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In this study, the possibility of bread machine utilization as a quality control tool in the baking industry was investigated. Three different flour samples (F-1, F-2, and F-3) having different protein contents were obtained and then 12% wheat starch and 2% vital gluten were added to these flours to adjust protein ratios. The physicochemical and rheological properties of these flour combinations were analyzed. Specific volume, crumb grain attributes, crust and crumb color, and bread firmness in terms of compressibility (g) were measured. Specific volumes changed between 5.22 and 6.69 mL g(-1) and between 4.87 and 6.29 mL g(-1) for hearth and machine bread, respectively. Crumb firmness values of hearth bread made from F-1, F-2 and F-3 flours were 174.2, 259.4, and 180.3 g, whereas the mean firmness values of machine breads made from those flours were 91.2, 157.58, and 154.98 g, respectively. The F-2 flour had the poorest performance in both baking methods with regard to the evaluated features. At the same time, the bread machine performances were different, but displayed similar responses with changing flour quality. The effects of protein content were not observed in hearth bread. However, these changes affected specific volume and crumb features in bread machine baking. The study showed that bread machines with an optimized formula could be successfully employed for determining flour quality in bread making.
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608
Turk J Agric For
36 (2012) 608-618
© TÜBİTAK
doi:10.3906/tar-1202-48
Determination of the bread-making quality of  ours using an
automatic bread machine
İsmail Sait DOĞAN1,*, Önder YILDIZ2, Burhan TAŞAN1
1Department of Food Engineering, Faculty of Engineering Architecture,
Yüzüncü Yıl University, 65080 Van - TURKEY
2Department of Food Engineering, Faculty of Engineering, Iğdır University, 76000 Iğdır - TURKEY
Received: 15.02.2012 Accepted: 22.02.2012
Abstract: In this study, the possibility of bread machine utilization as a quality control tool in the baking industry was
investigated.  ree di erent our samples (F1, F2, and F3) having di erent protein contents were obtained and then 12%
wheat starch and 2% vital gluten were added to these  ours to adjust protein ratios.  e physicochemical and rheological
properties of these  our combinations were analyzed. Speci c volume, crumb grain attributes, crust and crumb color,
and bread  rmness in terms of compressibility (g) were measured. Speci c volumes changed between 5.22 and 6.69 mL
g–1 and between 4.87 and 6.29 mL g–1 for hearth and machine bread, respectively. Crumb  rmness values of hearth bread
made from F1, F2, and F3 ours were 174.2, 259.4, and 180.3 g, whereas the mean  rmness values of machine breads
made from those  ours were 91.2, 157.58, and 154.98 g, respectively.  e F2 our had the poorest performance in both
baking methods with regard to the evaluated features. At the same time, the bread machine performances were di erent,
but displayed similar responses with changing  our quality.  e e ects of protein content were not observed in hearth
bread. However, these changes a ected speci c volume and crumb features in bread machine baking.  e study showed
that bread machines with an optimized formula could be successfully employed for determining  our quality in bread
making.
Key words: Bread machine, bread quality,  our quality, french bread
Research Article
* E-mail: isdogan@yyu.edu.tr
Introduction
Due to the high consumption of bread, the baking
sector constitutes the most important section of the
food industry. Frequently changing quality prevents
the development of these industries and o en leads
to consumer dissatisfaction. Consumer demand is
one of the most important factors in the production
progress and development.  erefore, technological
development of the bread industry is done for the
purpose of boosting quality. Additionally, the quality
of bread and reducing bread waste are extremely
important (Göçmen 2001).
Wheat gluten quantity and quality are closely
related to bread quality. Addition of high-quality
wheat into the blend and the use of permitted
baking additives are recommended to obtain a
desirable standard of quality. Moreover, a variety of
additives are used to increase the nutritional value
of the bread and to delay staleness and spoilage. In
particular, the additives used in large-scale bread
production facilities for the purpose of balancing
changes in  our quality signi cantly a ect the dough
rheology and bread features. In the baking industry,
widely used additives are oxidants, reducing agents,
İ. S. DOĞAN, Ö. YILDIZ, B. TAŞAN
609
emulsi ers, and enzymes (Stau er 1983).  e roles of
components and process steps should be well known
in order to correct any faults in the bread and identify
the source of the lack or surplus that may arise during
production. At the same time, it is possible for
knowledgeable and experienced bakery cra smen to
produce quality bread (Doğan 1997).
Professional sta , adequate equipment, and a
controlled environment are required to investigate
the bread-making potential of  our in baking
research institutes and facilities around the world.
Flour quality should always be veri ed with a baking
test in any instance of quality consideration.
e millers in Turkey o en send  our samples
to reputable bakeries and proceed according to
their feedback. Alternative approaches are needed
to determine the e ects of  our, additives, and the
other components on bread quality. Hansen and
Hansen (1992) investigated the possibility and
repeatability of using an automatic bread machine to
estimate the attainable bread volume. Czuchajowska
and Pomeranz (1993) used a system consisting
of a bread machine and a rheofermentometer to
assess gas formation and retention. Faa et al. (1994)
used an automatic bread machine to optimize the
bread formula and reported promising results. In
determining the quality of  our for bread making, a
method that is easy to apply and practical is needed.
Because of the changes in wheat quality from year to
year, the analysis must be repeated and the obtained
test results should be compared with each other.
In most mills, the existing tools and equipment
used to identify physical, chemical, and technological
characteristics of  our are rudimentary and not
su cient.  e bread machine may be important
for determining  our quality for bread making
in a reasonable period of time. Furthermore, the
companies that produce and market baking additives
have been requesting faster and more reliable
baking tests so that they can prepare an appropriate
combination of additives. No relevant scienti c
studies have been found that compare the results
of bread production using a bread machine and by
standard baking.
In this study, the possibility of using automatic
bread machines as quality control tools was
investigated.  e properties of bread made using
a bread machine were compared with those of a
standard free-type hearth (French) bread.
