Effect of quinoa flour on gluten-free bread batter rheology and bread quality

Effect of quinoa flour on gluten-free bread batter rheology and bread quality

Journal of Cereal Science 69 (2016) 174e181 Contents lists available at ScienceDirect Journal of Cereal Science journal homepage: www.elsevier.com/l...

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Journal of Cereal Science 69 (2016) 174e181

Contents lists available at ScienceDirect

Journal of Cereal Science journal homepage: www.elsevier.com/locate/jcs

Effect of quinoa flour on gluten-free bread batter rheology and bread quality Gulsum M. Turkut a, Hulya Cakmak a, Seher Kumcuoglu b, Sebnem Tavman b, * a b

Ege University, Graduate School of Natural and Applied Sciences, Department of Food Engineering, 35100, Bornova Izmir, Turkey Ege University, Faculty of Engineering, Department of Food Engineering, 35100, Bornova Izmir, Turkey

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 July 2015 Received in revised form 4 March 2016 Accepted 5 March 2016 Available online 8 March 2016

A new gluten-free bread formulations composed of quinoa, buckwheat, rice flour and potato starch were developed in the present study. Rheological characteristics of the bread batter with increasing amount of quinoa were determined; storage (G0 ) and loss modulus (G00 ) values were also measured for investigation of viscoelastic properties. To evaluate the quality of breads; technological and physical (bake loss %, specific volume, texture, microstructure, color), chemical (protein, moisture, ash) and sensory properties were determined. All batter formulations independent of the quinoa amount exhibited pseudoplastic behavior, and G0 values were found to be higher than G00 values in expressing the solid like characteristics of the batter. Amount of quinoa flour addition did not present significant difference on bake loss%, specific volume and protein content (p>0.05); however, 25% quinoa flour bread displayed better results with its higher sensory scores and softer texture. Quinoa and buckwheat flour mixture therefore will be a good alternative for conventional gluten-free bread formulations. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Quinoa Buckwheat Gluten-free Rheology

1. Introduction Prolamins in wheat, rye and barley are major sources for creating digestive problems in people with celiac disease (Capriles ^as, 2014). Nowadays, the treatment of this disease is only and Are possible by avoiding gluten in the daily diet. Gluten sensitivity ^as, represents the majority of food intolerance (Capriles and Are 2014), and the production of bread without gluten, is therefore essential. There are many conventional gluten-free bread recipes; however, the current technology of gluten-free bakery products is based only on starches from different botanical origins, such as corn and rice (Pruska-Kedzior et al., 2008). Unfortunately, those glutenfree products often have poor quality; lower loaf volume, poor texture (chalky and crumbly) and poor mouthfeel due to the lack of gluten elasticity and low nutritional value. Quality and shelf life of gluten-free breads can be improved by using pseudo-cereals such

Abbreviations: a, (þa: redness and a: greenness); b, (þb: yellowness and b: blueness); G0 , storage modulus; G00 , loss modulus; K, consistency index (Pa.sn); L, brightness (0: black, 100: white); n, power-law index; R2, coefficient of determination; RMSE, root mean square error; g, shear rate (s1); h0, plastic viscosity (Pa.s); t, shear stress (Pa); t0, yield stress (Pa). * Corresponding author. E-mail address: [email protected] (H. Cakmak). http://dx.doi.org/10.1016/j.jcs.2016.03.005 0733-5210/© 2016 Elsevier Ltd. All rights reserved.

as quinoa, buckwheat and amaranth with their nutritional value and the techno-functional properties (Torbica et al., 2010; ^as, 2014). Wronkowska et al., 2013; Capriles and Are Quinoa (Chenopodium quinoa) is an endemic crop of the Andean region (Stikic et al., 2012; Nascimento et al., 2014; Iglesias-Puig et al., 2015). It has been recognized as a very nutritious grain, due to the good quality and quantity of its protein and essential fatty acids (Hager, 2013). Essential amino acid content has also been found to be higher than that of wheat flour (Stikic et al., 2012); especially, lysine (a limiting amino acid for cereals) was found to be twice higher than wheat flour. According to the USDA nutrient database (2014), quinoa consists of 14.12% protein, 6.07% total lipid (fat), 64.16% carbohydrate and 7% dietary fiber. NASA declared that quinoa is an excellent crop with its good nutritional balance and that it can be used during long term human space missions (Schlick and Bubenheim, 1993). Clinical studies about the consumption of quinoa have indicated that childhood malnutrition and risk of cardiovascular diseases (by lowering triglycerides, LDL and cholesterol) may be reduced and help to modulate metabolic parameters (postmenopausal symptoms) in women with excess weight (Graf et al., 2015). In addition to good nutritional composition, quinoa does not contain any gluten, which has brought a new perspective to gluten-free bakery products. Buckwheat (Fagopyrum esculentum) is another pseudo-cereal

