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. 2025 Aug 18;11:101178. doi: 10.1016/j.crfs.2025.101178

Upcycling defatted rice bran into alginate based noodles via hydrocolloid assisted development and assessment of structural and functional properties

Siriyakorn Chantieng a, Vernabelle Balmori b, Kasinee Katelakha c, Tanyawan Suantawee a, Sathaporn Ngamukote a, Charoonsri Chusak a, Sirichai Adisakwattana a,⁎
PMCID: PMC12745821  PMID: 41473541

Abstract

Upcycling defatted rice bran (DRB), a nutrient rich byproduct of rice milling, offers a sustainable way to add value and reduce waste. Despite its nutritional potential, its coarse texture, low stability, and poor compatibility with food systems limit its direct application. This study aimed to valorize DRB by formulating functional noodles using alginate-based encapsulation and to investigate the effects of different hydrocolloids including gelatin, carrageenan, and agar on noodle structure, texture, in vitro digestion, and phenolic release. Sodium alginate was used at 1.8 % (w/v), DRB at concentrations ranging from 1 to 5 % (w/v), and hydrocolloids at 0.25–1.0 % (w/v). Response Surface Methodology identified the optimal formulation as 1.0 % (w/v) DRB combined with 1.0 % (w/v) hydrocolloid. Gelatin significantly improved tensile strength and encapsulation efficiency, carrageenan softened the texture, and agar provided balanced textural properties. FT-IR revealed stronger hydrogen bonding in gelatin-based noodles, while X-ray diffraction (XRD) indicated increased crystallinity. LC-MS-MS analysis confirmed greater retention of phenolic acids, particularly ferulic and sinapic acids, in gelatin formulations following thermal processing. In vitro digestion showed that gelatin-based noodles released the most phenolics and proteins with superior antioxidant activity, suggesting improved bioavailability. Although DRB incorporation increased glucose release in all formulations, the gelatin DRB combination yielded the lowest glucose release, likely due to the gel matrix formed by gelatin acting as a diffusion barrier. The findings suggest that alginate-based noodles can be sustainably developed using DRB, with gelatin enhancing structural integrity and bioactive stability, supporting a novel approach to functional food innovation.

Keywords: Hydrocolloid, Gelatin, Carrageenan, Agar, Noodles, Encapsulation, Defatted rice bran

Graphical abstract

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Highlights

  • •

    Gelatin enhanced encapsulation efficiency and tensile strength of noodles.

  • •

    Alginate-encapsulated DRB noodles retained higher phenolic content post-digestion.

  • •

    Gelatin noodles exhibited strongest molecular interactions (FTIR, XRD evidence).

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    Optimized formulations improved antioxidant activity and protein bioaccessibility.

  • •

    Upcycled defatted rice bran into sustainable functional noodles with superior quality.

1. Introduction

The increasing global emphasis on sustainability and food waste reduction has driven efforts to repurpose food processing by-products into value-added products. Defatted rice bran (DRB), a by-product of rice milling, is a nutrient-rich material with considerable potential due to its high content of dietary fiber, protein, and phenolic compounds such as ferulic, sinapic, and p-coumaric acids (Peanparkdee et al., 2019). Despite these beneficial components, DRB remains underutilized, primarily due to its coarse texture, poor stability, and limited compatibility with conventional food formulations. As a result, DRB is frequently discarded or utilized in low-value applications such as animal feed, representing a significant missed opportunity for functional food development (Alexandri et al., 2020). To address this, innovative strategies are required to integrate DRB into food systems, reducing waste while creating functional products with measurable health benefits.

Noodles, a widely consumed staple food across diverse cultures, provide a promising matrix for DRB incorporation due to their adaptability and broad consumer acceptance (Xie et al., 2025). However, the direct addition of DRB poses formulation challenges, including adverse effects on texture and sensory attributes. Moreover, phenolic compounds in DRB are susceptible to degradation during processing, diminishing their bioactive potential. Encapsulation technologies, along with the incorporation of hydrocolloids, have been proposed as strategies to stabilize these compounds, improve noodle structure, and preserve functional properties during digestion (Zabot et al., 2022). Among such approaches, alginate-based encapsulation has emerged as a promising technique, offering protection against phenolic compound degradation and facilitating targeted release within the gastrointestinal tract (Abdel-Aty et al., 2025). This strategy directly overcomes the limitations of previous studies in which DRB-derived phenolics failed to retain their bioactivity under conditions of thermal processing and digestive stress.

Hydrocolloids play a dual role in enhancing both noodle structure and the delivery of phenolic compounds. Commonly utilized hydrocolloids such as gelatin, carrageenan, and agar are well-established in food systems for their ability to improve texture, stability, and moisture retention. Gelatin, a protein derived from collagen, forms elastic gels that contribute to noodle firmness and chewiness (Ali et al., 2019; Burey et al., 2008). Carrageenan, a seaweed-derived polysaccharide, serves as a thickening and stabilizing agent, improving flexibility and moisture retention (Jíménez-Arias et al., 2023). Agar, also derived from seaweed, forms firm gels that support structural integrity (Burey et al., 2008). Investigating the effects of these hydrocolloids on DRB-fortified noodles is essential to determine the most effective formulation for optimizing physical and nutritional properties. Additionally, hydrocolloids may enhance the release and stability of DRB-derived bioactive during gastrointestinal digestion, promoting their absorption and health effects (Burey et al., 2008).

To optimize such multifactorial food systems, the application of factorial experimental designs is indispensable. However, despite technological advances, limited research has systematically employed factorial designs to investigate the incorporation of DRB and its interactions with hydrocolloids in noodle formulations. In the present study, Response Surface Methodology (RSM) is utilized to assess the effects of critical formulation variables, determine optimal conditions, and address the shortcomings of unstructured, single-factor experimental approaches prevalent in earlier research (Abdel-Aty et al., 2023).