Materials and methods
In this study, 3  our samples (Akova Flour and Feed
Co., Sakarya, Turkey; Toprakcan Flour and Food
Industry, Van, Turkey; and Başer Food Industry,
Sakarya, Turkey); instant active dry yeast (IADY;
Pak Food Production and Marketing Co., İstanbul,
Turkey); a  our treatment agent including alpha
amylase, vitamin C, and an emulsi er (Puratos
Food Industry, İstanbul, Turkey); wheat starch
(Tate and Lyle Europe NV, Aalst, Belgium); vital
gluten (Meelunie America, Inc., Farmington Hills,
MI, USA); and sugar and salt suitable for bread
production obtained from a local market were used.
To each of the 3  our samples, 12% wheat starch and
2% vital gluten were added to adjust the protein ratio
to between approximately 9.0% and 14.0%.
e following automatic bread machines were
used in this study: Moulinex Home Bread (Groupe
SEB İstanbul Household Appliances Trade Co.,
İstanbul, Turkey), Ekmatik Inox 033 (Art Kitchen
Household Tools Co., İstanbul, Turkey), and Sinbo
SBM-4701 (Depan Electronic Industry and Trade
Company, İstanbul, Turkey). For all bread machines,
the French bread program was selected.
Bread production with an automatic bread machine
Ingredients in the formula were  our (300 g, 14%
moisture basis), salt (5.4 g), IADY (2.4 g), a  our
treatment agent (6 g), and sugar (9 g).  e total amount
of  our was adjusted when starch and vital gluten
were added to the formula.  e amount of water to be
added for optimum dough properties (500 BU) was
decided based on a preliminary farinograph water
absorption experiment. All baking experiments were
performed in the same environment, free of air ow.
First water and then  our, salt, sugar, and the  our
treatment agent were added to the machines. IADY
was added 1-2 min a er the machine was started.
Hearth (french) bread production
Ingredients in the formula were  our (2000 g, 14%
moisture basis), salt (36 g), IADY (24 g), and a
our treatment agent (40 g).  e total amount of
our was adjusted when starch and vital gluten was
Determination of the bread-making quality of  ours using an automatic bread machine
610
added to the formula. Flour and treatment agents
were weighed, placed in a mixer (Öztiryakiler Öm-
20, İstanbul, Turkey), and blended for 15 s for a
homogeneous distribution. Later, water was added.
e water absorption level (%) of the  ours and the
total kneading duration (min) were predetermined
on the basis of extensograph absorption and
farinograph development time.  e selected
kneading speed was 100 rpm. Salt and yeast were
added to the dough just 5 and 3 min before the end,
respectively.  e kneaded dough was rested for 30
min at 30 °C and 85%-90% relative humidity.  e
dough was then cut into 350-g pieces, rounded, and
rested for 10 min before being formed into its  nal
shape.  e nal fermentation was performed at 30
°C and 90%-95% relative humidity.  e dough was
removed from the fermentation cabinet and scored
to give the characteristic appearance of the bread
a er 5 min of resting.  e dough was baked at 200
°C for 20 min in a convection oven (PS5, Köseoğlu
Heat Co., İstanbul, Turkey).  e bread samples were
cooled for 2 h, packaged in polyethylene bags, and
kept at 20 °C until analysis.
Analysis of  our and bread
Ash and protein content (American Association of
Cereal Chemists [AACC] methods 46-12, 08-01,
and 44-15A), sedimentation value (AACC method
56-81), wet gluten and gluten index (AACC method
38-12), falling number (AACC method 56-81), and
farinograph tests (water absorption, development
time, stability, and degree of so ening; AACC
method 54-21) were determined (AACC, 1995).
Bread volume (mL) was measured with a rapeseed
displacement method using a loaf volumeter (Şimşek
Laborteknik, Ankara, Turkey).  e speci c volume
of bread as used bread volume to weight (mL g–1) was
calculated. Baking loss is expressed as a percentage
of weight loss (%) a er baking and was calculated by
subtracting the baked bread weight from the dough
weight.
Crust and crumb color parameters (L, a, and b
values) of the bread were determined according to
the method used by Doğan (2002). Hue (color tone)
was calculated using the following formula: hue =
arctan(b/a). Images of the sliced bread were captured
using a  atbed scanner (HP Scan Jet 3500c, Hewlett
Packard Co., Palo Alto, CA, USA) at 600 dpi resolution
and analyzed as grey-level images (16 bits). Image
analysis was performed using digital image analysis
so ware 7.0 (MCID 2007). A threshold method was
used for di erentiating gas cells (pores) and noncells.
Form factors indicating the roundness of gas cells
and the ratio of gas cells to the total area (proportion)
were recorded.
Bread  rmness was measu red in accordance with
AACC (1995) standards a er 3 h of baking using a
TA.XTPlus texture analyzer (TA.TX2, Stable Micro
Systems Ltd., Godalming, Surrey, UK) equipped with
a 5-kg load cell and a 36-mm cylinder aluminum
probe (P36/R). Firmness was expressed as the force
(g) required for 25% compression of bread slices of
25 mm in thickness.
Statistical analysis
e  ours and automatic bread-making machines
were randomly coded as F1, F2, and F3 and as A, B,
and C, respectively. For production of hearth (french)
bread, 2-way analysis of variance (ANOVA; factorial
design) was applied in 3 replications. For production
using the automatic bread machines, 3-way ANOVA
(factorial design with 3 replications) was used on
the data. Results from the 2-way ANOVA and 3-way
ANOVA were evaluated independently. Fisher’s
least signi cant di erence (LSD) test was used to
determine signi cant di erences. e signi cance
level was considered to be P < 0.05. All statistical
analyses were performed using CoStat 6.3 and
StatGraphics Centurion 15.1 (Cohort 2004; StatPoint
2006).
Results
Table 1 presents the characteristics of the  our
samples used in the study. A farinograph assessment
of the experimental  our samples is given in Table
2. For the strong  our samples (F1 and F2), the
addition of starch signi cantly decreased dough
development time from 7.0 and 6.5 min to 1.8 and
1.9 min, respectively (P < 0.05). No signi cant
di erences were observed in development time
with the addition of vital gluten to the experimental
our samples. However, the addition of vital gluten
signi cantly increased mixing stability in the F1 and
F3 our samples.
