Impact of iron salt addition on the viscoelastic properties of rice flours

Impact of iron salt addition on the viscoelastic properties of rice flours | 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 Research Article Impact of iron salt addition on the viscoelastic properties of rice flours Aldrin Bonto, Joanne Jerenice Añonuevo, Nese Sreenivasulu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8688528/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Iron addition to rice is widely promoted to address iron-deficiency anemia, yet its effects on the rheological behavior of rice flour remain poorly understood. This study investigated the impact of iron salt (sodium iron EDTA) on the viscoelastic properties of rice flours with varying amylose content, specifically waxy IR65, low-amylose IR24, and high-amylose IR36. Dynamic oscillatory rheology, including temperature ramp, frequency sweep, and stress sweep tests, was employed to evaluate gel formation, elasticity, and deformation behavior. During gelatinization, high-amylose IR36 exhibited significantly stronger gel formation, with a maximum storage modulus (G′max) of 11,420 ± 270 Pa, compared with IR24 (9,376 ± 122 Pa) and IR65 (338 ± 29 Pa). Frequency sweep measurements showed that elasticity increased with amylose content, with G′ at 10 rad s⁻¹ reaching 16.90 ± 0.96 Pa for IR36. The addition of iron (2.5–10%, w/w) further modulated viscoelasticity in an amylose-dependent manner, enhancing gel elasticity and consistency in high-amylose rice while reducing elastic strength in waxy and low-amylose systems. Stress sweep tests revealed that iron addition did not alter the intrinsic deformation behavior of the starch gels, with IR36 and IR24 exhibiting Type III weak-strain overshoot and IR65 exhibiting Type I strain-thinning behavior. Overall, the results demonstrate that iron–starch interactions selectively reinforce amylose-rich networks while weakening amylopectin-dominant gels, providing critical insights for optimizing the formulation and processing of iron-fortified rice-based food products. Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Rice is consumed daily as a staple food, providing approximately 50% of the global dietary caloric supply to roughly 3.5 billion people [ 1 ]. Compared to other cereals, such as wheat and barley, rice is the most commonly consumed whole grain after cooking [ 2 ]. However, to keep up with the fast-paced modern lifestyle and cope with increasing consumer demand, rice is processed to produce convenient products such as rice extrudates, baked goods, crackers, and noodles [ 3 – 7 ]. Several gluten-free products contain a large amount of rice starch due to its advantageous traits, such as a hypoallergenic nature and bland flavor [ 8 ]. Starch is the most abundant component in milled rice, accounting for approximately 90 % of its dry ass—this branched glucose polymer comprises two types: amylose and amylopectin. Amylose has a smaller molecular weight (~ 10 5–6 ) with few branches, while amylopectin molecules are relatively large, highly branched molecules (~ 10 7–8 ) with a large number of short chains [ 9 ]. Amylose content is pivotal in designing new and novel food products with desired sensory and textural attributes. For example, rice varieties with intermediate-to-high amylose content (> 20%) are used in traditional rice noodle-making because they form a stronger gel network, a desired characteristic for this application [ 10 – 12 ]. The molecular structure and distribution of amylose and amylopectin fractions play a crucial role in determining the physicochemical and functional properties of rice [ 13 , 14 ] Fortification of rice and rice-based products with iron is an excellent way to combat the increasing global case of anemia [ 15 ]. In line with this goal, several studies have successfully incorporated metal into rice flour, producing extrudates[ 16 ] and noodles [ 17 ]. Exogeneous metal salts and starch can form different interactions: (1) forming Werner complexes in which central metal atoms coordinate or ligate to hydroxyl groups of amylose and amylopectin, (2) starch surface sorption complexes, (3) inclusion complexes involving the ability of the polysaccharides to form helical structures, and (4) capillary complexes holding metal compounds within capillaries between starch granules [ 18 ]. However, even though the development of iron-fortified rice products and understanding metal-starch complexes are sought, there is a limited understanding of how the addition of iron affects the rice’s viscoelastic behaviours. It is essential to note that molecular interactions between iron and starch (specifically amylose and amylopectin) can affect processing parameters and the textural properties of the final product. The effect of iron on the viscoelasticity of rice flour has not yet been examined. Therefore, the main objective of this study was to investigate the impact of iron fortificant on the viscoelastic properties of rice with varying amylose content. The first part described the characteristics of the selected rice varieties in terms of starch granule morphology, starch molecular weight distribution, thermal properties, and inherent rheological properties, while the latter part detailed the effects of different amounts of sodium iron EDTA on the rheological properties of rice flour having different amylose content determined by frequency sweep and stress sweep experiments. Materials and Methods Sample preparation The rice samples used in this study were IR65 (waxy), IR24 (low amylose), and IR36 (high amylose) rice. The rice was grown during the 2017 dry season in the irrigated field plots of the International Rice Research Institute (IRRI) in Los Baños, Laguna, Philippines, under optimal field management conditions. Seeds were harvested and dried to a moisture content of 12–14%. Paddy rice samples were dehulled (Rice sheller THU-35A, Satake Corporation) and were polished (Kett Mill). For an analysis that requires ground samples, milled grains were ground separately in a mixer mill (MM 400, Retsch GmbH, Germany) and stored at a dry, ambient temperature. The iron fortificant used in this study is Sodium iron EDTA (Ethylenediaminetetraacetic acid ferric sodium salt, C 10 H 12 FeN 2 NaO 8 , Sigma Aldrich). Rice Morphology through Scanning Electron Microscopy The surface morphology of native starch granules was examined by scanning electron microscopy (JEOL JSM-5310) operated at an accelerating voltage of 20 kV. Before imaging, samples were gold-coated, and micrographs were collected from the internal surface of the rice kernel. Starch Structure through Size Exclusion Chromatography Rice flour (50 mg) was dispersed in 400 µL of 95% ethanol and 1.0 mL of 0.25 M NaOH, then heated on a hot plate at 150°C for 120 min. During gelatinization, hot water was added in 800 µL increments (total of 0.8 mL), and additional hot water was subsequently added to bring the final sample mass to 4.0 g. An aliquot (794 µL) of the gelatinized dispersion was combined with 206 µL of sodium acetate buffer and debranched by incubation with 8.0 µL of isoamylase (Megazyme, P113541) at 50°C in a water bath. Enzymatic activity was terminated by boiling the mixture for 5 min, after which the samples were centrifuged. The resulting supernatant was transferred to a tube containing approximately 320 mg of ion-exchange resin and incubated at 50°C for 30 min. After a final centrifugation step, the clarified supernatant was collected and analyzed by size-exclusion chromatography. Thermal Properties Flour samples (4.0 mg) were mixed with 8.0 µL of water and sealed in hermetic aluminum pans prior to analysis using a differential scanning calorimeter (TA Instruments, DSC 250). Samples were heated from 25 to 110°C at 10°C/min, with an empty pan used as the reference for all measurements. Thermal transition parameters, including onset temperature (To), peak gelatinization temperature (Tp), enthalpy of gelatinization (ΔH), and amylose–lipid complex melting behavior, were determined using TRIOS software. Reported values represent the mean of triplicate analyses, expressed with standard deviations. Rheological Properties Before iron addition, the intrinsic rheological behavior of rice flour during thermal processing was evaluated using a dynamic oscillatory temperature ramp. Measurements were performed on a controlled-stress rheometer (AR 2000, TA Instruments, New Castle, DE) to characterize the viscoelastic response associated with starch gelatinization and retrogradation. A parallel-plate geometry (40 mm diameter) with a fixed gap of 1 mm was employed. A 25% (w/w) rice flour suspension (1.2 mL) was loaded onto a Peltier-controlled plate and covered with a solvent trap sealed with water to minimize moisture loss during analysis. Samples were equilibrated at 35°C for 1 min under 1% strain and 1 Hz, followed by a heating ramp from 35 to 95°C at 4°C min⁻¹, then a cooling ramp from 95 to 35°C at the same rate. The resulting gel was equilibrated for an additional 1 min at 35°C before conducting a frequency sweep from 0.1 to 100 rad s⁻¹ at an oscillatory stress of 0.1 Pa. For rice flour–iron fortificant systems, suspensions (0.5 g mL⁻¹, dry basis) were prepared by incorporating sodium iron EDTA at concentrations of 2.5%, 5.0%, and 10% (w/w, based on rice flour). Gel preparation followed the method of Li et al. [ 19 ] with minor modifications. Briefly, the iron–flour dispersions were heated in boiling water for 35 min under continuous stirring to obtain fully gelatinized starch gels, then cooled to room temperature (25°C). An aliquot (1.3 mL) of the gel was placed on the rheometer plate, and excess material was trimmed. Oscillatory stress sweeps were performed from 0.01 to 100 Pa at a constant angular frequency of 6.283 rad s⁻¹ and 25°C, while frequency sweeps were conducted from 0.1 to 10 rad s⁻¹ at a constant stress of 0.1 Pa and the same temperature. Viscoelastic parameters, including storage modulus (G′), loss modulus (G″), and loss tangent (tan δ = G″/G′), were recorded. All rheological measurements were conducted in duplicate. Statistical analysis Statistical analyses were conducted using one-way analysis of variance (ANOVA), followed by Tukey’s post hoc test at a significance level of α = 0.05. All analyses were performed using the online freeware ASTATSA ( https://astatsa.com/OneWay_Anova_with_TukeyHSD/ ). Results and Discussion Rice Microstructure The microstructural features of the internal regions of the rice kernels were analyzed by scanning electron microscopy, as presented in Fig. 1 . Native rice starch granules are generally characterized by polyhedral shapes with typical sizes ranging from approximately 3 to 8 µm [ 20 ]. As illustrated in Fig. 1 A–C, all rice varieties exhibited densely packed starch granules with irregular polyhedral morphology and particle sizes predominantly below 10 µm. Debranched Starch Structure of Rice Flour Table 1 Starch Molecular Distribution Using Size-exclusion chromatography (SEC) Rice Samples % Amylose Starch Molecular Distribution LCAM (DP > 1000) ICAP (DP 121–1000) MCAP (DP 37–120) SCAP (DP 6–36) IR65 0.084 ± 0.019 a 0.084 ± 0.019 a 4.70 ± 0.024 a 32.28 ± 0.037 a 62.52 ± 0.032 a IR24 12.10 ± 0.00 b** 10.16 ± 0.04 b** 5.89 ± 0.05 b* 26.46 ± 0.02 b* 56.71 ± 0.06 a IR36 26.20 ± 3.65 c* 20.44 ± 2.92 c* 10.39 ± 1.03 b* 22.63 ± 0.51 b* 45.82 ± 4.26 b** Within each column, values with different letters are significantly different (p < 0.05). SEC was employed to determine the molecular weight distribution of debranched starch isolated from native rice flour samples, as summarized in Table 1 . The obtained chain-length distributions were classified into four fractions: long-chain amylose (LCAM; degree of polymerization, DP > 1000), intermediate-chain amylopectin (ICAM; DP 1000–121), medium-chain amylopectin (MCAP; DP 120–37), and short-chain amylopectin (SCAP; DP 36–6). In addition to resolving starch chain architecture, SEC provides a more reliable estimate of amylose content than conventional colorimetric methods [ 21 ]. Amylose content (AC) is a key parameter for classifying rice and assessing its functional performance. Rice is categorized as waxy (< 2% amylose on a dry-basis), very low (5–12%), low (12–20%), intermediate (20–25%), or high amylose (25–33%) [ 22 ]. Based on SEC-derived amylose values, IR65 (0.084 ± 0.019%) was classified as waxy rice, IR24 (12.10 ± 0.00%) as low-amylose rice, and IR36 (26.20 ± 3.65%) as high-amylose rice. The SEC chromatograms further reflected these compositional differences (See Supplementary Fig. 1). Debranched non-waxy rice starches (IR24 and IR36) exhibited the characteristic SEC profile consisting of two dominant amylopectin peaks corresponding to different branch-chain populations, accompanied by a smaller amylose peak. In contrast, the waxy rice variety IR65 showed only amylopectin-derived peaks, confirming the near absence of amylose chains. Variations in the relative abundance of ICAM, MCAP, and SCAP fractions among the samples suggest differences in amylopectin fine structure, which can influence gelatinization behavior, retrogradation tendency, and enzymatic digestibility [ 23 ]. From a product development perspective, amylose level and starch chain-length distribution play decisive roles in determining rice functionality. Waxy and low-amylose rice varieties are generally preferred for applications requiring soft, cohesive, and stable starch gels, particularly in wet or refrigerated products [ 24 ]. In contrast, high-amylose rice varieties are favored in products that require firmer texture, reduced stickiness, and resistance to structural breakdown during cooking [ 25 ]. Notably, rice containing 25–33% amylose is considered optimal for rice noodle production due to its superior gel strength and cooking stability [ 26 ]. Furthermore, previous textural studies have demonstrated that the amylose-to-amylopectin ratio strongly governs cooked rice attributes such as hardness and stickiness [ 25 ]. Thermal Properties Table 2 Thermal Properties of Rice Varieties Rice Samples Gelatinization Amylose-Lipid Complex T onset1 T peak1 ΔH G T onset2 T peak2 ΔH ALC IR65 54.75 ± 0.11 a 68.27 ± 0.22 a 9.13 ± 0.98 a N/A N/A N/A IR24 55.91 ± 1.28 a 71.51 ± 1.30 b* 6.80 ± 0.74 b* 94.00 ± 2.89 a 103.32 ± 0.75 a 0.97 ± 0.36 a IR36 69.78 ± 0.035 b* 76.19 ± 0.040 b* 6.71 ± 0.17 b* 91.36 ± 0.10 a 99.47 ± 0.17 b* 1.27 ± 0.26 a Within each column, values with different letters are significantly different (p < 0.05). Table 2 summarizes the thermal properties of the three rice varieties as determined by differential scanning calorimetry. In general, rice starch thermograms exhibit two distinct endothermic transitions. The first transition corresponds to starch gelatinization, which involves the irreversible swelling and melting of the double helices and the disruption of crystalline regions within starch granules. The second transition, occurring at higher temperatures, is attributed to the melting of amylose–lipid complexes. The peak gelatinization temperature (T peak1 ) represents the energy required to initiate starch gelatinization, as hydration of the amorphous regions is restricted by the surrounding crystalline domains. Meanwhile, the enthalpy of gelatinization (ΔH G ) indicates the extent of crystalline-to-amorphous transformation and serves as an index of molecular order within the starch structure. Among the samples, the waxy rice IR65 exhibited the lowest T peak1 (68.27 ± 0.22°C) but the highest ΔH G (9.13 ± 0.98 J g⁻¹) relative to the non-waxy varieties IR24 and IR36. This behavior suggests a starch matrix with a higher proportion of crystalline regions and fewer amorphous domains, consistent with previous reports [ 28 ]. Overall, the enthalpy values associated with the first endothermic transition across all rice samples ranged from 6.71 to 9.13 J g⁻¹. For the non-waxy rice varieties, a second endothermic transition associated with amylose–lipid complex dissociation was observed. The amylose–lipid complex peak temperatures (T peak2 ) were 103.32°C for IR24 and 99.47°C for IR36. Notably, IR36 exhibited a higher ΔHALC (1.27 J g⁻¹) than IR24, which can be attributed to its greater proportion of long-chain amylose (DP > 1000; 20.44 ± 2.92%), favoring enhanced amylose–lipid inclusion complex formation. In contrast, no second endothermic transition was detected for IR65, consistent with its negligible amylose content and in agreement with previously reported findings [ 27 ]. These results highlight the importance of the inherent thermal behavior in rice starch, as variations in gelatinization and amylose–lipid complex formation directly influence processing conditions, cooking performance, and the quality attributes of rice-based food products [ 28 ]. Dynamic Shear Curves of rice flour at a controlled temperature ramp Figure 2 presents the viscoelastic behavior of the rice varieties subjected to a controlled temperature ramp, as characterized by advanced rheometry. The storage modulus (G′) reflects the elastic or solid-like component of the starch system, whereas the loss modulus (G″) and loss tangent (tan δ) describe its viscous or liquid-like behavior. Together, these parameters provide insight into the structural evolution of rice flour suspensions during thermal processing (Table 3 ). Table 3 Dynamic rheological properties of rice flour Rheological Properties IR65 IR24 IR36 Heating G’ max 338.00 ± 28.99 a 9376.00 ± 121.62 b* 11420.00 ± 270.00 c* G’’ max 105.21 ± 16.40 a 1503.50 ± 68.59 b* 1670.00 ± 74.00 b* tan δ max 0.31 ± 0.022 a 0.16 ± 0.0094 b* 0.15 ± 0.0030 b* G’ 95℃ 253.45 ± 25.10 a 3219.00 ± 305.47 b* 5441.00 ± 174.00 c* G’’ 95℃ 73.80 ± 0.29 a 332.25 ± 32.60 b* 386.30 ± 11.50 b* tan δ 95℃ 0.29 ± 0.034 a 0.10 ± 0.00033 b* 0.071 ± 0.00016 b* Cooling G’ 35℃ 329.75 ± 17.32 a 5201.50 ± 389.62 b* 9627.50 ± 238.50 c* G’’ 35℃ 93.96 ± 3.90 a 432.15 ± 13.93 b* 612.20 ± 25.60 c* tan δ 35℃ 0.29 ± 0.0031 a 0.083 ± 0.004 b* 0.64 0.0011 c** Within each row, values with different letters are significantly different (p < 0.05). During the heating phase (35–95°C), the starch suspensions underwent a transition from a sol state to a gel state. This sol–gel transformation was marked by the attainment of maximum storage modulus (G′ max ) and maximum loss tangent (tan δ max ). Among the samples, IR36 exhibited the strongest elastic response, characterized by a higher G′ max and a lower tan δ, indicative of a more rigid, well-developed gel network. This behavior is attributed to its higher amylose content and greater proportion of long-chain amylose (LCAM). In contrast, the waxy rice IR65 formed a comparatively weak gel, as evidenced by its lower G′ max (338.00 ± 28.99 Pa) and higher tan δ max (0.31 ± 0.022), showing a predominance of viscous behavior. The enhanced gel strength observed in non-waxy rice during gelatinization is associated with the leaching of amylose, which participates in the formation of a three-dimensional network through intermolecular hydrogen bonding among amylose, amylopectin, and water [ 29 , 30 ]. Conversely, in waxy rice, gel formation is mainly governed by interactions among leached amylopectin chains, leading to a weaker network. Prolonged heating beyond G′ max led to partial breakdown of the starch gel network, likely due to the melting of residual crystalline regions within swollen starch granules. This structural deterioration was reflected in the reduced G′ values observed at 95°C across all rice samples. During the cooling phase (95–35°C), a progressive increase in network strength was observed, coinciding with retrogradation of starch. Retrogradation refers to the reassociation and reordering of amylose and amylopectin chains following gelatinization, leading to the formation of more ordered structures [ 33 ]. Rice varieties with higher amylose content developed stronger gel networks upon cooling, as demonstrated by IR36, which showed higher G′ 35°C and lower tan δ 35°C than IR24 and IR65. These rheological trends are consistent with previous