# How natural variability of gluten and arabinoxylans drives wheat dough extensional properties

Laura Rezette, Guy Della Valle, Kamal Kansou, Laurent Chaunier, Sophie Le Gall, Luc Saulnier

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## To cite this version:

Laura Rezette, Guy Della Valle, Kamal Kansou, Laurent Chaunier, Sophie Le Gall, et al.. How natural variability of gluten and arabinoxylans drives wheat dough extensional properties. Food Hydrocolloids, 2025, 162, pp.111022. 10.1016/j.foodhyd.2024.111022. hal-05078696

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Submitted on 22 May 2025

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# How natural variability of gluten and arabinoxylans drives wheat dough extensional properties

Laura Rezette<sup>a,∗</sup>, Guy Della Valle<sup>a,∗</sup>, Kamal Kansou<sup>a,†</sup>, Laurent Chaunier<sup>a,‡</sup>, Sophie Le Gall<sup>a,b,§</sup>, Luc Saulnier<sup>a,||</sup>

## ARTICLE INFO

Keywords:

Dough rheology

Storage modulus

Lubricated squeezing flow

Consistency

Intrinsic viscosity

## ABSTRACT

This study investigates the influence of proteins and arabinoxylans contents of wheat grain on the dough extensional properties, critical determinants of bread quality. Thirty-seven wheat samples (37) were selected from an initial set of 150 wheats, according to technological criteria, including water absorption (WA), to assess the impact of natural variability of several protein and arabinoxylan (AX)-related features on dough behaviour. Dough were prepared at the hydration level determined by the WA Farinograph tests. TD-NMR results showed that, for all samples, the dough reached an optimal hydration state, reflected by a four-peak time distribution. Rheological tests were performed on dough samples at low deformation with Dynamic Mechanical Thermal Analysis (DMTA), and at large deformation, using Lubricated Squeezing Flow test (LSF). Results indicate that the maximum storage moduli E'max determined by DMTA, at temperature close to 70 °C, is primarily influenced by initial gluten network cross-linking. E'max decreased between 1.1 MPa and 0.6 MPa, with increasing wet gluten content from 17.2 to 40 g/100g. At large deformation, the extensional viscosity of all doughs followed a power law, from which was derived the consistency index K. Surprisingly, K increased from 11,100 to 22,200 Pa.s<sup>n</sup> when the intrinsic viscosity of water extractable arabinoxylans increased from 420 to 820 mL/g, n being the flow index of the dough. Results showed that the extensional viscosity is more closely affected by the AX characteristics than by protein characteristics. These results were interpreted in terms of supramolecular distribution of the gluten network and the entangled arabinoxylans in the liquid phase, and discussed for their possible impact on bread making for a wide range of wheats.

## 1. Introduction

Monitoring and understanding dough rheological behaviour is essential for wheat quality assessment. Wheat dough behaviour at mixing is traditionally characterised using a range of instruments such as alveographs or farinographs. Dough behaviour properties are also measured or observed for baking assays, such as the French bread-making test. The potential of wheat flour for baking is generally determined by combining information from these different empirical professional measurements, firmly rooted in traditional practices, which highlight the varying baking potential of different flours.

Bread dough rheology can be assessed through a wide range of tests, each designed to address specific aspects of its behaviour. These tests can be classified by the type of deformation applied, shear or extension, as well as by the nature of the controlled variable, be it stress or strain.

The temporal dimension plays also a crucial role, allowing for analyses in dynamic (oscillatory) or steady-state regimes. These various testing methods enable comprehensive characterisation of dough properties among different breadmaking operations and their overall impact on bread quality (Della Valle et al., 2022; Dobraszczyk & Morgenstern, 2003). Given their importance, a key question is how dough properties are influenced by the flour components.

Meerts et al. (2017) pointed out that the mechanisms affecting the gluten network and dough extensional properties are still not fully understood. They suggested that in extension, starch-starch and starch-gluten interactions, related to small strains, are affected by water content but not by mixing time, while gluten-gluten interactions, related to large strains with the gluten fully hydrated, are impacted by mixing time and less by water. However, simple systems composed of gluten and starch alone cannot exactly reproduce the rheological properties of

<footnote><sup>a</sup> INRAE, UR 1268, Biopolymers, Interactions & Assemblies (BIA), F-44316, Nantes, France</footnote>

<footnote><sup>b</sup> INRAE, PROBE Research Infrastructure, BIBS Facility, F-44316, Nantes, France</footnote>

<footnote>* Corresponding author.
E-mail address: guy.della-valle@inrae.fr (G. Della Valle).</footnote>
flour-based doughs, which indicates that other components also influ-
ence the rheology as highlighted by Uthayakumaran et al. (2002).
Pentosans, though minor constituents of the flour, are the primary
biopolymers of wheat endosperm cell walls, and are mainly composed of
arabinoxylans (AX). Despite their low concentration, pentosans have
been shown to significantly impact dough behaviour. Migliori and
Gabriele (2010) demonstrated that addition of pentosans was more
effective in increasing network strength under large deformation, than
under small deformation, in the viscoelastic domain. Meeus et al. (2021)
found that a strong hydrolysis of AX by xylanase addition, with a
decrease in insoluble components and an increase in soluble ones, led to
a slight decrease in the extensional viscosity of wheat flour dough.

In spite of valuable results, studies on the rheological properties of
wheat flour dough, generally focus on a limited number of flours and the
effect of specific ingredients, often by using recomposed, enriched or
defatted flours or by altering mixing conditions (Sun et al., 2023). These
studies often overlook the impact of natural variations of flour compo-
nents on dough rheological properties, especially at optimal hydration
levels, which more accurately reflect real breadmaking conditions.
While the importance of proteins in dough behaviour is well established,
their precise role and action mechanism in dough rheology remains a
subject of debate. This is probably because their properties depend on
other components such as fibres, which are cell wall components largely
composed of AX, whose interactions with gluten proteins are complex
(Zhou et al., 2021). Among fibres, arabinoxylans, which are minor
wheat components, can significantly impact dough technological prop-
erties, even at their natural variation in the wheat grain. Understanding
how the natural variability, in levels and characteristics, of these major
and minor components in French flours collectively influences dough
properties is essential for a comprehensive grasp of wheat flour func-
tionality in breadmaking.

This study aims to determine how the natural variation of proteins
and AX within wheat flours impacts dough rheological properties under
both small and large strains, especially in extension. Recently, we have
shown that AX along with proteins and damaged starch had a significant
impact on water absorption (WA) for a collection of 150 wheat samples,
for which proteins, lipids, damaged starch and arabinoxylans were
characterised (Rezette et al., 2025). The same collection was used in this
work, and since it was not feasible to perform rheological tests on all 150
samples, a subset was selected to represent significant differences in
protein and arabinoxylan contents. Dough rheological measurements
were carried out at low strain using Dynamic Mechanical Thermal
Analysis (DMTA) and at large strain using Lubricated Squeezing Flow
(LSF), ensuring a comprehensive understanding of how these compo-
nents influence dough extensional properties. In addition, TD-NMR
relaxometry was employed to determine dough hydration state during
the tests.

**2. Materials and methods**

2.1. Plant material

One hundred and fifty (150) wheat grain samples harvested in 2020 and 2021 were used for this work, covering a wide range of composition as detailed in *Rezette et al.* (2025). They were provided by Arvalis (F91-Boigneville), Limagrain (F63-Riom), and Axiane Meunerie (F35-Val d'Arnast). Flours were produced with the same experimental mill (MCKA, Bülher, Switzerland) and stored 20 days at room temperature before being frozen at -20 °C until use. The samples were unfrozen over night at room temperature prior to rheological analysis. Actually the 150 samples have been fully characterized in terms of composition and technological properties (*Rezette*, 2024; *Rezette et al.*, 2025). Methods used for these analyses have been described in detail by *Rezette et al.* (2025), and are briefly summarized here in section 2.2.