İ. S. DOĞAN, Ö. YILDIZ, B. TAŞAN
611
Speci c volume
e average speci c volume of hearth bread had
a range of 5.22 to 6.69 mL g–1 and a signi cant
di erence among the  our samples was found (P
< 0.001).  e average speci c volumes of the bread
samples made from F1, F2, and F3 were 6.27, 5.48,
and 6.43 mL g–1, respectively.  e di erence between
the average speci c volumes of bread samples
produced with F1 and F3 our was not signi cant,
while the speci c volume of bread produced with F2
our was signi cantly lower than the others (Table
3). No signi cant di erence exists among the  our
variations or the interaction of  ours and variations.
In hearth bread production, the impact of change in
the formula and process may not be easily observable
compared to pan bread production.
e average speci c volume of machine bread
changed between 4.87 and 6.29 mL g–1 depending on
the bread machine and  our variation.  e speci c
volume of the bread was signi cantly a ected by
the machines and  our sources (P < 0.001), and the
interactions of machine with  our and  our with
protein were also signi cant (P < 0.05).  e average
speci c volumes of bread obtained from machine C
(5.71 mL g–1), machine B (5.44 mL g–1), machine A
(5.33 mL g–1), F1 (5.99 mL g–1), F3 (5.54 mL g–1), and
F2 (4.94 mL g–1) are presented in Table 4 along with
other results.  e values of the speci c volumes of
bread made with both methods using di erent  our
combinations showed similar tendencies and were
a ected by the  our combinations used (Table 5,
Figure).
Baking loss
e baking losses of hearth bread varied between
21.78% and 23.62%, and the baking loss of bread
made from F2 was signi cantly lower than those of
Table 1. Chemical an d physicochemical analysis of experimental  our samples.*
Flour Ash (%) Protein (%) Sedimentation (mL) Falling number (s) Wet gluten (g) Gluten index (%)
F10.58 12.09 45 436 30.0 87
F20.60 12.50 44 380 31.0 93
F30.64 10.50 24 367 26.0 73
*Based on 14% moisture content.
Table 2. Farinographic analyses of experimental  our combinations.
Flour Variations Water absorption (%)* Development time (min) Stability (min) Degree of so ening (BU)
F1
ST 65.1b 1.8b 8.6c 48a
UT 67.4a 7.0a 11.9b 46a
VG 67.7a 6.8a 16.9a 32b
F2
ST 61.4b 1.9b 13.3b 31a
UT 63.2a 6.5a 18.5a 25b
VG 64.0a 7.2a 18.5a 30a
F3
ST 55.8b 1.3a 2.0c 104a
UT 57.2a 1.7a 6.8b 72b
VG 57.6a 1.8a 8.7a 52b
*Based on 14% moisture content.
ST: starch added, UT: untreated, VG: vital gluten added.
Di erent small letters indicate that the farinograph attributes are signi cantly di erent from each other when compared within each
group by LSD test, P < 0.05.
Determination of the bread-making quality of  ours using an automatic bread machine
612
the other  ours used in the study (P < 0.01). Less
breakage, leading to less rising during baking, was
probably the reason for its lower baking loss.
e baking losses of machine bread varied between
15.39% and 17.93% depending on the machine and
our sources.  e e ect of machine choice (Table
4) and the e ect of  our source on baking loss was
signi cant (P < 0.001). As expected, baking losses in
machine bread were lower than in hearth bread.
Bread  rmness
e e ects of  our and variations on the  rmness of
hearth bread samples were statistically important (P
< 0.01).  e rmness values of hearth bread made
from F1, F2, and F3 ours were 174.2, 259.4, and 180.3
g, respectively (Table 3).  e probable reason is a big
variation within each combination because of the
nature of the bread.
e average  rmness values of machine bread
samples varied between 129.3 and 138.1 g, but no
statistical di erence was found among the bread
machines for each  our sample in terms of  rmness.
e so est bread crumb (91.2 g) was obtained from
F1, the other  our samples yielded similar  rmness
values of 157.58 and 154.98 g, and the di erence
between F2 and F3 was not statistically signi cant.
e results are presented in Table 4.
Form factor of crumb grain
Depending on the  our sources, the form factor,
showing the roundness of the crumb grain (1 =
perfectly round), varied between 0.49 and 0.52 (Table
6) and the e ects of  our sources and variations on
Table 3. Speci c volume, baking loss, and  rmness values of hearth bread samples.
Speci c volume
(mL g–1)
Baking loss
(%)
Firmness
(g)
Mean ± SE Mean ± SE Mean ± SE
Flour
F16.27 ± 0.15a 23.41 ± 0.36a 174.16 ± 19.4b
F25.48 ± 0.15b 21.78 ± 0.36b 259.44 ± 19.4a
F36.43 ± 0.15a 23.62 ± 0.36a 180.28 ± 19.4b
Variation
ST 6.21 ± 0.15 23.27 ± 0.36 191.09 ± 19.4
UT 5.91 ± 0.15 22.69 ± 0.36 223.22 ± 19.4
VG 6.05 ± 0.15 22.85 ± 0.36 199.56 ± 19.4
Flour × variation
F1, ST 6.38 ± 0.26 24.22 ± 0.63 155.56 ± 33.6
F1, UT 6.16 ± 0.26 23.22 ± 0.63 182.49 ± 33.6
F1, VG 6.26 ± 0.26 22.80 ± 0.63 184.43 ± 33.6
F2, ST 5.58 ± 0.26 21.62 ± 0.63 241.13 ± 33.6
F2, UT 5.22 ± 0.26 21.56 ± 0.63 311.18 ± 33.6
F2, VG 5.64 ± 0.26 22.16 ± 0.63 226.02 ± 33.6
F3, ST 6.69 ± 0.26 23.98 ± 0.63 176.59 ± 33.6
F3, UT 6.34 ± 0.26 23.29 ± 0.63 176.00 ± 33.6
F3, VG 6.26 ± 0.26 23.57 ± 0.63 188.24 ± 33.6
ST: starch added, UT: untreated, VG: vital gluten added.