observations that higher amylose content is associated with increased storage modulus in rice gels [ 31 ]. Effects of Iron on Rice Viscoelasticity Dynamic (oscillatory) shear measurements offer valuable insight into the internal structure of starch gels [ 32 , 33 ]. In this study, frequency- and stress-sweep tests were conducted to evaluate changes in viscoelastic behavior with increasing levels of iron fortification in rice flour suspensions. Assessing the material response as a function of angular frequency and applied shear stress enabled clear differentiation between the storage (G′) and loss (G″) moduli. Frequency Sweep The frequency sweep results further emphasize the pivotal role of amylose content in governing the viscoelastic behavior of rice flour gels. As shown in Fig. 3 . A-C, The G’ value at 10 rad/s of IR65, IR24, and IR36 were 9.45 ± 0.76, 13.82 ± 0.69, and 16.90 ± 0.96 Pa, respectively, indicating that higher amylose content tends to have higher elasticity. IR36 consistently exhibited a higher storage modulus (G′) than waxy IR65, showing the ability of amylose to leach out during gelatinization and form compact, continuous gel networks. Additionally, Amylose exhibits lower steric hindrance and a more linear molecular structure, which enhances chain mobility and promotes rapid formation of a highly elastic three-dimensional gel network [ 34 ]. In contrast, the amylopectin-dominant structure of waxy rice limits network connectivity, resulting in weaker elastic responses. This trend is consistent with the work of Tian et al [ 35 ], who report that increasing amylose content is associated with elevated G′, G″, and complex viscosity (η*), with consistency coefficients (K*) increasing by as much as 17–24-fold when transitioning from waxy to high-amylose rice. Accordingly, IR36 (~ 26% amylose) typically exhibits solid-like behavior (G′ > G″), whereas IR65 displays predominantly weak gel characteristics. Table 4 Parameterized Data of Frequency Sweep Test of IR65, IR24, and IR36 rice flour gels with varying iron concentration levels. % Iron IR36 IR24 IR65 \(\:{K}^{*}\) \(\:{n}^{*}\) \(\:{K}^{*}\) \(\:{n}^{*}\) \(\:{K}^{*}\) \(\:{n}^{*}\) raw 0.41 ± 0.028 a 0.021 ± 0.00067 a 0.46 ± 0.041 a 0.030 ± 0.00086 a 0.45 ± 0.043 a 0.15 ± 0.0016 a 2.5% 0.52 ± 0.004 a 0.020 ± 0.00014 a 0.46 ± 0.017 a 0.033 ± 0.0021 a 0.30 ± 0.016 b** 0.055 ± 0.0010 b* 5.0% 0.57 ± 0.018 a 0.020 ± 0.00025 a 0.44 ± 0.051 a 0.035 ± 0.0022 a 0.34 ± 0.00064 b** 0.15 ± 0.0018 a 10.0% 0.61 ± 0.073 b** 0.020 ± 0.00004 a 0.39 ± 0.032 a 0.042 ± 0.00095 b * 0.33 ± 0.0047 b** 0.16 ± 0.00071 b** Within each column, values with different letters are significantly different (p < 0.05). Addition of iron further modulated these viscoelastic properties in an amylose-dependent manner. Iron forms a Werner-type complex with starch, as determined by electron paramagnetic resonance spectroscopy and thermal studies [ 36 , 37 ]. Iron ligates the lone pairs of the hydroxyl groups in starch, altering its physical properties, such as viscoelasticity [ 38 ]. In IR36, iron addition enhanced gel elasticity, as evidenced by increased G′ and K* values as listed in Table 4 , suggesting the formation of additional intermolecular junctions through amylose–iron cross-linking. Similar behavior has been reported in spelt starch [ 39 ], which contains 20–21% amylose, where iron(II) fortification increased the consistency index from approximately 1.06 to 2.60, closely mirroring the trends observed in IR36. Moreover, the complex modulus of the pea starch (~ 40% amylose content) composite gels was 4.65-fold greater than that of pea starch hydrogels without Fe³⁺ [ 40 ]. These findings support the hypothesis that iron ions can act as coordination bridges between amylose chains, reinforcing the starch gel network. Conversely, iron addition weakened the viscoelastic structure of IR65 and IR24, as shown by reduced G′ and K* values. The predominance of amylopectin in these systems likely restricts effective network formation, and metal–amylopectin interactions may further disrupt molecular conformation. Indeed, a study on Zn²⁺–amylopectin complexes has demonstrated conformational weakening of amylopectin chains [ 41 ], which may explain the reduced elasticity observed upon iron addition in amylopectin-rich waxy and low-amylose rice. The mechanical spectra of all rice flour–iron systems were well described by the power-law model, yielding flow behavior indices (n*) in the range of 0.02–0.15, indicative of pronounced shear-thinning behavior typical of starch-based gels. Given the dominance of G′ over G″ across samples, the consistency coefficient (K*) served as a reliable descriptor of elastic strength and effectively captured variations arising from differences in amylose content and iron fortification. Overall, these results highlight that the interplay between starch molecular architecture and iron coordination chemistry is a critical determinant of rice flour gel structure and functionality, with direct implications for the design of iron-fortified rice-based food products. Stress Sweep The oscillatory stress sweep responses of raw rice flour and rice–iron gels are presented in Fig. 4 , illustrating the dependence of the viscoelastic moduli (G′ and G″) on applied shear stress. For all samples, a well-defined linear viscoelastic region (LVR) was observed at low stress amplitudes (0.01–1 Pa), where the moduli remained independent of stress, indicating structural integrity of the gel network. Among the rice varieties, IR65 exhibited the narrowest LVR, extending only up to approximately 0.05 Pa, suggesting a comparatively weaker gel structure. Beyond the LVR (> 1 Pa), the storage modulus (G′) decreased progressively with increasing stress, while the loss modulus (G″) initially increased to a maximum before declining. Correspondingly, tan δ remained nearly constant within the LVR and increased sharply once the critical stress was exceeded, reflecting the onset of network breakdown and enhanced viscous dissipation. Similar stress sweep behavior has been reported for rice starch gels with amylose contents ranging from 18.5 to 24.5% [ 42 , 43 ]. The stress sweep profiles of raw and iron-fortified gels from IR24 and IR36 are characteristic of Type III behavior (weak strain overshoot), as evidenced by an initial increase in G″ followed by a decrease after reaching a maximum, concurrent with a continuous decline in G′. This response suggests that the starch network—particularly amylose with its extended molecular conformation—forms a weakly structured, interconnected system stabilized by intermolecular associations such as hydrogen bonding. Under increasing deformation, the network resists strain up to a critical point, beyond which structural disruption occurs, leading to polymer chain alignment along the flow field and a subsequent reduction in G″ [ 44 , 45 ]. In contrast, IR65 exhibited Type I strain-thinning behavior, where both G′ and G″ decreased monotonically with increasing stress. At low stress levels, polymer chains are predominantly entangled, resulting in constant moduli; as stress increases, progressive disentanglement and alignment of amylopectin-rich chains reduce viscoelastic resistance. Across all rice varieties, iron fortification did not alter the inherent oscillatory stress response, indicating that the fundamental deformation mechanisms of the starch networks remained unchanged. However, consistent with the frequency-sweep results, iron addition increased the elastic modulus of high-amylose rice (IR36) while decreasing the elasticity of waxy rice (IR65). These findings further support the amylose-dependent role of iron in modulating the strength and structural resilience of starch gels. Conclusion This study demonstrates that the addition of iron significantly influences the viscoelastic behavior of rice flour, acting in an amylose-dependent manner. Dynamic rheological analyses revealed that rice flour with higher amylose content forms stronger and more elastic gel networks during gelatinization and retrogradation, as evidenced by significantly higher storage moduli and lower loss tangents. Among the rice varieties examined, high-amylose IR36 consistently exhibited superior gel strength and elasticity compared with low-amylose IR24 and waxy IR65. The incorporation of sodium iron EDTA, an iron fortificant, further modulated these rheological properties. The addition of iron (2.5–10.0% w/w) enhanced the elastic response and consistency of high-amylose rice flour gels, likely through interactions between iron ions and amylose chains that reinforce the three-dimensional network. In contrast, iron addition weakened the viscoelastic structure of waxy and low-amylose rice flours, suggesting that iron–amylopectin interactions disrupt network formation in amylopectin-dominant systems. Importantly, stress sweep measurements indicated that iron fortification did not alter the intrinsic deformation behavior of the starch gels. Overall, the findings highlight the role of starch architecture in influencing the rheological response of iron-fortified rice flour. These insights provide a mechanistic basis for selecting appropriate rice varieties and optimizing processing conditions to develop iron-fortified rice-based foods with desirable texture and structural stability. Declarations Competing interests The authors declare no competing interests. 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Polym. 212 , 112 (2019) A.A. Wani, P. Singh, M.A. Shah, U. Schweiggert-Weisz, K. Gul, I.A. Wani, Compr. Rev. Food Sci. Food Saf. 11 , 417 (2012) V.M. Butardo, R. Anacleto, S. Parween, I. Samson, K. de Guzman, C.M. Alhambra, G. Misra, N. Sreenivasulu, Plant. Physiol. 173 , 887 (2017) J. Bao, Rice (Elsevier, 2019), pp. 55–108 R. Shoukat, M. Cappai, L. Pilia, G. Pia, Polym. (Basel). 17 , 110 (2025) Y. Chen, Y. Yao, Z. Gu, Y. Peng, L. Cheng, Z. Li, C. Li, Z. Chen, Y. Hong, J. Cereal Sci. 108 , 103571 (2022) H. Li, M.A. Fitzgerald, S. Prakash, T.M. Nicholson, R.G. Gilbert, Sci. Rep. 7 , 43713 (2017) Z.