Impact of fermented wheat flour on the quality of dried white salted noodles: cooking, physicochemical, structural breakdown, microstructure and sensory evaluations

Impact of fermented wheat flour on the quality of dried white salted noodles: cooking, physicochemical, structural breakdown, microstructure and sensory evaluations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Impact of fermented wheat flour on the quality of dried white salted noodles: cooking, physicochemical, structural breakdown, microstructure and sensory evaluations Muhammad Lubowa, Shin-Yong Yeoh, Viklawan Fricher, Ojukwu Moses, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4504789/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigated the physicochemical properties, cooking characteristics, structural breakdown, microstructure, and sensory qualities of dried white salted noodles with varying proportions of fermented wheat flour (FWF). The noodle formulations included 100% commercial wheat flour (100WF), 75% wheat flour with 25% FWF (75WF:25FWF), 50% of each (50WF:50FWF), and 25% wheat flour with 75% FWF (25WF:75FWF). Incorporating FWF reduced the optimum cooking time, cooking yield, pH and lightness values but increased the redness and yellowness values. Noodles with over 50% FWF exhibited greater cooking losses, increased breakability and lower textural and structural breakdown values. Scanning Electron Microscopy revealed that noodles with over 50% FWF had a weakened gluten structure with larger, more irregular pores. In contrast, 75WF:25FWF maintained similar cooking performance and structural integrity as 100WF, both featuring a compact and dense gluten network with smaller pores, which not only required significant effort to break down but also contributed to superior cooking performance and excellent texture. Proximate composition analysis revealed that 75WF:25FWF had lower moisture and higher fibre content. Despite lower sensory scores, the textural differences were not significantly noticeable. Incorporating FWF could potentially enhance the nutritional value of noodles by increasing fibre content while maintaining acceptable cooking and textural qualities. Biological sciences/Biochemistry Biological sciences/Biochemistry/Carbohydrates physicochemical sensory structural breakdown microstructure dried white salted noodles fermented wheat flour Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1.0 Introduction Wheat ( Triticum aestivum L.) ranks among the crops with the highest global yields, with an annual consumption reaching 791.2 million tons. Due to its distinctive capacity for gluten formation, wheat flour has become one of the most widely utilized ingredients in the food industry 1 . Kernels of wheat are sources of numerous phenolic substances, including ferulic, vanillic, gentisic, caffeic, salicylic, syringic, p-coumaric, and sinapic acids 2 . The rise in production of wheat emphasizes its global importance and its key contribution in the development of flour-based goods, such as pastries, pasta, doughnuts, breakfast cereals, rolls, and extruded snacks 3 . Consequently, wheat flour serves not only as a significant source of energy but also as an essential nutritional component of the human diet 1 . The majority of the micronutrients (vitamins and minerals) are located in the endosperm and is typically removed along with the bran in the process of producing refined wheat flour through conventional milling techniques 4 . As a result, wheat flour often lacks essential micronutrients, leading to various health issues globally 1 . Noodles have been a fundamental part of diets for over 4,000 years, particularly in Asian countries. Among the various types available, white salted noodles (WSN) are favoured for their superior taste, colour, and texture. WSN are produced in a range of formulations and shapes, with the dough comprising a blend of wheat flour, water, and salt 5 . Noodles are categorized as fresh (32% – 38% moisture content) and dried (< 12% moisture content) noodles based on their moisture levels. Due to their ease of storage, convenience, affordability, and versatility, dried noodles are becoming increasingly popular among consumers for daily consumption 6 . Nonetheless, the primary composition of most dried noodles is refined wheat flour, which is deficient in critical nutrients, including dietary fibre, minerals, vitamins, and bioactive compounds. Additionally, dried noodles produced from refined wheat flour exhibit a high digestion rate and starch content 7 . Prolonged consumption of such noodles is associated with an elevated risk of developing type 2 diabetes, obesity, and other chronic health conditions 8 . Fermentation, an ancient and cost-efficient food processing technique, not only extends shelf life and enhances sensory attributes but also significantly improves the digestibility of proteins and carbohydrates, along with the bioavailability of vitamins and minerals 9 . Solid-state fermentation enhanced the functionality, antioxidant and bioactive properties of wheat varieties 2 , 3 . Moreover, a mixture of probiotics had been used to ferment wheat dough as a novel therapeutic approach for celiac disease. Celiac Disease represents the most severe form of gluten intolerance and affects approximately 1% of the population. 10 . The enhanced functionality of bioprocessed whole wheat flour makes it a promising ingredient for producing functional food 3 . Fermenting wheat dough with lactic acid bacteria increased the levels of carotenoids and bioactive compounds, potentially enhancing health benefits 11 . Crumbly dough has been fermented to produce dried hollow noodles characterized by a quick cooking time, soft and elastic texture, and easy digestibility 12 . To our knowledge, no fermented wheat flour has been used to prepare dried WSN. This study investigated the physicochemical, sensory, structural breakdown preparties and microstructure of dried WSN prepared from fermented wheat flour. 2.0 Materials and methods 2.1 Materials Commercial WF (Cap Sauh) (~ 9% protein), and salt were purchased from Lotus Stores Malaysia Sdn Bhd (Lotus’s Malaysia) (Georgetown, Malaysia). FWF (~ 2.2% protein) was purchased from Deluxe Ingredients Sdn. Bhd (Shah Alam, Malaysia). Other chemicals used in this study (analytical grade) were purchased from Sigma–Aldrich (St. Louis, USA). 2.2 Preparation of wheat noodles The wheat noodles were prepared according to Ojukwu et al. (2023) and Tan et al. (2020) with modifications. The formula of the noodles is shown in Table 1 . All the ingredients were weighted and mixed by a mixer at speed 2 (Kenwood, UK) for 10 min. The dough was then kneaded and left to rest for 30 min. Next, it was rolled out into a thin sheet using a pasta maker (Marcato Ampia, Model 150, Campodarsego PD, Italy) with an initial gap setting at width 0 (2.2 mm) for 5 times, width 1 (2.0 mm), width 2 (1.8 mm), width 3 (1.6 mm), and width 4 (1.4 mm). The sheet was then cut into uniform noodles strands using the same pasta machine with dimensions 1.4 mm in width and 1.1 mm in thickness. Next the noodles were steamed for 10 min before drying in an oven (AFOS T500 dryer, London, UK) at 70°C for 2 h and 100°C for 3 h. The noodles were packaged using sealed packaging and stored for subsequent analysis. Table 1 Formulation of noodles. Ingredients (g) Types of noodles 100WF 75WF:25FWF 50WF:50FWF 25WF:75FWF WF 100 75 50 25 FWF - 25 50 50 Salt 2 2 2 2 Water 40 40 40 40 100WF, noodles with 100% WF, 75WF:25FWF, noodles with 75% WF and 25% FWF; 50WF:50FWF, noodles with 50% WF and 50% FWF, 25WF:75FWF, noodle with 25% WF and 75% FWF. 2.3 Determination of cooking qualities The cooking qualities of the noodles was measured through measurements of their optimum cooking time, cooking yield, and cooking loss along with the assessment of noodle breakability 15 , 16 . Three replicates were made for each type of noodles. Noodle samples (10 g) were cooked in 400 mL of boiling distilled water in a saucepan. Cooking time was defined as the time the white core in the central portion of the noodles strand disappeared upon squeezing the noodle between two slides of transparent glass. The cooking yield, reflecting the water holding capacity during cooking, was calculated using the following formula: $$\text{Cooking yield (%)}=\frac{\text{W}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{n}\text{o}\text{o}\text{d}\text{l}\text{e}\text{s} \text{a}\text{f}\text{t}\text{e}\text{r} \text{c}\text{o}\text{o}\text{k}\text{i}\text{n}\text{g}}{\text{W}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{n}\text{o}\text{o}\text{d}\text{l}\text{e}\text{s} \text{b}\text{e}\text{f}\text{o}\text{r}\text{e} \text{c}\text{o}\text{o}\text{k}\text{i}\text{n}\text{g}}\times \text{100%}$$ Cooking loss was measured by drying 100 mL of the cooking water in an oven at 105°C to a stable weight. Cooking loss was calculated by measuring the weight of solid substances lost in the cooking water from noodles strands. The breakability of noodles was measured using the equation below: $$\text{B}\text{r}\text{e}\text{a}\text{k}\text{a}\text{b}\text{i}\text{l}\text{i}\text{t}\text{y} \left(\text{%}\right) =\frac{\text{W}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{b}\text{r}\text{o}\text{k}\text{e}\text{n} \text{n}\text{o}\text{o}\text{d}\text{l}\text{e}\text{s} \text{s}\text{t}\text{r}\text{a}\text{n}\text{d}\text{s}}{\text{T}\text{o}\text{t}\text{a}\text{l} \text{c}\text{o}\text{o}\text{k}\text{e}\text{d} \text{n}\text{o}\text{o}\text{d}\text{l}\text{e}\text{s} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t}}\times \text{100%}$$ 2.4 Determination of pH The pH values of cooked noodles were determined using a Mettler-Toledo Delta 320 pH meter 16 . Each sample (10 g) were homogenized for 5 min in 100 mL of distilled water and then filtered. pH analysis was conducted after 30 min of waiting. Calibration on the pH meter was carried out before measurement. Three replicates were made for each type of noodles. 2.5 Determination of colour The colour of cooked noodles was measured using a colorimeter (Konica Minota, Model CM 3600d, USA) . International Commission on Illumination (CIE) L* (lightness), a* (redness), and b* (yellowness) values were recorded at random locations on the noodles' surface. Three replicates were made for each type of noodle. 2.6 Texture profile analysis (TPA) The textural properties of cooked noodles were measured using a Texture Analyzer (Stable Micro System, Surrey, England) calibrated with a 5 kg load cell before measurements 14 . Three noodle strands (70m length) were placed in parallel on the middle of the compression plate using pasta firmness rig (HDP/PFS) for analysis. The settings were: Mode, measure force in compression; Trigger type, auto with trigger force of 20 g; Pre-test speed, 2.0 mm/s; Test speed, 0.8 mm/s; Post-test speed, 0.8 mm/s; Strain, 75%; Interval between two compressions, 1.0 s. For every noodle type, two successive compressions were applied and measured thrice, with the values then averaged. Values for hardness, adhesiveness, cohesiveness, springiness, and chewiness were obtained. 2.7 Noodles firmness The firmness of the cooked noodles was determined by employing a TA-XT2 Plus Texture Analyser (Stable Micro Systems, Surrey, England), equipped with a 5 kg load cell and attached to a 1 mm flat Perspex blade 16 . The gap set between the Perspex blade and the robust platform was fixed at 30 mm. The assessment proceeded under the following parameters: Mode: Measure force in compression; Option: Return to start; Pre-Test Speed: 1.0 mm/s, Test Speed: 0.1 mm/s; Post-Test Speed: 10 mm/s; Distance: 4.98 mm; Data Acquisition Rate: 400 pps. To prepare for testing, five noodle strands, each 70 mm in length, were laid out in a straight line, side by side on the centre of the platform, and oriented perpendicular to the blade. The firmness of the noodles was indicated by the highest point on the force-time curve. This procedure was replicated fifteen times for each sample. 