This study aims to upcycle defatted rice bran (DRB) into functional noodles through alginate-based encapsulation. First, it employs Response Surface Methodology (RSM) to systematically design and optimize formulations. Second, it investigates the effects of different hydrocolloids including gelatin, carrageenan, and agar on the structural, textural, and functional characteristics of the noodles, with particular attention to their interactions with alginate. Third, it evaluates the in vitro digestion and bioaccessibility of phenolic compounds to clarify how the type of hydrocolloid influences nutrient release. These findings contribute to the development of sustainable, nutrient-enriched food products by highlighting the effective use of DRB and hydrocolloids in functional noodle formulation.

2. Materials and methods

2.1. Materials

Defatted rice bran flour was obtained from King Rice Oil Group Co., Ltd. (Bangkok, Thailand) Sodium alginate, gelatin, carrageenan, agar, and calcium chloride were purchased from Krungthepchemi Co., Ltd. (Bangkok, Thailand) Folin–Ciocalteu reagent, pepsin from porcine gastric mucosa powder (250 U/mg), α-amylase Type VI-B from porcine pancreas (15.8 U/mg), pancreatin from porcine pancreas (4 × U.S. Pharmacopeia (USP) specifications), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and gallic acid were purchased from Sigma-Aldrich, Inc. (St. Louis, MO, USA). Amyloglucosidase (3260 U/mL) was obtained from Megazyme International Ireland Ltd. (Bray, Ireland). The glucose oxidase kit (Glucose liquicolor) was sourced from Human Diagnostics (Wiesbaden, Germany).

2.2. Preparation of defatted rice bran noodles

Sodium alginate (1.8 % w/v) was dissolved in distilled water and heated to 60 °C with magnetic stirring for 30 min until fully homogenized. Defatted rice bran powder at concentrations of 1 %, 3 %, or 5 % (w/v) was then added, followed by gelatin, carrageenan, or agar in varying amounts (0.25 %, 0.5 %, or 1 %, depending on the formula). The mixture was stirred for another 30 min and then removed from the hotplate. The solution was extruded into a 1.2 % (w/v) calcium chloride cross-linking bath using a Baoding Longer Precision Pump (Hebei, China) set at 600 rpm. The cross-linking solution was maintained at room temperature, with a pH of 7. The extruded noodles were left in the cross-linking bath for 4 min under gentle magnetic stirring at 200 rpm to ensure even gelation. Finally, the noodles were rinsed with distilled water to remove excess calcium ions.

2.3. Optimization of defatted rice bran noodles by response surface methodology (RSM)

To evaluate the effects of two experimental factors on three parameters of defatted rice bran noodles, response surface methodology (RSM) was applied using Statistica software. The independent variables were defatted rice bran (X1:1–5 %) and hydrocolloid type (X2: gelatin, carrageenan, or agar at 0.25–1 %). A two-level factorial design with two factors was employed, resulting in 40 experimental runs. Optimal values for the selected variables were determined by solving the multiple regression equation as shown in Supplement Table 4S.

The selection of variable ranges for defatted rice bran (DRB) and hydrocolloids was informed by our preliminary formulation trials, evidence from the literature, and practical manufacturing feasibility. Our results indicated that 5 % DRB represented the maximum inclusion level at which noodle structure and texture could be maintained; higher concentrations could not form noodles due to excessive brittleness and breakage. A lower bound of 1 % was established to ensure a nutritionally meaningful level of DRB while minimizing formulation challenges. Concentrations below 1 % were excluded due to their limited potential to deliver functional or upcycling benefits.

For hydrocolloids (gelatin, carrageenan, and agar), we selected a range of 0.25–1.0 % based on their documented functional roles in food systems and validation through our preliminary trials Saha and Bhattacharya (2010). Our texture analyzer measurements showed that at concentrations over 1 %, hydrocolloids combined with alginate often produced undesirable textural properties such as gumminess or excessive gel firmness, particularly in fiber-rich formulations, and could not be extruded from the Pump. While the RSM model identified optimal textural and structural outcomes near the upper bound of 1.0 %, higher concentrations were not pursued due to the risk of negative sensory attributes, processing difficulties, and diminishing returns.

Based on the outputs of the RSM model and subsequent experimental validation, eight representative formulations were selected for further analysis to represent both control and optimized conditions. Alphabetical codes were assigned as follows: Formulation A consisted of 1.8 % alginate alone (control); Formulations B–D included 1.8 % alginate with 1 % of gelatin, carrageenan, or agar, respectively; Formulation E comprised 1.8 % alginate with 1 % DRB; and Formulations F–H consisted of 1.8 % alginate with 1 % DRB in combination with 1 % gelatin, carrageenan, or agar, respectively.

2.3.1. Texture analysis

The texture profile analysis (TPA) of cooked noodles was performed with slight modifications based on a previous study (Suklaew et al., 2021). Noodles were cooked for 90 s, and the analysis was conducted using a TA-XT Plus texture analyzer (Stable Micro Systems Ltd., Haslemere, UK) with a P75 probe and a Spaghetti/Noodle Rig. For hardness measurements, three strands of cooked noodles (5 cm in length) were compressed at a pre-test speed of 1.0 mm/s, a test speed of 5.0 mm/s, and a post-test speed of 5.0 mm/s, with a 75 % compression of their original thickness. Tensile strength was measured using the Spaghetti/Noodle Rig on 15 cm strands in triplicate. The test used a pre-test speed of 1.0 mm/s, a test speed of 3.0 mm/s, and a post-test speed of 10.0 mm/s.

