Sensory Acceptance of a Functional
Beverage Based on Orange Juice and
Soymilk
Estudo da Aceitação Sensorial de uma
Bebida à Base de Suco de Laranja e
Extrato Aquoso de Soja
AUTORES
AUTHORS
Maria Filomena VALIM
Elizeu A. ROSSI
Food and Nutrition Department,
Faculty of Pharmaceutical Sciences São Paulo State University, UNESP,
Rodovia Araraquara-Jaú, km 1,
Araraquara, SP, Brazil, 14801-902
Rui S. F. SILVA
Dionisio BORSATO
The State University of Londrina, UEL,
Londrina, PR, Brazil
SUMMARY
Consumer awareness concerning juice beverages has increased the number of
positive attributes desired for these products, apart from refreshment. However, no matter
how nutritious the beverage, the taste must be acceptable or it will not be consumed. The
objective of this study was to develop a beverage based on orange juice that aggregated
the sensory and nutritional properties of orange juice with the higher protein content of
soya, in addition to the bioactive components of both raw materials. A two factor central
composite design was employed to optimize the beverage in order to obtain a product with
adequate sensory properties, especially, overall acceptability. The independent variables were
the citric acid and protein concentrations at 5 different levels. All formulations were submitted
to 20 consumer assessors using a 9-point structured hedonic scale. The highest score for
overall acceptability (7.2) was achieved with a beverage containing 0.71g/100 mL citric acid
(19% of frozen concentrated orange juice) and a protein concentration of 1.22g/100 mL
(46% of soymilk).
RESUMO
PALAVRAS-CHAVE
KEY WORDS
A maior conscientização dos consumidores sobre os efeitos benéficos da inclusão
de sucos de frutas na dieta aumentou sua exigência em relação ao número de atributos
desejáveis no produto, principalmente sob o aspecto nutricional. Entretanto, para que uma
bebida seja consumida, ela deverá apresentar propriedades organolépticas adequadas. O
objetivo deste trabalho foi desenvolver uma bebida à base de extrato aquoso de soja e suco
de laranja no sentido de obter um alimento que agregue às propriedades nutritivas e
biocêuticas da soja, as propriedades sensoriais e nutritivas do suco de laranja. Foi utilizado
um delineamento fatorial completo de 2 fatores de modo a obter-se um produto com
propriedades sensoriais adequadas, principalmente aceitabilidade. A escolha deste
delineamento visou a análise pela metodologia de superfície de resposta. As variáveis
independentes selecionadas foram concentração de ácido cítrico e de proteína em 5 níveis
de variação. Todas as formulações foram submetidas a 20 provadores que utilizaram para a
avaliação das amostras uma escala estruturada de 9 pontos. A formulação que apresentou
o maior valor para aceitabilidade (7,2) foi preparada com concentrações de 0,71g/100mL de
ácido cítrico (19% de suco de laranja concentrado) e de 1,22g/100mL de proteína (46% de
extrato aquoso de soja).
Orange juice; Soymilk; Functional beverage; Response
surface methodology; Sensory acceptance
Suco de laranja; Extrato aquoso de soja; Bebida funcional;
Metodologia de Superfície de resposta; Aceitação sensorial
Braz. J. Food Technol., v.6, n.2, p. 153-156, jul./dez., 2003
153
Recebido / Received: 02/05/2002. Aprovado / Approved: 30/12/2002.
VALIM, M.F. et al.
1. INTRODUCTION
At the beginning of the new century, the global juice
industry faces new challenges driven by changing consumer
tastes and uses for commercial beverages. Consumers will
become more concerned with their health as scientific
information relates diet with health and wellness. For fruit and
vegetable juices this health and wellness trend leads to a
significant competitive advantage over other commercial
beverages (TILLOTSON, 2000).
The consumption of fruit juices in general, and of
orange juice in particular, has been related to dietar y
recommendations for healthy eating. The beneficial health
effects of orange juice are due, in part, to its vitamin C content,
this being a natural antioxidant which may inhibit the
development of heart disease and certain cancers. Orange juice
is also a relatively good source of folic acid, which plays an
important metabolic role as a coenzyme in amino-acid
metabolism and nucleic-acid synthesis (ROUSEFF; NAGY, 1994).
JOSHIPURA et al. (1999) examined the associations between
fruit and vegetable intake and ischemic strokes and their data
supported a protective relationship between the consumption
of citrus fruit and juice and ischemic stroke risk.
Soymilk presents a low production cost and is best
known for its protein content. Soy foods are being recognized
for their potential roles in the prevention and treatment of
heart disease and certain cancers due to the presence of
isoflavones. Potential roles with respect to osteoporosis and
kidney disease are also being investigated (MESSINA, 1995).
