Simon Oussama Khelissa

Charafeddine Jama

Marwan Abdallah

Rabah Boukherroub

Christine Faille

Nour-Eddine Chihib
email: nour-eddine.chihib@univ-lille1.fr

Correction to: Effect of incubation duration, growth temperature, and abiotic surface type on cell surface properties, adhesion and pathogenicity of biofilm-detached Staphylococcus aureus cells

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

  Correction to: Effect of incubation duration, growth temperature, and abiotic surface type on cell surface properties, adhesion and pathogenicity of biofilm-detached Staphylococcus aureus cells Oussama Khelissa, Charafeddine Jama, Marwan Abdallah, Rabah Boukherroub, Christine Faille, Nour-Eddine Chihib To cite this version: Oussama Khelissa, Charafeddine Jama, Marwan Abdallah, Rabah Boukherroub, Christine Faille, et al.. Correction to: Effect of incubation duration, growth temperature, and abiotic surface type on cell surface properties, adhesion and pathogenicity of biofilm-detached Staphylococcus aureus cells. AMB Express, 2017, 7 (191), 10.1186/s13568-017-0509-8. hal-02623145 Correction to: AMB Expr (2017) 7:191 https://doi.org/10.1186/s13568-017-0492-0 Following publication of the original article (Khelissa et al. 2017), the authors reported that the legend for Fig. 3 contained an error. Instead of "Adhesion of planktonic and biofilm-detached Staphylococcus aureus cells on stainless steel and polycarbonate. Cell cultures were grown at 20, 30 and 37 °C, during 24 h (white square) and 48 h (white square). Planktonic cells adhesion on stainless steel (a) and polycarbonate (b). Adhesion of stainless steel-biofilm-detached-cells on stainless steel 24 (c) and polycarbonate-biofilm-detached-cells on polycarbonate (d)", the legend should read "Adhesion of planktonic and biofilm-detached Staphylococcus aureus cells on stainless steel and polycarbonate. Cell cultures were grown at 20, 30 and 37 °C, during 24 h (black square) and 48 h (white square). Planktonic cells adhesion on stainless steel (a) and polycarbonate (b). Adhesion of stainless steel-biofilm-detached-cells on stainless steel 24 (c) and polycarbonate-biofilm-detached-cells on polycarbonate (d)". The original article has been corrected.

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Yann Morizet
email: yann.morizet@univ-nantes.fr

Michael Paris

David Sifré

Ida Di Carlo

Sandra Ory

Fabrice Gaillard

Michaël Paris

Michael Paris

Michael Paris

Michael Paris

Geology

Michael Paris

Towards the reconciliation of viscosity change and CO2-induced polymerization in silicate melt» by

Introduction

There is a growing interest into the study of carbon dioxide (CO 2 ) in magmatic systems and capturing the dissolution mechanisms of CO 2 and how it affects the structure of silicate melts constitutes a prime milestone. The comment by Xue and this reply illustrate well the difficulties in addressing this fundamental quest. In the comment, [START_REF] Xue | Comment on "Towards the reconciliation of viscosity change and CO 2induced polymerization in silicate melts[END_REF] provides corrected NBO/T values using the 17 O NMR data produced in Morizet et al. (2017c). The comment also shows that the quantitative relationship in between theoretical model for CO 2 dissolution in silicate melt structure and existing NMR data can be difficult to apprehend.

Finally, the comment points out the lack of agreement in between the XCO 3 2-from 17 O NMR and XCO 2 from Raman spectroscopy as reported in Morizet et al. (2017b). In the present reply, we propose a corrigendum to our work (Morizet et al., 2017c) and an addendum pointing towards the future scientific questions to be answered.

Since the seventies, many scientific questions arose concerning the CO 2 behaviour in magmatic systems: 1) the CO 2 solubility in silicate melts as a function of intensive conditions (P,T and fO 2 ) and compositions (e.g. silica content), 2) the way CO 2 molecules dissolve into the silicate melt structure (i.e. speciation) and 3) the influence CO 2 dissolution induces on the silicate melt physical properties (e.g. viscosity, density or electrical conductivity).

For the first two points, many scientific studies have produced large database for CO 2 solubility and subsequent thermodynamic modelling have been built to constrain CO 2 solubility (and degassing) in silicate melts and taking into account the CO 2 dissolution mechanisms [START_REF] Newman | VOLATILECALC: a silicate melt-H 2 O-CO 2 solution model written in Visual Basic for excel[END_REF][START_REF] Papale | The compositional dependence of the saturation surface of H 2 O+CO 2 fluids in silicate melts[END_REF][START_REF] Iacono-Marziano | New experimental data and semi-empirical parameterization of H 2 O-CO 2 solubility in mafic melts[END_REF][START_REF] Massuyeau | A model for the activity of silica along the carbonatite-kimberlite-melilitite-basanite melt compositional joint[END_REF]. For the third point, the effect CO 2 induces on melt physical properties is still highly debated. Recent works addressed the effect of CO 2 onto silicate melt

Journal Pre-proof J o u r n a l P r e -p r o o f density [START_REF] Seifert | Partial molar volume and compressibility of dissolved CO 2 in glasses with magmatic compositions[END_REF] and silicate melt electrical conductivity [START_REF] Sifré | Electrical conductivity during incipient melting in the oceanic low-velocity zone[END_REF]. For viscosity, the effect of CO 2 is unclear and requires further investigations to decipher the exact effect of CO 2 onto silicate melt viscosity. One way to address the effect CO 2 induces onto silicate melt viscosity is to investigate in detail the effect CO 2 dissolution induces onto the silicate melt structure which is considered as a proxy for melt physical properties and in particular viscosity. Our recent research has focused on this aspect and we believe to have

reached a substantial answer to the effect of CO 2 onto silicate melt viscosity (Morizet et al., 2017c). The comment by [START_REF] Xue | Comment on "Towards the reconciliation of viscosity change and CO 2induced polymerization in silicate melts[END_REF] and our accompanying reply constitute a cornerstone on this hot scientific topic and emphasise that there is a need for future work in the subject. In a recent paper (Morizet et al., 2014b), we conducted a similar work on a more polymerized melt composition (nephelinite with NBO/T ~ 1.3) than the one studied in Morizet et al.

(2017c; NBO/T ~ 2). Using 29 Si NMR, we showed that CO 2 was polymerizing the aluminosilicate network; however, there was a glitch in the interpretation because mass balance calculation was not satisfied with respect to the initial reaction for CO 2 dissolution mechanism:

Journal Pre-proof J o u r n a l P r e -p r o o f

melt n melt melt n fluid Q CO Q CO 1 2 3 2 2 2      
Eq. 1

Hence, it was then suspected that a more complex mechanism occurred and that 29 Si NMR was not able to identify it. We concluded that 29 Si NMR was probably not the best appropriate method to determine the effect CO 2 induces on the aluminosilicate network. For instance, the distinction in between the effects of the topological changes (Q n distribution) and geometrical changes (bond length and angles) (as defined in [START_REF] Massiot | Topological, geometric, and chemical order in materials: Insights from Solid-State NMR[END_REF] From our work (Morizet et al., 2017c), we showed that both 17 O and 29 Si NMR results are totally consistent. However, the approach we employed to determine the NBO/T from the 17 O NMR results is not correct as shown by [START_REF] Xue | Comment on "Towards the reconciliation of viscosity change and CO 2induced polymerization in silicate melts[END_REF] who proposes the right method to calculate the NBO/T from the subsequent 17 O NMR deconvolution results. Anyhow, our results and interpretations supported the previous recent investigations on the effect of CO 2 onto silicate melt structure (Morizet et al., 2014b;[START_REF] Moussallam | The molecular structure of melts along the carbonatite-kimberlite-basalt compositional joint: CO 2 and polymerization[END_REF].

The second mistake pointed out by Xue ( 2019) is with regards to the theoretical equation (Eq. does not have a more polymerizing effect than the effect quantified with Eq. 1.

Consequently, we propose a corrigendum to the work in Morizet et al. (2017b), section 5.2 Fig. 3. We followed the description made by [START_REF] Xue | Comment on "Towards the reconciliation of viscosity change and CO 2induced polymerization in silicate melts[END_REF] and results are shown in Figure 1.

We choose to represent the data in a NBO/T vs XCO 2 /T as it is more appropriate for apprehending the change in the degree of polymerization as a function of CO 2 content: different compositions (with different NBO/T) can be readily compared and the slope for CO 2 dissolution theoretical equation is -2.

