Selected materials techniques for evaluation of attributes of sourdough bread with Kombucha SCOBY

Juwairiya Tanveer; Debmalya Banerjee; Baishali Dey; Deblu Sahu; J. Sivaraman; Maciej Jarzebski; Floirendo Flores; Doman Kim; Hayeong Kim; P. Balasubramanian; Kunal Pal

doi:10.1515/rams-2025-0133

Article Open Access

Selected materials techniques for evaluation of attributes of sourdough bread with Kombucha SCOBY

Juwairiya Tanveer , Debmalya Banerjee , Baishali Dey , Deblu Sahu , J. Sivaraman , Maciej Jarzebski , Floirendo Flores , Doman Kim , Hayeong Kim , P. Balasubramanian and Kunal Pal

Published/Copyright: August 5, 2025

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From the journal REVIEWS ON ADVANCED MATERIALS SCIENCE Volume 64 Issue 1

Abstract

There is a high demand for new techniques and applications, which are typically used in materials science for food product development. As a novel food example, sourdough bread (SDB) has been previously evaluated for its prolonged shelf life, positive health effects, and distinctive flavor, yet conventional fermentation is time-consuming. The influence of dough hydration on the properties of SDB prepared using symbiotic culture of bacteria and yeast (SCOBY) derived from black tea Kombucha and how SCOBY reduced the overall time of the starter preparation to ∼16 h were studied. This decrement in the fermentation period, aided by the metabolically active microbial association in SCOBY, acts as a suitable alternative to conventional sourdough cultures that need extended fermentation periods. Several characterization techniques were employed to elucidate the effect of hydration levels (70–90%) of the samples, including impedance profile analysis. Results have revealed that the SDB with an 80% hydration level (SB80) displayed optimal characteristics concerning porosity, starch crystallization, texture, total phenolic content, and viscoelasticity. These findings suggest that SB80 attained a stable matrix with enticing nutritional and mechanical attributes, thereby emerging as an ideal candidate for developing novel bakeries with improved properties. Higher hydration levels enhanced the moisture retention ability and antioxidant activity. Furthermore, FTIR studies confirmed hydration-mediated molecular interactions, thereby affecting gluten structure and the process of starch gelatinization. Stress relaxation studies have revealed the superior mechanical strength of SB80, thus demonstrating improved texture and mouthfeel attributes. Electrical impedance spectroscopy studies further displayed hydration-driven modifications in water distribution and starch arrangement. These findings open a new dimension in utilizing SCOBY as an alternative in formulating novel SDBs to create sustainable, functional food products.

Graphical abstract

Keywords: Kombucha SCOBY; sourdough bread; starch crystallization; hydration optimization

Abbreviations

AUC: area under the curve
SCOBY: symbiotic culture of bacteria and yeast
SDB: sourdough bread
TPC: total phenolic content
WWF: whole wheat flour

1 Introduction

Bread comes in a wide variety, and each has its distinct flavor profile and historical importance, depending on the area in which it is being produced [1]. One of the most popular varieties of bread is sourdough bread (SDB). Preparing SDB involves using a fermented flour and water mixture, commonly called the sourdough (SD) starter. This starter is enriched with homo- and hetero-fermentative lactic acid bacteria and wild yeast [2]. Fermentation provides unique flavors, texture, and enhanced nutritional attributes to the bread [3]. Additionally, the organic acids generated during sourdough fermentation lower the pH considerably and thereby prevent the growth of unwarranted organisms, contributing to the enhanced shelf life of SDB [4]. The compounds, like alcohol, aldehyde, and acetic acid found in the SDB samples, are responsible for other properties, including antioxidant activity, color, crust formation, and digestibility [5]. In the case of SDB, the natural fermentation process facilitates the breakdown of gluten and phytic acid, making SDB easily digestible [6]. This degradation of phytic acid by the action of microbial phytases increases mineral bioavailability, while the slow process of fermentation confers a lower glycemic index than conventional bread [7]. Due to this, SDB can improve blood sugar control and promote consistent energy levels in the body [8]. Furthermore, the extended fermentation process paves the way for the development of various volatile compounds, e.g., esters, alcohols, and aldehydes, which are responsible for the unique flavor and aroma of SDB [9]. Expansion of dough or batter occurs due to the generation of carbon dioxide gas, which is often regarded as leavening [10]. The ingredients that help in the leavening are called leavening agents, which include biological agents and chemical compounds. Biological leavening agents, such as yeast and sourdough starter, and chemical leavening agents, such as baking soda and baking powder, are commonly used in bread making. The earliest method of introducing leavening agents into the breadmaking process involved a spontaneous fermentation process facilitated by indigenous yeast and bacteria in the surrounding environment. During the mid-19th century, baking powder was introduced, significantly changing the breadmaking process. However, the bread prepared using commercial yeast lacks the depth and complexity of flavor. This can be attributed to the fast-acting fermentation properties of commercial yeasts. Further, it has been proposed that SDB is better suited for patients with certain gastric conditions, including irritable bowel syndrome, over bread prepared with fast-acting commercial agents because of its enhanced digestibility [11]. Conventionally, the preparation of SDB involves using flour and water, with the fermentation process facilitated by naturally occurring microorganisms in the environment. This method is time-consuming, and the duration of the process may vary between 7 and 10 days, depending on the present temperature and humidity levels.

Recently, there has been an emerging trend of using the symbiotic culture of bacteria and yeast (SCOBY) as a natural leavening agent instead of relying on the naturally occurring bacteria and yeast in the surrounding environment. SCOBY is a cellulose-derived framework comprising a colony of microorganisms [12]. It appears to be a slimy and rubbery material that has been explored to prepare fermented beverages, such as Kombucha. Whole wheat flour (WWF) was used in our study as it is an excellent source of nutritional fiber, vitamins, minerals, and antioxidants [13]. To date, research in the field of SD has been mainly confined to traditional starter-making techniques. A study into the effect of dough hydration levels on the quality of SDB using Kombucha SCOBY as a natural leavening agent is currently limited in its scope. Accordingly, this article aimed to develop an innovative fermentation technology specifically using Kombucha SCOBY as the natural leavening agent. By implementing this innovative technique for leavening the dough, it was observed that the fermentation period could be significantly reduced to 16 h from 7 to 10 days in the traditional SDB-making technique. This reduction in the fermentation time may help enhance the efficiency of the breadmaking process without compromising the unique quality of SDB. Further, the hydration level was varied during the breadmaking process to understand how different hydration levels can affect the various quality parameters of SDB in terms of starch crystallization, total phenolic content (TPC), antioxidant properties, etc. Prior research has mainly concentrated on conventional SDB production, exploring various hydration levels. Incorporating SCOBY into the breadmaking process introduces a novel aspect to the investigation of dough hydration. Hence, tests were performed to analyze the impact of different hydration levels (70–90%) on the overall quality of the bread samples prepared using the SCOBY starter culture. As a novelty, we analyzed the impedance profiles of the SDB samples for understanding the intricate properties.