-H. Lu, L.S. Collado, Rice (Elsevier, 2019), pp. 557–588 C.M. Alhambra, M.K. de Guzman, S. Dhital, A.P. Bonto, E.I. Dizon, K.A.C. Israel, W.A. Hurtada, V.M. Butardo, N. Sreenivasulu, J. Cereal Sci. 86 , 108 (2019) B.O. Juliano, Overview of Rice and Rice-Based Products Starch Properties (2005) S. Hsu, S. Lu, C. Huang, J. Food Sci. 65 , 215 (2000) F. Zhu, Y.-J. Wang, Food Res. Int. 49 , 757 (2012) C.G. Biliaderis, B.O. Juliano, Food Chem. 48 , 243 (1993) I. Rosalina, M. Bhattacharya, Carbohydr. Polym. 48 , 191 (2002) S. Singh, M. Kaur, Int. J. Food Prop. 20 , 3282 (2017) M. Mariotti, G. Caccialanza, C. Cappa, M. Lucisano, Food Hydrocoll. 84 , 257 (2018) J. Tian, L. Qin, X. Zeng, P. Ge, J. Fan, Y. Zhu, Foods. 12 , 1210 (2023) W. Ciesielski, C. Lii, M.-T. Yen, P. Tomasik, Carbohydr. Polym. 51 , 47 (2003) W. Ciesielski, P. Tomasik, Int. J. Food Sci. Technol. 39 , 691 (2004) W. Ciesielski, M. Krystyjan, E-Polymers 9 , (2009) J. Rożnowski, T. Fortuna, K. Nowak, E. Szuba, Brazilian Archives Biology Technol. 59 , (2016) T. Wang, Y. Qin, C. Cui, N. Ji, L. Dai, Y. Wang, L. Xiong, R. Shi, Q. Sun, Int. J. Biol. Macromol. 224 , 1228 (2023) P. Liu, Y. Li, X. Shang, F. Xie, Carbohydr. Polym. 206 , 528 (2019) H. Li, N. Lei, S. Yan, J. Yang, T. Yu, Y. Wen, J. Wang, B. Sun, Carbohydr. Polym. 212 , 112 (2019) O.S. Lawal, R. Lapasin, B. Bellich, T.O. Olayiwola, A. Cesàro, M. Yoshimura, K. Nishinari, Food Hydrocoll. 25 , 1785 (2011) H.G. Sim, K.H. Ahn, S.J. Lee, J. Nonnewton Fluid Mech. 112 , 237 (2003) K. Hyun, S.H. Kim, K.H. Ahn, S.J. Lee, J. Nonnewton Fluid Mech. 107 , 51 (2002) Additional Declarations No competing interests reported. Supplementary Files PUBsupplementary.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 30 Jan, 2026 Reviews received at journal 29 Jan, 2026 Reviews received at journal 28 Jan, 2026 Reviewers agreed at journal 27 Jan, 2026 Reviewers agreed at journal 27 Jan, 2026 Reviewers invited by journal 27 Jan, 2026 Editor assigned by journal 27 Jan, 2026 Submission checks completed at journal 27 Jan, 2026 First submitted to journal 24 Jan, 2026 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-8688528","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582347818,"identity":"c4314153-1cf8-4933-9f8f-72367bd81b8a","order_by":0,"name":"Aldrin Bonto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYDACdgYDhgQGEAKCD2wWYFqCASaCDTDDtTAzMM5gkyBSCwNUCzMPMVr4m5m3fXi4gyGPX7r/4GObMgl7gwPMB2/zMNzJw6VF4jBb8YzEMwzFknMOMxvnnJNI3HCALdmah+FZMU6HHeYxZkhsY0jccCOZTTq3TSLB4ACPmTQPw+HEBhw65FG0WLaBHMb/Da8WAxQtjG0SjBsO8LDh1WII9AtQi0Sx5IxkY8MeoF9mHmYztpxj8AynFrnjzZsZf7bZ5PFLJD588KPMxp7vePPDG28q7uDUAgUSSGxmsIMP4NeADZChZRSMglEwCoYrAACxN1Fs+jJJ5wAAAABJRU5ErkJggg==","orcid":"","institution":"De La Salle University","correspondingAuthor":true,"prefix":"","firstName":"Aldrin","middleName":"","lastName":"Bonto","suffix":""},{"id":582347819,"identity":"305ad697-1301-4ae6-9a31-9856ed55b679","order_by":1,"name":"Joanne Jerenice Añonuevo","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Joanne","middleName":"Jerenice","lastName":"Añonuevo","suffix":""},{"id":582347820,"identity":"df029f39-bd7e-47e2-9f74-80c9e245ab09","order_by":2,"name":"Nese Sreenivasulu","email":"","orcid":"","institution":"International Rice Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Nese","middleName":"","lastName":"Sreenivasulu","suffix":""}],"badges":[],"createdAt":"2026-01-24 18:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8688528/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8688528/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101528730,"identity":"46405ba4-81fb-42cb-ac76-56cb71c545cf","added_by":"auto","created_at":"2026-01-30 19:10:08","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":230363,"visible":true,"origin":"","legend":"\u003cp\u003eScanning electron micrographs of interior endosperm starch granules from IR65 (A), IR24 (B), and IR36 (C).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8688528/v1/4425424069bd18e548a07334.jpeg"},{"id":101528726,"identity":"105ad5cb-9d7b-4a17-8358-8b150d426ed4","added_by":"auto","created_at":"2026-01-30 19:10:06","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":106246,"visible":true,"origin":"","legend":"\u003cp\u003eRheological behavior of rice samples during controlled temperature ramp\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8688528/v1/a515e438de2d4a279f26103c.jpeg"},{"id":101528727,"identity":"04401ef6-bb95-4eac-9f1b-f44ea666846a","added_by":"auto","created_at":"2026-01-30 19:10:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":285298,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency sweep profiles of storage modulus (G′), loss modulus (G″), and loss tangent (tan δ) for (A) IR65, (B) IR24, and (C) IR36 rice flour gels with varying iron fortificant levels.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8688528/v1/552b7397cc0ff9cfa0c8f690.png"},{"id":101528728,"identity":"2e7f62ee-c554-4bee-b3ec-1c0f8d26a2db","added_by":"auto","created_at":"2026-01-30 19:10:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":291806,"visible":true,"origin":"","legend":"\u003cp\u003eOscillatory stress sweep behavior of rice flour–iron gels illustrating storage and loss moduli (G′, G″; A–C) and loss tangent (tan δ; D–F) for IR65, IR24, and IR36.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8688528/v1/8a1829e6d22332df297d8cf8.png"},{"id":101752605,"identity":"94dfccda-0101-4de2-9c00-fdc6823f5128","added_by":"auto","created_at":"2026-02-03 10:28:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1653806,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8688528/v1/310e86de-602f-4a01-b40a-22fe88c86d11.pdf"},{"id":101528729,"identity":"61f97d77-ef8d-4881-96ae-3c3aafd39851","added_by":"auto","created_at":"2026-01-30 19:10:06","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":215448,"visible":true,"origin":"","legend":"","description":"","filename":"PUBsupplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-8688528/v1/fbfb06a10e43f54415bdc657.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of iron salt addition on the viscoelastic properties of rice flours ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRice is consumed daily as a staple food, providing approximately 50% of the global dietary caloric supply to roughly 3.5\u0026nbsp;billion people [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Compared to other cereals, such as wheat and barley, rice is the most commonly consumed whole grain after cooking [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, to keep up with the fast-paced modern lifestyle and cope with increasing consumer demand, rice is processed to produce convenient products such as rice extrudates, baked goods, crackers, and noodles [\u003cspan additionalcitationids=\"CR4 CR5 CR6\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Several gluten-free products contain a large amount of rice starch due to its advantageous traits, such as a hypoallergenic nature and bland flavor [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Starch is the most abundant component in milled rice, accounting for approximately 90 % of its dry ass\u0026mdash;this branched glucose polymer comprises two types: amylose and amylopectin. Amylose has a smaller molecular weight (~\u0026thinsp;10\u003csup\u003e5\u0026ndash;6\u003c/sup\u003e) with few branches, while amylopectin molecules are relatively large, highly branched molecules (~\u0026thinsp;10\u003csup\u003e7\u0026ndash;8\u003c/sup\u003e) with a large number of short chains [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Amylose content is pivotal in designing new and novel food products with desired sensory and textural attributes. For example, rice varieties with intermediate-to-high amylose content (\u0026gt;\u0026thinsp;20%) are used in traditional rice noodle-making because they form a stronger gel network, a desired characteristic for this application [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The molecular structure and distribution of amylose and amylopectin fractions play a crucial role in determining the physicochemical and functional properties of rice [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eFortification of rice and rice-based products with iron is an excellent way to combat the increasing global case of anemia [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In line with this goal, several studies have successfully incorporated metal into rice flour, producing extrudates[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and noodles [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Exogeneous metal salts and starch can form different interactions: (1) forming Werner complexes in which central metal atoms coordinate or ligate to hydroxyl groups of amylose and amylopectin, (2) starch surface sorption complexes, (3) inclusion complexes involving the ability of the polysaccharides to form helical structures, and (4) capillary complexes holding metal compounds within capillaries between starch granules [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, even though the development of iron-fortified rice products and understanding metal-starch complexes are sought, there is a limited understanding of how the addition of iron affects the rice\u0026rsquo;s viscoelastic behaviours. It is essential to note that molecular interactions between iron and starch (specifically amylose and amylopectin) can affect processing parameters and the textural properties of the final product. The effect of iron on the viscoelasticity of rice flour has not yet been examined. Therefore, the main objective of this study was to investigate the impact of iron fortificant on the viscoelastic properties of rice with varying amylose content. The first part described the characteristics of the selected rice varieties in terms of starch granule morphology, starch molecular weight distribution, thermal properties, and inherent rheological properties, while the latter part detailed the effects of different amounts of sodium iron EDTA on the rheological properties of rice flour having different amylose content determined by frequency sweep and stress sweep experiments.