For the RB8 sample, we report the NBO/T calculated from the 29 Si NMR data and corrected values of NBO/T from 17 O NMR data; we also added the data for nephelinite (Morizet et al., 2014b) and haplokimberlite (Morizet et al., 2017a). From Figure 1, it can be observed that the whole dataset agrees and that CO 2 incorporation in the melt induces a decreasing in the NBO/T whatever the considered melt compositions. Using the correct calculation, the NBO/T derived from 17 O NMR is in agreement with the 29 Si NMR results. Hence, the distribution of Q n species as determined by 29 Si NMR can be used to constrain the change in the silicate glass degree of polymerization as a function of CO 2 content dissolved as Free Ionic Carbonate CO 3 2-molecular groups. Based on the Q n distribution, we proposed the following equation for CO 2 dissolution mechanism in silica undersaturated melts:

melt melt melt melt fluid Q Q CO Q CO 3 2 2 3 1 2 0 . 2 5 . 0 25 . 2 5 . 2 25 . 2       Eq. 2
We emphasise that 17 O NMR results were only used in a qualitative manner in Morizet et al. (2017c) and the reaction for CO 2 dissolution was constrained by 29 Si NMR results. The Eq. 2 is a combination of several individual reactions such as the one reported in Eq. 1. We think that the use of this global reaction is more representative of the thermodynamic at stake: each individual reaction may not have the same equilibrium constant; the configuration entropy Journal Pre-proof J o u r n a l P r e -p r o o f (i.e. related to viscosity) is proportional to the sum of all Q n species molar fraction. The Eq. 2 constitutes a real and unambiguous advance in our knowledge of the CO 2 dissolution in the silicate network structure for depolymerized silicate glass compositions.

The proposed Eq. 2 is equivalent to the theoretical Eq. 1. In Figure 1, we report the linear trends derived from Eq. 1 and for three different compositions (i.e. NBO/T = 1, 2 and 3). The change in the NBO/T as a function of CO 2 content from the theory and NMR data are in agreement; at least for RB8 (Morizet et al., 2017c) and HK (Morizet et al., 2017a) data. It suggests that the measured change in the glass polymerization degree strictly follows the theoretical change in the degree of polymerization imposed by Eq. 1. It seems that data obtained for nephelinite composition ( 29 Si NMR, Morizet et al., 2014b) departs from the theory imposed by Eq. 1; which is only valid if CO 2 dissolves as Free Ionic Carbonates that is the case for strongly depolymerized RB8 and HK compositions. The off-trend pattern for nephelinite data could be explained by a different CO 2 dissolution mechanism owing to the higher degree of polymerization for this glass composition (NBO/T ~ 1). For moderately depolymerized compositions, several CO 2 dissolution mechanisms can be evoked. We suspect that Free Ionic Carbonates are formed but accompanied by other types of CO 3 2-such as network carbonates and NBO carbonates [START_REF] Brooker | Structural controls on the solubility of CO 2 in silicate melts. Part II: IR characteristics of carbonate groups in silicate glasses[END_REF]; however, these different types of CO 3 2-molecular groups do not necessarily involve an increase in the degree of polymerization and therefore cannot explain the steeper slope observed in Figure 1 for nephelinite 29 Si NMR data. One alternative explanation lies in the difficulty to interpret quantitatively the 29 Si NMR data: for example, we know that the δ iso of each individual Q n species is modified by the presence of surrounding Al atoms [START_REF] Engelhardt | Structural studies of calcium aluminosilicate glasses by high-resolution solid-state 29 Si and 27 Al magic angle spinning nuclear magnetic resonance[END_REF][START_REF] Hiet | Probing chemical disorder in glasses using silicon-29 NMR spectral editing[END_REF]. As a result, if the question of the CO 2 effect onto the degree of polymerization is clearly sorted out for depolymerized glass composition and that reconciliation to the change in Journal Pre-proof J o u r n a l P r e -p r o o f physical properties has been proposed; we believe that the question still remains opened for glass compositions demonstrating several CO 2 dissolution mechanisms.

3. Quantification of CO 3 2-species with 17 O NMR spectroscopy

In our recent work (Morizet et al., 2017b), using 17 O NMR spectroscopy, we have shown that the peak intensity at ~+150 ppm was linearly correlated to the total CO 2 content determined by Raman spectroscopy [START_REF] Morizet | Quantification of CO 2 dissolved in silicate glasses of various compositions with Micro-Raman spectroscopy[END_REF]. The observed correlation helped us to assign the 17 O NMR peak located at ~+150 ppm to carbonate environments in an unambiguous manner. We should point out that this was the first piece of evidence for CO 3 2-dissolved in silicate glasses by 17 O NMR. The proposed assignment was later confirmed in our work (Morizet et al., 2017a) We doubt that the CO 2 concentration determined by Raman can be put into question as most of the samples were also analysed using elemental analyser which is an absolute method [START_REF] Moussallam | CO 2 solubility in kimberlite melts[END_REF]. Instead, we believe that the quantification of CO 3 2-species using 17 O NMR spectra acquired on a 500 MHz NMR spectrometer is inherently limited. Due to the broadening of the peak at ~+150 ppm and its relatively low intensity, the quantification of CO 3 2-species is certainly accompanied by a substantial error. The corollary problem is that it will induce an error in the derived oxygen species concentrations (NBO and BO); however, considering the large scatter observed in Figure 1 and the range of investigated CO 2 , the quantitative error will have a limited impact. The reported trend in Morizet et al. (2017a) Journal Pre-proof J o u r n a l P r e -p r o o f using 17 O NMR can only be used in a qualitative manner and quantitative application will necessitate more thorough investigation.

Future work and perspectives

As pointed out in the introduction, obtaining a clear vision of the CO 2 dissolution mechanisms in silicate melt structure is a prerequisite for the understanding of the effect CO 2 dissolution induces on the silicate melt physical properties such as viscosity or electrical conductivity. It appears clear from the subsequent discussion, and the recent work we have published as well as the decades of knowledge on the CO 2 behaviour in silicate melts that there are still discoveries to be made. In particular, the work we accomplished (Morizet et al., 2017a, b, c) is only a small part of the iceberg as it focuses on particular melt compositions which are depolymerized (i.e. low silica content), CO 2 -rich and analogous to natural magmas which are very peculiar on Earth. As mentioned earlier, the question of the effect of CO 2 dissolution on the silicate melt structure for compositions having multiple CO 2 dissolution mechanisms (Free Ionic Carbonates, Network Carbonates and NBO Carbonates) is still to be determined.

Previous NMR studies (Kohn et al., 1991;[START_REF] Brooker | Solubility, speciation and dissolution mechanisms for CO 2 in melts on the NaAlO 2 -SiO 2 join[END_REF]Morizet et al., 2014a[START_REF] Morizet | A NMR and molecular dynamics study of CO 2bearing basaltic melts and glasses[END_REF] have commonly used 13 C NMR approach to investigate the CO 2 behaviour in silicate melt.

Pioneer work by Kohn et al. (1991) used the 13 C NMR to investigate the CO 2 speciation in glasses when CO 2 is dissolved as both CO 2 mol and CO 3 2-groups. Considerable progresses were conducted with the work of [START_REF] Brooker | Solubility, speciation and dissolution mechanisms for CO 2 in melts on the NaAlO 2 -SiO 2 join[END_REF][START_REF] Brooker | Structural controls on the solubility of CO 2 in silicate melts. Part II: IR characteristics of carbonate groups in silicate glasses[END_REF] confirmed for CO 2 -bearing phonolitic glasses [START_REF] Morizet | CO 2 in haplo-phonolite Melt: Solubility, speciation and carbonate complexation[END_REF]. We proposed an assignment for 13 C NMR signature above +165 ppm to NBO-Carb. M n+ or free carbonate groups (Morizet et al., 2014a). These carbonate groups were also suggested to be present in depolymerized composition from [START_REF] Brooker | Structural controls on the solubility of CO 2 in silicate melts. Part II: IR characteristics of carbonate groups in silicate glasses[END_REF]. However, the discrimination in between NBO-Carb M n+ and CO 3 2-M n+ was impossible using 13 C NMR and we had to access We have conducted a simple approach which is to report the change in the peak centroid of the carbonate 13 C NMR peak (Figure 2) as a function of composition expressed as wt.% Al 2 O 3 + SiO 2 for simplicity. We considered 13 C NMR spectra for compositions ranging from molten carbonates to depolymerized haplokimberlites [START_REF] Moussallam | The molecular structure of melts along the carbonatite-kimberlite-basalt compositional joint: CO 2 and polymerization[END_REF] and to fully polymerized jadeite [START_REF] Morizet | Annealing experiments on CO 2 -bearing jadeite glass: an insight into the true temperature dependence of CO 2 speciation in silicate melts[END_REF], nepheline and albite [START_REF] Brooker | Solubility, speciation and dissolution mechanisms for CO 2 in melts on the NaAlO 2 -SiO 2 join[END_REF] having varying Al/Si ratio. We observe that the 13 C peak centroid is slightly changing (~2 ppm) with increasing Al 2 O 3 + SiO 2 content up to 60 wt.% Al 2 O 3 + SiO 2 . The slight decrease in the 13 C ppm shift from 0 to 60 wt.% Al 2 O 3 + SiO 2 is then followed by a brutal decrease in the 13 C peak centre. This dichotomy might indicate the change in the CO 3 2-dissolution mechanisms from Free Ionic Carbonates (and possibly NBO-Carb. M n+ ) to Network Carbonates (T-Carb.-T). The brutal change in the 13 C peak centre also seems to mark the limit between slightly depolymerized (NBO/T ~ 0.2 for phonolite, [START_REF] Morizet | CO 2 in haplo-phonolite Melt: Solubility, speciation and carbonate complexation[END_REF] to fully polymerized (NBO/T ~ 0 for jadeite, [START_REF] Morizet | Annealing experiments on CO 2 -bearing jadeite glass: an insight into the true temperature dependence of CO 2 speciation in silicate melts[END_REF][START_REF] Morizet | The influence of H 2 O and CO 2 on the glass transition temperature: insights into the effects of volatiles on magma viscosity[END_REF]. In the Network carbonate region, [START_REF] Brooker | Solubility, speciation and dissolution mechanisms for CO 2 in melts on the NaAlO 2 -SiO 2 join[END_REF] made the distinction in between the different types of carbonates for nepheline, jadeite and albite which have different Al/Si ratio. However, within the Free Ionic Carbonates

