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Papaya nectar formulated with prebiotics: Chemical characterization and sensory acceptability
LWT - Food Science and Technology 62 (2015) 854e860
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Papaya nectar formulated with prebiotics: Chemical characterization and sensory acceptability berly Fernandes Braga a, Ana Carolina Conti-Silva b, * He ~o, Ci^ ^ngulo Mineiro, Ca ^mpus Ituiutaba, Rua Belarmino Vilela Junqueira, s./n., CEP 38305-200, Instituto Federal de Educaça encia e Tecnologia do Tria Ituiutaba, MG, Brazil b ~o va Departamento de Engenharia e Tecnologia de Alimentos, Instituto de Bioci^ encias, Letras e Ci^ encias Exatas, UNESP e Univ Estadual Paulista, Rua Cristo ~o Jos Colombo, 2265, CEP 15054-000, Sa e do Rio Preto, SP, Brazil a
a r t i c l e i n f o
a b s t r a c t
Article history: Received 8 September 2014 Received in revised form 17 December 2014 Accepted 30 December 2014 Available online 8 January 2015
Mixture modeling methodology was used to investigate interactions of sugar, oligofructose and inulin in papaya nectars as related to sensory liking and chemical characteristics. Mixing sugar and inulin and increasing the sugar proportion raised the liking of flavor and sweetness and the overall acceptability of papaya nectars. Addition of the three components, along with raising the sugar proportion, increased the ash and soluble solids content in papaya nectars. The internal preference mappings showed that all nectars with oligofructose and inulin were as well liked as nectar containing sugar alone, except for some formulations with lower quantities of sugar. Formulations with 6 g/100 g sugar and 6 g/100 g inulin, or with 8 g/100 g sugar, 2 g/100 g inulin and 2 g/100 g oligofructose, can be considered to be the best formulations to produce, with regard to sensory liking and adequacy of chemical parameters, besides all papaya nectars with addition of oligofructose and inulin can potentially be claimed as prebiotic. © 2015 Elsevier Ltd. All rights reserved.
Keywords: Oligofructose Inulin Hedonic scale Internal preference mapping
1. Introduction Prebiotics as functional foods have been widely researched because of the benefits that are promoted. These include stimulation of the proliferation or activity of desirable bacterial populations in the colon, such as bifidobacteria and lactobacilli (probiotics), with consequent fermentation that produces lactic acid, short chain fatty acids (acetic, propionic and butyric acids) and gases, thereby reducing the intestinal pH and inhibiting proliferation of harmful microorganisms (Wang, 2009). The main prebiotics currently available and used by the food industry worldwide belong to the group of carbohydrates, and specifically the category of fibers. Among these, isomaltooligosaccharides, trans-galacto-oligosaccharides, fructo, Ka polna, Ka polna, oligosaccharides and inulin can be cited (Siro & Lugasi, 2008). The latter two are the ones that have been most studied and are the ones still to be approved by the Brazilian National Agency for Sanitary Surveillance (ANVISA, 2013) with regard
* Corresponding author. Tel.: þ55 17 32212548; fax: þ55 17 32212299. E-mail addresses: [email protected] (H.F. Braga), [email protected] (A.C. Conti-Silva). http://dx.doi.org/10.1016/j.lwt.2014.12.064 0023-6438/© 2015 Elsevier Ltd. All rights reserved.
to claimed contributions towards balancing the intestinal microbiota. Prebiotics have been applied in different foods, and especially in dairy-based beverages (Champagne, Gardner, & Roy, 2005). However, consumption of these products coming up against the growing number of people with lactose intolerance, dyslipidemia and allergy to milk proteins, as well as cultural and behavioral issues such as vegetarianism (Granato, Masson, & Ribeiro, 2012; Heenan, Adams, Hosken, & Fleet, 2004). The development of prebiotic drinks from fruits and vegetables is an alternative that allows better choice for consumers (Renuka, Kulkarni, & Prapulla, 2009), and such plants contribute towards prevention of chronic diseases (Hauly, Fuchs, & Prudencio-Ferreira, 2005). Moreover, the application of prebiotic ingredients in beverages with a fruit base is advantageous, because fructans provide sweetness similar to sucrose, but with reduced calories (MacFarlene, Steed, & MacFarlene, 2008). Papaya (Carica papaya L.) is a source of biologically active substances such as carotenoids (Sentanin & Rodriguez Amaya, 2007) that stimulate the immune system and prevent the incidence of degenerative diseases (McGraw & Ardia, 2003). Its pulp has attractive sensory, chemical and digestive characteristics that make it an ideal food for preparation of different products such as nectars. However, papaya nectar is not widespread and commonly
H.F. Braga, A.C. Conti-Silva / LWT - Food Science and Technology 62 (2015) 854e860
marketed in Brazil, a tropical country with high potential for fruit processing, and, in this way, a papaya nectar with potential to be claimed as prebiotic is necessary and represents an innovative functional product. Few studies have been conducted on the acceptability of addition of prebiotics to juices and fruit nectars (Granato, Branco, Nazzaro, Cruz, & Faria, 2010; Luckow & Delahunty, 2004; Rebouças, Rodrigues, & Afonso, 2014). In addition, consumers are not interested in buying functional beverages if the added ingredients promote strange or unpleasant flavors in the products, even taking into consideration the health benefits (Tuorila & Cardello, 2002). Therefore, the new product development is a constant challenge, because there are several aspects to be considered, such as convenience, quality, economy, variety, and especially nutritional and sensory factors (Jousse, 2008). In this way, it is pertinent using experimental designs that optimize (maximized or minimized) a dependent variable of interest or, at least, that allow understanding how the independent variables influence in one or more response variables. The mixture modeling methodology is suitable for food products that require a composition or a blend of key ingredients, since proportions of the ingredients in the mixture, and their levels, are dependent on each other, and the sum of all components is always one or 100% (Hare, 1974). In these cases, the ingredients are the independent variables or factors and the dependent variable or response is the objective to be optimized or investigated (Castro, Silva, Tirapegui, Borsato, & Bona, 2003). Therefore, the present study aimed to evaluate the effects of sugar, oligofructose and inulin on the sensory acceptability and chemical characteristics of papaya nectars using mixture modeling methodology. 2. Materials and methods 2.1. Materials Frozen pasteurized whole papaya pulp was provided by a fruit rcio de Frutas processing company (De Marchi Indústria e Come Ltda., S~ ao Paulo, Brazil). The pulp composition was as follows: soluble solids 9.9 Brix; pH 4.3; acidity in citric acid 0.20 g/100 g; total sugar 18.1 g/100 g; and total solids 9.54 g/100 g (analyses performed at laboratory). The fructans Orafti®P95 and Orafti®GR were provided by BeneoOrafti, a Belgian company that extracts and produces oligofructose and inulin. Orafti®P95 is composed of 93.2 g/100 g of oligofructose and 6.8 g/100 g of glucose þ fructose þ sucrose. Orafti®GR is composed of 90 g/100 g of inulin (average degree of
Table 1 Simplex centroid design and sugar (X1), oligofructose (X2) and inulin (X3) levels in papaya nectar. Formulation
1 2 3 4 5 6 7 8 9 10 11 a
Component proportiona
g/100 g of each component
X1
X2
X3
Sugar
Oligofructose
Inulin
1 0 0 0.5 0.5 0 0.33 0.33 0.66 0.17 0.17
0 1 0 0.5 0 0.5 0.33 0.33 0.17 0.66 0.17
0 0 1 0 0.5 0.5 0.33 0.33 0.17 0.17 0.66
12 0 0 6 6 0 4 4 8 2 2
0 12 0 6 0 6 4 4 2 8 2
0 0 12 0 6 6 4 4 2 2 8
X1 þ X2 þ X3 ¼ 1.