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crop that attracts attention with its nutritional composition, since it contains 13.25% protein, 3.4% total lipid (fat), 71.50% carbohydrate, and 10% dietary fiber (USDA, 2014), as well as essential vitamins _ lu, 2015). Studies have shown that and minerals (Bilgiçli and Ibano g antioxidant capacity and amount of aroma compounds were improved in buckwheat bread compared to wheat flour bread (Lin et al., 2008). Replacement of wheat flour with an increasing amount of buckwheat flour also increased the mineral content of breads; Cu, Fe, K, Mg, Mn, P and Zn were statistically higher than in the _ lu, 2015). control sample (Bilgiçli and Ibano g The aim of this study was to develop a new gluten-free bread formulation from different amounts of quinoa and buckwheat flour incorporated into rice flour and potato starch mixture. The effects of quinoa and buckwheat flour were evaluated by means of rheological properties of bread batter as well as technological, physical, and sensory properties of gluten-free breads. 2. Materials and methods

Table 1 Bread formulations, flour composition, flour and bread properties, A: Gluten-free bread formulations for 100 g of total flour þ starch basis; B: composition and water absorption capacities of flours; C: baking properties of gluten-free breads. A Sample code Ingredients (On flour þ starch %)






Rice flour Potato starch Quinoa flour Buckwheat flour Salt Sugar Oil Yeast Xanthan gum Water

25 25 e 50 2 3 6 3 0.5 87

25 25 12.5 37.5 2 3 6 3 0.5 87

25 25 25 25 2 3 6 3 0.5 87

25 25 37.5 12.5 2 3 6 3 0.5 87

25 25 50 e 2 3 6 3 0.5 87

B Flour type

Moisture Ash1 Protein1 SDF1 IDF1 (%) (%) (%) (%) (%)

TDF1 (%)

Quinoa Buckwheat Rice Potato starch

9.13a 9.95a 16.07c 11.22b

16.48c 119.87c 12.58b 102.67b 4.85a 146.16d e 67.79a

2.1. Materials Whole quinoa seed was purchased from Bora Tarim Urunleri Gida San. Tic. Ltd. (Istanbul, Turkey). Buckwheat seeds (Degirmen Tic., Izmir, Turkey), rice flour (Kenton, Ankara, Turkey), potato starch, sugar, salt, sunflower oil, compressed yeast (Pakmaya, Izmir, Turkey) and xanthan gum (SigmaeAldrich) were purchased from local markets in Izmir. Quinoa and buckwheat seeds were ground in a lab scale hammer mill (Armfield, UK), and then subjected to sieving. Flours having a diameter lower than 0.5 mm were used in the experiments. 2.2. Methods 2.2.1. Preparation of breads Gluten-free bread formulations are given in Table 1A. The formulation was developed according to the study of AlvarezJubete et al. (2010) with some major modifications: rice flour and potato starch were kept constant at 50% of the total flour and starch mixture, and buckwheat flour was replaced with increasing amounts of quinoa flour. The control bread (C) was composed of only buckwheat flour, rice flour and potato starch. The amount of water used in the formulations was kept constant at 87% (on flour mixture basis) as recommended in the study of Alvarez-Jubete et al. (2010) and the structure of obtained mixtures were like a thick batter rather than dough. For the batter preparation, all ingredients except xanthan gum were mixed thoroughly for 10 min at low speed in a spiral mixer (Kitchen Aid 5k45 Mixer, USA). After the addition of xanthan gum, the batter was mixed for another 5 min at high speed. The batter was then divided into 400 g portions and poured into Teflon-coated baking pans. Finally, it was fermented in the fermentation chamber (Inoksan FGM 100, Turkey) at 35  C and 85% RH for 30 min. Following the fermentation step, the samples were baked at 200  C and 50% RH for 50 min in a convection oven (Inoksan FBE 010, Turkey). The bread was removed from the pans immediately after baking and cooled at room temperature (25  C) for at least 6 h before the analyses. 2.3. Rheological measurements Rheological measurements were conducted using a DHR3 rheometer (TA Instruments, USA). Bread batter were prepared according to the formulations given in Table 1A without adding any yeast to the formulations as recommended in the study of