  1) for CO 2 dissolution. We lacked clear sighting in handling this theoretical equation. It has two consequences (see Figure 1): 1) the NMR results are in agreement with the theoretical Journal Pre-proof J o u r n a l P r e -p r o o f equation proposed in early work for CO 2 dissolution and corresponding to Eq. 1; and 2) CO 2

  using { 13 C}-17 O J-HMQC NMR technique. In this correlation (based on 7 data points), we determined a slope of 0.8. As reported in Morizet et al. (2017b) the XCO 3 2-17 O NMR cannot be straightforwardly related to XCO 2 Raman mainly because the quantitative calculations are dependent on too many parameters as pointed out by Xue (2019).

  which stated that several types of carbonates groups are present in silicate glasses; with the type of CO 3 2-depending on the silicate glass composition. They clearly demonstrated that network carbonates (T-Carb.-T) are identified below +165 ppm in the 13 C NMR spectrum and the chemical shift being dependent on the nature of the cation (e.g. Si or Al) in the tetrahedral unit. This assignment was also later Journal Pre-proof J o u r n a l P r e -p r o o f

  this information by alternative means: { 13 C}-17 O J-HMQC NMR technique(Morizet et al., 2017a). The recent work by[START_REF] Xue | Comment on "Towards the reconciliation of viscosity change and CO 2induced polymerization in silicate melts[END_REF] combining 13 C NMR and Ab-Initio calculations went further in identifying the different CO 3 2-species and investigated the change in the CO 3 2molecular configuration for a wide range of glass compositions (i.e. from fully polymerized to strongly depolymerized).

Figure caption : Figure 1 :

 :1 Figure caption:

Figure 2 :

 2 Figure 2: Change in the peak centroid position for carbonate molecular groups determined by 13 C MAS NMR spectroscopy as a function of wt.% Al 2 O 3 + SiO 2 . Peak position in ppm has

  appears difficult to determine with the sole use of 29Si NMR. We suggested that CO

2 could induce unquantified topological changes and that the measured polymerization using 29 Si NMR did not reflect the true change in the degree of polymerization upon CO 2 solubility. Consequently, we changed our strategy and considered that it would be more appropriate to conduct 17 O NMR investigation (i.e. probing BO and NBO concentrations) in conjunction to 29 Si NMR (i.e. probing Q n distribution). As such, the combined use of 17 O and 29 Si NMR spectroscopy would answer the initial problem as to whether or not the Q n distribution measured by 29 Si NMR reflects the true change in the polymerization upon CO 2 dissolution.

Declaration of interests

☒ 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.

☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:


M Kristiawan
email: magdalena.kristiawan@inra.fr

V Micard

P Maladira

C Alchamieh

J.-E Maigret

A.-L Réguerre

M A Emin

G Della Valle

Multi-scale structural changes of starch and proteins during pea flour extrusion

Keywords: Composite morphology, expansion, protein aggregates, solid foam, solubility

Dehulled yellow pea flour (48.2% starch, 23.4% proteins, d.b.), was processed by a twinscrew extruder at various moisture contents MC (18-35% w.b.), product temperature T (115-165°C), and specific mechanical energy SME (50-1200 kJ/kg). Structural changes of extruded pea flour were determined at different scales by measurements of density (expansion), crystallinity (X-ray diffraction), gelatinisation enthalpy (DSC), starch solubility in water and protein solubility in SDS and DTE (SE-HPLC). Foam density dropped from 820 to 85 kg/m 3 with increase in SME and T (R 2 >0.78).

DSC and XRD results showed that starch was amorphous whatever extrusion conditions. Its solubility in water augmented up to 50%. Increasing temperature from 115 to 165°C decreased proteins soluble in SDS from 95 to 35% (R 2 =0.83) of total proteins, whereas the proteins soluble in DTE increased from 5 to 45% (R 2 =0.75) of total proteins. These trends could be described by sigmoid models, which allowed determining onset temperatures for changes of protein solubility in the interval [125, 146°C], whatever moisture content. The SME impact on protein solubility followed similar trends. These results suggest the creation of protein network by S-S bonds, implicating larger SDS-insoluble protein aggregates, as a result of increasing T and SME, accompanied by creation of covalent bonds other than S-S ones. CSLM images suggested that extruded pea flour had a composite morphology that changed from dispersed small protein aggregates to a bi-continuous matrix of large protein aggregates and amorphous starch. This morphology would govern the expansion of pea flour by extrusion.

Flory-Huggins starch-water interaction parameter (dimensionless)

Introduction

Pulse legumes (pea, lentil, faba bean) are excellent source of proteins (20-30% dry basis), dietary fibers (10-30%), starch (40-55%), vitamins and minerals, and they are low in sugar, sodium and fat [START_REF] El-Adawy | Nutritional potential and functional properties of germinated mung bean, pea and lentil seeds[END_REF]. Pulse proteins are relatively high in lysine and low in sulphur-containing amino acids: cysteine, methionine, and tryptophan [START_REF] Leterme | Amino acid composition of pea (Pisum sativum) proteins and protein profile of pea flour[END_REF]. Combination of pulse proteins with low-lysine cereal proteins allows a nutritional adequate protein profile. The formulation of gluten-free extruded snacks made entirely from pulse legumes is also an interesting way to introduce pulse to modern consumers demanding vegan, gluten free, non-GMO and protein enriched functional foods.

Extrusion is one of the most versatile and efficient food processing technique used in preparation of starch based foods and especially to process protein-fortified extrudates [START_REF] Day | Functionality of protein-fortified extrudates[END_REF]. After melting, the viscous material is forced through a die where the vapour expands the material to a porous structure. Texture properties of extruded products, envisioned like solid foam, depend not only on density and cellular structure but also on the mechanical properties of the material which constitutes the cell walls of the foam. These properties depend on the morphology of the cell wall material created during extrusion under high temperature and shear. These conditions lead to many biopolymer transformations: starch melting, depolymerisation, protein denaturation, browning, and destruction of anti-nutritional components. With increasing temperature, molecular changes in proteins take place in several steps: association, dissociation, and aggregation of subunits by noncovalent (hydrophobic, ionic, H) and covalent (disulphide, isopeptide) bonds [START_REF] Stanley | Protein reactions during extrusion processing[END_REF]). In the case of extrusion of soy and pea protein isolates, the increasing shear energy promotes protein unfolding resulting in protein re-association (Della [START_REF] Valle | Relationships between processing conditions and starch and protein modifications during extrusion-cooking of pea flour[END_REF][START_REF] Fang | Effects of specific mechanical energy on soy protein aggregation during extrusion process studied by size exclusion chromatography coupled with multi-angle laser light scattering[END_REF]. Besides, moisture content probably increases the mobility of proteins and their cross-linking [START_REF] Holay | Influenece of the extrusion shear environment on plant protein texturization[END_REF].

The knowledge about the bonding forces involved in protein changes during extrusion was generally deducted from experiments on protein solubility of extrudates in selective reagents capable to disrupt specific bonds. Most of the studies on legume protein solubility have focused on high moisture extrusion (>50% w.b.) producing meat analogues from soy and pea protein isolates. Recent studies show that the meat analogue structuring is more related to thermodynamic incompatibility, which could be induced by protein-protein interactions [START_REF] Tolstoguzov | Creation of fibrous structures by spinneretless spinning[END_REF].