855
polymerization > 10) and 10 g/100 g of glucose þ fructose þ sucrose. Drinking mineral water without gas and pH 5.1 at 25 C (Nativa, s, Brazil) and refined sugar crystal to culinary use (Caete , Minas Goia Gerais, Brazil) were purchased in a local market and the same brands were used for all formulations. 2.2. Experimental design Eleven formulations of papaya nectars were prepared using the mixture modeling methodology (Table 1). This methodology is applied to manipulate ingredients of different kinds of foods (Dutcosky, Grossmann, Silva, & Welsch, 2006; Ellouze-Ghorbel €ßle, Ktenioudaki, & Gallagher, 2011; Souza et al., et al., 2010; Ro 2012). A simplex centroid design for ternary mixtures was used, with one replication of the central point. The three components were sugar, oligofructose and inulin, and the mixture of the components was standardized at 12 g/100 g of nectar. The dependent variables of the experimental design were hedonic liking ratings for the sensory attributes appearance, aroma, viscosity, flavor and sweetness and overall liking and chemical parameters (soluble solids at 20 C, total sugars, acidity in citric acid, total solids, ash and pH). The means for the dependent variables were subjected to multiple regression analysis and only coefficients with p-values below 0.05 were considered for construction of the mathematical models. The regression was submitted to analysis of variance and it was considered significant when p 0.05 and no lack of fit at p > 0.05. Triangular diagrams were generated using contour curves for the adjusted models. Quadratic and special cubic models were tested to explain the influence of the components on the response variables, because the relationships between independent and dependent variables were unknown and, therefore, it was necessary to find adequate approximation to the true relationship between these variables (Montgomery & Runger, 2006). All the statistical analyses and construction of triangular diagrams were performed using StatSoft, Inc. (2004). 2.3. Nectar preparation The papaya pulp was thawed under refrigeration (7e10 C) for 12 h. Subsequently, a mixture was made, composed of 35 g of pulp per 100 g (minimum quantity of papaya pulp required, in accordance with Brasil, 2003), 53 g/100 g water and 12 g/100 g variable ‘sugar, oligofructose, inulin’ mix. The products were packaged in sterile glass bottles and kept refrigerated (7e10 C), until the time of analyses. No heat was applied to any of the formulations, and all procedures were performed while following good practices for strict handling. Around three liters of each formulation were prepared. 2.4. Sensory analysis Sensory analysis was performed at the Sensory Analysis Labo~o, Cie ^ncia e Tecnologia do ratory of the Instituto Federal de Educaça ^ngulo (“Federal Institute of Education, Science and Technology Tria of the Minas Gerais Triangle”), Ituiutaba campus, with 85 consumers (46% female and 54% male, aged 15e48 years and averaging 22 years), using individual booths with white light. This study was approved by the Research Ethics Committee of the Instituto de ^ncias, Letras e Cie ^ncias Exatas (“Institute of Biosciences, Biocie Literature and Exact Sciences”), Universidade Estadual Paulista ~o Jose do Rio Preto campus “Julio de Mesquita Filho” (UNESP), Sa (Opinion Report 123.364).
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A questionnaire was applied to gather consumer demographics, degree of liking of papaya and frequency of consumption of fruit nectars. The frequency of consumption of papaya nectar was not asked because of the absence of the product in the Brazilian market. The formulations were then evaluated on sensory 9-point hedonic scales ranging from “dislike extremely” to “like extremely” (Meilgaard, Civille, & Carr, 2007), in the following order: appearance, aroma, viscosity, flavor, sweetness and overall acceptability. The test was performed with 85 untrained consumers on three consecutive days and the samples were evaluated in a monadic and randomized manner, through a complete and balanced block (MacFie & Bratchell, 1989). The samples were presented in transparent plastic cups coded with three random digits, with 30 mL per sample and at a temperature from 7 to 10 C. Pearson's correlation was applied to the means of sensory acceptability to investigate the correlation between sensory attributes and overall acceptability. A correlation coefficient above 0.70 € nfeldt, & Kruger, indicates fairly strong correlation (Leighton, Scho 2010) and is considered to be significant when p 0.05. All statistical analyses were performed using StatSoft, Inc. (2004). Internal preference mappings for acceptability of flavor and sweetness and overall acceptability were constructed using multivariate analyses at StatSoft, Inc. (2004): cluster analysis and multidimensional scaling (MDS). For that, formulations of papaya nectars were fixed in columns (variables) and the individual scores in rows (cases), and the data for the central point was taken to be the mean of formulations 7 and 8. First, a joining cluster analysis taking Euclidean distances as the distance measurements and Ward's hierarchy as the amalgamation rule was applied to the individual data from each consumer, and the midpoint of the major increment was taken to separate the groups. The matrix resulting from cluster analysis was then subjected to multidimensional scaling analysis, that is a multivariate technique based on proximities between objects, subjects or stimuli that is used to produce a spatial representation of these items (Hair, Black, Babin, Anderson, & Tatham, 2006). Moreover, multidimensional scaling is often used to understand how people perceive and evaluate certain signals and information, and it is widely used in market research in order to shed light on the way consumers evaluate brands and to assess €rdle & Simar, 2012). the relationship between product attributes (Ha The resulting graph from multidimensional scaling was called the internal preference mapping. Multidimensional scaling can be evaluated by the stress value, and values below 0.05 indicate that use of this multivariate analysis is appropriate (Johnson & Wichern, 1992; Kruskal & Wish, 1978). 2.5. Chemical analyses The following parameters are required by Brazilian legislation to characterize a product as papaya nectar and, therefore, were analyzed (Brasil, 2003): soluble solids at 20 C ( Brix), total sugars (g/100 g) and acidity in citric acid (g/100 g). In addition, analyses were performed on total solids (g/100 g), ash (g/100 g) and pH. All analyses were performed in triplicate in accordance with AOAC (2012).
(cases), and the data were standardized before analysis. The PCA was performed with a correlation matrix and without factor rotation. Percentage variation greater than 70% explained by the two first principal components indicates strong correlation among variables and that PCA is an appropriate multivariate analysis to be applied to the data (Mardia, Kent, & Bibby, 1979). 3. Results and discussion 3.1. Sensory acceptability of papaya nectars Fifty-nine percent of the consumers mentioned that they consumed fruit nectar at least twice a week and 14% once a week; and 100% of the consumers indicated that they liked papaya: 33% were very fond of it, 58% like it moderately and 9% only a little. The ranges of sensory acceptability of the papaya nectars were: 7.0 to 8.0 for appearance, 5.9 to 7.0 for aroma, 5.7 to 7.1 for viscosity, 4.8 to 6.7 for flavor, 4.4 to 7.1 for sweetness and 5.0 to 6.8 for overall acceptability. Regarding to liking of appearance, aroma and viscosity, all the models did not show any lack of fit (p > 0.05), but were not significant (p > 0.05), thus indicating that the three components did not have any effect on these dependent variables. The liking of the flavor and sweetness and the overall acceptability were influenced by the three individual components and the interaction between sugar and inulin (Table 2). Since the components showed the same effects in relation to the three dependent variables and the models are very similar (Table 2), only one triangular diagram is shown, but the results and discussion are the same for the three variables. The triangular diagram showed that increasing the proportion of sugar increased the liking of flavor and sweetness and the overall acceptability of the papaya nectars, although in the same region of the response surface, the mixture of sugar and inulin resulted in high liking for the nectars (Fig. 1). On the other hand, the increment on proportions of inulin or oligofructose decreased the liking of all sensory variables. Inulin and oligofructose have different technological characteristics. Inulin is an amorphous white powder, with a neutral odor and tastes (Franck & De Leenheer, 2005), while oligofructose has functional qualities similar to those of sucrose or glucose syrup (Roberfroid, 2007) and may provide 30e50% of the sweetness of sugar (Kaur & Gupta, 2002). Thus, high concentrations of inulin or oligofructose may interfere negatively with the sensory liking of nectars, through either low or high sweetness, respectively. In another study, around of 37% of the consumers reported having noticed a change in the taste or the presence of a residual taste in the throat when peach nectar with inulin, at a concentration of 2 g/ 100 mL of nectar, was compared with another peach nectar without inulin (Pimentel, Prudencio, & Rodrigues, 2011). Nectar with caja (Spondians mombin L.) and cashew (Anacardium occidentale) enriched with inulin with a high degree of polymerization was less
Table 2 Models and goodness of fit for the dependent variables. Dependent variable Equationa
2.6. Principal component analysis The sensory and chemical data were subjected to principal component analysis (PCA), using StatSoft, Inc. (2004). The data for the central point were taken to be the mean of the three formulations and the acidity was not considered in the analysis because it did not show any variation among the formulations. The sensory and chemical means were fixed in columns (variables) and the different formulations of papaya nectars in rows
Flavor Sweetness Overall acceptability Ash (g/100 g) Soluble solids ( Brix) a
R2 (%)
p-value Lack of fit
YF ¼ 5.91S þ 4.94O þ 4.67I þ 4.98SI 70.5 0.038 YS ¼ 6.20S þ 4.39O þ 4.53I þ 5.52SI 80.7 0.014 YOA ¼ 5.95S þ 5.49O þ 4.87I þ 4.98SI 55.6 0.097
0.654 0.741 0.085
YA ¼ 11.48S þ 10.50O þ 10.30I þ 34.03SOI YA ¼ 11.63S þ 10.72O þ 10.50I þ 37.33SOI
83.3 0.024
0.677
68.6 0.079
0.967
S ¼ sugar, O ¼ oligofructose, I ¼ inulin.
