Gluten-free Bread Based on Tapioca Starch: Texture and Sensory Studies

Abstract

In the present work, gluten-free formulations for breadmaking, destined to celiac people, were studied. A base blend of tapioca
starch and corn flour (80:20) and typical bread ingredients such as yeast, salt, sugar and water were utilised. Ingredients
such us vegetable fat, hen egg, and soybean flour were incorporated in different levels by means of an experimental design
of three factors. Bread quality was analysed throughout physical (specific volume, weight loss percentage) and textural (firmness,
elasticity and firmness recovery) parameters. The optimum bread selected, the bread with highest levels of fat and soybean
flour and one egg, presented low values of firmness (≤100N) and elasticity (>65%) and the lowest variation of these parameters
with storage. Overall acceptability of this bread was 84% for habitual consumers of wheat bread and 100% by celiac people.
Therefore, tapioca starch-based breads with spongy crumb, high volume and a good sensory acceptance were obtained.

KeywordsGluten-free bread–Tapioca–Soybean–Bread texture–Sensory quality

Full text

ORIGINAL PAPER
Gluten-free Bread Based on Tapioca Starch: Texture
and Sensory Studies
Laura B. Milde &Laura A. Ramallo &María C. Puppo
#Springer Science+Business Media, LLC 2010
Abstract In the present work, gluten-free formulations for
breadmaking, destined to celiac people, were studied. A
base blend of tapioca starch and corn flour (80:20) and
typical bread ingredients such as yeast, salt, sugar and water
were utilised. Ingredients such us vegetable fat, hen egg,
and soybean flour were incorporated in different levels by
means of an experimental design of three factors. Bread
quality was analysed throughout physical (specific volume,
weight loss percentage) and textural (firmness, elasticity
and firmness recovery) parameters. The optimum bread
selected, the bread with highest levels of fat and soybean
flour and one egg, presented low values of firmness
(≤100 N) and elasticity (>65%) and the lowest variation
of these parameters with storage. Overall acceptability of
this bread was 84% for habitual consumers of wheat bread
and 100% by celiac people. Therefore, tapioca starch-based
breads with spongy crumb, high volume and a good
sensory acceptance were obtained.
Keywords Gluten-free bread .Tapioca .Soybean .
Bread texture .Sensory quality
Introduction
Technological advancement promotes the development of
new functional foods. Due to additive and new ingredients
incorporation, this kind of foods sometimes can be related
to non-natural foods. Therefore, sensory tests must be
performed (Sabanis and Tzia 2009). Celiac disease is an
inflammatory disease, manifested by genetically susceptible
individuals, of the upper small intestine which results from
gluten ingestion (Kelly et al. 1999; Mc Carthy et al. 2004).
People with this disease require gluten-free foods; those
that do not contain wheat, oat, barley and rye. Gluten-free
(GF) bread needs to be prepared with non-cereal flour, so as
to avoid gluten (specifically gliadins) content. Wheat gluten
proteins are the unique proteins that form a distinctive
cohesive and viscoelastic dough capable of retaining carbon
dioxide during fermentation and contribute to the appear-
ance and crumb structure of bread (Gallagher et al. 2003;
Gallagher et al. 2004); consequently, additives must be
included to improve gluten-free bread volume (Di Cagno et
al. 2004). Common bread is traditionally the more
consumed food by humans, because it is a product of low
price with high nutritional value. Following this objective,
formulation of gluten-free bread presents a challenge to
both cereal technologists and bakers, because of the
absence of gluten network that is the responsible for
physical and sensory properties of bread. Gluten-free
bakery products can be produced with alternative ingre-
dients such as starches, gum and hydrocolloids, dairy
products, leguminous proteins, prebiotics and several
combinations (Gallagher et al. 2004).