2.8 Structural breakdown analysis Structural breakdown analysis was carried out using a texture analyser (model TA-TX2, Stable Micro Systems, Surrey, UK) with a 30 kg load cell 17 . Cooked noodles samples weighing 20 g were tested in 10 mL artificial saliva across three replicates. The pH was adjusted to 7.0 with 0.1 M HCl. The texture analyser settings were as follows: Mode set to measure compression force; Option to cycle until a specified count; Test Speed at 10 mm/s; Post-Test Speed at 5 mm/s; Distance set at 95 mm; Count set for 20 cycles; Data acquisition rate at 2 pps. The results were plotted on a force vs. time graph and analysed using a single exponential decay equation: $${W}_{\left(n\right)} = {W}_{inf}+ {W}_{1}\left.EXP\left(- \frac{n}{{n}_{1}}\right.\right)$$ where W (n) denotes the work performed in each extrusion cycle (n), w inf represents the work per extrusion after numerous (effectively infinite) cycles, w 1 specifies the quantity and strength of the degraded noodle structure, and n 1 indicates the rate at which the work per extrusion decreases as the number of extrusions increases. 2.9 Scanning Electron Microscopy (SEM) The microstructures of all samples were examined using a SEM with a Quanta 650 FEG SEM (FEI Technologies Inc., US) 18 . Prior to analysis, noodle samples were dried at 60°C for 1 h. Dried noodles were then cut and mounted on a sample holder with the fractured side exposed. The cross-sections of the noodles were observed under the SEM at 125× magnification and examined at 5 kV. 2.10 Proximate composition analysis of noodles The composition of 100WF and 75WF:25FWF, including moisture, protein, fat, crude fibre, and ash, was assessed according to the 19 standard procedures. Carbohydrate content was determined using the difference method, which involves subtracting the sum of percentages of protein, moisture, crude fibre, crude fat, and ash from 100. 2.11 Sensory evaluation The study was approved by the University human ethics committee (code number: USM/JEPeM/23110839, Jawatankuasa Penyelidikan Manusia USM (JEPeM)). Informed consent was obtained from all human participants. 30 panellists were Food Technology undergraduate and postgraduate students at Universiti Sains Malaysia. Before the sensory evaluation, all panellists were informed and given written informed consent. 100WF and 75WF:25FWF were prepared for sensory evaluation. Each sample was cooked according to the optimum cooking time and kept in a covered container before being served in a small paper cup in a 4 g portion, with a labelled 3-digit random number, and in random order. Each panellist was required to evaluate each of the noodle’s samples for the five attributes (colour, aroma, texture, taste, and overall acceptability) using a 7-point hedonic scale in which numbers are present (1 = dislike strongly, 2 = dislike moderately, 3 = dislike slightly, 4 = neither like nor dislike, 5 = like slightly, 6 = like moderately, 7 = like strongly). The panellists were provided with tissue paper, an empty cup, and a cup of bottled water to rinse their mouths at the beginning of the evaluation and between evaluations of each sample. 2.12 Statistical Analysis The SPSS 27.0 software (SPSS Inc. Chicago IL, USA) was used to perform analysis of variance (ANOVA) on the data generated. Results were expressed as means and standard deviation. Duncan’s test determined the significant differences ( P < 0.05) among the means. Independent t-test was performed to calculate the data obtained from proximate composition analysis and sensory evaluation. 3.0 Results and discussion 3.1 Noodles description A excellent quality of dried noodles should have a bright, clean, and smooth surface, with noodle strands that are straight and robust, free from any cracks, warps, or splits 20 . During 100WF preparation, the noodles fortified with 100% commercial WF (~ 9% protein) exhibited remarkable handling characteristics in dough kneading, sheeting, noodles strands cutting and steaming, contributed to the added elasticity from gluten. Both the dough and noodles maintained consistently manageable texture, ensuring ease of handling throughout the entire process. Subsequently, 75WF:25FWF comprising 25% FWF showed favourable handling properties during preparation. The dough and noodles were responsive and easy to manage without any complications. Next, 50WF:50FWF consisting of equal proportions of commercial WF and FWF produced a softer and slight sticky dough. This dough demonstrated moderate manageability through the preparation. However, 25WF:75FWF with an increased proportion of FWF resulted in an extremely soft and sticky dough, leading to difficulties during all stages of the process. 3.2 Cooking qualities Good quality of noodles should possess short cooking time, higher cooking yield and low cooking loss 16 . The cooking qualities of noodles are illustrated in Fig. 1 . 100WF contained the highest protein content, which probably contributed to the significantly longest optimum cooking time (Fig. 1 a). Gluten is the main protein (85%) in wheat flour and comprises two components: polymeric glutenin, which gives noodles their elasticity, and monomeric gliadin, which provides viscosity. Both components influence the quality of the noodles 21 . During the noodles-making process, gluten protein experiences a series of dynamic changes, including directional rearrangement, depolymerization, and polymerization. It also induces a three-dimensional network within the wheat dough, with starch granules embedded throughout the gluten matrix. During cooking, starch granules absorb water, causing them to swell. The gelatinized starch and solidified gluten then form a dual-network hydrogel characterized by large pores. Heating facilitates additional polymerization of gluten, particularly through the creation of disulfide (S–S) bonds and other non-covalent interactions. This process can stabilize the gluten network, thereby impacting the textural characteristics of the noodles after cooking 22 . Additionally, Yao et al. (2020) reported that the optimum cooking time for noodles demonstrated a positive correlation with protein content. Their findings align with our results, where the FWF noodles with lower protein content required shorter optimum cooking times. The optimum cooking time of 25WF:75FWF was the shortest ( P < 0.05) among all noodles, probably due to its lower protein content and weaker protein network. In addition, the gas produced by microbial metabolism during wheat flour fermentation resulted in the formation of numerous pores within the noodles. These pores enhanced the contact between water and starch during cooking, consequently reducing the cooking time for FWF noodles 12 . As the ratio of FWF increased in the formulation, more pores were generated within the noodle structure, significantly decreasing the cooking time. The interaction between protein and starch in noodles significantly influences water absorption and optimum cooking time. When noodles are cooked in an excess of water, the starch absorbs water, the hydrogen bonds between the gluten protein and starch begin to deteriorate, which triggers starch gelatinization and protein coagulation 5 . 100WF exhibited the highest cooking yield ( P < 0.05) among all samples, whereas noodles incorporating FWF displayed lower cooking yields, although these differences not being statistically significant across different ratios. Longer optimum cooking time for noodles were linked to a higher cooking yield 5 , a trend observed in the case of 100WF. Moreover, high gluten content enhanced the dough's ability to absorb water due to the formation of hydrogen bonds with water 24 . All FWF noodles showed reduced cooking yields, likely due to their reduced gluten protein content, which impacted their ability to absorb water. Cooking loss refers to the amount of dry matter that is released into the water when noodles are cooked optimally 16 . It primarily occurs from the leaching of starch, soluble protein, and salt, which are released from the breakdown of the protein matrix within the noodles due to the boiling water. The cooking losses of 100WF and 75WF:25FWF were significantly the lowest among all samples, whereas 25WF:75FWF exhibited the highest cooking loss ( P < 0.05). The higher gluten protein content in 100WF and 75WF:25FWF helped trap the starch within a compact and denser gluten network, thus preventing most of it from leaching out during cooking. It is evident that the increasing FWF level led to higher cooking loss. In 25WF:75FWF, the starch embedded within and around the weakened gluten network structure leached into the cooking water easily due to the lower gluten protein level. Fermentation induced hydrolysis of gluten and starch by the microorganisms or their metabolites, increasing the leaching of starch molecules during cooking and resulting in greater cooking loss 12 . Furthermore, research has shown that fermentation caused the surface of starch granules to develop indentations, cracks, and holes. These changes resulted from the breakdown of starch molecules due to organic acids and enzymes produced during fermentation 25 . In this study, all cooking losses were under 10%, meeting the acceptable standards set by the Chinese Agriculture Trade Standards for starch noodles 16 . Significant differences were observed in the breakability of the samples. 100WF and 75WF:25FWF exhibited the lowest breakability ( P < 0.05), which can be attributed to the presence of higher gluten level that strengthened the noodles. Gluten proteins absorb water and swell, forming a network that enhances the physical properties of the dough. They consist of glutenin and gliadin, which are crucial to the dough's structure and viscoelastic properties 24 . Zhao et al. (2020) reported that wheat gluten helped the dough develop a strong gluten network, thereby improving noodle quality. In the case of 50WF:50FWF and 25WF:75FWF, a lower gluten level resulted in a weaker network structure and dough that was difficult to form and inherently weak, as found in Xie et al. (2024)’s study. Similarly, our study observed that increasing the FWF level yielded dough that was soft and weak. 3.2 pH and colour analysis The pH of all samples is exhibited in Fig. 2 a. The pH of 100WF was significantly ( P < 0.05) the highest, aligning with the pH of wheat flour (pH 6.05). Increasing the proportion of FWF in noodles resulted in a significant reduction in their pH, which can be attributed to the acidic pH of FWF (pH 5.73). The conversion of complex organic molecules like carbohydrates into organic acids by enzymes during the fermentation of the grains contributed to the decrease in pH in FWF noodles. During fermentation, enzymes like α-amylase and maltase are activated, which convert starch into simple sugars and cause other changes, including metabolites that lower the pH 3 . All FWF noodles exhibited significantly lower L*, higher a* and b* values compared to 100WF, although no significant differences in L* and b* values were observed among the FWF noodles. Increased light reflection from a greater number of starch granules results in a brighter or whiter appearance 27 . The incorporation of FWF into noodle formulations enhanced the dark, red, and yellow colour attributes of the noodles. 3 noted similar colour changes in fermented wheat flour, attributing these changes to enzyme-driven hydrolysis of macromolecules during fermentation. Furthermore, they reported that the darker colour of wheat flour was associated with increased antioxidant activities, likely due to a higher concentration of phenolic compounds. Specifically, elevated levels of carotenoids, which are pigments ranging in colour from yellow to red or orange, were observed in wheat dough after fermentation by certain L. plantarum strains 11 . Furthermore, the bio accessibility of these carotenoids was enhanced due to their presence in the aleurone layer of the grain, potentially increasing their free concentrations. Notably, the researchers found increased levels of lutein and zeaxanthin—types of carotenoids—in wheat dough fermented with two L. plantarum strains known for producing the C30 carotenoid 4,4-diaponeurosporene. Increasing FWF levels led to a decrease in a* values, possibly due to higher cooking losses (Fig. 1 c), particularly from the leaching of phenolic compounds during cooking. The photos of cooked noodles are shown in Figs. 2 e, f, g and h. 3.3 Textural properties of noodles The FWF ratio in the noodles had a significant influence on the selected textural parameters (hardness, adhesiveness, springiness, cohesiveness, and chewiness) and firmness of noodles. No significant was observed in the adhesiveness and springiness values. Typically, the sequence for textural parameters illustrates a similar trend. Therefore, only hardness value is depicted in Fig. 3 a. It can be outlined as: 100WF, 75WF:25FWF > 50WF:5FWF, 25WF:75FWF. The structure of the cooked noodles deteriorated as the FWF ratio in the formulation increased. 