2.3.2. Encapsulation efficiency

The encapsulation efficiency (% EE) was calculated based on total phenolic content (TPC) data, using a modified Folin-Ciocalteu assay adapted from a previous study (Wongverawattanakul et al., 2022). To prepare the sample, 2 g was dissolved in 6 mL of sodium citrate solution (5 % w/v) to break down the alginate coating. The mixture was stirred for 30 min until fully dissolved, then centrifuged at 10,000 rpm for 20 min. The supernatant was collected for TPC measurement. For the assay, 50 μL of the sample solution was mixed with 50 μL of Folin-Ciocalteu reagent and incubated at room temperature for 10 min. Then, 50 μL of sodium carbonate solution (10 % w/v) was added, and the mixture was incubated for an additional 30 min at room temperature. The absorbance was measured at 760 nm using a UV–vis spectrophotometer (BioTek PowerWave XS2, Winooski, VT, USA). Gallic acid was used as the standard reference, and its concentration was determined using a calibration curve. Encapsulation efficiency (% EE) was calculated using the following equation:

Encapsulationefficiency(%EE)=TPCe/TPCi (1)

where TPCe was the total phenol content encapsulated in the sample, while TPCi was the total phenol content encapsulated in the initial extract solution.

2.4. Quality properties analysis of defatted rice bran noodles

The cooking yield was determined following the method described in a previous study (Xie et al., 2025). The weight of the noodle solution was measured before extrusion through a pump (Baoding Longer Precision Pump Co., Ltd., Hebei, China) into a CaCl2 solution. After rinsing the extruded noodles with distilled water, their net weight was recorded. The cooking yield was calculated using the equation:

%Yield=[(Weightoffinalnoodles−Noodlessolution)/(Noodlessolution)]×100 (2)

The color analysis of cooked noodles was conducted using a colorimeter (ColorFlex, Hunter Associates Laboratory, Inc., VA, USA) according to the previous study (Suklaew et al., 2021). Noodle sheets (5 × 5 cm) were boiled for 90 s at a 1:10 (w/v) noodle-to-water ratio. After calibration of the instrument (45°/0° geometry, 10° observer) with standard black glass and a white tile, the color values L∗ (lightness), a∗ (red-green), and b∗ (yellow-blue) were recorded.

2.5. Fourier transform infrared spectroscopy (FTIR) analysis of defatted rice bran noodles

The interaction between defatted rice bran flour and hydrocolloids was characterized by FTIR using a spectrometer (Alpha II, Bruker, Massachusetts, USA). Four scans between 675 and 4000 cm−1 were obtained. The cooked noodle samples were semi-dried for 6 h at room temperature (25 °C). On the FTIR sample holder, a 2 mg sample of the semi-dried noodles was placed. The different peaks in the noodles' FTIR spectra were examined and interpreted.

2.6. X-ray Diffractometer (XRD) analysis of defatted rice bran noodles

X-ray diffraction (XRD) patterns of the noodles were obtained using an X-Ray Diffractometer (Bruker AXS Model D8 Discover, Leipzig, Germany) equipped with a copper tube operating at 40 kV and 45 mA. The spectra were scanned over a diffraction angle (2θ) range of 5–40° at a scan rate of 0.02° 2θ/second. Semi-dried noodle samples were prepared by cooking the noodles and allowing them to rest at 25 °C for 6 h. A 1 g sample of the noodles was placed in a container and transferred to the analyzer. The percentage of crystallinity was calculated using the following equation.

%Relativecrystallinity=(Areaabovethesmoothcurve/Totaldiffractionareaabovethebaseline)×100

2.7. In vitro digestibility analysis of noodles

In vitro digestion was performed following a previous method with slight modifications (Suklaew et al., 2020). Cooked noodle samples (30 g) were first subjected to the oral phase, during which 1 mL of α-amylase (250 U/mL in 0.2 M carbonate buffer, pH 7) was added and mixed for 20 s. The mixture was then combined with 5 mL of pepsin solution (3200 U/mL in 0.02 N HCl, pH 2) and incubated at 37 °C in a water bath shaker (100 rpm) for 1 h. To neutralize the digesta, 25 mL of 0.2 M sodium acetate buffer (pH 6) and 5 mL of 0.02 N NaOH were added. Next, 5 mL of a solution containing amyloglucosidase (28 U/mL) and porcine pancreatin (2 mg/mL in 0.2 M sodium acetate buffer, pH 6) was added. Samples were collected at 0, 20, 30, 60, 90, 120, and 180 min, and the reaction was stopped by heating at 105 °C for 10 min. The samples were then centrifuged at 11,000 rpm for 15 min at 25 °C. The supernatant was collected for analysis of TPC, ninhydrin, antioxidant activity, LCMS and glucose determination using a glucose oxidase kit (Human diagnostics, Wiesbaden, Germany). TPC, ninhydrin-reactive compounds, antioxidant activity, and glucose were analyzed at each digestion time point (0–180 min), and the incremental area under the curve (iAUC) was calculated. The simulated digestion profiles over the 180-min period are presented in Supplementary Fig. 2S. In contrast, LC-MS analysis was conducted only at 180 min, comparing the digested sample (180 min digesta) with the undigested noodle extract to evaluate changes in compound profiles due to in vitro digestion.

2.8. Total phenolic content (TPC)

The TPC released for the noodle samples was determined using the Folin-Ciocalteau assay, as previously described.

2.9. Protein content (ninhydrin)

Ninhydrin was measured following a method from a previous study (Sachanarula et al., 2022). Briefly, 20 μL of each sample was mixed with 380 μL of distilled water and 200 μL of ninhydrin reagent. The mixture was heated at 100 °C for 10 min, then cooled for 10 min, and the absorbance was measured at 568 nm using a microplate reader (PowerWave XS2, BioTek, Winooski, VT, USA). Lysine, with concentrations ranging from 1.56 to 200 μg/mL, was used as the standard for calibration.