2 Materials and methods

2.1 Materials

WWF (Ashirwad Shudh Chakki Atta, ITC Limited, Kolkata, India), sulphurless sugar (Uttam Sugar Sulphurless Sugar, Uttam Sugar Mills Ltd., Uttarakhand, India), and iodized salt (Tata Chemicals Ltd., Mumbai, India) were taken from the local grocery stores. Per the manufacturer’s label, the nutritional content of the flour per 100 g is 396 kcal of energy, 77 g of carbohydrate, 10.8 g of protein, 5.6 g of sugar, 11.1 g of dietary fiber, and 1.8 g of fat. The flour contained 10.5% moisture and 2.2% ash, and the particle size was <100 µm. SCOBY from black tea kombucha was sourced from the Agriculture and Environment Biotechnology Lab, NIT Rourkela. It is a microbial consortium representing a symbiotic culture of Komagataeibacter xylinus and Brettanomyces bruxellensis (pH 2.5) [14]. Moreover, the SCOBY had no visible mold contamination, and the acidic pH ensured it was safe from unwanted contaminants.

2.2 Methods

2.2.1 Preparation of starter

The ingredients of the prepared starter are specified in Table 1. A grinder was used to grind the SCOBY (30 g) in water (150 mL) to convert it into a slurry. This slurry was then combined with WWF to form a starter mixture. Subsequently, the starter was placed in a temperature-controlled incubator (at 32 ± 2°C) and allowed to remain undisturbed for 16 h. This fermentation time was optimal experimentally, as shorter periods would lead to inadequate microbial activity, and more extended incubation periods would cause a decrement in the starter culture volume due to over-acidification. Following the incubation, the starter was used to prepare SDB.

Table 1

Composition of the starter

Ingredients	Quantity (g)
SCOBY	30.00
Purified water	150.00
WWF	150.00

2.2.2 Making of SDB

The components of the bread are listed in Table 2. All ingredients were introduced into the bread maker (model: 16010; make: Kent RO Systems Ltd., Uttar Pradesh, India), which was then operated in the whole wheat bread mode with medium color settings. Initially, the ingredients were mixed for 70 min, including intermittent resting phases. Once the mixing process was completed, the dough was fermented for 120 min at ambient room temperature (RT) (35 ± 2°C). Finally, the dough was removed from the machine and carefully transferred onto a baking sheet lined with a baking tray. The tray was then placed in the preheated oven (model: MC32J7035CT, make: Samsung Electronics Pvt. Ltd., Kuala Lumpur, Malaysia), which was operated in the convection mode at 200°C for 5 min. Then, the baking was carried out in the convection mode for 55 min at 200°C. Subsequently, the bread samples were allowed to cool at RT (25 ± 2°C) for 2 h before further use. The hydration level of the bread was changed in the range of 70–90% to examine the alterations in the texture and other characteristics of the bread.

Table 2

Composition of the SDB samples

Ingredients	Quantity (g)
Ingredients	SB70	SB75	SB80	SB85	SB90
Flour	220.00	217.00	210.00	208.00	192.00
Starter	115.00	115.00	115.00	115.00	115.00
Water	154.00	162.00	168.00	174.00	173.00
Salt	5.50	3.00	3.50	1.50	10.00
Sugar	5.50	3.00	3.50	1.50	10.00

2.2.3 Moisture analysis

The moisture content of the SDB crumb was measured using a digital moisture balance (model: PGB1MB, make: Wensar Weighing Scales Limited, Chennai, India). Precisely measured crushed crumb samples weighing 2 g (approx.) were carefully positioned on an aluminum pan. After that, the samples were heated until constant weight was attained at 180°C. Subsequently, the percentage of mass loss, also known as moisture content percentage (% M), was calculated and noted as per Eq. (1). Each dough sample was measured three times to ensure accuracy and consistency:

(1) % M = M i − M f M i × 100 ,

where M _i denotes the initial weight of the dough and M _f represents the final weight of the dough.

2.2.4 TPC

The phenolic compounds were extracted from the SDB samples to determine the TPC. At first, the crumb and crust were segregated, and after that, 1 g of the crumb (torn into small pieces) was put into 9 mL of ethanol solution (80%, v/v). The mixture was then subjected to sonication for 30 min at 40°C, utilizing an ultrasonicator (model: LMUC3, make: Labman Scientific Instruments Pvt. Ltd., Chennai, India). Then, the mixture was subjected to filtration, and the filtered solution was kept in a refrigerator. For the TPC analysis, 0.5 mL of the extract was combined with 1.8 mL of water and 2.5 mL of 10% Folin–Ciocalteau reagent. After incubating for 5 min, 2 mL of 7% sodium carbonate solution and 0.8 mL of distilled water were added. The mixture was thoroughly mixed and incubated for 90 min. The absorbance was then measured at 750 nm using a UV–visible spectrophotometer employing gallic acid as a standard, and the results were reported in mg gallic acid equivalent/g [15].

2.2.5 Impedance analysis

The impedance profiles were recorded using an Impedance Analyser (model: Impedance breakout board for Analog Discovery 2; make: National Instruments Corp., Austin, USA). Stainless steel electrodes with a diameter of 1 cm and a distance of 1 cm were put into the crumbs [16]. The impedance profiles of the samples were subsequently measured within the frequency range of 1 Hz to 5 kHz.

2.2.6 Microscopic analysis

The surface morphology of the crust and crumb of the rectangular SDB samples, with dimensions of 30 mm in length and breadth, was observed using a Stereo Zoom Microscope (model: SM-2TZ; make: AMscope, Irvine, USA). Images were acquired using an external eyepiece lens camera (model: AMscope MD500, make: AMscope, Irvine, USA) attached to the microscope.

