Maize‐derived arabinoxylans modulate starch pasting, gel structure, and retrogradation

Abstract

BACKGROUND

Starch–fiber interactions play a paramount role in determining the functional quality and stability of starch‐based food products. This study systematically examined how maize arabinoxylans (MAX) influences the hydration, pasting, textural, and microstructural properties of maize starch gels.

RESULTS

Maize starch composites containing 0, 1, 3, 6, and 9 g 100 g⁻¹ (w/w) MAX were subjected to water‐ and oil‐binding assays, Rapid Visco Analyzer (RVA) profiling, texture profile analysis (TPA), and scanning electron microscopy with morphometric quantification. Inclusion of MAX produced a marked shift in polymer–fluid dynamics: water‐binding capacity decreased from 0.95 (control) to 0.74–0.77 g g⁻¹, while oil‐binding capacity increased from 0.61 to 0.73 g g⁻¹ at 9 g 100 g⁻¹ MAX. Correspondingly, RVA pasting profiles exhibited concentration‐dependent reductions in peak, breakdown, and final viscosities, indicative of restricted granule swelling, diminished amylose leaching, and attenuated retrogradation. TPA revealed that gels with composites containing ≥ 6 g 100 g⁻¹ MAX were significantly firmer, gummier, chewier, and more resilient both immediately and after 48 h of cold storage, confirming enhanced network rigidity and resistance to structural rearrangement. Microstructural analysis demonstrated a progressive transition where low MAX levels (1–3 g 100 g⁻¹) yielded open, porous matrices, whereas higher levels (6–9 g 100 g⁻¹) produced dense, cohesive architecture with thicker cell walls.

CONCLUSION

Collectively, these findings reveal that MAX contributes to the development of starch gels with controlled viscosity, improved structural stability, and minimized retrogradation. This mechanistic understanding provides a framework for tailoring starch–fiber composites in complex food matrices requiring controlled thickening and improved stability. © 2025 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

INTRODUCTION

Arabinoxylans (AX) are anionic, non‐starch polysaccharides predominantly found in the cell walls of cereal grains, where they play structural roles and contribute to dietary fiber content. ¹ They are composed of a linear β‐(1 → 4) linked xylan backbone to which α‐l‐arabinofuranose units are connected as side residues via α‐(1 → 3) and/or α‐(1 → 2) linkages. ² In addition to their recognized health benefits, such as prebiotic and antioxidant activity as well as glycemic control, ³ , ⁴ their relevance in food technology has grown substantially due to their ability to modulate water retention, viscosity, and gelation properties in starch‐based systems. ⁵ , ⁶ Given that AX can alter key physicochemical properties of starch, including its gelatinization behavior, ⁷ , ⁸ there is growing interest in understanding AX–starch interactions as a strategy to enhance the quality and performance of starch‐based formulations.

Starch, as a key structural and functional component in many cereal‐derived food matrices, plays a pivotal role in defining texture, stability, and overall product quality. ⁹ Its functional performance is strongly influenced by interactions with other food constituents, among them dietary fiber such as AX. Yan et al. ¹⁰ reported that the addition of low concentrations (0.25 and 1 g 100 g⁻¹) of wheat AX increased the hardness of wheat starch gel. When incorporated at 2 g 100 g⁻¹, wheat AX significantly reduced the swelling power, solubility, and peak viscosity of wheat starch, along with the storage modulus (G′) and loss modulus (G″) during heating. ⁷ Additionally, 2 g 100 g⁻¹ wheat AX modified starch gel microstructure by creating smaller pores and a denser, more cohesive matrix, in contrast to the fibrous, spongy, and less uniform structure observed in control gels. ⁷ On the other hand, emerging evidence suggests that the addition of 2 g 100 g⁻¹ wheat AX effectively delayed both the gelatinization and retrogradation of wheat starch and, during cold storage, starch–AX mixtures exhibited higher paste transparency, indicative of reduced retrogradation. ¹¹ At higher concentrations, Xie et al. ⁵ found that 4 g 100 g⁻¹ addition of wheat AX markedly reduced starch swelling and amylose leaching, while simultaneously enhancing amylose solubility. In contrast, AX from rye at 2 g 100 g⁻¹ level promoted starch retrogradation across different starches, including wheat, waxy maize, and amylomaize starches. After 7 days of storage, gels containing AX exhibited increased rigidity, as indicated by higher storage modulus (G′) and decreased elasticity compared to freshly prepared gels. ¹²

To date, a substantial body of research on AX‐starch has focused on AX extracted from wheat and rye, while AX from maize (MAX) has received comparatively little attention. Maize bran, an underutilized by‐product of milling and bioethanol industries, is a promising source of MAX that not only represents a sustainable valorization route for cereal processing side‐streams but also exhibits distinct structural characteristics compared to AX from other cereals. ¹³ MAX differs structurally from wheat or rye AX by generally having a lower arabinose‐to‐xylose ratio and fewer ferulic acid crosslinks – factors that influence solubility, viscosity, and interaction potential with starch. ¹⁴ While recent studies, such as Solomou et al., ¹⁵ have investigated AX in bread dough systems and highlighted functional differences between wheat‐ and maize‐derived AX, these complex systems do not isolate starch interactions, leaving a gap in understanding the behavior of MAX in simplified starch‐based matrices. Despite their abundance and potential functionality, the role of MAX in modifying starch characteristics remains largely unexplored. Existing studies on MAX have primarily addressed extraction, structural characterization, and gelling capacity. ¹³ , ¹⁶ , ¹⁷ Only one study has investigated the effects of MAX on maize starch, but it assessed a single fixed level of addition (5%), without exploring concentration‐dependent effects. ¹⁸ Thus, data on how a wider range of MAX concentrations interact with maize starch at both molecular and functional levels are lacking. Moreover, a mechanistic understanding of their impact on technological properties such as pasting, texture, and microstructure is still needed to better exploit MAX in food formulation and processing applications.

