Food Science and Technology Research
Online ISSN : 1881-3984
Print ISSN : 1344-6606
ISSN-L : 1344-6606
Original papers
Optimization of The Amount of Chickpea Sourdough and Dry Yeast in Wheat Bread Formulation: Evaluation of Physicochemical, Sensory and Antioxidant Properties
Müge Hendek ErtopŞeker İbrahim Tuğkan
Author information

2018 Volume 24 Issue 1 Pages 45-53


The aim of this study was to optimize amounts of chickpea sourdough (A) and instant active dry yeast (B) in bread formulation and to evaluate the potential use of chickpea sourdough in bread production by examining various quality parameters. An experimental design suggested by Response Surface Methodology was used. The bread produced according to the optimized model (OBrd) was compared with control bread (CBrd) in terms of several quality parameters. According to the optimization results, optimum levels of usage were 59.06 g for A and 3.39 g for B. Smaller and more homogeneous pore structures were obtained in bread (OBrd) texture by the use of chickpea sourdough according to the image analysis. The bread also acquired sour, sweetish and acceptable sensory profiles. Physicochemical properties and antioxidant activity were also improved by the use of chickpea sourdough.


The cereals and legumes are an important part of the daily diet and mainly provide nutrients and functional compounds (Coda et al., 2012; Rizzello et al., 2014a). Although legumes have been a component of the dietary customs of many countries for thousands of years, their use and nutritional and functional value have only recently started to be rediscovered and investigated by using suitable techniques (Curiel et al., 2015).

The chickpea is a source of high-quality protein (Gomez et al., 2008) due to its well-balanced amino acid composition and protein bioavailability, with a better content than that of several legume seeds (Roy et al., 2010). The chickpea is rich in Ca, P, Mg,K, vitamin A and amino acid histidine (Jukanti et al., 2012).

The chickpea sourdough has been used in bread production as a traditional leavening agent and to bestow a distinctive sweet flavor and aroma. It is also known as “sweet yeast” or “chickpea yeast,” and is well-known in various Mediterranean and Balkan countries (Pasqualone et al., 2004), but it's traditional method has begun to be forgotten nowadays (Hatzikamari et al., 2007). The chickpea sourdough may also prolong shelf life (Sikili, 2003) and provides functional, nutritional and textural quality to bakery products. In this respect, the usage of chickpea sourdough will satisfy consumers' natural and healthy product expectations as a natural ingredient. The synthesis of microbial metabolites, activation of enzymes, acidification and proteolysis cause various changes during sourdough fermentation, which affect the dough and product. Moreover they also affect enzyme activity, formation of bioactive peptides, level of phenolic acids, antioxidant activity, improve the bioavailability, functional and nutritional quality. Microbial metabolism during sourdough fermentation may also produce new active compounds, such as peptides and amino acid derivatives with various functionalities, so the bioactivity is increased (Gobbetti et al., 2014).

Some previous studies have investigated the addition of peas or chickpea to several bakery products such as chapattis, cakes, biscuits and crackers (Kadam et al., 2012; Hera et al., 2012). However, studies concerning chickpea fermentation or bakery products produced with chickpea sourdough are very limited (Tulbek, 2006; Kefalas et al., 2009). Only few studies regarding the use of chickpea flour in cake (Gomez et al., 2008; Hera et al., 2012) or in breads (Rizzello et al., 2014a) have been reported. In this study, the optimized level of chickpea sourdough and instant active dry yeast in the bread formula was determined in terms of volume (V) and acceptability value (AV), and the effects of chickpea sourdough on bread quality were examined.

Materials and Methods

Material    The wheat flour used for bread production (Cesur Milling Co, Trabzon) had a 14.3% moisture, 0.63% ash, 11.3% protein and 59.2% water absorption. The salt, instant active dry yeast (DrOetker) and chickpea (Cicer arietinum L) cv. Koçbaşı were purchased from a local supermarket. The chemicals used for analysis were supplied by Merck (Germany).

Experimental design and optimization    The amounts of instant active dry yeast and chickpea sourdough were considered as two independent factors and two main responses were Volume (V) and Acceptability values (AV). Response surface methodology (RSM)-Central composite rotatable design (CCRD) desirability function was used for the effect of the two factors on the two responses (Design Expert 7.0.0, Stat-Ease Inc., Minneapolis, USA). The two factors and five replicates at the center point led to a set of 13 experiments. The bread samples were produced according to the experimental design. The V and AV results were evaluated by the software, and optimized results were calculated.