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample preparation\u003c/h2\u003e \u003cp\u003eThe rice samples used in this study were IR65 (waxy), IR24 (low amylose), and IR36 (high amylose) rice. The rice was grown during the 2017 dry season in the irrigated field plots of the International Rice Research Institute (IRRI) in Los Ba\u0026ntilde;os, Laguna, Philippines, under optimal field management conditions. Seeds were harvested and dried to a moisture content of 12\u0026ndash;14%. Paddy rice samples were dehulled (Rice sheller THU-35A, Satake Corporation) and were polished (Kett Mill). For an analysis that requires ground samples, milled grains were ground separately in a mixer mill (MM 400, Retsch GmbH, Germany) and stored at a dry, ambient temperature. The iron fortificant used in this study is Sodium iron EDTA (Ethylenediaminetetraacetic acid ferric sodium salt, C\u003csub\u003e10\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eFeN\u003csub\u003e2\u003c/sub\u003eNaO\u003csub\u003e8\u003c/sub\u003e, Sigma Aldrich).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRice Morphology through Scanning Electron Microscopy\u003c/h3\u003e\n\u003cp\u003eThe surface morphology of native starch granules was examined by scanning electron microscopy (JEOL JSM-5310) operated at an accelerating voltage of 20 kV. Before imaging, samples were gold-coated, and micrographs were collected from the internal surface of the rice kernel.\u003c/p\u003e\n\u003ch3\u003eStarch Structure through Size Exclusion Chromatography\u003c/h3\u003e\n\u003cp\u003eRice flour (50 mg) was dispersed in 400 \u0026micro;L of 95% ethanol and 1.0 mL of 0.25 M NaOH, then heated on a hot plate at 150\u0026deg;C for 120 min. During gelatinization, hot water was added in 800 \u0026micro;L increments (total of 0.8 mL), and additional hot water was subsequently added to bring the final sample mass to 4.0 g. An aliquot (794 \u0026micro;L) of the gelatinized dispersion was combined with 206 \u0026micro;L of sodium acetate buffer and debranched by incubation with 8.0 \u0026micro;L of isoamylase (Megazyme, P113541) at 50\u0026deg;C in a water bath. Enzymatic activity was terminated by boiling the mixture for 5 min, after which the samples were centrifuged. The resulting supernatant was transferred to a tube containing approximately 320 mg of ion-exchange resin and incubated at 50\u0026deg;C for 30 min. After a final centrifugation step, the clarified supernatant was collected and analyzed by size-exclusion chromatography.\u003c/p\u003e\n\u003ch3\u003eThermal Properties\u003c/h3\u003e\n\u003cp\u003eFlour samples (4.0 mg) were mixed with 8.0 \u0026micro;L of water and sealed in hermetic aluminum pans prior to analysis using a differential scanning calorimeter (TA Instruments, DSC 250). Samples were heated from 25 to 110\u0026deg;C at 10\u0026deg;C/min, with an empty pan used as the reference for all measurements. Thermal transition parameters, including onset temperature (To), peak gelatinization temperature (Tp), enthalpy of gelatinization (ΔH), and amylose\u0026ndash;lipid complex melting behavior, were determined using TRIOS software. Reported values represent the mean of triplicate analyses, expressed with standard deviations.\u003c/p\u003e\n\u003ch3\u003eRheological Properties\u003c/h3\u003e\n\u003cp\u003eBefore iron addition, the intrinsic rheological behavior of rice flour during thermal processing was evaluated using a dynamic oscillatory temperature ramp. Measurements were performed on a controlled-stress rheometer (AR 2000, TA Instruments, New Castle, DE) to characterize the viscoelastic response associated with starch gelatinization and retrogradation. A parallel-plate geometry (40 mm diameter) with a fixed gap of 1 mm was employed. A 25% (w/w) rice flour suspension (1.2 mL) was loaded onto a Peltier-controlled plate and covered with a solvent trap sealed with water to minimize moisture loss during analysis. Samples were equilibrated at 35\u0026deg;C for 1 min under 1% strain and 1 Hz, followed by a heating ramp from 35 to 95\u0026deg;C at 4\u0026deg;C min⁻\u0026sup1;, then a cooling ramp from 95 to 35\u0026deg;C at the same rate. The resulting gel was equilibrated for an additional 1 min at 35\u0026deg;C before conducting a frequency sweep from 0.1 to 100 rad s⁻\u0026sup1; at an oscillatory stress of 0.1 Pa.\u003c/p\u003e \u003cp\u003eFor rice flour\u0026ndash;iron fortificant systems, suspensions (0.5 g mL⁻\u0026sup1;, dry basis) were prepared by incorporating sodium iron EDTA at concentrations of 2.5%, 5.0%, and 10% (w/w, based on rice flour). Gel preparation followed the method of Li et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] with minor modifications. Briefly, the iron\u0026ndash;flour dispersions were heated in boiling water for 35 min under continuous stirring to obtain fully gelatinized starch gels, then cooled to room temperature (25\u0026deg;C). An aliquot (1.3 mL) of the gel was placed on the rheometer plate, and excess material was trimmed. Oscillatory stress sweeps were performed from 0.01 to 100 Pa at a constant angular frequency of 6.283 rad s⁻\u0026sup1; and 25\u0026deg;C, while frequency sweeps were conducted from 0.1 to 10 rad s⁻\u0026sup1; at a constant stress of 0.1 Pa and the same temperature. Viscoelastic parameters, including storage modulus (G\u0026prime;), loss modulus (G\u0026Prime;), and loss tangent (tan δ\u0026thinsp;=\u0026thinsp;G\u0026Prime;/G\u0026prime;), were recorded. All rheological measurements were conducted in duplicate.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using one-way analysis of variance (ANOVA), followed by Tukey\u0026rsquo;s post hoc test at a significance level of α\u0026thinsp;=\u0026thinsp;0.05. All analyses were performed using the online freeware ASTATSA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://astatsa.com/OneWay_Anova_with_TukeyHSD/\u003c/span\u003e\u003cspan address=\"https://astatsa.com/OneWay_Anova_with_TukeyHSD/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eRice Microstructure\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe microstructural features of the internal regions of the rice kernels were analyzed by scanning electron microscopy, as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Native rice starch granules are generally characterized by polyhedral shapes with typical sizes ranging from approximately 3 to 8 \u0026micro;m [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u0026ndash;C, all rice varieties exhibited densely packed starch granules with irregular polyhedral morphology and particle sizes predominantly below 10 \u0026micro;m.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDebranched Starch Structure of Rice Flour\u003c/h2\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\u003eStarch Molecular Distribution Using Size-exclusion chromatography (SEC)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice Samples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% Amylose\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eStarch Molecular Distribution\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLCAM\u003c/p\u003e \u003cp\u003e(DP\u0026thinsp;\u0026gt;\u0026thinsp;1000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eICAP\u003c/p\u003e \u003cp\u003e(DP 121\u0026ndash;1000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMCAP\u003c/p\u003e \u003cp\u003e(DP 37\u0026ndash;120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSCAP\u003c/p\u003e \u003cp\u003e(DP 6\u0026ndash;36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.084\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.084\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.024\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.037\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.032\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eb**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65\u003csup\u003ec*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.92\u003csup\u003ec*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.82\u0026thinsp;\u0026plusmn;\u0026thinsp;4.26\u003csup\u003eb**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWithin each column, values with different letters are significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eSEC was employed to determine the molecular weight distribution of debranched starch isolated from native rice flour samples, as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The obtained chain-length distributions were classified into four fractions: long-chain amylose (LCAM; degree of polymerization, DP\u0026thinsp;\u0026gt;\u0026thinsp;1000), intermediate-chain amylopectin (ICAM; DP 1000\u0026ndash;121), medium-chain amylopectin (MCAP; DP 120\u0026ndash;37), and short-chain amylopectin (SCAP; DP 36\u0026ndash;6). In addition to resolving starch chain architecture, SEC provides a more reliable estimate of amylose content than conventional colorimetric methods [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Amylose content (AC) is a key parameter for classifying rice and assessing its functional performance. Rice is categorized as waxy (\u0026lt;\u0026thinsp;2% amylose on a dry-basis), very low (5\u0026ndash;12%), low (12\u0026ndash;20%), intermediate (20\u0026ndash;25%), or high amylose (25\u0026ndash;33%) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Based on SEC-derived amylose values, IR65 (0.084\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019%) was classified as waxy rice, IR24 (12.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00%) as low-amylose rice, and IR36 (26.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65%) as high-amylose rice.\u003c/p\u003e \u003cp\u003eThe SEC chromatograms further reflected these compositional differences (See Supplementary Fig.