In this study, a simplified maize starch–MAX binary system was employed to isolate and mechanistically examine their direct interactions without the compositional interference of proteins and lipids, or other components typically present in cereal dough matrices. From an industrial perspective, understanding the concentration‐dependent influence of MAX is essential for developing fiber‐enriched, clean‐label, and texture‐optimized starch‐based foods. Maize starch was selected because it is a widely used industrial ingredient across multiple product categories, including extruded snacks, gels, and gluten‐free formulations, making it a relevant model system for practical applications.

In this context, the present study aims to systematically investigate the concentration‐dependent effects of commercial MAX on the hydration, pasting behavior, textural properties, and microstructure of maize starch‐based gels. The findings are expected to provide novel insights into the techno‐functional role of MAX in starch systems, supporting their rational application in food design and processing.

MATERIALS AND METHODS

Materials

MAX were kindly provided by Pannonia Bio Zrt. (Dunaföldvár, Hungary) and were extracted from maize (Zea mays L.) bran. Their composition was 9.2 g 100 g⁻¹ moisture, 80.7 g 100 g⁻¹ soluble fiber, 7.6 g 100 g⁻¹ protein, 0.6 g 100 g⁻¹ fat, 0.5 g 100 g⁻¹ ash, and 17.7 mg 100 g⁻¹ ferulic acid. The weight‐average molecular weight was 285 ± 13 kDa, and the arabinose‐to‐xylose (A:X) ratio was 0.6. The maize feedstock was processed using an alkaline extraction followed by ethanol precipitation. Maize starch (10.6 g 100 g⁻¹ moisture content, 88.1 g 100 g⁻¹ carbohydrates, 0.6 g 100 g⁻¹ protein, 0.3 g 100 g⁻¹ fat, 0.4 g 100 g⁻¹ ash, and amylose 38.6%) was obtained from a local grocery store in Winnipeg (Fleischmann's Canada Corn Starch, Canada). All other chemicals used in this study were of analytical grade.

Functional characterization of maize starch–MAX composites

The water‐binding capacity (WBC) of the samples was determined in accordance with AACC International Method 56–30.01, ¹⁹ referring to the quantity of water retained by the sample after centrifugation and calculated as follows:

$$\mathrm{WBC}\left(\mathrm{g}{\mathrm{g}}^{-1}\right)=\text{Weight of sediment after water removal}\left(\mathrm{g}\right)/\text{Initial sample weight}\left(\mathrm{g}\right)$$

Oil absorption capacity (OAC) was measured as grams of oil bound per gram of the sample and following the protocol described by Cornejo and Rosell: ²⁰

$$\mathrm{OAC}\left(\mathrm{g}{\mathrm{g}}^{-1}\right)=\text{Weight of sediment after oil removal}\left(\mathrm{g}\right)/\text{Initial sample weight}\left(\mathrm{g}\right)$$

All the analyses were run in triplicate.

Maize starch–MAX gel preparation

The control starch gel was prepared by dispersing 1.75 g (dry basis) starch powder in 12.5 mL distilled water in a small jar with an internal diameter of 40 mm and a height of 40 mm. To assess the effect of MAX, increasing amounts (1, 3, 6, and 9 g 100 g⁻¹) were used to partially substitute the starch powder. The dispersions were continuously stirred and heated in a boiling water bath for 15 min and then allowed to cool to room temperature for 2 h. One set of samples was analyzed immediately, while another set was stored at 4 °C for 48 h to assess changes during cold storage.

Apparent viscosity of maize starch–MAX composites

The apparent viscosity of the samples was determined using a Rapid Visco Analyzer (RVA 4800, PerkinElmer Inc., Waltham, MA, USA). Pre‐weighed amounts of sample were used to obtain 3.5 g total solids (adjusted to 14% moisture content) and mixed with 25 mL distilled water in an RVA canister. A ‘starch‐only’ Control_MAX‐9 gel was prepared using the same starch mass as the MAX‐9 sample but omitting MAX to isolate dilution effects. To evaluate the role of pH, this control gel was then acidified to pH 3.2, matching the MAX‐9 sample, by the dropwise addition of 0.1 mol L⁻¹ hydrochloric acid under constant stirring, while maintaining the original solids‐to‐water ratio, yielding the Control_MAX‐9_pH 3.2 variant. Final pH values of all gels were confirmed after the RVA run using a spear‐tip, gel‐filled capillary junction combination electrode (Fisher Scientific, Waltham, MA, USA). The analysis of pasting properties was performed following AACC International Method 76–21.02 ¹⁹ using the Standard 1 temperature profile. Pasting parameters were calculated with Thermocline for Windows (TCW3) software, including peak viscosity (maximum viscosity during heating, cP), trough viscosity (minimum viscosity during the high‐temperature holding phase, cP), breakdown (difference between peak and trough viscosity, cP), final viscosity (viscosity at the end of the test, cP), and total setback (difference between final and trough viscosities, cP). The analysis was conducted in duplicate.