Preparation of chickpea sourdough    The method used traditionally to prepare chickpea sourdough was slightly modified. 100 g chickpea with 100 mL water was soaked for 12 h and then milled with a laboratory blender (Bosch MMR15A1). It was mixed with the same amount of water. Salt (2 g), sugar (10 g) and wheat flour (50 g) were added and incubated at 26°C for 12 h, pH up to 4.5. It was filtered by stainless steel strainer and approx. 280 g filtrate was obtained. It was mixed with wheat flour (140 g), then incubated at 26°C for 6 h, pH to 4.5.

Enumeration of lactic acid bacteria (LAB) and yeast    Numbers of LAB were determined in elective media MRS agar (Merck, Germany). Appropriate dilutions were plated on MRS agars and the plates incubated anaerobically at 35°C for 48–72 h. For yeast counting, appropriate dilutions were plated on YGC agar (Merck, Germany), incubated aerobically at 25°C for 72 h and At the end of incubation the colonies were counted (Lönner et al., 1986; Simsek et al., 2006).

Preparation of bread samples    The bread production formula and the straight dough method of Keswet et al. (2003) were used as slightly modified. The water (59% based on flour), salt (1.5% based on dry matter), instant active dry yeast (2%), flour (300 g) and chickpea sourdough were mixed (KitchenAid KSM150PSER, Belgium) for 15 min. The dough divided to two pieces after preparing. The baking experiment of bread samples were done as two repetitions and two parallel in each baking. Bread production followed the main steps as premixing, kneading, fermentation for 40 min, shaping, proofing for 50 min, and finally baking for 30 min at 180°C. While the amounts of instant active dry yeast and chickpea sourdough were used at suggested quantity by experimental design for optimized bread (OBrd), the instant active dry yeast was used 6 g in control bread (CBrd).

Quality properties of breads

Pore structure    Images of both faces of two central slices (20 mm thickness) from each loaf were captured using a flatbed scanner (Model Scanjet 8200, HP, Cupertino, USA) with a resolution of 600 dots per inch (dpi) and converted from true color to grayscale. The images of bread samples were calibrated, standardized and optimized by applying appropriate filters to measure pore size and distribution using Image-Pro Plus 60 (Media Cybernetics Inc, USA) software. The number and area of pores were characterized by enumerating the pores present in six pre-selected dimensional classes based on their area (class1 = 0.05–0.49 mm2; class 2 = 0.50–0.99 mm2; class 3 = 1.00–4.99 mm2; class 4 = 5.00–9.99 mm2; class 5 = 10.00–49.99 mm2; class 6 = >50 mm2) as previously described by Bianchia et al., (2008). The number and the area of the pores and the percentages thereof were calculated by the software. Pore area and numbers were then classified by Microsoft Excel (Office 2007, Microsoft Corp, Redmond, WA).

Specific volume and crust thickness    The volumes of breads, cooled under room conditions for 1 h after baking were determined using the method based on displacement with rape seed. Their weights were measured. The specific volumes of bread samples were calculated by using the formula (Artan et al., 2010; Torrieri et al., 2014). The crust thicknesses (mm) of the samples were measured at five different points using a digital caliper.

Acceptability Value (AV)    For calculating of AV, the panel test was carried out to determine that various properties of the bread samples. The sensory evaluation method with hedonic scale used by Olapade and Adetuyi (2007) were slightly modified. Twenty trained volunteers (staff and professors) having prior experience of testing bakery products. The samples were labeled randomly with three-digit numerical codes and then given to the panelists. Twenty trained panelists (staff and professors) from The Dept. of Food Eng, Gümüşhane University, having prior experience of testing bakery products assessed (Ndife et al., 2011) the features of bread samples, such as crust color, baking quality and baking symmetry, and internal features such as structural homogeneity, crumb color, taste and aroma. The samples were labeled randomly with three-digit numerical codes and then given to the panelists. Each of 10 attributes was scored using a 10-point hedonic scale, and total AV was calculated out of a maximum 100 points.

pH and total titratable acidity (TTA)    The bread and distilled water were mixed (1:9, w/v) and crumbled by ultra turrax (IKA, T25, Germany) until a homogeneous mixture was obtained. The mixture was then kept to for 10 minutes, and the pH was measured. The mixture was titrated with 0.1 N NaOH by adding phenolphthalein, and then TTA was calculated (Rizzello et al., 2016).