Di erent small letters indicate that evaluated attributes in each column are signi cantly di erent from each other when compared
within each group by LSD test, P < 0.05.
İ. S. DOĞAN, Ö. YILDIZ, B. TAŞAN
613
Table 4. Speci c volume, baking loss, and  rmness values of machine bread samples.
Speci c volume
(mL g–1)
Baking loss
(%)
Firmness
(g)
Mean ± SE Mean ± SE Mean ± SE
Flour
F15.99 ± 0.04a 17.11 ± 0.17a 91.22 ± 6.33b
F24.94 ± 0.04b 17.15 ± 0.17a 157.58 ± 6.33a
F35.55 ± 0.04c 16.20 ± 0.17b 154.98 ± 6.33b
Variation
ST 5.52 ± 0.04 16.91 ± 0.17 144.31 ± 6.33
UT 5.41 ± 0.04 16.61 ± 0.17 126.11 ± 6.33
VG 5.55 ± 0.04 16.95 ± 0.17 133.37 ± 6.33
Machine
A 5.33 ± 0.04b 17.36 ± 0.17a 138.15 ± 6.33
B 5.44 ± 0.04b 16.13 ± 0.17b 129.26 ± 6.33
C 5.71 ± 0.04a 16.97 ± 0.17a 136.38 ± 6.33
Flour × variation
F1, ST 5.89 ± 0.08b 17.18 ± 0.29 92.08 ± 10.96
F1, UT 5.96 ± 0.08ab 16.80 ± 0.29 89.99 ± 10.96
F1, VG 6.14 ± 0.08a 17.34 ± 0.29 91.59 ± 10.96
F2, ST 5.03 ± 0.08e 17.19 ± 0.29 166.70 ± 10.96
F2, UT 4.90 ± 0.08e 17.11 ± 0.29 151.26 ± 10.96
F2, VG 4.87 ± 0.08e 17.15 ± 0.29 154.78 ± 10.96
F3, ST 5.65 ± 0.08c 16.36 ± 0.29 174.16 ± 10.96
F3, UT 5.35 ± 0.08d 15.91 ± 0.29 137.07 ± 10.96
F3, VG 5.63 ± 0.08c 16.35 ± 0.29 153.72 ± 10.96
Flour × machine
F1, A 5.93 ± 0.08b 17.374 ± 0.29 95.18 ± 10.96
F1, B 5.77 ± 0.08b 16.552 ± 0.29 93.05 ± 10.96
F1, C 6.29 ± 0.08a 17.396 ± 0.29 85.44 ± 10.96
F2, A 4.77 ± 0.08e 17.936 ± 0.29 166.92 ± 10.96
F2, B 5.03 ± 0.08d 16.456 ± 0.29 143.71 ± 10.96
F2, C 5.10 ± 0.08d 17.067 ± 0.29 162.11 ± 10.96
F3, A 5.38 ± 0.08c 16.780 ± 0.29 152.34 ± 10.96
F3, B 5.51 ± 0.08c 15.392 ± 0.29 151.03 ± 10.96
F3, C 5.74 ± 0.08b 16.441 ± 0.29 161.58 ± 10.96
Variation × machine
ST, A 5.26 ± 0.08 17.20 ± 0.29 146.56 ± 10.96
ST, B 5.45 ± 0.08 16.39 ± 0.29 138.02 ± 10.96
ST, C 5.86 ± 0.08 17.14 ± 0.29 148.37 ± 10.96
UT, A 5.27 ± 0.08 17.67 ± 0.29 139.00 ± 10.96
UT, B 5.43 ± 0.08 15.51 ± 0.29 121.71 ± 10.96
UT, C 5.52 ± 0.08 16.64 ± 0.29 117.61 ± 10.96
VG, A 5.45 ± 0.08 17.22 ± 0.29 128.89 ± 10.96
VG, B 5.43 ± 0.08 16.50 ± 0.29 128.06 ± 10.96
VG, C 5.75 ± 0.08 17.12 ± 0.29 143.15 ± 10.96
ST: starch added, UT: untreated, VG: vital gluten added.
Di erent small letters indicate that evaluated attributes in each column are signi cantly di erent from each other when compared
within each group by LSD test, P < 0.05.
Determination of the bread-making quality of  ours using an automatic bread machine
614
Table 5. Comparison of bread properties by bread-making test method.
Bread property Flour
(UT)
Bread-making test method
Hearth bread Automatic bread machine
(mean of 3 di erent machines)
Speci c volume
(mL g–1)
F16.27 ± 0.15a 5.99 ± 0.04a
F25.48 ± 0.15b 4.94 ± 0.04b
F36.43 ± 0.15a 5.55 ± 0.04c
Baking loss
(%)
F123.41 ± 036a 17.11 ± 0.17a
F221.78 ± 036b 17.15 ± 0.17a
F323.62 ± 036a 16.20 ± 0.17b
Firmness
(g)
F1174.16 ± 19.4b 91.22 ± 6.33b
F2259.44 ± 19.4a 157.58 ± 6.33a
F3180.28 ± 19.4b 154.98 ± 6.33b
Di erent small letters indicate that evaluated attributes in each column are signi cantly di erent from each other when compared
within each group by LSD test, P < 0.05.
Table 6. Crumb and crust attributes of hearth bread samples.