2.2.7 Colorimetric and reflectance analysis

A colorimeter, created in the laboratory, was used to conduct colorimetric and visible spectrum analysis on the SDB crumbs. This analysis aimed to acquire the CIELab (L*, a*, and b*) values. A detailed explanation of the operation mechanism is described in Jain et al. [17]. Essentially, the colorimeter was calibrated initially by utilizing black and white tiles. Subsequently, the specimens (with a cuboidal shape; dimensions 20 mm in height, 15 mm in length, and 15 mm in width) were placed within a 35 mm Petri dish, and the colorimeter was used to collect surface photos. The colorimeter then computed the L* (lightness), a* (values ranging from red to green), and b* (values ranging from yellow to blue). Also, the derived color parameters, namely whiteness index (WI) and yellowness index (YI), of the samples were computed using the formula provided by Jain et al. [17] and Sahu et al. [34].

(2) WI = ( 100 − L ⁎ ) 2 + ( a ⁎ ) 2 + ( b ⁎ ) 2 ,

(3) YI = 142.86 × b ⁎ L ⁎ ,

where WI refers to whiteness index, YI denotes yellowness index, L* depicts lightness, and a* and b* are the chromatic parameters.

Reflectance analysis is frequently employed to study the interaction between light and material. In this experiment, the reflectance properties of the SDB samples were analyzed in the visible light spectrum (380–730 nm).

2.2.8 Texture analysis

The SDB samples were subjected to texture analysis for characterizing their textural characteristics. For this purpose, the texture profile analysis (TPA) was performed at ambient temperature using a texture analyzer (model: Texture analyzer HD plus; make: Stable Micro Systems, Godalming, UK). The bread slice was cut into rectangular cuboidal pieces, measuring 15 mm in length and breadth and 20 mm in height. Herein, a flat circular probe with a diameter of 35 mm was used to compress the samples twice. During the compression stages, a strain level of 50% was achieved at a crosshead speed of 1 mm·s⁻¹. A time interval of 5 s was maintained between the two cycles. The texture attributes include hardness, cohesiveness, springiness, gumminess, chewiness, and resilience [16].

Thereafter, the stress relaxation test was performed using the texture analyzer to evaluate and analyze the viscoelastic characteristics of the manufactured SDB samples. The SDB samples (L: 15 mm, B: 15 mm, H: 20 mm) were subjected to a compressive displacement of 2 mm at a velocity of 1 mm·s⁻¹ by the probe (flat circular probe, diameter: 35 mm) after a trigger force of 5 g was attained. At the said position, the probe was kept constant for 60 s, and the relaxation profiles were obtained by recording the force values. Subsequently, the probe was returned to its original height [16].

2.2.9 FTIR analysis

The infrared (IR) absorption spectra of SDB samples were obtained using an attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectrophotometer (model: Alpha-E; make: Bruker, Bremen, Germany) equipped with an ATR-ZnSe crystal. Thin slices of the bread crumbs were directly placed onto the crystal surface without any prior processing conditions. The in-built integrated pressure arm of the ATR-FTIR probe was employed to ensure maximal contact between the sample and the ATR-ZnSe crystal. Eventually, scanning was conducted across the 4,000 to 500 cm⁻¹ wavenumber spectrum. Each scan comprised 29 scans, with a spectral resolution of 4 cm⁻¹ [18].

The acquired IR spectra were deconvoluted using the Gaussian function in Multifit peak tools within Origin Pro software (v9.0, OriginLab Corporation, Northampton, USA). Numerical deconvolution was applied to determine the proportions of key bands such as OH, Amide I, and starch. The criteria for this process included R ² > 0.99 and χ ² < 0.001. Bands associated with specific conformations were combined and standardized relative to the total area of the corresponding main band [19]. Concerning the water region (3,800–3,000 cm⁻¹), the peak assignments were done based on previous studies that differentiate between strongly hydrogen-bonded water (∼3,088–3,216 cm⁻¹), weakly bonded water (∼3,389–3,543 cm⁻¹), and free water (∼3,625 cm⁻¹) using FTIR deconvolution [20]. With regard to the starch region, the bands near the wavenumbers 1,046, 1,021, and 997 cm⁻¹ were selected based on the previous literature, where it has been reported that starch exhibits three modes of vibration corresponding to crystalline, amorphous, and hydrated crystalline domains, respectively [21]. For the deconvolution process, the Gaussian function was employed as it can effectively model the natural broadening of the spectral bands arising from hydrogen bonding and molecular interactions in complex food systems, including SDB. Moreover, it enhances the accuracy and precision of peak resolution and quantification, particularly in the cases where overlapping vibrations are present [22,23].

2.2.10 Swelling study

For this study, crumbs of all the SDB samples were cut into small cubes (with each side 2 cm), and their initial weight was measured (∼6 g). The experiment was performed in triplicates in a water bath (model: DFD-700, make: Labman Scientific Instruments Pvt. Ltd., Chennai, India) set at 37°C to maintain consistent conditions. Then, the crumb cubes were immersed in water to induce swelling, and measurements of their weights were recorded at specific time intervals. Initially, measurement was taken every 15 min for the first 2 h. Then, for the next 3 h, measurement was taken at 1 h. Eq. (4) was used to calculate the swelling index (SI) percentage.

(4) Swelling index ( % ) = W f − W i W i × 100 ,

where W _i denotes the initial weight and W _f refers to the final weight of the samples.

3 Results and discussion

3.1 Visual and physical appearance

After baking, the samples were set aside for 2 h to cool down and reach a temperature where they could be handled. The photographs of the SDB samples were captured at a distance of 150 mm. Figures 1 and 2 show the top view and cross-sectional view of the samples, respectively. The top surface (crust) of the samples showed a notable coarse and uneven texture with a yellowish hue. SB70 exhibited a uniform crust. In SB75, a discontinuity (cracks) on the crust was observed (marked with a red arrow). The surface cracks were prominent in SB80 and SB85 compared to SB75. Among SB80 and SB85, the surface cracks on SB80 were quite wide. Interestingly, no surface cracks were observed in SB90. However, the surface of the SDB was very irregular.

Figure 1

Top view of the samples. (a) SB70, (b) SB75, (c) SB80, (d) SB85, and (e) SB90.

Figure 2

Cross-sectional view of the samples. (a) SB70, (b) SB75, (c) SB80, (d) SB85, and (e) SB90.

The cross-sectional view of the samples offers a comprehensive understanding of the crumb’s texture (Figure 2). It was observed that the crumb of SB70 exhibited a higher degree of compactness. Also, SB70 was firmer to the touch than other samples. This compactness and stiffness decreased in SB75. In SB80, notable pores were seen, and the apparent texture exhibited significant enhancement. On the other hand, the crumb of SB85 had a denser texture and a more soggy appearance than SB80, probably due to an increase in hydration level. Lastly, SB90 exhibited a denser and comparatively more soggy granular crumb structure, unlike a typical open and airy structure found in bread crumbs (Figure 2e).