2.10. Antioxidant activity

Initially, 10 μL of supernatant was combined with 90 μL of 0.2 mM DPPH solution in ethanol, followed by a 30-min incubation in darkness. Absorbance readings at 515 nm were measured, with ethanol serving as the blank. The result was reported as mg ascorbic acid/mL.

2.11. Determination of phytochemical compounds

The preparation and analysis of phytochemical compounds were conducted using LC-MS-MS, following a modified version of the method described by Peanparkdee et al. (2019). Cooked noodles (100 g) were mixed with 30 mL of 0.1 % formic acid in methanol and stirred for 30 min. The mixture was filtered through a 0.45 μm nylon syringe filter, then centrifuged at 12,000 rpm for 10 min. The supernatant was collected and desiccated at 40 °C for 24 h. The dried sample was resuspended in 100 μL of 0.1 % formic acid in methanol, centrifuged again, and transferred to a glass tube for analysis.

LC-MS-MS analysis was performed using a Dionex Ultimate 300 UHPLC system (Thermo Fisher Scientific) coupled with a QTOF Impact II mass spectrometer (Bruker Daltonics). Separation was achieved on a Hypersil GOLD C18 column (2.1 × 100 mm, 1.9 μm) with a flow rate of 0.3 mL/min and a gradient elution from 0 to 99 % acetonitrile (B) over 15 min. The total run time was 25 min with a 3 μL injection. Mass spectra were acquired in positive ESI mode (m/z 50–1200), with a collision energy of 20 eV and a capillary voltage of 3800 V. Targeted analysis compared the extract to standard phenolic compounds, including protocatechuic, p-coumaric, ferulic, and sinapic acids. Quantification was performed using a six-point calibration curve (0–0.01 mg/mL), and compound identification was based on retention times and mass/charge ratios. Triplicate analyses were conducted to ensure analytical reliability.

2.12. Statistical analysis

The results were expressed as mean ± standard error of the mean (SEM) for N = 3. One-way analysis of variance (ANOVA) followed by Tukey's test was used to compare the differences between individual means, with p < 0.05 considered significant. All statistical analyses were conducted using SPSS version 29.0. Surface Methodology (RSM) was performed using Statistica version 13.5 to develop regression models, evaluate the significance of model terms, and determine the optimal formulation conditions.

3. Results and discussion

3.1. Optimization of formulation parameters for the development of defatted rice bran alginate

The effects of hydrocolloid type and defatted rice bran (DRB) concentration on encapsulation efficiency (EE), tensile strength, and hardness of alginate-based noodles are summarized in Table 1, Table 2, Table 3S. The results demonstrate that both the type and concentration of hydrocolloids significantly influence the structural and functional performance of the noodle matrix.

Table 1.

Effect of hydrocolloid addition on yield, color values, texture, and encapsulation efficiency of defatted rice bran alginate encapsulation noodles.

Formulation Yield (%) Lightness (L∗) Redness (a∗) Yellowness (b∗) Tensile Strength (g) Hardness (g) Encapsulation Efficiency (%)
A (Control) 76.83 ± 0.62a 41.94 ± 0.07d −1.09 ± 0.02cd −0.57 ± 0.06e 32.77 ± 0.29e 6547.95 ± 36.38e NA
B 77.06 ± 0.47a 39.57 ± 0.15a −1.13 ± 0.07b −0.46 ± 0.32bc 54.10 ± 0.84a 8645.05 ± 19.23b NA
C 79.17 ± 0.52a 35.12 ± 0.13c −0.91 ± 0.05cd −1.06 ± 0.12e 45.96 ± 0.80c 9568.21 ± 18.20a NA
D 77.43 ± 0.57a 41.92 ± 0.04f −1.33 ± 0.03c 0.42 ± 0.01c 46.39 ± 0.75c 8501.21 ± 49.25b NA
E 79.88 ± 0.36a 50.35 ± 0.02d 2.12 ± 0.06d 20.89 ± 0.14d 38.50 ± 0.49d 8227.36 ± 12.97c 39.92 ± 0.55c
F 80.10 ± 0.38a 49.97 ± 0.01b 2.85 ± 0.13a 21.84 ± 0.19a 57.31 ± 0.84a 8518.88 ± 40.53b 59.51 ± 0.65a
G 79.91 ± 0.50a 50.05 ± 0.02ab 1.92 ± 0.13b 20.11 ± 0.14c 50.20 ± 0.99b 7770.37 ± 48.44d 55.48 ± 0.51b
H 79.06 ± 0.45a 49.02 ± 0.01c 2.82 ± 0.09ab 21.17 ± 0.16b 55.06 ± 0.34a 8096.24 ± 47.91c 54.63 ± 0.32b
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Values are presented as mean ± standard error of the mean (SEM), n = 3. Different superscript letters in the same column indicate a significant difference (p < 0.05). Formulations: A = 1.8 % alginate (control); B–D = 1.8 % alginate with 1 % gelatin, carrageenan, or agar, respectively; E = 1.8 % alginate with 1 % defatted rice bran (DRB); F–H = 1.8 % alginate with 1 % DRB and 1 % gelatin, carrageenan, or agar, respectively. NA = not applicable (formulation does not contain DRB for encapsulation efficiency testing).

Table 2.

Phenolic compound release in defatted rice bran alginate encapsulation noodles with various types of hydrocolloids.

Formulation Phenolic compounds (μg/mg sample)
Ferulic acid Sinapic acid p-coumaric acid Protocatechuic acid
E 93.74 ± 0.05c 18.25 ± 0.07c 9.57 ± 0.07c 4.35 ± 0.03a
F 99.80 ± 0.04a 20.77 ± 0.06a 10.06 ± 0.04a 4.41 ± 0.07a
G 99.21 ± 0.07b 20.58 ± 0.06a 9.71 ± 0.00bc 4.41 ± 0.03a
H 99.36 ± 0.11b 19.44 ± 0.12b 9.87 ± 0.03ab 4.45 ± 0.07a
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Values are expressed as mean ± standard error of the mean (SEM), n = 3. Different superscript letters within each column indicate significant differences (p < 0.05). Formulation E consists of 1.8 % alginate with 1 % defatted rice bran (DRB), while formulations F to H contain 1.8 % alginate with 1 % DRB and 1 % gelatin, carrageenan, or agar, respectively.