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Internal preference mappings for appearance, aroma, viscosity and sweetness were not constructed because stress values of multidimensional scaling were higher than 0.05. 3.2. Chemical characterization of papaya nectars
Fig. 1. Triangular diagram for the acceptability of flavor of papaya nectar.
liked in terms of “overall impression” than nectars containing standard inulin or fructo-oligosaccharides (all nectars with 5 g of fructan per 100 g of nectar) (Da Silva et al., 2011). The effect of the three components and the interaction between sugar and inulin was similar for flavor, sweetness and overall acceptability. In fact, a high correlation could be seen between flavor and sweetness (r ¼ 0.98; p 0.05), between flavor and overall acceptability (r ¼ 0.93; p 0.05) and between sweetness and overall acceptability (r ¼ 0.88; p 0.05). Cluster analysis on flavor acceptability formed three groups: one group with formulations 1/9/4 (mean of 5.97), another group with formulations 2/5/7-8/10 (mean of 5.73) and a last group with formulations 3/6/11 (mean of 5.07) (Fig. 2A). Samples from the same group were evaluated in similar ways by the panelists. The proximity between the formulations in the same group could also be seen from the internal preference mapping (stress value equal to 0.018), although formulation 2 is distant from the other formulations of the group (Fig. 2B). The points dispersed in Fig. 2B represent each consumer, and higher numbers of consumers near a formulation indicate liking for this sample. The consumers were distributed in all the quadrants, but more concentrated around groups of formulations 1, 4 and 9 and formulations 2/5/7-8/10, which coincided with the means for the groups, which were higher than the mean of the other two group of formulations 3/6/11. Moreover, it could be seen that some consumers were dispersed in the vector space and many did not like any formulation. The dispersion of the consumers can be explained by the different scores given to the samples by the consumers, although these consumers gave similar scores for all the formulations and, therefore, they were not positioned near to any formulation and did not like any of them in particular. The cluster analysis on overall acceptability resulted in the same three groups of formulations, as well as acceptability to flavor: one group with formulations 1/9/4 (mean of 6.04), a second group with formulations 2/5/7-8/10 (mean of 6.08) and a last group with formulations 3/6/11 (mean of 5.13) (Fig. 2C). Low numbers of consumers are dispersed near the formulations 3, 6 and 11 (Fig. 2D; stress value equal to 0.021), and, in fact, this group of formulations showed low means in relation to the other groups. At the same time, the consumers are more concentrated around the formulations 1/4/9 and 2/5/7-8/10, indicating a higher liking for these formulations. Moreover, some consumers did not like any formulation, probably because they did not like any particular formulation. Therefore, the maps demonstrate that nectars with addition of fructans can be also liked as much as nectars with sugar alone.
The ranges of chemical characteristics of the papaya nectars were: 11.0e12.5 g/100 g for total solids, 10.2e11.7 g/100 g for ash, 4.0 to 5.1 for pH, 10.5 to 12.0 Brix for soluble solids and 17.4e20.6 g/100 g for total sugar. The acidity had values of 0.1 g/ 100 g for all formulations. All chemical parameters were in accordance with Brasil (2003) and all formulations could be commercialized as papaya nectar. The three individual components influenced and had interactions between each other, regarding the dependent variables of ash and soluble solids (Table 2). Since the same effects of components were observed for the two dependent variables and the models were very similar (Table 2), only one triangular diagram is shown, but the results and discussion are the same for the two variables. The addition of high proportions of inulin or oligofructose or both fructans decreased the ash and soluble solids in the papaya nectars (Fig. 3), and this feature may be related to the purity of the fructan added, which did not contain gluten, fat, protein or phytic acid, and only had negligible amounts of minerals and salts (Roberfroid, 2007; Stephen, 2006). Furthermore, addition of the three components enhanced the quantities of the same chemical variable, and the same response was observed when the sugar proportion was increased in the nectar formulation. The models for pH and total sugars did not show any lack of fit (p > 0.05), but were not significant (p > 0.05), in opposite of models for total solids, that were not significant and also showed lack of fit (p 0.05). The total fructan content in the formulations was not quantified, since these formulations were not subjected to heat treatment and also had pH values in the range 3.9e7.0, which is considered to be compatible with the stability range for fructo-oligosaccharides (Courtin, Swennen, Verjans, & Delcour, 2009; Huebner, Wehling, Parkhurst, & Hutkins, 2008). All the formulations, except the one without addition of fructans (formulation 1), may potentially be claimed to be prebiotic. Knowing that the lowest level of total fructans added (inulin þ oligofructose) was 4 g/100 g (formulation 10), a portion of 200 mL of this formulation of papaya nectar provided 8 g of total fructan. This formulation would have a bifidogenic effect, because a dose of 5 g/day of inulin or oligofructose, or a mixture between them, would be sufficient to beneficially alter the colonic microbiota (Gibson, 2007; Kolida, Meyer, & Gibson, 2007). In addition, all of the papaya nectars could be claimed to be prebiotic in terms of Brazilian legislation (ANVISA, 2013), which requires that liquid products of this nature must contain at least 1.5 g of fructans separately or in association. 3.3. Characterization of papaya nectars using principal component analysis Principal component analysis on the sensory acceptance and chemical parameters of the papaya nectars showed that the first and second principal components explained respectively 48.1 and 32.2% of the data variation, thus totaling 80.3% (Fig. 4). The first principal component, characterized as “sensory acceptability,” was explained by the liking of all the sensory attributes and the overall acceptability, all of which correlated positively (Fig. 4A). Low sensory liking was observed for the nectars: 12 g/100 g oligofructose; 12 g/100 g inulin; 6 g/100 g oligofructose and 6 g/100 g inulin; and 2 g/100 g sugar, 2 g/100 g oligofructose and 8 g/100 g inulin (formulations 2, 3, 6 and 11, respectively).
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Fig. 2. Dendograms resulting from cluster analysis (A, C) and internal preference mapping (B, D) for papaya nectars. Legend: 1 ¼ 12 g/100 g sugar; 2 ¼ 12 g/100 g oligofructose; 3 ¼ 12 g/100 g inulin; 4 ¼ 6 g/100 g sugar/6 g/100 g oligofructose; 5 ¼ 6 g/100 g sugar/6 g/100 g inulin; 6 ¼ 6 g/100 g oligofructose/6 g/100 g inulin; 7-8 ¼ 4 g/100 g sugar/4 g/100 g oligofructose/4 g/100 g inulin; 9 ¼ 8 g/100 g sugar/2 g/100 g oligofructose/2 g/100 g inulin; 10 ¼ 2 g/100 g sugar/8 g/100 g oligofructose/2 g/100 g inulin; 11 ¼ 2 g/100 g sugar/2 g/ 100 g oligofructose/8 g/100 g inulin. Numbers I to IV indicate the quadrants of the graphs.