## 2.2. Flour composition and dough characterisation

High-Performance Size-Exclusion Chromatography (HPSEC) was used to characterise the proteins as described in a previous work (*Rezette et al.*, 2025) and following the procedure of Morel et al. (2000). It included the measurement of content in: protein (Prot), insoluble glutenin (GluI), soluble glutenin (GluS), and gliadin (Gli). The quality of the gluten network, including wet gluten (W.Gluten) and dry gluten (D. Gluten) was determined using a Glutomatic® device (PerkinElmer, USA, NF EN ISO 21415-2).

Polysaccharides characterisation was performed by Gas Liquid Chromatography (GLC) after acid hydrolysis based on Englyst and Cummings (1988)'s method. This method includes the measurement of soluble starch (SS), total arabinoxylans content (AX-TOT), water-extractable arabinoxylan content (WE-AX) and their respective arabinose to xylose ratio (A/X.TOT and A/X.WE). Additionally, the intrinsic and specific viscosity of water-extractable arabinoxylans (IV. AX and SV.AX, respectively) were analysed as described by *Rezette et al.*, 2025 with an HPSEC-system (OMNISEC RESOLVE-REVEAL - Malvern Panalytical- Malvern, UK) using a Viscotek AGuard precolumn (50 × 6 mm) and a Viscotek A4000 column (300 × 8 mm – Malvern Panalytical- Malvern, UK) maintained at 35 °C and eluted with 50 mM sodium nitrate at a flow rate of 0.7 mL/min.

Lipids were characterised as fatty acids, as previously described by
Rezette et al. (2025), using GLC after acid hydrolysis and trans-
methylation based on Welch (1977) method. Fatty acids content
measured included the contents of total palmitic acid C16 (C16.TOT),
total stearic acid C18 (C18.TOT), total vaccenic acid C18:1n-7 (C181n7.
TOT), total oleic acid C18:1n-9 c (C181n9.TOT), total linoleic acid
C18:2n-6 (C182n6.TOT) and total alpha-linolenic acid C183n-3
(C183n3.TOT).

The Hagberg falling number (HFN) was determined using a standard
protocol (Falling number 1500, ISO 3093:2009). Damaged starch (SD)
was measured by iodine absorption using an amperometric method
(Medcalf & Gilles, 1965) and expressed in Chopin Units corrected based
on protein and moisture content (UCDc; SDMatic; Chopin, France).

The elasticity index (Ie), a widely used quality criterion for assessing
wheat baking quality of wheat, especially its rheological properties, was
obtained using standard Alveograph® protocols (NF EN ISO 27971,
Chopin, France). It is used for selection purpose in this study.

2.3. *Sampling*

A subset of 37 wheat samples was selected from a total of 150 to
conduct a thorough rheological characterisation of the dough. The
protein content is known to play a predominant role on the water ab-
sorption (WA) and on dough rheology, reflected by the elasticity index
(Ie), measured from the Alveograph. Therefore, the selection process
considers these two aspects as follows.

- 8 samples with varying protein contents that followed a linear relationship between the protein content and Ie, were selected and referred to as P-selection;

- 14 samples with varying protein content that deviated from this linear relationship, were selected to highlight the impact of non-protein components on Ie. These samples are referred to as the PP-selection;

- 15 samples that exhibited variations in WA while maintaining a protein content close to the average value, were selected to include the influence of other components than proteins on WA. These samples are referred to as the PS-selection.

In addition, the classification of wheats according to their end use
was also provided. Hence, the selection included samples categorized for
breadmaking applications, and others for different uses, such as biscuit
applications, feed, or as wheat improvers.
## 2.4. Rheological characterisation

Dough was prepared by mixing flour with water and 2% salt using a Farinograph Brabender at a rotation speed of 80 rpm for a duration of 9 min, corresponding to a standard mixing time, and with hydration value (from 50.2 to 62.1% based on flour weight) determined by water absorption farinograph tests (Rezette et al., 2025).

### 2.4.1. Low deformations with dynamic mechanical thermal analysis (DMTA)

The dough thermomechanical behaviour was studied at low deformation using a Dynamic Thermo-Mechanical Analyser (DMA, MK IV, Rheometric Scientific, USA) in compression mode, with a deformation amplitude of 0.1% at a frequency of 1Hz, according to same method as described by Dufour et al. (2024). For this analysis, about 0.9 g of dough sample was taken from the initially prepared dough and left to rest in the absence of air at room temperature for 30 min. The piece of dough was then placed between two 17 mm diameter plates, separated by a gap $h_0$ = 3.2 mm. Silicone grease (SuperLube, Bohemia, NY, USA) was applied around the dough to prevent it from drying out during the analysis. A constant static force of $10^{-2}$ N, considered negligible to the modulus measured, was applied to the sample to maintain contact between the dough and the plates during the temperature rise. The dough was rested for 5 min before starting the analysis. The oven was closed over the sample and a heating rate of 3 °C/min was applied to increase the temperature from 22 °C to 120 °C.

Since the internal temperature of the dough (T) does not instantly equilibrate with the oven environment, it remained lower than the oven's set temperature ($T_{Oven}$). To account for this discrepancy, calibration was performed by simultaneously measuring T using a thermocouple and recording the corresponding $T_{Oven}$. T was then adjusted using the following correction equation:

$$T = 3.4*10^{-3}*T_{oven}^2 + 0.29*T + 13.2 \quad (1)$$

The storage modulus $E'$ and the viscous modulus $E''$ were measured during temperature rise and calculated using RSI Orchestrator software (Rheometric Scientific, USA), which monitored the system. For every sample, DMTA was performed on 3 pieces of dough from the same preparation.

### 2.4.2. Large deformations with Lubricated Squeezing Flow

The dough pieces (5 g) are shaped in lubricated Teflon™ moulds and the test is carried out at 3 compression rates as described in (Turbin-Orger et al., 2016).

Data was processed as described in (Launay & Michon, 2008; Van Vliet, 2008). The force F applied to the sample is recorded as a function of displacement ($H_0$ - H(t)), $H_0$ and H(t) being respectively the initial height and height at time t, of the sample. The stress $\sigma$ is obtained from F as follows:

$$\sigma = \frac{F}{S} \quad (2)$$

with S the surface area of the moving top plate ($\emptyset$ = 20 mm). The biaxial strain $\varepsilon_b$ is determined by:

$$\varepsilon_b = \frac{1}{2} \ln \left( \frac{H(t)}{H_0} \right) \quad (3)$$

Therefore, biaxial strain rates $\dot{\varepsilon}_b$ can be calculated for given strain values [0.1, 0.25, 0.5, 0.75, 1.0, 1.25]:

$$\dot{\varepsilon}_b = \frac{\nu}{2H(t)} \quad (4)$$

The slope of the curve representing $\ln(\sigma)$ as a function of $\varepsilon_b$, for a given $\dot{\varepsilon}_b$ value, defines the Strain Hardening Index (SHI). In this study, it is calculated for $\dot{\varepsilon}_b = 0.01 \text{ s}^{-1}$:

$$SHI = \left( \frac{dln\sigma}{d\varepsilon_b} \right)_{\dot{\varepsilon}_b=0.01 \text{ s}^{-1}} \quad (5)$$

Finally, for any constant strain value, bi-extensional viscosity $\eta_E$ is determined, by the Ostwald-de Waele power law as follows:

$$\eta_E = \frac{\sigma}{\dot{\varepsilon}_b} = K \dot{\varepsilon}_b^{n-1} \quad (6)$$

From equation (6), the consistency index K and the flow index n are derived for any value of biaxial strain $\varepsilon_b$. In this study, they will be calculated for $\varepsilon_b = 1$.

Measurements were repeated on four dough pieces coming from a same dough preparation, for each compression rate.

### 2.5. TD NMR relaxometry measurements

The TD NMR relaxometry measurements were conducted a Minispec (mq20, Bruker Biospin) following the procedure and signal treatment outlined by Dufour et al. (2023). Approximately 0.9 g of dough was introduced into a 10 mm diameter NMR tube and compressed to a height of approximately 10 mm. The tubes were sealed with a stopper to prevent moisture loss, and stored for 24 h at 4 °C, prior to analysis. The Carr-Purcell-Meilboom-Gill (CPMG) sequence was employed to determine the distribution of $T_2$ relaxation times and visualise the mobile protons assigned to water. While 2500 data points were acquired by taking only the paired echoes, 64 scans were performed to ensure a total acquisition time of 10 min instead of the 20 min, as reported by Dufour et al. (2023). These experiments focused on the PS-selection, as detailed in section 2.3., the preparation of doughs was the same as for rheological measurement (see 2.4). $T_2$ measurements were repeated on 5 dough pieces coming from a same dough preparation.