Crumb form factor Crumb proportion Crust color Crumb color
(L value) Hue (L value) Hue
Mean ± SE Mean ± SE Mean ± SE Mean ± SE Mean ± SE Mean ± SE
Flour
F10.522 ± 0.011 0.124 ± 0.007b 33.56 ± 2.69b 1.06 ± 0.03 86.70 ± 0.34a –0.86 ± 0.4b
F20.511 ± 0.011 0.164 ± 0.007a 48.44 ± 2.69a 1.17 ± 0.03 84.50 ± 0.34c 1.55 ± 0.4a
F30.488 ± 0.011 0.132 ± 0.007b 34.92 ± 2.69b 1.13 ± 0.03 85.65 ± 0.34b 0.86 ± 0.4a
Variation
ST 0.507 ± 0.011 0.154 ± 0.007a 36.36 ± 2.69 1.09 ± 0.03 86.67 ± 0.34b 0.51 ± 0.4
UT 0.516 ± 0.011 0.152 ± 0.007a 37.63 ± 2.69 1.13 ± 0.03 85.35 ± 0.34b 0.51 ± 0.4
VG 0.499 ± 0.011 0.113 ± 0.007b 42.93 ± 2.69 1.14 ± 0.03 84.82 ± 0.34b 0.51 ± 0.4
Flour × variation
F1, ST 0.529 ± 0.019 0.128 ± 0.013 27.80 ± 4.67 0.94 ± 0.06 86.70 ± 0.60 –1.55 ± 0.69
F1, UT 0.542 ± 0.019 0.134 ± 0.013 36.38 ± 4.67 1.12 ± 0.06 86.99 ± 0.60 –0.52 ± 0.69
F1, VG 0.495 ± 0.019 0.112 ± 0.013 36.50 ± 4.67 1.11 ± 0.06 84.82 ± 0.60 0.52 ± 0.69
F2, ST 0.506 ± 0.019 0.179 ± 0.013 45.78 ± 4.67 1.17 ± 0.06 85.96 ± 0.60 1.55 ± 0.69
F2, UT 0.517 ± 0.019 0.188 ± 0.013 43.64 ± 4.67 1.14 ± 0.06 84.15 ± 0.60 1.54 ± 0.69
F2, VG 0.511 ± 0.019 0.124 ± 0.013 55.91 ± 4.67 1.20 ± 0.06 83.40 ± 0.60 1.56 ± 0.69
F3, ST 0.485 ± 0.019 0.156 ± 0.013 35.50 ± 4.67 1.16 ± 0.06 87.35 ± 0.60 1.55 ± 0.69
F3, UT 0.491 ± 0.019 0.136 ± 0.013 32.87 ± 4.67 1.11 ± 0.06 84.93 ± 0.60 0.52 ± 0.69
F3, VG 0.490 ± 0.019 0.105 ± 0.013 36.38 ± 4.67 1.11 ± 0.06 84.66 ± 0.60 0.51 ± 0.69
ST: starch added, UT: untreated, VG: vital gluten added
Form factor: pore roundness; proportion: the ratio of pore to total area.
Di erent small letters indicate that evaluated attributes in each column are signi cantly di erent from each other when compared
within each group by LSD test, P < 0.05.
İ. S. DOĞAN, Ö. YILDIZ, B. TAŞAN
615
Table 7. Crumb and crust attributes of machine bread samples.
Crumb form factor Crumb proportion Crust color Crumb color
(L value) Hue (L value) Hue
Mean ± SE Mean ± SE Mean ± SE Mean ± SE Mean ± SE Mean ± SE
Flour
F10.490 ± 0.006a 0.249 ± 0.012c 77.94 ± 0.66a 1.34 ± 0.01c 82.60 ± 0.3a –1.41 ± 0.2c
F20.445 ± 0.006b 0.417 ± 0.012a 74.98 ± 0.66b 1.41 ± 0.01a 77.82 ± 0.3c 0.86 ± 0.2a
F30.456 ± 0.006b 0.326 ± 0.012b 78.61 ± 0.66a 1.37 ± 0.01b 80.51 ± 0.3b 0.06 ± 0.2b
Variation
ST 0.461 ± 0.006 0.352 ± 0.012 75.69 ± 0.66a 1.35 ± 0.01 79.71 ± 0.3b 1.18 ± 0.2
UT 0.465 ± 0.006 0.314 ± 0.012 75.16 ± 0.66b 1.35 ± 0.01 80.42 ± 0.3ab –0.40 ± 0.2
VG 0.465 ± 0.006 0.325 ± 0.012 80.69 ± 0.66b 1.41 ± 0.01 80.81 ± 0.3a -0.28 ± 0.2
Machine
A 0.452 ± 0.006 0.356 ± 0.012a 75.44 ± 0.66b 1.38 ± 0.01 79.64 ± 0.3b 0.18 ± 0.2
B 0.467 ± 0.006 0.333 ± 0.012ab 80.93 ± 0.66a 1.42 ± 0.01 80.17 ± 0.3b –0.51 ± 0.2
C 0.472 ± 0.006 0.303 ± 0.012b 75.16 ± 0.66b 1.32 ± 0.01 81.13 ± 0.3a -0.16 ± 0.2
Flour × variation
F1, ST 0.453 ± 0.011 0.289 ± 0.020 83.06 ± 1.14 1.31 ± 0.02 81.19 ± 0.52 –1.54 ± 0.35c
F1, UT 0438 ± 0.011 0.223 ± 0.020 78.50 ± 1.14 1.33 ± 0.02 77.90 ± 0.52 –1.18 ± 0.35c
F1, VG 0.503 ± 0.011 0.234 ± 0.020 80.49 ± 1.14 1.38 ± 0.02 83.34 ± 0.52 –1.52 ± 0.35c
F2, ST 0.464 ± 0.011 0.415 ± 0.020 75.84 ± 1.14 1.39 ± 0.02 80.80 ± 0.52 0.86 ± 0.35ab
F2, UT 0.444 ± 0.011 0.410 ± 0.020 71.60 ± 1.14 1.39 ± 0.02 77.60 ± 0.52 1.21 ± 0.35a
F2, VG 0.488 ± 0.011 0.426 ± 0.020 78.04 ± 1.14 1.43 ± 0.02 82.85 ± 0.52 0.52 ± 0.35ab
F3, ST 0.451 ± 0.011 0.351 ± 0.020 76.92 ± 1.14 1.34 ± 0.02 79.55 ± 0.52 1.22 ± 0.35a
F3, UT 0.451 ± 0.011 0.310 ± 0.020 74.84 ± 1.14 1.33 ± 0.02 77.96 ± 0.52 –1.22 ± 0.35c
F3, VG 0.481 ± 0.011 0.317 ± 0.020 75.30 ± 1.14 1.43 ± 0.02 81.63 ± 0.52 0.18 ± 0.35b
Flour × machine
F1, A 0.479 ± 0.011 0.221 ± 0.020f 77.43 ± 1.14 1.32 ± 0.02 82.94 ± 0.52 –1.18 ± 0.35
F1, B 0.482 ± 0.011 0.280 ± 0.020de 82.98 ± 1.14 1.42 ± 0.02 81.30 ± 0.52 –1.53 ± 0.35
F1, C 0.510 ± 0.011 0.245 ± 0.020ef 73.42 ± 1.14 1.27 ± 0.02 83.57 ± 0.52 –1.53 ± 0.35