2.35b 2.21b 0.55a 0.51a

15.54c 14.72b 7.07a e

2.09b 1.74a 1.49a e

14.39b 10.84b 3.39a e

Water absorption capacity (%)

C Sample code

Bake loss (%)

Specific volume (cm3/g)

Moisture (%)

Protein1 (%)

Ash1 (%)

Water activity

C Q1 Q2 Q3 Q4

14.4a 15.4a 15.1a 15.1a 15.4a

1.87a 1.85a 1.76a 1.78a 1.73a

47.5c 44.3b 44.4b 41.2a 40.9a

7.65a 7.81a 8.40a 8.17a 8.18a

1.68a 1.36a 2.33a 2.16a 2.06a

0.940c 0.930c 0.930c 0.925a,b 0.910a


Different letters in the same column indicate significant differences between means (p < 0.05). 1 On dry basis.

Demirkesen et al. (2010a). All measurements were conducted at 25  C, using parallel plate geometry (40 mm diameter, with 1 mm gap). Amplitude sweep analyses were carried out between 103e102% strain to determine linear viscoelastic region of the batter samples. The amplitude sweep test results showed that all bread batter formulations showed a linear region between 0.1 and 10%; therefore, 0.1% strain was selected for frequency sweep tests for determining differences between samples. Frequency sweep experiments were carried out between a frequency of 0.1e10 Hz, and storage (G0 ) and loss modulus (G00 ) versus frequency values were recorded. Flow ramp tests were conducted at shear rate between 0.01 and 50 s1 under steady shear conditions. Bread batter formulations were prepared in two parallels, the rheological experiments were performed in triplicate, and their averages are reported in this study.

2.4. Analysis of flour samples Water absorption capacity and protein content of flour samples were measured according to AACC method no 56-11 and 46-12, respectively (AACC, 2010). Moisture (ICC, 1996), and ash contents (ICC, 1996) of the flour were determined using ICC standard methods. Soluble and insoluble dietary fiber content of the flours was determined by using AOAC method no 991.43 (AOAC, 1998).


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2.5. Analyses of breads 2.5.1. Physical properties of bread Bake loss of breads was determined according to the following formula;

Bake loss ð%Þ ¼ ½ðWbb  Wab Þ=Wbb   100


where Wbb is the weight of the loaf before baking and Wab is the weight of the loaf after baking and cooling (Alvarez-Jubete et al., 2010). Specific volume of the breads was determined by rapeseed displacement method according to AACC method 10-05 (AACC, 2010). Protein contents of breads were determined by AACC method 46-12 (AACC, 2010). Moisture (ICC, 1996) and ash contents (ICC, 1996) of breads were determined according to ICC standard methods. Water activity of the bread samples were measured using a Testo AG 400 measurement device (Lenzkirch, Germany). Data were obtained from the averages of three replicates of each formulation. 2.5.2. Texture of the bread crumbs Texture profile analysis (TPA) of bread crumbs was performed the day after baking using TA-XT 2i model texture analyzer (Stable Micro System Co. Ltd., Surrey, England) equipped with a 30 kg load cell. A cylindrical probe of 36 mm in diameter was attached to the crosshead. The instrument test parameters included: pre-test speed: 2.0 mm/s; crosshead speed: 1 mm/s; post-test speed 5.0 mm/s and compression set to 40%. Bread loaves were sliced into 15 mm thickness and crusts were removed before analysis. Textural quality properties (hardness, springiness, cohesiveness, chewiness, adhesiveness and resilience) of bread slices were measured, but results of adhesiveness and resilience are not shown in the present study. All the tests were conducted in six parallels, and the average values are reported. 2.5.3. Scanning electron microscopy (SEM) images of flours and breads Quanta FEG 250 Scanning Electron Microscope (FEI, Czech Republic) was used to examine flour and crumb structures. Bread crumbs were cut into cubes (1 cm3) and dried in a freeze-drier (Armfield, FT 33, England) for 6 h prior to microscopic analysis. An accelerating voltage of 7 kV and 10 kV was used for flours and breads; system pressures were 80 Pa and 110 Pa for flours and breads, respectively. Those obtained SEM images of flours were evaluated with ImageJ software for determining particle size distribution. 2.5.4. Color analysis The crust and crumb colors were measured using HunterLab ColorFlex (Hunter Associates Inc., Reston, VA, USA). Averages of three measurements of L (brightness; 0: black, 100: white), a (þa: redness; a: greenness) and b (þb: yellowness; b: blueness) values were recorded. 2.5.5. Sensory analysis Sensory analysis was performed with a group of 25 semi-trained panelists, none of them having celiac disease, recruited among the staff, undergraduate and graduate students of Ege University Food Engineering Department. Panelists were asked to assess the glutenfree breads for flavor, crumb hardness, crumb color and overall liking. Each sensory attribute was evaluated with a ranking test with a scale of “1” (the least) to “5” (the most). The sensory analysis was conducted in duplicate.