Table 3.

Phenolic compound release in digesta of defatted rice bran alginate encapsulation noodles with various types of hydrocolloids.

Formulation Phenolic compounds (μg/mL)
Ferulic acid Sinapic acid p-coumaric acid Protocatechuic acid
E 2.03 ± 0.02a 3.18 ± 0.01a 6.43 ± 0.02c 4.81 ± 0.06a
F 2.01 ± 0.01a 3.32 ± 0.01a 7.92 ± 0.06a 4.25 ± 0.04b
G 1.88 ± 0.06a 3.11 ± 0.05a 7.17 ± 0.20b 4.59 ± 0.15ab
H 1.96 ± 0.11a 3.22 ± 0.11a 7.03 ± 0.12b 4.90 ± 0.03a
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Values are expressed as mean ± standard error of the mean (SEM), n = 3. Different superscript letters within each column indicate significant differences (p < 0.05). Formulation E contains 1.8 % alginate with 1 % defatted rice bran (DRB), while formulations F to H contain 1.8 % alginate with 1 % DRB and 1 % gelatin, carrageenan, or agar, respectively.

Gelatin at a 1 % concentration consistently achieved the highest encapsulation efficiency (EE) across all DRB levels. The peak encapsulation efficiency was observed in Alg1.8 %+DRB1 %+G1 % at 67.56 ± 0.76 % (Table 1S), while the corresponding values at DRB3 % and DRB5 % were 49.51 ± 0.65 % and 47.95 ± 0.92 %, respectively (Table 2, Table 3S). This trend indicates that the beneficial effect of gelatin on EE decreases as DRB content increases, possibly due to interference from high fiber content. Carrageenan and agar resulted in moderate EE values. For example, C1 % showed 58.34 ± 0.69 % (DRB1 %), 55.48 ± 0.51 % (DRB3 %), and 49.80 ± 0.22 % (DRB5 %), while A1 % showed 57.88 ± 0.64 %, 54.63 ± 0.32 %, and 56.36 ± 0.48 %, respectively. These patterns suggest a relative stability of EE with agar, contrasting with the more variable results from carrageenan, which may be due to its brittle gel structure (Saha and Bhattacharya, 2010; Udo et al., 2023).

For tensile strength, the highest value was found in Alg1.8 %+DRB1 %+A1 % (68.51 ± 0.89 g) (Table 1S), while at DRB3 %, A0.25 % gave the maximum (59.93 ± 0.26 g), and at DRB5 %, C0.5 % provided the highest (61.95 ± 0.02 g) (Table 2, Table 3S). These findings indicate that agar is effective in maintaining tensile strength at lower DRB, while carrageenan becomes more effective at higher DRB levels due to its rigid helix structure and ionic crosslinking potential (Huang et al., 2007; Nisa, 2021). Gelatin showed intermediate but consistent values across DRB concentrations: G1 % yielded 54.15 ± 0.55 g (DRB1 %), 57.31 ± 0.84 g (DRB3 %), and 48.27 ± 0.25 g (DRB5 %), suggesting that its gel matrix offers flexibility but is increasingly challenged by high fiber load.

Regarding hardness, the maximum value was observed at DRB1 %+G0.5 % (9369.12 ± 62.07 g) (Table 1S). However, as DRB concentration increased, hardness values generally declined. For instance, G0.5 % produced 8819.08 ± 40.31 g (DRB3 %) and 8512.74 ± 53.63 g (DRB5 %). Likewise, for alginate-only noodles, hardness decreased from 9634.84 ± 30.94 g (DRB1 %) to 8227.36 ± 12.97 g (DRB3 %) and 7777.06 ± 31.61 g (DRB5 %), indicating that increasing DRB disrupts matrix compactness, leading to softer textures. Carrageenan and agar also followed this pattern, with the lowest hardness observed in C1 % at DRB5 % (7436.05 ± 54.40 g).

Overall, increasing DRB from 1 % to 5 % reduced EE, tensile strength, and hardness in many formulations, particularly where hydrocolloids could not compensate for fiber-induced matrix disruption (Zabot et al., 2022; Elsebaie et al., 2022). Notably, gelatin at 0.5–1 % concentration produced the best combination of encapsulation and mechanical properties, although the optimal concentration varied with DRB level.

These findings highlight the importance of optimizing both hydrocolloid type and concentration alongside DRB levels to preserve functional and textural integrity in noodle formulations. As the interactions are nonlinear and multivariate, the use of response surface methodology (RSM) is justified for identifying the optimal formulation matrix (Deng et al., 2023; Elsebaie et al., 2022).

3.2. Comparative evaluation of hydrocolloids on physicochemical properties of DRB alginate encapsulation noodles

To determine the optimal formulation, DRB–alginate noodle samples with varying hydrocolloid types and concentrations were initially screened for encapsulation efficiency, tensile strength, and hardness (Table 1, Table 2, Table 3S). These data were analyzed using response surface methodology (RSM) to develop regression models, and the predictive equations together with the model validation parameters are summarized in Table 4S. The effects of DRB and hydrocolloid levels on response variables are illustrated in Fig. 1. Based on the optimization results, formulations containing 1.8 % alginate, 1 % DRB, and 1 % hydrocolloid (gelatin, carrageenan, or agar) were selected for further analysis. These samples were evaluated for yield, color, texture, and encapsulation efficiency (Table 1), with their visual appearances shown in Fig. 1S.

Fig. 1.