L. B. Milde :L. A. Ramallo
Facultad de Ciencias Exactas, Químicas y Naturales-Universidad
Nacional de Misiones,
Mariano Moreno,
1375, 3300 Posadas, Argentina
M. C. Puppo
Facultad de Ciencias Agrarias y Forestales-Universidad Nacional
de La Plata,
60 y 119,
1900 La Plata, Argentina
M. C. Puppo (*)
CONICET–Facultad de Ciencias Exactas UNLP (CIDCA),
47 y 116,
1900 La Plata, Argentina
e-mail: mcpuppo@quimica.unlp.edu.ar
Food Bioprocess Technol (2012) 5:888–896
Received: 29 December 2009 /Accepted: 6 May 2010 /Published online: 22 May 2010
DOI 10.1007/s11947-010-0381-x

The common flours used to replace wheat in breadmak-
ing for celiac people may be corn, soybean and rice
(Machado 1996; Nishita et al. 1976; Sanchez et al. 2002,
2004; Specher Sierra 2005; Rosales-Juárez et al. 2008) and
in some cases, maize (Brites et al. 2009). Cassava starch
could be a suitable option of gluten-free bread ingredient.
Mandioca or Tapioca (Manihot esculenta Crantz) is a
regional plant typical of South America, which grows in
Misiones province of Argentina and surroundings. This
crop grows in wet and tropical weather, and also under low
nutrients availability. It also survives in drought conditions
(Burrell 2003). Tapioca is a naturally GF ingredient;
however, GF formula requires polymeric substances, like
proteins or hydrocolloids, for reproducing viscoelastic
properties of gluten to provide structure and retain gas
(McCarthy et al. 2005).
Soybean flour and soy protein concentrate were first
used by Ranhotra et al. (1975) to prepare soy-fortified GF
bread; and later by other researchers (Sanchez et al. 2002,
2004; Sciarini et al. 2010). Dairy ingredients were used in
GF bread formulas to increase water absorption and to
improve shape, volume and crumb firmness of loaves,
especially those with high protein/low lactose content
(Gallagher et al. 2003). Sanchez et al. (2004) used, in GF
bread formulation, both ingredients: soy flour and dry milk.
They could increase protein content of GF bread by
modifying in small degree the specific volume and sensory
quality of loaves.
The objective of this work was to obtain gluten-free
bread with local tapioca starch and to analyse the influence
of the addition of fat, whole egg and soybean flour on
texture and sensory properties of loaves.
Materials and Methods
Materials
Materials used in this work were all gluten free and regional
(Argentina). Tapioca starch (Ranchito, Misiones), corn
flour (Indelma, Santa Fe), fresh yeast (Calsa, Buenos
Aires), salt (Celusal, Tucumán), sugar (Ledesma, Jujuy),
soybean flour (Instituto, Misiones), whole egg and vegeta-
ble fat (Margadán, Buenos Aires), were utilised.
Experimental Design and Statistical Analysis
Preliminary assays were performed to achieve adequate
experimental conditions to prepare GF bread with tapioca
as main ingredient. Changes were followed with a sensory
panel of habitual consumers of wheat bread. The tapioca
starch-corn flour ratio and the type of ingredients incorpo-
rated (fat, whole egg and soybean flour) were selected
according to different sensory attributes: colour, flavour,
texture and overall acceptability. The optimum dry mix was
found to be composed of tapioca starch-corn flour 80:20.
Salt (1.4%), sugar (5%), yeast (5%), vegetable fat (2–6%),
egg (0–2 units) and soybean flour (0–10%) as protein
ingredients were also incorporated. A quantity of water
(50–58%) sufficient to give optimum dough was aggregat-
ed to the mix before kneading. Percentage of ingredients is
expressed as grams ingredient/100 g tapioca starch-corn
flour mix. The optimum dough consistency was determined
by measuring extensibility in a hand-made way.
In spite of the experimental limitations of this study, a
final formulation of GF bread was obtained from an
experimental design that allowed acquiring optimal
amounts of each ingredient. A random experimental design
of three factors was used: fat (F), whole egg (E) and
soybean flour (S). Twelve formulations for preparing bread
(b1-b12) were defined and are shown in Table 1.