Microstructural analysis and digital image‐based morphometric profiling

Gels coming from the RVA tests were freeze dried and their microstructure was examined using a scanning electron microscope (FEI Quanta 650 FEG SEM, Thermo Fisher Scientific, Waltham, MA, USA) operating at an accelerating voltage of 10 kV. Prior to imaging, the samples were coated with a thin layer of gold–palladium using a Desk II Sputter Coater (Denton Vacuum, Moorestown, NJ, USA) and observed at a magnification of 200×.

For each sample, two micrographs were captured and analyzed using ImageJ software (version 1.54p, NIH, Bethesda, MD, USA) to assess microstructural features. All images were converted to 8‐bit grayscale and optimized for contrast and brightness. Thresholding was manually adjusted for each image by adapting the algorithm parameters within the software to ensure accurate segmentation.

Morphometric analysis was performed by determining the following parameters:

• Porosity (%) = (number of pores (n))/(total area (μm²)) × 100

• Matrix coverage (%) = 100 − porosity (%)

• Pore number distribution (PND, %) = (Number of pores/total pores) × 100. This refers to the frequency distribution of pores across three defined size classes (<1000, 1000–10 000, 10 000 μm²).

• Median pore distribution (MPD, μm²) = median value of the pore size distribution.

Impact of MAX on gel texture during storage

The effect of MAX on starch gel retrogradation was assessed at 0 and 48 h after cold storage at 4 °C using a TA.XTplus Texture Analyzer (Stable Micro Systems, Godalming, UK), equipped with a 5 kg load cell and controlled via Texture Exponent software (version 2.0.7.0). Texture profile analysis (TPA) was conducted on the gel contained in the jar using a double compression test with a cylindrical probe (20 mm diameter). The samples were compressed to 75% strain, with a set distance of 30 mm and a 2 s holding time between compressions. The pre‐test speed was set to 1 mm s⁻¹, while the test and post‐test speeds were both 5 mm s⁻¹, with a trigger force of 5 g. The peak force recorded during the first compression was defined as hardness, and additional parameters including gumminess, chewiness, and resilience were also calculated. ²¹ Each experimental condition was tested in quadruplicate.

Statistical analysis

All experiments were conducted on two independent batches of samples. The number of replicates varied according to the specific analysis, as detailed in the corresponding sections above. The experimental data were analyzed using Statgraphics Centurion XIX software (Statistical Graphics Corp., Rockville, MD, USA). Results are presented as mean values ± standard deviation, and Tukey's honestly significant difference (HSD) test was applied to determine statistically significant differences between group means at a confidence level of P ≤ 0.05. Pearson correlation coefficients (r) were calculated to assess the strength and significance of relationships among variables. Principal component analysis (PCA) was applied on mean‐centered, autoscaled data (averaged replicates) using OriginPro 2024 (OriginLab, Northampton, MA, USA), retaining components with eigenvalues >1 and sufficient explained variance to generate score and loading plots.

RESULTS AND DISCUSSION

Functional characterization of MAX–maize starch composites

Table 1 summarizes the WBC and oil‐binding capacity (OBC) of maize starch–MAX composites. A significant decrease (P < 0.05) in WBC was observed upon MAX addition compared to the control (0.95 ± 0.04 g g⁻¹), with all MAX‐enriched samples exhibiting similar and significantly lower values (ranging from 0.74 to 0.77 g g⁻¹). This reduction suggested that the presence of MAX disrupts the starch network's ability to retain water, probably due to multiple intermolecular interactions. As hydrophilic colloids, AX can compete with starch granules for available water, thereby limiting their hydration and expansion. ⁷ In addition, some AX molecules may bind to the surface of starch granules via hydrogen bonding, while others may interact with leached amylose, gradually forming a coating around the granules. ²² Furthermore, ferulic acid within the AX structure can form non‐covalent interactions (hydrogen bonds, hydrophobic interactions, and electrostatic forces) with starch molecules. ²³ In the current MAX, the ferulic acid content was measured at 17.7 mg 100 g⁻¹ (range 10–23 mg 100 g⁻¹), which is moderate compared to typical values reported in wheat bran (136–251 mg 100 g⁻¹). ²⁴ These results suggest that ferulic acid‐mediated interactions likely contributed to the observed reduction in water binding, though their effect is expected to be moderate relative to highly feruloylated AX.

Table 1.

Impact of different maize arabinoxylans (MAX) levels on the hydration properties of maize starch composites

Parameter	Control	MAX‐1	MAX‐3	MAX‐6	MAX‐9
WBC (g g−1)	0.95 ± 0.04b	0.76 ± 0.01a	0.77 ± 0.02a	0.74 ± 0.03a	0.74 ± 0.02a
OBC (g g−1)	0.61 ± 0.04a	0.64 ± 0.02ab	0.66 ± 0.05ab	0.66 ± 0.02ab	0.73 ± 0.05b

Values are expressed as mean ± standard deviation. Different lower‐case letters within the same row indicate statistically significant differences between formulations (P < 0.05). Control: 100% maize starch; MAX‐1: maize starch composite with 1 g 100 g⁻¹ maize arabinoxylan; MAX‐3: maize starch composite with 3 g 100 g⁻¹ maize arabinoxylan; MAX‐6: maize starch composite with 6 g 100 g⁻¹ maize arabinoxylan; MAX‐9: maize starch composite with 9 g 100 g⁻¹ maize arabinoxylan. WBC, water‐binding capacity; OBC, oil‐binding capacity.