2.5.6. Statistical analyses Results were analyzed using SPSS software version 20.0. Data were compared using analysis of variance (ANOVA) and the calculated mean values compared using Duncan's multiple range test with a significance level of 95%. Rheological models were tested in Matlab software 7.12.0 (Mathworks Inc., USA) using curvefitting tool box. 3. Results and discussion 3.1. Composition of flours Composition and water absorption capacities of the flours used in this study are presented in Table 1B. These results were in accordance with the literature. Moisture content of quinoa flour was given between 9.97 and 12.62%; ash was between 1.97 and 5.46%; and protein content was between 12.05 and 15.47% € mo €sko €zi et al., 2011; Repo-Carrasco-Valencia and Serna, 2011; (To _ € ste et al., 2014; Bilgiçli and Ibano lu, 2015). For buckwheat flour, Fo g moisture content given in the literature was between 9.72 and 10.60%, ash was between 1.92 and 2.00%, and protein content was between 11.50 and 15.80% (Pruska-Kedzior et al., 2008; Bilgiçli and _ lu, 2015; Wronkowska et al., 2015). Ibano g Soluble and total dietary fiber content of quinoa flour were found significantly higher than buckwheat flour as presented in Table 1B (p < 0.05). Insoluble dietary fiber of quinoa and buckwheat were found statistically in the same group (p > 0.05). Soluble dietary fiber content of raw quinoa seed is given from 1.41 to 2.3% on dry basis, and total dietary fiber is given from 13.40 to 15.99% on dry basis in the literature (Ruales and Nair, 1994; Repo-CarrascoValencia and Serna, 2011). For buckwheat seeds, soluble dietary fiber is given as 2.21% (He˛ s et al., 2014), and total dietary fiber is der et al., 2010). between 12.18 and 13.05% on dry basis (Le Water absorption capacity of flour is related with protein (Ogungbenle, 2003) and fiber content (Torbica et al., 2010). Quinoa having higher soluble dietary fiber than buckwheat flour then gradually increased the water absorption capacity of bread batter by replacement of buckwheat with quinoa flour. Quinoa with its dietary fiber content is used to improve the structure of highly viscous food products such as dough and bakery products (Ogungbenle, 2003). 3.2. Rheological properties of bread batter Fig. 1 represents the effect of quinoa flour supplementation on gluten-free bread batter rheology at constant water level without yeast addition. Shear stress (Pa) versus shear rate (s1) data was fitted to power law (Eq. (2)), HerscheleBulkley (Eq. (3)), and Bingham model (Eq. (4)) as given in the following equations;

t ¼ KðgÞn


t ¼ KðgÞn þ t0


t ¼ t0 þ h0 g


where t indicates shear stress (Pa), g indicates shear rate (s1), K is the consistency index (Pa.sn), n is the power-law index, t0 yield stress (Pa) and h0 represents plastic viscosity (Pa.s). These rheological models were compared depending on R2 and root mean square error (RMSE), and the higher R2 with lower RMSE showed the best fit among them. The rheological models fitted to experimental data shows a good correlation (R2 ¼ 0.9079e0.9992),