Moisture    After 3 h of baking, a slice was taken from the bread loaf (Poinot et al., 2008). The crust and crumb were homogenized and 5 g was weighed out. Moisture was determined by oven drying at 105°C to constant weight (Akgün and Doymaz, 2005). The bread samples were stored at the same room conditions (24 ± 2°C, kept away directly sunlight). Moisture loss during shelf life was also determined between days 0 and 8.

Color (L*, a*, b*)    The color profile for crust and crumb of bread sample was determined using a colorimeter (Konica-Minolta, CR400, Japan) in the form of L*, a* and b*. The measurement was carried out on five points on crust and crumb. Mean values were calculated (Torrieri et al., 2014; Rizzello et al., 2014b).

Antioxidant activity    For the DPPH radical scavenging activity, 0.00197 g of DPPH (α, α-diphenyl-β-picrylhydrazyl) was dissolved in 50 mL of 80% methanol. The sample extract was mixed with 600 µL DPPH solution and 4 mL of 80% methanol and kept in the dark at room temperature for 30 min. The absorbance (A sample) was recorded at 517 nm through a UV-VIS spectrophotometer (Agilent, UV-Visible, USA). A blank was prepared using 0.1 mL of methanol and 3.9 mL of DPPH solution, and its absorbance (control) was also recorded. DPPH radical scavenging activity was calculated using the formula (Eq.1) (Karamac et al., 2002);   

Sensory profile (SPA)    Hansen et al., (1989) evaluated odor and taste intensities of four attributes for sourdough bread: sour, sweet, crusty and off-flavor. These attributes were adopted in order to determine the sensorial profile in this study. Sensory evaluation of the bread samples, which was modified according to Volpini-Rapina et al. (2012), was performed by a panel of 20 male and female trained volunteers (from staff and professors) having prior experience of testing bakery products. It was taken into consideration for the panelist selection that their liking and usage of the product, age (between 18–45), no allergies to bakery products or used ingredients. The samples were labeled randomly with three-digit numerical codes and given to the panelists in the same room condition under the fluorescent light. The intensities of attributes (sour, sweet, crusty, off-flavor, fatty and overall) for each bread were evaluated and scored using a 5-point hedonic scale. Five means more intense and zero means imperceptible. The results were presented by sensory diagrams.

Statistical analysis    After optimization, the results were validated experimentally. The bread sample produced by the optimized model was evaluated in terms of physicochemical and sensory profile analysis in comparison with the control sample. The one sample T-test (SPSS 1701) was used for the comparison (p < 0.05) of results.

Results and Discussion

LAB and yeast    Yeast number of chickpea sourdough were between 6x102 and 8x103 CFU/g, while LAB were between 47x108 and 1x109 CFU/g. There have been found more than 50 species of LAB which especially belongs to the genus Lactobacillus, and more than 20 species of yeasts which mostly belongs to the genera Saccharomyces and Candida, in the traditional sourdoughs (Lattanzi et al., 2013; Minervini et al., 2012). These data are consistent with another study, which showed dominating microorganisms in spontaneously fermented doughs. The homofermentative Lactobacillus and Pediococcus have been found both in wheat and rye sourdoughs at the level of 3x108 − 3x109 CFU/g (Tulbek, 2006).

Optimization    The V and AV determined based on the experimental design are also given in Table 1.

Table 1. Volume (V) and Acceptability values (AV) obtained from the experimental design
Factor 1 Factor 2 Response 1 Response 2
mount of usage (g)
No A B V (cm3) AV
1 128.03 5.12 1888 75
2 75.00 3.00 1660 86
3 75.00 3.00 1530 85
4 21.97 0.88 1210 70
5 75.00 3.00 1620 75
6 75.00 3.00 1500 81
7 21.97 5.12 1350 56
8 128.03 0.88 1085 60
9 150.00 3.00 1825 79
10 75.00 3.00 1520 77
11 0.00 3.00 1250 72
12 75.00 0.00 720 42
13 75.00 6.00 1803 67

A-Chickpea sourdough, B-Instant active dry yeast

The data were analyzed by the software in order to determine which functions would be suggested. “Sequential model sum of squares” and “lack of fit” tests were carried out (Table 2) for V (cm3) and AV. Standard deviation, R2 (R-squared) and adjusted R2 were determined for each function. The values were compared and suggested functions was thus ascertained.