Most studies on expanded snacks, made from legume proteins extruded at lower moisture (<25% w.b.), focused mainly on the effect of extrusion variables on density, expansion and functional properties using black box modelling for optimizing. Studies on the changes of protein structure and solubility were performed after extrusion, generally in a narrow extrusion domain, and did not involve macroscopic features like expansion [START_REF] Alonso | Effect of extrusion cooking on structure and functional properties of pea and kidney bean proteins[END_REF][START_REF] Ben-Hdech | Extrusioncooking of pea flour: Structural and immunocytochemical aspects[END_REF] Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. ( 2018). Multi-scale structural changes of starch and proteins during pea [START_REF] Ben-Hdech | Extrusioncooking of pea flour: Structural and immunocytochemical aspects[END_REF][START_REF] Valle | Relationships between processing conditions and starch and protein modifications during extrusion-cooking of pea flour[END_REF][START_REF] Gujska | High temperature extrusion effects on protein solubility and distribution in navy and pinto beans[END_REF]. More recently, protein aggregations have been studied on pulse legume based pasta extruded at moisture content between 30 and 35% (w.b.) and low temperature (<100°C) [START_REF] Laleg | How the structure, nutritional and sensory attributes of pasta made from legume flour is affected by the proportion of legume protein[END_REF]. However pasta are not expanded product. The diversity of protein sources and processing conditions make the comparison of results difficult and sometimes contradictory. Published results about the effect of protein content on sectional expansion index (SEI) showed both negative and positive impact. [START_REF] Paton | Component interactions in the extrusion cooking process: Influence of process conditions on the functional viscosity of the wheat flour system[END_REF] found that for extrusion of gluten-wheat starch blend (moisture content MC 21%, 163°C, 50 rpm), the SEI increased from 3 to 5 when adding 10% gluten. Conversely, for extrusion held at the same level of MC but higher mechanical energy (230 rpm), De [START_REF] De Mesa | Soy protein-fortified expanded extrudates: Baseline study using normal corn starch[END_REF] found that an The first objective of this work is to ascertain the effect of biopolymer transitions on the structure of extruded pea flour. The structure was studied at two levels: (1) the cell walls of foams constituted by starch-protein blends, and (2) the overall expansion. Second objective is to determine the relationship between extrusion variables, product structure, and material transformations on a mechanistic basis. A wide range of extrusion conditions was selected and resulting products were thoroughly analysed at different levels of matter organization.

A C C E P T E D M A N U S C R I P T Gallant,

Materials and methods

Raw materials

Dehulled yellow split pea grits was obtained from Sotexpro (France). The pea (variety Karpate) was harvested in spring 2016. The pea grits were ground by a miller (Sarl Giraud, France) in order to obtain pea flour with median diameter of about 480µm.

Chemical composition (in dry basis)

Total crude protein content of pea flour was obtained using Kjeldahl procedure with a nitrogen-to-protein conversion factor of 6.25. Total starch content was determined with an enzymatic assay kit (Megazyme, Co., Ireland). Ash content was determined by incineration at 900 °C for 2h according to the French standard (NF 03-720). Total lipids were extracted according to method of [START_REF] Folch | A simple method for the isolation and purification of total lipides from animal tissues[END_REF]. All measurements were conducted in triplicate. The reported values are averages

ACCEPTED MANUSCRIPT

Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. ( 2018). Multi-scale structural changes of starch and proteins during pea

A C C E P T E D M A N U S C R I P T
with relative standard deviation lower than 5%. Fibre content was calculated by subtraction of average content (% d.b.) of ash, fat, protein and starch from total chemical content.

Extrusion trials

Pea flour was extruded using a laboratory scale co-rotating twin-screw extruder (Coperion

Werner & Pfleiderer ZSK 26Mc). The screw diameter was 25.5mm. The barrel was divided into 7 sections with a total length of 740mm. During the experiments, each barrel section, except the first one, was heated separately to 40, 60, 80, 90, 90, and 90°C. The raw material was fed by a gravimetrically controlled feeder (Brabender DDW-DDSR 40). Water was added into the second barrel by a volumetric pump. The screw profile included (i) conveying elements with decreasing pitch from 36 to 24mm, (ii) followed by three 45° kneading discs (length of 12mm each) located inside the fourth barrel, (iii) three reverse elements having pitch and length of 12 mm located inside the fifth barrel, (iv) conveying elements having pitch of 24mm. This geometry assured (i) homogeneous mixing of flour and water at the inlet (ii) melting dough completely in the stagnant area generated by reverse elements and (iii) conveying the molten phase to die.

In order to obtain extrudates having a wide range of structures and biopolymer transformations,a large domain of operating parameters was applied: moisture content 18-35% w.b., screw speed 300-700 rpm, total feed rate 10-25 kg/h, extruder configuration with (A) and without (B) restrictive elements, and imposed die temperature 130-150°C. Two die geometries were used: die C consisted of a long slit die (thickness 3mm, width 15mm, length 72mm) followed by an orifice die (Ø 3mm, length 15mm), die D consisted of an orifice die mounted directly to the extruder head without slit die. Extrusion parameters are summarized in Table 1. The interval of variations of these parameters was chosen by numerical screening using a twin-screw simulation software Ludovic ® [START_REF] Vergnes | A global computer software for polymer flows in corotating twin screw extruders[END_REF], in order to cover a wide range of extrusion variables, such as product temperature 115-165°C and specific mechanical energy (SME) 40-1200 kJ/kg. In addition, the knowledge of pea starch melting temperature at various moisture contents was used for setting extrusion conditions to obtain extrudates with amorphous starch mainly under low SME (< 100 kJ/kg) [START_REF] Logié | How does temperature govern mechanisms of starch changes during extrusion?[END_REF].

In particular, experiments using relatively high moisture content (between 26 and 35%) were performed to produce dense material samples (low expansion) that can be considered as the constitutive material ("parietal material") of the pea flour foams (expanded samples). Die pressure and product temperature were measured just in the last section of the extruder with an accuracy of +0.25% and +0.5°C, respectively. Specific mechanical energy (SME, kJ/kg) was calculated from screw speed, where N and N max are the actual and maximum screw speed (N max = 1800 rpm), τ and τ empty are the actual and empty measured torque . The maximum power of extruder P max is 40 kW. Q is the total mass flow rate (kg/h).

The extrudates were dried under vacuum at 40°C overnight in order to get final moisture content less than 10% w.b. and stored in airtight plastic bags at room temperature. A part of each extrudate was ground into a fine powder using a grinder (M20, IKA Werke GmbH & Co., Germany).

The ground samples and pea flour were sieved to pass a 250 µm mesh and conditioned at a relative humidity of 59% at 20°C for two weeks.

Product analysis

Density and sectional expansion index

Extrudate density reflects overall or volumetric expansion expressed by the index VEI ≈ melt density / extrudate density. Volumetric expansion results from radial and longitudinal expansions, each term being assessed by a specific index [START_REF] Kristiawan | Modeling of starchy melts expansion by extrusion[END_REF]. Longitudinal expansion index (LEI) characterizes the expansion in die flow direction, whereas radial or sectional expansion index (SEI) refers to the increase of cross section in the plane orthogonal to flow direction. The three indices are linked by the relationship:

𝑉𝐸𝐼 = 𝐿𝐸𝐼 × 𝑆𝐸𝐼 (2)
In this work, macro structure of extrudates was characterized by density and SEI. The bulk density was obtained using glass beads displacement method. The extrudate density (ρ * ) was calculated from the mass of extrudate and its volume measured through the displacement of glass beads (Ø 1mm). The reported values (Table 2) were the averages of three repetitions (relative error 10%). The SEI was calculated as the ratio of cross-sectional area of extrudate to that of die. For each sample, diameter was measured at five random positions on each of seven pieces of extrudates. The reported SEI values were the averages of these thirty-five measurements (relative error 15%).

Starch transformation

Melting transition

Pea flours with various moisture contents (5 to 35% wet basis) were prepared under controlled relative humidity of 11 to 97% over saturated salts at 20°C for 1-2 weeks. DSC Q10 (TA Instrument, France) was used for melting point analysis following the method of [START_REF] Barron | Structural modifications of low hydrated pea starch subjected to high thermomechanical processing[END_REF]. The samples were heated from 25 to 180°C at a heating rate of 3°C/min. Melting temperature (T m ) was defined as the offset temperature of endothermic peak. The measurements were done in duplicate (relative error 10%).

Residual gelatinization analysis

Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea

A C C E P T E D M A N U S C R I P T
The degree of starch transformation (crystallinity loss and granular disorganization) was determined by duplicate measurements of DSC gelatinization enthalpy of extrudates, in excess water, compared to untreated pea flour. Absence of residual gelatinization enthalpy means that starch is amorphous. The DSC scans were run at 3°C/min from 10 to 120°C.

Crystallinity state by WAXS

The loss of crystallinity was also examined using a wide angle x-ray scattering analysis (WAXS) [START_REF] Barron | Structural modifications of low hydrated pea starch subjected to high thermomechanical processing[END_REF]. The analysis was performed using a Bruker D8 diffractometer (Bruker AXS Inc., USA) equipped with a copper source operating at 40 kV and 40 mA.