3.2 Moisture content analysis

The moisture content of the SDB is a critical factor for determining its qualities, such as texture, flavor, and shelf life. This study is based on the analysis of SDB when different hydration levels were employed; hence, the samples were prepared using hydration levels ranging from 70 to 90%. Figure 3 depicts the moisture content of the samples. SB70 showed the lowest moisture content, which can be accounted for the lower initial hydration and better moisture loss during baking. The moisture content of SB75 and SB80 was higher than SB70 (p < 0.05) due to better water absorption by starch and gluten at the said hydration levels. However, SB75 and SB80 showed similar moisture content (p > 0.05), even though the moisture content of SB80 was meagerly higher than SB75. Similarly, in SB80, the moisture content was statistically identical to SB85 despite the higher moisture content in SB85 (p > 0.05). SB90 had the highest moisture content among all the samples, which can be attributed to the presence of excess unbound water that could not escape during baking at such a high hydration level (p < 0.05).

Figure 3

Graphs showing the moisture content of the samples. Bars with different letters are statistically different (p < 0.05).

3.3 TPC

Phenolic compounds are a class of antioxidants that are beneficial to the human body. Therefore, conducting a TPC test can assist in evaluating the antioxidant qualities of SDB [24,25]. The TPC of the SDB samples was determined accordingly. Figure 4 describes the results of the TPC. Overall, an increase in the TPC values was observed, along with an increment in the moisture levels of the SDB samples. SB70, containing 70% moisture, had a TPC value of 1.34 mg·g⁻¹. The elevation of moisture content in SB75 resulted in a significantly higher TPC value (1.54 mg·g⁻¹). Subsequently, the TPC of SB80, SB85, and SB90 exhibited a higher value compared to SB70 and SB75 (p < 0.05). However, the TPC values of SB80, SB85, and SB90 were similar (p > 0.05). The observed correlation between the rise in TPC and moisture content can be attributed to the fermentation process of SD. During SD fermentation, the enzymatic activity of phenolic acid esterase results in an elevation of free phenolic acid levels, thus leading to an overall rise in TPC [26]. Additionally, few studies have reported that an increase in moisture content may enhance the solubility of phenolic compounds, and hence its extractability and content in food samples [27].

Figure 4

Graph showing the TPC of the samples. Bars with different letters are statistically different (p < 0.05).

3.4 Electrical impedance spectroscopy (EIS)

EIS is a methodology used to assess the electrical characteristics of materials by applying a sinusoidal test voltage or current to the samples [16,28]. The impedance vs frequency plots of the samples showed an exponential decay as the injecting current frequency was increased (Figure 5). Due to space charge polarization at low frequencies, impedance variation differs between lower and higher frequencies [29]. Moreover, this impedance variation can be attributed to the capacitive nature of the impedance-measuring setup [30]. With regard to bakery systems, EIS offers a non-destructive methodology to monitor hydration-mediated structural changes, with immense practical implications for studying crumb integrity and several other properties [31]. Therefore, EIS has emerged as one of the powerful tools in understanding the physicochemical attributes of complex food entities, like SDB, which can be used to create bakeries with desirable organoleptic attributes. Compared to the other samples, SB70 had the highest impedance. The impedance values correlate well with the moisture analysis, where it was found that SB70 had the lowest amount of moisture content, thereby resulting in lower conductance. Similar findings have been documented while analyzing the impedance profiles of carrot slices during the drying process [32]. On the other hand, as the moisture content was raised in the remaining four samples (SB75, SB80, SB85, and SB90), similar impedance values were observed. However, a careful observation of the impedance profiles indicated that SB80 had the lowest impedance. The reason for this could be that the open and uniform crumb structure of SB80 allows for better movement of ions, which results in lower impedance.

Figure 5

Graphs showing the impedance profiles of various samples.

3.5 Microscopic analysis

Microscopic examinations were performed to observe the surface microstructure of the samples’ crust and crumb. The micrographs of the crust of all the samples exhibited a high degree of similarity. All the samples had a caramelized yellow appearance, as shown in Figure 6. This appearance can be accounted for by the formation of melanoidins (a group of anionic and colored compounds) produced during the Maillard reaction. The Maillard reaction is responsible for various properties of the SDB, including color, flavor, and aroma [33]. The micrograph of the crust of SB70 revealed a uniformly smooth structure. However, in the case of SB75, the presence of granular structures was observed. SB80 showed a uniform surface with few irregularities. It was observed that the smoothness of the crust improved in SB85 and SB90 as the moisture level gradually increased.

Figure 6

Micrographs of the crust of the samples. (a) SB70, (b) SB75, (c) SB80 (d) SB85, and (e) SB90 (scale bar: 500 µm – for all micrographs).

Subsequently, the crumb of the samples was also subjected to analysis. The observed samples exhibited the presence of prominent pores within the crumb (Figure 7). SB70 showed the presence of closed pores. This closed structure of the crumb in SB70 may be attributed to its lower moisture levels than the other samples. As the hydration level was increased to 75%, open yet small-sized pores were observed. Thereafter, an enhanced porosity level became evident when hydration was increased to 80% (SB80). The pore size and its distribution within the crumb decreased in the case of SB85. Likewise, in the case of SB90, it was observed that the increased hydration level resulted in the formation of a smooth and closed crumb structure with tightly sealed pores.

Figure 7

Micrographs of the crumb of the samples. (a) SB70, (b) SB75, (c) SB80, (d) SB85, and (e) SB90 (scale bar: 500 µm – for all micrographs).

3.6 Colorimetry and reflectance analysis

One of the most important ways to assess the sensory qualities of food is through color analysis. The CIELab colorspace offers a system for measuring color as part of its defined and standardized framework. This protocol is widely used to perform color analysis on various food products. L* values, also called brightness or luminous values, cover a range of grayscale numbers from 0 (black) to 100 (white). With a numerical range of −120 to +120, the chromatic components are represented as a* and b* in the CIELab color space. Deviation from the green axis denotes a change toward the blue spectrum, whereas repositioning along the positive a* axis denotes a transition toward the red spectrum. Also, moving along the positive b* axis indicates a movement toward the yellow color spectrum, while moving along the negative b* axis indicates a shift toward the blue color spectrum [34].