Table 2. Statistical parameters of optimization; p values for model selection and lack of fit tests; Model and independent variable factors (a), R2 and Corrected R2 for quadratic function (b)
p values*
V (cm3) AV
Model selection and lack of fit test Quadratic 0.0204 0.0019
Lack of fit 0.0944 0.2400
Model 0.0005 0.0052
Model and independent variable factors A 0.0054 0.2919
B < 0.0001 0.0644
V (cm3) AV
R2 0.94 0.87
Corrected R2 0.89 0.78
*  p<0.05 was considered statistically significant

V,volume; AV, acceptability value; A, chickpea sourdough; B, Instant active dry yeast

Quadratic function in terms of V (cm3) and AV was approved (p < 0.05). “Lack of fit” was identified as insignificant for both properties (p > 0.05). When the effects of independent factors on V (cm3) and AV were taken into account (Table 2), the influences of chickpea sourdough and instant active dry yeast use in terms of bread. V were statistically significant (p < 0.05), whereas the influences in terms of AV were statistically insignificant (p > 0.05). The model was also determined to be statistically significant (p < 0.05). According to analysis of variance of the quadratic function are given in Table 2. The final equations with factors were coded (A representing chickpea sourdough and B representing instant active dry yeast) as they follow:   

The purpose of optimization is to determine accurate values for parameters which will help to obtain the desired response. Numerical optimization was used in this study. The V and AV were evaluated together, and the first solution was selected from the 30 solutions offered by the software. According to the solution, amounts of use 59.06 g for A, 3.39 g for B were offered for obtaining 1561.03 cm3 V and 79.84 AV values..

Figure 1 shows the response to the interaction for the level of B and V (cm3) increases in line with the levels of A. The AV increases in line with the level of the A and B. However, the AV exhibits a tendency to decrease after the central point with the increase of these independent variables. The insignificant internal interaction between the level of the A and B can be seen through the circular curves at the bottom of the second graph in Figure 1.

Fig. 1.

Response surface plot showing the mutual effect of the amount of chickpea sourdough (A) and active dry yeast (B) on volume and acceptability values

Experimental validation of optimization results    Following optimization, the levels of usage were determined as 59.06 g for A and 3.39 g for B. The bread was produced using optimized amounts in three replicates. The V (cm3) and AV values of OBrd were determined, and the mean value was calculated. The presence of any statistically significant (p < 0.05) difference between the mean value and estimated values from the model was investigated using the one sample T-test. The one sample T-test results for each response are given in Table 3. No statistically significant difference (p > 0.05) was determined between the results obtained from the validation test. This indicates that the model obtained with optimization was experimentally successful.

Table 3. Comparison of optimum point verification test results with the estimated values from the model
Response Estimated value Average experimental result* Difference p-value
V (cm3) 1561.03 1569 ±81.50 7.97 0.881
AV 79.84 83.33 ± 3.33 3.49 0.186
*  Mean ± standart deviation; p<0.05 was considered statistically significant V,volume; AV,acceptability value

Determination of differences between the OBrd and CBrd    Differences between the OBrd and CBrd were compared in terms of various physicochemical and sensory properties.

Pore structure    The pore structure of samples was examined using image analysis (Figure 2) which revealed that while the OBrd had 876 pores per unit area, the CBrd had 666 pores. Pore number per unit area thus increased with the use of chickpea sourdough. Furthermore, the increase in pore numbers per unit area was the result of the formation of smaller pores.

Fig. 2.

Pore structure images obtained by Image Pro Plus software of bread samples (OBrd; optimized bread, CBrd; control bread)

The pore numbers for Class 1, which had pores with the smallest area, were 616 (70.32%) for the OBrd and 449 (67.42%) for the CBrd. While the total number of large pores in Class 4 and Class 5 was 46 (6.90%) for the CBrd, it was only 40 (4.57%) for the OBrd (Figure 3). In a study about the microflora of chickpea sourdough, Enterococcus spp, Lactobacillus spp, Streptococcus spp, Pediococcus spp and Saccharomyces cerevisiae were determined in the microflora (Sikili, 2003). The microbiota of chickpea sourdough contains homo and heterofermentative lactic acid bacteria. The heterofermentative strains can produce CO2 in addition to the other metabolites. While only yeast fermentation occurred in CBrd, fermentation of yeast and LAB originating from chickpea sourdough occurred in OBrd. There is a symbiotic relationship and interaction between yeasts and LAB in sourdough fermentation. Yeasts and heterofermentative LAB are together responsible for leavening of the dough of OBrd. The pore number per unit area in the OBrd was therefore higher than that in the CBrd.