Water Solubility Index (WSI) and Water Absorption Index (WAI)

Water solubility index of total solids (WSI solids ) and water absorption index (WAI) of flour and ground extrudates were determined using the method of [START_REF] Anderson | Gelatinization of corn grits by roll cooking, extrusion cooking and steaming[END_REF]. Mass of 2.5 g of samples was dispersed in 30 ml of distilled water, then agitated at 30°C for 30 min and finally centrifuged at 3000 g for 10 min at 20°C. The supernatant was dried overnight in a Chopin oven at 105°C. WAI was calculated as the ratio of mass of wet pellet to dry original sample. WSI solids was determined as the percentage of mass of supernatant dry solid to dry original sample.

For determining WSI of starch (WSI starch ), the samples underwent firstly the same extraction and centrifugation procedure as described before. Thereafter, the supernatant was titrated with orcinol in an automatic spectrocolorimeter, according to the method of [START_REF] Tollier | Adaptation de la méthode à l'orcinol sulfurique au dosage automatique des glucides neutres totaux: conditions d'application aux extraits d'origine végétale[END_REF].

The measurements of WSI and WAI were carried out in triplicate (relative error 15%).

Protein transformation

Procedure of protein extraction

Proteins were extracted using a method adapted from [START_REF] Morel | 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[END_REF]. Samples underwent two successive extractions. The first stage, aiming to extract SDS-soluble proteins, was conducted at 60°C for 80 min with a sodium phosphate buffer containing 1% of sodium dodecyl sulphate (SDS, 0.1 M) with a solid-to-solvent ratio of 8 mg/mL. SDS disrupts the electrostatic, hydrophobic and hydrophilic interactions between proteins. After centrifugation, 1 mL of the supernatant was analysed

Measurement of molecular weight distribution of proteins aggregates

The size distribution of protein aggregates in the extracts was studied by Size-Exclusion High-Performance Liquid Chromatography (SE-HPLC). The SE-HPLC apparatus (Waters LC Module1 plus) was equipped with an analytical column TSK G4000-SW, 7.5 x 300 mm (Merck, France) and a guard column TSK G3000-SW, 7.5 x 75 mm (Merck, France). Apparent molecular weights were determined in the column calibrated with protein standards [START_REF] Redl | Extrusion of wheat gluten plasticized with glycerol: Influence of process conditions on flow behavior, rheological properties, and molecular size distribution[END_REF]. Once corrected for their different solid-to-solvent ratios, the integrated areas of SDSsoluble and DTE-soluble proteins of samples were expressed as percentage of the total area of the reference sample D8 giving the maximum total extractable proteins. The solubility experiments were duplicated (relative error 5%).

Color measurement

Color changes of ground samples (sieved between 250 and 500µm) were assessed by measurement of CIE Lab color space (L*, a* and b*) using a chromameter (Konica Minolta CR-400)

with a standard illuminant D65 (natural daylight), and an observation angle of 2°. L* stands for lightness black-white (0, 100), a* and b* for color opponents green-red (-100, +100) and blue-yellow (-100, +100), respectively. Color measurements were done in triplicate (relative error 1%). These color changes could reflect Maillard reactions occurring between reducing sugars and free amine groups due to thermo-mechanical treatment.

Morphology of starch-protein blends

Confocal laser scanning microscopy (CLSM) was used to locate the starch/protein phases in the constitutive material of extruded samples. The extrudates were cut perpendicularly and embedded in paraffin using a method adapted from Ben Hdech et al. (1991). The slices of 10 µm were then cut using a rotary microtome. Starch was stained red with oxidation in periodic acid solution followed by coloration with Acriflavine-Schiff reagent, called as PAA staining. Proteins were stained green with 0.01% (w/v) Fuchsine Acid in 1% (v/v) acetic acid [START_REF] Kristiawan | Structure and mechanical behaviour of corn flour and starch-zein based materials in the glassy state[END_REF]. Images were acquired using a confocal laser scanning microscope (Nikon A1) with attached NIS imaging system (Nikon, Germany). Samples were examined in the epifluorescence mode of the microscope, excited by a green laser beam at 561nm for Fuchsine Acid stain and at 488nm for PAA stain. The emitted light was selected by a long-pass filter (>570nm). Three-dimensional images of samples were obtained by observing 20 planes of 1µm thick, every 1µm. Each image corresponds to the projection of these 20 planes of a sample area of 318 x 318 µm 2 .

Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. ( 2018). Multi-scale structural changes of starch and proteins during pea

A C C E P T E D M A N U S C R I P T 2.

Statistical analysis

The significant difference between means of measured extrusion variables (Table 1) within a grouped samples extruded using same extruder and die configuration was determined by analysis of one-way ANOVA and Fisher's least significant different (LSD). Analysis of one-way ANOVA was also conducted to determine effect of several levels of extrusion variables on protein solubility (Table 3). All statistical analysis were performed at 5% significance level using Microsoft Excel 2010.

Results and discussion

Native pea flour contained three major components: starch (46.3% d.b.), proteins (23.9% d.b.).

The minor components were ash (2.1% d.b.) and lipids (2% d.b.). The chemical composition was in the range determined by [START_REF] Li | Chemical composition, pasting, and thermal properties of 22 different varieties of peas and lentils[END_REF] for five varieties of yellow peas. The resulting fiber content was 25.7% (d.b.).

Flour melting, extrusion and expansion

The measured melting temperature of pea flour T m was 118°C (MC = 20% w.b.), defined as the temperature at peak offset, was slightly higher than those found by [START_REF] Li | Chemical composition, pasting, and thermal properties of 22 different varieties of peas and lentils[END_REF] in the interval [108, 113°C]. Variation of melting temperature of pea flour with water volume fraction, was fitted by Flory-Huggins equation, R 2 = 0.93 (Appendix, Eq. A1, Fig. A1).

Extrusion parameters and variables are summarized in Table 1. The selected processing conditions, using screw configuration A, resulted in a wide domain of extrusion variables: product temperature T varied between 120 and 165°C, MC between 18 and 26%, and SME between 400 and 1200 kJ/kg (Fig. 1a). The most severe extrusion conditions values corresponding to highest temperature and SME were obtained for sample C1 with low moisture content (21.4%). Conversely, samples E1-E4 were processed at lower temperature (<130°C) and low SME (<100 kJ/kg) using screw configuration B and larger MC (≥26%). Under all conditions, product temperature at the die T was higher than T m . The extrusion domain exceeded that covered in the previous studies on pea extrusion [START_REF] Berrios | Extruded legumes[END_REF][START_REF] Kristiawan | Effect of protein, moisture content and barrel temperature on the physicochemical characteristics of pea flour extrudates[END_REF][START_REF] Li | Extrusion expansion characteristics of samples of select varieties of whole yellow and green dry pea flours[END_REF][START_REF] Maskus | Extrusion processing and evaluation of an expanded, puffed pea snack product[END_REF].

Fair correlation (R 2 =0.74) between T and SME was found, whatever the values of other variables (Fig. 1a). Indeed, higher T and SME values were obtained for lower MC. This general trend, which has not been underlined yet for legume extrusion, is common to starchy products. It is due to the influence of solid friction between flour particles and viscous dissipation in the molten phase [START_REF] Colonna | Extrusion cooking of starch and starchy products[END_REF].

The SME effect on the proteins transformation is complex. The heat due to viscous dissipation can enhance the polymerisation whereas shear causes depolymerisation. Therefore, it is interesting to find how to control SME by processing parameters. This is illustrated in Fig. 1b, where SME was plotted as a function of the ratio of total flow rate to screw speed, Q/N, which is proportional to the filling ratio of screw for a given screw configuration. Good correlation (R 2 =0.86) between SME and Q/N was obtained for the screw configuration involving reverse elements, whatever MC and die geometry. The same trend was observed in the case of twin-screw extrusion of starchy products: SME increases when screw speed increases and decreases when feed rate is inc reased [START_REF] Kristiawan | Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A[END_REF]. Obviously, the SME depends on screw filled length, which changes with screw configuration.

In the applied domain of thermomechanical conditions, the density varied in a large interval (85-1060 kg/m 3 , Table 2). Samples extruded with the configuration B (no restrictive elements) were not expanded, likely because of low temperature and SME. They are called dense samples. Extruded samples with density lower than 200 kg/m 3 had similar aspect to directly expanded starchy snacks or foams. Higher expansion is generally preferable because it favours the obtaining of lighter and crispier products.

Density was negatively correlated with product temperature (T) (R 2 =0.77, Fig. 2a). The same trend was observed for SME (R 2 =0.80 result not shown). On the other hand, MC was correlated positively with foam density (R 2 >0.75 result not shown).