These samples were represented in the opposite quadrant for sensory acceptability (Fig. 4B). This result reinforces the results obtained from internal preference maps (Fig. 2). The formulation with 6 g/100 g sugar and 6 g/100 g inulin (formulation 5) had high
Fig. 3. Triangular diagram for ash (g/100 g) in papaya nectars.
liking for all the sensory attributes, and for overall acceptability, since it was positioned further away from the zero point in the two principal components and on the same side of the vectors relating to sensory acceptability. The second main component, characterized as “chemical characteristics” was explained by the ash, soluble solids and total solids (Fig. 4A). It was observed that the formulations containing 12 g/ 100 g sugar, 4 g/100 g of each component and 8 g/100 g sugar, 2 g/ 100 g inulin and 2 g/100 g oligofructose (formulations 1, 7-8 and 9, respectively) were characterized by their ash, soluble solid and total solids content. This result coincided with the triangular diagrams for the chemical characteristics (Fig. 3), as the darkest band, and this corresponded to the highest values for ash and soluble solids, comprising the formulations described above. Combining the three statistical analyses used in this work, mixture modeling methodology, internal preference mapping and principal component analysis, is possible to reach conclusions about different samples and dependent variables. Papaya nectar with sugar alone (formulation 1), or with 6 g/100 g sugar and 6 g/ 100 g inulin (formulation 5) or even with 8 g/100 g sugar, 2 g/100 g inulin and 2 g/100 g oligofructose (formulation 9), are located in the region of high sensory liking in the triangular diagrams for flavor, sweetness and overall liking (Fig. 1). These formulations also can be
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and soluble solids in the papaya nectars. The internal preference mappings show that nectars with addition of oligofructose and inulin are as well liked regarding flavor and the overall acceptability as nectar containing sugar alone, although some nectars, when prepared with lower quantities of sugar, are liked less. Moreover, all the papaya nectars with addition of oligofructose and inulin can potentially be claimed to be prebiotic, since the minimum quantity of fructans used (4 g/100 g) exceeds the recommended daily amount per serving (1.5 g of inulin or oligofructose, or both, per 200 mL of nectar according to Brazilian legislation). Formulations with 6 g/100 g of sugar and 6 g/100 g of inulin, or with 8 g/100 g sugar, 2 g/100 g inulin and 2 g/100 g oligofructose, can be considered to be the best formulations to produce, regarding sensory liking and adequacy of chemical parameters. Acknowledgments rcio de The authors are grateful to De Marchi Indústria e Come Frutas Ltda. for supplying the frozen papaya pulp, and to BeneoOrafti for supplying the fructans. References
Fig. 4. Principal component analysis on sensory and chemical characteristics of the papaya nectars (A e projection of the variables, B e projection of the samples). Legend: S ¼ sugar, O ¼ oligofructose, I ¼ inulin; the percentages mean g/100 g.
considered as having high sensory liking according to dendograms (Fig. 2A/C) and internal preference mappings (Fig. 2B/D). Moreover, principal component analysis (Fig. 4) indicated that the formulation with 6 g/100 g sugar and 6 g/100 g inulin was highly liked with regard to all the sensory attributes, and for overall acceptability. Since all formulations are in accordance with Brazilian legislation regarding chemical parameters (item 3.2), formulations with 6 g/ 100 g sugar and 6 g/100 g inulin or with 8 g/100 g sugar, 2 g/100 g inulin and 2 g/100 g oligofructose can be considered to be the best formulations to produce.
4. Conclusions The interactions among sugar, oligofructose and inulin influence the sensory acceptability and chemical characteristics of the papaya nectars. Increasing the sugar proportion and mixing sugar and inulin raise the liking of flavor and sweetness and the overall acceptability of the papaya nectars. Addition of the three components, just like increasing the sugar proportion, increases the ash
~es de propriedades ANVISA. (August 23, 2013). Alimentos/Alimentos com alegaço ~es de propriedade funcional aprovadas. http:// funcionais e ou de saúde/Alegaço www.anvisa.gov.br. AOAC. (2012) (19th ed.). Official methods of analysis of AOAC international (19th ed.), (Vol. 2). Gaithersburg: AOAC International. ria e Abastecimento. Instruça ~o NorBrasil. (2003). Minist erio da Agricultura, Pecua ~es de mativa n.12, de 04 de setembro de 2003. Regulamento T ecnico para os padro , Caju, Goiaba, identidade e qualidade dos N ectares de Abacaxi, Acerola, Caja ~o, Manga, Maracuja , P^ rio Graviola, Mama essego e Pitanga. (Anexo III). Brasília: Dia ~o. Oficial da Unia Castro, I. A., Silva, R. S. F., Tirapegui, J., Borsato, D., & Bona, E. (2003). Simultaneous optimization of response variables in protein mixture formulation: constrained simplex method approach. International Journal of Food Science and Technology, 38, 103e110. Champagne, C. P., Gardner, N. J., & Roy, D. (2005). Challenges in the addition of probiotic cultures to foods. Critical Reviews in Food Science and Nutrition, 45, 61e84. Courtin, C. M., Swennen, K., Verjans, P., & Delcour, J. A. (2009). Heat and pH stability of prebiotic arabinoxylooligosaccharides, xylooligosaccharides and fructooligosaccharides. Food Chemistry, 112, 831e837. Da Silva, L. M. R., Lima, A. S., Maia, G. A., Rodrigues, M. C. P., De Figueiredo, R. W., & De Sousa, P. H. M. (2011). Lima development of mixed beverages made of caja (Spondias mombin L.) and cashew apple (Anacardium occidentale) added of n, 61, fructooligosaccharides and inulin. Archivos Latinoamericanos de Nutricio 209e215. Dutcosky, S. D., Grossmann, M. V. E., Silva, R. S. S. F., & Welsch, A. K. (2006). Combined sensory optimization of a prebiotic cereal product using multicomponent mixture experiments. Food Chemistry, 98, 630e638. Ellouze-Ghorbel, R., Kamoun, A., Neifar, M., Belguith, S., Ayadi, M. A., Kamoun, A., et al. (2010). Journal of Texture Studies, 41, 472e491. Franck, A., & De Leenheer, L. (2005). Inulin. In Biopolymers online (Vol. 6). Gibson, G. R. (2007). Functional foods: probiotics and prebiotics. Culture, 28, 1e3. Granato, D., Branco, G. F., Nazzaro, F., Cruz, A. G., & Faria, J. A. F. (2010). Functional foods and nondairy probiotic food development: trends, concepts, and products. Comprehensive Reviews in Food Science and Food Safety, 9, 292e302. Granato, D., Masson, M. L., & Ribeiro, J. C. B. (2012). Sensory acceptability and physical stability evaluation of a prebiotic soy-based dessert developed with passion fruit juice. Food Science and Technology, 32, 119e126. Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis. New Jersey: Prentice Hall. €rdle, W. K., & Simar, L. (2012). Applied multivariate statistical analysis (3rd ed.). Ha Heidelberg: Springer. Hare, L. B. (1974). Mixture designs applied to food formulations. Food Technology, 29, 50e62. Hauly, M. C. O., Fuchs, R. H. B., & Prudencio-Ferreira, S. H. (2005). Soymilk yogurt supplemented with fructooligosaccharides: probiotic properties and acceptance. Brazilian Journal of Nutrition, 18, 613e622. Heenan, C. N., Adams, M. C., Hosken, R. W., & Fleet, G. H. (2004). Survival and sensory acceptability of probiotic microorganisms in a nonfermented frozen vegetarian dessert. LWT e Food Science and Technology, 37, 461e466. Huebner, J., Wehling, R. L., Parkhurst, A., & Hutkins, R. W. (2008). Effect of processing conditions on the prebiotic activity of commercial prebiotics. International Dairy Journal, 18, 287e293. Johnson, R. A., & Wichern, D. W. (1992). Applied multivariate statistical analysis (3rd ed.). Englewood Cliffs: Prentice Hall.