Fig. 1

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Response surface plots (a, e, i) and corresponding contour plots (b to d for gelatin, f to h for carrageenan, j to l for agar) showing the combined effects of hydrocolloid and defatted rice bran (DRB) concentrations on encapsulation efficiency (b, f, j), tensile strength (c, g, k), and hardness (d, h, l) in alginate-based noodle formulations.

Yield of DRB noodles ranged from 76.83 % to 80.10 %, with the highest value observed in the gelatin formulation (Formulation F). This is attributed to gelatin's superior water binding capacity. Gelatin, containing polar amino acid residues, forms a flexible, water retaining network more effectively than carrageenan or agar. In contrast, carrageenan and agar form more rigid structures, resulting in lower moisture retention. This suggests that gelatin improves processing performance and moisture stability in DRB enriched noodles, consistent with the findings of Karim and Bhat (2008) and Sairam et al. (2011).

In terms of color, DRB addition resulted in darker noodles with increased redness and yellowness, due to the presence of natural pigments such as oryzanol and phenolic compounds. The addition of hydrocolloids into DRB alginate noodles did not significantly influence the color parameters (L∗, a∗, b∗), indicating that the observed differences were primarily attributed to DRB itself.

Texture varied notably across formulations, reflecting the influence of both the base alginate matrix and the added hydrocolloids. Alginate (1.8 %) provided structural support through calcium mediated crosslinking, contributing to noodle firmness and cohesion (Hong et al., 2021). However, alginate alone lacks flexibility and has limited ability to retain bioactive compounds. Among the tested hydrocolloids, gelatin exhibited the best overall enhancement of textural and biochemical properties, attributed to its flexible network formation and strong molecular interactions with DRB components. As a partially hydrolyzed protein from collagen, gelatin exhibits amphiphilic characteristics that enable extensive hydrogen bonding and electrostatic interactions with hydroxyl and carboxyl groups in DRB fibers and phenolics. These interactions promote the formation of a flexible and cohesive network, resulting in significantly greater tensile strength (57.31 ± 0.84 g) and encapsulation efficiency (59.51 ± 0.65 %).

Moreover, gelatin undergoes triple helix formation during gelation, aligning and densely packing peptide chains to form an ordered matrix that traps DRB phenolic compounds such as ferulic acid through hydrogen bonding, π–π stacking, and hydrophobic interactions. These interactions reduce molecular mobility and enhance stability during digestion, as supported by the higher crystallinity observed in the gelatin formulation (33.4 %, Fig. 2d). Similar protein–polyphenol binding has been reported for gelatin with epigallocatechin gallate (EGCG), where hydrogen bonding improved structural integrity and antioxidant activity (Wang et al., 2019). Gelatin's random coil regions also fill voids created by coarse DRB particles, improving matrix uniformity and cohesion, consistent with previous findings on its role in enhancing elasticity and structural stability in rice based formulations (Muhammad et al., 2024; Kraithong et al., 2023; Li and Nie, 2016; Thirathumthavorn et al., 2022; Zhang et al., 2020; Padalino et al., 2016).

Fig. 2.

Fig. 2

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Fourier transform infrared (FTIR) spectra (a to c) and X ray diffraction (XRD) patterns with relative crystallinity in parentheses, expressed as percent (d to f) of alginate-based noodle formulations. Formulations: A = 1.8 % alginate (control); B to D = 1.8 % alginate with 1 % gelatin, carrageenan, or agar, respectively; E = 1.8 % alginate with 1 % defatted rice bran (DRB); F to H = 1.8 % alginate with 1 % DRB and 1 % gelatin, carrageenan, or agar, respectively.

Carrageenan, a sulfated polysaccharide, forms rigid helices through ionic interactions. When combined with DRB, carrageenan demonstrated lower compatibility. The negatively charged carboxyl groups in DRB likely compete with the sulfate groups of carrageenan for calcium mediated ionic binding, which may interfere with helix formation and lead to a brittle, less cohesive matrix (Huang et al., 2007). Furthermore, the rigid structure of carrageenan may hinder uniform DRB distribution, introducing discontinuities that reduce tensile strength (50.20 ± 0.99 g) and increase hardness (7770.37 ± 48.44 g). These results align with those of Nisa (2021), who reported that carrageenan may increase brittleness and reduce mechanical stability in fiber rich formulations.

Agar, primarily composed of agarose, forms firm gels via hydrogen bonding between linear galactose chains. In the presence of DRB, agar produced a stable but moderately elastic matrix. However, its interaction appeared to rely more on physical entanglement than molecular bonding, which may explain its intermediate values for tensile strength and encapsulation efficiency (54.63 ± 0.32 %). Although agar supports matrix structure, its limited chemical affinity for DRB phenolics and fibers reduces its effectiveness in stabilizing bioactives. This observation is consistent with studies reporting that agar forms firm but less interactive gels when blended with polysaccharides (Saha and Bhattacharya, 2010).

Encapsulation efficiency results further highlighted the role of hydrocolloid selection. Formulation F (gelatin) exhibited the highest efficiency, demonstrating gelatin's superior capacity to retain phenolic compounds and protect them from degradation during processing (Reineccius and Meng, 2023; Rousta et al., 2021). Gelatin has also been shown to stabilize bioactive compounds against thermal and oxidative stresses (Li and Nie, 2016). In comparison, carrageenan and agar, while forming structurally stable gels, yielded lower efficiencies due to weaker interactions with DRB or more brittle matrix structures (Udo et al., 2023; Zabot et al., 2022).

Overall, the comparative findings confirm that gelatin is the most effective hydrocolloid for enhancing the texture, yield, and bioactive compound retention of DRB alginate noodles. Its molecular flexibility, cohesive gel forming ability, and specific interactions with DRB components make it the most suitable choice for functional noodle development. These results provide strong justification for continued investigation of gelatin-based formulations, particularly Formulation F, in further research.