Full factorial designs are the optimal experimental
strategy to simultaneously study the effect of several factors
on the answer and its interactions. In the Response Surface
Method, the experiment is designed to estimate interaction
and even quadratic effects of factors and to obtain an
optimal response (Montgomery 1997; Khuri and Cornell
1996). Central composite design is an experimental design,
useful in response surface methodology, for building a
second order (quadratic) model for the response variable
(Corzo and Gomez 2004;Cortes-Gómezetal.2005;
Toufeili et al. 1994).
Central composite designs consist of a factorial design
(the corners of a cube) together with centre and star points
that allow for estimation of second-order effects. If the
Table 1 Experiment design of bread formulations
Bread Coded variable levels Decoded variable levels
FESF(g)
a
E(unit) S(g)
a
1−1−1−110 0 0
2+1−1−130 0 0
3+1+1−130 2 0
4+1+1+130250
5−1+1+1 10 2 50
6−1−1+1 10 0 50
7−1+1−110 2 0
8+1−1+1 30 0 50
9 0 0 0 20 1 25
10 +1 0 +1 30 1 50
11 +1 0 0 30 1 25
12 0 0 +1 20 1 50
Ffat, Ewhole egg, Ssoybean flour
a
F, S: g ingredient (F or S)/500 g tapioca starch-corn flour mix
Food Bioprocess Technol (2012) 5:888–896 889

distance from the centre of the design space to a factorial
point is ±1 unit for each factor, the distance from the centre
of the design space to a star point is ±αwith |α| > 1. The
precise value of αdepends on certain properties desired for
the design and on the number of factors involved. Since the
amount of eggs to incorporate had to be an integer number,
it was not possible to apply the popular rotatable central
composite design. Fortunately, easy-to-use software, for
example Statgraphics plus, for desired function methodol-
ogy implementation is available. Due to these modifica-
tions, the applied response surface model is not the optimal
one, but it allowed finding a relation between the
independent variables and the response.
All treatments were performed randomly and data
obtained (Tables 1and 2) from mechanical parameters
(firmness, elasticity, firmness recovery) were analysed
using response surface methodology by Statgraphics plus
for Windows 5.1 software. Data obtained from physical
parameters (specific volume, weight loss) were subjected to
analysis of variance (ANOVA). Average parameters and
standard deviation were calculated (Table 2). The second
order model proposed (Khuri and Cornell 1996; Sanchez et
al. 2002) for each textural and physical parameter was
(Eq. 1):
Y¼b0þb1X1þb2X2þb3X3þb11X12þb22 X22
þb33X32þb12 X1X2þb13X1X3þb23 X2X3ð1Þ
Where Yis the response (firmness (f), elasticity (e) and
firmness recovery (fr)); b
0
,b
i
,b
ii,
and b
ij
are regression
coefficients; X
1
,X
2
and X
3
are coded variables that
represent the F, E and S, respectively.
The model adequacies were checked by the variance
analysis (Ftest) and R
2
values. The effect of variables was
registered using surface graphs.
Breadmaking
Ingredients were mixed in a home kneader Philips 32 Serie
(Philips, Brasil) at 160 rpm for 2 min. Kneading was
continued by hand up to obtaining homogeneous dough
(10 min). Dough was incorporated in greased stainless
rectangular moulds (29.3× 10.2 × 9.5 cm) and fermented
30 min at 35°C. Breads were baked at 240°C for 20 min
and at 280°C for 10 min, with steam.
Physical and Mechanical Evaluation
Specific Volume of Bread Volume of bread pieces, that were
almost regular in shape, was calculated by measuring
height, width and length of the loaves, with a ruler. As
the loaves were not regular in width, the last one was
measured in the bottom and in the top of each cross-section
of the bread. The average width between both measure-
ments was calculated for all pieces of bread. Specific
volume (V
e
) was obtained dividing each volume by its
respective weight (Reyes Aguilar et al. 2004). Three
replicates were acquired for each formulation.
