www.elsevier.com/locate/postharvbio
Development of a sensory quality index for strawberries based on correlation between sensory data and consumer perception Gastón Ares a,b,∗ , Sofía Barrios b , Claudia Lareo b , Patricia Lema b a Sección Evaluación Sensorial, Departamento de Ciencia y Tecnología de Alimentos, Facultad de Química, Universidad de la República, Gral. Flores 2124, C.P. 11800 Montevideo, Uruguay b Instituto de Ingeniería Química, Facultad de Ingeniería, Universidad de la República, Julio Herrera y Reissig 565, C.P. 11300 Montevideo, Uruguay
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Article history: Received 17 July 2008 Accepted 3 November 2008 Keywords: Sensory quality Strawberries Quality control
a b s t r a c t The aim of the present work was to develop a sensory quality index for the appearance and odour of strawberries based on consumer perception. Six samples of strawberries with different degrees of ripeness and deterioration were evaluated by a trained sensory panel and a consumer panel. Using principal component analysis, the sensory quality of strawberries was defined by two indices, one related to the sensory deterioration and another related to the intensity of desirable sensory attributes. As expected, consumer acceptability and intention to purchase strawberries decreased as sensory deterioration index increased and desirable attributes index decreased. A sensory quality index was calculated by correlating consumer acceptability scores with the aforementioned indices. This index allows objective evaluation of the sensory quality of strawberries using a trained assessors panel. Limits for this index could be used in quality control programs or to estimate sensory shelf life of strawberries. The methodology applied in the present work could be applied to other products in order to develop appropriate sensory quality indices based on consumer perception. © 2008 Elsevier B.V. All rights reserved.
1. Introduction According to Molnar (1995), “The quality of food products, in conformity with consumers’ requirements and acceptance, is determined by their sensory attributes, chemical composition, physical properties, level of microbiological and toxicological contaminants, shelf life, packaging and labeling”. Colour and appearance are critical quality aspects for shoppers when selecting fresh fruits and vegetables (IFT, 1990; Ragaert et al., 2004). Moreover, sensory quality often limits the shelf life of fresh and minimally processed fruits and vegetables (IFT, 1990; King et al., 1991; Jacxsens et al., 2002, 2003). This stresses the importance of sensory quality assurance for fresh and minimally processed fruits and vegetables. Sensory quality is related to consumer acceptance and confidence in the product (Cardello, 1995), being defined by the interaction between the food and the consumer. Thus, sensory quality depends on both the sensory characteristics of the food and how consumers perceive them (Costell, 2002).
∗ Corresponding author at: Sección Evaluación Sensorial, Departamento de Ciencia y Tecnología de Alimentos, Facultad de Química, Universidad de la República, Gral. Flores 2124, C.P. 11800 Montevideo, Uruguay. Tel.: +598 2 9245735; fax: +598 2 9241906. E-mail address: [email protected] (G. Ares). 0925-5214/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.postharvbio.2008.11.001
Strawberries are highly perishable products that lose sensory quality shortly after harvest, which limits their shelf life to a few days at ambient temperature (Shamaila et al., 1992; Harker et al., 2000; Van der Steen et al., 2002; Cordenunsi et al., 2003; Pelayo et al., 2003). For this reason, it is important to rely on suitable methods for estimating the sensory quality of strawberries for quality control programs. Traditionally, sensory quality of strawberries has been evaluated considering only their sensory characteristics (Shamaila et al., 1992; Van der Steen et al., 2002; Pelayo et al., 2003; Péneau et al., 2007). This has been done using a trained assessor panels (Shamaila et al., 1992; Van der Steen et al., 2002; Péneau et al., 2007) which objectively evaluate a set of sensory attributes, or using an expert panel (Péneau et al., 2007) which evaluate sensory quality based on their previous experience. Since trained assessor and expert panels might not be representative of consumer perception, the main problem of this approach is how to determine acceptance limits, i.e. which criteria should be used to determine if a strawberry is acceptable or not. Usually, acceptance limits are arbitrarily selected, but information about the implication of these limits for food companies is lacking. Acceptance limits for sensory defects in food products could be appropriately determined using consumer studies, as they are the ones that decide if they would purchase a certain product or ˜ not (Munoz et al., 1992; Hough et al., 2004). However, performing
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consumer studies in quality control programs would be both impractical and expensive (Hough et al., 2002). By correlating data from a consumer panel with those obtained from a trained panel, acceptance limits for the sensory attributes relevant for consumers could be properly established. The aims of the present work were to: (a) correlate consumer acceptability scores with sensory attribute intensities; (b) develop a sensory quality index based on trained assessors data; and (c) estimate acceptance limits for the developed index that could be used in sensory quality control programs and shelf life estimation.
Table 2 Definition of the sensory attributes used for the descriptive analysis of strawberries by the trained assessors’ panel. Attribute
Definition
Off-odour
Intensity of fermentation or other non-characteristic odours Intensity of characteristic strawberry odour Extent of red colour on the outside Shiny appearance on the outer surface Extent of dark bruises or brown stains of the outer surface Absence of shriveling on the outer surface Extent of brown colours on the sepals
Strawberry odour Red colour Gloss Dark bruises Surface evenness Browning on the sepals
2. Materials and methods 2.1. Samples Strawberries (Fragaria ananassa Duch., cv Aroma) were obtained from a local farm near Montevideo, Uruguay. Within 12 h after harvest, strawberries were transported under ambient conditions (20–25 ◦ C) to the School of Engineering in Montevideo. Strawberries were classified into three groups according to their degree of ripeness, judged by the percentage of red colour: unripe (less than 50% red colour), ripe (more than 75% red colour) and overripe strawberries (100% red colour and signs of sensory deterioration—presence of dark bruises, browning of the sepals and shriveling). This classification was performed by three of the trained sensory assessors who participated in the study. Strawberries from these three groups were placed in open plastic containers and stored under different conditions for different times until their evaluation in order to obtain samples with different sensory qualities. The samples used in the present study are summarised in Table 1. These storage conditions were selected considering results from preliminary studies. 2.2. Trained assessors panel A descriptive analysis of the odour and appearance of the strawberries was performed. Only these attributes were considered, as they are usually responsible for consumer purchase decisions. Descriptive analysis was performed by a panel of seven trained assessors, six females and one male, ages ranging from 24 to 45 years old. Assessors were selected and trained following the guidelines of the ISO (1993) standard. They all had a minimum of 100 h of experience in discrimination and descriptive tests of different food products, particularly fresh fruits and vegetables, and had a minimum of 20 h experience in the evaluation of strawberries. To identify those sensory characteristics that define the sensory quality of strawberries, a preliminary test was performed in which five samples with different storage times at 25 ◦ C were presented to assessors. In this session, assessors had to write down the descriptors that made those samples different. By open discussion with the panel leader, assessors agreed on the best descriptors
Table 1 Description of the evaluated strawberry samples and conditions in which they were stored until evaluations were performed. Sample
Description and storage condition
Unripe Ripe Overripe A B C
Stored at 0 ◦ C for 6 d Stored at 0 ◦ C for 6 d Stored at 0 ◦ C for 6 d Ripe strawberries stored at 5 ◦ C for 6 d Ripe strawberries stored at 0 ◦ C for 5 d and at 25 ◦ C for 1 d Ripe strawberries stored at 0 ◦ C for 2 d and at 25 ◦ C for 4 d