F2, A 0.430 ± 0.011 0.478 ± 0.020a 68.66 ± 1.14 1.45 ± 0.02 76.83 ± 0.52 1.55 ± 0.35
F2, B 0.456 ± 0.011 0.405 ± 0.020b 79.09 ± 1.14 1.41 ± 0.02 78.03 ± 0.52 0.17 ± 0.35
F2, C 0.448 ± 0.011 0.369 ± 0.020bc 77.19 ± 1.14 1.35 ± 0.02 78.59 ± 0.52 0.86 ± 0.35
F3, A 0.448 ± 0.011 0.369 ± 0.020bc 80.23 ± 1.14 1.36 ± 0.02 79.16 ± 0.52 0.17 ± 0.35
F3, B 0.462 ± 0.011 0.314 ± 0.020cd 80.72 ± 1.14 1.41 ± 0.02 81.16 ± 0.52 –0.17 ± 0.35
F3, C 0.458 ± 0.011 0.294 ± 0.020de 74.87 ± 1.14 1.33 ± 0.02 81.21 ± 0.52 0.18 ± 0.35
Variation × machine
ST, A 0.454 ± 0.011 0.376 ± 0.020 73.31 ± 1.14 1.40 ± 0.02 79.88 ± 0.52 0.53 ± 0.35
ST, B 0.470 ± 0.011 0.350 ± 0.020 79.74 ± 1.14 1.48 ± 0.02 80.81 ± 0.52 –0.16 ± 0.35
ST, C 0.459 ± 0.011 0.329 ± 0.020 74.01 ± 1.14 1.35 ± 0.02 81.73 ± 0.52 0.17 ± 0.35
UT, A 0.451 ± 0.011 0.329 ± 0.020 74.83 ± 1.14 1.36 ± 0.02 80.27 ± 0.52 –0.17 ± 0.35
UT, B 0.476 ± 0.011 0.320 ± 0.020 77.68 ± 1.14 1.39 ± 0.02 80.04 ± 0.52 –0.51 ± 0.35
UT, C 0.469 ± 0.011 0.294 ± 0.020 72.96 ± 1.14 1.30 ± 0.02 80.93 ± 0.52 –0.50 ± 0.35
VG, A 0.451 ± 0.011 0.376 ± 0.020 73.31 ± 1.14 1.38 ± 0.02 78.78 ± 0.52 0.53 ± 0.35
VG, B 0.454 ± 0.011 0.350 ± 0.020 79.74 ± 1.14 1.37 ± 0.02 79.64 ± 0.52 –0.16 ± 0.35
VG, C 0.489 ± 0.011 0.329 ± 0.020 74.01 ± 1.14 1.29 ± 0.02 80.71 ± 0.52 0.17 ± 0.35
ST: starch added, UT: untreated, VG: vital gluten added
Di erent small letters indicate that evaluated attributes in each column are signi cantly di erent from each other when compared
within each group by LSD test, P < 0.05.
Determination of the bread-making quality of  ours using an automatic bread machine
616
the form factor of hearth bread crumb grain were
insigni cant (P > 0.05).
e highest form factor was obtained from F1
and the e ects of  our sources on the form factor
of machine bread crumb grain were signi cant (P
< 0.001). In both baking methods, the average and
highest form factors were obtained from F1 (0.52 for
hearth bread and 0.49 for machine bread).  e results
are shown in Table 7.
Grain-to-total area ratio (proportion)
e our source and variations signi cantly a ected
the proportions of hearth bread (P < 0.01).  e highest
proportion was observed when F2 was used (Table 6).
e interaction between  our and protein was not
signi cant (P > 0.05). Higher proportions indicated
an increase in crumb gas cells in the evaluated crumb
region.
e e ects of  our sources and machines on
proportion are shown in Table 7.  e average
proportion v alues of machine bread made from F1,
F2, and F3 were 0.249, 0.417, and 0.326, respectively,
and were signi cantly di erent from each other (P <
0.001).
Crust color
e crust color of bread a ects consumer preference
at the point of purchase and serves as an indicator of
well-baked bread (Zanoni et al. 1995).  e average
L and hue values of crust color of bread samples
obtained from di erent  our sources and variations
are given in Tables 6 and 7.
e L values of hearth bread crust varied between
33.6 and 48.4, and a signi cant di erence was found
only among  our sources. Hue values of crust
were not signi cantly a ected by  our sources and
variations.
e crust L and hue values of machine bread were
also signi cantly a ected by  our source, variation,
and the machine used in the experiment (P < 0.001).
e average L values of machine bread ranged
between 75.16 and 80.93.  e highest L value, the
lightest color, was obtained with machine B (Table 7).
e average L values of bread made from each  our
source were di erent from each other (P < 0.05),
but the interval was narrow, ranging from 74.98 to
78.61. Hue values were signi cantly a ected by  our
sources, variations, and bread machines (P < 0.001).
ST UT VG
ST UT VG ST UT VG ST UT VG
Machine A Machine B Machine C
Hearth (French) bread
F3
F2
F1
F3
F2
F1
Figure. Cross cut of experimental bread samples (ST: starch added, UT: untreated, VG:
vital gluten added).