The total water content of the system was calculated from the initial water content of the flour and the water added for mixing. The precise water content of each sample was determined by dehydration (105 °C for 72 h) following NMR acquisition.

The relaxation signal obtained from the CPMG sequence was converted into a continuous distribution of $T_2$ relaxation components using an Inverse Laplace transformation (ILT) as described by Lahaye et al. (2018). This transformation was accomplished using a primal-dual interior method for convex objectives (PDCO) implemented in MATLAB® (MathWorks, Inc., Natick, MA, USA). Quantitative analysis of the continuous distribution was performed using a custom-developed MATLAB® routine.

This transformation produces a graphical representation of the $T_2$ relaxation time distribution in the form of distinct peaks. These peaks can then be analysed individually to obtain detailed information about the different proton populations in the sample: Relative peak area ($P_2$), peak width/dispersion (LW) and transverse relaxation time ($T_2$). Each peak corresponds to a specific proton population with distinct mobility characteristics.

### 2.6. Statistical analysis

The linear correlations between all the variables are analysed with hierarchical clustering and visualized by a heatmap, performed using R v4.1.3 with the heatmap function. The thresholds level of correlation are: p-value <0.05 ($|r| > 0.33$), p-value <0.01 ($|r| > 0.42$), and p-value <0.001 ($|r| > 0.52$). The average of replicates is used for the statistical analysis.

## 3. Results and discussion

### 3.1. Samples selection and correlation between variables

Samples selection was based on the variations of two dough technological properties, elasticity index (Ie) and water absorption (WA),
and their correlations with the protein content (Prot) as shown in Fig. 1A and B, respectively. The positive linear relations observed in both cases confirm the predominant effect of the protein content on these properties. However, the important scattering of the points along the regression line suggests that additional factors, distinct from protein content, also contribute to these properties. In Fig. 1A, the P-selection gather the samples for which the values of Ie align with the regression line, while the PP-selection includes the samples for which the Ie values deviate from the regression line, indicating a potential effect of other factors than protein content. These factors could be damaged starch, and also the ratio arabinose on xylose from total arabinoxylans (A/X.TOT), as shown in our recent results (Rezette, 2024). A total of 22 samples were selected in this way: 14 from PP-selection and 8 from P-selection.

Fig. 1B also displays a significant scattering of the points around the regression line that relate the protein content with WA. Is has been shown in a previous work (Rezette et al., 2025) that components, such as damaged starch and arabinoxylans, especially their specific viscosity

(SV.AX), have a significant effect on WA. In this case, the PS-selection consists of samples with similar protein contents (and close to the average) but distinct WA. Fifteen (15) samples were selected this way to capture the impact of non-protein components. To emphasize the effect of arabinoxylans over starch, the selected samples were chosen with a wide distribution of SV.AX values, as shown by results reported in Table 1.

As depicted in Fig. 1., the selection of 37 samples captures the variability of the initial sample set, particularly in terms of protein content, WA and Ie. The range of values for the different variables in the whole selection is reported in Table 1A. Table 1B presents the values for the PS-selection. In this selection, as expected, the range of protein content (Prot) is quite narrower compared to the total selection, while the ranges for WE-AX and SV.AX remain of the same amplitude. In addition, the numerical values for the composition and dough technological properties for these 37 samples have been reported in Table S0 (Supplementary material).

<figure><img src="image_5.png" /><figcaption>**Fig. 1.** Distribution of selected samples according to two dough characteristics: A) Elasticity index (Ie) versus protein content (Prot) (data from Rezette et al. (2025)), under review); B) Water Absorption (WA) versus Prot (data from Rezette et al. (2025)). The characteristics are the following: Selected samples ■ are characterised by a good prediction of Ie by Prot alone; Selected samples ■ are characterised by a poor prediction of Ie by Prot alone; Selected samples are ● characterised by variations in WA and tiny variation of Prot.</figcaption></figure>
<caption>**Table 1**</caption>

Value intervals of data from (A) the total selection of 37 samples (P-, PP- and PS-selections), and (B) the PS-selection of 15 samples alone.
Prot: Protein content; WE-AX: Water-Extractable Arabinoxylan content; SV-AX: Specific Viscosity of WE-AX; WA: Water Absorption; IE: Elasticity Index. PS-Selection: selection with constant protein content but varying WA.

<table><thead><tr><th colspan="8">Total selection:</th></tr><tr><th>A)</th><th>Prot</th><th>WE-AX</th><th>SV-AX</th><th>SS</th><th>SD</th><th>WA</th><th>Ie</th></tr></thead><tbody><tr><td>Unit</td><td>g/100 g</td><td>g/100 g</td><td>mV.mL</td><td>g/100 g</td><td>UCDc</td><td>%</td><td>%</td></tr><tr><td>Min-Max</td><td>6.1-14</td><td>0.30-0.86</td><td>204-754</td><td>1.2-6.2</td><td>12.1-23.9</td><td>50.9-62.1</td><td>32.8-72.3</td></tr><tr><td>Mean</td><td>9.4</td><td>0.50</td><td>424</td><td>3.3</td><td>17.6</td><td>56</td><td>54.3</td></tr><tr><td>CV (%)</td><td>15.6</td><td>28.6</td><td>34</td><td>31.4</td><td>15.2</td><td>5.2</td><td>16.5</td></tr><tr><th colspan="8">PS - selection:</th></tr><tr><th>B)</th><th>Prot</th><th>WE-AX</th><th>SV-AX</th><th>SS</th><th>SD</th><th>WA</th><th>Ie</th></tr><tr><td>Unit</td><td>g/100 g</td><td>g/100 g</td><td>mV.mL</td><td>g/100 g</td><td>UCDc</td><td>%</td><td>%</td></tr><tr><td>Min-Max</td><td>8.9-10.4</td><td>0.30-0.86</td><td>229-754</td><td>2.9-3.9</td><td>13.4-23.9</td><td>52.5-58.5</td><td>44.3-65.3</td></tr><tr><td>Mean</td><td>9.5</td><td>0.54</td><td>435</td><td>3.4</td><td>17.5</td><td>55.6</td><td>55.7</td></tr><tr><td>CV (%)</td><td>4.4</td><td>33.5</td><td>40</td><td>11.1</td><td>15.7</td><td>3.2</td><td>10.5</td></tr></tbody></table>

The correlations amongst the composition and rheological variables are reported by the heatmap; the dendrogram at the top represents the hierarchical clustering (Fig. 2). Two groups may be identified.

- the group on the left of the heatmap includes a first set of variables related to soluble arabinoxylans (WEAX, SV-AX, and IV-AX) and consistency (K), a second set with the minimum and maximum modulus values (E'min and E'max), a third set with the corresponding temperatures at which these moduli are observed (T°E'min and T°E'max) along with the flow index (n), and finally the total amount of arabinoxylans (AXTOT), which is isolated from the other variables;

- the group on the right of the heatmap includes a set of variables related to water absorption (WA), damaged starch (SD and SS), and all lipid-related variables, except for C18.TOT, which remains more isolated, and a set with the arabinose-to-xylose ratios (A/X.WE and A/X.TOT), and most protein-related variables (Prot, Gli GluS, W. Gluten and D.Gluten), except for the insoluble glutenins (GluI), which stands apart, associated with the elasticity index (Ie), the Hagberg Falling Number (HFN), the Strain Hardening Index (SHI), and the modulus ratio (E'max/E'min).

The map reveals some significant correlations (p-value<0.001) between the rheological measurements and composition variables. Notably, a correlation is observed between IV-AX and consistency K (r = 0.67) in the left cluster. Additionally, proteins (W.Gluten, Prot, Gli and GluS) show negative correlations with E'max (r = -0.69, -0.62, -0.70 and -0.63 respectively), and, to a lesser extent, with E'min (r = -0.6, -0.62, -0.66, -0.55) in the right cluster.