100WF and 75WF:25FWF demonstrated the highest textural parameters significantly, possibly due to the compact gluten network. The quality of dried noodles improved because of a higher degree of protein aggregation during cooking, which retained a denser gluten network and minimized the gelatinization and dissolution of starch. During the drying process, high temperatures cause a swift decrease in the free –SH content of proteins and induces the folding and masking of aromatic amino acid residues (tryptophan). Glutenin and prolamin experience further cross-linking, leading to the formation and enhancement of protein aggregates, and establishing a uniform and dense gluten network structure 28 . When the gluten protein experiences greater polymerization, the resulting complete, continuous, and tight gluten network structure traps the starch, preventing its expansion and leaching, thereby improving the noodles' edible quality 14 . The gluten network imparts structural strength to noodles, yet protein content alone does not fully determine the textural qualities of wheat-based products. Factors such as protein composition, including molecular weight, the presence of disulfide bonds, and the ratio of monomeric to polymeric proteins, can also impact texture. Nonetheless, the specific influence of protein composition on the textural properties of noodles requires additional research 23 . The poor gluten network in 50WF:50FWF and 25WF:75FWF likely contributed to significantly ( P < 0.05) lower textural parameters. An underdeveloped gluten network could diminish the textural quality of noodles 22 . 3.4 Structural breakdown analysis The direct link between structural breakdown properties and FWF highlights their importance for noodles. An entire extrusion cycle includes both downward and upward movements, and the patterns of structural breakdown in the noodles can be observed across 20 extrusion cycles 17 . The MEC parameters derived from the decay curves are presented in Fig. 4 . The FWF ratio significantly impacted the structure breakdown analysis, exhibiting a similar trend. The order was: 100WF, 75WF:25FWF > 50WF:5FWF, 25WF:75FWF. Work 1st, which is the area under each downward extruding motion, indicates the amount of work needed to break down the entire noodles. The work measured in the first extrusion cycle (w 1 ) reflects the amount of effort required to break down the intact noodle and w inf represents work per cycle after an infinite number of extrusions, signifying that the entire structure has been broken down 17 . Both values show a positive correlation with the hardness 29 . n 1 indicates the rate of degradation as the number of extrusions increased. A higher n 1 value implies a slower breakdown rate, suggesting that the samples breakdown slowly 17 . The work and n 1 values for 100WF and 75WF:25FWF are the highest ( P < 0.05) and correlate closely with the textural results (Fig. 3 ). Both types of noodles required more effort to break down their integral structure, likely attributable to their increased hardness and firmer texture, resulting from a denser gluten network. 50WF:50WF and 25WF:75FWF scored the lower work and n 1 values ( P < 0.05), indicating less work required and their high breakdown rate, which corresponds well with their textural results. 3.5 SEM The drying process involves the shrinking of noodles, decrease of surface moisture, outward movement, diffusion, and evaporation of water from the noodles, potentially resulting in the formation of pores of various sizes within the product. The pores affect the rate of moisture diffusion by facilitating the entry of water and heat transfer, thereby accelerating starch gelatinization and decreasing the edible quality of the noodles 28 . During cooking, starch granules absorb water and expand, leading to the formation of a dual-network hydrogel composed of gelatinized starch and solidified gluten 22 . The microstructure of cooked noodles cross section is demonstrated in Fig. 5 . The gluten structures in 100WF (Fig. 5 a) and 75WF:25FWF (Fig. 5 b) were denser, tighter and more compact, featuring numerous small pores due to their higher protein content, which contributed to lower cooking losses (Fig. 1 c). The pores in 100WF ranged from 20.98 to 111.9 µm, whereas those in 75WF:25FWF ranged from 29.49 to 51.6 µm. Liu et al. (2024) reported that the protein tightly surrounded the starch granules, forming a more compact structure with smaller pores. This tight and dense gluten structure is crucial for textural quality and structural integrity, contributing to improved results in textural (Fig. 3 ) and structural breakdown analysis (Fig. 4 ) for both samples. Additionally, the abundance of smaller pores may enhance water absorption during cooking, which is reflected in the higher cooking yield (Fig. 1 b) and reduced breakability (Fig. 1 d) observed in both samples. The weakened gluten network in 50WF:50FWF (Fig. 5 c) and 25WF:75FWF (Fig. 5 d) likely led to increased cooking loss and breakability. Moreover, the presence of larger and more irregular pores in 50WF:50FWF (90.91-136.36 µm) and 25WF:75FWF (98.21-357.14µm) suggest uneven shrinkage during drying, adversely affecting the textural quality of noodles. This effect is evident in both samples, which demonstrated poor outcomes in texture and structural breakdown analysis. Liu et al., (2024) also found that larger pores contributed to increased residual stress and led to uneven protein distribution in dried noodles. 3.6 Proximate composition The samples of 100WF and 75WF:25FWF were selected for proximate composition analysis and sensory evaluation because both demonstrated excellent and positive handling characteristics, being easy to work with and maintaining a manageable texture throughout the process. The pH levels of these samples influence the overall taste and texture of the noodles. Therefore, formulations with desirable pH levels for proximate composition and sensory acceptance are prioritized. Additionally, both samples exhibited higher cooking yield and textural characteristic, lower cooking loss and breakability, which are especially prioritized to ensure superior structural integrity. The proximate composition of 100WF and 75WF:25FWF are presented in Table 2 . The incorporation of FWF influenced all the proximate composition of dried noodles, except for the fat content. The moisture content of 100WF was significantly higher than that of 75WF:25FWF. Yang et al. (2024) reported similar findings, stating that the moisture content of noodles increased with the gluten ratio. They explained that gluten protein possessed a greater capacity for water absorption compared to raw starch, which could increase moisture content in noodles with higher gluten content. Furthermore, increasing the gluten content not only enhances their water retention capabilities during the drying process but also significantly slows the rate of moisture loss during drying phases 20 . The moisture content of both types of noodles were below the 14% threshold set by the Codex Alimentarius Commission for non-fried noodles, making them suitable for extended storage. Lower moisture content extends the shelf life of food products by preventing microbial growth and reducing the risk of spoilage and flour quality degradation 31 . The low fat content of the samples might imply a reduced susceptibility to rancidity, especially given their low moisture content, as suggested by 3 . 75WF:25FWF possessed a higher ash content ( P < 0.05) than 100WF and yielded, which resulted in an increased a* value (Fig. 2 c). The increase in ash content could be associated with the release of bound mineral elements following the breakdown of antinutrient compounds during the fermentation of wheat flour 3 . Flour with a higher ash content reduced the brightness and darken the colour of noodles 27 . The significantly higher fibre content observed in 75WF:25FWF could be related to the higher fibre content (~ 17.6% crude fibre) in FWF, or a different type of wheat flour, such as whole wheat flour, known for its higher fibre 3 . The carbohydrate content in 75WF:25FWF was significantly lower due to the higher levels of ash and fibre in the noodles. Table 2 Proximate composition and sensory evaluation of selected noodles samples. Parameters 100WF 75WF:25FWF Proximate composition Moisture (%) 2.43 ± 0.18 a 1.62 ± 0.05 b Protein (%) 10.84 ± 0.05 a 9.32 ± 0.47 b Fat (%)* 1.39 ± 0.48 3.28 ± 1.44 Ash (%) 1.77 ± 0.06 b 10.4 ± 0.1 a Crude fibre (%) 0.77 ± 0.06 b 7.77 ± 0.15 a Carbohydrate (%) 82.81 ± 0.29 a 64.71 ± 1.2 b Sensory evaluation Colour 5.80 ± 0.10 a 4.30 ± 1.21 b Aroma 5.47 ± 1.07 a 4.35 ± 1.36 b Texture* 6.07 ± 0.91 5.36 ± 1.27 Taste 5.57 ± 1.14 a 3.53 ± 1.53 b Overall acceptability 5.80 ± 0.71 a 3.87 ± 1.59 b Result display mean values ± standard deviation for proximation composition ( n = 3) and sensory evaluation ( n = 30). Different letters superscripted indicate significant difference ( P < 0.05) between different samples. *No significant difference was observed in fat content and sensory texture. Kindly refer Table 1 for noodle sample definitions and descriptions. 3.7 Sensory evaluation The results of the five sensory qualities are presented in Table 2 . Panellists showed a preference for the colour, aroma, taste, and overall acceptability of 100WF. 75WF:25WFW exhibited a higher a* value (Fig. 2 b), potentially leading to a lower rating in sensory colour. The colour of noodles is a crucial determinant of quality. Consumers are initially attracted to noodles that have a bright, even colour without darkening or discoloration 32 . The lower ratings for aroma, taste and overall acceptability of 75WF:25FWF were likely due to the distinct acidic flavour from organic acids (lactic and acetic acid) produced from LAB, which affected the taste and acceptability attributes. LAB also released proteases that broke down proteins into peptides and amino acids, enhancing the fundamental flavours of fermented foods. Additionally, specific enzymes like lipase and phospholipase, secreted by LAB, facilitated lipolysis, resulting in the formation of free fatty acids. These acids play a crucial role as key aroma compounds in many fermented foods 33 . However, panellist did not detect a significant difference in texture between both types of noodles, consistent with the results from textural properties (Fig. 3 ). Sensory evaluations of noodle texture corresponds closely with instrumental textural measurements, such as hardness TPA 32 . 