to differentiate the odour and appearance of the samples and their description. These attributes were: off-odour, strawberry odour, red colour, gloss, dark bruises, surface evenness, and browning on the sepals. A description of the attributes is shown in Table 2. For scoring, 10 cm unstructured scales anchored with “nil” and “high” were used. Once the descriptors were selected, assessors were trained by evaluating samples with different degrees of ripeness and different storage times at 25 ◦ C. In the first session, assessors were asked to score six samples with different sensory qualities in each of the seven attributes, using 10 cm unstructured scales. Through open discussion with the panel leader assessors agreed on the scores for each of the samples. Samples were stored in sealed polyethylene bags at 0 ◦ C for 2 and 3 d in order to assure that no significant changes in their sensory quality occurred. Two successive sessions were carried out 2 and 3 d after the first session, in which assessors were asked to evaluate the six samples, coded with 3-digit numbers. Assessors were asked to evaluate the samples. A variation in the scale of ± 1 cm from the consensus score was considered acceptable. This procedure was performed four different times using different samples. Thus, a total of twelve 20 min sessions were used to train the panel. For each of the six samples considered in the present study, four strawberries were presented to the assessors in closed odourless plastic containers labelled with three digit random numbers, at room temperature. A balanced complete block design was carried out for duplicate evaluation of the samples. Testing was carried out in a sensory laboratory that was designed in accordance with ISO 8589 (1988). Evaluations were performed under artificial daylight type illumination with temperature control (between 22 and 24 ◦ C) and air circulation. 2.3. Consumer panel Sixty consumers were recruited among students, teachers, and workers from the School of Chemistry in Montevideo, Uruguay. Participants were approximately 50% female and 50% male, and their ages ranged between 18 and 50. For each of the six samples considered in the study, four strawberries were presented to the consumers in closed odourless plastic containers labelled with three digit random numbers, at room temperature. Consumers were asked to evaluate the strawberries and indicate their degree of liking using a 9-point hedonic scale consisting of nine boxes labelled with “dislike very much” on the left, “indifferent” in the middle and “like very much” on the right. Consumers also had to respond “yes” or “no” to the questions “Would you buy these strawberries?” and “Would you consume these strawberries if you had them stored in your refrigerator?”. Consumers were told to evaluate the strawberries as they would normally do if they were going to purchase them. Therefore, consumers could observe and smell the strawberries if they wished to do so.
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3. Data analysis 3.1. Analysis of variance An analysis of variance (ANOVA) was performed on the trained assessors’ data considering sample, assessor, and their interaction as fixed sources of variation. For consumer data, an ANOVA was performed considering sample as a fixed source of variation. Honestly significant differences were calculated using Tukey’s test. Differences were considered significant when p ≤ 0.05. 3.2. Principal component analysis A principal component analysis (PCA) was performed on the mean scores of the trained assessors’ panel data in order to illustrate the relationship among sensory attributes variables and between sensory attributes and samples. PCA was performed considering standardized data. 3.3. Regression analysis A multiple regression analysis was performed considering consumer appearance acceptability as dependent variable and sample loadings for the first two principal components (PCs) of the PCA (PC1 and PC2) of the sensory data as explanatory variables, as shown in Eq. (1). Consumer acceptability = a + b1 PC1 + b2 PC2
(1)
A first- and second-order polynomial regression was performed considering consumer rejection to consume and purchase as dependent variables and consumer appearance acceptability as independent variable. All statistical analyses were performed using Genstat Discovery Edition 2 (VSN International, Oxford, UK). 4. Results and discussion 4.1. Sensory data As shown in Table 3, ANOVA showed that all the evaluated sensory attributes were highly significant in discriminating among samples (p < 0.001), indicating that samples showed different sensory quality. Average scores for the evaluated samples are presented in Table 4. A PCA was performed on the average scores of the seven sensory attributes for the six strawberry samples. The first two principal components accounted for 60.2% and 28.1% of the variance of the experimental data, respectively. As shown in Fig. 1, the first principal component (PC1) on the one hand contrasted positively with off-odour, dark bruises, and browning on the sepals; and negatively with surface evenness. All these attributes are sensory defects related to decay, fermentation, bruising and shriveling. Therefore, PC1 was correlated to sensory attributes that reflect the sensory deterioration of strawberries throughout storage and could be considered an index of sensory deterioration. These attributes explained the greater part of the variability of the sensory characteristics of the evaluated strawberries (60.2%), suggesting that the occurrence of sensory defects could be one of the most important factors that determine the sensory quality of strawberries. On the other hand, the second principal component (PC2) was positively correlated to strawberry odour, red colour, and gloss. Red colour and strawberry odour are indicators of ripeness, whereas gloss could be considered an indicator of freshness. Thus, PC2 was related to attributes that are desirable sensory characteristics of
Fig. 1. Factor loadings on the principal component analysis of data from the trained assessors’ panel descriptive analysis of strawberries with different sensory quality.
strawberries. For this reason, PC2 could be considered a desirable attributes index of strawberries. These results showed that the sensory quality of strawberries could be defined by the intensity of desirable sensory characteristics and their degree of sensory deterioration. The sample scores in the PCA of the sensory data are plotted for the first two PCs in Fig. 2. This figure enabled the discrimination of different groups of strawberries according to their sensory quality. Samples were sorted into four groups. One group was located in the second quadrant, with high values of PC2 and low values of PC1, corresponding to ripe strawberries with little sensory deterioration (ripe and A samples). Another group was located in the fourth quadrant and corresponded to deteriorated strawberries which showed high values of PC1 (samples B and C). Unripe strawberries were located down in PC2 and left in PC1, which suggests a low degree of ripeness and deterioration. Finally, overripe strawberries showed intermediate values of PC1 and high values of PC2, corresponding to slightly deteriorated overripe strawberries.
Fig. 2. Scores of strawberries with different sensory qualities on the principal component analysis plot of data from the trained assessors’ panel descriptive analysis.
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Table 3 F-ratios in the analysis of variance of the sensory data, considering sample, assessor and their interaction as fixed sources of variation. Off-odour
Strawberry odour
***
Sample Assessor Assessor × sample
Browning on the sepals
***
27.4 1.4 ns 0.7 ns
***
30.8 1.1 ns 0.8 ns
Red colour ***
42.5 0.8 ns 1.1 ns
37.6 1.5 ns 1.2 ns
Dark bruises ***
40.9 1.7 ns 0.7 ns
Gloss
Surface evenness
***
73.9*** 0.7 ns 1.4 ns
39.8 1.8 ns 1.2 ns
ns, not significant (p > 0.05). *** Significant at 0.001 probability level.
Table 4 Average scores for the evaluated sensory attributes for strawberries with different sensory qualities, as evaluated by the trained assessors’ panel. Sample
Off-odour
Strawberry odour
Browning on the sepals
Red colour
Dark bruises
Gloss
Surface evenness
Unripe Ripe Overripe A B C
1.9c 1.3c 1.8c 1.4c 3.5b 8.5a
0.9b 8.3a 7.5a 7.8a 2.8b 1.8b
2.6a 1.6a 6.8b 2.8a 5.7b 8.3c
2.9c 7.7b 9.4a 8.8a 9.2a 9.1a
0.3d 0.5d 4.0c 2.6c 6.1b 7.9a
2.1b 6.7a 6.7a 1.2b,c 1.5b,c 0.3c
8.7a 9.1a 1.3c 4.3b 1.7c 0.7c
Scores within the same column with different superscript are significantly different according to Tukey’s test (p ≤ 0.05). A: ripe strawberries stored at 5 ◦ C for 6 d; B: ripe strawberries stored at 0 ◦ C for 5 d and at 25 ◦ C for 1 d; C: ripe strawberries stored at 0 ◦ C for 2 d and at 25 ◦ C for 4 d.