Foam density was inversely related to sectional expansion index (SEI) (R 2 =0.91) for any die geometry (Fig. 2b). This general trend that is known for starchy product extrusion has not been evidenced yet for legumes. Calculation of longitudinal expansion index using Eq. ( 2), LEI = VEI / SEI, led to LEI values lower than 1 for all pea extrudates. Hence, the volumetric expansion was governed by radial expansion. This result is different from that obtained for starch melts, where increasing die length favoured longitudinal expansion [START_REF] Kristiawan | Modeling of starchy melts expansion by extrusion[END_REF].

The impact of extrusion variables (MC, T, SME) on pea flour expansion was the same as on proteinaceous products including legumes [START_REF] Berrios | Extruded legumes[END_REF][START_REF] Li | Extrusion expansion characteristics of samples of select varieties of whole yellow and green dry pea flours[END_REF]. However, contrary to starch expansion, the effect of product temperature on pea flour expansion was positive and large (Fig. 2a). Indeed starch expansion is governed by different mechanisms: nucleation, water vaporization, growth, coalescence and shrinkage of gas bubbles in a homogeneous viscous fluid. The influence of temperature on these mechanisms result in opposite effects on final expansion, and thus on density [START_REF] Kristiawan | Modeling of starchy melts expansion by extrusion[END_REF]. The positive influence of temperature on expansion of pea flour by extrusion, suggests that this phenomenon is not only govern by these mechanisms, but also by rheological changes of material structure linked to the morphology of starch-protein composites.

Unlike starch melt, pea flour melt cannot be considered as a fully homogenous viscous fluid, this will be discussed in the later discussion about the morphology of parietal material of extrudates (section 3.4).

Protein modifications

Proteins proteins were mainly linked by non-covalent interactions and less by disulphide bonds. Pea proteins were mainly composed of salt-soluble globulins (45-60%) and water-soluble albumins (14-30%), with minor acid/alkali soluble-glutelins and alcohol-soluble prolamines, which explains the high solubility in SDS. The low content in protein DT-soluble can be explained by the poor content of native flour in sulphur containing amino acids such as methionine and cysteine which are able to produce disulphide bonds [START_REF] Leterme | Amino acid composition of pea (Pisum sativum) proteins and protein profile of pea flour[END_REF].

According to SE-HPLC elution profile (Fig. 3), SDS-soluble extract was divided into six major fractions: S1 (1.2%), S2 (6.8%), S3 (32.3%), S4a (13.7%), S4b (17.7%), and S5 (20.2%). Pea flour consisted mainly of proteins with intermediate and small sizes having molecular weights ranging from 41 to 91 kDa (S3) and from 9 to 24 kDa (S5) [START_REF] Barac | Profile and functional properties of seed proteins from six pea (Pisum sativum) genotypes[END_REF][START_REF] Mession | Thermal denaturation of pea globulins (Pisum sativum L.)-Molecular interactions leading to heat-induced protein aggregation[END_REF]. Albumin 2 (5-80 kDa) can contribute to S3, S4 and S5 fractions. Some of pea globulins (150-420 kDa), i.e. the convicilin (~290 kDa) and vicilin (~170-180 kDa), make a part of S2.

Legumins are hexameric proteins with subunit linked by disulphide bonds, 300-420 kDa, which contribute to S2, and Albumin 1 (cysteine-rich peptide, ~10 kDa) is part of S5.

Protein solubility of dense samples (E1-E4), extruded at low temperature and SME values was close to that of the native flour (Table 2). With increasing product temperature, beyond 140°C, SDSsoluble proteins decreased from 95% to 35% (R 2 =0.83) (Fig. 4a). Conversely, DTE-soluble proteins increased from 5% to 45% with temperature (R 2 =0.75). Given the strong correlation between SME and T, the same trends were observed on variations of protein solubility with SME (result not shown). This result indicated the formation of SDS-insoluble protein aggregates via protein cross-linking by disulphide bonds, which was confirmed by the negative correlation between solubility in SDS and DTE (R 2 =0.93, result not shown). The best fitting for solubility variations with temperature was obtained using the sigmoid function (see Fig. 4a, R 2 ≥0.75):

Sol. = a/(1 + exp(-k(T-T c ))) (3a)
where Sol. is the solubility (in SDS, DTE…), T is the material temperature measured inside the die and A1). Onset temperature of the events governing the variation of protein solubility, T i , was found using the sigmoid model, see Appendix 3. The loss of protein solubility in SDS started at 146°C, while the onset of formation of DTE-soluble proteins occurred at 125°C. The variation of solubility with SME could be fitted with a similar sigmoid function (result not shown). By subtracting SDS and DTE-soluble proteins from the total protein content in samples (100%), the fraction of non-extracted proteins was found. It resulted from the formation of aggregates linked by other covalent bonds than S-S. This fraction could reach up to 26 % (sample C1, Table 1). Formation of these bonds started massively at a temperature close to 152°C.

The impact of material temperature on size distribution of SDS-soluble proteins of extrudates is illustrated by the variation of fractions identified by SE-HPLC (Fig. 4b). Increasing material temperature led to a marked decrease in the SDS solubility of S1, S2, S3 and S4a fractions following Eqs.

(3) (R 2 >0.85, Fig. 3). The model parameters are reported in Appendix, Table A1. Conversely, ANOVA analysis showed that protein fraction of S4b and S5 did not vary significantly with temperature (Table 3) and they took average values close to 8.2 and 21.8 %, respectively. Each protein fraction had different onset temperature for solubility change, S1 and S2: 151°C, S3: 135°C, and S4a:

147°C, and SME in the range 550-600 kJ/kg. These values are closed to those for the formation of protein aggregates linked by S-S (125°C; 625 kJ/kg) and other covalent bonds (152°C, 550 kJ/kg) (Fig. 4a). As expected, the SDS solubility of S3, S3 and S4a fractions decreases with increasing DTEsoluble and non-extractable proteins, which shows that these fractions become insoluble with the formation of S-S and other covalent bonds.

Thermal induced protein in-solubilisation due to S-S cross-linking has been reported for extrusion of legumes [START_REF] Alonso | Effect of extrusion cooking on structure and functional properties of pea and kidney bean proteins[END_REF][START_REF] Laleg | Structural, culinary, nutritional and anti-nutritional properties of high protein, gluten Free, 100% legume Pasta[END_REF][START_REF] Stanley | Protein reactions during extrusion processing[END_REF] and gluten [START_REF] Pommet | Thermoplastic processing of protein-based bioplastics: chemical engineering aspects of mixing, extrusion and hot molding[END_REF]. Increasing SME favoured proteins cross-linking by S-S and non S-S covalent bonds due to the enhancement of unfolding and re-association of protein aggregates under high shear force [START_REF] Anderson | Changes in disulfide and sulfhydryl contents and electrophoretic patterns of extruded wheat flour proteins[END_REF][START_REF] Camire | Protein functionality modification by extrusion cooking[END_REF][START_REF] Valle | Relationships between processing conditions and starch and protein modifications during extrusion-cooking of pea flour[END_REF]. Although SME is directly correlated to T because of solid friction and viscous dissipation, our results suggest that it is the temperature which influenced directly these changes. Moreover, the ANOVA analysis did not show any significant effect of die geometry (configuration C and D) on protein solubility (Table 3), probably because shear did not contribute to protein transformation. The close protein transformations between two die geometries mean that the main structural changes happened in the screw extruder section and no further changes occurred in long die. ANOVA analysis also demonstrated that there was insignificant effect of moisture content on protein changes for the three conditions (0.18; 0.21; 0.26) (Table 3). The material temperature corresponding to the onsets of proteins cross-linking during extrusion of pea flour were determined for the first time. Both S-S and non S-S covalent bonds contributed to protein in-solubilisation. Della [START_REF] Valle | Relationships between processing conditions and starch and protein modifications during extrusion-cooking of pea flour[END_REF] pretended that the role of S-S was less important than other covalent bonding based

Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. ( 2018). Multi-scale structural changes of starch and proteins during pea

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on the fact that protein aggregates with S-S bonds did not vary much with extrusion conditions. This discrepancy can be attributed to different methods of protein extraction and quantification. In the earlier works, neither sonication-assisted extraction procedure nor precise SE-HPLC for solubleprotein quantification was performed. Moreover, different reagents (DTT in citrate phosphate buffer vs. DTE in SDS-phosphate buffer) and extraction temperature were implemented to disrupt S-S bonds.

The use of DTT in the absence appropriate denaturant (urea, guanidine, or SDS) is less effective because it cannot reduce buried (solvent-inaccessible) disulfide bonds [START_REF] Hermanson | Chapter 2 -Functional Targets for Bioconjugation[END_REF].