\u0026nbsp;1). Debranched non-waxy rice starches (IR24 and IR36) exhibited the characteristic SEC profile consisting of two dominant amylopectin peaks corresponding to different branch-chain populations, accompanied by a smaller amylose peak. In contrast, the waxy rice variety IR65 showed only amylopectin-derived peaks, confirming the near absence of amylose chains. Variations in the relative abundance of ICAM, MCAP, and SCAP fractions among the samples suggest differences in amylopectin fine structure, which can influence gelatinization behavior, retrogradation tendency, and enzymatic digestibility [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a product development perspective, amylose level and starch chain-length distribution play decisive roles in determining rice functionality. Waxy and low-amylose rice varieties are generally preferred for applications requiring soft, cohesive, and stable starch gels, particularly in wet or refrigerated products [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In contrast, high-amylose rice varieties are favored in products that require firmer texture, reduced stickiness, and resistance to structural breakdown during cooking [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Notably, rice containing 25\u0026ndash;33% amylose is considered optimal for rice noodle production due to its superior gel strength and cooking stability [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, previous textural studies have demonstrated that the amylose-to-amylopectin ratio strongly governs cooked rice attributes such as hardness and stickiness [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThermal Properties\u003c/h2\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\u003eThermal Properties of Rice Varieties\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice Samples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eGelatinization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAmylose-Lipid Complex\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT\u003csub\u003eonset1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT\u003csub\u003epeak1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eΔH\u003csub\u003eG\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT\u003csub\u003eonset2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eT\u003csub\u003epeak2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eΔH\u003csub\u003eALC\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e103.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.035\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.040\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWithin each column, values with different letters are significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the thermal properties of the three rice varieties as determined by differential scanning calorimetry. In general, rice starch thermograms exhibit two distinct endothermic transitions. The first transition corresponds to starch gelatinization, which involves the irreversible swelling and melting of the double helices and the disruption of crystalline regions within starch granules. The second transition, occurring at higher temperatures, is attributed to the melting of amylose\u0026ndash;lipid complexes. The peak gelatinization temperature (T\u003csub\u003epeak1\u003c/sub\u003e) represents the energy required to initiate starch gelatinization, as hydration of the amorphous regions is restricted by the surrounding crystalline domains. Meanwhile, the enthalpy of gelatinization (ΔH\u003csub\u003eG\u003c/sub\u003e) indicates the extent of crystalline-to-amorphous transformation and serves as an index of molecular order within the starch structure. Among the samples, the waxy rice IR65 exhibited the lowest T\u003csub\u003epeak1\u003c/sub\u003e (68.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u0026deg;C) but the highest ΔH\u003csub\u003eG\u003c/sub\u003e (9.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98 J g⁻\u0026sup1;) relative to the non-waxy varieties IR24 and IR36. This behavior suggests a starch matrix with a higher proportion of crystalline regions and fewer amorphous domains, consistent with previous reports [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Overall, the enthalpy values associated with the first endothermic transition across all rice samples ranged from 6.71 to 9.13 J g⁻\u0026sup1;. For the non-waxy rice varieties, a second endothermic transition associated with amylose\u0026ndash;lipid complex dissociation was observed. The amylose\u0026ndash;lipid complex peak temperatures (T\u003csub\u003epeak2\u003c/sub\u003e) were 103.32\u0026deg;C for IR24 and 99.47\u0026deg;C for IR36. Notably, IR36 exhibited a higher ΔHALC (1.27 J g⁻\u0026sup1;) than IR24, which can be attributed to its greater proportion of long-chain amylose (DP\u0026thinsp;\u0026gt;\u0026thinsp;1000; 20.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.92%), favoring enhanced amylose\u0026ndash;lipid inclusion complex formation. In contrast, no second endothermic transition was detected for IR65, consistent with its negligible amylose content and in agreement with previously reported findings [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These results highlight the importance of the inherent thermal behavior in rice starch, as variations in gelatinization and amylose\u0026ndash;lipid complex formation directly influence processing conditions, cooking performance, and the quality attributes of rice-based food products [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDynamic Shear Curves of rice flour at a controlled temperature ramp\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the viscoelastic behavior of the rice varieties subjected to a controlled temperature ramp, as characterized by advanced rheometry. The storage modulus (G\u0026prime;) reflects the elastic or solid-like component of the starch system, whereas the loss modulus (G\u0026Prime;) and loss tangent (tan δ) describe its viscous or liquid-like behavior. Together, these parameters provide insight into the structural evolution of rice flour suspensions during thermal processing (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDynamic rheological properties of rice flour\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRheological Properties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIR65\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIR24\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIR36\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eHeating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u0026rsquo;\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e338.00\u0026thinsp;\u0026plusmn;\u0026thinsp;28.99\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9376.00\u0026thinsp;\u0026plusmn;\u0026thinsp;121.62\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11420.00\u0026thinsp;\u0026plusmn;\u0026thinsp;270.00\u003csup\u003ec*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u0026rsquo;\u0026rsquo;\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105.21\u0026thinsp;\u0026plusmn;\u0026thinsp;16.40\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1503.50\u0026thinsp;\u0026plusmn;\u0026thinsp;68.59\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1670.00\u0026thinsp;\u0026plusmn;\u0026thinsp;74.00\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etan δ\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.022\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0094\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0030\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u0026rsquo;\u003csub\u003e95℃\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253.45\u0026thinsp;\u0026plusmn;\u0026thinsp;25.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3219.00\u0026thinsp;\u0026plusmn;\u0026thinsp;305.47\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5441.00\u0026thinsp;\u0026plusmn;\u0026thinsp;174.00\u003csup\u003ec*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u0026rsquo;\u0026rsquo;\u003csub\u003e95℃\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e332.25\u0026thinsp;\u0026plusmn;\u0026thinsp;32.60\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e386.30\u0026thinsp;\u0026plusmn;\u0026thinsp;11.50\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etan δ\u003csub\u003e95℃\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.034\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00033\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.071\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00016\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCooling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u0026rsquo;\u003csub\u003e35℃\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e329.75\u0026thinsp;\u0026plusmn;\u0026thinsp;17.32\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5201.50\u0026thinsp;\u0026plusmn;\u0026thinsp;389.62\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9627.50\u0026thinsp;\u0026plusmn;\u0026thinsp;238.50\u003csup\u003ec*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG\u0026rsquo;\u0026rsquo;\u003csub\u003e35℃\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.96\u0026thinsp;\u0026plusmn;\u0026thinsp;3.90\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e432.15\u0026thinsp;\u0026plusmn;\u0026thinsp;13.93\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e612.20\u0026thinsp;\u0026plusmn;\u0026thinsp;25.60\u003csup\u003ec*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etan δ\u003csub\u003e35℃\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0031\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.083\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.64 0.0011\u003csup\u003ec**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWithin each row, values with different letters are significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eDuring the heating phase (35\u0026ndash;95\u0026deg;C), the starch suspensions underwent a transition from a sol state to a gel state. This sol\u0026ndash;gel transformation was marked by the attainment of maximum storage modulus (G\u0026prime;\u003csub\u003emax\u003c/sub\u003e) and maximum loss tangent (tan δ\u003csub\u003emax\u003c/sub\u003e). Among the samples, IR36 exhibited the strongest elastic response, characterized by a higher G\u0026prime;\u003csub\u003emax\u003c/sub\u003e and a lower tan δ, indicative of a more rigid, well-developed gel network. This behavior is attributed to its higher amylose content and greater proportion of long-chain amylose (LCAM). In contrast, the waxy rice IR65 formed a comparatively weak gel, as evidenced by its lower G\u0026prime;\u003csub\u003emax\u003c/sub\u003e (338.00\u0026thinsp;\u0026plusmn;\u0026thinsp;28.99 Pa) and higher tan δ\u003csub\u003emax\u003c/sub\u003e (0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.022), showing a predominance of viscous behavior.