Conversely, a progressive increase in OBC was observed with increasing MAX concentration. While the control sample showed the lowest OBC (0.61 ± 0.04 g g⁻¹), a significant increase was recorded at 9 g 100 g⁻¹ MAX (0.73 ± 0.05 g g⁻¹, P < 0.05). It is important to highlight that pure MAX had a much higher OBC (9.85 g g⁻¹), being responsible for the increase in the OBC of the composite gels. This enhancement could be attributed to the structural rearrangement of the matrix and the greater surface availability of non‐polar or hydrophobic sites facilitated by MAX integration. ²⁵ Such reorganization of the starch–fiber network supports increased interaction with lipophilic substances.

The divergent trends in WBC and OBC suggest that MAX altered the matrix–fluid interactions, potentially by restructuring the starch network, reducing water entrapment, and exposing additional regions capable of interacting with lipophilic substances. These functional shifts may have important implications for tailoring the textural, moisture retention, and sensory attributes of MAX‐starch‐based formulations.

Apparent viscosity of maize starch–MAX composites

The RVA profiles (Fig. 1) illustrate the effect of MAX at increasing concentrations (1–9 g 100 g⁻¹) on the pasting behavior of starch‐based systems under a controlled heating–holding–cooling cycle (indicated by the dotted red temperature curve).

Figure 1.

Pasting profiles of starch systems with increasing MAX levels (1–9 g 100 g⁻¹) and control (0 g 100 g⁻¹). Control: 100 g 100 g⁻¹ maize starch; MAX‐1: maize starch composite with 1 g 100 g⁻¹ maize arabinoxylans; MAX‐3: maize starch composite with 3 g 100 g⁻¹ maize arabinoxylans; MAX‐6: maize starch composite with 6 g 100 g⁻¹ maize arabinoxylans; MAX‐9: maize starch composite with 9 g 100 g⁻¹ maize arabinoxylans. Control_MAX‐9 matched the starch content of the 9 g 100 g⁻¹ MAX sample without MAX; Control_MAX‐9_pH 3.2 was acidified to match the pH of the MAX‐9 sample.

The control sample (100 g 100 g⁻¹ starch, no MAX) exhibited a typical pasting pattern, characterized by a rapid rise in apparent viscosity during gelatinization, a well‐defined peak, a reduction during the holding phase (breakdown), and a final increase during cooling (setback). This curve represents the baseline pasting behavior of starch in the absence of non‐starch polysaccharides. Upon MAX addition, a clear trend emerged: increasing concentrations of MAX progressively reduced peak, breakdown, and final viscosity values. The formulations containing 6 and 9 g 100 g⁻¹ MAX showed the lowest peak viscosities, reaching 2619 ± 66 and 2449 ± 4 cP, respectively (P < 0.05). MAX significantly delayed the appearance of peak viscosity. Specifically, the MAX‐9 sample reached its peak viscosity at 6.07 ± 0.04 min, which was approximately 1.4 min later than the control sample lacking MAX (4.70 ± 0.33 min). However, differential scanning calorimetry analysis did not reveal significant differences in thermal properties between the two formulations. The onset temperature, peak gelatinization temperature, and enthalpy values (data not shown) were comparable between the control (64.34 ± 2.28 °C, 70.91 ± 0.37 °C, and 16.37 ± 1.05 J g⁻¹, respectively) and MAX‐9 (66.47 ± 0.47 °C, 70.86 ± 0.16°C, and 16.17 ± 2.21 J g⁻¹, respectively). During the holding phase (95 °C), the control and MAX‐1 samples showed the highest trough viscosities, with no significant difference between them, while trough values decreased progressively with higher MAX levels. The breakdown viscosity (difference between peak and trough viscosities), an indicator of paste stability under shear and heat, was significantly reduced by the presence of MAX. However, no significant differences in breakdown values were observed among the MAX‐containing samples, suggesting a consistent stabilizing effect at all inclusion levels. Final viscosity, measured during the cooling stage and often related to amylose reassociation and gel formation, significantly decreased with increasing MAX content. The control exhibited the highest final viscosity, while the MAX‐9 sample showed the lowest, confirming the inhibitory effect of MAX on amylose retrogradation‐related viscosity development. Total setback viscosity (final viscosity minus trough viscosity) showed no clear dose‐dependent pattern. The samples with 1 and 3 g 100 g⁻¹ MAX exhibited the lowest setback values, while no significant differences were observed among the control, MAX‐6, and MAX‐9 formulations. Observing the overall pattern with increasing MAX concentrations, the impact on reducing the apparent peak viscosity was more pronounced than that of the final viscosity. This trend indicates that MAX was having a greater impact on the amylopectin swelling and rupture than on the amylose chains.

These observations are consistent with previous findings reported by Hou et al., ⁷ in which wheat AX inclusion (up to 2 g 100 g⁻¹) significantly lowered the peak viscosity of wheat starch. Peak viscosity is influenced by multiple factors, including granule swelling, friction between swollen granules, amylose leaching, and water availability. ²⁶ The observed reduction may be due to MAX limiting starch swelling and retaining more amylose within the ungelatinized granules, as supported by the following decreased final viscosities. ⁷ Similar trends have been described for other non‐starch polysaccharides such as inulin and pectin. Studies have shown that the addition of inulin and pectin significantly reduced the peak viscosity and breakdown values of starch pastes. ²⁷ , ²⁸ , ²⁹ This reduction was attributed to their ability to adsorb onto starch granule surfaces during gelatinization, inhibiting granule swelling and amylose leaching, which in turn lowered the apparent viscosity of the system. ²⁹ , ³⁰ Furthermore, the high hygroscopicity of inulin reduced water availability for starch granule hydration, preventing full gelatinization and viscous network formation. ³¹ Also, MAX may act as a plasticizer in the continuous phase, like pectin, reducing friction between swollen granules and decreasing resistance to flow, which results in a lower peak viscosity. ²⁹ In a more diluted system (1 mg MAX with 20 mg maize starch in 25 mL water, 5% w/w relative to starch), Zhang et al. ¹⁸ reported that MAX of varying molecular weights increased peak viscosity due to interaction with the leached amylose molecules via intermolecular hydrogen bonding or entanglement. Similar to MAX, the presence of inulin also improved starch paste stability, reflected by a decreased breakdown viscosity, and retarded short‐term retrogradation by interfering with amylose reassociation during cooling, as indicated by reduced setback viscosity. ³¹ However, differences in molecular structure, such as the arabinose substitution on the xylan backbone of MAX compared to the fructose‐based inulin, may lead to variations in WBC and steric hindrance effects, potentially explaining some of the distinctions in their impact on starch pasting behavior.