G.M. Turkut et al. / Journal of Cereal Science 69 (2016) 174e181

although power law model presents statistically better results (Table 2). Flow behavior index values of power law model were found between from 0.18 to 0.30, and from 0.19 to 0.47 for Herschel-Bulkley model, therefore all the batter samples displayed shear thinning (pseudoplastic) behavior. Similar results were observed by researchers who studied rheological properties of rice bread dough containing different gums with or without emulsifiers (Demirkesen et al., 2010a) and gluten-free bread dough from corn starch and rice flour, including hydrocolloids (Sabanis and Tzia, 2011). Addition of quinoa flour significantly affected K values and the viscosity. This could be related with the increasing amount of quinoa caused an increase in water absorption capacity of batter by higher soluble dietary fiber fraction than buckwheat as similarly € ste et al. (2014). Increasing amounts of quinoa flour also stated by Fo resulted in a higher consistency index for power law model; on the contrary, increasing quinoa rate resulted in a decrease in K in Herschel-Bulkley model. Yield stress values and plastic viscosity of the batters shown in Herschel-Bulkley and Bingham model also increased with increasing quinoa rate. As stated in the literature, fiber supplementation in the gluten free bread dough influences the resistance to flow by entanglement of fiber and increase the yield stress as well as apparent viscosity (Demirkesen et al., 2010b). Viscoelastic properties of all gluten-free batters are shown in Fig. 1B and C, depending on their frequency sweep responses. Storage (or elastic) modulus, G0 was greater than the loss (or viscous) modulus, G00 , and both increased with increasing frequency for all tested samples. This behavior indicates that those gluten-free batter formulations had a solid like structure. Similar observations have been stated in the literature. The elastic modulus of gluten-free dough prepared with buckwheat, rice and maize flour was greater than loss modulus (Pruska-Kedzior et al., 2008). G0 and G00 values of control sample were smaller than the values of that batters containing quinoa flour at each level. Also increasing amounts of quinoa flour increases elasticity of the bread batter and €ste et al. improves the dough structure in the same way as gluten. Fo (2014) stated that gluten-free dough became more elastic with increasing the amount of quinoa bran at the same frequency range (1e10 Hz). Storage modulus of all formulations increased exponentially (R2 > 0.95), although the incline was sharper for the control sample at lower frequencies (0.1e1.0 Hz). Also, G00 values were found to be exponentially increasing (R2 ¼ 0.82e0.95) for all samples between the studied frequency ranges (1e10 Hz). 3.3. Evaluation of bread properties Baking properties of breads, i.e. percent of bake loss, specific volume, water activity, protein, ash and moisture content are shown in Table 1C. No significant differences were observed in bake loss, specific volume, protein and ash values of breads containing different amounts of quinoa flour (p>0.05). Baking loss was found in accordance with the study of Hager (2013), however the formulation was