Weight Loss of Bread Weight loss (WL) of bread was
determined according to method utilised by Da Mota
Zanella et al. (2005) (Eq. 2):
%WL ¼weight of dough weight of breadðÞ=weight of dough½100
ð2Þ
Texture Evaluation Texture Profile Analysis of bread was
performed using a Universal Dynamometer (Adamel
Lhomargy DY32, Roissy en Brie, France) provided with a
1,000 N cell (with a sensitivity of tenth of N). Each sample
was subjected to two cycles of compression up to 50% of
Physical parameters
a
Texture parameters
a
Bread V
e
(cm
3
/g) %WL f(N)e(%) fr (%)
1 1.88± 0.04bc 9.38 ± 0.04a 132 ± 0.1a 70.9 ± 0.1a 89.0± 0.5d
2 1.75± 0.03a 11.35± 0.06b 183 ± 6.6b 73.0 ± 4.0bc 90.2 ±0.2e
3 2.07± 0.04d 13.68±0.03c 108±9.8c 67.7± 2.8d 90.8±1.4f
4 2.68± 0.01e 25.58± 0.05d 81 ± 0.7d 63.6± 0.4e 88.2± 1.4c
5 2.23± 0.02f 17.07± 0.02e 98 ± 11e 72.9±5.1b 85.9 ± 0.7a
6 1.61± 0.06g 14.29±0.03f 152±13f 48.1±1.6f 89.1 ± 1.7cd
7 2.10± 0.00d 15.38±0.04g 158±22g 73.6± 2.1c 91.3± 0.4g
8 1.51± 0.02h 13.95±0.00h 329±35h 71.1± 2.5a 86.0± 1.1a
9 1.81± 0.04ab 14.29 ± 0.03f 207 ± 19i 60.1± 1.7g 87.5± 2.3b
10 2.01±0.01d 15.91 ± 0.02i 101 ± 3.6j 67.6±3.5d 89.0 ± 1.5cd
11 1.91±0.01c 12.20±0.06j 101 ± 7.0j 67.8 ± 0.1d 91.8±1.4g
12 1.72±0.03a 11.11± 0.05k 110± 16k 60.2± 1.7g 92.7± 0.9h
Tab l e 2 Physical and texture
parameters of breads
Different letters in the same
column indicate significant
differences (p<0.05).
V
e
specific volume, %WL
percentage of weight loss,f
firmness, eelasticity,frfirmness
recovery, 30°C testing tempera-
ture, 2htime after baking
a
Average values and standard
deviations.
890 Food Bioprocess Technol (2012) 5:888–896

the original height with a rectangular probe (20×20 cm;
Bourne 2002).Forcetimecurveswereobtainedata
crosshead speed of 100 mm/min. Samples were cut in
blocks of 9 cm width×9 cm length× 7 cm height. Product
firmness, elasticity and firmness recovery were determined
in triplicates for each formulation of the experimental design.
Firmness is defined as the maximum force registered during
the first compression cycle and was measured according to
AACC standard method (AACC 2000). Elasticity was
calculated as of the ratio of L2/L1, expressed as percentage;
being L2 and L1 the distances between the beginning and
the maximum force of the second and first compression
cycle, respectively. Firmness recovery was calculated as the
percentage of F2/F1; where F2 and F1 are maximum forces
of the second and first compression peaks, respectively.
All evaluations were performed with fresh bread and the
same bread was then stored at 25 °C for 24 h, in order to
study the effect of storage time on mechanical properties of
different bread formulations. Samples were stored in sealed
plastic containers to avoid moisture loss.
Sensory Evaluation
Two separate consumer studies were performed. Sensory
analysis tests with habitual consumers of bread from wheat
flour (non-celiac people) and celiac people were performed
with a selected bread formulation. The more suitable bread
formula for sensory evaluation was selected according to the
best textural (low firmness, high elasticity and high firmness
recovery) and physical (high specific volume, low weight
loss) parameters. All breads were baked and packaged in the
morning of the day of testing, and were tested within 4 h
from baking (fresh bread) and tested within approximately
26 h from baking (stored bread). Sensory attributes evaluated
were firmness, cohesiveness and overall acceptability. In
order to analyse overall acceptability, a five-point hedonic
scale was utilised. Some authors have assigned values to
each score, assuming equal intervals (Carpenter et al. 2000;
Watts et al. 1989). The higher rating reflected good quality
attributes. Scores ranged from “Like very much”(score 5)
to “Dislike very much”(score 1; Meilgaard et al. 1999;
Gallagher et al. 2003).