Fig. 3.

Distribution of pore numbers according to image analysis

Physicochemical properties    The parameters determined of the bread properties were listed in Table 4. While the usage of chickpea sourdough caused significant decrease in bread pH, it caused an increase in TTA (p < 0.05)

Table 4. Properties of bread samples
Properties OBrd CBrd p-value
pH 5.12 ± 0.07 5.95 ± 0.03 0.009
TTA 4.33 ± 0.056 2.94 ± 0.106 0.008
Specific volume (cm3/g) 3.32 ± 0.02 3.12 ± 0.03 0.004
Crust thickness (mm) 4.29 ± 0.11 2.98 ± 0.26 0.016
L* 63.98 ± 2.35 66.71 ± 1.20 0.023
a* 7.48 ± 1.25 5.61 ± 1.11 0.105
b* 29.75 ± 1.34 27.00 ± 1.84 0.029
L* 67.84 ± 1.15 71.58 ± 0.97 0.011
a* −0.75 ± 0.08 −0.72 ± 0.14 0.068
b* 14.48 ± 0.96 16.16 ± 0.63 0.042

Mean ± standard deviation, p<0.05 was considered statistically significant OBrd; optimized bread, CBrd; control bread

Since the CBrd samples were produced by using yeast fermentation only, the pH was higher than that in OBrd, and the TTA was lower. However, in OBrd, yeast and LAB were together responsible for fermentation. The LAB synthesize lactic acid by the homofermentation of hexoses, and synthesize lactic acid, acetic acid, ethanol and CO2 by the heterofermentation of hexoses (Olapade and Adetuyi, 2007). A reduction in pH causes an increase in the protease activity of cereals. Additionally, LAB also have their own enzyme activity. Increased enzyme activity raises the free amino acid content by hydrolyzing proteins (Hansen and Schieberle, 2005). Therefore it may lead resulting higher TTA value. In a study that used three heterofermentative (L. sanfrancisco, L. brevis and L. fermentum) and two homofermentative LAB (L. delbrueckii and L. plantarum), Hansen et al. (1989) determined that TTA was increased by the heterofermentative LAB.

The crust thickness of OBrd was found significantly higher than the CBrd sample (p < 0.05). The specific volume of OBrd sample also significantly increased with the use of chickpea sourdough (p < 0.05). While only yeast fermentation in CBrd was responsible of gas production, the CO2 produced by the fermentation performed by yeast and heterofermentative LAB, was responsible of gas production and pore structure in OBrd.

The enhancing effects of the chickpea sourdough on the volume may have been due to various factors. The gluten structure in acidic doughs that contain sourdough has a better gas retention capacity (Gobbetti et al., 1995). This is caused by the solubility of pentosanes during the sourdough process (Corsetti et al., 2000), and by the increase in endogenous enzyme activities through lower pH related to the use of sourdough (Clarke et al., 2003). The use of chickpea sourdough resulted in the positive effects on volume and specific volume. The researchs show that the addition of sourdough increases the volume and specific volume of bread (Dal Bello et al., 2007; Wu et al., 2012). Pore structure analysis revealed a higher pore number per unit area in OBrd. This result was supported by the results of specific volume.

According to color measurements, L* values decreased not only in bread crust, but also in bread crumb. While a* and b* values increased in bread crust, they decreased in bread crumb. However, the changes in a* values was not found statistically significant (p > 0.05). Color is one of the most important factors affecting consumer preferences for bakery products. The formation of the yellow-gold-brown colors often described as browning reactions is due to non-enzymatic chemical reactions such as the Maillard and caramelization which are produce colored compounds during the baking. When bakery products containing reducing sugars and amino groups are heated, caramelization and the Maillard reaction may take place simultaneously (Purlis and Salvadori, 2009). The reactions lead to color changes at different levels in crumb and crust during baking (Artan et al., 2010). A decrease in pH during fermentation positively affects the browning reactions, probably because the Amadori rearrangement requires H+. The duration of fermentation has been reported to influence color of the bakery product through the formation of various compounds as precursors of brown pigments (Martinez Anaya, 1995).