3.3. Fourier transform infrared spectroscopy (FTIR) analysis

Fourier Transform Infrared (FTIR) spectroscopy was employed to characterize functional groups and investigate molecular interactions in noodle formulations composed of alginate, defatted rice bran (DRB), and different hydrocolloids (gelatin, carrageenan, and agar). The spectra (Fig. 2a–c) revealed distinct transmittance patterns, reflecting specific interactions among DRB, hydrocolloids, and the alginate matrix. All formulations exhibited characteristic peaks corresponding to functional groups commonly found in polysaccharides and proteins. A broad peak observed around 1628 to 1638 cm−1, associated with O–H stretching vibrations, was especially prominent in DRB alginate encapsulation noodles, suggesting extensive hydrogen bonding between DRB components—such as dietary fibers and phenolic compounds—and the hydrocolloid matrix. Peaks in the range of 1406–1410 cm−1, attributed to C–H bending, further confirmed the carbohydrate-rich nature of the samples (Copikova et al., 2001).

DRB alginate gelatin-containing formulations (Fig. 2a) exhibited distinctive peaks at 1574 to 1585 cm−1, assigned to N–H bending vibrations, which are characteristic of proteins. These peaks were more pronounced in formulation F, indicating strong interactions between gelatin and proteinaceous components of DRB. Such interactions are believed to enhance gel matrix formation, thereby improving encapsulation efficiency, phenolic compound retention, and mechanical properties. This observation is supported by the higher tensile strength and phenolic compound retention measured in the same formulation.

In contrast, DRB alginate formulations containing carrageenan (Fig. 2b) showed enhanced peaks at 1014 to 1029 cm−1, related to C–O stretching vibrations of polysaccharides. These peaks reflect the rigid and ordered structure of carrageenan gels, which is consistent with the high hardness and low encapsulation efficiency observed in these samples. The rigidity of the matrix may limit molecular interactions with DRB components and reduce the ability to entrap and protect bioactive compounds, resulting in reduced phenolic retention and antioxidant capacity.

Agar-based formulations (Fig. 2c) presented sharper peaks at 1059 to 1078 cm−1, corresponding to glycosidic bonds typical of agar structures. A noticeable shift in the O–H stretching region around 1638 cm−1 indicated moderate interactions between agar and DRB. These interactions may explain the balanced but intermediate encapsulation and textural properties observed in formulation H.

The presence of DRB also introduced peaks in the 1380 to 1394 cm−1 region, assigned to symmetric stretching of carboxylate groups (COO−), which are indicative of phenolic acids and other bioactive. The elevated intensity of these peaks in DRB alginate gelatin-containing formulations suggests potential interactions between gelatin and phenolic compounds, possibly involving hydrogen and ionic bonding, which may contribute to a more cohesive and stable gel network, enhancing bioactive protection during digestion (Copikova et al., 2001; Mecozzi et al., 2012).

In summary, FTIR analysis provided evidence of specific molecular interactions between DRB and each hydrocolloid. Gelatin exhibited the strongest affinity for DRB components, supporting its superior performance in terms of encapsulation efficiency, phenolic retention, antioxidant activity, and tensile strength. Carrageenan and agar contributed to distinct structural properties but showed weaker interactions with DRB at the molecular level. These findings reinforce the importance of hydrocolloid selection in enhancing the structural integrity and functional outcomes of DRB alginate encapsulation noodles.

3.4. X-ray Diffractometer (XRD) analysis

X-ray diffraction (XRD) analysis (Fig. 2d–f) was performed to evaluate the crystalline and amorphous characteristics of DRB alginate encapsulation noodles containing different hydrocolloids. The diffraction patterns reflect structural organization influenced by molecular interactions. The addition of gelatin (Fig. 2d) increased crystallinity to 33.4 %, as shown by sharper and more defined peaks. This indicates improved molecular alignment within the starch and protein matrix, contributing to enhanced texture, strength, and thermal stability. The tighter packing and more ordered structure likely also limited water and enzyme penetration, which could explain the improved retention of phenolics and reduced glucose release observed in gelatin-base formulations. Similar effects have been reported in rice bran fiber enriched noodles (Liu et al., 2021).

In contrast, carrageenan containing noodles (Fig. 2e) exhibited reduced peak intensity and broader patterns, lowering crystallinity to 31.6 %. This suggests partial disruption of the ordered matrix, resulting in a softer and more flexible structure. The lower crystallinity may also contribute to greater permeability and faster release of encapsulated compounds, including both phenolics and glucose, which aligns with the lower antioxidant activity and higher glucose release observed in these samples (Prasetyaningrum et al., 2021).

Agar incorporation (Fig. 2f) slightly reduced crystallinity to 30.8 % with minimal peak changes, indicating weak interactions with starch and protein. While agar forms firm gels, its influence on crystalline structure was limited, which may explain the intermediate functional outcomes, including moderate textural strength and bioactive stability. Previous studies also support these findings. Calcium ions were shown to modulate starch crystallinity in alginate systems (Wang et al., 2023), and gelatin–alginate interactions have been linked to altered crystalline behavior (Moradi Pour et al., 2022). In summary, gelatin enhances crystallinity and reinforces noodle structure, contributing to better mechanical properties and bioactive retention. Carrageenan disrupts crystallinity, softening the matrix but reducing encapsulation performance. Agar has minimal impact on crystallinity and functionally delivers moderate outcomes. These structural insights, supported by XRD and FTIR, explain the differential performance of each formulation and highlight the mechanistic role of hydrocolloids in determining the structure–function relationship in DRB-based encapsulated noodles.