The average a* values for all the SDB samples exhibited minor variations. It was observed that the a* values ranged from 14 to 17. SB70, SB75, and SB80 showed similar a* values (Figure 8). Thereafter, the a* value of SB85 was found to be similar to SB70 and SB75. Finally, even though SB90 had the highest average a* value, it did not differ statistically from the a* values of other samples (p > 0.05) (Figure 8). Another study examining the physical and techno-functional qualities of a combination of breadcrumbs and yellow pea flour found a similar pattern. The study’s results showed that the a* values also increased when the moisture content increased [35].

Figure 8

Graphs showing colorimetric analysis and visible spectral analysis of the samples. (a) L* values, (b) a* values, (c) b* values, (d) WI, (e) YI, and (f) reflectance vs wavelength plot. Bars with different letters are statistically different (p < 0.05).

Analysis of the b* values of the samples indicated that the b* values were in the range of 54–65. This indicates the considerable contribution of the yellow color in the samples. SB70 had the lowest b* value. An increase in the water content increased the b* value in all other samples compared to SB70 (p < 0.05). b* value of SB75 was significantly higher than SB70. SB80, SB85, and SB90 showed similar b* values (p > 0.05), which were higher than SB70. Overall, an increasing trend in b* values was observed as the water content in the dough was increased (Figure 8). However, increasing hydration beyond 80% did not significantly change the yellow color intensity. An increase in the yellow color development trend with an increase in the moisture content has been previously mentioned in [35].

Subsequently, the WI and YI were determined using the L*, b*, and a* values. The observed WI values for the samples ranged between 61 and 76. SB70 showed the lowest WI value compared to all other samples (p < 0.05). Afterward, a notable increase in the WI value was seen compared to SB70 as the moisture content increased. The WI values of all other samples (SB75, SB80, SB85, and SB90) were alike (p > 0.05) regardless of the increase in moisture content (Figure 8). YI values of the samples ranged from 108 to 150, indicating a considerable presence of yellow hue in the samples. The yellow color noticed in WWF might be linked to lutein [36]. The YI value of SB70 resembled the YI values of SB75 and SB80 (p > 0.05). Furthermore, the YI value of SB85 was similar to the YI values of SB75 and SB80. There was a remarkable decrease in the YI value of SB90 compared to other samples (p < 0.05) (Figure 8). Thus, it is evident that the overall change in the moisture content of the food product affects the color parameters [37].

The reflectance analysis concerning food products involves an analysis of the color of the food products when exposed to visible-range electromagnetic radiations of different wavelengths. The reflectance profile of the visible light helps to evaluate the quality, freshness, and maturity of the food products [38]. Figure 8(f) shows the variation of reflectance spectra of all the samples. It was observed that all the samples showed a sigmoidal reflectance profile. At lower wavelengths, reflectance values for all the samples were lower, which increased in the mid-wavelengths and became constant at higher wavelengths. Among the prepared samples, it was noted that SB70 exhibited the lowest reflectance value across all wavelengths of the visible spectrum. An increase in reflectance value was seen by increasing the hydration level to 75% (SB75). Upon further increasing the hydration level to 80% (SB80), a significant elevation in the reflectance value was noted. SB80 showed the highest reflectance spectral values among all the samples. It has been previously proposed that reflectance values can be correlated with the uniformity of the porous structures [39]. Interestingly, SB80 was observed to have the most uniform crumb structure out of all the samples. When the hydration level was increased to 85% (SB85), a higher reflectance value than SB75 was observed at lower wavelengths. However, at wavelengths over 500 nm, the reflectance value of SB85 was lower than that of SB75. This resulted in a crossover between the reflectance curves of SB75 and SB85 in their exponential phases, as shown in Figure 8f. Finally, when the hydration level was increased to 90% in SB90, it was observed that the reflectance was lower than that of SB80. However, the reflectance values of SB90 were more significant than the reflectance values of SB70, SB75, and SB85. According to a study by Dong et al., when the moisture content is increased to an extent, it facilitates enhanced movement of amylopectin (a constituent of starch), resulting in starch crystallization [40]. This crystallization process can be correlated to an increase in the reflectance value in SB70, SB75, and SB80 with a corresponding increased moisture content [41]. In general, starch crystallization is generally favored at lower moisture content. Suh et al. reported that starch crystallization can also occur at higher moisture content when starch is mixed with other ingredients or subjected to higher temperatures [42]. This phenomenon can be reasoned towards the unexpected increase in the reflectance values in SB90.

3.7 Texture analysis

TPA is a crucial evaluation of bread products. The TPA analysis facilitates the assessment of the structural qualities, mouthfeel, and overall sensory experience [43]. Hence, TPA was performed to determine several textural parameters such as hardness, chewiness, cohesiveness, gumminess, and resilience of the SDB sample. Hardness is the force required to deform a product [44]. A negative correlation was detected between the sample’s moisture content and hardness, possibly due to increased moisture content from SB70 to SB90. The hardness of SB70 exhibited a comparable hardness to that of SB75, whereas SB75 also showed a resemblance in hardness to SB80 (p < 0.05). Afterward, SB80 displayed a hardness value akin to SB85; ultimately, SB85 showed a similar hardness to SB90 (p < 0.05) (Figure 9a).

Figure 9

Graphs showing bar plots of the TPA parameters. (a) Hardness, (b) cohesiveness, (c) gumminess, (d) chewiness, and (e) resilience. Bars with different letters are statistically different (p < 0.05).

Following that, the second parameter evaluated was the cohesiveness of the samples. Cohesiveness is the ratio of the first deformation area to the second deformation area [45]. It measures how well the food holds together during its second deformation compared to its resistance during the initial deformation. The cohesiveness value of all the samples was in the range of 0.25–0.65. SB70 showed the lowest cohesiveness. Afterward, as the moisture content increased to SB75, a significant rise in cohesiveness values was observed. SB75 showed similar values to SB80 and SB85 (p > 0.05). However, SB80 showed cohesiveness similar to that of other samples except for SB70. The low cohesiveness of SB70 can be attributed to its low moisture content. As the moisture content of bread decreases, its hardness increases, indicating a rise in the cohesive force within the crumb structure. Consequently, there was a reduction in the bread’s cohesiveness, resulting in increased ease of separation and accelerated decomposition (Figure 9b) [46].