The nine-point hedonic scale is recommended for use in
sensory evaluation of food product. Its use has been
validated in the scientific literature (Stone and Sidel
1993). However, in some instances, adaptations of the
nine-point hedonic scale were found useful (Pittia et al.
1999; Zandstra et al. 1999; Abdullah and Cheng 2001). We
must choose scales that are easy for the panellists to use;
thus, they can concentrate on the product evaluation. A
five-point scale was used in order to simplify the
respondent’s task. In addition, five-point hedonic scale
provided all the answers needed for our objectives.
Texture parameters Sensory hardness and cohesiveness
were evaluated by applying three-point scale: 1, “hard”;2,
“firm”;3,“soft”for hardness. For the cohesiveness
evaluation, the sensory scale was: 1, “brittle”;2,“tender”;
3, “gummy”. For evaluation of bread texture, approximate-
ly 50 g of each bread sample were presented to judges in
individual white plastic plates under white light at room
temperature.
Bread consumers Sixty students and staff from the Univer-
sity of Misiones, Argentina, aged between 20 and 55 years,
participated in this taste test. Sensory evaluation was
conducted in the Sensory Laboratory of the Department of
Food Science-University of Misiones, and was performed
on fresh bread and the same bread that was stored at 25°C
for 24 h. Two coded samples were presented to the judges
simultaneously, and the judges were asked to indicate their
hedonic response to each sample on the scale.
Celiac people Sensory evaluation with 20 celiac people
was performed with the same bread formulation (only fresh
bread) as was tasted by consumers. Celiac patients from the
Dr. Ramón Madariaga Hospital (Posadas, Argentina)
participated in the sensory studies on the acceptability of
the bread by celiac individuals.
Panellists of both sensory evaluations were not trained
(Zacarías et al. 1985; Hellemann et al. 1990; Hamad and
Fields 2006).
Results and Discussion
V
e
and WL of different formulated breads (Table 1), are
shown in Table 2. Statistical analysis (ANOVA) showed
that significant differences (p<0.05) in Ve and WL were
observed between samples.
Bread 4 (b4) presented the highest V
e
and WL. Soybean
proteins usually present high water imbibing capacity.
Nevertheless, their interaction with starch (tapioca and
corn) and in the presence of high levels of egg is not able to
retain water in bread.
Diminishing level of F but maintaining E and S (b5),
produced a slight decrease in V
e
and WL. This decrease was
intensified when E was eliminated from formulation (b6),
presenting one of the lowest values of V
e
. The egg must not
be absent if we want to obtain bread with an acceptable
volume.
When E and S are present together, there is a synergic
effect, because the highest values of both parameters (V
e
and WL) were obtained. Bread maintained water in crumb
structure better if low levels of fat were used (b4 vs. b5).
Comparing formulations F and S in intermediate and high
levels (b9, b10, b11, b12) and with only one egg, better
Food Bioprocess Technol (2012) 5:888–896 891

volume was obtained when F and S were in their high level
(b10). In this work, a low WL level was searched, in order
to ensure moisture content that impede bread dehydration
and to prevent a great increase of hardness and elasticity of
product (Esparza Rivera et al. 2005).
Formulations without soybean flour and with two whole
eggs (2 units) developed good volume (b3 and b7). Since
tapioca starch and corn flour contain virtually no protein,
soybean flour was included to ensure a nutritionally balanced
product with enriched in protein content (Sanchez et al. 2004).
Eggleston et al. (1992) reported an increase in bread
volume in products made with fat, tapioca and soybean flour.
A uniform distribution of size of gas cells were obtained,
allowing a soft and sponge crumb texture. In our case,
breads not only with soybean flour and fat, but also by one
or two whole eggs in the formulation presented high specific
volume with a soft crumb texture (low firmness). Edema et
al. (2005) reported, in bread formulated with soybean flour
and corn starch, a regular cell distribution with small crust
cracking, due to high hydration capacity of soybean proteins.