3.5. In vitro digestibility and phenolic compound release

Fig. 3 illustrates the incremental release of key bioactive compounds from alginate-based noodle formulations during in vitro digestion. Among all formulations, formulation F demonstrated the highest phenolic release (Fig. 3a; p < 0.05), suggesting enhanced encapsulation efficiency and digestion-mediated liberation. This may be attributed to synergistic interactions between gelatin and DRB, which improve matrix flexibility and facilitate phenolic diffusion (Liu et al., 2021). Formulations G (carrageenan) and H (agar) also enhanced phenolic release relative to the control (A), although less than formulation F. Notably, all DRB-containing formulations (E–H) exhibited significantly greater phenolic release than formulation A and hydrocolloid-only groups (B–D), confirming DRB as a primary source of phenolic compounds.

Fig. 3.

Fig. 3

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In vitro simulated digestion and incremental area under the curve (iAUC) for the release of (a) total phenolic content, (b) total protein content, (c) total antioxidant activity, and (d) total glucose from alginate-based noodle formulations. Values are expressed as mean ± standard error of the mean (SEM), N = 3. Means with different superscript letters are significantly different (p < 0.05). Formulations: A = 1.8 % alginate (control); B to D = 1.8 % alginate with 1 % gelatin, carrageenan, or agar, respectively; E = 1.8 % alginate with 1 % defatted rice bran (DRB); F to H = 1.8 % alginate with 1 % DRB and 1 % gelatin, carrageenan, or agar, respectively.

Protein release, measured via the ninhydrin assay (Fig. 3b), also peaked in formulation F (p < 0.05), likely due to the high protein content and digestibility of gelatin. Carrageenan (G) led to the second-highest protein release, followed by agar (H), while alginate-only (A) showed the lowest values. The results suggest that hydrocolloids influence protein solubility and enzymatic accessibility during digestion, with gelatin offering the most favorable release conditions (Abdel-Aty et al., 2024).

Antioxidant capacity, determined by DPPH radical scavenging activity (Fig. 3c), mirrored phenolic release patterns. Formulation F again showed the highest antioxidant activity, consistent with its superior phenolic yield. Carrageenan and agar (G and H) also showed moderate antioxidant potential, whereas alginate-only (A) and gelatin-alone (B) groups demonstrated the lowest activity. This correlation highlights the contribution of DRB-derived phenolics to antioxidant functionality.

Glucose release (Fig. 3d) significantly increased in all DRB-containing formulations (E–H) compared to control A (p < 0.05), due to the digestible carbohydrate content of defatted rice bran. Interestingly, formulation F exhibited slightly lower glucose release than other DRB-hydrocolloid combinations (G and H), despite its higher phenolic and protein release. This observation suggests a synergistic interaction between the dietary fiber in DRB and gelatin, in which the viscous gel network formed by gelatin may limit α-amylase diffusion and substrate accessibility, thereby slowing starch hydrolysis and glucose liberation. The soluble fiber fraction in DRB likely increases chyme viscosity and reduces enzyme–substrate interactions, while gelatin reinforces this barrier effect by forming a cohesive and continuous matrix. In contrast, carrageenan and agar produce more rigid and porous gels that may permit greater enzyme penetration, resulting in higher glucose release. These results are consistent with previous reports demonstrating that gel-forming agents can modulate postprandial glycemic responses (Akhavan Farid et al., 2020).

LC-MS analysis confirmed that DRB contained high levels of phenolics, particularly ferulic and sinapic acids. Although processing reduced phenolic content, formulation F retained the highest levels post-processing (Table 2), suggesting that gelatin effectively protects phenolics from thermal and oxidative degradation (Kraithong et al., 2023; Peanparkdee et al., 2018).

Digesta analysis (Table 3) further demonstrated that formulation F (gelatin) released the highest levels of p-coumaric and sinapic acids, while maintaining ferulic acid content. This is likely due to gelatin's flexible gel matrix, which facilitates sustained bioactive release. Carrageenan enhanced p-coumaric acid release but reduced ferulic acid, possibly due to selective binding within its rigid structure. Agar showed moderate release across all phenolics, while formulation E (alginate only) yielded the highest protocatechuic acid, suggesting that the absence of secondary hydrocolloids may favor specific compound diffusion. These findings reinforce gelatin's superior role in enhancing phenolic bioaccessibility in DRB alginate encapsulation noodles.

4. Conclusion

This study successfully developed noodles enriched with defatted rice bran (DRB) using alginate calcium encapsulation, enhancing their nutritional and functional properties. The incorporation of hydrocolloids significantly improved noodle quality, with gelatin showing the most pronounced effects. Among the tested hydrocolloids, gelatin most effectively enhanced textural characteristics and promoted the retention and release of phenolic compounds, attributed to its flexible gel network and strong molecular interactions with DRB components. Carrageenan and agar contributed to softer and balanced textures, respectively. These findings underscore the potential of gelatin-based DRB encapsulation systems as a sustainable and innovative approach for upcycling rice milling byproducts into value-added functional foods. Nevertheless, the study is limited by its reliance on an in vitro digestion model, the absence of shelf-life evaluation, and the lack of scalability or cost analysis. Future research will address these limitations by conducting an ongoing clinical trial to evaluate the postprandial effects of DRB noodles in humans and by investigating industrial-scale production and advanced encapsulation strategies for broader commercial applications.

Credit author statement

Siriyakorn Chantieng: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review and editing. Vernabelle Balmori; Data curation, Software. Kasinee Katelakha; Data curation. Charoonsri Chusak; Investigation. Tanyawan Suantawee; Conceptualization. Sathaporn Ngamukote; Conceptualization. Sirichai Adisakwattana; Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Visualization, Writing – review and editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research was supported by Fundamental Fund of Chulalongkorn University (FOOD_FF_68_072_3700_004) and the National Research Council of Thailand (NRCT): N42A680622.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.crfs.2025.101178.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

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Multimedia component 2
mmc2.docx (1MB, docx)

Data availability

Data will be made available on request.

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