\u003c/p\u003e \u003cp\u003eThe enhanced gel strength observed in non-waxy rice during gelatinization is associated with the leaching of amylose, which participates in the formation of a three-dimensional network through intermolecular hydrogen bonding among amylose, amylopectin, and water [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Conversely, in waxy rice, gel formation is mainly governed by interactions among leached amylopectin chains, leading to a weaker network. Prolonged heating beyond G\u0026prime;\u003csub\u003emax\u003c/sub\u003e led to partial breakdown of the starch gel network, likely due to the melting of residual crystalline regions within swollen starch granules. This structural deterioration was reflected in the reduced G\u0026prime; values observed at 95\u0026deg;C across all rice samples.\u003c/p\u003e \u003cp\u003eDuring the cooling phase (95\u0026ndash;35\u0026deg;C), a progressive increase in network strength was observed, coinciding with retrogradation of starch. Retrogradation refers to the reassociation and reordering of amylose and amylopectin chains following gelatinization, leading to the formation of more ordered structures [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Rice varieties with higher amylose content developed stronger gel networks upon cooling, as demonstrated by IR36, which showed higher G\u0026prime;\u003csub\u003e35\u0026deg;C\u003c/sub\u003e and lower tan δ\u003csub\u003e35\u0026deg;C\u003c/sub\u003e than IR24 and IR65. These rheological trends are consistent with previous observations that higher amylose content is associated with increased storage modulus in rice gels [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEffects of Iron on Rice Viscoelasticity\u003c/h2\u003e \u003cp\u003eDynamic (oscillatory) shear measurements offer valuable insight into the internal structure of starch gels [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In this study, frequency- and stress-sweep tests were conducted to evaluate changes in viscoelastic behavior with increasing levels of iron fortification in rice flour suspensions. Assessing the material response as a function of angular frequency and applied shear stress enabled clear differentiation between the storage (G\u0026prime;) and loss (G\u0026Prime;) moduli.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFrequency Sweep\u003c/h2\u003e \u003cp\u003eThe frequency sweep results further emphasize the pivotal role of amylose content in governing the viscoelastic behavior of rice flour gels. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. A-C, The G\u0026rsquo; value at 10 rad/s of IR65, IR24, and IR36 were 9.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76, 13.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69, and 16.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96 Pa, respectively, indicating that higher amylose content tends to have higher elasticity. IR36 consistently exhibited a higher storage modulus (G\u0026prime;) than waxy IR65, showing the ability of amylose to leach out during gelatinization and form compact, continuous gel networks. Additionally, Amylose exhibits lower steric hindrance and a more linear molecular structure, which enhances chain mobility and promotes rapid formation of a highly elastic three-dimensional gel network [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In contrast, the amylopectin-dominant structure of waxy rice limits network connectivity, resulting in weaker elastic responses. This trend is consistent with the work of Tian et al [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], who report that increasing amylose content is associated with elevated G\u0026prime;, G\u0026Prime;, and complex viscosity (η*), with consistency coefficients (K*) increasing by as much as 17\u0026ndash;24-fold when transitioning from waxy to high-amylose rice. Accordingly, IR36 (~\u0026thinsp;26% amylose) typically exhibits solid-like behavior (G\u0026prime; \u0026gt; G\u0026Prime;), whereas IR65 displays predominantly weak gel characteristics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParameterized Data of Frequency Sweep Test of IR65, IR24, and IR36 rice flour gels with varying iron concentration levels.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% Iron\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eIR36\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eIR24\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eIR65\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{K}^{*}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{n}^{*}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{K}^{*}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{n}^{*}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{K}^{*}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{n}^{*}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eraw\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.028\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.021\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00067\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.041\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.030\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00086\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.043\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0016\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.020\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00014\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.017\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.033\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0021\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.016\u003csup\u003eb**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.055\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0010\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.018\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.020\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00025\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.051\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.035\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0022\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00064\u003csup\u003eb**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0018\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.073\u003csup\u003eb**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.020\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00004\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.032\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.042\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00095\u003csup\u003eb\u003c/sup\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0047\u003csup\u003eb**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00071\u003csup\u003eb**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWithin each column, values with different letters are significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAddition of iron further modulated these viscoelastic properties in an amylose-dependent manner. Iron forms a Werner-type complex with starch, as determined by electron paramagnetic resonance spectroscopy and thermal studies [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Iron ligates the lone pairs of the hydroxyl groups in starch, altering its physical properties, such as viscoelasticity [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In IR36, iron addition enhanced gel elasticity, as evidenced by increased G\u0026prime; and K* values as listed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, suggesting the formation of additional intermolecular junctions through amylose\u0026ndash;iron cross-linking. Similar behavior has been reported in spelt starch [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which contains 20\u0026ndash;21% amylose, where iron(II) fortification increased the consistency index from approximately 1.06 to 2.60, closely mirroring the trends observed in IR36. Moreover, the complex modulus of the pea starch (~\u0026thinsp;40% amylose content) composite gels was 4.65-fold greater than that of pea starch hydrogels without Fe\u0026sup3;⁺ [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. These findings support the hypothesis that iron ions can act as coordination bridges between amylose chains, reinforcing the starch gel network. Conversely, iron addition weakened the viscoelastic structure of IR65 and IR24, as shown by reduced G\u0026prime; and K* values. The predominance of amylopectin in these systems likely restricts effective network formation, and metal\u0026ndash;amylopectin interactions may further disrupt molecular conformation. Indeed, a study on Zn\u0026sup2;⁺\u0026ndash;amylopectin complexes has demonstrated conformational weakening of amylopectin chains [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], which may explain the reduced elasticity observed upon iron addition in amylopectin-rich waxy and low-amylose rice.