Gumminess is characterized by the energy needed to break the food product fully before swallowing [47]. An overall increase in its values can be observed with an increase in moisture content (Figure 9c). SB70 showed the lowest gumminess values, while SB85 showed the highest. As the moisture content was elevated, gumminess also increased till SB85. In the case of SB90, the gumminess remained the same as that of SB80 and SB85. Lastly, the chewiness and resilience of the samples were calculated (Figure 9d and e). Chewiness resembles the energy needed to masticate the food [48]. It showed a similar trend as the gumminess. Resilience is defined as the ability of the sample to regain its shape upon compression [49]. The resilience of all the samples was similar (p > 0.05) except SB70, which had the lowest value (p < 0.05).

Stress relaxation is a commonly used technique in the food industry to analyze and quantify the viscoelastic characteristics of various food items. The maximum force (denoted by F ₀) achieved in the stress relaxation profile is used to predict the firmness of the samples (Figure 10). Herein, the F ₀ value of SB70, having a 70% hydration level, was 243.492 ± 9.065 g. Afterward, as the hydration level was raised to 75% (SB75), a significant reduction in the F ₀ value was observed (p < 0.05). Interestingly, a further increase in the hydration level to 80% (in SB80) resulted in a substantial rise in the F ₀ value, the highest among all the samples (p < 0.05). According to a study by da Rosa Zavareze and Dias, an increase in temperature and moisture content can lead to a greater level of starch crystallization, which can influence the mechanical characteristics of food items [50]. After SB80, it was observed that the F ₀ value exhibited a monotonous decline as the hydration levels increased up to the highest hydration level. The F ₀ values of SB70 and SB85 and SB75 and SB90 were statistically similar (p > 0.05). Further, the F ₆₀ values corresponding to the residual stress at the end of the relaxation profile followed a similar pattern to that of F ₀. The F ₀ and F ₆₀ values were subsequently employed to compute the percentage of stress relaxation (% SR). SB70 showed the highest % SR (p < 0.05), after which a significant decrease in its value was observed. SB75, SB80, SB85, and SB90 exhibited comparable % SR values, indicating similar stress relaxation created within these samples (p > 0.05). A lower stress relaxation has been associated with the formation of bread samples with superior quality in terms of texture, crumb structure, and overall sensory characteristics [51].

Figure 10

Graphs showing the stress relaxation profiles and bar plots of the parameters of the prepared samples. (a) Stress relaxation profiles, (b) F ₀, (c) F ₆₀, and (d) % SR. Bars with different letters are statistically different (p < 0.05).

The stress relaxation data were further analyzed using Weichert’s model of viscoelasticity (Eq. (5)). This model offers a versatile framework for characterizing the viscoelastic nature of the samples by analyzing stress relaxation profiles. The model incorporates several Maxwell units, which consist of springs and dashpots connected in parallel [52]. In our study, this model was utilized to elucidate the viscoelastic properties of SDB samples with two distinct characteristic times. Table 3 enlists the P ₀, τ ₁, and τ ₂ values of the samples. The P ₀ value indicates the residual force and elastic characteristics exhibited by the samples [18]. For SB70, the P ₀ value was found to be 0.47. An increase in the P ₀ value was observed as the hydration was raised to SB75 (p < 0.05). Further increase in hydration levels had no impact on P ₀ values; hence, the remaining samples exhibited values similar to SB75. The variables τ ₁ and τ ₂ refer to instantaneous and delayed relaxation times, respectively. Instantaneous relaxation time (τ ₁) indicates how bread undergoes stress relaxation and structural modifications in response to an externally imposed pressure or deformation. The τ ₁ and τ ₂ values of all the samples exhibited statistically similar results, indicating that the molecular arrangement within the samples was occurring at a similar rate [18]. It might have happened due to a resilient gluten network that was strong enough to control the relaxation processes, resulting in similar rates of molecular reorganization [53].

(5) P ( t ) = P 0 + P 1 exp − t τ 1 + P 2 exp − t τ 2 ,

where P(t) = variation in force concerning time, P ₀ = residual force at the termination of the relaxation phase, P ₁ and P ₂ = spring constants, and τ ₁ and τ ₂ = time constants (s).

Table 3

Different parameters of Weichert modeling concerning different samples

	P ₀	P ₁	τ ₁ (s)	P ₂	τ ₂ (s)	R ²
SB70	0.47 ± 0.00^a	0.24 ± 0.06^a	11.16 ± 8.94^a	0.28 ± 0.06^b	5.79 ± 8.57^a	0.99
SB75	0.62 ± 0.00^b	0.16 ± 0.02^a	10.77 ± 15.6^a	0.18 ± 0.02^a	14.96 ± 12.55^a	0.99
SB80	0.65 ± 0.05^b	0.17 ± 0.01^a	13.2 ± 10.52^a	0.18 ± 0.04^a	7.63 ± 0.91^a	0.99
SB85	0.59 ± 0.01^b	0.19 ± 0.02^a	20.23 ± 16.71^a	0.21 ± 0.02^ab	6.92 ± 8.56^a	0.99
SB90	0.63 ± 0.01^b	0.18 ± 0.01^a	7.26 ± 0.53^a	0.18 ± 0.02^a	13.45 ± 10.74^a	0.99

Different letters signify statistical differences among the samples column wise for each parameter (p < 0.05).

3.8 FTIR analysis

FTIR analysis was conducted on all bread samples to acquire IR spectra within the wavelength range of 4,000–500 cm⁻¹. The obtained IR spectra can be categorized into two distinct regions, namely the functional region (wavenumber: 4,000–1,000 cm⁻¹) and the fingerprint region (wavenumber: <1,000 cm⁻¹) [54]. Prominent peaks were observed at wavenumbers 3,407, 2,934, 2,850, 1,642, 1,146, 1,014, and 934 cm⁻¹ in all the SDB samples (Figure 11). First, the notable broadband peak observed at 3,307 cm⁻¹ can be associated with the stretching vibrations of –OH groups (Rohman et al., 2020). The presence of moisture and the phenolic compounds (e.g., Ferulic acid, phytic acid, flavonoids, etc.) in the samples can account for the occurrence of this peak. Phenolic compounds are characterized by hydroxyl (−OH) groups [55,56]. Variations in this peak intensity were observed across the SDB samples. The results indicate that SB90 had the maximum intensity, whereas SB70 exhibited the lowest intensity. This observation can be correlated with the outcome of TPC (Section 3.3). During the determination of the TPC of SDB samples, it was observed that SB70 showed the lowest TPC, whereas SB80, SB85, and SB90 showed similar and comparatively higher values.

Figure 11

FTIR spectrum of SDB samples.