## 3.2. Variations of viscoelastic moduli with temperature

The thermo-viscoelastic behaviour of dough prepared from the selected flour was studied by Dynamic Mechanical Thermal Analysis (DMTA) by measuring the variations of storage modulus E' during temperature rise. A summary of results from DMTA measurements is presented in Table 2. Complete numerical results are available in supplementary data (S1). In the present study, the values of storage modulus E' were consistently found to be larger than those of dissipative modulus E", confirming that, over the interval of temperature investigated, wheat flour dough behaved more like a solid rather than a fluid. Fig. 3 displays two typical thermograms, where the storage modulus E' decreases from its initial value at ambient temperature to a minimum value (E'min) around 45 °C, before sharply rising to a maximum value (E'max) around 70 °C, and then dropping steeply thereafter. Notably, Fig. 3 reports the thermograms with the highest (1125 kPa) and lowest (610 kPa) E'max values over the whole selection of samples. They were obtained from flours characterised respectively by a low protein content

(6.1 g/100 g of flour), referred to as LPF, and a high protein content (10.4 g/100 g of flour), referred to as HPF. This result is in accordance with the negative correlation found between Prot and E'max (r = -0.62). Actually, the increase of E' between 45 and 70 °C, has been primarily attributed to gluten cross-linking and secondly to starch granules swelling (Rouillé et al., 2010). So, this difference of E'max values suggests that the gluten network, just after mixing, was tighter for sample HPF than for sample LPF; consequently, crosslinking and starch granule swelling were less important upon heating.

The relatively small temperature variation observed at minimum and maximum storage modulus for the whole sampling (T°E'min and T°E'max; Coefficient of Variation CV% = 2.2% and 5.5% respectively, Table 2) is in line with results reported in previous works (Dufour et al., 2024; Rouillé et al., 2010). These small variations suggest that the differences of flour composition do not induce significant structural changes other than gluten cross-linking and starch granule swelling. Nonetheless, the amplitude of these structural changes varies, as reflected by the variations of minima and maxima values of storage modulus (E'min and E'max, CV% = 14.3 and 14.8% respectively).

These changes are usually evaluated by calculating the ratio of maximum to minimum modulus E'max/E'min. Its value varied between 7.2 and 14, in a narrower interval than the one found by Shehzad et al. (2012) (10–35, for 24 different mixing conditions), or by Dufour et al. (2024) (3.8–25.6, for 4 different flours, 5 different moisture contents and mixing conditions) but closer to the values interval found by Angioloni and Dalla Rosa (2005) (8–10, varying salt concentration, speed and mixing time).

## 3.3. Extensional behaviour

Large strain measurements were performed using Lubricated Squeezing Flow test (LSF). For all dough samples, the variations of the extensional viscosity with the strain rate were found to follow a power law (eq. (6)), at fixed strain, as illustrated by typical flow curves in Fig. 4. The power law provides a convenient way to represent deformation of dough samples during the various stages of breadmaking. As illustrated in Fig. 4, the value $\dot{e}_b = 0.01 \text{ s}^{-1}$ is the order of magnitude of internal dough strain rate during fermentation, where extensional properties are the force which constrains the growth of gas bubbles in the dough, while higher values of strain rate ($>1.10^{-1} \text{ s}^{-1}$) are more typically observed/generated during mixing and shaping operations (Amemiya & Menjivar, 1992; Della Valle et al., 2014).

Strain hardening index (SHI) was determined for a fixed strain rate, $\dot{e}_b = 0.01 \text{ s}^{-1}$ (eq. (5)), and together with the consistency (K) and the flow indices (n), derived from the power law, these three indices account for the extensional behaviour of wheat flour dough. A summary of the variations of these indices for the 37 selected samples is presented on Table 2. Complete data is provided in supplementary data (S1).
<figure><img src="image_6.png" /></figure>

(caption on next page)
**Fig. 2.** Heatmap made on the 37 selected samples. Significance Thresholds: p-value <0.05 (|r| > 0.33), p-value <0.01 (|r| > 0.42), and p-value <0.001 (|r| > 0.52). WEAX: Water-Extractable Arabinoxylan content; SV.AX: Specific Viscosity of WEAX; IV.AX: Intrinsic Viscosity of WEAX; K: Consistency index for biaxial strain εb = 1; E'min: Minimum value of storage modulus; E'max: Maximum value of storage modulus; T°E'min: Temperature at E'min; n: Flow index for biaxial strain εb = 1; T°E'max: Temperature at E'max; AXTOT: Total Arabinoxylan content; A.X.WE: Arabinose to Xylose ratio from WEAX; A.X.TOT: Arabinose to Xylose ratio from AXTOT; Prot: Protein content; Gli: Gliadin content; GluS: Soluble Glutenin content; W.Gluten: Wet Gluten; D.Gluten: Dry Gluten; Glul: Insoluble Glutenin Content; Ie: Elasticity Index; HFN: Hagberg Falling Number; SHI: Strain Hardening Index for strain rate εb = 0.01 s⁻¹; E'max/E'min: E'max on E'min ratio; SS: Soluble Starch; C16.TOT: Total palmitic acid C16 content; C18n7.TOT: Total vaccenic acid C18:1n-7 content; C18n9.TOT: Total oleic acid C18:1n-9 content; C182n6.TOT: Total linoleic acid C18:2n-6 content; C183n3.TOT: Total alpha-linolenic acid C18:3n-3 content; SD: Damaged starch measured by iodine absorption; C18.TOT: Total stearic acid C18 content.

<caption>**Table 2**</caption>

Results from Dynamic Thermo-Mechanical Analysis (DMTA) and Lubricated Squeezing Flow (LSF) measurements on the 37 selected samples. E'min: Minimum value of storage modulus; E'max: Maximum value of storage modulus; E'max/E'min: E'max on E'min ratio; T°E'min: Temperature at E'min; T°E'max: Temperature at E'max; SHI: Strain Hardening Index for strain rate εb = 0.01 s⁻¹; K: Consistency index for biaxial strain εb = 1; n: Flow index for biaxial strain εb = 1.

<table><thead><tr><th></th><th>E'min</th><th>E'max</th><th>E'max/E'min</th><th>T°E'min</th><th>T°E'max</th><th>SHI</th><th>K</th><th>n</th></tr></thead><tbody><tr><td>Unit</td><td>kPa</td><td>kPa</td><td>/</td><td>°C</td><td>°C</td><td>Pa</td><td>kPa.s<sup>n</sup></td><td>/</td></tr><tr><td>Min-Max</td><td>51-141</td><td>618-1125</td><td>7.2-14.0</td><td>40-49</td><td>67-74</td><td>1.45-2.07</td><td>11.1-22.2</td><td>0.23-0.42</td></tr><tr><td>Mean</td><td>86</td><td>847</td><td>10.3</td><td>44</td><td>71</td><td>1.72</td><td>16.7</td><td>0.32</td></tr><tr><td>CV (%)</td><td>14.3</td><td>14.8</td><td>18.5</td><td>5.5</td><td>2.2</td><td>8.2</td><td>18.1</td><td>11.4</td></tr></tbody></table>

<figure><img src="image_7.png" /><figcaption>**Fig. 3.** Typical variations of storage modulus E' as a function of dough temperature determined by DMTA for the two flours having the highest and the lowest maximum storage modulus (E'max) values respectively corresponding to a Low-Protein Flour (LPF) and a High-protein Flour (HPF).</figcaption></figure>