Total solubility, color and starch changes

Native pea flour displayed peaks at 5.6°, 9.8°, 11.3°, 15.2°, 17°, 18.2°, 21.9°, 23° and 26.3° on the WAXS diffractograms (Fig. 5a). These peaks are typical for C-type crystallinity pattern of starch from legumes [START_REF] Buleon | Details of the crystalline ultrastructure of C-starch granules revealed by synchrotron microfocus mapping[END_REF]. For extruded samples, these peaks have disappeared, which suggested that starch was amorphous. This is in agreement with the values of T, always larger than T m (see 3.1). The absence of DSC residual gelatinisation (Fig. 5b) confirmed that the extruded samples were amorphous.

The water solubility index of total solids WSI solids of flour and extrudates took into account starch and other soluble components like fibers and proteins. WSI solids was correlated positively with that of starch (R 2 =0.81, result not shown). As protein aggregates resulting from cross-linking of water soluble proteins were not soluble in water, and since only 1.1% (d.b.) of total fibers (13.4% d.b.) in native split pea flour was water soluble [START_REF] Petitot | Impact of legume flour addition on pasta structure: Consequences on its in vitro starch digestibility[END_REF], we supposed that fibers, the third major component in pea flour, were solubilized during extrusion [START_REF] Ralet | Raw and extruded fibre from pea hulls. Part I: Composition and physico-chemical properties[END_REF].

Extruded starches were partially soluble with WSI 50%, i.e. lower than WSI of solids. Both indices increased with temperature (Fig. 6), and also with SME (result not shown). Both temperature and shear energy are known to increase the breakdown of starch granules and macromolecules and subsequently to raise the amount of water-soluble components (from 12 to 55%) compared to starch in native flour (11.7%). Moreover, WSI of total solids was negatively and linearly correlated with WAI (R 2 =0.83, result not shown), suggesting that extrudates that are less soluble in water may absorb more water. Higher WAI indicates the presence of larger starch granule fragments, while higher WSI implies that starch was depolymerized (de [START_REF] De Mesa | Soy protein-fortified expanded extrudates: Baseline study using normal corn starch[END_REF][START_REF] Kirby | An experimental study of screw configuration effects in the twin-screw extrusion-cooking of maize grits[END_REF]. These results are rather confirmatory, since they are common to extrusion of starches [START_REF] Chinnaswamy | Macromolecular and functional properties of native and extrusion-cooked corn starch[END_REF]. However, [START_REF] Mercier | Modification of carbohydrate components by extrusioncooking of cereal products[END_REF] reported that in the temperature domain [90;

250°C] WAI of extruded corn starch increased with WSI, reaching maximum at 175°C. We found that the increase of both WSI indices with material temperature could be fitted sufficiently with sigmoid model (Fig. 6). This model allowed determination of onset temperature of starch solubility increase, close to 115°C. This value is lower than the onset temperatures of protein solubility decrease and formation of S-S bonds. The interval between onset temperature of starch and protein changes can be Extruded materials were darker as shown by the decrease of L* values from 87 to 58 and more reddish and bluish (higher a* and lower b*) with increase of T (Fig. 7a). Moreover, correlations of a* with protein solubility in DTE (R 2 =0.80) and non-extractable proteins (R 2 =0.80) showed that protein aggregations by other covalent bonds occurred at the same time as darkening and increase in redness, i.e. browing (Fig. 7b). Extrudate browning can be related to the development of Maillard reactions between reducing sugars and free amine groups (lysine). Reducing sugars can result from starch breakdown during extrusion [START_REF] Camire | Protein functionality modification by extrusion cooking[END_REF]. The higher intensity of thermo-mechanical treatment, the higher was the transformation of starch and proteins and the interactions between their derivatives.

Consequently, Maillard reactions can be related to the reduction of lysine availability in the extruded pea [START_REF] Asp | Nutritional properties of extruded foods[END_REF][START_REF] Kristiawan | Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A[END_REF]. Lysine is one of the most sensitive and most limiting amino acids in humane diets, so lysine availability is one of nutritional quality criteria for processed legumes [START_REF] Asp | Nutritional properties of extruded foods[END_REF][START_REF] Kristiawan | Effect of protein, moisture content and barrel temperature on the physicochemical characteristics of pea flour extrudates[END_REF][START_REF] Laleg | How the structure, nutritional and sensory attributes of pasta made from legume flour is affected by the proportion of legume protein[END_REF]. Finally, extrudate color can be utilised as indicator of protein aggregation by covalent linkages others than S-S ones; in a first approach for sample screening before analysis of protein solubility using SE-HPLC.

Cell wall morphology

The morphology of starch-protein blend in the cell wall materials of expanded samples was ascertained using CSLM for two samples extruded at similar T, higher than the onset of proteins aggregation by S-S bonds: sample C12 (550 kJ/kg, 136°C) and D11 (720 kJ/kg, 140°C). Sample D11 had slightly higher starch and DTE-protein solubility, likely due to higher SME. For C12 (Fig. 8a).

CSLM micrograph shows small protein aggregates (≈10 µm, green) dispersed among some swollen and stretched starch granules ("ghosts", ≈50 µm, light red), and entrapped in a continuous reddish network, formed by dispersed starch macromolecules. Conversely, CSLM of sample D11 (Fig. 8b) revealed larger stretched protein aggregates connected together (30-50 µm, green) and forming morphology of co-continuous phases with starch macromolecules (reddish), with much less swollen granules. In both cases, the presence of swollen granules and dispersed starch phase was expected, since starch was amorphous and solubility index was about 35%. Together with preceding results (3.2 and 3.3) these images suggest that different states of protein aggregations can lead to various starchprotein morphologies. Hence the composite morphology of the cell wall of expanded pea flour would be governed by the size and continuity of protein aggregates. Their presence may lead to a continuous protein phase which can limit the access of water to starch, and explain the lower values of starch swelling and solubility in pea flour compared to the pure starch with WSI as high as 100% [START_REF] Meuser | Kochextrusion von stärken. Vergleich experimenteller ergebnisse zwischen laborextrudern und produktionsextrudern mittels systemanalyse[END_REF]. Moreover, these results confirmed that pea flour cannot be considered as a homogenous viscous fluid during extrusion, as suggested in chapter 3.1, and they

Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. ( 2018). Multi-scale structural changes of starch and proteins during pea

A C C E P T E D M A N U S C R I P T

could explain the difficulties encountered when measuring its melt viscosity under thermomechanical conditions close to those of extrusion [START_REF] Beck | Effect of different heat-treatment times and applied shear on secondary structure, molecular weight distribution, solubility and rheological properties of pea protein isolate as investigated by capillary rheometry[END_REF].

The changes of morphology can affect the viscosity of the pea flour during extrusion and modify its behaviour during expansion. Although extrusion conditions (SME, T) were very close to each other, density values (103 vs 439 kg/m 3 , see Table 2) indicated that sample D11 was much more expanded than C12. Expansion during extrusion involves the succession of various mechanisms and the influence of extrusion variables on these mechanisms has been recently reviewed [START_REF] Kristiawan | Modeling of starchy melts expansion by extrusion[END_REF]. By increasing interface area between protein aggregates and amorphous starch, like in the case of the co-continuous phases (sample D11), bubble nucleation is increased which favours expansion. Moreover, for composite morphology, bubble coalescence can be reduced because of increased elongational viscosity of the melts, as shown by results for starch/zein composites [START_REF] Chanvrier | Flow and foam properties of extruded maize flour and its biopolymer blends expanded by microwave[END_REF][START_REF] Chanvrier | Mechanical behaviour of corn flour and starch-zein based materials in the glassy state: matrix-particle interpretation[END_REF]. These authors found that the starch-protein blends with co-continuous phases morphology of (like sample D11) had higher elongational viscosity than the blends with the morphology of particles dispersed in a matrix (sample C12). This interpretation was comforted by the fact that sample D11 was extruded with the circular die D, where, due to section contraction, elongational strains were larger than for the slit die C with prevailing shear. Clearly, this interpretation has to be confirmed by studying the rheological behaviour of pea flour envisioned like a composite material of protein aggregates with amorphous starch and by ascertaining the morphology of these materials.

Conclusion

The large domain of hydro-thermo-mechanical conditions of pea flour extrusion led to a large panel of starch and protein chemical changes, and of morphologies of the foams cell wall material. The symbols refer to measured data, and the solid lines represent data fitting using Eqs.:

Multi

𝑇 = 𝑚 × 𝑆𝑀𝐸 + 𝑏 (Fig. 1a), and 𝑆𝑀𝐸 = 𝑏 1 × ( 𝑄/𝑁 ) 𝑏 2 (Fig. 1b). The fitting equations are shown in the Appendix (Table A1) The symbols refer to measured data, and the solid lines represent data fitting using Eqs.: 𝜌 * = 𝑎/ (1 + 𝑒𝑥𝑝 (-𝑘 × ( 𝑇 -𝑇 𝑐 ))) (Fig. 2a), and 𝑆𝐸𝐼 = 𝑏 1 × 𝜌 * ( 𝑏 2 ) (Fig. 2b). The fitting equations are shown in the Appendix (Table A1) The open symbols refer to measured data of flour while the closed ones for extrudates. The solid lines represent data fitting using Eq. 3a: 𝑆𝑜𝑙. = 𝑎/ (1 + 𝑒𝑥𝑝(-𝑘 × (𝑇 -𝑇 𝑐 ))).