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Jousse, F. (2008). Modeling to improve the efficiency of product and process development. Comprehensive Reviews in Food Science and Food Safety, 7, 175e181. Kaur, N., & Gupta, A. K. (2002). Applications of inulin and oligofructose in health and nutrition. Journal of Biosciences, 27, 703e714. Kolida, S., Meyer, D., & Gibson, G. R. (2007). A double-blind placebo e controlled study to establish the bifidogenic dose of inulin in healthy humans. European Journal of Clinical Nutrition, 61, 1189e1195. Kruskal, J. B., & Wish, M. (1978). Multidimensional scaling. Newbury Park: Sage. €nfeldt, H. C., & Kruger, R. (2010). Quantitative descriptive senLeighton, C. S., Scho sory analysis of five different cultivars of sweet potato to determine sensory and texture profiles. Journal of Sensory Studies, 25, 2e18. Luckow, T., & Delahunty, C. (2004). Which juice is ‘healthier’? A consumer study of probiotic non-dairy juice drinks. Food Quality and Preference, 15, 751e759. MacFarlene, G. T., Steed, H., & MacFarlene, S. (2008). Bacterial metabolism and health e related effects of galacto-oligosaccharides and other prebiotics. Journal of Applied Microbiology, 104, 305e344. MacFie, H. J., & Bratchell, N. (1989). Designs to balance the effect of order of presentation and first-order carry-over effects in hall tests. Journal of Sensory Studies, 4, 129e148. Mardia, K. V., Kent, J. T., & Bibby, J. M. (1979). Multivariate analysis. London: Academic Press. McGraw, K. J., & Ardia, D. R. (2003). Carotenoids, immunocompetence, and the information content of sexual colors: an experimental test. The American Naturalist, 162, 704e712. Meilgaard, M., Civille, G. V., & Carr, B. T. (2007). Sensory evaluation techniques (4th ed.). Boca Raton: CRC Press. Montgomery, D. C., & Runger, G. C. (2006). Applied statistics and probability to food engineers (4th ed.). New York: John Wiley & Sons. Pimentel, T. C., Prudencio, S. H., & Rodrigues, R. S. (2011). Potentially synbiotic peach nectar. Brazilian Journal of Food and Nutrition, 22, 455e464.
Rebouças, M. C., Rodrigues, M. C. P., & Afonso, M. R. A. (2014). Optimization of the acceptance of prebiotic beverage made from cashew nut kernels and passion fruit juice. Journal of Food Science, 79, S1393eS1398. Renuka, B., Kulkarni, P., & Prapulla, S. G. (2009). Fructooligosaccharide fortification of selected fruit juice beverages: effect on the quality characteristics. LWT e Food Science and Technology, 42, 1031e1033. Roberfroid, M. B. (2007). Inulin-type fructans: functional food ingredients. The Journal of Nutrition, 137, 2493Se2502S. €ßle, C., Ktenioudaki, A., & Gallagher, E. (2011). Inulin and oligofructose as fat and Ro sugar substitutes in quick breads (scones): a mixture design approach. European Food Research and Technology, 233, 167e181. Sentanin, M. A., & Rodriguez Amaya, D. B. (2007). Carotenoid levels in papaya and peach determined by high performance liquid chromatography. Food Science and Technology, 27, 13e19. , I., Ka polna, E., K Siro apolna, B., & Lugasi, A. (2008). Functional food. Product development, marketing and consumer acceptance e a review. Appetite, 51, 456e467. Souza, V. R., Pereira, P. A. P., Pinheiro, A. C. M., Nunes, C. A., Silva, T. L. T., Borges, S. V., et al. (2012). Multivariate approaches for optimization of the acceptance: optimization of a brazilian cerrado fruit jam using mixture design and parallel factor analysis. Journal of Sensory Studies, 27, 417e424. StatSoft, Inc.. (2004). STATISTICA (data analysis software system), version 7. www. statsoft.com. Stephen, A. (2006). Food polysaccharides and their applications (2th ed.). New York: Marcel Dekker. Tuorila, H., & Cardello, A. V. (2002). Consumer responses to an off-flavor in juice in the presence of specific health claims. Food Quality and Preference, 13, 561e569. Wang, Y. (2009). Prebiotics: present and future in food science and technology. Food Research International, 42, 8e12.
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Papaya nectar formulated with prebiotics: Chemical characterization and sensory acceptability berly Fernandes Braga a, Ana Carolina Conti-Silva b, * He ~o, Ci^ ^ngulo Mineiro, Ca ^mpus Ituiutaba, Rua Belarmino Vilela Junqueira, s./n., CEP 38305-200, Instituto Federal de Educaça encia e Tecnologia do Tria Ituiutaba, MG, Brazil b ~o va Departamento de Engenharia e Tecnologia de Alimentos, Instituto de Bioci^ encias, Letras e Ci^ encias Exatas, UNESP e Univ Estadual Paulista, Rua Cristo ~o Jos Colombo, 2265, CEP 15054-000, Sa e do Rio Preto, SP, Brazil a
a r t i c l e i n f o
a b s t r a c t
Article history: Received 8 September 2014 Received in revised form 17 December 2014 Accepted 30 December 2014 Available online 8 January 2015
Mixture modeling methodology was used to investigate interactions of sugar, oligofructose and inulin in papaya nectars as related to sensory liking and chemical characteristics. Mixing sugar and inulin and increasing the sugar proportion raised the liking of flavor and sweetness and the overall acceptability of papaya nectars. Addition of the three components, along with raising the sugar proportion, increased the ash and soluble solids content in papaya nectars. The internal preference mappings showed that all nectars with oligofructose and inulin were as well liked as nectar containing sugar alone, except for some formulations with lower quantities of sugar. Formulations with 6 g/100 g sugar and 6 g/100 g inulin, or with 8 g/100 g sugar, 2 g/100 g inulin and 2 g/100 g oligofructose, can be considered to be the best formulations to produce, with regard to sensory liking and adequacy of chemical parameters, besides all papaya nectars with addition of oligofructose and inulin can potentially be claimed as prebiotic. © 2015 Elsevier Ltd. All rights reserved.
Keywords: Oligofructose Inulin Hedonic scale Internal preference mapping
1. Introduction Prebiotics as functional foods have been widely researched because of the benefits that are promoted. These include stimulation of the proliferation or activity of desirable bacterial populations in the colon, such as bifidobacteria and lactobacilli (probiotics), with consequent fermentation that produces lactic acid, short chain fatty acids (acetic, propionic and butyric acids) and gases, thereby reducing the intestinal pH and inhibiting proliferation of harmful microorganisms (Wang, 2009). The main prebiotics currently available and used by the food industry worldwide belong to the group of carbohydrates, and specifically the category of fibers. Among these, isomaltooligosaccharides, trans-galacto-oligosaccharides, fructo, Ka polna, Ka polna, oligosaccharides and inulin can be cited (Siro & Lugasi, 2008). The latter two are the ones that have been most studied and are the ones still to be approved by the Brazilian National Agency for Sanitary Surveillance (ANVISA, 2013) with regard
* Corresponding author. Tel.: þ55 17 32212548; fax: þ55 17 32212299. E-mail addresses: [email protected] (H.F. Braga), [email protected] (A.C. Conti-Silva). http://dx.doi.org/10.1016/j.lwt.2014.12.064 0023-6438/© 2015 Elsevier Ltd. All rights reserved.