To isolate the effect of MAX from starch dilution, a Control_MAX‐9 sample was prepared using the same amount of starch as in the 9 g 100 g⁻¹ MAX formulation but without any MAX. This sample exhibited a significantly higher peak viscosity (3496 ± 11 cP) compared to the MAX‐9 sample (2449 ± 4 cP), confirming that the reduction in viscosity is due to the presence of MAX rather than decreased starch content. To further investigate the role of pH, this control was acidified to match the pH of the MAX‐9 sample (pH 3.2), creating the Control_MAX‐9_pH 3.2 sample. This formulation showed a moderately lower viscosity (3352 ± 32 cP) than its non‐acidified counterpart, but still significantly higher than the MAX‐9 sample. This indicates that, while acidification slightly reduces viscosity, it does not account for the full effect observed with MAX inclusion, suggesting that MAX exerts a dominant structural effect on the pasting behavior of starch.

Microstructural analysis and digital image‐based morphometric profiling

Figure 2 displays scanning electron microscopy (SEM) images of maize starch matrices (cross‐section) containing increasing concentrations (1–9 g 100 g⁻¹) of MAX, compared with the control sample without MAX. It must be noted that the porous architecture observed in conventional SEM of freeze‐dried gels largely reflected the size and morphology of ice crystals formed during freezing and subsequently removed by sublimation, rather than the native pore structure present in the hydrated gel. ³² Nevertheless, MAX concentration can strongly influence freezing behavior by modifying water distribution, local viscosity, and interactions within the starch network. Such changes affect ice nucleation and growth, and thus determine the size, shape and connectivity of the voids that remain after lyophilization. Consequently, the systematic differences among samples still provide useful insight into how MAX affects the physical organization and structural stability of the gel matrices.

Figure 2.

Scanning electron microscope images at 200× magnification. Control: 100 g 100 g⁻¹ maize starch; MAX‐1: maize starch composite with 1 g 100 g⁻¹ maize arabinoxylans; MAX‐3: maize starch composite with 3 g 100 g⁻¹ maize arabinoxylans; MAX‐6: maize starch composite with 6 g 100 g⁻¹ maize arabinoxylans; MAX‐9: maize starch composite with 9 g 100 g⁻¹ maize arabinoxylans.

The control sample (Fig. 1(a)) exhibited a porous and well‐developed network with relatively uniform cell walls and interconnected voids. Upon incorporation of 1 g 100 g⁻¹ MAX, the matrix displayed a visibly more open and aerated structure, with larger and more irregular pores. This indicated that a low concentration of MAX modified the thermal and physical environment for ice formation, leading to fewer nucleation events and the development of larger ice crystals. As the MAX concentration increased to 3 g 100 g⁻¹, the structure appeared more compact, the pore more rounded and with thicker walls. The trend toward structural densification was more pronounced at 6 and 9 g 100 g⁻¹ MAX levels. At 6 g 100 g⁻¹, the matrix was characterized by markedly fewer pores and smoother, thicker walls, suggesting that increasing MAX concentration hindered ice crystal growth and favored the development of a more cohesive gel network upon freezing. Similarly, the 9 g 100 g⁻¹ sample retained a dense matrix but with more irregular voids, less continuous porous network and broken cell walls compared to the control. Such heterogenicity may result from extensive restriction of ice crystal growth, resulting from MAX adsorption onto the surface of starch granules, which limited their swelling and expansion and altered local water mobility during the freezing process.

These observations align with findings from Zeng et al., ³³ who reported that arabinoxylan–starch composite films exhibited increased structural stability and reduced water diffusion rates with increasing starch content, indicating that interactions between arabinoxylan and starch significantly influence the microstructure and water mobility within the matrix. It has also been reported that wheat gel structure characterized by a rough surface and a weak, fragile framework were obtained when wheat AX addition increased from 0.2 to 4 g 100 g⁻¹. ⁵ An opposite trend was described by Yan et al., ⁸ who observed that wheat starch gels containing 0.25 g 100 g⁻¹ wheat AX had small pores with thick cell walls, whereas increasing the AX concentration to 1 g 100 g⁻¹ produced gels with noticeably larger pore openings. The authors attributed this to AX hindering amylose chains, resulting in an insufficient amount of amylose in the starch's amorphous regions to form a well‐developed network.