In a principal component analysis, each of the principal components consists of a linear combination of variables. In this case, each PC is a linear combination of sensory attributes. Considering the abovementioned results and only the attributes that mostly contribute to each PC, PC1 is mainly a linear combination of sensory attributes related to deterioration, whereas PC2 is mainly a combination of desirable sensory attributes of strawberries. Thus, PC1 can be regarded as a sensory deterioration index and PC2 an index of the intensity of desirable attributes. Therefore, these indices could be calculated by using the average scores for the evaluated sensory attributes and their loadings in the PCA of the sensory data. These two quality indices, desirable attributes and deterioration index, could be calculated by multiplying the score for the attribute by its eigenvector, as shown in Eqs. (2) and (3). Deterioration index = −1.62 + 0.15 × Off-odour + 0.17 × Browning on the sepals + 0.16 × Dark bruises − 0.12 × Surface evenness (2)
for these indices by taking into account consumer perception of strawberries. 4.2. Consumer perception Consumers showed highly significantly different degrees of liking (p < 0.001) for the evaluated strawberries. As shown in Table 5, consumer acceptability scores ranged from 7.7 for ripe strawberries to 1.9 for overripe. Consumer rejection to purchase and consume also differed between the samples. This indicates that differences in the sensory quality of the strawberries affected consumer perception and acceptance. In order to determine how the evaluated sensory attributes affected consumer acceptability scores, a multiple linear regression was performed considering acceptability scores as dependent variable and the sample scores for the sensory deterioration and desirable attributes index (Eqs. (2) and (3)) as explanatory variables. This regression explained 86.5% of the variance of the experimental data: Consumer acceptability = 5.24 − 0.74 × Sensory deterioration index
Desirable sensory attribute index = −2.86 + 0.18
+ 0.63 × Desirable attributes index
× Strawberry odour + 0.22 × Red colour + 0.16 × Gloss (3) The abovementioned equations show how each of the attributes contribute to the degree of deterioration and the intensity of desirable sensory attributes of strawberries and their relative importance in this sense. In the case of Eq. (2), the coefficients preceding each term are similar, meaning that all attributes contribute evenly to the deterioration index. The same happens in the case of Eq. (3), where red colour, strawberry odour, and gloss have a similar contribution to the sensory attributes index. Therefore, the sensory quality of strawberries could be characterized by estimating these two indices, i.e. quantifying the degree of sensory deterioration and the intensity of desirable sensory attributes of strawberries. However, the relationships established in the equations presented above do not reflect consumer perception and do not provide information regarding the acceptance of the strawberries. In order to use these indices in sensory quality control programs or sensory shelf life studies objective acceptance limits should be established
(4)
As shown in Eq. (4), consumer acceptability decreased with an increase in the sensory deterioration index and a decrease in the desirable sensory attribute index. This indicates that consumers like ripe strawberries without signs of deterioration. The development of sensory defects, such as dark bruises, browning on the Table 5 Average consumer acceptability and rejection to purchase and consume percentages for strawberries with different sensory quality. Samples
Consumer acceptability
Rejection to purchase percentage (%)
Rejection to consume percentage (%)
Unripe Ripe Overripe A B C
4.8d 7.7a 5.6c 6.1b,c 5.5c 1.9e
57 12 43 32 42 100
27 2 13 10 15 83
Acceptability scores with different superscript are significantly different according to Tukey’s test (p ≤ 0.05). A: ripe strawberries stored at 5 ◦ C for 6 d; B: ripe strawberries stored at 0 ◦ C for 5 d and at 25 ◦ C for 1 d; C: ripe strawberries stored at 0 ◦ C for 2 d and at 25 ◦ C for 4 d.
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sepals, off-odour, and shriveling, lead to a decrease in acceptability. As shown in Eq. (4) the influence of sensory defects of consumer acceptability was higher than that of positive attributes, as shown by the coefficients for both indices. Péneau et al. (2007) reported that freshness of strawberries was mainly affected by the absence of a set of negative attributes rather than by the occurrence of positive attributes. This was not so in the present work, where both negative and positive attributes evaluated contributed to the consumer acceptability of strawberries, and consequently to their sensory quality. Using Eq. (4) consumer acceptability of strawberries could be predicted by estimating both the sensory deterioration index and the desirable attributes index, i.e. by determining the sensory characteristics of strawberries with a trained assessors’ panel. Acceptance limits for the developed indices need to be established in order to determine how deteriorated a strawberry can be before consumers reject it. In order to establish these acceptance limits for quality control programs or sensory shelf life studies, a minimum acceptability should be selected. For shelf life estimation and quality control, a score of 6 in a 9-point hedonic scale has been used as cut-off point, since it is the first liking score (Gámbaro et al., 2006; Giménez et al., 2007). Thus, in order to accept a strawberry for its commercialization, it should show an acceptability score higher than 6. Considering Eq. (4) and this score, the following relationship could be established: 5.24 − 0.74 × Sensory deterioration index + 0.63 × Desirable attributes index ≥ 6
(5)
not consume overripe strawberries, 43% of the consumers would not buy them. This difference between rejection to consume and rejection to purchase could be attributed to the fact that when consumers think of consuming the product they are more tolerant to defects because they have already bought it and they do not want to discard it. Therefore, rejection to purchase instead rejection to consume should be considered for estimating acceptance limits as it might be a more conservative criterion to assure the product quality. If sensory quality of strawberries is determined considering rejection to consume, a high proportion of consumers might reject to purchase the product at supermarkets. This could cause important economic losses at both production and commercialization stages, as some of these products might not be bought. This is in agreement with previous results for lettuce in modified atmosphere packages (Ares et al., 2008). Thus, only rejection to purchase was considered for further analysis. A linear relationship was found between consumer acceptability scores and rejection to purchase data, as shown in Eq. (8). Rejection to purchase = 129.8 − 15.4 × Acceptability (R2 = 0.993) (8) Twenty-five percent has been considered as maximum rejection percentage in quality control (Giménez et al., 2008). Thus, using this percentage, the minimum acceptability score could be calculated using Eq. (8). This percentage corresponds to an acceptability score of 6.7, stricter than the score of 6 considered above. Using this limit in Eqs. (5) and (6), Eq. (7) would become the following expression: Sensory Quality index ≥ 1.46
Therefore, the above relationship could be used in order to determine if a strawberry is accepted or rejected using scores for the sensory deterioration and desirable attributes indices. Using Eq. (5), a sensory quality index could be calculated from the sensory deterioration index and the desirable sensory attributes index using the following equation: Sensory Quality Index = −0.74 × Sensory deterioration index + 0.63 × Desirable sensory attributes index
(6)
Considering a minimum consumer acceptability of 6, and the expressions in Eqs. (5) and (6), if a strawberry shows a sensory quality index higher than 0.76, it would show a consumer acceptability higher than 6, which could be considered acceptable. Then Eq. (6) could be established. Sensory Quality index ≥ 0.76