to claimed contributions towards balancing the intestinal microbiota. Prebiotics have been applied in different foods, and especially in dairy-based beverages (Champagne, Gardner, & Roy, 2005). However, consumption of these products coming up against the growing number of people with lactose intolerance, dyslipidemia and allergy to milk proteins, as well as cultural and behavioral issues such as vegetarianism (Granato, Masson, & Ribeiro, 2012; Heenan, Adams, Hosken, & Fleet, 2004). The development of prebiotic drinks from fruits and vegetables is an alternative that allows better choice for consumers (Renuka, Kulkarni, & Prapulla, 2009), and such plants contribute towards prevention of chronic diseases (Hauly, Fuchs, & Prudencio-Ferreira, 2005). Moreover, the application of prebiotic ingredients in beverages with a fruit base is advantageous, because fructans provide sweetness similar to sucrose, but with reduced calories (MacFarlene, Steed, & MacFarlene, 2008). Papaya (Carica papaya L.) is a source of biologically active substances such as carotenoids (Sentanin & Rodriguez Amaya, 2007) that stimulate the immune system and prevent the incidence of degenerative diseases (McGraw & Ardia, 2003). Its pulp has attractive sensory, chemical and digestive characteristics that make it an ideal food for preparation of different products such as nectars. However, papaya nectar is not widespread and commonly
H.F. Braga, A.C. Conti-Silva / LWT - Food Science and Technology 62 (2015) 854e860
marketed in Brazil, a tropical country with high potential for fruit processing, and, in this way, a papaya nectar with potential to be claimed as prebiotic is necessary and represents an innovative functional product. Few studies have been conducted on the acceptability of addition of prebiotics to juices and fruit nectars (Granato, Branco, Nazzaro, Cruz, & Faria, 2010; Luckow & Delahunty, 2004; Rebouças, Rodrigues, & Afonso, 2014). In addition, consumers are not interested in buying functional beverages if the added ingredients promote strange or unpleasant flavors in the products, even taking into consideration the health benefits (Tuorila & Cardello, 2002). Therefore, the new product development is a constant challenge, because there are several aspects to be considered, such as convenience, quality, economy, variety, and especially nutritional and sensory factors (Jousse, 2008). In this way, it is pertinent using experimental designs that optimize (maximized or minimized) a dependent variable of interest or, at least, that allow understanding how the independent variables influence in one or more response variables. The mixture modeling methodology is suitable for food products that require a composition or a blend of key ingredients, since proportions of the ingredients in the mixture, and their levels, are dependent on each other, and the sum of all components is always one or 100% (Hare, 1974). In these cases, the ingredients are the independent variables or factors and the dependent variable or response is the objective to be optimized or investigated (Castro, Silva, Tirapegui, Borsato, & Bona, 2003). Therefore, the present study aimed to evaluate the effects of sugar, oligofructose and inulin on the sensory acceptability and chemical characteristics of papaya nectars using mixture modeling methodology. 2. Materials and methods 2.1. Materials Frozen pasteurized whole papaya pulp was provided by a fruit rcio de Frutas processing company (De Marchi Indústria e Come Ltda., S~ ao Paulo, Brazil). The pulp composition was as follows: soluble solids 9.9 Brix; pH 4.3; acidity in citric acid 0.20 g/100 g; total sugar 18.1 g/100 g; and total solids 9.54 g/100 g (analyses performed at laboratory). The fructans Orafti®P95 and Orafti®GR were provided by BeneoOrafti, a Belgian company that extracts and produces oligofructose and inulin. Orafti®P95 is composed of 93.2 g/100 g of oligofructose and 6.8 g/100 g of glucose þ fructose þ sucrose. Orafti®GR is composed of 90 g/100 g of inulin (average degree of
Table 1 Simplex centroid design and sugar (X1), oligofructose (X2) and inulin (X3) levels in papaya nectar. Formulation
1 2 3 4 5 6 7 8 9 10 11 a
Component proportiona
g/100 g of each component
X1
X2
X3
Sugar
Oligofructose
Inulin
1 0 0 0.5 0.5 0 0.33 0.33 0.66 0.17 0.17
0 1 0 0.5 0 0.5 0.33 0.33 0.17 0.66 0.17
0 0 1 0 0.5 0.5 0.33 0.33 0.17 0.17 0.66
12 0 0 6 6 0 4 4 8 2 2
0 12 0 6 0 6 4 4 2 8 2
0 0 12 0 6 6 4 4 2 2 8
X1 þ X2 þ X3 ¼ 1.
855
polymerization > 10) and 10 g/100 g of glucose þ fructose þ sucrose. Drinking mineral water without gas and pH 5.1 at 25 C (Nativa, s, Brazil) and refined sugar crystal to culinary use (Caete , Minas Goia Gerais, Brazil) were purchased in a local market and the same brands were used for all formulations. 2.2. Experimental design Eleven formulations of papaya nectars were prepared using the mixture modeling methodology (Table 1). This methodology is applied to manipulate ingredients of different kinds of foods (Dutcosky, Grossmann, Silva, & Welsch, 2006; Ellouze-Ghorbel €ßle, Ktenioudaki, & Gallagher, 2011; Souza et al., et al., 2010; Ro 2012). A simplex centroid design for ternary mixtures was used, with one replication of the central point. The three components were sugar, oligofructose and inulin, and the mixture of the components was standardized at 12 g/100 g of nectar. The dependent variables of the experimental design were hedonic liking ratings for the sensory attributes appearance, aroma, viscosity, flavor and sweetness and overall liking and chemical parameters (soluble solids at 20 C, total sugars, acidity in citric acid, total solids, ash and pH). The means for the dependent variables were subjected to multiple regression analysis and only coefficients with p-values below 0.05 were considered for construction of the mathematical models. The regression was submitted to analysis of variance and it was considered significant when p 0.05 and no lack of fit at p > 0.05. Triangular diagrams were generated using contour curves for the adjusted models. Quadratic and special cubic models were tested to explain the influence of the components on the response variables, because the relationships between independent and dependent variables were unknown and, therefore, it was necessary to find adequate approximation to the true relationship between these variables (Montgomery & Runger, 2006). All the statistical analyses and construction of triangular diagrams were performed using StatSoft, Inc. (2004). 2.3. Nectar preparation The papaya pulp was thawed under refrigeration (7e10 C) for 12 h. Subsequently, a mixture was made, composed of 35 g of pulp per 100 g (minimum quantity of papaya pulp required, in accordance with Brasil, 2003), 53 g/100 g water and 12 g/100 g variable ‘sugar, oligofructose, inulin’ mix. The products were packaged in sterile glass bottles and kept refrigerated (7e10 C), until the time of analyses. No heat was applied to any of the formulations, and all procedures were performed while following good practices for strict handling. Around three liters of each formulation were prepared. 2.4. Sensory analysis Sensory analysis was performed at the Sensory Analysis Labo~o, Cie ^ncia e Tecnologia do ratory of the Instituto Federal de Educaça ^ngulo (“Federal Institute of Education, Science and Technology Tria of the Minas Gerais Triangle”), Ituiutaba campus, with 85 consumers (46% female and 54% male, aged 15e48 years and averaging 22 years), using individual booths with white light. This study was approved by the Research Ethics Committee of the Instituto de ^ncias, Letras e Cie ^ncias Exatas (“Institute of Biosciences, Biocie Literature and Exact Sciences”), Universidade Estadual Paulista ~o Jose do Rio Preto campus “Julio de Mesquita Filho” (UNESP), Sa (Opinion Report 123.364).