Among these three indices, the consistency values (K) exhibited the highest variations, ranging from 11, 100 Pa.sⁿ to 22,200 Pa.sⁿ. These values, for εb = 1, are of the same order of magnitude as those reported by Turbin-Orger et al. (2016) who found K values between 5 and 18.6 kPa.sⁿ for doughs prepared under different mixing conditions or formulations. They were lower than those reported by Dufour et al. (2024) who reported K values up to 40 kPa.sⁿ, for doughs subjected to three mixing times and three hydration levels (under-hydrated, optimally-hydrated and over-hydrated). For Dufour et al. (2024) the significant variation in water content was by far the main factor influencing K, while considering only dough optimally hydrated, regardless of the mixing conditions and type of flour, K ranged between 14 and 25 kPa.sⁿ, an interval similar to the one observed in the present study (Table 2). Regarding the flow index (n), the range of values (0.23–0.42) is below 1, reflecting a strain rate-thinning behaviour of all the tested doughs, similar to those found by Dufour et al. (2024) (0.27–0.48), and narrower compared to those reported by Turbin-Orger et al. (2016) (0.3–0.6). Finally, the strain hardening index (SHI) exhibited the smallest variations, with a range of values (1.45–2.07), slightly narrower than that reported by Turbin-Orger et al. (2016) (1.2–2) or Dufour et al. (2024) (1.5–2.7). The comparison of these results suggests that the

<figure><img src="image_8.png" /><figcaption>**Fig. 4.** Extensional viscosity as function of biaxial strain rate εb for a biaxial strain of εb = 1 for: (a) the two flours with the lowest and highest protein content (resp. LPF and HPF) and, (b) the two flours with the most distinct curves and with low and high AX intrinsic viscosities (resp. L-IV.AX and H-IV. AX). Colours shading indicate strain rate value experienced by the dough during breadmaking process. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)</figcaption></figure>

variations of extensional behaviour of dough, resulting from a wide range of wheat grain composition, are of the same order of magnitude than those obtained when changing formulation and processing conditions for a single wheat flour.

In contrast to DMTA results (section 3.2), which showed that the rheological behaviour at low deformation is primarily influenced by proteins, the LSF results indicated a lower impact of protein content. Indeed, while HPF and LPF presented distinct curves illustrated with dashed line in Fig. 4, the most distinct curves were observed in samples with markedly different intrinsic viscosities of arabinoxylans (IV.AX) (4.2 dL/g vs 8.2 dL/g). The sample with high IV.AX (H-IV.AX) presented higher extensional viscosity compared with the sample with low IV.AX (L-IV.AX). These results illustrate the correlation between K and IV.AX already pointed out from the heatmap (r = 0.67, see section 3.1 and Fig. 2). Conversely, doughs made from flours with extreme IV.AX values did not exhibit significant differences in E' values (see S2).

This result aligns with Migliori and Gabriele (2010), who noted that pentosans (and thus mainly AX) effects on the dough were more pronounced at large deformations than at small deformations. Arufe et al.
(2017) also showed the same general trend with dough supplemented with a mix of soluble dietary fibres. Meeus et al. (2021) reported a decrease of about 20% in extensional viscosity with increasing levels of soluble arabinoxylans achieved through xylanase addition. This discrepancy with the present study may be attributed to the fact that xylanase treatment also reduces the insoluble fraction of AX, and this fraction is, like for insoluble fibres, known to increase extensional viscosity. The decrease of insoluble AX would then balance the potential increase of viscosity due to the rise of soluble AX, resulting in a moderate effect compared to the one observed in the present study.

### 3.4. Dough hydration state

To determine whether AX can impact water mobility in the dough, TD-NMR relaxometry measurements were performed on PS-selection, which presents a narrow range of protein content (Table 1b). TD-NMR measurements allowed to identify different populations of water pro- tons based on their mobility.

All samples of the PS-selection exhibited the same T₂ distribution, characterised by four peaks A, B, C and D, as illustrated in Fig. 5. In biological samples there is no simple relationships between T₂ compo- nents and specific morphological compartments or constituents (Lahaye et al., 2015). Each T₂ peak can be assigned to a water population at a given mobility, corresponding to specific molecular environment. It is characterised by its relative peak area (P₂), peak width/dispersion (LW), and transverse relaxation time (T₂). The parameters associated with each of the peaks varied between samples, but without any significant correlation with flour composition (for all numerical values, see S3). Peak A, with a relaxation time domain (T₂) of less than 1 ms and peak B with a T₂ between 2 and 5 ms, are associated with the populations of water most tightly bound to macromolecular components of the sample. Peak C, with a T₂ ranging from 6 to 40 ms, and peak D, with a T₂ ranging from 40 to 60 ms, correspond to water populations that are less tightly bound and are more likely to be found in microporosities (Barron et al., 2021; Parenti et al., 2021).

This four-peak distribution is typical of dough in an optimal hydra- tion state, as previously identified by (Dufour et al., 2023), and char- acterised by a well-structured and compact gluten network with many thin protein strands (Dufour et al., 2024). Since a four-peak distribution is observed in all wheat flour doughs from the PS-selection, it can be concluded that the doughs were optimally prepared with respect to hydration and mixing time. While all flours tested, in PS collection, had protein contents close to 9.5%, their WEAX content and SVAX levels varied (Table 1). This result indicates that changes in water-extractable AX did not affect the number of water populations neither the distri- bution of relaxation time. Consequently, the hydration state of the

gluten network is not changed, even though water-unextractable ara- binoxylans (WU-AX, i.e. insoluble fibres) have been reported to interact with gluten proteins (Zhou et al., 2021) or to change its structure (Nawrocka et al., 2018). Dufour et al. (2023) indicated that hydration level, especially when deviating from the optimum value, is the most impactful factor. Therefore, difference of protein content alone would likely not affect the number of peaks in the distribution. This assumption was confirmed by testing TD-NMR relaxometry measurements on two additional samples (see S3) having the highest and the lowest protein content (14 and 6.1% respectively), who displayed the same distribution of relaxation time, characterised by four peaks, i.e. typical of a gluten network with optimal hydration state.

### 3.5. Effects of gluten network structuring and starch gelatinization on low strain dough rheological behaviour

The variations of the storage modulus E' with rising temperatures has been predominantly attributed to gluten cross-linking (Rouillé et al., 2010), and, to a lesser extent, to the gelatinization of starch granules. The swelling of starch granules is influenced by the structuring of the gluten, as the gluten network limits the swelling of the granules, while the two biopolymers compete for water (Rolee & LeMeste, 1999). To analyse E' variations, the ratio E'max/E'min is often considered as an important indicator (Dufour et al., 2024; Turbin-Orger et al., 2016). In these studies, E'max/E'min is used to emphasize the influence of the temperature in cross linking the gluten network, suggesting that the ratio E'max/E'min is inversely related to the initial level of gluten network structuring. However, this usual interpretation does not hold in the present case, as no relation has been found between E'max/E'min and a variable reflecting gluten network such as W.Gluten, Gli, GluS or Prot. Moreover, in the present work, no significant correlation was found between this ratio, and the technological parameters or the composition (Fig. 2). This result can be attributed to the fact that these two previous studies were conducted on a limited number of flours with varying formulations and/or processing conditions. In contrast, this study examines a broad spectrum of grain and flour compositions, with dough under optimal hydration, in order to provide a more compre- hensive and specific evaluation of the effect of protein and arabinoxylans.

Interestingly, the modules themselves (E'max and E'min), exhibited more significant relationships with protein-related variables (W.Gluten, Gli, GluS or Prot, which are all correlated) than their ratio E'max/E'min as indicated the heatmap (Fig.2). Both E'max and E'min displayed large negative correlations with the protein content (Prot) ($r = -0.62$ for both) in contrast to the weaker positive correlation of Prot with E'max/ E'min ($r = 0.35$). Similar patterns are observed for other protein and gluten-related variables, such as Gli, GluS and W.Gluten. Notably, the maximum storage modulus (E'max) clearly depends on the amount of Wet Gluten (W.Gluten) or Gliadin content (Gli), with an inverse rela- tionship ($R^2 = 0.5$ or $R^2 = 0.51$ respectively), as illustrated in Fig.6. W. Gluten measures the combined weight of the gluten and the water it entraps, providing insight into the mixing capacity of the flour. A higher W.Gluten indicates greater water absorption (WA). Indeed, E'max showed a great negative correlation with water absorption (WA) ($r = -0.65$) while E'max/E'min displayed no correlation with WA ($r = 0.01$). This relationship aligns with the relationship between E'max and W. Gluten (Fig.6). It reflects the significant role of proteins in water ab- sorption (Dexter et al., 1994; Greer & Stewart, 1959; Tara et al., 1972). The primarily role of proteins in WA has been ascertained for this sample collection (Rezette et al., 2025) closely followed by damaged starch. This would explain why damaged starch, as shown by the heatmap (Fig. 2), also shares a relationship with E'max ($r = -0.48$). The strong correlation between protein content and W.Gluten ($r = 0.82$) coupled with NMR results, reflecting a gluten network optimally hydrated, for all samples, provides compelling evidence for the structural evolution of the gluten network. As protein content and hydration increases, the