(7)
Most published work dealing with the estimation of sensory quality of strawberries uses trained assessors to estimate sensory quality (Shamaila et al., 1992; Van der Steen et al., 2002; Ragaert et al., 2006). However, this approach relies on the fact that each assessor determines the relative importance of each of the sensory attributes of strawberries. Therefore, the methodology proposed in the present work consists is an improvement because the importance of each attribute is determined using statistical techniques and consumer perception of the product. A sensory quality index is calculated considering only objective data from a trained assessors’ panel which analytically measures sensory attributes. Another criterion for estimating acceptance limits is selecting a maximum rejection to consume or to purchase (Hough et al., 2004; Giménez et al., 2008). As shown in Table 5, rejection to consume was always lower than rejection to purchase, suggesting that consumers are stricter at time of purchase than at the consumption stage. For example, whereas only 13% of the consumers would
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(9)
Thus, a strawberry showing a sensory quality index lower than 1.46 would be bought by less than 75% of the consumers. Since these limits take into account consumer perceptions of the product, they consist an improvement over more arbitrary criteria used by other authors for estimating the sensory quality of strawberries (Shamaila et al., 1992; Van der Steen et al., 2002). These limits for sensory quality could be used to estimate the sensory shelf life of strawberries. Some studies have estimated the sensory shelf life of minimally processed strawberries as the time necesarry to reach an arbitrary limit of a certain sensory attribute, as evaluated by a trained sensory panel. However, in order to assure the products’ quality at the end of their shelf life these limits should be based on consumer perceptions. The estimation of sensory quality based on data from a trained assessors’ panel could be a cost-effective and interesting alternative, particularly in small developing countries such as Uruguay. However it could be interesting to study correlations between sensory quality and physicochemical or instrumental measurements in order to make the estimation of sensory quality faster and easier. Further research is necessary to develop a quality index that correlates with consumer perception and is based on this type of technique. 5. Conclusions In the present work, the objective data obtained from a trained assessors’ panel was correlated to consumer perceptions of strawberries. By relating subjective consumer data to objective assessors’ data, a Sensory Quality Index was developed. The developed index could be used for estimating sensory quality of strawberries using a sensory panel which objectively evaluates sensory characteristics. Limits for this index would be useful in quality control and sensory shelf life studies to assure the quality of strawberries and minimize consumer rejection of the product. In this study, limits were defined using consumer acceptability and rejection to purchase because they are more objective criteria that take consumer
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perception into account, instead of relying on trained assessors to decide the relative importance of each of the sensory characteristics of strawberries. The methodology applied in the present work could be applied to other products in order to develop objective sensory quality indices based on consumer perception. Acknowledgements The authors are indebted to CSIC (Comisión Sectorial de Investigación Científica, Uruguay) and Comisión Administradora del Mercado Modelo (Intendencia Municipal de Montevideo) for financial support. References Ares, G., Giménez, A., Gámbaro, A., 2008. Shelf life estimation of minimally processed lettuce considering two stages of consumers’ decision making process. Appetite 50, 529–535. Cardello, A.V., 1995. Food quality: conceptual and sensory aspects. Food Qual. Pref. 6, 163–168. Cordenunsi, B.R., Nascimento, J.R.O., Lajolo, F.M., 2003. Physico-chemical changes related to quality of five strawberry fruit cultivars during cool-storage. Food Chem. 83, 167–183. Costell, E., 2002. A comparison of sensory methods in quality control. Food Qual. Pref. 13, 341–353. Gámbaro, A., Ares, G., Giménez, A., 2006. Shelf life estimation of apple baby food. J. Sens. Stud. 21 (1), 101–111. Giménez, A., Varela, P., Salvador, A., Ares, G., Fiszman, S., Garitta, L., 2007. Shelf life estimation of brown bread: a consumer approach. Food Qual. Pref. 18, 196–204. Giménez, A., Ares, G., Gámbaro, A., 2008. Consumers’ perception of sandiness in dulce de leche. J. Sens. Stud. 23 (2), 171–185. Harker, F.R., Elgar, H.J., Watkins, C.B., Jackson, P.J., Hallett, I.C., 2000. Physical and mechanical changes in strawberry fruit after high carbon dioxide treatments. Postharvest. Biol. Technol. 19, 139–146. Hough, G., Sánchez, R.H., Garbarini De Pablo, G., Sánchez, R.G., Calderón Villaplana, S., Giménez, A.M., Gámbaro, A., 2002. Consumer acceptability versus trained sensory panel scores of powdered milk shelf-life defects. J. Dairy Sci. 85, 1–6.
Hough, G., Garrita, L., Sánchez, R., 2004. Determination of consumer acceptance limits to sensory defects using survival analysis. Food Qual. Pref. 15, 729–734. IFT, 1990. Quality of fruits and vegetables. A scientific status summary of IFT expert panel on food safety and nutrition. Food Technol. 44, 99–106. ISO, 1988. Sensory Analysis: General Guidance for the Design of Test Rooms, ISO 8589. International Organization for Standardization, Geneva, Switzerland. ISO, 1993. ISO Standard 8586-1. Sensory Analysis—General Guidance for the Selection, Training, and Monitoring Of assessors. Part 1: Selected Assessors, 1st ed. International Organization for Standardization, Geneva, Switzerland. Jacxsens, L., Devlieghere, F., Debevere, J., 2002. Temperature dependence of shelflife as affected by microbial proliferation and sensory quality of equilibrium modified atmosphere packaged fresh produce. Postharvest. Biol. Technol. 26, 59–73. Jacxsens, L., Devlieghere, F., Ragaert, P., Vanneste, E., Debevere, J., 2003. Relation between microbiological quality, metabolite production and sensory quality of equilibrium modified atmosphere packaged fresh-cut produce. Int. J. Food Microbiol. 83, 263–280. King, A.D., Magnuson, J.A., Török, T., Goodman, N., 1991. Microbial flora and storage quality of partially processed lettuce. J. Food Sci. 56, 459–461. Molnar, P.J., 1995. A model for overall description of food quality. Food Qual. Pref. 6, 185–190. ˜ Munoz, A.M., Civille, V.G., Carr, B.T., 1992. Sensory Evaluation in Quality Control. Van Mostrand, Reinhold, USA. Pelayo, C., Ebeler, S.E., Kader, A.A., 2003. Postharvest life and flavor quality of three strawberry cultivars kept at 5 ◦ C in air or air +20 kPa CO2 . Postharvest. Biol. Technol. 27, 171–183. Péneau, S., Brockhoff, P.B., Escher, F., Nuessli, J., 2007. A comprehensive approach to evaluate the freshness of strawberries and carrots. Postharvest. Biol. Technol. 45, 20–29. Ragaert, P., Devlieghere, F., Loos, S., Dewulf, J., Van Langenhove, H., Foubert, I., Vanrolleghem, P.A., Debevere, J., 2006. Role of yeast proliferation in the quality degradation of strawberries during refrigerated storage. Int. J. Food Microbiol. 108, 42–50. Ragaert, P., Verbeke, W., Devlieghere, F., Debevere, J., 2004. Consumer perception and choice of minimally processed vegetables and packaged fruits. Food Qual. Pref. 15, 259–270. Shamaila, M., Powrie, W.D., Skura, B.J., 1992. Sensory evaluation of strawberry fruit stored under modified atmosphere packaging (MAP) by quantitative descriptive analysis. J. Food Sci. 57, 1168–1172. Van der Steen, C., Jacxsens, L., Devlieghere, F., Debevere, J., 2002. Combining high oxygen atmospheres with low oxygen modified atmosphere packaging to improve the keeping quality of strawberries and raspberries. Postharvest. Biol. Technol. 26, 49–58.