The moisture contents were 38.08% and 36.88% for OBrd and CBrd, respectively (Figure 4). The reduction of moisture was lower for the OBrd samples during storage possibly corresponding a facilitated moisture retention by the use of chickpea sourdough.

Fig. 4.

Moisture loss during shelf life of bread samples (OBrd and CBrd)

For bakery products, not only high initial moisture level, but also moisture retention during shelf life is important. The retrogradation process known as staling is also related to moisture loss. Additionally, the exopolysaccharide production of LAB has been thought to play a role in moisture retention (Galle and Arendt, 2014). The conversion of starch into simple sugars as a result of fermentation affects moisture retention. The crust thickness was greaterin the OBrd than in the CBrd. The thick crust that formed may have led to moisture retention inside the crumb. The gas retention capacity of gluten is known to increases in acidic dough (Gobbetti et al., 1995) and the modification of gluten caused by chemical reactions and biological action of microorganisms may together have a function for the retention of moisture in the bread structure.

DPPH radical scavenging activity    DPPH radical scavenging activity (%) for the CBrd and OBrd were 15.29 ± 08 and 32.35 ± 16, respectively. Inhibition increased with the use of chickpea sourdough in the bread sample. The antioxidant properties of baked goods are affected by the various factors and phytochemicals are mainly altered in during processing such as fermentation. The formation or modification of bioactive compounds during sourdough fermentation can improve the antioxidant activity of bread. Several studies have shown that some lactic acid bacteria are capable of releasing antioxidant peptides during sourdough fermentation (Rızello et al., 2012; Coda et al., 2012).

Sensory profile    The radar graphs (Figure 5) clearly showed that difference of sensory profiles between the bread samples. The OBrd sample exhibited generally higher scores in terms of all sensory characteristics.

Fig. 5.

Sensory characteristics of bread samples indicated with radar graphs (OBrd, optimized bread; CBrd, control bread)

Fatty character was detected at equal levels, while no off-flavor character was determined in any sample. An acidic, sweetish character and general aromatic profile were more dominant in the OBrd compared to CBrd. Although the chickpea yeast is a kind of the sourdough type, it gave a soft and sweet flavor/aroma on the bread sample. This effect depends on the microbiota and their metabolites contained in the chickpea sourdough. Another reason is that the chickpea, which is part of the chickpea's sourdough formula, have high starch content. Starch-simple sugar conversions occur during fermentation. The OBrd sample acquired a sweet and soft sensory character due to sugar conversion resulting from fermentation. In addition, the acidic flavor in the OBrd samples may results from organic acids produced by LAB during fermentation process.


In conclusion, the use of chickpea sourdough enriched the sensory profile and improved the texture and physicochemical properties of bread in this study. It also improved the crust color of bread as well as volume and pore structure. Following optimization, the levels were 59.06 g for chickpea sourdough and 3.39 g for instant active dry yeast (based on 300 g flour), while the control sample contained 6 g instant active dry yeast. The results suggest that the chickpea sourdough can be used, as a natural ingredient, as a partial replacement for instant active dry yeast in bread formulation. Furthermore,the chickpea sourdough can be used for other chemically leavened bakery products.

The metabolites formed during chickpea sourdough fermentation and acidic profile were transferred to the bread sensory profile. The use of chickpea sourdough enriched the aromatic structure of bread by giving it a sour, sweetish and soft sensory character. The bread crust color was also enhanced, and the bread crumb acquired a lighter color. Moisture loss during shelf life was lower and slower in the bread containing chickpea sourdough. This may be attributed to a smaller and more intense pore structure, and to a thicker bread crust.

The use of the chickpea sourdough can improve the nutritional and bioactive properties of bread, because the chickpea sourdough involves partly chickpea, and the legumes particularly rich in minerals. The traditional chickpea sourdough production method used in this study was a typical multistage fermentation, which combines a soaking stage and lactic acid fermentation. This may have had the potential to reduce anti nutrient factors and to improve bioavailability. The bioavailability of proteins, minerals and other nutritional properties can be examined in future studies. If the traditional chickpea sourdough production can be adopted for the industrial level, it can serve as alternative for the satisfaction of the todays consumer's demands toward additive free, functional bakery products. In the light of the findings of the present study, further detailed exploration of the beneficial properties of chickpea sourdough for the bakery industry and consumers is now required.

© 2018 by Japanese Society for Food Science and Technology