İ. S. DOĞAN, Ö. YILDIZ, B. TAŞAN
617
Crumb color
e crumb L and hue values of hearth bread were
signi cantly a ected by  our source and variation (P
< 0.001).  e average L values of hearth bread ranged
between 84.50 and 86.70 (Tables 6 and 7). Crumb
color was a ected by the addition of starch and vital
gluten to the  ours. e our source also signi cantly
a ected the crumb hue values (P < 0.01)
Although the values are very close to each other
(Table 7), the crumb L values of machine bread were
signi cantly a ected by all  our sources (P < 0.001),
machines (P < 0.01), machine and  our interactions
(P < 0.05), and the interaction of machine,  our, and
variations (P < 0.05), as shown in the Figure. Crumb
hue values were also signi cantly a ected by  our
source (P < 0.001),  our and protein interactions
(P < 0.001), and machine,  our, and variations
interactions (P < 0.05).
Discussion
e addition of 12% starch to the experimental  our
samples weakened the gluten strength so that the
mixing stability decreased, whereas adding 2% extra
vital gluten increased the stability.
One of the most important criteria used in
determining the quality of  our is to determine the
volume of the bread. We observed in this study that
a higher protein content yielded either tight dough
or resulted in less breakage or shredding at the point
of scoring, yielding lower volume and inferior crumb
features. A hearth bread process is more di cult
than pan bread production; therefore, sometimes it is
di cult to see the e ect of small variations in protein
content.
Because bread machines have better control of
the baking process, the e ects of  our combination
on bread volume were observable.  e signi cant
interactions between machine and  our indicate that
the performances of bread machines di er depending
on their design and programming. However, all
machines showed similar tendencies in relation to
the  our source used in the experiment.
e relationship between the protein content of
our and the volume of bread has been known for
many years and is used in quality bread production
with new wheat varieties (Unal and Boyacioglu 1984).
Færgestad et al. (1999) prepared 12 mixtures from 4
di erent  our samples in variations of 10.2%-14.3%
and a very important relationship between bread
volume and variation was found. More than the
total variation, the importance of gluten quality on
bread volume was highlighted in this study.  e ideal
gluten quantity and quality is not the same in the
production of hearth, whole wheat, and pan breads.
Baking losses changed between 21.78% and
23.62% for hearth bread, and between 15.39% and
17.93% for machine bread.  e type of baking pans
and machine design contributed to the alteration in
baking loss. In comparison to hearth bread, baking
loss in machine bread is less than about 5%-7% as
a consequence of the controlled baking in bread
machines, and variation in baking loss between the
machines was 1%-2% (Table 4).
Even though the proportion of crumb with gas
cells was di erent for hearth and machine breads,
the magnitude and direction of di erence for the
ratio were similar. Coalescence of gas cells and bigger
grain formation in hearth bread probably caused a
lower proportion rate. Crumb grain structure and
grain distribution throughout the bread is important
for sensory evaluation. Both loaf volume and crumb
grain quality are equally important for the overall
quality. For crumb grain evaluation, 2-dimensional
digital image analyses, crumb grain size and
distribution analyses, magnetic resonance imaging,
and Monte Carlo simulation techniques may be also
used (Regier et al. 2007).
e crust L values of bread made from di erent
ours in both methods were signi cantly di erent.
e temperature of the baking chamber in the
bread machine was about 70 °C lower than the oven
temperature and the moisture removal rate was also
lower due to a closed top cover.  erefore, the top
crust color of machine bread was lighter than that of
hearth bread.
Even though no signi cant di erences exist
among the hearth bread data, the obtained average
data are similar to those of machine breads.  e oven
temperature during bread machine production is
completely controlled.  e smaller color di erences
between assessments make the di erence important
due to a smaller standard error of average results of
color L and hue values from bread machines.
Determination of the bread-making quality of  ours using an automatic bread machine
618
e e ect of protein levels (variation) on the
rmness values of both hearth and machine bread
was statistically insigni cant (P > 0.05).  e  our
sources signi cantly a ected crumb  rmness in both
baking methods, with F1 yielding the so est crumb
and F2 yielding the hardest crumb. Because of the
nature of hearth bread, the compressibility values
of hearth bread were higher than those of machine
bread, as seen in most pan breads due to variations in
baking methods (Tables 3 and 4).
e crumb L values in both hearth and machine
bread were the highest for F1 and the lowest for F2,
with F3 in the middle, and we observed the e ect of
our source and variations in both baking methods.
e e ect of  our sources on crumb hue values was
observed to have similar tendencies in both methods.
However, the level of signi cance was not the same
due to the di erence of baking methods. Hue value
provides information about the intensity of the color.
A lower hue value means the color is darker.
One important factor is that the speci c volumes
of breads produced by both methods changed
depending on  our source.  e amount of protein
signi cantly a ected the machine bread volume, but
changing the protein level (variation) did not a ect
the volume of the hearth bread.  e bread machine
production was more controlled. Changes in the
quantity of protein were re ected in the speci c
volumes of the bread. Furthermore, the signi cance of
bread machine and  our source interaction indicates
that the performances of the bread machines are not
the same.  is di erence in performance may be
caused by the heterogeneity of the machines’ baking
programs. In addition, crumb  rmness and crust and
crumb color of bread made with both methods were
signi cantly a ected by  our sources in the same way
but not at the same level of signi cance. Considering
the repeatability of the results, it can be concluded
that the bread-making potential of  our can be
achieved by using a bread machine.  e performance
of bakery additives can also be assessed with a bread
machine without professional experience in the  eld.
Acknowledgments
e authors would like to thank TÜBİTAK (107O61)
and Yüzüncü Yıl University (2007-FBE-YL94) for
providing  nancial support.
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In this study, an automation system is designed for bakeries, biscuit factories, flour and bakery products used dough kneading and dosing machines. This microprocessor-based design, made of 5-flowing flour and water dispensing operation. For this, the area is very easy to become available and can be programmed PIC16F877A microcontroller used. This automation system isn't used in most of the plants and mixing ratios. Therefore the operator's ability and speed very important for mixing ratios and the production rate without automation system. This is quite a challenge, raw material and leads to a loss of time. This study, carried out the difficulties that emerged from the automation system can be provided at low cost and hassle-free.