Due to benefit properties of soybean proteins, through S,
and of E, and acceptable V
e
and low WL values, b10 was
considered as one of the optimum bread. Bread 10
presented a similar response than the best breads (b4 and
b5), but with only one egg in its formulation. Simulta-
neously, b10 were selected by non-trained consumers (data
not shown), as a good bread.
Mean values and standard deviation of texture parame-
ters (firmness, elasticity and firmness recovery) of all bread
samples are also shown in Table 2. The bread with lowest
firmness, that is, with softer crumb, was bread 4 (b4). On
the other hand, the bread with highest firmness and lowest
elasticity and firmness recovery was b8. These results agree
with specific volume and water loss results. Both breads
have the same and highest content of fat and soybean.
However, b4 was formulated with two eggs, while b8 did
not contain egg in its formulation. These results indicate
that egg is an important ingredient in formulating gluten-
free bread with adequate physical and textural properties.
Surface response (SR) graphs shows variation of texture
parameters as function of two independent variables, main-
taining the third variable at the middle level (code variable=
0). Figure 1shows surface response of f. Breads with fat, at
middle level, presented maximum firmness values, with the
exception when F was combined with the middle level of E
(Fig. 1a). This effect was accentuated with soybean addition,
presenting a maximum at level 0 of S (Fig. 1b). On the other
hand, with level 0 of E and the highest level of S, lowest
firmness values were observed (Fig. 1c).
Figure 2shows SR graph of e. The presence of fat did
not provoke a significant influence in elasticity values
(Fig. 2a, b), whereas soybean addition decreased bread
elasticity probably due to interaction with fat (Fig. 2b). The
egg addition produced a maximum in elasticity at middle
level (one egg; Fig. 2a); the elasticity decreased with the
presence of soybean flour (Fig. 2c).
Edema et al. (2005), in concordance with our results,
evaluating bread with corn flour reported moderate
10 20 30
Fat
012
Egg
0
100
200
300
400
Firmess (Newton)
Fat Soybean
Firmess (Newton)
10 20 30 0
25 30
-10
30
70
110
150
190
Egg Soybean
Firmess (Newton)
0 120
25 50
100
150
200
250
300
350
400
ab c
Fig. 1 Response surface for firmness (f) of gluten-free breads as a function of afat (F) and egg (E), bfat (F) and soybean flour (S), cegg (E) and
soybean flour (S)
10 20 30
Fat
0
12
Egg
38
43
48
53
58
63
68
Elasticity (%)
Fat
Soybean
Elasticity (%)
10 20 30 0
25
50
56
66
76
86
96
106
E
gg
Soybean
Elasticity (%)
0120
25
50
35
45
55
65
75
85
95
ab c
Fig. 2 Response surface for elasticity (e) of gluten-free breads as a function of afat (F) and egg (E), bfat (F) and soybean flour (S), cegg (E) and
soybean flour (S)
892 Food Bioprocess Technol (2012) 5:888–896

elasticity values when soybean was incorporated to
formulation.
Surface response of fr was similar to those obtained for
elasticity due to relationship between parameters.
Variation of texture parameters of fresh breads, with the
level of different ingredients (F, E, S) according to
experimental design showed in Table 1, was analysed with
a second order polynomial model, and regression coeffi-
cient was obtained (p<0.05; Table 3). The model well
predicted firmness and elasticity variations (r
2
>85%),
while for firmness recovery, the model did not render a
good correlation (r
2
<50%).
Fat and eggs showed significant linear effects on
firmness (Table 3). All variables showed significant
quadratic and interaction effects on this parameter. Only
soybean flour showed significant linear effects on elasticity
and firmness recovery, while eggs exhibited significant
quadratic effect on elasticity and firmness recovery. These
results indicate that fat does not affect the elasticity of the
fresh bread.
The optimum bread formula was selected according to
firmness and elasticity values of fresh bread and according
to the lowest variation with storage, of firmness (Δf) and
elasticity (Δe). Low and intermediate values of firmness
(≤100 N) and elasticity (>65%), respectively, were prefer-
able to be chosen, due to avoiding crumb disaggregation.