In the present study the objective was to study the
overall acceptability of a beverage based on orange juice, which
aggregated the sensory and nutritional properties of orange
juice with the higher protein content of soymilk together with
the bioactive components of both raw materials. Response
surface methodology (RSM) was used to model the sensory
acceptability response of consumers, to generate a predictive
equation with the variables studied: concentration of protein
and of citric acid. The predictive equation was used to estimate
the expected consumer response according to a given beverage
formula.
2.2 Methods
Experimental Design. The beverages were prepared by
mixing the soymilk with the concentrated orange juice and
adding enough water to complete the final volume (1 liter)
according to a random central composite rotatable design,
consisting of a 22 factorial design with two levels (–1, +1),
four central points (0) and four axial points (±α, 0); (0, ±α),
resulting in 12 treatments (BOX; DRAPER, 1987). The
independent variables were the protein (Z1) and citric acid (Z2)
concentrations, as shown in Tables 1 and 2. The central point
values were selected in order to provide a beverage that would
have one third of the protein content of soymilk. The dependent
variable (response) was the consumer acceptance scores (overall
acceptability). This procedure was selected such that the data
could be analyzed by Response Surface Methodology to
determine the optimum concentrations of the ingredients. The
validity of the model was evaluated by its adjusted coefficient
of determination (R2) and the lack of fit.
TABLE 1. Independent variables and levels used in beverage
formulation.
Variation of levels used in the formula
Natural variables
–1.41
–1
0
+1
+1.41
Z1 (g/100 mL)
0.293
0.5
1.0
1.5
1.707
Z2 (g/100 mL)
0.251
0.375
0.675
0.975
1.099
Z1: Soymilk protein concentration (g/100 mL);
Z2: Citric acid concentration (g/100 mL).
TABLE 2. Outline of experimental design for the sensory
acceptance study of the beverage formulation.
Codi fi ed
Vari ables
Decodi fi ed
Ingredi ents
Vari ables
(%)
Protei n Ci tri c aci d
Concentraded
Soymi lk
Conc.
Conc.
Orange Jui ce
10.1
0.5
0.375
18.5
Experi ment
X1
X2
1
-1
-1
2
-1
1
0.5
0.975
18.5
3
1
-1
1.5
0.375
55.5
4
1
1
1.5
0.975
55.5
5
-1.41
0
0.293
0.675
10.8
6
1.41
0
1.707
0.675
63
7
0
-1.41
1
0.251
37
8
0
1.41
1
1.099
37
9
0
0
1
0.675
37
10
0
0
1
0.675
37
11
0
0
1
0.675
37
12
0
0
1
0.675
37
2. MATERIALS AND METHODS
2.1 Materials
Concentrated orange juice (66°Brix, Brix/titratable acidity
ratio=17.8) obtained from a citrus processing plant in Sao Paulo
State and soymilk (protein concentration of 2.65%) processed
at UNISOJA (Soya by-products processing plant) at The Faculty
of Pharmaceutical Sciences, UNESP, Araraquara, SP, BRAZIL.
Sensory Acceptance of a Functional
Beverage Based on Orange Juice and
Soymilk
26.3
10.1
26.3
18.2
18.2
6.8
29.6
18.2
18.2
18.2
18.2
Coding: X1 = (Z 1 – 1) / 0.5; X2 = (Z2 – 0.675) / 0.3; protein and citric acid
concentration are expressed as g/100 mL.
Braz. J. Food Technol., v.6, n.2, p.153-156, jul./dez., 2003
154
VALIM, M.F. et al.
Sensory analysis. Consumer acceptance tests were
carried out in individual sensory booths, using 20 consumer
assessors recruited amongst the students and staff of the Faculty
of Pharmaceutical Sciences in Araraquara, Brazil. Samples were
codified with random 3-digit numbers in 30mL glass containers
and were evaluated for overall acceptability using a 9-point
structured hedonic scale (1= dislike extremely; 9=like
extremely) (STONE; SIDEL, 1985). The samples were randomly
evaluated; three in each session, and all assessors evaluated
all the samples. The statistical analyses and graphs were done
using the statistical package program STATISTICA, 1998.
3. RESULTS AND DISCUSSION
Twelve beverages were produced according to the
proposed experimental design and submitted to the assessors
for sensor y evaluation. The average values for overall
acceptability and standard deviation are presented in Table 3.
The standard deviation was within the expected range since
each assessor judged the samples according to his own
expectations with respect to the beverage.
TABLE 3. Average values and standard deviation for overall
acceptability of the beverages.
Beverage
1
2
3
4
5
6
7
8
9
10
11
12
Average
4.7 6.0 6.3 6.2 6.1 6.7 4.3 5.7 6.9 6.8 7.6
7.1
SD
1.9 1.8 1.8 1.8 1.2 1.6 1.9 2.2
methodology was a very useful tool to provide an insight into
the interactions and identify the optimum combination of the
variables, with a relatively small number of experiments, thus
reducing the time and cost of the study.