Thesis
The traditional bread "khobz eddar" is an important food for the Algerian population, due to the fact that it is a homemade product produced using natural ingredients. Developing this product with gluten-free ingredients for celiac patients is a challenge that deserves to be investigated. The aim of this study was to develop a natural gluten-free product for Algerian celiac patients based on the traditional "khobz eddar" bread flow diagram. Hydro-thermal treatment, starches (tapioca and corn) and hydrocolloїds (agar-agar, carob gum and arabic gum) as well as Moringa leaves and pomegranate seed powder are studied for their improving potential of the physical, sensory and nutritional characteristics of gluten-free "khobz eddar" bread type. The household’s survey in the commune of Constantine allowed to establish the flow diagram of the targeted bread. The response surface methodology optimized gluten-free production based on a rice/Fieldbeans and corn/Fieldbeans formula, improved by a treated rice and treated corn, respectively. The results showed a better volume and hardness of corn-based bread compared to that of rice. On the other hand, the sensory results depicted a better appreciation of rice-based bread than that of corn. The approach through a definitive screening design was used to locate the effect of starch/hydrocolloids interactions on the technological quality of gluten-free bread based on the rice/Fieldbeans formula. The effect of additive interactions has been reported and optimum bread has been technologically and sensorly characterized. The results show that gum arabic has an improving effect on all the quality parameters. Two types of plant ingredients were used to enrich gluten-free bread, pomegranate seed powder and Moringa leaf powder, with different levels (0, 2.5, 5, 7.5, 10% w/w). The technological and sensory quality was evaluated. The assay of total polyphenols and the determination of antioxidant activity by different methods were performed. The results reported optimums with additions of 7.5% of the pomegranate seed powder and 2.5% of the Moringa leaf powder. The results obtained in the different parts of this study are of high interest and deserve to be developed and a complementary work has been done in order to diversify the gluten-free formulation. Combinations between improvers were carried out, three types of formulations were proposed: a first combination of treated rice and different levels of gum arabic (0.5, 1 and 1.5%), a second one with treated rice combined with three levels of the Pomegranate seed powder (2.5, 5 and 7.5%) and a third one between processed rice and three levels of Moringa leaf powder (2.5, 5 and 7.5%). The main results indicate that for all combinations, the specific volume increased significantly (p < 0.05) compared to optimum breads with single improvers and gluten-free control bread. The best results for texture parameters are thus obtained with gluten-free breads made by incorporating improvers in combination. The best combination between improvers is obtained with treated rice and 1.5% of arabic gum, then comes the combination of rice treated with 5% of the seed powder of pomegranates and finally the combination of rice treated with 2.5 % of the powder from Moringa leaves.
Article
A modified American Association of Cereal Chemists (AACC) parameter for white bread crumb, CFV20, was established using a 20-mm-diameter plunger, and represents an interchangeable parameter to compression force values (CFV) used in the AACC method. The relationship between CFV and storage days was expressed by a 2nd order polynomial equation. Using this equation, the storage days at maximum CFV was around 4 days at 5°C. In addition, mouthfeel firmness was evaluated by 20-year-old participants, and also showed a maximum score at around 4 storage days. Moreover, CFV20 reflected not only mouthfeel firmness but also tactile sensory score, resulting in a good parameter describing sensory white bread crumb firmness, and is interchangeable with CFV of the AACC method, evidenced by the high correlation between CFV20 and CFV of the AACC method.
Article
The applicability of household baking machines for test baking in small cereal laboratories was investigated. Repeatability and reproducibility of four baking machines (Funai FAB-100) were evaluated. Factorial analysis was applied to bread weight, height and loaf specific volume. No variation among the machines and within the individual machines was found, but small variations among different lots of flour could be detected. The machines can be of good use for evaluation of flour quality if there is a demand for homogeneous flour quality in bakeries without a test baker.
Article
Hearth bread was made from 12 blends of four flours, which varied in protein content (10·2–14·3%) and protein quality, by a straight dough baking procedure. Doughs were mixed using a Farinograph operated at 63 rpm for variable mixing times (5–25 min), and proof times were also varied (35–60 min). Loaf volume was strongly positively related to protein content (r=0·95), Farinograph dough development time (FDT) (r=0·88) and Farinograph dough stability (FDS) (r=−0·97), but not to Zeleny sedimentation volume, SDS sedimentation volume or Mixograph peak time (MPT). Similar observations were found for the form ratio of loaves. The positive relationships between protein content on the one hand and loaf volume and form ratio on the other were only observed at medium (15 min) and long (25 min) mixing times, but not after a short mixing time (5 min). Furthermore, loaf characteristics were strongly affected by the process parameters, giving independent effects on loaf volume vs. form ratio.
Article
Structural and transport properties of extruded snacks as well as a bread sample were characterised by a 2D scanner image and 3D magnetic resonance imaging data-analysis. The algorithms were able to determine pore size distributions as well as surface to volume ratios. The results for 2D and 3D were compared and strengths and weaknesses discussed. Additionally by a Monte Carlo simulation the connectivity of the pore space was accessible.
Article
A mathematical model was set up to predict browning kinetics of bread crust during baking. A bread dough was placed into a cylindrical steel mould and baked in a pilot forced-convection oven at 200 and 250°C. The sample surface temperature was measured using both a type J thermocouple and an infrared thermometer. Surface browning (ΔE) of bread crust during baking was measured by a tristimulus colorimeter. The kinetic model for bread crust browning was obtained by instant heating of dried crumb on contact with a refractory plate at 140, 150, 165, 185, 210, 235 and 250°C. At all temperatures ΔE tended asymptotically to ΔE∞ = 52, which corresponded to the burnt sample. The colour difference varies as a function of first-order kinetics. The rate constant k depends on temperature according to the Arrhenius equation (ko = 42,000 s−1; Ea = 64,151 J/mol). Kinetics was validated under dynamic temperature conditions: the experimental results were compared with those obtained from a mathematical model for heat and mass transfer during baking connected to the kinetic model for browning.
Conditions and problems of bakery plants in Van Province
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Doğan İS (1997) Conditions and problems of bakery plants in Van Province. Technol Flour Prod 6: 22-31.
A new approach of measuring colours in biscuit as quality criteria
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