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Development of a sensory quality index for strawberries based on correlation between sensory data and consumer perception Gastón Ares a,b,∗ , Sofía Barrios b , Claudia Lareo b , Patricia Lema b a Sección Evaluación Sensorial, Departamento de Ciencia y Tecnología de Alimentos, Facultad de Química, Universidad de la República, Gral. Flores 2124, C.P. 11800 Montevideo, Uruguay b Instituto de Ingeniería Química, Facultad de Ingeniería, Universidad de la República, Julio Herrera y Reissig 565, C.P. 11300 Montevideo, Uruguay
a r t i c l e
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Article history: Received 17 July 2008 Accepted 3 November 2008 Keywords: Sensory quality Strawberries Quality control
a b s t r a c t The aim of the present work was to develop a sensory quality index for the appearance and odour of strawberries based on consumer perception. Six samples of strawberries with different degrees of ripeness and deterioration were evaluated by a trained sensory panel and a consumer panel. Using principal component analysis, the sensory quality of strawberries was defined by two indices, one related to the sensory deterioration and another related to the intensity of desirable sensory attributes. As expected, consumer acceptability and intention to purchase strawberries decreased as sensory deterioration index increased and desirable attributes index decreased. A sensory quality index was calculated by correlating consumer acceptability scores with the aforementioned indices. This index allows objective evaluation of the sensory quality of strawberries using a trained assessors panel. Limits for this index could be used in quality control programs or to estimate sensory shelf life of strawberries. The methodology applied in the present work could be applied to other products in order to develop appropriate sensory quality indices based on consumer perception. © 2008 Elsevier B.V. All rights reserved.
1. Introduction According to Molnar (1995), “The quality of food products, in conformity with consumers’ requirements and acceptance, is determined by their sensory attributes, chemical composition, physical properties, level of microbiological and toxicological contaminants, shelf life, packaging and labeling”. Colour and appearance are critical quality aspects for shoppers when selecting fresh fruits and vegetables (IFT, 1990; Ragaert et al., 2004). Moreover, sensory quality often limits the shelf life of fresh and minimally processed fruits and vegetables (IFT, 1990; King et al., 1991; Jacxsens et al., 2002, 2003). This stresses the importance of sensory quality assurance for fresh and minimally processed fruits and vegetables. Sensory quality is related to consumer acceptance and confidence in the product (Cardello, 1995), being defined by the interaction between the food and the consumer. Thus, sensory quality depends on both the sensory characteristics of the food and how consumers perceive them (Costell, 2002).
∗ Corresponding author at: Sección Evaluación Sensorial, Departamento de Ciencia y Tecnología de Alimentos, Facultad de Química, Universidad de la República, Gral. Flores 2124, C.P. 11800 Montevideo, Uruguay. Tel.: +598 2 9245735; fax: +598 2 9241906. E-mail address: [email protected] (G. Ares). 0925-5214/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.postharvbio.2008.11.001
Strawberries are highly perishable products that lose sensory quality shortly after harvest, which limits their shelf life to a few days at ambient temperature (Shamaila et al., 1992; Harker et al., 2000; Van der Steen et al., 2002; Cordenunsi et al., 2003; Pelayo et al., 2003). For this reason, it is important to rely on suitable methods for estimating the sensory quality of strawberries for quality control programs. Traditionally, sensory quality of strawberries has been evaluated considering only their sensory characteristics (Shamaila et al., 1992; Van der Steen et al., 2002; Pelayo et al., 2003; Péneau et al., 2007). This has been done using a trained assessor panels (Shamaila et al., 1992; Van der Steen et al., 2002; Péneau et al., 2007) which objectively evaluate a set of sensory attributes, or using an expert panel (Péneau et al., 2007) which evaluate sensory quality based on their previous experience. Since trained assessor and expert panels might not be representative of consumer perception, the main problem of this approach is how to determine acceptance limits, i.e. which criteria should be used to determine if a strawberry is acceptable or not. Usually, acceptance limits are arbitrarily selected, but information about the implication of these limits for food companies is lacking. Acceptance limits for sensory defects in food products could be appropriately determined using consumer studies, as they are the ones that decide if they would purchase a certain product or ˜ not (Munoz et al., 1992; Hough et al., 2004). However, performing
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consumer studies in quality control programs would be both impractical and expensive (Hough et al., 2002). By correlating data from a consumer panel with those obtained from a trained panel, acceptance limits for the sensory attributes relevant for consumers could be properly established. The aims of the present work were to: (a) correlate consumer acceptability scores with sensory attribute intensities; (b) develop a sensory quality index based on trained assessors data; and (c) estimate acceptance limits for the developed index that could be used in sensory quality control programs and shelf life estimation.
Table 2 Definition of the sensory attributes used for the descriptive analysis of strawberries by the trained assessors’ panel. Attribute
Definition
Off-odour
Intensity of fermentation or other non-characteristic odours Intensity of characteristic strawberry odour Extent of red colour on the outside Shiny appearance on the outer surface Extent of dark bruises or brown stains of the outer surface Absence of shriveling on the outer surface Extent of brown colours on the sepals
Strawberry odour Red colour Gloss Dark bruises Surface evenness Browning on the sepals
2. Materials and methods 2.1. Samples Strawberries (Fragaria ananassa Duch., cv Aroma) were obtained from a local farm near Montevideo, Uruguay. Within 12 h after harvest, strawberries were transported under ambient conditions (20–25 ◦ C) to the School of Engineering in Montevideo. Strawberries were classified into three groups according to their degree of ripeness, judged by the percentage of red colour: unripe (less than 50% red colour), ripe (more than 75% red colour) and overripe strawberries (100% red colour and signs of sensory deterioration—presence of dark bruises, browning of the sepals and shriveling). This classification was performed by three of the trained sensory assessors who participated in the study. Strawberries from these three groups were placed in open plastic containers and stored under different conditions for different times until their evaluation in order to obtain samples with different sensory qualities. The samples used in the present study are summarised in Table 1. These storage conditions were selected considering results from preliminary studies. 2.2. Trained assessors panel A descriptive analysis of the odour and appearance of the strawberries was performed. Only these attributes were considered, as they are usually responsible for consumer purchase decisions. Descriptive analysis was performed by a panel of seven trained assessors, six females and one male, ages ranging from 24 to 45 years old. Assessors were selected and trained following the guidelines of the ISO (1993) standard. They all had a minimum of 100 h of experience in discrimination and descriptive tests of different food products, particularly fresh fruits and vegetables, and had a minimum of 20 h experience in the evaluation of strawberries. To identify those sensory characteristics that define the sensory quality of strawberries, a preliminary test was performed in which five samples with different storage times at 25 ◦ C were presented to assessors. In this session, assessors had to write down the descriptors that made those samples different. By open discussion with the panel leader, assessors agreed on the best descriptors
Table 1 Description of the evaluated strawberry samples and conditions in which they were stored until evaluations were performed. Sample
Description and storage condition
Unripe Ripe Overripe A B C
Stored at 0 ◦ C for 6 d Stored at 0 ◦ C for 6 d Stored at 0 ◦ C for 6 d Ripe strawberries stored at 5 ◦ C for 6 d Ripe strawberries stored at 0 ◦ C for 5 d and at 25 ◦ C for 1 d Ripe strawberries stored at 0 ◦ C for 2 d and at 25 ◦ C for 4 d