MENDES et al. (2001) studied the roasting of robusta
coffee to optimize the settings for roasting time and
temperature with respect to the acceptance of the sensory
attributes of aroma, flavor and color. The use of the optimum
roasting range resulted in a beverage with a mean acceptance
for both aroma and flavor between 6 and 7 on the hedonic
scale. The fitted model presented coefficients of determination
of 0.8, 0.71 and 0.96 for aroma, flavor and color, respectively.
In most Response Surface Methodology problems, the
relationship between the response and the independent
variables is unknown. In this study, a second order quadratic
equation was selected for optimization of the response, overall
acceptability (Y):
Y = β0 + β1X1 + β2X2 + β11X12 + β22X22 + β12X1X2 + ε
Where X1 = protein concentration, X2 = citric acid
concentration, ε = experimental error and the values for β are
the parameters of the least square estimators. The analysis of
variance carried out for the fitted equation for overall
acceptability (F test - Table 4), showed that the quadratic model
was suitable for the experimental data, as the lack of fit was
not significant.
TABLE 4. Analysis of variance of the quadratic model fitted to
the overall acceptability (response).
1.1 1.3 1.1 1.2
Average of 20 assessors; SD = standard deviation; beverages numbered from
1 to 12 according to Table 2.
Response Surface Methodology has been used for the
optimization of several food processes with respect to their
sensory attributes and other chemical characteristics of the
products developed (ROSSI et al., 1990; CHANG et al., 1998;
ALVAREZ; CANET, 1999; RASTOGI; RASHMI, 1999; ULGEN;
OZILGEN, 1993; MENDES et al., 2001).
ROSSI et al. (1990) used RSM to determine the optimum
concentrations of stabilizers to improve the texture and overall
acceptability of a soy-whey yogurt. An 8-member trained
sensory panel evaluated fifteen formulations of soy-whey
yogurt. Revised models were calculated and the determination
coefficients were above 0.90.
CHANG et al. (1998) studied, amongst other factors,
the appearance of a snack based on blends of jatoba flour and
cassava starch. Thirty potential consumers evaluated the
products using a 9-point hedonic scale. The fitted model
presented a coefficient of determination of 0.71.
The enzymatic liquefaction of mango pulp was
optimized by response surface methodology by RASTOGI;
RASHMI (1999). These authors studied the effect of enzyme
concentration and incubation time on the yield, clarity and
viscosity of mango pulp. The coefficients of determination were
above 0.90. The authors pointed out that response surface
Braz. J. Food Technol., v.6, n.2, p. 153-156, jul./dez., 2003
Sensory Acceptance of a Functional
Beverage Based on Orange Juice and
Soymilk
Sum of squares
DF
MeanSquare
F-rati o
Model
9.4221
5
1.8844
19.7528 (**)
Resi dual
0.5721
6
0.0954
L ack of fi t
0.1921
3
0.0640
Pure Error
0.3800
3
0.1267
Total
9.9942
11
0.5056 (ns)
(**) Significant at p < 0.01 (1%). (Ns) Non-significant at p < 0.05 (5%).
A revised model was calculated for overall acceptability:
Y = 7.010 + 0.326 X1 + 0.412 X2 – 0.330 X12 – 1.020 X22 –
0.335 X1X2.
As can be seen in Table 4, the linear and quadratic
parameters of the variables protein and citric acid
concentrations, significantly influenced (p < 0.05) the
acceptance of the beverage. The fact that the linear parameter
of both variables was positive indicates that an increase in
these variables within the limits studied in this experiment,
contributed to an increase in the acceptance of the beverage.
The quadratic terms of both variables were negative, thus
indicating that the stationary point within the experimental
region was the maximum to obtain the best acceptance. It
can also be observed that the quadratic term for citric acid
concentration (X 2) was more important than for protein
concentration (X1). The interaction between X1 and X2 can be
understood by observing that the effect of X1 on the response
was different from the X2 effect at two different levels of X2.
155
VALIM, M.F. et al.
The adjusted coefficient of determination (R2) was 0.89,
showing that the percentage of explained variability was high,
considering that the response variable is a hedonic
measurement, which can often present considerable variation
as the assessors were not trained. In accordance with the
complete model, a response surface was constructed for overall
acceptability of the beverage (Figure 1). It can be seen that the
surface created by the predictive model indicated a maximum
for overall acceptability that would allow the formulation of
the optimum beverage.
Sensory Acceptance of a Functional
Beverage Based on Orange Juice and
Soymilk
ACKNOWLEDGMENTS
This project was supported by PADC/FCF/UNESP.
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