Ageing of bread involves physicochemical and sensory
changes, such as crumb firmness increase, loss of flavour,
crust hardening, formation of more opaque crumb and a
decrease in starch solubility (Kulp and Ponte 1981). Inagaki
and Seib (1992) proposed that the more important change
occurs in crumb firmness.
Table 4shows changes in texture parameters due to
bread storage (24 h at 25°C). Breads b5 and b10 presented
the lowest firmness increase and elasticity loss. This
behaviour could be due to the fact that both breads have
the highest content of soybean flour and also they have egg
in their formulations. Bread b2, that not contained egg nor
soybean flour, presented the highest firmness increase. It can
be observed that the addition of egg and soybean proteins
Source Firmness Elasticity Firmness recovery
Coefficient pvalue Coefficient pvalue Coefficient pvalue
Constant (b
0
) 187.86 60.83 89.4217
b
1
21.01 0.0151 0.77 0.6274 −0.06 0.9293
b
2
−42.84 0.0001 −1.13 0.4810 0.19 0.7757
b
3
10.94 0.1688 −14.17 0.0001 −1.58 0.0331
b
11
−88.93 0.0013 5.46 0.2469 0.51 0.7923
b
22
125.18 0.0001 −21.09 0.0005 −4.03 0.0593
b
33
−70.07 0.0066 12.89 0.0133 2.98 0.1454
b
12
−37.81 0.0002 2.91 0.0842 0.53 0.4377
b
13
21.25 0.0130 2.56 0.1177 −0.35 0.6035
b
23
−32.79 0.0008 0.44 0.7637 −0.44 0.5224
R
2
90.4% 88.3% 43.2%
Table 3 Analysis of variance
and regression coefficients for
the second-order polynomial
model
Significant differences at
pvalue <0.05
Texture parameters
Bread Δf=f
24
-f
0
(N)Δe=e
24
-e
0
(%) Δrf= fr
24
-fr
0
(%)
1 234.6
ab
−34.8
a
−13.4
a
2 619.0
e
−13.8
b
−9.1
b
3 321.2
d
−30.1
c
−6.2
c
4 125.1
f
−2.4
d
−3.7
d
5 83.2
f
−2.3
d
−7.4
e
6 274.7
bc
−10.5
e
−9.2
b
7 241.8
ab
−24.4
f
−12.1
f
8 210.9
a
−3.3
g
−11.3
g
9 216.7
a
14.9
h
−10.2
h
10 109.1
f
−0.7
i
−11.8
g
11 259.5
bc
−4.2
j
−16.0
i
12 291.8
cd
7.4
k
−18.6
j
Table 4 Variation of firmness
(Δf), elasticity (Δe) and firm-
ness recovery (Δfr) of gluten-
free bread with storage
Different letters in the same
column indicate significant dif-
ferences (p<0.05)
Storage conditions: T. Average
texture parameters of fresh
bread: firmness (f), elasticity
(e), firmness recovery (fr). Fresh
breads: f
0
,e
0
,fr
0
. Stored brads:
f
24
,e
24
,fr
24
Food Bioprocess Technol (2012) 5:888–896 893

contribute to the decrease of ageing. Soybean, specially
accompanied by egg at the highest level (b4, b5), did not
favour the increase of bread firmness in a great extent.
An intermediate level of egg (1 unit) does not contribute
in the same manner with the different levels of fat or
soybean flour. Breads with similar high firmness and
elasticity increase, was obtained with intermediate levels
of E and F; and medium and high level of S (b9 and b12).
The lowest variation with storage, of firmness (Δf) and
elasticity (Δe) was obtained with b10, that is, with the
highest levels of F and S.
Esparza et al. (2005) found in wheat bread, in which part
of wheat flour was replaced by soybean flour; that firmness
of bread did not change with storage time (1-48 h).
Nevertheless, breads with soybean retained more water
during time, due to the high water holding capacity and
the ability of these proteins to reinforce crumb structure.