The microstructural morphometric analysis of gels is represented in Fig. 3. Spider plots, coupled with SEM images (100×), highlight significant shifts in porosity, matrix coverage, and PND across three pore size ranges (<1000, 1000–10 000, >10 000 μm²). The control sample exhibited the lowest porosity (43%) and the highest percentage of small pores (59%), indicating a compact and finely structured matrix. Incorporation of 1 g 100 g⁻¹ MAX markedly increased porosity (51%) and the presence of large pores (>10 000 μm²), suggesting a more open, less compact structure consistent with conditions favoring growth of larger ice crystals. This trend continued at 3 g 100 g⁻¹ MAX, with similarly high porosity and a more balanced pore distribution, pointing to a more expanded and stabilized network. At 6 g 100 g⁻¹ MAX, porosity slightly decreased while matrix coverage peaked (52%), with the highest proportion of large pores (16%), indicating denser yet well‐developed structures. Interestingly, at 9 g 100 g⁻¹ MAX, porosity dropped back to control levels, large pores declined sharply (5%), and matrix coverage reached its highest value (57%), suggesting partial pore collapse of larger ice‐templated voids. Overall, the incorporation of MAX modulated the starch microstructure in a concentration‐dependent manner: low to moderate levels (1–3 g 100 g⁻¹) enhanced porosity and pore expansion, supporting a more open and aerated structure, while higher levels (6–9 g 100 g⁻¹) promoted densification and reduced structural heterogeneity. The size and wall thickness of the pores measured in the freeze‐dried samples may reflect enhanced entanglement forces between starch fragments. Greater entanglement improves repulsive forces, which in turn drive water redistribution away from a homogeneous gel matrix. ³⁴ The increased porosity detected in samples containing up to 3 g 100 g⁻¹ MAX mirrored the effect reported with sodium alginate additions to maize starch (up to 2 g 100 g⁻¹), where larger cavities and wider spacing between partition walls were also noted. ³⁵ Conversely, the reduction of porosity progressively recorded along with all the MAX continuing samples has also been described in binary systems containing lotus root starch in the presence of increasing concentration (up to 1.5 g 100 g⁻¹) of xanthan gum. In those systems, the gel structure became progressively denser compared to the control sample without xanthan gum. ³⁶

Figure 3.

Morphometric profiling of samples. Different letters indicate statistically significant differences (P < 0.05). Control: 100 g 100 g⁻¹ maize starch; MAX‐1: maize starch composite with 1 g 100 g⁻¹ maize arabinoxylans; MAX‐3: maize starch composite with 3 g 100 g⁻¹ maize arabinoxylans; MAX‐6: maize starch composite with 6 g 100 g⁻¹ maize arabinoxylans; MAX‐9: maize starch composite with 9 g 100 g⁻¹ maize arabinoxylans.

To elucidate how pore architecture governs hydration, pasting behavior, and structure in MAX–starch gels, Pearson correlation coefficients were calculated between pore size metrics and key functional parameters. The proportion of small pores (<1000 μm²) exhibited a very strong positive correlation with WBC (r = 0.91, P ≤ 0.05); a finer (ice‐templated) microstructure was associated with reduced MAX interference and thus greater water availability for starch swelling. This was further confirmed by a moderate positive correlation with both peak viscosity (r = 0.77, P ≤ 0.05) and final viscosity (r = 0.70, P ≤ 0.05). In fact, during pasting, this densely interconnected network resisted shear and confined leached amylose, resulting in higher apparent viscosities at gelatinization peak and upon cooling. ³⁷ On the other hand, median pore size (1000–10 000 μm²) demonstrated strong negative correlations with WBC (r = −0.90, P ≤ 0.05), peak viscosity (r = −0.75, P ≤ 0.05), and final viscosity (r = −0.70, P ≤ 0.05). This implies that increased MAX content resulted in coarser structures with reduced water availability for starch swelling and gelatinization. Consequently, less amylose was leached and weaker network formation occurred, leading to lower viscosity development during and after pasting. ⁷

Impact of MAX on gel texture during storage

The incorporation of MAX markedly influenced the texture profile of starch‐based gels (Table 2). At 0 h, a significant (P < 0.05) increase in hardness was observed with increasing MAX levels: each formulation differed from the others, except for MAX‐1 and MAX‐3, as well as MAX‐3 and MAX‐6, which were not significantly different. The control was significantly softer than all MAX‐containing gels, while MAX‐9 exhibited the highest hardness value (395 ± 19 g). This suggests that MAX acted as a structuring filler, reinforcing the three‐dimensional amylose/amylopectin network. A similar trend has been reported with AX from wheat, where increasing their concentration (from 0.2 to 4 g 100 g⁻¹) led to progressively firmer (from 7.7 to 10.4 N) freshly prepared wheat starch gels. ⁵ At 48 h, a similar concentration‐dependent trend was observed: MAX‐9 (471 ± 61 g) remained significantly firmer than all other formulations in which the impact of MAX was less noticeable. A significant effect of storage time was observed only in control (P < 0.05), and in MAX‐3, where hardness increased significantly from 194 ± 1 to 217 ± 5 g. No significant changes were observed in the other formulations. Overall, the incorporation of MAX appeared to reduce the retrogradation tendency of starch, likely by interfering with the reassociation of amylose and amylopectin chains during storage, as previously reported for wheat AX. ¹⁰ The starch retrogradation process appears to be influenced differently depending on the molecular weight of AX. For instance, Yan et al. ⁸ reported that the degree of hardening of wheat starch gels decreased with increasing concentrations of low‐molecular‐weight wheat AX (280 kDa), while high‐molecular‐weight AX (754 kDa) led to greater hardening as its concentration increased. These findings align with the trend observed in the present study, where MAX (285 kDa) also reduced gel hardening.