4.0 Conclusion In conclusion, the addition of FWF notably decreased the optimum cooking time, cooking yield, pH, and lightness, while it enhanced the redness and yellowness of the noodles. Noodles with a FWF content exceeding 50% experienced increased cooking losses and breakability, along with reduced textural and structural integrity. SEM demonstrated that such noodles possessed a deteriorated gluten structure characterized by larger and more irregular pores. In contrast, 75WF:25FWF maintained cooking performance and structural integrity comparable to 100WF, featuring a compact and dense gluten network with smaller pores that improved cooking performance and texture. The proximate composition analysis indicated that the 75WF:25FWF had lower moisture and higher fibre content. Although sensory evaluations yielded lower scores, the textural differences were minimally perceptible. The incorporation of FWF could potentially offer health benefits due to a higher fibre content, suggesting that FWF has promising applications in enhancing the nutritional profile of dried noodles while maintaining acceptable cooking and textural qualities. Future research could investigate the influence of fermented wheat flour on various noodle varieties, and assess the scalability of these findings for broader industrial applications to potentially enhance nutritional profiles and consumer satisfaction across different markets. Declarations Acknowledgements The authors acknowledge the Ministry of Higher Education Malaysia for Prototype Development Research Grant (PRGS) with Project Code: PRGS/1/2022/TK02/USM/01/1 for funding. The authors acknowledge the School of Industrial Technology, Universiti Sains Malaysia and Centre for Global Archaeological Research, Universiti Sains Malaysia for testing facilities and the support. Author contributions Shin-Yong Yeoh: Writing - Review & Editing, Validation, Formal analysis, Investigation, Methodology, Data Curation, Visualization, Project administration. Viklawan Fricher: Writing - original draft, Formal analysis, Investigation, Methodology. Lubowa Muhammad: Conceptualization, Methodology, Validation, Writing - Review & Editing. Ojukwu Moses: Writing - Review & Editing. Azhar Mat Easa: Conceptualization, Methodology, Validation, Resources, Supervision, Writing - Review & Editing, Funding acquisition. Competing Interest declaration. All authors declare no financial or non-financial competing interests. Data availability Data sharing is not applicable to the main text. The data supporting the findings of this study are available on request from the corresponding authors. Ethics approval and consent to participate The study was conducted in accordance with the University human ethics committee (code number: USM/JEPeM/23110839, Jawatankuasa Penyelidikan Manusia USM (JEPeM)). Informed consent was obtained from all human participants. References Liu, Y. et al. Effect of heat-moisture treatment of wheat ( Triticum aestivum L.) grain on micronutrient content of flour, and noodles and bread qualities. J. Cereal Sci. 115, 103836 (2024). Sandhu, K. S., Punia, S. & Kaur, M. Effect of duration of solid state fermentation by Aspergillus awamorinakazawa on antioxidant properties of wheat cultivars. LWT - Food Sci. Technol. 71, 323–328 (2016). Chinma, C. E. et al. Physicochemical properties, anti-nutritional and bioactive constituents, in vitro digestibility, and techno-functional properties of bioprocessed whole wheat flour. J. Food Sci. n/a, (2024). Meziani, S. et al. Wheat aleurone layer: A site enriched with nutrients and bioactive molecules with potential nutritional opportunities for breeding. J. Cereal Sci. 100, 103225 (2021). Ye, X. & Sui, Z. Physicochemical properties and starch digestibility of Chinese noodles in relation to optimal cooking time. Int. J. Biol. Macromol. 84, 428–433 (2016). Li, G. et al. Insights into the quality and structure of dried wheat noodles as affected by monascus pigments. J. Cereal Sci. 116, 103869 (2024). Wang, J. et al. Regulating the quality and starch digestibility of buckwheat-dried noodles through steam treatment. LWT 195, 115826 (2024). Bharath Kumar, S. & Prabhasankar, P. Low glycemic index ingredients and modified starches in wheat based food processing: A review. Trends Food Sci. Technol. 35, 32–41 (2014). Şanlier, N., Gökcen, B. B. & Sezgin, A. C. Health benefits of fermented foods. Crit. Rev. Food Sci. Nutr. 59, 506–527 (2019). Ramedani, N., Sharifan, A., Nejad, M. R. & Yadegar, A. Influence of a combination of three probiotics on wheat dough fermentation; new therapeutic strategy in celiac disease. J. Food Meas. Charact. 18, 2480–2488 (2024). Antognoni, F., Mandrioli, R., Potente, G., Taneyo Saa, D. L. & Gianotti, A. Changes in carotenoids, phenolic acids and antioxidant capacity in bread wheat doughs fermented with different lactic acid bacteria strains. Food Chem. 292, 211–216 (2019). Lu, X., Guo, X. & Zhu, K. Effect of Fermentation on the Quality of Dried Hollow Noodles and the Related Starch Properties. Foods 11, 3685 (2022). Ojukwu, M., Tan, H. L., Murad, M., Nafchi, A. M. & Easa, A. M. Improvement of cooking and textural properties of rice flour-soy protein isolate noodles stabilised with microbial transglutaminase and glucono-δ-lactone and dried using superheated steam. Food Sci. Technol. Int. Cienc. Tecnol. Los Aliment. Int. 29, 799–808 (2023). Tan, H.-L., Tan, T.-C. & Easa, A. M. The use of selected hydrocolloids and salt substitutes on structural integrity, texture, sensory properties, and shelf life of fresh no salt wheat noodles. Food Hydrocoll. 108, 105996 (2020). Ma, D. et al. Color, cooking properties and texture of yellow alkaline noodles enriched with millet and corn flour. Int. Food Res. J. (2014). Yeoh, S.-Y., Lubowa, M., Tan, T.-C., Murad, M. & Mat Easa, A. The use of salt-coating to improve textural, mechanical, cooking and sensory properties of air-dried yellow alkaline noodles. Food Chem. 333, 127425 (2020). Yeoh, S.-Y. et al. Sensory, structural breakdown, microstructure, salt release properties, and shelf life of salt-coated air-dried yellow alkaline noodles. Npj Sci. Food 7, 8 (2023). Ojukwu, M., Tan, J. S. & Easa, A. M. Cooking, textural, and mechanical properties of rice flour-soy protein isolate noodles prepared using combined treatments of microbial transglutaminase and glucono-δ-lactone. J. Food Sci. 85, 2720–2727 (2020). AOAC. Official Methods of Analysis of AOAC International . (AOAC International, Rockville, MD, 2016). Wang, Z. et al. Effects of gluten and moisture content on water mobility during the drying process for Chinese dried noodles. Dry. Technol. 37, 759–769 (2019). Cao, Z.-B. et al. Impact of gluten quality on textural stability of cooked noodles and the underlying mechanism. Food Hydrocoll. 119, 106842 (2021). Zhang, M., Ma, M., Yang, T., Li, M. & Sun, Q. Dynamic distribution and transition of gluten proteins during noodle processing. Food Hydrocoll. 123, 107114 (2022). Yao, M., Li, M., Dhital, S., Tian, Y. & Guo, B. Texture and digestion of noodles with varied gluten contents and cooking time: The view from protein matrix and inner structure. Food Chem. 315, 126230 (2020). Xie, D., Li, X., Li, X. & Ren, S. Effect of gluten protein levels on physicochemical and fermentation properties of corn dough. Int. J. Food Sci. Technol. 59, 189–196 (2024). Zhao, G. et al. Structural characteristics and paste properties of wheat starch in natural fermentation during traditional Chinese Mianpi processing. Int. J. Biol. Macromol. 262, 129993 (2024). Zhao, B. et al. Effects of gluten on rheological properties of dough and qualities of noodles with potato–wheat flour blends. Cereal Chem. 97, 601–611 (2020). Xiong, X., Liu, C., Song, M. & Zheng, X. Effect of characteristics of different wheat flours on the quality of fermented hollow noodles. Food Sci. Nutr. 9, 4927–4937 (2021). Liu, J. et al. Effect of high-temperature drying at different moisture levels on texture of dried noodles: Insights into gluten aggregation and pore distribution. J. Cereal Sci. 115, 103817 (2024). Liu, G. et al. Simulated oral processing of cooked rice using texture analyzer equipped with multiple extrusion cell probe (TA/MEC). LWT 138, 110731 (2021). Yang, J. et al. Exploring the dynamic water mobility and distribution in model systems of wheat noodles with different gluten-to-starch ratios based on LF-NMR. J. Cereal Sci. 116, 103855 (2024). Akonor, P. T., Tortoe, C., Buckman, E. S. & Hagan, L. Proximate composition and sensory evaluation of root and tuber composite flour noodles. Cogent Food Agric. 3, 1292586 (2017). Buzera, A. et al. Investigating potato flour processing methods and ratios for noodle production. Food Sci. Nutr. n/a, (2024). Yan, X., McClements, D. J., Luo, S., Ye, J. & Liu, C. A review of the effects of fermentation on the structure, properties, and application of cereal starch in foods. Crit. Rev. Food Sci. Nutr. 0, 1–20 (2024). Additional Declarations (Not answered) Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4504789","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":309098824,"identity":"c2b3564b-ba58-4879-9e92-974542d46366","order_by":0,"name":"Muhammad Lubowa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYBACAwYeKEsCTDLLka7FmHQtiQ0EtUjkHnzMU8MQbXC7+emmGzXW6WunnTFg+FHDkDjfAZeWvGRjnmMMuRvuHDO7nXMsPXfb7RwDxp5jDIkbD+DSkmMmncMG1HIjAaiF7TBYCwNvA1ALDidCtPwDaUn/djvn3+F0M5AtfwlpyW0Dackxu53bdhhklwEzyJb5uLzP8y7Z+G+fRO7MGzllt3P70g233U4rOCxzTMJ4Aw4t9u25Bx/O+GaT23cjHeiLb9byZreTNz58U2MjOx+Hw6BAApV7ACRicACvFmxAHr8to2AUjIJRMHIAAE4TYGCQ86FpAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-1093-2579","institution":"Mountains of the Moon University","correspondingAuthor":true,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Lubowa","suffix":""},{"id":309098825,"identity":"48ec8853-da26-4db3-9f99-4289a73ad86e","order_by":1,"name":"Shin-Yong Yeoh","email":"","orcid":"https://orcid.org/0000-0003-4635-4923","institution":"Universiti Sains Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Shin-Yong","middleName":"","lastName":"Yeoh","suffix":""},{"id":309098826,"identity":"2e1829bf-d7ac-4dc4-8e96-9da9255c61a4","order_by":2,"name":"Viklawan Fricher","email":"","orcid":"","institution":"Universiti Sains Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Viklawan","middleName":"","lastName":"Fricher","suffix":""},{"id":309098827,"identity":"8429fc56-d1e4-432a-8fe8-d397861a0674","order_by":3,"name":"Ojukwu Moses","email":"","orcid":"","institution":"Federal University of Technology Owerri","correspondingAuthor":false,"prefix":"","firstName":"Ojukwu","middleName":"","lastName":"Moses","suffix":""},{"id":309098828,"identity":"2179b41f-435b-432e-a3c9-f07ffa665f4d","order_by":4,"name":"Azhar Mat Easa","email":"","orcid":"","institution":"Universiti Sains Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Azhar","middleName":"Mat","lastName":"Easa","suffix":""}],"badges":[],"createdAt":"2024-05-30 19:00:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4504789/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4504789/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60127433,"identity":"6ca0b864-10b5-4b5f-91e8-3040e40872f4","added_by":"auto","created_at":"2024-07-12 06:19:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":86460,"visible":true,"origin":"","legend":"\u003cp\u003eCooking qualities of noodles. (a) Optimum cooking time, (b) cooking yield, (c) cooking loss and (d) breakability. Error bars indicate mean values ± standard deviations (\u003cem\u003en\u003c/em\u003e = 3). Different letters superscripted indicate significant difference (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05) between different bars. Kindly refer Table 1 for noodle sample definitions and descriptions.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4504789/v1/9b9151e367d81ed0ac098e55.png"},{"id":60127089,"identity":"3c77d187-e448-4493-ac0d-2f6a3f4841d3","added_by":"auto","created_at":"2024-07-12 06:11:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":707444,"visible":true,"origin":"","legend":"\u003cp\u003epH, colour values and photos of cooked noodles. (a) pH, (b) L*, (c) a*, (d) b*, (e) 100WF, (f) 75WF:25FWF, (g) 50WF:20FWF and (h) 25WF:75FWF. Error bars indicate mean values ± standard deviations (\u003cem\u003en\u003c/em\u003e = 3). Different letters superscripted indicate significant difference (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05) between different bars. Kindly refer Table 1 for noodles samples definitions and descriptions.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4504789/v1/5dde5f226f4fdd5795e70c5d.png"},{"id":60127084,"identity":"e69c4ca0-65ec-4c0c-ae9c-031073a2bbe3","added_by":"auto","created_at":"2024-07-12 06:11:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":33868,"visible":true,"origin":"","legend":"\u003cp\u003eTextural properties of noodles. (a) Hardness and (b) firmness. Error bars indicate mean values ± standard deviations (\u003cem\u003en\u003c/em\u003e = 3) for hardness and mean values ± standard deviations (\u003cem\u003en\u003c/em\u003e = 15) for firmness. Different letters superscripted indicate significant difference (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05) between different bars. Kindly refer Table 1 for noodles samples definitions and descriptions.