\u003c/p\u003e \u003cp\u003eThe mechanical spectra of all rice flour\u0026ndash;iron systems were well described by the power-law model, yielding flow behavior indices (n*) in the range of 0.02\u0026ndash;0.15, indicative of pronounced shear-thinning behavior typical of starch-based gels. Given the dominance of G\u0026prime; over G\u0026Prime; across samples, the consistency coefficient (K*) served as a reliable descriptor of elastic strength and effectively captured variations arising from differences in amylose content and iron fortification. Overall, these results highlight that the interplay between starch molecular architecture and iron coordination chemistry is a critical determinant of rice flour gel structure and functionality, with direct implications for the design of iron-fortified rice-based food products.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStress Sweep\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe oscillatory stress sweep responses of raw rice flour and rice\u0026ndash;iron gels are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, illustrating the dependence of the viscoelastic moduli (G\u0026prime; and G\u0026Prime;) on applied shear stress. For all samples, a well-defined linear viscoelastic region (LVR) was observed at low stress amplitudes (0.01\u0026ndash;1 Pa), where the moduli remained independent of stress, indicating structural integrity of the gel network. Among the rice varieties, IR65 exhibited the narrowest LVR, extending only up to approximately 0.05 Pa, suggesting a comparatively weaker gel structure.\u003c/p\u003e \u003cp\u003eBeyond the LVR (\u0026gt;\u0026thinsp;1 Pa), the storage modulus (G\u0026prime;) decreased progressively with increasing stress, while the loss modulus (G\u0026Prime;) initially increased to a maximum before declining. Correspondingly, tan δ remained nearly constant within the LVR and increased sharply once the critical stress was exceeded, reflecting the onset of network breakdown and enhanced viscous dissipation. Similar stress sweep behavior has been reported for rice starch gels with amylose contents ranging from 18.5 to 24.5% [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe stress sweep profiles of raw and iron-fortified gels from IR24 and IR36 are characteristic of Type III behavior (weak strain overshoot), as evidenced by an initial increase in G\u0026Prime; followed by a decrease after reaching a maximum, concurrent with a continuous decline in G\u0026prime;. This response suggests that the starch network\u0026mdash;particularly amylose with its extended molecular conformation\u0026mdash;forms a weakly structured, interconnected system stabilized by intermolecular associations such as hydrogen bonding. Under increasing deformation, the network resists strain up to a critical point, beyond which structural disruption occurs, leading to polymer chain alignment along the flow field and a subsequent reduction in G\u0026Prime; [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast, IR65 exhibited Type I strain-thinning behavior, where both G\u0026prime; and G\u0026Prime; decreased monotonically with increasing stress. At low stress levels, polymer chains are predominantly entangled, resulting in constant moduli; as stress increases, progressive disentanglement and alignment of amylopectin-rich chains reduce viscoelastic resistance. Across all rice varieties, iron fortification did not alter the inherent oscillatory stress response, indicating that the fundamental deformation mechanisms of the starch networks remained unchanged. However, consistent with the frequency-sweep results, iron addition increased the elastic modulus of high-amylose rice (IR36) while decreasing the elasticity of waxy rice (IR65). These findings further support the amylose-dependent role of iron in modulating the strength and structural resilience of starch gels.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that the addition of iron significantly influences the viscoelastic behavior of rice flour, acting in an amylose-dependent manner. Dynamic rheological analyses revealed that rice flour with higher amylose content forms stronger and more elastic gel networks during gelatinization and retrogradation, as evidenced by significantly higher storage moduli and lower loss tangents. Among the rice varieties examined, high-amylose IR36 consistently exhibited superior gel strength and elasticity compared with low-amylose IR24 and waxy IR65. The incorporation of sodium iron EDTA, an iron fortificant, further modulated these rheological properties. The addition of iron (2.5\u0026ndash;10.0% w/w) enhanced the elastic response and consistency of high-amylose rice flour gels, likely through interactions between iron ions and amylose chains that reinforce the three-dimensional network. In contrast, iron addition weakened the viscoelastic structure of waxy and low-amylose rice flours, suggesting that iron\u0026ndash;amylopectin interactions disrupt network formation in amylopectin-dominant systems. Importantly, stress sweep measurements indicated that iron fortification did not alter the intrinsic deformation behavior of the starch gels. Overall, the findings highlight the role of starch architecture in influencing the rheological response of iron-fortified rice flour. These insights provide a mechanistic basis for selecting appropriate rice varieties and optimizing processing conditions to develop iron-fortified rice-based foods with desirable texture and structural stability.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAPB: Conceptualization; Formal analysis; Methodology; Software; Validation; Investigation; Writing-original draft. JJA: Formal analysis; Methodology; Investigation. NS: Funding acquisition; Project administration; Resources; Supervision; Writing-review \u0026amp; editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eN. Hashim, M.M. Ali, M.R. Mahadi, A.F. Abdullah, A. Wayayok, M.S. Mohd, Kassim, A. 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Nonnewton Fluid Mech. \u003cb\u003e112\u003c/b\u003e, 237 (2003)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK. Hyun, S.H. Kim, K.H. Ahn, S.J. Lee, J. Nonnewton Fluid Mech. \u003cb\u003e107\u003c/b\u003e, 51 (2002)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"food-biophysics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Biophysics](https://www.springer.com/journal/11483)","snPcode":"11483","submissionUrl":"https://submission.nature.com/new-submission/11483/3","title":"Food Biophysics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8688528/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8688528/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIron addition to rice is widely promoted to address iron-deficiency anemia, yet its effects on the rheological behavior of rice flour remain poorly understood. This study investigated the impact of iron salt (sodium iron EDTA) on the viscoelastic properties of rice flours with varying amylose content, specifically waxy IR65, low-amylose IR24, and high-amylose IR36. Dynamic oscillatory rheology, including temperature ramp, frequency sweep, and stress sweep tests, was employed to evaluate gel formation, elasticity, and deformation behavior. During gelatinization, high-amylose IR36 exhibited significantly stronger gel formation, with a maximum storage modulus (G\u0026prime;max) of 11,420\u0026thinsp;\u0026plusmn;\u0026thinsp;270 Pa, compared with IR24 (9,376\u0026thinsp;\u0026plusmn;\u0026thinsp;122 Pa) and IR65 (338\u0026thinsp;\u0026plusmn;\u0026thinsp;29 Pa). Frequency sweep measurements showed that elasticity increased with amylose content, with G\u0026prime; at 10 rad s⁻\u0026sup1; reaching 16.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96 Pa for IR36. The addition of iron (2.5\u0026ndash;10%, w/w) further modulated viscoelasticity in an amylose-dependent manner, enhancing gel elasticity and consistency in high-amylose rice while reducing elastic strength in waxy and low-amylose systems. Stress sweep tests revealed that iron addition did not alter the intrinsic deformation behavior of the starch gels, with IR36 and IR24 exhibiting Type III weak-strain overshoot and IR65 exhibiting Type I strain-thinning behavior. Overall, the results demonstrate that iron\u0026ndash;starch interactions selectively reinforce amylose-rich networks while weakening amylopectin-dominant gels, providing critical insights for optimizing the formulation and processing of iron-fortified rice-based food products.\u003c/p\u003e","manuscriptTitle":"Impact of iron salt addition on the viscoelastic properties of rice flours","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-30 19:10:01","doi":"10.21203/rs.3.rs-8688528/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-30T06:40:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-29T09:53:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-28T10:50:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"267904253471844270288927632811623361525","date":"2026-01-28T04:28:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105091398795738354348988750317995166056","date":"2026-01-28T01:22:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-28T00:37:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-27T06:50:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-27T06:49:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Food Biophysics","date":"2026-01-24T17:53:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"food-biophysics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Biophysics](https://www.springer.com/journal/11483)","snPcode":"11483","submissionUrl":"https://submission.nature.com/new-submission/11483/3","title":"Food Biophysics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b49e5e73-e557-4cc3-8ecc-ebae998222a3","owner":[],"postedDate":"January 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T17:24:22+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-30 19:10:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8688528","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8688528","identity":"rs-8688528","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}