Further, two shoulder peaks with comparatively lower intensity were noticed at 2,934 and 2,850 cm⁻¹. These peaks can be associated with C–H bonds in aliphatic hydrocarbons. The presence of these bonds can be attributed to various components (e.g., phenolic acids, flavonoids, and vitamin E) present in whole wheat SB. These compounds may lead to the formation of C–H bonds [57]. The peak observed at a wavenumber of 2,934 cm⁻¹ can be attributed to the asymmetric stretching vibration of −CH₃ groups, while the peak observed at 2,850 cm⁻¹ is associated with the symmetric stretching vibration of −CH₂ groups [54]. At ∼1,642 cm⁻¹, a sharp peak was observed in the spectra that indicates the presence of C═C (double bonds) in alkenes [58]. Later, three distinct peaks were seen at 1,146, 1,014, and 934 cm⁻¹ in the fingerprint region of the IR spectra. The former two peaks can be attributed to the symmetric and asymmetric stretching vibrations of C–O bonds commonly found in alcohols, phenols, and ethers. This also confirms the presence of phenolic content in our samples [59].

Numerical deconvolution of the obtained FTIR spectra was performed for water and starch regions to separate and accurately identify the hidden peaks [21]. It allows for determining the area under the curve (AUC), which can be related to the concentration of respective components [19]. The wavenumber region from 3,800 to 3,000 cm⁻¹ is called the “water region.” Peaks observed within this region indicate the extent of interaction between water molecules and the gluten network [60]. Numerical deconvolution of this region resulted in five Gaussian peaks at 3,088 (peak 1), 3,208 (peak 2), 3,381 (peak 3), 3,540 (peak 4), and 3,619 (peak 5) cm⁻¹ (Figure S1a). The observed peaks were at a deviation of approximately ±10–15 cm⁻¹ concerning the peaks identified by Peng et al. and Laurson et al. [20,21]. Such observed variations can be attributed to the distinct composition of the sample and the specific method of its preparation [61]. Peak 1 corresponds to the stretching vibrations of O–H bonds and strong hydrogen bonding between molecules [62]. It was observed that peak 1 exhibited a relatively small intensity across all samples. The AUC value of SB70 corresponding to peak 1 was similar to all the samples. An increase in hydration level up to 75% in SB75 did not affect the AUC value and remained identical to that of SB70 (p > 0.05). Subsequently, in SB80, the AUC value significantly decreased compared to SB75 (p < 0.05). Lastly, AUC values of SB85 and SB90 were found to be similar to SB80 (p > 0.05). Overall, the low intensity of peak 1 suggests that the content of strongly bonded water molecules in the samples is relatively low. Further, peak 2 is linked to the oscillations arising from the presence of tightly interconnected water molecules via hydrogen bonding [19]. The content of peak 2 is comparatively higher in all the samples than peak 1. The AUC observed for SB70 was ∼35%. SB75 also showed a similar value for peak 2 compared to SB70 (p > 0.05). Increasing the hydration level to 80% in SB80 and 85% in SB85 decreased the AUC value significantly compared to the other samples (p < 0.5). Lastly, in SB90, peak 2 content increased considerably compared to SB85; however, the value was similar to SB70. Based on the findings, it can be inferred that SB70, SB75, and SB90 contain more tightly interconnected water molecules. Interestingly, the intensity of peak 3 was the highest among all other peaks. It suggests the existence of a substantial quantity of water molecules exhibiting relatively weak intermolecular hydrogen bonding [62]. Variation of the AUC of peak 3 followed a similar trend as that of peak 2. According to Shengwei et al., peak 4 is associated with the symmetric vibrations of the hydroxyl group, explicitly concerning the non-hydrogen-bonded or free water molecules [41]. SB70 and SB75 showed similar peak 4 content (p > 0.05). Although peak 4 content significantly decreased when hydration reached 80% in SB80 (p < 0.05), the value again increased as the hydration value was further increased in SB85 and SB90 (Figure S1b). From this result, it can be concluded that SB80 had the least free water molecules. The possible reason for this finding is that, at moderate levels of hydration, gluten has the ability to effectively attach to water molecules, integrating them into its structure and thereby decreasing the amount of unbound water molecules [63]. At last, peak 5 corresponds to asymmetric vibrations of non-hydrogen-bonded water molecules [64].

According to the study reported by Garcia-Valle et al., 1,070–950 cm⁻¹ is a fingerprint region of molecular vibrations related to the starch molecules [65]. In our study, we observed three distinct peaks at 1,045, 1,021, and 998 cm⁻¹ in the starch region of all the samples (Figure S2a). As per the literature, peaks at around 1,047 cm⁻¹ represent the crystalline region of the starch, which is related to the stretching vibration of the C–O–C bond. The peak observed at 1,022 cm⁻¹ represents an amorphous structure, whereas bands between 1,000 and 995 cm⁻¹ represent hydrated crystalline structures [66]. Thereafter, we calculated two crucial ratios that quantify the starch structures. These ratios, 1,045/1,021 (ratio 1) and 995/1,022 (ratio 2), were computed for all the samples as per the procedure followed by Garcia-Valle et al. [65]. Ratio 1 denotes the ordered degree of starch’s external structure. It serves as a quantitative measure for assessing the level of organization in the external starch. A larger ratio signifies a greater order of organization [67,68]. Figure S2b represents the variation of the ratios obtained in the starch region. Ratio 1 was similar for all samples except SB90, which showed a significantly higher value than the rest (p < 0.05). This finding suggests that SB90 exhibits a more organized structural arrangement of starch granules and a greater fraction of crystalline areas inside the starch granules. Ratio 2 is a quantitative measure for assessing the relative extent of amorphous and crystalline regions [69]. For ratio 2, SB70 showed a similar value to SB75 (p > 0.05). The ratio 2 value increased significantly in SB80 as the hydration level increased (p < 0.05). SB85 and SB90 showed a similar value to that of SB80 (p > 0.05). The results indicate increased complexity of crumb structure with both ordered and disordered regions, with an increase in the hydration level above 75% [68,70].