to differentiate the odour and appearance of the samples and their description. These attributes were: off-odour, strawberry odour, red colour, gloss, dark bruises, surface evenness, and browning on the sepals. A description of the attributes is shown in Table 2. For scoring, 10 cm unstructured scales anchored with “nil” and “high” were used. Once the descriptors were selected, assessors were trained by evaluating samples with different degrees of ripeness and different storage times at 25 ◦ C. In the first session, assessors were asked to score six samples with different sensory qualities in each of the seven attributes, using 10 cm unstructured scales. Through open discussion with the panel leader assessors agreed on the scores for each of the samples. Samples were stored in sealed polyethylene bags at 0 ◦ C for 2 and 3 d in order to assure that no significant changes in their sensory quality occurred. Two successive sessions were carried out 2 and 3 d after the first session, in which assessors were asked to evaluate the six samples, coded with 3-digit numbers. Assessors were asked to evaluate the samples. A variation in the scale of ± 1 cm from the consensus score was considered acceptable. This procedure was performed four different times using different samples. Thus, a total of twelve 20 min sessions were used to train the panel. For each of the six samples considered in the present study, four strawberries were presented to the assessors in closed odourless plastic containers labelled with three digit random numbers, at room temperature. A balanced complete block design was carried out for duplicate evaluation of the samples. Testing was carried out in a sensory laboratory that was designed in accordance with ISO 8589 (1988). Evaluations were performed under artificial daylight type illumination with temperature control (between 22 and 24 ◦ C) and air circulation. 2.3. Consumer panel Sixty consumers were recruited among students, teachers, and workers from the School of Chemistry in Montevideo, Uruguay. Participants were approximately 50% female and 50% male, and their ages ranged between 18 and 50. For each of the six samples considered in the study, four strawberries were presented to the consumers in closed odourless plastic containers labelled with three digit random numbers, at room temperature. Consumers were asked to evaluate the strawberries and indicate their degree of liking using a 9-point hedonic scale consisting of nine boxes labelled with “dislike very much” on the left, “indifferent” in the middle and “like very much” on the right. Consumers also had to respond “yes” or “no” to the questions “Would you buy these strawberries?” and “Would you consume these strawberries if you had them stored in your refrigerator?”. Consumers were told to evaluate the strawberries as they would normally do if they were going to purchase them. Therefore, consumers could observe and smell the strawberries if they wished to do so.
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3. Data analysis 3.1. Analysis of variance An analysis of variance (ANOVA) was performed on the trained assessors’ data considering sample, assessor, and their interaction as fixed sources of variation. For consumer data, an ANOVA was performed considering sample as a fixed source of variation. Honestly significant differences were calculated using Tukey’s test. Differences were considered significant when p ≤ 0.05. 3.2. Principal component analysis A principal component analysis (PCA) was performed on the mean scores of the trained assessors’ panel data in order to illustrate the relationship among sensory attributes variables and between sensory attributes and samples. PCA was performed considering standardized data. 3.3. Regression analysis A multiple regression analysis was performed considering consumer appearance acceptability as dependent variable and sample loadings for the first two principal components (PCs) of the PCA (PC1 and PC2) of the sensory data as explanatory variables, as shown in Eq. (1). Consumer acceptability = a + b1 PC1 + b2 PC2
(1)
A first- and second-order polynomial regression was performed considering consumer rejection to consume and purchase as dependent variables and consumer appearance acceptability as independent variable. All statistical analyses were performed using Genstat Discovery Edition 2 (VSN International, Oxford, UK). 4. Results and discussion 4.1. Sensory data As shown in Table 3, ANOVA showed that all the evaluated sensory attributes were highly significant in discriminating among samples (p < 0.001), indicating that samples showed different sensory quality. Average scores for the evaluated samples are presented in Table 4. A PCA was performed on the average scores of the seven sensory attributes for the six strawberry samples. The first two principal components accounted for 60.2% and 28.1% of the variance of the experimental data, respectively. As shown in Fig. 1, the first principal component (PC1) on the one hand contrasted positively with off-odour, dark bruises, and browning on the sepals; and negatively with surface evenness. All these attributes are sensory defects related to decay, fermentation, bruising and shriveling. Therefore, PC1 was correlated to sensory attributes that reflect the sensory deterioration of strawberries throughout storage and could be considered an index of sensory deterioration. These attributes explained the greater part of the variability of the sensory characteristics of the evaluated strawberries (60.2%), suggesting that the occurrence of sensory defects could be one of the most important factors that determine the sensory quality of strawberries. On the other hand, the second principal component (PC2) was positively correlated to strawberry odour, red colour, and gloss. Red colour and strawberry odour are indicators of ripeness, whereas gloss could be considered an indicator of freshness. Thus, PC2 was related to attributes that are desirable sensory characteristics of
Fig. 1. Factor loadings on the principal component analysis of data from the trained assessors’ panel descriptive analysis of strawberries with different sensory quality.
strawberries. For this reason, PC2 could be considered a desirable attributes index of strawberries. These results showed that the sensory quality of strawberries could be defined by the intensity of desirable sensory characteristics and their degree of sensory deterioration. The sample scores in the PCA of the sensory data are plotted for the first two PCs in Fig. 2. This figure enabled the discrimination of different groups of strawberries according to their sensory quality. Samples were sorted into four groups. One group was located in the second quadrant, with high values of PC2 and low values of PC1, corresponding to ripe strawberries with little sensory deterioration (ripe and A samples). Another group was located in the fourth quadrant and corresponded to deteriorated strawberries which showed high values of PC1 (samples B and C). Unripe strawberries were located down in PC2 and left in PC1, which suggests a low degree of ripeness and deterioration. Finally, overripe strawberries showed intermediate values of PC1 and high values of PC2, corresponding to slightly deteriorated overripe strawberries.
Fig. 2. Scores of strawberries with different sensory qualities on the principal component analysis plot of data from the trained assessors’ panel descriptive analysis.
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Table 3 F-ratios in the analysis of variance of the sensory data, considering sample, assessor and their interaction as fixed sources of variation. Off-odour
Strawberry odour
***
Sample Assessor Assessor × sample
Browning on the sepals
***
27.4 1.4 ns 0.7 ns
***
30.8 1.1 ns 0.8 ns
Red colour ***
42.5 0.8 ns 1.1 ns
37.6 1.5 ns 1.2 ns
Dark bruises ***
40.9 1.7 ns 0.7 ns
Gloss
Surface evenness
***
73.9*** 0.7 ns 1.4 ns
39.8 1.8 ns 1.2 ns
ns, not significant (p > 0.05). *** Significant at 0.001 probability level.
Table 4 Average scores for the evaluated sensory attributes for strawberries with different sensory qualities, as evaluated by the trained assessors’ panel. Sample
Off-odour
Strawberry odour
Browning on the sepals
Red colour
Dark bruises
Gloss
Surface evenness
Unripe Ripe Overripe A B C
1.9c 1.3c 1.8c 1.4c 3.5b 8.5a
0.9b 8.3a 7.5a 7.8a 2.8b 1.8b
2.6a 1.6a 6.8b 2.8a 5.7b 8.3c
2.9c 7.7b 9.4a 8.8a 9.2a 9.1a
0.3d 0.5d 4.0c 2.6c 6.1b 7.9a
2.1b 6.7a 6.7a 1.2b,c 1.5b,c 0.3c
8.7a 9.1a 1.3c 4.3b 1.7c 0.7c
Scores within the same column with different superscript are significantly different according to Tukey’s test (p ≤ 0.05). A: ripe strawberries stored at 5 ◦ C for 6 d; B: ripe strawberries stored at 0 ◦ C for 5 d and at 25 ◦ C for 1 d; C: ripe strawberries stored at 0 ◦ C for 2 d and at 25 ◦ C for 4 d.