rather different, and the gluten-free dough was prepared with a variable amount of water. Moisture of the samples was found between 40.9% and 47.5%. The control sample (C) which includes the highest amount of buckwheat flour, had significantly the highest moisture content, while Q4 bread had the lowest moisture. The moisture content of gluten-free bread significantly decreased with increasing amount of quinoa flour in gluten-free bread (p < 0.05). Alvarez-Jubete et al. (2010) indicated that bread with quinoa flour (50% quinoa flour, 50% rice flour, 87% water) had lower moisture content than buckwheat flour bread (50% buckwheat flour, 50% rice flour, 87% water) similar to our findings. Q4 bread (the highest percent of quinoa) had 40.9% moisture, while the control bread (the highest percent of buckwheat) had 47.5%. This could be attributed to the differences in soluble dietary fiber contents of the buckwheat and quinoa flour. Specific volume is one of the primary quality parameters of bread. Although the negative effect of quinoa and buckwheat flour on the specific volume of bread has been stated in the literature (Torbica et al., 2010; Stikic et al., 2012; Bilgiçli and _ lu, 2015; Iglesias-Puig et al., 2015), there was no significant Ibano g difference (p>0.05) observed between samples containing different amounts of quinoa. Agents such as gums can help to retain gas in a gluten-free dough matrix (Delcour and Hoseney, 2010) and therefore it may help to retain the specific volume similar with the control sample and negative effect of quinoa flour on specific vol€ ste et al. (2014) reported that the ume therefore compensated. Fo replacement of rice and corn flour by 40% whole grain quinoa flour significantly increased bread volume, while addition of the same amount of quinoa bran significantly decreased loaf volume. In addition, Sabanis and Tzia (2011) reported that higher consistency index values and apparent viscosity in their gluten-free dough resulted in lower specific volume. Sample Q4, having higher K value obtained from power law model, had the lowest specific volume among the samples, although the difference was not significant (p>0.05) differing the given literature. Digital images of bread samples are shown in Fig. 2. 3.4. Result of texture analysis The results of texture profile analysis of gluten-free breads are presented in Table 3A. The required force to compress foods between teeth demonstrates hardness since it stimulates the freshness perception of foods (Giannou and Tzia, 2007). Therefore, the bread with 25% quinoa flour which had the lower instrumental hardness value had also the higher sensory flavor score. As stated in Table 3A, the control bread had lower cohesiveness and chewiness. This can be related to the higher moisture content (47.5%) of the control bread. It was also observed that increasing the amount of quinoa flour increased crumb hardness and chewiness. Wronkowska et al. (2013) stated in their study that amount of buckwheat flour significantly affects crumb hardness, because the increasing levels decreased the crumb hardness. For the control sample, which had the highest amount of buckwheat, the crumb texture was not significantly different from Q3 and Q4 breads

Table 2 Statistical results of fitted rheological models. Power law model

HerscheleBulkley model

Bingham model

Sample code














C Q1 Q2 Q3 Q4

117.80 120.60 144.80 181.80 182.60

0.18 0.29 0.29 0.29 0.30

0.9873 0.9943 0.9940 0.9992 0.9981

3.307 4.398 5.996 2.774 4.391

110.90 79.52 78.87 74.36 73.04

0.19 0.35 0.40 0.45 0.47

10.38 49.67 83.99 142.90 148.00

0.9799 0.9952 0.9968 0.9808 0.9958

4.341 4.197 4.519 13.910 6.723

154.90 181.50 223.30 277.90 279.80

2.02 4.07 5.38 6.64 7.17

0.9079 0.9398 0.9504 0.9254 0.9331

9.217 14.780 17.660 27.350 27.860

K; consistency index; n; flow behavior index; t0; yield stress, h0; plastic viscosity.


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Fig. 1. Rheological properties of batters; A: flow curves, B: storage modulus (G0 ), C: loss modulus (G00 ) of batter samples.

Fig. 2. Crumb (A), and crust (B) images of bread slices.

(p>0.05). The effect of buckwheat flour may be suppressed by quinoa flour, that is, breads made with quinoa flour have comparably higher crumb hardness than breads with buckwheat flour, as indicated by other researchers (Alvarez-Jubete et al., 2010). Also, Iglesias-Puig et al. (2015) reported that crumb firmness (hardness) increased when the amount of quinoa in wheat flour þ quinoa flour

mixture rose from 25 g/100 ge50 g/100 g. Crumb springiness values did not considerably change between quinoa breads and the control bread.

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Table 3 Physical and sensorial properties of gluten-free breads, A: Texture profile analysis, B: crumb and crust color, C: Sensory evaluation of gluten-free breads. A Sample code

Crumb hardness (N)

Crumb springiness


C Q1 Q2 Q3 Q4

Crumb cohesiveness


0.81 0.84b 0.84b 0.81a,b 0.79a

24.3 16.4a 18.9a 32.6b 35.0b

Crumb chewiness


5.39a 5.86a 5.77a 9.81b 12.17c

0.41 0.44a.b 0.47b 0.45a,b 0.42a

B Crumb color Sample code C Q1 Q2 Q3 Q4

Crust color







51.4a 56.3b 58.5c 60.9d 65.5e

6.8e 6.6d 6.4c 6.0b 5.5a

10.3a 12.3b 13.8c 15.2d 16.9e

42.9a 44.2b 45.5c 46.4d 47.9e

14.9e 14.8d 14.4c 14.3b 14.2a

15.8a 16.1b 16.2c 16.5d 16.8e

C Sample code C Q1 Q2 Q3 Q4 aee

Flavor a

2.96 3.60a,b 4.24b 2.68a,b 3.48a,b


Crumb color



4.60 3.44b 3.04a,b 2.52a 2.44a

5.60 4.60c 4.00b 3.20a 2.64a

Overall liking 1.20a 2.80b 4.96d 2.48b 3.48c

Different letters in the same column indicate significant differences between means (p < 0.05).