3.9 Swelling study

The SI can be indicative of the texture quality of the SDBs. In general, a higher SI indicates a more pronounced gelatinization of starch, which can divulge information on the textural quality of bread [71,72]. Variation in moisture content in the SDBs was found to affect the SI considerably (Figure 12a and b). Initially, there was a gradual increment in the SI of SB70, which continued till 130 min. After that, the SI values remained constant till 250 min. At the end of 300 min, the SI of SB70 was 34.55%. Compared to SB70, SB75 swelled quickly in the starting period, following which the swelling capacity increased at a slower pace and reached a constant value (26.80%) at ∼175 min. Interestingly, SB80 and SB85 exhibited rapid swelling within 10 min following water immersion. However, beyond this time frame, the SI values of both samples were found to be equivalent and remained steady afterward. At the end of the experiment, while SB80 had an SI of 97.13%, SB85 had an SI of 95.92%. A further increase in hydration resulted in a significant fall in the SI values of SB90. These observations indicate that the swelling capacity or the potential to absorb water increases till a certain level of hydration, after which the capacity decreases. Similar results were observed in a study by González-Torralba et al., who assessed the influence of temperature and relative humidity during storage on wheat breadmaking quality. This study found that the SI of whole wheat bread increased with a concurrent rise in the moisture content, which can be reasoned for the increment in the hydration of gluten protein in the dough [73]. In another study, where the effect of moisture absorption capacity on the operational characteristics of gluten was analyzed, it was found that gluten hydration results in more water uptake. This causes an increase in its flexibility and extensibility. Hydration initiates the activation of wheat gluten proteins, promoting the interaction between gliadin and glutenin proteins. This interaction leads to the formation of a cohesive and viscoelastic gluten matrix, and the development of this gluten network increases the swelling capacity of bread samples [63]. In our case, SB90 showed lower moisture content than SB80 and SB85. This might have happened due to the saturation of flour granules, which limited their ability to absorb water further [74].

Figure 12

Graphs showing (a) variation of SI of samples for 300 min (5 h) and (b) SI of samples at the end of the experiment. Bars with different letters are statistically different (p < 0.05).

4 Conclusion

This article thoroughly analyzes how different levels of hydration in the dough affect the quality of SDB when Kombucha SCOBY is utilized as a natural leavening agent. In this work, the novel method helped decrease the fermentation duration from 7 to 10 days to a mere ∼16 h, demonstrating a notable advancement in SDB-making technology. The findings of this study indicate that the best starch crystallization and overall bread quality were attained at the hydration level of 80%. This optimal hydration level resulted in the formation of SDB with desirable structure and distinct pores, leading to a desirable texture and consistency. At the hydration levels below 80% (SB70 and SB75), the restricted water availability likely curbed gluten extensibility, diffusion of enzymes, and so forth, which resulted in a diminished phenolic extractability and tighter crumb structure, owing to the lack of softness and airiness at a level required for the preparation of SDB with optimal organoleptic attributes. On the contrary, although the water content was high in SB85 and SB90, the dough matrix could not maintain the desired consistency, leading to debilitated crumb architecture and contributing to the degradation of mechanical integrity. SB80, out of all the samples, attained a delicate equilibrium between water availability for the action of enzymes and a robust gluten network needed for optimal structural stability. Also, a positive correlation between higher hydration levels and increased TPC was observed, leading to increased antioxidant activity. TPCs were significantly higher in SB80, SB85, and SB90 than in SB70 and SB75 but interestingly similar across SB80, SB85, and SB90. This is essential for promoting health benefits such as enhanced disease prevention and greater general wellness. Further, SDB with 80% hydration showed the highest SI, suggesting an ideal equilibrium between moisture content and the capacity of SB80 to retain water without becoming excessively dense or soggy. SB80 and SB85 exhibited rapid swelling within 10 min, with SI values stabilizing at 97.13 and 95.72%, respectively. Notably, the 80% hydration level significantly improved texture and structural integrity. The stress relaxation study revealed that SB80 had the highest F ₀ value. This reflects the improved initial resistance to deformation property, which emphasizes the formation of an optimum gluten-starch network in SB80. Therefore, this study highlights the biochemical effects of SCOBY on SDBs and delves deep into improving the quality and nutritional value of food in bakeries. The implications of these discoveries for improving dietary choices are substantial, indicating a promising path for future research and advancements in the field of food science. Furthermore, the experimental results showed how different material methods can be successfully applied to evaluate the novel food composition characteristics. Overall, it could be observed that SB80 represented all the desirable characteristics of optimal porosity, structural cohesiveness, and other attributes that clearly distinguish it from the other samples in terms of the organoleptic properties as a whole. Though we have gained promising results, there is a need for in-depth analysis to delineate the effect of Kombucha SCOBY on SDBs as a whole, including sensory analysis, biochemical tests like cytotoxic analysis, microbial shelf life studies, proximate analysis, in vitro starch digestibility tests, and so forth.

# These authors contributed equally to this work and should be considered first co-authors.

Acknowledgments

The authors acknowledge the National Institute of Technology Rourkela for providing the necessary resources and lab facilities crucial for the successful completion of this study and the Department of Science and Technology, Government of India, for the financial support.

Funding information: This research work has been supported by the funding received from the Department of Science and Technology, Government of India (Sanction Number: DST/INT/Philippines/P-01/2022(G), 29.12.2022).
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Conflict of interest: Maciej Jarzebski, who is the co-author of this article, is a current Editorial Board member of Reviews on Advanced Materials Science. This fact did not affect the peer-review process. The authors state no other conflict of interest.
Data availability statement: The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.

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Received: 2025-03-26

Revised: 2025-05-05

Accepted: 2025-07-08

Published Online: 2025-08-05

This work is licensed under the Creative Commons Attribution 4.0 International License.

Supplementary material

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https://doi.org/10.1515/rams-2025-0133

Keywords for this article

Kombucha SCOBY; sourdough bread; starch crystallization; hydration optimization

Creative Commons

BY 4.0

Selected materials techniques for evaluation of attributes of sourdough bread with Kombucha SCOBY

Article

Abstract

Graphical abstract

Abbreviations

1 Introduction

2 Materials and methods

2.1 Materials

2.2 Methods

2.2.1 Preparation of starter

2.2.2 Making of SDB

2.2.3 Moisture analysis

2.2.4 TPC

2.2.5 Impedance analysis

2.2.6 Microscopic analysis

2.2.7 Colorimetric and reflectance analysis

2.2.8 Texture analysis

2.2.9 FTIR analysis

2.2.10 Swelling study

3 Results and discussion

3.1 Visual and physical appearance

3.2 Moisture content analysis

3.3 TPC

3.4 Electrical impedance spectroscopy (EIS)

3.5 Microscopic analysis

3.6 Colorimetry and reflectance analysis

3.7 Texture analysis

3.8 FTIR analysis

3.9 Swelling study

4 Conclusion

Acknowledgments

References

Supplementary Material

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