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4504789/v1/c8221e7c6f470ec1582343fb.png"},{"id":60127087,"identity":"2e8c6b23-db96-4509-882f-343b5d9ea98c","added_by":"auto","created_at":"2024-07-12 06:11:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":82719,"visible":true,"origin":"","legend":"\u003cp\u003eStructural breakdown parameters using MEC analysis. (a) Work 1st, (b) w\u003csub\u003einf\u003c/sub\u003e, (c) w\u003csub\u003e1\u003c/sub\u003e and (d) n\u003csub\u003e1\u003c/sub\u003e. Error bars indicate mean values ± standard deviations (\u003cem\u003en\u003c/em\u003e = 3). Different letters superscripted indicate significant difference (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05) between different bars. Kindly refer Table 1 for noodles samples definitions and descriptions.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4504789/v1/eb75ab8b784d721aa9e10b32.png"},{"id":60127085,"identity":"b92fa195-62a7-483a-b5b7-c0c58e5c8276","added_by":"auto","created_at":"2024-07-12 06:11:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":856926,"visible":true,"origin":"","legend":"\u003cp\u003eSEM images of noodle samples at 125× magnification consisting of WF and FWF noodles. (a) 100WF, (b) 75WF:25FWF, (c) 50WF:50FWF and (d) 25WF:75FWF. The circles in the images represent larger hollows and voids.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4504789/v1/7da6264247990884c046fd70.png"},{"id":62003634,"identity":"08fe3da3-1323-4f30-9071-974691b75bcb","added_by":"auto","created_at":"2024-08-08 06:23:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2697877,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4504789/v1/a3bafe80-ca1a-4a3d-bd30-1ea4cca8d83e.pdf"}],"financialInterests":"(Not answered)","formattedTitle":"Impact of fermented wheat flour on the quality of dried white salted noodles: cooking, physicochemical, structural breakdown, microstructure and sensory evaluations","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eWheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L.) ranks among the crops with the highest global yields, with an annual consumption reaching 791.2\u0026nbsp;million tons. Due to its distinctive capacity for gluten formation, wheat flour has become one of the most widely utilized ingredients in the food industry \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Kernels of wheat are sources of numerous phenolic substances, including ferulic, vanillic, gentisic, caffeic, salicylic, syringic, p-coumaric, and sinapic acids \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The rise in production of wheat emphasizes its global importance and its key contribution in the development of flour-based goods, such as pastries, pasta, doughnuts, breakfast cereals, rolls, and extruded snacks \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Consequently, wheat flour serves not only as a significant source of energy but also as an essential nutritional component of the human diet \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The majority of the micronutrients (vitamins and minerals) are located in the endosperm and is typically removed along with the bran in the process of producing refined wheat flour through conventional milling techniques \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. As a result, wheat flour often lacks essential micronutrients, leading to various health issues globally \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNoodles have been a fundamental part of diets for over 4,000 years, particularly in Asian countries. Among the various types available, white salted noodles (WSN) are favoured for their superior taste, colour, and texture. WSN are produced in a range of formulations and shapes, with the dough comprising a blend of wheat flour, water, and salt \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Noodles are categorized as fresh (32% \u0026ndash; 38% moisture content) and dried (\u0026lt;\u0026thinsp;12% moisture content) noodles based on their moisture levels. Due to their ease of storage, convenience, affordability, and versatility, dried noodles are becoming increasingly popular among consumers for daily consumption \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Nonetheless, the primary composition of most dried noodles is refined wheat flour, which is deficient in critical nutrients, including dietary fibre, minerals, vitamins, and bioactive compounds. Additionally, dried noodles produced from refined wheat flour exhibit a high digestion rate and starch content \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Prolonged consumption of such noodles is associated with an elevated risk of developing type 2 diabetes, obesity, and other chronic health conditions \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFermentation, an ancient and cost-efficient food processing technique, not only extends shelf life and enhances sensory attributes but also significantly improves the digestibility of proteins and carbohydrates, along with the bioavailability of vitamins and minerals \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Solid-state fermentation enhanced the functionality, antioxidant and bioactive properties of wheat varieties \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Moreover, a mixture of probiotics had been used to ferment wheat dough as a novel therapeutic approach for celiac disease. Celiac Disease represents the most severe form of gluten intolerance and affects approximately 1% of the population.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The enhanced functionality of bioprocessed whole wheat flour makes it a promising ingredient for producing functional food \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFermenting wheat dough with lactic acid bacteria increased the levels of carotenoids and bioactive compounds, potentially enhancing health benefits \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Crumbly dough has been fermented to produce dried hollow noodles characterized by a quick cooking time, soft and elastic texture, and easy digestibility \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo our knowledge, no fermented wheat flour has been used to prepare dried WSN. This study investigated the physicochemical, sensory, structural breakdown preparties and microstructure of dried WSN prepared from fermented wheat flour.\u003c/p\u003e"},{"header":"2.0 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Materials\u003c/h2\u003e \u003cp\u003eCommercial WF (Cap Sauh) (~\u0026thinsp;9% protein), and salt were purchased from Lotus Stores Malaysia Sdn Bhd (Lotus\u0026rsquo;s Malaysia) (Georgetown, Malaysia). FWF (~\u0026thinsp;2.2% protein) was purchased from Deluxe Ingredients Sdn. Bhd (Shah Alam, Malaysia). Other chemicals used in this study (analytical grade) were purchased from Sigma\u0026ndash;Aldrich (St. Louis, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Preparation of wheat noodles\u003c/h2\u003e \u003cp\u003eThe wheat noodles were prepared according to Ojukwu et al. (2023) and Tan et al. (2020) with modifications. The formula of the noodles is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All the ingredients were weighted and mixed by a mixer at speed 2 (Kenwood, UK) for 10 min. The dough was then kneaded and left to rest for 30 min. Next, it was rolled out into a thin sheet using a pasta maker (Marcato Ampia, Model 150, Campodarsego PD, Italy) with an initial gap setting at width 0 (2.2 mm) for 5 times, width 1 (2.0 mm), width 2 (1.8 mm), width 3 (1.6 mm), and width 4 (1.4 mm). The sheet was then cut into uniform noodles strands using the same pasta machine with dimensions 1.4 mm in width and 1.1 mm in thickness. Next the noodles were steamed for 10 min before drying in an oven (AFOS T500 dryer, London, UK) at 70\u0026deg;C for 2 h and 100\u0026deg;C for 3 h. The noodles were packaged using sealed packaging and stored for subsequent analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFormulation of noodles.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIngredients (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eTypes of noodles\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100WF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75WF:25FWF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50WF:50FWF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25WF:75FWF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFWF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e100WF, noodles with 100% WF, 75WF:25FWF, noodles with 75% WF and 25% FWF; 50WF:50FWF, noodles with 50% WF and 50% FWF, 25WF:75FWF, noodle with 25% WF and 75% FWF.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Determination of cooking qualities\u003c/h2\u003e \u003cp\u003eThe cooking qualities of the noodles was measured through measurements of their optimum cooking time, cooking yield, and cooking loss along with the assessment of noodle breakability \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Three replicates were made for each type of noodles. Noodle samples (10 g) were cooked in 400 mL of boiling distilled water in a saucepan. Cooking time was defined as the time the white core in the central portion of the noodles strand disappeared upon squeezing the noodle between two slides of transparent glass. The cooking yield, reflecting the water holding capacity during cooking, was calculated using the following formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\text{Cooking yield (%)}=\\frac{\\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{n}\\text{o}\\text{o}\\text{d}\\text{l}\\text{e}\\text{s} \\text{a}\\text{f}\\text{t}\\text{e}\\text{r} \\text{c}\\text{o}\\text{o}\\text{k}\\text{i}\\text{n}\\text{g}}{\\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{n}\\text{o}\\text{o}\\text{d}\\text{l}\\text{e}\\text{s} \\text{b}\\text{e}\\text{f}\\text{o}\\text{r}\\text{e} \\text{c}\\text{o}\\text{o}\\text{k}\\text{i}\\text{n}\\text{g}}\\times \\text{100%}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eCooking loss was measured by drying 100 mL of the cooking water in an oven at 105\u0026deg;C to a stable weight. Cooking loss was calculated by measuring the weight of solid substances lost in the cooking water from noodles strands. The breakability of noodles was measured using the equation below:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\text{B}\\text{r}\\text{e}\\text{a}\\text{k}\\text{a}\\text{b}\\text{i}\\text{l}\\text{i}\\text{t}\\text{y} \\left(\\text{%}\\right) =\\frac{\\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{b}\\text{r}\\text{o}\\text{k}\\text{e}\\text{n} \\text{n}\\text{o}\\text{o}\\text{d}\\text{l}\\text{e}\\text{s} \\text{s}\\text{t}\\text{r}\\text{a}\\text{n}\\text{d}\\text{s}}{\\text{T}\\text{o}\\text{t}\\text{a}\\text{l} \\text{c}\\text{o}\\text{o}\\text{k}\\text{e}\\text{d} \\text{n}\\text{o}\\text{o}\\text{d}\\text{l}\\text{e}\\text{s} \\text{w}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t}}\\times \\text{100%}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Determination of pH\u003c/h2\u003e \u003cp\u003eThe pH values of cooked noodles were determined using a Mettler-Toledo Delta 320\u003c/p\u003e \u003cp\u003epH meter \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Each sample (10 g) were homogenized for 5 min in 100 mL of distilled water and then filtered. pH analysis was conducted after 30 min of waiting. Calibration on the pH meter was carried out before measurement. Three replicates were made for each type of noodles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Determination of colour\u003c/h2\u003e \u003cp\u003eThe colour of cooked noodles was measured using a colorimeter (Konica Minota, Model CM\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e3600d, USA) . International Commission on Illumination (CIE) L*\u003c/h3\u003e\n\u003cp\u003e(lightness), a* (redness), and b* (yellowness) values were recorded at random locations on\u003c/p\u003e \u003cp\u003ethe noodles' surface. Three replicates were made for each type of noodle.