<figure><img src="image_9.png" /><figcaption>**Fig. 5.** Typical TD NMR T2 distributions of wheat flour dough for three different samples of the PS collection. The x axis is the logarithmic scale of the relaxation time T2. The y axis corresponds to the distribution amplitude expressed in absolute water content (% w/w).</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Fig. 6.** Variations of maximum storage modulus (E'max) with Wet Gluten (W. Gluten), and, in the insert, comparative evolution with water absorption (WA); dotted line represents the best fitting by least squares regression: E'max = 564,82*(W.Gluten)²−50326*(W.Gluten) + 2E+06. As suggested by the two pieces of sketch, the gluten network became tighter with the protein and water content increase.</figcaption></figure>

gluten network becomes more structured and tighter as depicted in the sketches in Fig. 6, which, finally negatively impacts E'max.

Consequently, higher E'max values suggest that, a gluten network initially less structured (i.e low W.Gluten), offers more available water and less resistance for the swelling of starch granules during heating. The latter mechanism is enhanced by the higher water adsorption capacity of gluten compared to starch, which hinders wheat starch hydrothermal changes, as shown by Rakhshi et al. (2024) on starch-gluten model systems, of similar hydration level as wheat flour dough. This interpretation is in line with the results obtained, in the shear mode, by (Jekle et al., 2016), also on starch-gluten model systems, showing that the addition of gluten increased the solid character of the dough (G''/G' = tan δ decreases) while G*max decreased. The minimum storage modulus (E'min) also showed similar correlations as E'max, with Prot (r = −0.62) and Gli (r = −0.66) but their interpretation is tricky because E'min values are obtained for low values of stress, close to the sensitivity limits of the DMTA equipment.

Finally, these results confirm the significant role of initial structuring of the gluten network, either in limiting starch granule swelling or gluten cross-linking, as the temperature increases. Therefore, E'max is somehow an indicator of gluten network development and structure. It reflects the complex interplay between protein, starch, and dough hydration, and provides crucial insights into the rheological properties of dough within the optimal hydration interval. Low-strain properties, i.e. in linear viscoelastic domain, enhancing the solid behaviour of dough, are governed by the gluten network, which explains the observed impact of W.Gluten.

### 3.6. Effect of arabinoxylans on large strain dough rheological behaviour

Unlike the moduli, measured at low strain, there was no significant correlation between the consistency index K and the protein content. However, K presents a correlation with the intrinsic viscosity of water extractable arabinoxylans, IV.AX (Fig.7, R² = 0.47). Note that this relation is enhanced when considering only the 25 wheat samples intended for breadmaking (R² = 0.60), which is of importance for practical applications. In addition, the range of K values is independent of the wheat samples selection (PS or PP). When considering only the P and PP-selection from flours classified for breadmaking, the relation between K and IV.AX remains (R² = 0.67, data not shown), suggesting that it is independent of the protein content. These results underscore the significant role of AX in determining dough extensional properties.

In contrast with low strain tests, large strain tests primarily engage

the viscous properties of the dough matrix, which are involved during dough processing and reveal its liquid-like behaviour. The consistency index, K, provides an index of extensional viscosity, and the intrinsic viscosity is related to the AX chain-length distribution (Dervilly-Pinel et al., 2001). So, the relationship between K and the intrinsic viscosity of arabinoxylans (IV.AX) can be explained by the presence of larger AX molecules (high IV-AX), which are more prone to entangle. These molecular features concur to increase the viscosity of the liquid phase embedding the gluten network and therefore, they would contribute to an additional resistance to deformation and, consequently an increase in the overall consistency of the dough. The involvement of soluble arabinoxylans properties in this liquid phase supports previous hypotheses. Calculations by Neukom et al. (1967) suggested that the concentration of arabinoxylans in the available water within the dough is such that they would form a soft gel rather than a viscous solution, inevitably contributing to the consistency of the dough (Neukom, H., T. Geissmann, and T. J. Painter: Bakers Digest 41 (1967); cited in McCleary et al. (1986)) (see Fig. 7).

In addition, NMR results showed that changes of IV.AX did not modify water proton mobility, hence dough hydration state (see section 3.4). So, the correlation between IV.AX and K suggests that dough extensional viscosity is mainly influenced by the environment of the gluten-starch matrix. This environment may be envisioned as the aqueous fraction between the gluten strands, and it has been studied through dough liquor analysis for its role in bubble growth and film stability during dough fermentation (Janssen et al., 2020; Min et al., 2020; Turbin-Orger et al., 2015). These studies have shown that this fraction exhibits a flow behaviour characteristic of a polysaccharide-protein mixture, whose surface tension is determined by lipid and soluble protein contents, whereas its bulk viscosity is governed by the polysaccharides molecular weight. An attempt to summarise such complex structure and interactions is proposed in a diagram in Fig. 8, representing the medium in which the properties of soluble arabinoxylans manifest at dough scale. Our results suggest that higher molecular weight arabinoxylans increase entanglements and coverage of the gluten-starch interface, as illustrated in Fig. 8. These findings provide valuable insights into the complex interplay between gluten network and soluble polysaccharides, parts of dietary fibres (Zhou et al., 2021). They can better explain the effect of soluble fibres on dough rheological behaviour, in breadmaking applications (Arufe et al., 2017).

<figure><img src="image_11.png" /><figcaption>**Fig. 7.** Variations of consistency index K, derived from extensional viscosity, with the intrinsic viscosity of water-extractable arabinoxylans IV.AX, for breadmaking flours (full forms ○■) and flour for other uses (empty forms □) with distinction between P and PP-selection (□○) and PS-selection (■). Fitting by least squares regression has been performed only for breadmaking flour samples (K = −379,79*(IV.AX)² + 6977,6*(IV.AX) − 11158).</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>**Fig. 8.** Schematic interpretation of the macro-distribution of various components in bread dough.</figcaption></figure>

## 4. Conclusion

This study offers insights into the complex interplay between proteins and arabinoxylans in determining wheat dough rheological properties. Doughs were mixed at optimum hydration state, as checked by TD-NMR results. The study selected 37 wheat flour samples from a pool of 150 to explore the impact of a broad range of arabinoxylan and protein contents and features, reflecting the typical variation expected across different harvests and cultivars.

At low deformations, as expected, dough behaviour is primarily influenced by gluten network development. The inverse relationship between maximum storage modulus and wet gluten content suggests that a more developed gluten network offers less available water and more resistance to starch granule swelling upon heating. At large deformations, the influence of arabinoxylan properties, particularly their intrinsic viscosity, on dough extensional viscosity, prevails. Indeed, the consistency of the dough was found to increase with arabinoxylan intrinsic viscosity. This last result is reported for the first time, and it underlines the role of a minor component, the arabinoxylans, in dough rheology. Our findings highlight the differential impacts of these components on dough behaviour at low and large deformations, which are critical for various stages of the breadmaking process. They also contribute to provide professional, breeders and bakers, with new criteria to handle wheat variability and assess its technological quality.

### CRediT authorship contribution statement

**Laura Rezette:** Writing – original draft, Visualization, Validation, Methodology, Investigation, Formal analysis, Conceptualization.
**Guy Della Valle:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Investigation, Formal analysis, Conceptualization.
**Kamal Kansou:** Writing – review & editing, Supervision, Methodology, Formal analysis.
**Laurent Chaunier:** Writing – review & editing, Validation, Methodology.
**Sophie Le Gall:** Writing – review & editing, Validation, Supervision, Methodology.
**Luc Saulnier:** Writing – review & editing, Validation, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization.