Table 2.

Impact of different concentrations of MAX on maize gel texture during storage

Parameter	Storage time (h)	Control	MAX‐1	MAX‐3	MAX‐6	MAX‐9
Hardness (g)	0	144 ± 8aA	182 ± 4bA	194 ± 1bcA	221 ± 4cA	395 ± 19dA
	48	180 ± 8aB	205 ± 8aA	217 ± 5aB	242 ± 34aA	471 ± 61bA
Gumminess	0	108 ± 1aA	111 ± 12aA	112 ± 2aA	139 ± 8abA	215 ± 48bA
	48	110 ± 7aA	116 ± 5aA	141 ± 25aA	157 ± 24aA	281 ± 34bA
Chewiness (g)	0	99 ± 0aA	103 ± 11aA	103 ± 1aA	127 ± 9abA	160 ± 25bA
	48	102 ± 6aA	105 ± 4aA	127 ± 22aA	143 ± 23aA	272 ± 19bB
Resilience	0	0.21 ± 0.00aB	0.21 ± 0.04aA	0.18 ± 0.02aA	0.20 ± 0.03aA	0.41 ± 0.07bA
	48	0.16 ± 0.01aA	0.20 ± 0.03aA	0.19 ± 0.05aA	0.23 ± 0.02aA	0.61 ± 0.12aA

Values are expressed as mean ± standard deviation. Different lower‐case letters within the same row indicate statistically significant differences between formulations at the same storage time (P < 0.05). Different upper‐case letters within the same column indicate statistically significant differences between storage times (0 h and 48 h) for the same formulation (P < 0.05). Control: 100 g 100 g⁻¹ maize starch; MAX‐1: maize starch composite with 1 g 100 g⁻¹ maize arabinoxylans; MAX‐3: maize starch composite with 3 g 100 g⁻¹ maize arabinoxylans; MAX‐6: maize starch composite with 6 g 100 g⁻¹ maize arabinoxylans; MAX‐9: maize starch composite with 9 g 100 g⁻¹ maize arabinoxylans.

For gumminess, at 0 h, MAX‐9 was significantly higher than all other samples (P < 0.05), while the control, MAX‐1, and MAX‐3 showed no significant differences. Conversely, Ji et al. ²⁷ reported a significant decrease in gumminess with increasing inulin concentration in pea starch gels, highlighting that the impact of fiber type on gel texture may vary depending on the starch–fiber interaction. After 48 h, gumminess increased slightly in all formulations, although not significantly. MAX‐9 remained significantly higher than all other samples. No significant differences over storage time were detected within any formulation.

In the case of chewiness, at 0 h MAX‐9 was significantly higher than the control and MAX‐1 and MAX‐3, while MAX‐6 showed an intermediate value. In contrast, previous studies have shown that inulin reduces chewiness in starch gels by competing for water and weakening the gel network. ²⁷ At 48 h, chewiness values increased in all samples, but the differences between control (102 ± 6 g), MAX‐1 (105 ± 4 g), 3 g 100 g⁻¹ (127 ± 22 g), and 6 g 100 g⁻¹ (143 ± 23 g) were not statistically significant. In contrast, MAX‐9 (272 ± 19 g) was not only significantly higher than all others at 48 h but also showed a significant increase from its initial value of 160 ± 25 g, indicating further gel integrity over storage.

Regarding resilience, values at 0 h were similar across the control (0.21 ± 0.00), MAX‐1 (0.21 ± 0.04), MAX‐3 (0.18 ± 0.02), and MAX‐6 (0.20 ± 0.03). Only MAX‐9 (0.41 ± 0.07) was significantly higher (P < 0.05), suggesting that threshold concentration is required to elicit improvements in this parameter. After 48 h, resilience decreased significantly in control (0.16 ± 0.01), while all MAX‐enriched gels maintained values similar to those at 0 h. MAX‐9 (0.61 ± 0.12) continued to exhibit the highest resilience, although the increase over time was not statistically significant. The stabilization of resilience by MAX aligns with previous studies of non‐starch polysaccharides. These polysaccharides likely reinforce the gel network by forming additional crosslinks or physical entanglements with starch, as supported by previous studies. These interactions improve the gel's ability to recover from deformation and resist structural weakening during storage, thereby enhancing mechanical integrity, elasticity, and overall textural stability. ³⁸

Interesting Pearson correlations were found between textural outcomes and morphometric parameters. Hardness, chewiness, and resilience showed strong correlations (r = 0.92, 78, 84; P ≤ 0.05, respectively) with medium‐sized pores (1000–10 000 μm²). This pore range appeared to strike an optimal balance between matrix connectivity and wall thickness: pores were sufficiently large to accommodate deformation, which contributed to energy dissipation (chewiness) and elastic recovery (resilience), yet bounded by robust polysaccharide walls that conferred high resistance to compression (hardness). ³⁹

Principal component analysis

The PCA biplot (Fig. 4) illustrates the relationships between the different samples (control, MAX‐1, MAX‐3, MAX‐6, and MAX‐9) and the measured parameters. The first two principal components (PC1 and PC2) accounted for a total of 90.28% of the total variance in the data, with PC1 explaining 56.87% and PC2 explaining 33.41%. This high percentage indicates that the two‐dimensional plot provides a robust and reliable overview of the data structure.

Figure 4.