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Texture profile analysis (TPA)\u003c/h2\u003e \u003cp\u003eThe textural properties of cooked noodles were measured using a Texture Analyzer (Stable Micro System, Surrey, England) calibrated with a 5 kg load cell before measurements \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Three noodle strands (70m length) were placed in parallel on the middle of the compression plate using pasta firmness rig (HDP/PFS) for analysis. The settings were: Mode, measure force in compression; Trigger type, auto with trigger force of 20 g; Pre-test speed, 2.0 mm/s; Test speed, 0.8 mm/s; Post-test speed, 0.8 mm/s; Strain, 75%; Interval between two compressions, 1.0 s. For every noodle type, two successive compressions were applied and measured thrice, with the values then averaged. Values for hardness, adhesiveness, cohesiveness, springiness, and chewiness were obtained.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Noodles firmness\u003c/h2\u003e \u003cp\u003eThe firmness of the cooked noodles was determined by employing a TA-XT2 Plus Texture Analyser (Stable Micro Systems, Surrey, England), equipped with a 5 kg load cell and attached to a 1 mm flat Perspex blade \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The gap set between the Perspex blade and the robust platform was fixed at 30 mm. The assessment proceeded under the following parameters: Mode: Measure force in compression; Option: Return to start; Pre-Test Speed: 1.0 mm/s, Test Speed: 0.1 mm/s; Post-Test Speed: 10 mm/s; Distance: 4.98 mm; Data Acquisition Rate: 400 pps. To prepare for testing, five noodle strands, each 70 mm in length, were laid out in a straight line, side by side on the centre of the platform, and oriented perpendicular to the blade. The firmness of the noodles was indicated by the highest point on the force-time curve. This procedure was replicated fifteen times for each sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Structural breakdown analysis\u003c/h2\u003e \u003cp\u003eStructural breakdown analysis was carried out using a texture analyser (model TA-TX2, Stable Micro Systems, Surrey, UK) with a 30 kg load cell \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Cooked noodles samples weighing 20 g were tested in 10 mL artificial saliva across three replicates. The pH was adjusted to 7.0 with 0.1 M HCl. The texture analyser settings were as follows: Mode set to measure compression force; Option to cycle until a specified count; Test Speed at 10 mm/s; Post-Test Speed at 5 mm/s; Distance set at 95 mm; Count set for 20 cycles; Data acquisition rate at 2 pps. The results were plotted on a force vs. time graph and analysed using a single exponential decay equation:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$${W}_{\\left(n\\right)} = {W}_{inf}+ {W}_{1}\\left.EXP\\left(- \\frac{n}{{n}_{1}}\\right.\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere W\u003csub\u003e(n)\u003c/sub\u003e denotes the work performed in each extrusion cycle (n), w\u003csub\u003einf\u003c/sub\u003e represents the work per extrusion after numerous (effectively infinite) cycles, w\u003csub\u003e1\u003c/sub\u003e specifies the quantity and strength of the degraded noodle structure, and n\u003csub\u003e1\u003c/sub\u003e indicates the rate at which the work per extrusion decreases as the number of extrusions increases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Scanning Electron Microscopy (SEM)\u003c/h2\u003e \u003cp\u003eThe microstructures of all samples were examined using a SEM with a Quanta 650 FEG SEM (FEI Technologies Inc., US) \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Prior to analysis, noodle samples were dried at 60\u0026deg;C for 1 h. Dried noodles were then cut and mounted on a sample holder with the fractured side exposed. The cross-sections of the noodles were observed under the SEM at 125\u0026times; magnification and examined at 5 kV.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Proximate composition analysis of noodles\u003c/h2\u003e \u003cp\u003eThe composition of 100WF and 75WF:25FWF, including moisture, protein, fat, crude fibre, and ash, was assessed according to the \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e standard procedures. Carbohydrate content was determined using the difference method, which involves subtracting the sum of percentages of protein, moisture, crude fibre, crude fat, and ash from 100.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Sensory evaluation\u003c/h2\u003e \u003cp\u003e The study was approved by the University human ethics committee (code number: USM/JEPeM/23110839, Jawatankuasa Penyelidikan Manusia USM (JEPeM)). Informed consent was obtained from all human participants.\u003c/p\u003e \u003cp\u003e30 panellists were Food Technology undergraduate and postgraduate students at Universiti Sains Malaysia. Before the sensory evaluation, all panellists were informed and given written informed consent. 100WF and 75WF:25FWF were prepared for sensory evaluation. Each sample was cooked according to the optimum cooking time and kept in a covered container before being served in a small paper cup in a 4 g portion, with a labelled 3-digit random number, and in random order. Each panellist was required to evaluate each of the noodle\u0026rsquo;s samples for the five attributes (colour, aroma, texture, taste, and overall acceptability) using a 7-point hedonic scale in which numbers are present (1\u0026thinsp;=\u0026thinsp;dislike strongly, 2\u0026thinsp;=\u0026thinsp;dislike moderately, 3\u0026thinsp;=\u0026thinsp;dislike slightly, 4\u0026thinsp;=\u0026thinsp;neither like nor dislike, 5\u0026thinsp;=\u0026thinsp;like slightly, 6\u0026thinsp;=\u0026thinsp;like moderately, 7\u0026thinsp;=\u0026thinsp;like strongly). The panellists were provided with tissue paper, an empty cup, and a cup of bottled water to rinse their mouths at the beginning of the evaluation and between evaluations of each sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.12 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe SPSS 27.0 software (SPSS Inc. Chicago IL, USA) was used to perform analysis of variance (ANOVA) on the data generated. Results were expressed as means and standard deviation. Duncan\u0026rsquo;s test determined the significant differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among the means. Independent t-test was performed to calculate the data obtained from proximate composition analysis and sensory evaluation.\u003c/p\u003e \u003c/div\u003e"},{"header":"3.0 Results and discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Noodles description\u003c/h2\u003e \u003cp\u003eA excellent quality of dried noodles should have a bright, clean, and smooth surface, with noodle strands that are straight and robust, free from any cracks, warps, or splits \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. During 100WF preparation, the noodles fortified with 100% commercial WF (~\u0026thinsp;9% protein) exhibited remarkable handling characteristics in dough kneading, sheeting, noodles strands cutting and steaming, contributed to the added elasticity from gluten. Both the dough and noodles maintained consistently manageable texture, ensuring ease of handling throughout the entire process. Subsequently, 75WF:25FWF comprising 25% FWF showed favourable handling properties during preparation. The dough and noodles were responsive and easy to manage without any complications. Next, 50WF:50FWF consisting of equal proportions of commercial WF and FWF produced a softer and slight sticky dough. This dough demonstrated moderate manageability through the preparation. However, 25WF:75FWF with an increased proportion of FWF resulted in an extremely soft and sticky dough, leading to difficulties during all stages of the process.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Cooking qualities\u003c/h2\u003e \u003cp\u003eGood quality of noodles should possess short cooking time, higher cooking yield and low cooking loss \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The cooking qualities of noodles are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. 100WF contained the highest protein content, which probably contributed to the significantly longest optimum cooking time (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Gluten is the main protein (85%) in wheat flour and comprises two components: polymeric glutenin, which gives noodles their elasticity, and monomeric gliadin, which provides viscosity. Both components influence the quality of the noodles \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. During the noodles-making process, gluten protein experiences a series of dynamic changes, including directional rearrangement, depolymerization, and polymerization. It also induces a three-dimensional network within the wheat dough, with starch granules embedded throughout the gluten matrix. During cooking, starch granules absorb water, causing them to swell. The gelatinized starch and solidified gluten then form a dual-network hydrogel characterized by large pores. Heating facilitates additional polymerization of gluten, particularly through the creation of disulfide (S\u0026ndash;S) bonds and other non-covalent interactions. This process can stabilize the gluten network, thereby impacting the textural characteristics of the noodles after cooking \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Additionally, Yao et al. (2020) reported that the optimum cooking time for noodles demonstrated a positive correlation with protein content. Their findings align with our results, where the FWF noodles with lower protein content required shorter optimum cooking times. The optimum cooking time of 25WF:75FWF was the shortest (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among all noodles, probably due to its lower protein content and weaker protein network. In addition, the gas produced by microbial metabolism during wheat flour fermentation resulted in the formation of numerous pores within the noodles. These pores enhanced the contact between water and starch during cooking, consequently reducing the cooking time for FWF noodles \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. As the ratio of FWF increased in the formulation, more pores were generated within the noodle structure, significantly decreasing the cooking time.\u003c/p\u003e \u003cp\u003eThe interaction between protein and starch in noodles significantly influences water absorption and optimum cooking time. When noodles are cooked in an excess of water, the starch absorbs water, the hydrogen bonds between the gluten protein and starch begin to deteriorate, which triggers starch gelatinization and protein coagulation \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. 100WF exhibited the highest cooking yield (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among all samples, whereas noodles incorporating FWF displayed lower cooking yields, although these differences not being statistically significant across different ratios. Longer optimum cooking time for noodles were linked to a higher cooking yield \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, a trend observed in the case of 100WF. Moreover, high gluten content enhanced the dough's ability to absorb water due to the formation of hydrogen bonds with water \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. All FWF noodles showed reduced cooking yields, likely due to their reduced gluten protein content, which impacted their ability to absorb water.