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H.F. Braga, A.C. Conti-Silva / LWT - Food Science and Technology 62 (2015) 854e860
A questionnaire was applied to gather consumer demographics, degree of liking of papaya and frequency of consumption of fruit nectars. The frequency of consumption of papaya nectar was not asked because of the absence of the product in the Brazilian market. The formulations were then evaluated on sensory 9-point hedonic scales ranging from “dislike extremely” to “like extremely” (Meilgaard, Civille, & Carr, 2007), in the following order: appearance, aroma, viscosity, flavor, sweetness and overall acceptability. The test was performed with 85 untrained consumers on three consecutive days and the samples were evaluated in a monadic and randomized manner, through a complete and balanced block (MacFie & Bratchell, 1989). The samples were presented in transparent plastic cups coded with three random digits, with 30 mL per sample and at a temperature from 7 to 10 C. Pearson's correlation was applied to the means of sensory acceptability to investigate the correlation between sensory attributes and overall acceptability. A correlation coefficient above 0.70 € nfeldt, & Kruger, indicates fairly strong correlation (Leighton, Scho 2010) and is considered to be significant when p 0.05. All statistical analyses were performed using StatSoft, Inc. (2004). Internal preference mappings for acceptability of flavor and sweetness and overall acceptability were constructed using multivariate analyses at StatSoft, Inc. (2004): cluster analysis and multidimensional scaling (MDS). For that, formulations of papaya nectars were fixed in columns (variables) and the individual scores in rows (cases), and the data for the central point was taken to be the mean of formulations 7 and 8. First, a joining cluster analysis taking Euclidean distances as the distance measurements and Ward's hierarchy as the amalgamation rule was applied to the individual data from each consumer, and the midpoint of the major increment was taken to separate the groups. The matrix resulting from cluster analysis was then subjected to multidimensional scaling analysis, that is a multivariate technique based on proximities between objects, subjects or stimuli that is used to produce a spatial representation of these items (Hair, Black, Babin, Anderson, & Tatham, 2006). Moreover, multidimensional scaling is often used to understand how people perceive and evaluate certain signals and information, and it is widely used in market research in order to shed light on the way consumers evaluate brands and to assess €rdle & Simar, 2012). the relationship between product attributes (Ha The resulting graph from multidimensional scaling was called the internal preference mapping. Multidimensional scaling can be evaluated by the stress value, and values below 0.05 indicate that use of this multivariate analysis is appropriate (Johnson & Wichern, 1992; Kruskal & Wish, 1978). 2.5. Chemical analyses The following parameters are required by Brazilian legislation to characterize a product as papaya nectar and, therefore, were analyzed (Brasil, 2003): soluble solids at 20 C ( Brix), total sugars (g/100 g) and acidity in citric acid (g/100 g). In addition, analyses were performed on total solids (g/100 g), ash (g/100 g) and pH. All analyses were performed in triplicate in accordance with AOAC (2012).
(cases), and the data were standardized before analysis. The PCA was performed with a correlation matrix and without factor rotation. Percentage variation greater than 70% explained by the two first principal components indicates strong correlation among variables and that PCA is an appropriate multivariate analysis to be applied to the data (Mardia, Kent, & Bibby, 1979). 3. Results and discussion 3.1. Sensory acceptability of papaya nectars Fifty-nine percent of the consumers mentioned that they consumed fruit nectar at least twice a week and 14% once a week; and 100% of the consumers indicated that they liked papaya: 33% were very fond of it, 58% like it moderately and 9% only a little. The ranges of sensory acceptability of the papaya nectars were: 7.0 to 8.0 for appearance, 5.9 to 7.0 for aroma, 5.7 to 7.1 for viscosity, 4.8 to 6.7 for flavor, 4.4 to 7.1 for sweetness and 5.0 to 6.8 for overall acceptability. Regarding to liking of appearance, aroma and viscosity, all the models did not show any lack of fit (p > 0.05), but were not significant (p > 0.05), thus indicating that the three components did not have any effect on these dependent variables. The liking of the flavor and sweetness and the overall acceptability were influenced by the three individual components and the interaction between sugar and inulin (Table 2). Since the components showed the same effects in relation to the three dependent variables and the models are very similar (Table 2), only one triangular diagram is shown, but the results and discussion are the same for the three variables. The triangular diagram showed that increasing the proportion of sugar increased the liking of flavor and sweetness and the overall acceptability of the papaya nectars, although in the same region of the response surface, the mixture of sugar and inulin resulted in high liking for the nectars (Fig. 1). On the other hand, the increment on proportions of inulin or oligofructose decreased the liking of all sensory variables. Inulin and oligofructose have different technological characteristics. Inulin is an amorphous white powder, with a neutral odor and tastes (Franck & De Leenheer, 2005), while oligofructose has functional qualities similar to those of sucrose or glucose syrup (Roberfroid, 2007) and may provide 30e50% of the sweetness of sugar (Kaur & Gupta, 2002). Thus, high concentrations of inulin or oligofructose may interfere negatively with the sensory liking of nectars, through either low or high sweetness, respectively. In another study, around of 37% of the consumers reported having noticed a change in the taste or the presence of a residual taste in the throat when peach nectar with inulin, at a concentration of 2 g/ 100 mL of nectar, was compared with another peach nectar without inulin (Pimentel, Prudencio, & Rodrigues, 2011). Nectar with caja (Spondians mombin L.) and cashew (Anacardium occidentale) enriched with inulin with a high degree of polymerization was less
Table 2 Models and goodness of fit for the dependent variables. Dependent variable Equationa
2.6. Principal component analysis The sensory and chemical data were subjected to principal component analysis (PCA), using StatSoft, Inc. (2004). The data for the central point were taken to be the mean of the three formulations and the acidity was not considered in the analysis because it did not show any variation among the formulations. The sensory and chemical means were fixed in columns (variables) and the different formulations of papaya nectars in rows
Flavor Sweetness Overall acceptability Ash (g/100 g) Soluble solids ( Brix) a
R2 (%)
p-value Lack of fit
YF ¼ 5.91S þ 4.94O þ 4.67I þ 4.98SI 70.5 0.038 YS ¼ 6.20S þ 4.39O þ 4.53I þ 5.52SI 80.7 0.014 YOA ¼ 5.95S þ 5.49O þ 4.87I þ 4.98SI 55.6 0.097
0.654 0.741 0.085
YA ¼ 11.48S þ 10.50O þ 10.30I þ 34.03SOI YA ¼ 11.63S þ 10.72O þ 10.50I þ 37.33SOI
83.3 0.024
0.677
68.6 0.079
0.967
S ¼ sugar, O ¼ oligofructose, I ¼ inulin.
H.F. Braga, A.C. Conti-Silva / LWT - Food Science and Technology 62 (2015) 854e860
857
Internal preference mappings for appearance, aroma, viscosity and sweetness were not constructed because stress values of multidimensional scaling were higher than 0.05. 3.2. Chemical characterization of papaya nectars
Fig. 1. Triangular diagram for the acceptability of flavor of papaya nectar.
liked in terms of “overall impression” than nectars containing standard inulin or fructo-oligosaccharides (all nectars with 5 g of fructan per 100 g of nectar) (Da Silva et al., 2011). The effect of the three components and the interaction between sugar and inulin was similar for flavor, sweetness and overall acceptability. In fact, a high correlation could be seen between flavor and sweetness (r ¼ 0.98; p 0.05), between flavor and overall acceptability (r ¼ 0.93; p 0.05) and between sweetness and overall acceptability (r ¼ 0.88; p 0.05). Cluster analysis on flavor acceptability formed three groups: one group with formulations 1/9/4 (mean of 5.97), another group with formulations 2/5/7-8/10 (mean of 5.73) and a last group with formulations 3/6/11 (mean of 5.07) (Fig. 2A). Samples from the same group were evaluated in similar ways by the panelists. The proximity between the formulations in the same group could also be seen from the internal preference mapping (stress value equal to 0.018), although formulation 2 is distant from the other formulations of the group (Fig. 2B). The points dispersed in Fig. 2B represent each consumer, and higher numbers of consumers near a formulation indicate liking for this sample. The consumers were distributed in all the quadrants, but more concentrated around groups of formulations 1, 4 and 9 and formulations 2/5/7-8/10, which coincided with the means for the groups, which were higher than the mean of the other two group of formulations 3/6/11. Moreover, it could be seen that some consumers were dispersed in the vector space and many did not like any formulation. The dispersion of the consumers can be explained by the different scores given to the samples by the consumers, although these consumers gave similar scores for all the formulations and, therefore, they were not positioned near to any formulation and did not like any of them in particular. The cluster analysis on overall acceptability resulted in the same three groups of formulations, as well as acceptability to flavor: one group with formulations 1/9/4 (mean of 6.04), a second group with formulations 2/5/7-8/10 (mean of 6.08) and a last group with formulations 3/6/11 (mean of 5.13) (Fig. 2C). Low numbers of consumers are dispersed near the formulations 3, 6 and 11 (Fig. 2D; stress value equal to 0.021), and, in fact, this group of formulations showed low means in relation to the other groups. At the same time, the consumers are more concentrated around the formulations 1/4/9 and 2/5/7-8/10, indicating a higher liking for these formulations. Moreover, some consumers did not like any formulation, probably because they did not like any particular formulation. Therefore, the maps demonstrate that nectars with addition of fructans can be also liked as much as nectars with sugar alone.