In a principal component analysis, each of the principal components consists of a linear combination of variables. In this case, each PC is a linear combination of sensory attributes. Considering the abovementioned results and only the attributes that mostly contribute to each PC, PC1 is mainly a linear combination of sensory attributes related to deterioration, whereas PC2 is mainly a combination of desirable sensory attributes of strawberries. Thus, PC1 can be regarded as a sensory deterioration index and PC2 an index of the intensity of desirable attributes. Therefore, these indices could be calculated by using the average scores for the evaluated sensory attributes and their loadings in the PCA of the sensory data. These two quality indices, desirable attributes and deterioration index, could be calculated by multiplying the score for the attribute by its eigenvector, as shown in Eqs. (2) and (3). Deterioration index = −1.62 + 0.15 × Off-odour + 0.17 × Browning on the sepals + 0.16 × Dark bruises − 0.12 × Surface evenness (2)
for these indices by taking into account consumer perception of strawberries. 4.2. Consumer perception Consumers showed highly significantly different degrees of liking (p < 0.001) for the evaluated strawberries. As shown in Table 5, consumer acceptability scores ranged from 7.7 for ripe strawberries to 1.9 for overripe. Consumer rejection to purchase and consume also differed between the samples. This indicates that differences in the sensory quality of the strawberries affected consumer perception and acceptance. In order to determine how the evaluated sensory attributes affected consumer acceptability scores, a multiple linear regression was performed considering acceptability scores as dependent variable and the sample scores for the sensory deterioration and desirable attributes index (Eqs. (2) and (3)) as explanatory variables. This regression explained 86.5% of the variance of the experimental data: Consumer acceptability = 5.24 − 0.74 × Sensory deterioration index
Desirable sensory attribute index = −2.86 + 0.18
+ 0.63 × Desirable attributes index
× Strawberry odour + 0.22 × Red colour + 0.16 × Gloss (3) The abovementioned equations show how each of the attributes contribute to the degree of deterioration and the intensity of desirable sensory attributes of strawberries and their relative importance in this sense. In the case of Eq. (2), the coefficients preceding each term are similar, meaning that all attributes contribute evenly to the deterioration index. The same happens in the case of Eq. (3), where red colour, strawberry odour, and gloss have a similar contribution to the sensory attributes index. Therefore, the sensory quality of strawberries could be characterized by estimating these two indices, i.e. quantifying the degree of sensory deterioration and the intensity of desirable sensory attributes of strawberries. However, the relationships established in the equations presented above do not reflect consumer perception and do not provide information regarding the acceptance of the strawberries. In order to use these indices in sensory quality control programs or sensory shelf life studies objective acceptance limits should be established
(4)
As shown in Eq. (4), consumer acceptability decreased with an increase in the sensory deterioration index and a decrease in the desirable sensory attribute index. This indicates that consumers like ripe strawberries without signs of deterioration. The development of sensory defects, such as dark bruises, browning on the Table 5 Average consumer acceptability and rejection to purchase and consume percentages for strawberries with different sensory quality. Samples
Consumer acceptability
Rejection to purchase percentage (%)
Rejection to consume percentage (%)
Unripe Ripe Overripe A B C
4.8d 7.7a 5.6c 6.1b,c 5.5c 1.9e
57 12 43 32 42 100
27 2 13 10 15 83
Acceptability scores with different superscript are significantly different according to Tukey’s test (p ≤ 0.05). A: ripe strawberries stored at 5 ◦ C for 6 d; B: ripe strawberries stored at 0 ◦ C for 5 d and at 25 ◦ C for 1 d; C: ripe strawberries stored at 0 ◦ C for 2 d and at 25 ◦ C for 4 d.
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sepals, off-odour, and shriveling, lead to a decrease in acceptability. As shown in Eq. (4) the influence of sensory defects of consumer acceptability was higher than that of positive attributes, as shown by the coefficients for both indices. Péneau et al. (2007) reported that freshness of strawberries was mainly affected by the absence of a set of negative attributes rather than by the occurrence of positive attributes. This was not so in the present work, where both negative and positive attributes evaluated contributed to the consumer acceptability of strawberries, and consequently to their sensory quality. Using Eq. (4) consumer acceptability of strawberries could be predicted by estimating both the sensory deterioration index and the desirable attributes index, i.e. by determining the sensory characteristics of strawberries with a trained assessors’ panel. Acceptance limits for the developed indices need to be established in order to determine how deteriorated a strawberry can be before consumers reject it. In order to establish these acceptance limits for quality control programs or sensory shelf life studies, a minimum acceptability should be selected. For shelf life estimation and quality control, a score of 6 in a 9-point hedonic scale has been used as cut-off point, since it is the first liking score (Gámbaro et al., 2006; Giménez et al., 2007). Thus, in order to accept a strawberry for its commercialization, it should show an acceptability score higher than 6. Considering Eq. (4) and this score, the following relationship could be established: 5.24 − 0.74 × Sensory deterioration index + 0.63 × Desirable attributes index ≥ 6
(5)
not consume overripe strawberries, 43% of the consumers would not buy them. This difference between rejection to consume and rejection to purchase could be attributed to the fact that when consumers think of consuming the product they are more tolerant to defects because they have already bought it and they do not want to discard it. Therefore, rejection to purchase instead rejection to consume should be considered for estimating acceptance limits as it might be a more conservative criterion to assure the product quality. If sensory quality of strawberries is determined considering rejection to consume, a high proportion of consumers might reject to purchase the product at supermarkets. This could cause important economic losses at both production and commercialization stages, as some of these products might not be bought. This is in agreement with previous results for lettuce in modified atmosphere packages (Ares et al., 2008). Thus, only rejection to purchase was considered for further analysis. A linear relationship was found between consumer acceptability scores and rejection to purchase data, as shown in Eq. (8). Rejection to purchase = 129.8 − 15.4 × Acceptability (R2 = 0.993) (8) Twenty-five percent has been considered as maximum rejection percentage in quality control (Giménez et al., 2008). Thus, using this percentage, the minimum acceptability score could be calculated using Eq. (8). This percentage corresponds to an acceptability score of 6.7, stricter than the score of 6 considered above. Using this limit in Eqs. (5) and (6), Eq. (7) would become the following expression: Sensory Quality index ≥ 1.46
Therefore, the above relationship could be used in order to determine if a strawberry is accepted or rejected using scores for the sensory deterioration and desirable attributes indices. Using Eq. (5), a sensory quality index could be calculated from the sensory deterioration index and the desirable sensory attributes index using the following equation: Sensory Quality Index = −0.74 × Sensory deterioration index + 0.63 × Desirable sensory attributes index
(6)
Considering a minimum consumer acceptability of 6, and the expressions in Eqs. (5) and (6), if a strawberry shows a sensory quality index higher than 0.76, it would show a consumer acceptability higher than 6, which could be considered acceptable. Then Eq. (6) could be established. Sensory Quality index ≥ 0.76