\u003c/p\u003e \u003cp\u003eCooking loss refers to the amount of dry matter that is released into the water when noodles are cooked optimally \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. It primarily occurs from the leaching of starch, soluble protein, and salt, which are released from the breakdown of the protein matrix within the noodles due to the boiling water. The cooking losses of 100WF and 75WF:25FWF were significantly the lowest among all samples, whereas 25WF:75FWF exhibited the highest cooking loss (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The higher gluten protein content in 100WF and 75WF:25FWF helped trap the starch within a compact and denser gluten network, thus preventing most of it from leaching out during cooking. It is evident that the increasing FWF level led to higher cooking loss. In 25WF:75FWF, the starch embedded within and around the weakened gluten network structure leached into the cooking water easily due to the lower gluten protein level. Fermentation induced hydrolysis of gluten and starch by the microorganisms or their metabolites, increasing the leaching of starch molecules during cooking and resulting in greater cooking loss \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Furthermore, research has shown that fermentation caused the surface of starch granules to develop indentations, cracks, and holes. These changes resulted from the breakdown of starch molecules due to organic acids and enzymes produced during fermentation \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In this study, all cooking losses were under 10%, meeting the acceptable standards set by the Chinese Agriculture Trade Standards for starch noodles \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSignificant differences were observed in the breakability of the samples. 100WF and 75WF:25FWF exhibited the lowest breakability (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which can be attributed to the presence of higher gluten level that strengthened the noodles. Gluten proteins absorb water and swell, forming a network that enhances the physical properties of the dough. They consist of glutenin and gliadin, which are crucial to the dough's structure and viscoelastic properties \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Zhao et al. (2020) reported that wheat gluten helped the dough develop a strong gluten network, thereby improving noodle quality. In the case of 50WF:50FWF and 25WF:75FWF, a lower gluten level resulted in a weaker network structure and dough that was difficult to form and inherently weak, as found in Xie et al. (2024)\u0026rsquo;s study. Similarly, our study observed that increasing the FWF level yielded dough that was soft and weak.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.2 pH and colour analysis\u003c/h2\u003e \u003cp\u003eThe pH of all samples is exhibited in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea. The pH of 100WF was significantly (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) the highest, aligning with the pH of wheat flour (pH 6.05). Increasing the proportion of FWF in noodles resulted in a significant reduction in their pH, which can be attributed to the acidic pH of FWF (pH 5.73). The conversion of complex organic molecules like carbohydrates into organic acids by enzymes during the fermentation of the grains contributed to the decrease in pH in FWF noodles. During fermentation, enzymes like α-amylase and maltase are activated, which convert starch into simple sugars and cause other changes, including metabolites that lower the pH \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAll FWF noodles exhibited significantly lower L*, higher a* and b* values compared to 100WF, although no significant differences in L* and b* values were observed among the FWF noodles. Increased light reflection from a greater number of starch granules results in a brighter or whiter appearance \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The incorporation of FWF into noodle formulations enhanced the dark, red, and yellow colour attributes of the noodles. \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e noted similar colour changes in fermented wheat flour, attributing these changes to enzyme-driven hydrolysis of macromolecules during fermentation. Furthermore, they reported that the darker colour of wheat flour was associated with increased antioxidant activities, likely due to a higher concentration of phenolic compounds. Specifically, elevated levels of carotenoids, which are pigments ranging in colour from yellow to red or orange, were observed in wheat dough after fermentation by certain L. \u003cem\u003eplantarum\u003c/em\u003e strains \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Furthermore, the bio accessibility of these carotenoids was enhanced due to their presence in the aleurone layer of the grain, potentially increasing their free concentrations. Notably, the researchers found increased levels of lutein and zeaxanthin\u0026mdash;types of carotenoids\u0026mdash;in wheat dough fermented with two L. \u003cem\u003eplantarum\u003c/em\u003e strains known for producing the C30 carotenoid 4,4-diaponeurosporene. Increasing FWF levels led to a decrease in a* values, possibly due to higher cooking losses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec), particularly from the leaching of phenolic compounds during cooking.\u003c/p\u003e \u003cp\u003eThe photos of cooked noodles are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee, f, g and h.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Textural properties of noodles\u003c/h2\u003e \u003cp\u003eThe FWF ratio in the noodles had a significant influence on the selected textural parameters (hardness, adhesiveness, springiness, cohesiveness, and chewiness) and firmness of noodles. No significant was observed in the adhesiveness and springiness values. Typically, the sequence for textural parameters illustrates a similar trend. Therefore, only hardness value is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea. It can be outlined as: 100WF, 75WF:25FWF\u0026thinsp;\u0026gt;\u0026thinsp;50WF:5FWF, 25WF:75FWF. The structure of the cooked noodles deteriorated as the FWF ratio in the formulation increased. 100WF and 75WF:25FWF demonstrated the highest textural parameters significantly, possibly due to the compact gluten network. The quality of dried noodles improved because of a higher degree of protein aggregation during cooking, which retained a denser gluten network and minimized the gelatinization and dissolution of starch. During the drying process, high temperatures cause a swift decrease in the free \u0026ndash;SH content of proteins and induces the folding and masking of aromatic amino acid residues (tryptophan). Glutenin and prolamin experience further cross-linking, leading to the formation and enhancement of protein aggregates, and establishing a uniform and dense gluten network structure \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. When the gluten protein experiences greater polymerization, the resulting complete, continuous, and tight gluten network structure traps the starch, preventing its expansion and leaching, thereby improving the noodles' edible quality \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The gluten network imparts structural strength to noodles, yet protein content alone does not fully determine the textural qualities of wheat-based products. Factors such as protein composition, including molecular weight, the presence of disulfide bonds, and the ratio of monomeric to polymeric proteins, can also impact texture. Nonetheless, the specific influence of protein composition on the textural properties of noodles requires additional research \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The poor gluten network in 50WF:50FWF and 25WF:75FWF likely contributed to significantly (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) lower textural parameters. An underdeveloped gluten network could diminish the textural quality of noodles \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Structural breakdown analysis\u003c/h2\u003e \u003cp\u003eThe direct link between structural breakdown properties and FWF highlights their importance for noodles. An entire extrusion cycle includes both downward and upward movements, and the patterns of structural breakdown in the noodles can be observed across 20 extrusion cycles \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The MEC parameters derived from the decay curves are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The FWF ratio significantly impacted the structure breakdown analysis, exhibiting a similar trend. The order was: 100WF, 75WF:25FWF\u0026thinsp;\u0026gt;\u0026thinsp;50WF:5FWF, 25WF:75FWF. Work 1st, which is the area under each downward extruding motion, indicates the amount of work needed to break down the entire noodles. The work measured in the first extrusion cycle (w\u003csub\u003e1\u003c/sub\u003e) reflects the amount of effort required to break down the intact noodle and w\u003csub\u003einf\u003c/sub\u003e represents work per cycle after an infinite number of extrusions, signifying that the entire structure has been broken down \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Both values show a positive correlation with the hardness \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. n\u003csub\u003e1\u003c/sub\u003e indicates the rate of degradation as the number of extrusions increased. A higher n\u003csub\u003e1\u003c/sub\u003e value implies a slower breakdown rate, suggesting that the samples breakdown slowly \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The work and n\u003csub\u003e1\u003c/sub\u003e values for 100WF and 75WF:25FWF are the highest (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and correlate closely with the textural results (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Both types of noodles required more effort to break down their integral structure, likely attributable to their increased hardness and firmer texture, resulting from a denser gluten network. 50WF:50WF and 25WF:75FWF scored the lower work and n\u003csub\u003e1\u003c/sub\u003e values (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating less work required and their high breakdown rate, which corresponds well with their textural results.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.5 SEM\u003c/h2\u003e \u003cp\u003eThe drying process involves the shrinking of noodles, decrease of surface moisture, outward movement, diffusion, and evaporation of water from the noodles, potentially resulting in the formation of pores of various sizes within the product. The pores affect the rate of moisture diffusion by facilitating the entry of water and heat transfer, thereby accelerating starch gelatinization and decreasing the edible quality of the noodles \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. During cooking, starch granules absorb water and expand, leading to the formation of a dual-network hydrogel composed of gelatinized starch and solidified gluten \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The microstructure of cooked noodles cross section is demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The gluten structures in 100WF (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea) and 75WF:25FWF (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb) were denser, tighter and more compact, featuring numerous small pores due to their higher protein content, which contributed to lower cooking losses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). The pores in 100WF ranged from 20.98 to 111.9 \u0026micro;m, whereas those in 75WF:25FWF ranged from 29.49 to 51.6 \u0026micro;m. Liu et al. (2024) reported that the protein tightly surrounded the starch granules, forming a more compact structure with smaller pores. This tight and dense gluten structure is crucial for textural quality and structural integrity, contributing to improved results in textural (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and structural breakdown analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) for both samples. Additionally, the abundance of smaller pores may enhance water absorption during cooking, which is reflected in the higher cooking yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) and reduced breakability (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed) observed in both samples. The weakened gluten network in 50WF:50FWF (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec) and 25WF:75FWF (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed) likely led to increased cooking loss and breakability. Moreover, the presence of larger and more irregular pores in 50WF:50FWF (90.91-136.36 \u0026micro;m) and 25WF:75FWF (98.21-357.14\u0026micro;m) suggest uneven shrinkage during drying, adversely affecting the textural quality of noodles. This effect is evident in both samples, which demonstrated poor outcomes in texture and structural breakdown analysis. Liu et al., (2024) also found that larger pores contributed to increased residual stress and led to uneven protein distribution in dried noodles.