The ranges of chemical characteristics of the papaya nectars were: 11.0e12.5 g/100 g for total solids, 10.2e11.7 g/100 g for ash, 4.0 to 5.1 for pH, 10.5 to 12.0 Brix for soluble solids and 17.4e20.6 g/100 g for total sugar. The acidity had values of 0.1 g/ 100 g for all formulations. All chemical parameters were in accordance with Brasil (2003) and all formulations could be commercialized as papaya nectar. The three individual components influenced and had interactions between each other, regarding the dependent variables of ash and soluble solids (Table 2). Since the same effects of components were observed for the two dependent variables and the models were very similar (Table 2), only one triangular diagram is shown, but the results and discussion are the same for the two variables. The addition of high proportions of inulin or oligofructose or both fructans decreased the ash and soluble solids in the papaya nectars (Fig. 3), and this feature may be related to the purity of the fructan added, which did not contain gluten, fat, protein or phytic acid, and only had negligible amounts of minerals and salts (Roberfroid, 2007; Stephen, 2006). Furthermore, addition of the three components enhanced the quantities of the same chemical variable, and the same response was observed when the sugar proportion was increased in the nectar formulation. The models for pH and total sugars did not show any lack of fit (p > 0.05), but were not significant (p > 0.05), in opposite of models for total solids, that were not significant and also showed lack of fit (p 0.05). The total fructan content in the formulations was not quantified, since these formulations were not subjected to heat treatment and also had pH values in the range 3.9e7.0, which is considered to be compatible with the stability range for fructo-oligosaccharides (Courtin, Swennen, Verjans, & Delcour, 2009; Huebner, Wehling, Parkhurst, & Hutkins, 2008). All the formulations, except the one without addition of fructans (formulation 1), may potentially be claimed to be prebiotic. Knowing that the lowest level of total fructans added (inulin þ oligofructose) was 4 g/100 g (formulation 10), a portion of 200 mL of this formulation of papaya nectar provided 8 g of total fructan. This formulation would have a bifidogenic effect, because a dose of 5 g/day of inulin or oligofructose, or a mixture between them, would be sufficient to beneficially alter the colonic microbiota (Gibson, 2007; Kolida, Meyer, & Gibson, 2007). In addition, all of the papaya nectars could be claimed to be prebiotic in terms of Brazilian legislation (ANVISA, 2013), which requires that liquid products of this nature must contain at least 1.5 g of fructans separately or in association. 3.3. Characterization of papaya nectars using principal component analysis Principal component analysis on the sensory acceptance and chemical parameters of the papaya nectars showed that the first and second principal components explained respectively 48.1 and 32.2% of the data variation, thus totaling 80.3% (Fig. 4). The first principal component, characterized as “sensory acceptability,” was explained by the liking of all the sensory attributes and the overall acceptability, all of which correlated positively (Fig. 4A). Low sensory liking was observed for the nectars: 12 g/100 g oligofructose; 12 g/100 g inulin; 6 g/100 g oligofructose and 6 g/100 g inulin; and 2 g/100 g sugar, 2 g/100 g oligofructose and 8 g/100 g inulin (formulations 2, 3, 6 and 11, respectively).
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Fig. 2. Dendograms resulting from cluster analysis (A, C) and internal preference mapping (B, D) for papaya nectars. Legend: 1 ¼ 12 g/100 g sugar; 2 ¼ 12 g/100 g oligofructose; 3 ¼ 12 g/100 g inulin; 4 ¼ 6 g/100 g sugar/6 g/100 g oligofructose; 5 ¼ 6 g/100 g sugar/6 g/100 g inulin; 6 ¼ 6 g/100 g oligofructose/6 g/100 g inulin; 7-8 ¼ 4 g/100 g sugar/4 g/100 g oligofructose/4 g/100 g inulin; 9 ¼ 8 g/100 g sugar/2 g/100 g oligofructose/2 g/100 g inulin; 10 ¼ 2 g/100 g sugar/8 g/100 g oligofructose/2 g/100 g inulin; 11 ¼ 2 g/100 g sugar/2 g/ 100 g oligofructose/8 g/100 g inulin. Numbers I to IV indicate the quadrants of the graphs.
These samples were represented in the opposite quadrant for sensory acceptability (Fig. 4B). This result reinforces the results obtained from internal preference maps (Fig. 2). The formulation with 6 g/100 g sugar and 6 g/100 g inulin (formulation 5) had high
Fig. 3. Triangular diagram for ash (g/100 g) in papaya nectars.
liking for all the sensory attributes, and for overall acceptability, since it was positioned further away from the zero point in the two principal components and on the same side of the vectors relating to sensory acceptability. The second main component, characterized as “chemical characteristics” was explained by the ash, soluble solids and total solids (Fig. 4A). It was observed that the formulations containing 12 g/ 100 g sugar, 4 g/100 g of each component and 8 g/100 g sugar, 2 g/ 100 g inulin and 2 g/100 g oligofructose (formulations 1, 7-8 and 9, respectively) were characterized by their ash, soluble solid and total solids content. This result coincided with the triangular diagrams for the chemical characteristics (Fig. 3), as the darkest band, and this corresponded to the highest values for ash and soluble solids, comprising the formulations described above. Combining the three statistical analyses used in this work, mixture modeling methodology, internal preference mapping and principal component analysis, is possible to reach conclusions about different samples and dependent variables. Papaya nectar with sugar alone (formulation 1), or with 6 g/100 g sugar and 6 g/ 100 g inulin (formulation 5) or even with 8 g/100 g sugar, 2 g/100 g inulin and 2 g/100 g oligofructose (formulation 9), are located in the region of high sensory liking in the triangular diagrams for flavor, sweetness and overall liking (Fig. 1). These formulations also can be
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and soluble solids in the papaya nectars. The internal preference mappings show that nectars with addition of oligofructose and inulin are as well liked regarding flavor and the overall acceptability as nectar containing sugar alone, although some nectars, when prepared with lower quantities of sugar, are liked less. Moreover, all the papaya nectars with addition of oligofructose and inulin can potentially be claimed to be prebiotic, since the minimum quantity of fructans used (4 g/100 g) exceeds the recommended daily amount per serving (1.5 g of inulin or oligofructose, or both, per 200 mL of nectar according to Brazilian legislation). Formulations with 6 g/100 g of sugar and 6 g/100 g of inulin, or with 8 g/100 g sugar, 2 g/100 g inulin and 2 g/100 g oligofructose, can be considered to be the best formulations to produce, regarding sensory liking and adequacy of chemical parameters. Acknowledgments rcio de The authors are grateful to De Marchi Indústria e Come Frutas Ltda. for supplying the frozen papaya pulp, and to BeneoOrafti for supplying the fructans. References
Fig. 4. Principal component analysis on sensory and chemical characteristics of the papaya nectars (A e projection of the variables, B e projection of the samples). Legend: S ¼ sugar, O ¼ oligofructose, I ¼ inulin; the percentages mean g/100 g.
considered as having high sensory liking according to dendograms (Fig. 2A/C) and internal preference mappings (Fig. 2B/D). Moreover, principal component analysis (Fig. 4) indicated that the formulation with 6 g/100 g sugar and 6 g/100 g inulin was highly liked with regard to all the sensory attributes, and for overall acceptability. Since all formulations are in accordance with Brazilian legislation regarding chemical parameters (item 3.2), formulations with 6 g/ 100 g sugar and 6 g/100 g inulin or with 8 g/100 g sugar, 2 g/100 g inulin and 2 g/100 g oligofructose can be considered to be the best formulations to produce.
4. Conclusions The interactions among sugar, oligofructose and inulin influence the sensory acceptability and chemical characteristics of the papaya nectars. Increasing the sugar proportion and mixing sugar and inulin raise the liking of flavor and sweetness and the overall acceptability of the papaya nectars. Addition of the three components, just like increasing the sugar proportion, increases the ash
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