### Declaration of competing interest

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

## Acknowledgments

We extend our sincere gratitude to the numerous individuals who contributed their expertise to this research: to Marion Didier and Michelle Viau for their invaluable assistance in devising the lipid analysis protocol and for their enriching contribution to advancing knowledge in this field. We would also like to thank Marie-Hélène Morel (UMR 1208 IATE, Univ Montpellier, INRAE, L'Institut-Agro Montpellier, F-34060 Montpellier, France) for producing and sharing the protein data, Benoît Méléard (Arvalis, Institut du végétal, F-91720 Boigneville, France) for the alveograph measurements, Laurent Linossier (Limagrain Céréales Ingrédients F-63200 RIOM, France) for water absorption and Baptiste Chambrey (Axiane Meunerie, F-35330 Val d'Anast, France) for the damaged starch measured by iodine absorption and for the gluten measurements. The authors would like to thank also Pascale Millart and Bérengère Marais (INRAE, UR 1268, Biopolymers, Interactions & Assemblies, F-44316 Nantes, France) for their support with biochemical analyses. Special thanks go to Denis Lourdin for his guidance on DMTA usage, and to Loïc Foucat and Catherine Deborde for their assistance with TD-NMR analyses. The collective expertise of these individuals has been instrumental in the success of this study.

This work is part of the Evagrain project. EVAGRAIN is funded by the French National Research Agency and coordinated by the INRAE research unit BIA. The authors thanks everyone from the 10 academic and private partners who collected a dataset on the 150 wheat samples.

Part of the work was realized on the INRAE-BIA BIBS instrumental platform (http://www.bibs.inrae.fr/, UR1268 BIA, IBiSA, Biogenouest, Phenome-Emphasis-FR ANR-11-INBS0012, PROBE and CALIS French Research infrastructures).

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.foodhyd.2024.111022.

### Data availability

Data will be made available on request.

### References

Amemiya, J. I., & Menjivar, J. A. (1992). Comparison of small and large deformation measurements to characterize the rheology of wheat flour doughs. In *Rheology of foods* (Vol. 16). ELSEVIER SCIENCE PUBLISHERS LTD. https://doi.org/10.1016/b978-1-85166-877-9.50011-0

Angioloni, A., & Dalla Rosa, M. (2005). Dough thermo-mechanical properties: Influence of sodium chloride, mixing time and equipment. *Journal of Cereal Science, 41*, 327–331. https://doi.org/10.1016/j.jcs.2004.10.004

Arufe, S., Chiron, H., Doré, J., Savary-Auzeloux, I., Saulnier, L., & Della Valle, G. (2017). Processing & rheological properties of wheat flour dough and bread containing high levels of soluble dietary fibres blends. *Food Research International, 97*, 123–132. https://doi.org/10.1016/j.foodres.2017.03.040

Barron, C., Devaux, M.-F., Foucat, L., Falourd, X., Looten, R., Joseph-Aime, M., ... Guillon, F. (2021). Enzymatic degradation of maize shoots: Monitoring of chemical and physical changes reveals different saccharification behaviors. *Biotechnology for Biofuels, 14*(1), 1. https://doi.org/10.1186/s13068-020-01854-1

Della Valle, G., Chiron, H., Cicerelli, L., Kansou, K., Katina, K., Ndiaye, A., Whitworth, M., & Poutanen, K. (2014). Basic knowledge models for the design of bread texture. *Trends in Food Science and Technology, 36*(1), 5–14. https://doi.org/10.1016/j.tifs.2014.01.003

Della Valle, G., Dufour, M., Hugon, F., Chiron, H., Saulnier, L., & Kansou, K. (2022). Rheology of wheat flour dough at mixing. *Issue “Food Physics & Material Science”. Current Opinion in Food Science, 47*, Article 100873. https://doi.org/10.1016/j.cofs.2022.100873

Dervilly-Pinel, G., Thibault, J. F., & Saulnier, L. (2001). Experimental evidence for a semi-flexible conformation for arabinoxylans. *Carbohydrate Research, 330*(3), 365–372. https://doi.org/10.1016/S0008-6215(00)00300-1

Dexter, J. E., Preston, K. R., Martin, D. G., & Gander, E. J. (1994). The effects of protein content and starch damage on the physical dough properties and bread-making quality of Canadian durum wheat. *Journal of Cereal Science, 20*(2), 139–151. https://doi.org/10.1006/jcrs.1994.1054
Dobraszczyk, B. J., & Morgenstern, M. P. (2003). Review: Rheology and the breadmaking process. *Journal of Cereal Science*, **38**, 229-245. https://doi.org/10.1016/S0733-5210(03)00059-5

Dufour, M., Chaunier, L., Lourdin, D., Réguerre, A.-L., Hugon, F., Dugué, A., Kansou, K., Saulnier, L., & Della Valle, G. (2024). Unravelling the relationships between wheat dough extensional properties, gluten network and water distribution. *Food Hydrocolloids*, **146**, Article 109214. https://doi.org/10.1016/j.foodhyd.2023.109214

Dufour, M., Foucat, L., Hugon, F., Dugué, A., Chiron, H., Della Valle, G., Kansou, K., & Saulnier, L. (2023). Water mobility and microstructure of gluten network during dough mixing using TD NMR. *Food Chemistry*, **409**(December 2022). https://doi.org/10.1016/j.foodchem.2022.135329

Englyst, H. N., & Cummings, J. H. (1988). Improved method for measurement of dietary fiber as non-starch polysaccharides in plant foods. *Journal - Association of Official Analytical Chemists*, **71**(4), 808-814. https://doi.org/10.1093/jaoac/71.4.808

Greer, E. N., & Stewart, B. A. (1959). The water absorption of wheat flour: Relative effects of protein and starch. *Journal of the Science of Food and Agriculture*, **10**(4), 248-252. https://doi.org/10.1002/JSFA.2740100409

Janssen, F., Wouters, A. G. B., Meeus, Y., Moldenaers, P., Vermant, J., & Delcour, J. A. (2020). The role of non-starch polysaccharides in determining the air-water interfacial properties of wheat, rye, and oat dough liquor constituents. *Food Hydrocolloids*, **105**, Article 105771. https://doi.org/10.1016/J.FOODHYD.2020.105771

Jekle, M., Mühlberger, K., & Becker, T. (2016). Starch-gluten interactions during gelatinization and its functionality in dough like model systems. *Food Hydrocolloids*, **54**, 196-201. https://doi.org/10.1016/j.foodhyd.2015.10.005

Lahaye, M., Bouin, C., Barbacci, A., Le Gall, S., & Foucat, L. (2018). Water and cell wall contributions to apple mechanical properties. *Food Chemistry*, **268**, 386-394. https://doi.org/10.1016/j.FOODCHEM.2018.06.110

Lahaye, M., Falourd, X., Limami, A. M., & Foucat, L. (2015). *Water Mobility and Microstructure Evolution in the Germinating Medicago truncatula Seed Studied by NMR Relaxometry*. A Revisited Interpretation of Multicomponent Relaxation. https://doi.org/10.1021/jf505515n

Launay, B., & Michon, C. (2008). Biaxial extension of wheat flour doughs: Lubricated squeezing flow and stress relaxation properties. *Journal of Texture Studies*, **39**(5), 496-529. https://doi.org/10.1111/j.1745-4603.2008.00156.X

McCleary, B. V., Gibson, T. S., Allen, H., & Gams, T. C. (1986). Enzymatic hydrolysis and industrial importance of barley β-glucans and wheat flour pentosans. *Starch - Stärke*, **38**(12), 433-437. https://doi.org/10.1002/STAR.19860381209

Medcalf, D. G., & Gilles, K. A. (1965). Determination of starch damage by rate of iodine absorption. *Cereal Chemistry*, **42**, 546-557.