3.5. Scanning electron microscopy (SEM) analysis SEM images of the flour samples used in the production of gluten-free breads are shown in Fig. 3. For comparison of particle size, images with the same magnification level are presented in this figure. The images were evaluated with ImageJ software and at least 50 different particles were measured from three different images for each flour type for calculation of average particle size distribution. As can be seen in this figure, potato starch has the largest particle size, 16.86 ± 4.66 mm, while the smallest particle size was observed for quinoa flour (1.43 ± 0.22 mm). The average particle size of buckwheat flour was found as 4.74 ± 0.88 mm, and for the potato starch it was found as 5.78 ± 1.11 mm. SEM images of gluten-free bread crumbs are shown in Fig. 3. Up to 50% of quinoa flour, starch granules are visible in the structure. Breads with 37.5% and 50% of quinoa flour showed more homogeneous structure than the rest. Especially, less porous, and more sheet-like structure can be seen in the image of bread with 37.5% quinoa flour. The sheet-like structure is attributed to gluten proteins (Fleming and Sosulski, 1978), which can withstand the pressure difference that occurs during baking. However, for gluten-free bread dough, this pressure difference cannot be tolerated and therefore smaller pores occur at the weakest points that are covering starch granules (Fleming and Sosulski, 1978). The smallest particle size distribution of quinoa flour, especially at a higher quinoa flour replacement level, may therefore affect the final porous structure of the Q4 bread.

3.6. Color analysis Bread color is a result of complex chemical reactions between proteins and carbohydrates during the baking process. Moreover, the bread formulation itself could change the final bread color. The effects of quinoa flour on bread color are shown in Table 3B. Crust and crumb color of control and quinoa breads were statistically different (p<0.05), and the amount of quinoa flour created a noticeable difference on all color parameters for both crumb and

crust. Especially, the yellowness of bread crumb was the highest in the highest quinoa replacement due to the characteristic quinoa color. Gluten-free breads are usually identified by having lighter color than wheat breads because of starches and rice flour; thus, darker color in breads is favorable (Wronkowska et al., 2013). Although studies indicate that increasing the amount of both quinoa and buckwheat flour statistically decreased the lightness values of crumb and crust (Alvarez-Jubete et al., 2010; Wronkowska et al., _ lu, 2015), there was no such difference 2013; Bilgiçli and Ibano g observed in the present study. This result could be related to the composition of gluten-free bread, since it contains a constant amount of rice flour and potato starch. 3.7. Sensory evaluation Sensory evaluation of gluten-free bread was performed using a ranking test for different bread quality attributes. The results are presented in Table 3C. Differences in crumb color were clearly perceived by the panelists and these results are in agreement with the instrumental color values, that is, crumb lightness was increased with increasing amount of quinoa. Gluten-free bread with 25% quinoa flour statistically had the highest average score in flavor, and overall liking, while the control sample received the lowest average scores for those quality attributes. The difference in sensory hardness of breads was not clear as the instrumental values, but even so, the similarity in the hardness of Q1 and Q2 breads were perceived by the panelists. Sensory analysis of newly developed gluten-free breads may be conducted with people having celiac disease in future studies for further improvement of these formulations, since their sensory perception might differ from other people. 4. Conclusions Gluten-free bread batter was formulated with rice flour, potato starch and buckwheat flour which were replaced with increasing

180 G.M. Turkut et al. / Journal of Cereal Science 69 (2016) 174e181 Fig. 3. Scanning electron micrographs (10000) of flour samples, A: quinoa, B: buckwheat, C: rice flour, D: potato starch (in the upper row); scanning electron micrographs (2500) of the crumbs of control (C) and quinoa breads (in the lower row).

G.M. Turkut et al. / Journal of Cereal Science 69 (2016) 174e181

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