The use of egg in addition with soybean maintained the
elasticity characteristic of tapioca. The presence of egg
favours bread with more soft texture (Torres and Pacheco
2007). Studies performed by Eggleston et al. (1992)
suggest the use of tapioca-soybean flour mixtures, with
the aim to increase nutritional value of bread. They also
proposed the addition of fat and egg albumen for reducing
the extent of starch solubilisation and gelatinization,
increasing the quantity of air trapped during batter mixing.
The combination E+S could interfere with starch retrogra-
dation, inhibiting firmness increase and elasticity changes.
Textural changes during storage were also considered in
the selection of the best tapioca-corn bread used in sensory
analysis by celiac people.
Sensory analysis with habitual consumers of bread (non-
celiac people) and celiac people was performed with a one
selected bread formulation. The bread chosen was the bread
that presented suitable physical and textural characteristics
fresh and with 1-day storage. Figure 3shows that bread 10
(b10) presented also a good crust and crumb structure.
With respect to the sensory evaluation of each product,
quantitative scores information was analysed by frequencies.
Tab le 5shows percentage of different attributes: overall
Sensorial parameters Score Bread consumers Celiac people
Fresh Stored (24h) Fresh
Overall acceptability
Like very much 5 5 14 45
Like moderately 4 42 26 45
Neither like nor dislike 3 37 39 10
Dislike moderately 2 10 18 0
Dislikes very much 1 6 3 0
Hardness
Soft 3 60 19 0
Firm 2 39 74 100
Hard 1 1 7 0
Cohesiveness
Gummy 3 60 27 10
Tender 2 32 39 85
Brittle 1 8 34 5
Table 5 Frequency of terms
(scores) for sensorial attributes
of b10 formulation (fresh and
stored by 24 h): Overall accept-
ability, hardness and cohesive-
ness evaluated by habitual
consumers of bread and celiac
people
Fig. 3 Control bread (a) and
bread prepared with the opti-
mum formulation, b10 (b)
894 Food Bioprocess Technol (2012) 5:888–896

acceptability (OA), hardness and cohesiveness, for bread 10
(b10). Scores can be grouped into two levels: acceptable (3-
5) and non-acceptable (1 and 2). B10 exhibited equal OA for
categories 4 and 5. Bread 10 was well accepted by celiac
people. Major part of consumers, habitual consumers of
wheat flour bread (non-celiac people; 84%) accepted the
fresh bread and that percentage was slightly reduced (79%)
when they evaluated the stored bread.
For hardness attribute, scores 3 and 2 were grouped as
acceptable; therefore, b10 was totally accepted by celiac
people. This sensory attribute, hardness, had good accept-
ability in an elevated percentage of bread consumers (98%),
still through samples with 24 h of storage (93%). The
increase in firmness of bread with storage time was
observed by consumers, but without arriving to rejection.
Cohesiveness scores gummy and tenderness (3 and 2)
were considered both acceptable; therefore, b10 obtained
95% of acceptation by celiac people. Habitual bread
consumers considered this attribute 93% acceptable in fresh
bread, and 66% in storage bread. Storage period (24 h)
downgraded cohesiveness characteristics of bread b10.
Conclusions
This study has demonstrated that gluten-free breads with high
acceptability can be made from tapioca starch and corn flour.
These breads were totally natural, without chemical additives.
Analysis of interaction between components (fat, egg, soybean
flour) at different levels of fresh and stored breads was
performed. Bread with the highest content of F, E and S
showed the highest specific volume and lowest crumb
firmness and elasticity, but a great weight loss. The optimum
formulation (b10), selected according to physical and texture
data, presented a similar response than the best breads but with
only one egg in its formulation. In addition, b10 presented low
firmness and elasticity changes after 1-day storage. Sensory
evaluation with bread consumers and especially celiac people
confirmed the proposed objectives. Bread with 100% of
acceptance, prepared with local raw materials, enriched in
proteins due to soybean flour incorporation and natural (free of
additives and preservatives), was able to be obtained.
Acknowledgements The authors would like to acknowledge SeCyT
(UNAM) and FCAyF (UNLP) of Argentina for the financial support.
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