(7)
Most published work dealing with the estimation of sensory quality of strawberries uses trained assessors to estimate sensory quality (Shamaila et al., 1992; Van der Steen et al., 2002; Ragaert et al., 2006). However, this approach relies on the fact that each assessor determines the relative importance of each of the sensory attributes of strawberries. Therefore, the methodology proposed in the present work consists is an improvement because the importance of each attribute is determined using statistical techniques and consumer perception of the product. A sensory quality index is calculated considering only objective data from a trained assessors’ panel which analytically measures sensory attributes. Another criterion for estimating acceptance limits is selecting a maximum rejection to consume or to purchase (Hough et al., 2004; Giménez et al., 2008). As shown in Table 5, rejection to consume was always lower than rejection to purchase, suggesting that consumers are stricter at time of purchase than at the consumption stage. For example, whereas only 13% of the consumers would
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(9)
Thus, a strawberry showing a sensory quality index lower than 1.46 would be bought by less than 75% of the consumers. Since these limits take into account consumer perceptions of the product, they consist an improvement over more arbitrary criteria used by other authors for estimating the sensory quality of strawberries (Shamaila et al., 1992; Van der Steen et al., 2002). These limits for sensory quality could be used to estimate the sensory shelf life of strawberries. Some studies have estimated the sensory shelf life of minimally processed strawberries as the time necesarry to reach an arbitrary limit of a certain sensory attribute, as evaluated by a trained sensory panel. However, in order to assure the products’ quality at the end of their shelf life these limits should be based on consumer perceptions. The estimation of sensory quality based on data from a trained assessors’ panel could be a cost-effective and interesting alternative, particularly in small developing countries such as Uruguay. However it could be interesting to study correlations between sensory quality and physicochemical or instrumental measurements in order to make the estimation of sensory quality faster and easier. Further research is necessary to develop a quality index that correlates with consumer perception and is based on this type of technique. 5. Conclusions In the present work, the objective data obtained from a trained assessors’ panel was correlated to consumer perceptions of strawberries. By relating subjective consumer data to objective assessors’ data, a Sensory Quality Index was developed. The developed index could be used for estimating sensory quality of strawberries using a sensory panel which objectively evaluates sensory characteristics. Limits for this index would be useful in quality control and sensory shelf life studies to assure the quality of strawberries and minimize consumer rejection of the product. In this study, limits were defined using consumer acceptability and rejection to purchase because they are more objective criteria that take consumer
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perception into account, instead of relying on trained assessors to decide the relative importance of each of the sensory characteristics of strawberries. The methodology applied in the present work could be applied to other products in order to develop objective sensory quality indices based on consumer perception. Acknowledgements The authors are indebted to CSIC (Comisión Sectorial de Investigación Científica, Uruguay) and Comisión Administradora del Mercado Modelo (Intendencia Municipal de Montevideo) for financial support. References Ares, G., Giménez, A., Gámbaro, A., 2008. Shelf life estimation of minimally processed lettuce considering two stages of consumers’ decision making process. Appetite 50, 529–535. Cardello, A.V., 1995. Food quality: conceptual and sensory aspects. Food Qual. Pref. 6, 163–168. Cordenunsi, B.R., Nascimento, J.R.O., Lajolo, F.M., 2003. Physico-chemical changes related to quality of five strawberry fruit cultivars during cool-storage. Food Chem. 83, 167–183. Costell, E., 2002. A comparison of sensory methods in quality control. Food Qual. Pref. 13, 341–353. Gámbaro, A., Ares, G., Giménez, A., 2006. Shelf life estimation of apple baby food. J. Sens. Stud. 21 (1), 101–111. Giménez, A., Varela, P., Salvador, A., Ares, G., Fiszman, S., Garitta, L., 2007. Shelf life estimation of brown bread: a consumer approach. Food Qual. Pref. 18, 196–204. Giménez, A., Ares, G., Gámbaro, A., 2008. Consumers’ perception of sandiness in dulce de leche. J. Sens. Stud. 23 (2), 171–185. Harker, F.R., Elgar, H.J., Watkins, C.B., Jackson, P.J., Hallett, I.C., 2000. Physical and mechanical changes in strawberry fruit after high carbon dioxide treatments. Postharvest. Biol. Technol. 19, 139–146. Hough, G., Sánchez, R.H., Garbarini De Pablo, G., Sánchez, R.G., Calderón Villaplana, S., Giménez, A.M., Gámbaro, A., 2002. Consumer acceptability versus trained sensory panel scores of powdered milk shelf-life defects. J. Dairy Sci. 85, 1–6.
Hough, G., Garrita, L., Sánchez, R., 2004. Determination of consumer acceptance limits to sensory defects using survival analysis. Food Qual. Pref. 15, 729–734. IFT, 1990. Quality of fruits and vegetables. A scientific status summary of IFT expert panel on food safety and nutrition. Food Technol. 44, 99–106. ISO, 1988. Sensory Analysis: General Guidance for the Design of Test Rooms, ISO 8589. International Organization for Standardization, Geneva, Switzerland. ISO, 1993. ISO Standard 8586-1. Sensory Analysis—General Guidance for the Selection, Training, and Monitoring Of assessors. Part 1: Selected Assessors, 1st ed. International Organization for Standardization, Geneva, Switzerland. Jacxsens, L., Devlieghere, F., Debevere, J., 2002. Temperature dependence of shelflife as affected by microbial proliferation and sensory quality of equilibrium modified atmosphere packaged fresh produce. Postharvest. Biol. Technol. 26, 59–73. Jacxsens, L., Devlieghere, F., Ragaert, P., Vanneste, E., Debevere, J., 2003. Relation between microbiological quality, metabolite production and sensory quality of equilibrium modified atmosphere packaged fresh-cut produce. Int. J. Food Microbiol. 83, 263–280. King, A.D., Magnuson, J.A., Török, T., Goodman, N., 1991. Microbial flora and storage quality of partially processed lettuce. J. Food Sci. 56, 459–461. Molnar, P.J., 1995. A model for overall description of food quality. Food Qual. Pref. 6, 185–190. ˜ Munoz, A.M., Civille, V.G., Carr, B.T., 1992. Sensory Evaluation in Quality Control. Van Mostrand, Reinhold, USA. Pelayo, C., Ebeler, S.E., Kader, A.A., 2003. Postharvest life and flavor quality of three strawberry cultivars kept at 5 ◦ C in air or air +20 kPa CO2 . Postharvest. Biol. Technol. 27, 171–183. Péneau, S., Brockhoff, P.B., Escher, F., Nuessli, J., 2007. A comprehensive approach to evaluate the freshness of strawberries and carrots. Postharvest. Biol. Technol. 45, 20–29. Ragaert, P., Devlieghere, F., Loos, S., Dewulf, J., Van Langenhove, H., Foubert, I., Vanrolleghem, P.A., Debevere, J., 2006. Role of yeast proliferation in the quality degradation of strawberries during refrigerated storage. Int. J. Food Microbiol. 108, 42–50. Ragaert, P., Verbeke, W., Devlieghere, F., Debevere, J., 2004. Consumer perception and choice of minimally processed vegetables and packaged fruits. Food Qual. Pref. 15, 259–270. Shamaila, M., Powrie, W.D., Skura, B.J., 1992. Sensory evaluation of strawberry fruit stored under modified atmosphere packaging (MAP) by quantitative descriptive analysis. J. Food Sci. 57, 1168–1172. Van der Steen, C., Jacxsens, L., Devlieghere, F., Debevere, J., 2002. Combining high oxygen atmospheres with low oxygen modified atmosphere packaging to improve the keeping quality of strawberries and raspberries. Postharvest. Biol. Technol. 26, 49–58.