Principal component analysis biplot. Control: 100 g 100 g⁻¹ maize starch; MAX‐1: maize starch composite with 1 g 100 g⁻¹ maize arabinoxylans; MAX‐3: maize starch composite with 3 g 100 g⁻¹ maize arabinoxylans; MAX‐6: maize starch composite with 6 g 100 g⁻¹ maize arabinoxylans; MAX‐9: maize starch composite with 9 g 100 g⁻¹ maize arabinoxylans.

The score plot reveals a distinct separation of the samples along PC1, primarily driven by the concentration of added MAX. The control sample is located in the upper‐left quadrant (negative PC1, positive PC2). Samples with low MAX concentrations (MAX‐1 and MAX‐3) are positioned in the lower‐left quadrant (negative PC1, negative PC2). Conversely, samples with high MAX concentrations (MAX‐6 and MAX‐9) are found on the right‐hand side of the plot (positive PC1). This distribution clearly shows that the incorporation of MAX, especially at levels of 6 g 100 g⁻¹ and above, fundamentally changed the system's properties compared to the control and low‐concentration samples.

The loading plot, which indicates the contribution of each variable to the principal components, provides further insight. PC1 is positively correlated with textural attributes such as hardness, chewiness, resilience, and gumminess. It is also positively associated with setback viscosity, matrix coverage, OBC, and PND in the 1000–10 000 μm² range. In contrast, PC1 is negatively correlated with pasting properties like peak viscosity, final viscosity, trough viscosity, and breakdown, as well as WBC, porosity, and the smallest pore fraction (PND < 1000 μm²). PC2 separates the samples based on other characteristics. For instance, the control sample is characterized by high values for breakdown and WBC, which have strong positive loadings on PC2. In contrast, low MAX concentrations (MAX‐1 and MAX‐3) are associated with high porosity and a greater number of large pores (PND > 10 000 μm²), which have negative loadings on PC2.

Overall, the PCA reveals a concentration‐dependent effect of arabinoxylan addition. At high levels (≥6 g 100 g⁻¹), MAX acts as a structuring agent, significantly increasing the textural hardness and stability of the system while suppressing starch pasting properties. At low levels (1–3 g 100 g⁻¹), it appears to disrupt the native structure without providing substantial reinforcement, leading to increased porosity. Notably, similar concentration‐dependent transitions of MAX have been observed in bread dough systems, where a functional shift occurs at 1–2% MAX addition. ¹⁵ This supports the interpretation that MAX can exhibit qualitatively different behaviors depending on its concentration, even in simplified starch‐based systems. From a practical perspective, these findings suggest that the functional role of MAX is context‐ and concentration‐dependent: low levels may be used to modulate gel porosity or create softer textures, whereas higher levels can reinforce structure and improve stability, providing guidance for designing fiber‐enriched or texture‐optimized starch‐based foods, including gluten‐free formulations.

CONCLUSIONS

Incorporation of MAX into maize starch produced marked, concentration‐dependent alterations in hydration, pasting, textural, and microstructural properties. MAX addition (1–9 g 100 g⁻¹ w/w) significantly decreased WBC, while increasing OBC. RVA profiles revealed progressive suppression of peak, breakdown, and final viscosities with rising MAX levels, consistent with inhibited granule swelling, reduced amylose leaching, and attenuated short‐term retrogradation. TPA demonstrated that gels containing ≥6 g 100 g⁻¹ MAX exhibited significantly higher hardness, gumminess, chewiness, and resilience both immediately and after 48 h of cold storage, confirming MAX's role in reinforcing the three‐dimensional starch network and retarding retrogradation. SEM and quantitative morphometric profiling of freeze‐dried samples further indicated a transition from more open, ice‐templated matrices at low MAX concentrations (1–3 g 100 g⁻¹) to denser and more cohesive ice‐templated structures with thicker cell walls at higher inclusion levels (6–9 g 100 g⁻¹). The effects of MAX were clearly concentration‐dependent: low additions can be used to fine‐tune gel softness and cohesiveness, whereas higher additions strengthen network density while slowing starch chain reassociation, delaying retrogradation.

This work establishes a mechanistic foundation for tailoring starch–fiber composites with controlled viscosity development, minimized retrogradation, and enhanced structural stability, while acknowledging that the current findings are based on a single commercial MAX. Future studies should compare homologous series of AX from different botanical origins to generalize these observations. Further research should also explore MAX fractions across a wider molecular weight spectrum, evaluate long‐term thermal cycling behavior, and validate performance within complex food matrices. In addition, investigating MAX at levels below 1 g 100 g⁻¹ would be valuable, as results indicate a pronounced change at 1 g 100 g⁻¹, suggesting that intermediate concentrations may provide critical insights into the onset and progression of starch–MAX interactions. Crucially, sensory profiling and in vitro digestibility assessments will be essential to translate these functional characteristics into applications for starch‐based food products.

AUTHOR CONTRIBUTIONS

Nicola Gasparre: writing – original draft, validation, conceptualization, methodology, investigation, data curation, visualization. Fatma Boukid: writing – review and editing, conceptualization, validation, resources. Cristina M Rosell: writing – review and editing, validation, methodology, conceptualization, supervision, resources, funding acquisition.

CONFLICT OF INTEREST

The authors declare that there are no conflicts of interest. Author Fatma Boukid is currently employed by ClonBio Group Ltd. All other authors confirm that the research was carried out without any commercial or financial ties that could be perceived as a potential conflict of interest.

FUNDING INFORMATION

This study was funded by the NSERC Discovery Grant Program (RGPIN‐2023‐04289), the Canada Foundation for Innovation, and Research Manitoba.

DATA AVAILABILITY STATEMENT

Data will be made available on request.