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Proximate composition\u003c/h2\u003e \u003cp\u003eThe samples of 100WF and 75WF:25FWF were selected for proximate composition analysis and sensory evaluation because both demonstrated excellent and positive handling characteristics, being easy to work with and maintaining a manageable texture throughout the process. The pH levels of these samples influence the overall taste and texture of the noodles. Therefore, formulations with desirable pH levels for proximate composition and sensory acceptance are prioritized. Additionally, both samples exhibited higher cooking yield and textural characteristic, lower cooking loss and breakability, which are especially prioritized to ensure superior structural integrity.\u003c/p\u003e \u003cp\u003eThe proximate composition of 100WF and 75WF:25FWF are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The incorporation of FWF influenced all the proximate composition of dried noodles, except for the fat content. The moisture content of 100WF was significantly higher than that of 75WF:25FWF. Yang et al. (2024) reported similar findings, stating that the moisture content of noodles increased with the gluten ratio. They explained that gluten protein possessed a greater capacity for water absorption compared to raw starch, which could increase moisture content in noodles with higher gluten content. Furthermore, increasing the gluten content not only enhances their water retention capabilities during the drying process but also significantly slows the rate of moisture loss during drying phases \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The moisture content of both types of noodles were below the 14% threshold set by the Codex Alimentarius Commission for non-fried noodles, making them suitable for extended storage. Lower moisture content extends the shelf life of food products by preventing microbial growth and reducing the risk of spoilage and flour quality degradation \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The low fat content of the samples might imply a reduced susceptibility to rancidity, especially given their low moisture content, as suggested by \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. 75WF:25FWF possessed a higher ash content (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than 100WF and yielded, which resulted in an increased a* value (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). The increase in ash content could be associated with the release of bound mineral elements following the breakdown of antinutrient compounds during the fermentation of wheat flour \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Flour with a higher ash content reduced the brightness and darken the colour of noodles \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The significantly higher fibre content observed in 75WF:25FWF could be related to the higher fibre content (~\u0026thinsp;17.6% crude fibre) in FWF, or a different type of wheat flour, such as whole wheat flour, known for its higher fibre \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The carbohydrate content in 75WF:25FWF was significantly lower due to the higher levels of ash and fibre in the noodles.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProximate composition and sensory evaluation of selected noodles samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100WF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75WF:25FWF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProximate composition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoisture (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat (%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsh (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude fibre (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensory evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAroma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTexture*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall acceptability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eResult display mean values\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for proximation composition (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) and sensory evaluation (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;30). Different letters superscripted indicate significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between different samples. *No significant difference was observed in fat content and sensory texture. Kindly refer Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for noodle sample definitions and descriptions.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Sensory evaluation\u003c/h2\u003e \u003cp\u003eThe results of the five sensory qualities are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Panellists showed a preference for the colour, aroma, taste, and overall acceptability of 100WF. 75WF:25WFW exhibited a higher a* value (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), potentially leading to a lower rating in sensory colour. The colour of noodles is a crucial determinant of quality. Consumers are initially attracted to noodles that have a bright, even colour without darkening or discoloration \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The lower ratings for aroma, taste and overall acceptability of 75WF:25FWF were likely due to the distinct acidic flavour from organic acids (lactic and acetic acid) produced from LAB, which affected the taste and acceptability attributes. LAB also released proteases that broke down proteins into peptides and amino acids, enhancing the fundamental flavours of fermented foods. Additionally, specific enzymes like lipase and phospholipase, secreted by LAB, facilitated lipolysis, resulting in the formation of free fatty acids. These acids play a crucial role as key aroma compounds in many fermented foods \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. However, panellist did not detect a significant difference in texture between both types of noodles, consistent with the results from textural properties (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Sensory evaluations of noodle texture corresponds closely with instrumental textural measurements, such as hardness TPA \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"4.0 Conclusion","content":"\u003cp\u003eIn conclusion, the addition of FWF notably decreased the optimum cooking time, cooking yield, pH, and lightness, while it enhanced the redness and yellowness of the noodles. Noodles with a FWF content exceeding 50% experienced increased cooking losses and breakability, along with reduced textural and structural integrity. SEM demonstrated that such noodles possessed a deteriorated gluten structure characterized by larger and more irregular pores. In contrast, 75WF:25FWF maintained cooking performance and structural integrity comparable to 100WF, featuring a compact and dense gluten network with smaller pores that improved cooking performance and texture. The proximate composition analysis indicated that the 75WF:25FWF had lower moisture and higher fibre content. Although sensory evaluations yielded lower scores, the textural differences were minimally perceptible. The incorporation of FWF could potentially offer health benefits due to a higher fibre content, suggesting that FWF has promising applications in enhancing the nutritional profile of dried noodles while maintaining acceptable cooking and textural qualities. Future research could investigate the influence of fermented wheat flour on various noodle varieties, and assess the scalability of these findings for broader industrial applications to potentially enhance nutritional profiles and consumer satisfaction across different markets.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the Ministry of Higher Education Malaysia for Prototype Development Research Grant (PRGS) with Project Code: PRGS/1/2022/TK02/USM/01/1 for funding. The authors acknowledge the School of Industrial Technology, Universiti Sains Malaysia and Centre for Global Archaeological Research, Universiti Sains Malaysia for testing facilities and the support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShin-Yong Yeoh: Writing - Review \u0026amp; Editing, Validation, Formal analysis, Investigation, Methodology, Data Curation, Visualization, Project administration. Viklawan Fricher: Writing - original draft, Formal analysis, Investigation, Methodology. Lubowa Muhammad: Conceptualization, Methodology, Validation, Writing - Review \u0026amp; Editing. Ojukwu Moses: Writing - Review \u0026amp; Editing. Azhar Mat Easa: Conceptualization, Methodology, Validation, Resources, Supervision, Writing - Review \u0026amp; Editing, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest declaration. \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no financial or non-financial competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData sharing is not applicable to the main text. The data supporting the findings of this study are available on request from the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the University human ethics committee (code number: USM/JEPeM/23110839, Jawatankuasa Penyelidikan Manusia USM (JEPeM)). 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Nutr. 0, 1\u0026ndash;20 (2024).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"physicochemical, sensory, structural breakdown, microstructure, dried white salted noodles, fermented wheat flour","lastPublishedDoi":"10.21203/rs.3.rs-4504789/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4504789/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigated the physicochemical properties, cooking characteristics, structural breakdown, microstructure, and sensory qualities of dried white salted noodles with varying proportions of fermented wheat flour (FWF). The noodle formulations included 100% commercial wheat flour (100WF), 75% wheat flour with 25% FWF (75WF:25FWF), 50% of each (50WF:50FWF), and 25% wheat flour with 75% FWF (25WF:75FWF). Incorporating FWF reduced the optimum cooking time, cooking yield, pH and lightness values but increased the redness and yellowness values. Noodles with over 50% FWF exhibited greater cooking losses, increased breakability and lower textural and structural breakdown values. Scanning Electron Microscopy revealed that noodles with over 50% FWF had a weakened gluten structure with larger, more irregular pores. In contrast, 75WF:25FWF maintained similar cooking performance and structural integrity as 100WF, both featuring a compact and dense gluten network with smaller pores, which not only required significant effort to break down but also contributed to superior cooking performance and excellent texture. Proximate composition analysis revealed that 75WF:25FWF had lower moisture and higher fibre content. Despite lower sensory scores, the textural differences were not significantly noticeable. Incorporating FWF could potentially enhance the nutritional value of noodles by increasing fibre content while maintaining acceptable cooking and textural qualities.\u003c/p\u003e","manuscriptTitle":"Impact of fermented wheat flour on the quality of dried white salted noodles: cooking, physicochemical, structural breakdown, microstructure and sensory evaluations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-12 06:11:10","doi":"10.21203/rs.3.rs-4504789/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3bf81df8-2808-4e7f-82c8-acdd5f75bd4d","owner":[],"postedDate":"July 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":32661614,"name":"Biological sciences/Biochemistry"},{"id":32661615,"name":"Biological sciences/Biochemistry/Carbohydrates"}],"tags":[],"updatedAt":"2024-08-08T06:15:12+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-12 06:11:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4504789","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4504789","identity":"rs-4504789","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}