Meerts, M., Cardinaels, R., Oosterlinck, F., Courtin, C. M., & Moldenaers, P. (2017). The impact of water content and mixing time on the linear and non-linear rheology of wheat flour dough. *Food Biophysics*, **12**, 151-163. https://doi.org/10.1007/s11483-017-9472-9

Meeus, Y., Janssen, F., Wouters, A. G. B., Delcour, J. A., & Moldenaers, P. (2021). The role of arabinoxylan in determining the non-linear and linear rheology of bread doughs made from blends of wheat (Triticum aestivum L.) and rye (Secale cereale L.) flour. *Food Hydrocolloids*, **120**(April), Article 106990. https://doi.org/10.1016/j.foodhyd.2021.106990

Migliori, M., & Gabriele, D. (2010). Effect of pentosan addition on dough rheological properties. *Food Research International*, **43**(9), 2315-2320. https://doi.org/10.1016/J.FOODRES.2010.08.008

Min, B., Salt, L., Wilde, P., Kosik, O., Hassall, K., Przewieslik-Allen, A., Burridge, A. J., Poole, M., Snape, J., Wingen, L., Haslam, R., Griffiths, S., & Shewry, P. R. (2020). Genetic variation in wheat grain quality is associated with differences in the galactolipid content of flour and the gas bubble properties of wheat liquor. *Food Chemistry X*, **6**(May), 1-6. https://doi.org/10.1016/j.fochx.2020.100093

Morel, M., Dehlon, P., Autran, J. C., Leygue, J. P., & Helgouac, C. B. (2000). Effects of temperature, sonication time, and power settings on size distribution and extractability of total wheat flour proteins as determined by size-exclusion high-performance liquid Chromatography. https://doi.org/10.1094/CCHEM.2000.77.5.685

Nawrocka, A., Krekora, M., Niewiadomski, Z., & Miś, A. (2018). FTIR studies of gluten matrix dehydration after fibre polysaccharide addition. *Food Chemistry*, **252**(August 2017), 198-206. https://doi.org/10.1016/j.foodchem.2018.01.110

Neukom, H., Geissmann, T., & Painter, T. J. (1967). *Bakers digest* **41**.

Parenti, O., Guerrini, L., Zanoni, B., Marchini, M., Tuccio, M. G., & Carini, E. (2021). Use of the 1H NMR technique to describe the kneading step of wholewheat dough: The effect of kneading time and total water content. *Food Chemistry*, **338**, Article 128120. https://doi.org/10.1016/j.foodchem.2020.128120

Rakhshi, F., Falourd, X., Adel, R. den, van Duynhoven, J., Lucas, T., & Rondeau-Mouro, C. (2024). Multi-scale investigation of the heat-induced transformation of starch in model dough and starch systems. *Food Hydrocolloids*, **149**, Article 109616. https://doi.org/10.1016/j.FOODHYD.2023.109616

Rezette, L. (2024). *Impact of wheat endosperm minor components on soft wheat technological quality* (p. 226p). ONIRIS VetAgroBio Nantes, France. PhD Thesis defended on Nov. 22nd 2024.

Rezette, L., Kansou, K., Della Valle, G., Le Gall, S., Saulnier, L. (2025). The role of wheat flour minor components in predicting water absorption. Food Chemistry, 463(P2), 141232. https://doi.org/10.1016/j.foodchem.2024.141232.

Rolee, A., & LeMeste, M. (1999). Effect of moisture content on thermomechanical behavior of concentrated wheat starch-water preparations. *Cereal Chemistry*, **76**(3), 452-458. https://doi.org/10.1094/CCHEM.1999.76.3.452

Rouillé, J., Chiron, H., Colonna, P., Della Valle, G., & Lourdin, D. (2010). Dough/crumb transition during French bread baking. *Journal of Cereal Science*, **52**(2), 161-169. https://doi.org/10.1016/j.jcs.2010.04.008

Shehzad, A., Chiron, H., Della Valle, G., Lamrini, B., & Lourdin, D. (2012). Energetical and rheological approaches of wheat flour dough mixing with a spiral mixer. https://doi.org/10.1016/j.jfoodeng.2011.12.008.

Sun, X., Wu, S., Koksel, F., Xie, M., & Fang, Y. (2023). Effects of ingredient and processing conditions on the rheological properties of whole wheat flour dough during breadmaking - a review. *Food Hydrocolloids*, **135**, Article 108123. https://doi.org/10.1016/j.FOODHYD.2022.108123

Tara, K. A., Bains, G. S., & Finney, P. L. (1972). Damaged starch and protein contents in relation to water absorption of flours of Indian wheats. *Starch - Stärke*, **24**(10), 342-345. https://doi.org/10.1002/STAR.19720241005

Turbin-Orger, A., Della Valle, G., Doublier, J. L., Fameau, A.-L., Marze, S., & Saulnier, L. (2015). Foaming and rheological properties of the liquid phase extracted from wheat flour dough. *Food Hydrocolloids*, **43**, 114-124. https://doi.org/10.1016/j.foodhyd.2014.05.003

Turbin-Orger, A., Shehzad, A., Chaunier, L., Chiron, H., & Della Valle, G. (2016). Elongational properties and proofing behaviour of wheat flour dough. *Journal of Food Engineering*, **168**, 129-136. https://doi.org/10.1016/j.jfoodeng.2015.07.029

Uthayakumaran, S., Newberry, M., Phan-Thien, N., & Tanner, R. (2002). Small and large strain rheology of wheat gluten. *Rheologica Acta*, **41**(1), 162-172. https://doi.org/10.1007/S003970200015

Van Vliet, T. (2008). Strain hardening as an indicator of bread-making performance: A review with discussion. *Journal of Cereal Science*, **48**, 1-9. https://doi.org/10.1016/j.jcs.2007.08.010

Welch, R. W. (1977). A micro-method for the estimation of oil content and composition in seed crops. *Journal of the Science of Food and Agriculture*, **28**(7), 635-638. https://doi.org/10.1002/jsfa.2740280710

Zhou, Y., Dhital, S., Zhao, C., Ye, F., Chen, J., & Zhao, G. (2021). Dietary fiber-gluten protein interaction in wheat flour dough: Analysis, consequences and proposed mechanisms. *Food Hydrocolloids*, **111**(2), Article 106203. https://doi.org/10.1016/j.foodhyd.2020.106203

## Glossary

**AX:** Arabinoxylans

**A/X.TOT:** Arabinose on Xylose ratio from Total Arabinoxylans

**AXTOT:** Total Arabinoxylans

**A/X.WE:** Arabinose on Xylose ratio from Water-Extractable Arabinoxylans

**A.X.WU:** Arabinose on Xylose ratio from Water-Unextractable Arabinoxylans

**C16.TOT:** Total palmitic acid C16 content

**C18.TOT:** Total stearic acid C18 content

**C181n7.TOT:** Total vaccenic acid C18:1n-7 content

**C181n9.TOT:** Total oleic acid C18:1n-9 content

**C182n6.TOT:** Total linoleic acid C18:2n-6 content

**C183n3.TOT:** Total alpha-linolenic acid C183n-3 content

**D.Gluten:** Dry Gluten

**E'min:** Minimum value of storage modulus

**E'max:** Maximum value of storage modulus

**E'max/E'min:** E'max on E'min ratio

**DMTA:** Dynamic Mechanical Thermal Analysis

**Gli:** Gliadin content

**Glu:** Insoluble Glutenin content

**GluS:** Soluble Glutenin content

**IV.AX:** Intrinsic Viscosity of Water-Extractable Arabinoxylans

**K:** Consistency index for biaxial strain $\varepsilon_b = 1$

**LSF:** Lubricated Squeezing Flow

**Lw:** Line Width of $T_{2i}$ peak

**n:** Flow index for biaxial strain $\varepsilon_b = 1$

**Prot:** Protein content

**Pz:** Populations i associated with $T_{2i}$ relaxation time

**SD:** Damaged Starch measured with SD-Matic (iodine absorption)

**SHI:** Strain hardening Index for strain rate $\dot{\varepsilon}_b = 0.01 \text{ s}^{-1}$

**SS:** Soluble Starch

**SV.AX:** Specific Viscosity of Water-Extractable Arabinoxylans

**Tz:** relaxation time of the population i

**T E'min:** Temperature at E'min

**T E'max:** Temperature at E'max

**WA:** Water Absorption

**WEAX:** Water-Extractable Arabinoxylans

**W.Gluten:** Wet Gluten