Sol. indicates either soluble proteins in specified reagents (Fig. 4a) or SDS-soluble protein fractions (Fig. 4b). T i is the temperature at the onset of solubility change. The fitting equation is shown in the Appendix (Table A1) The symbols refer to measured data, and the solid lines represent data fitting using Eqs.: 𝐿 * , 𝑎 * , 𝑏 * = 𝑎/ (1 + 𝑒𝑥𝑝 (-𝑘 × ( 𝑇 -𝑇 𝑐 ))) (Fig. 7a), and 𝑆𝑜𝑙. 𝐷𝑇𝐸 = 𝑎/ (1 + 𝑒𝑥𝑝(-𝑘 × ( 𝑇 -𝑇 𝑐 ))) and 𝑛𝑜𝑛 -𝑒𝑥𝑡𝑟𝑎𝑐. = 𝑚 × 𝑎 * + 𝑏 (Fig. 7b). Sol. DTE indicates DTE-soluble proteins while non-extrac. refers to non-extractable proteins. The fitting equations are shown in the Appendix (Table A1) The morphology of cell wall changed from dispersed small protein aggregates embedding some swelled starches (Fig. 8a) to a bi-continuous matrix between large protein aggregates and amorphous starch (Fig. 8b).

Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J. The comparison was done between means of measured variables of samples made from same configuration of extruder and die. The reported values are the mean of three determinations (𝜈 1 -𝜒 1 𝜈 1 2 ) (A1)

where 𝑇 𝑚 ° is the melting temperature of anhydrous starch (in K), R is the gas constant (8.31 J/mol.K), Δ𝐻 𝑢 is the melting enthalpy per mole of monomer unit (or anhydroglucose) (in J/mol), V u /V 1 is the ratio of molar volume of the monomer unit to the molar volume of water (dimensionless), and 𝜒 1 is the reported in literature for starches (Colonna & Buléon, 1994) 2 .

Fitting parameters

Table A1. Fitting of measured extrudate properties For T→∞ values y ∞ are a and 0 for k positive and negative, respectively.

For T→ -∞ values y -∞ are 0 and a for k positive and negative, respectively.

The derivative of the sigmoid function is

 )  )  )  )   2

  a, b, b 1 , b 2 , k, m, T c parameters in fitting equations a* one of three coordinates of CIE color space which represents redness b* one of three coordinates of CIE color space which represents coordinates of CIE color space which represents lightness LEI longitudinal expansion index Δ𝐻 𝑢 melting enthalpy per mole of monomer unit (or anhydroglucose) (in kJ/mol) MC moisture content, in wet basis M W molecular weight Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T

  ., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T

  on size distribution using SE-HPLC. During the second extraction, the pellet was suspended in a 5mL of the SDS-phosphate buffer containing 20 mM of dithioerythritol (DTE) at 60°C for 60 min, sonicated for 5 min and centrifuged. The supernatant, referred as DTE-soluble proteins, was sampled for SE-HPLC analysis. The combination of sonication and DTE causes disruption of disulphide bonds. The remaining pellet made of non-extractable proteins represents proteins linked by other covalent bonds than S-S ones (e.g. isopeptides bonds). Protein solubility (%) in a specified reagent (SDS or DTE) is expressed as the percentage of integrated area to that of all extractable proteins of a ACCEPTED MANUSCRIPT Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T reference sample D8. As explained in detail later, D8 has been chosen because it has maximum total extractable proteins.

  Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T

  in native flour consisted of a high fraction of SDS-soluble proteins (91.9%), a low fraction of DTE-soluble proteins (8.1%), and no traces of non-extractable proteins. This indicates that Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T

T

  c is the temperature at inflexion point, and a and k are the parameters in sigmoid model (Appendix 3), with Sol(T c ) = a/2 (3b) and k is linked to the rate and magnitude of solubility change: k = 4×dSol/dT(T c )/a (3c) Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T Numerical values of these parameters are summarized in Appendix (Table

  Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T considered as experimental window to obtain extruded products having sufficient soluble starch and to avoid massive in-solubilisation of proteins.

Figure captions Fig. 1 .

 captions1 Figure captionsFig. 1. Domaine of extrusion variables: moisture content (MC), product temperature (T) and specific mechanical energy (SME) (a) Variation of T with SME. Data dispersion is due to differences in die configuration, imposed die temperature, and total mass flow rate.

Fig. 2 .

 2 Fig. 2. Macro structure of pea extrudates (a) Variation of density (ρ * ) with product temperature (b) Relation between sectional expansion index (SEI) and density

Fig. 3 .

 3 Fig. 3. SE-HPLC elution profile of SDS-soluble proteins of pea flour and extrudates (C2 and C12) at different extrusion temperature

Fig. 5 .

 5 Fig. 5. Amorphous extruded samples (a) Absence of crystallinity peaks in WAXS spectrum (b) Absence of DSC gelatinisation enthalpy

Fig. 8 .

 8 Fig. 8. CSLM images of cell wall of foams, extruded at close T values (138°C +/-2°C). Proteins were stained as green with fuchsin acid. Starch was stained red with PPA.

FigFigFigFig

  Fig. 1.

FigFigFig

  Fig. 5.

  Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T

  . The values followed by a different superscript in each column are significantly different (p< 0.05). Q F = mass flow rate of pea flour Q W = mass flow rate of water ACCEPTED MANUSCRIPT Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T N = screw speed T die = imposed die temperature T = product temperature MC = moisture content SME = specific mechanical energy

*

  Fig. A1. Change of melting temperature (T m ) with the water volume fraction v 1 . The points refer to melting temperature obtained by DSC. The solid lines refer to the best fit using Flory-Huggins equation (Eq. A1)

  ., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea A C C E P T E D M A N U S C R I P T Flory-Huggins starch-water interaction parameter (dimensionless).  1 was obtained under the assumption that the density of anhydrous flour is the same as anhydrous starch, 1500 kg/m 3 (Della Valle & Vergnes, 1994) 1 . Fitting the experimental data on T m and  1 by Eq. A1, see Fig. A1, we obtained the following results: 𝑇 𝑚 ° = 168.4 °C, Δ𝐻 𝑢 = 56.49 kJ/mol, 𝜒 1 = 0.4999. The computed values of melting temperature and melting enthalpy of anhydrous pea flour were in accordance with those

  FigData seriesEquation Parameters

  Fig.7bDTE-soluble proteins (%)Sol. DTE = a/(1 + exp(-k × (T-T c ))) a T c k R 2

  the tangent at the inflection point with the line parallel with the axis T at a distance of y -∞ stands for the temperature of the solubility change onset T i :

Table 1 .

 1 Summary of extrusion parameters and variables

				Expanded samples
			Extruder configuration A and die configuration C
			Operating conditions			Measured variables
	Trial	MC	Q F	Q W	N	T die	T	SME	Die pressure
		%w.b.	(kg/h)	(kg/h)	(rpm)	(°C)	(°C)	(kJ/kg)	(bar)
	C1	21	10	1.13	700	150	162 a	1156 a	47 h
	C2	21	10	1.13	500	150	158 b	1002 b	58 gh
	C3	21	10	1.13	300	150	139 de	754 ce	84 e
	C4	21	20	2.26	700	150	159 ab	830 c	83 e
	C5	21	20	2.26	500	150	151 c	698 def	102 d
	C6	21	20	2.26	300	150	134 f	549 g	134 b
	C7	26	20	3.53	300	150	127 g	448 h	100 d
	C8	26	20	3.53	500	150	142 d	627 f	78 ef
	C9	26	20	3.53	700	150	152 c	690 ef	70 fg
	C10	21	20	2.27	700	130	161 ab	955 b	121 c
	C11	21	20	2.27	500	130	153 c	770 cd	133 bc
	C12	21	20	2.27	300	130	136 ef	549 g	179 a
			Extruder configuration A and die configuration D
			Operating conditions			Measured variables
	D1	21	10	1.12	700	-	157 a	1107 a	42 h
	D2	21	10	1.12	500	-	152 b	967 b	46 gh
	D3	21	10	1.12	300	-	136 e	754 d	76 ce
	D4	26	20	3.56	700	-	148 c	618 fg	43 gh
	D5	26	20	3.56	500	-	138 de	524 h	63 ef
	D6	26	20	3.56	300	-	123 g	427 i	80 cd
	D7	21	20	2.26	300	-	132 f	549 gh	106 b
	D8	21	20	2.26	500	-	149 bc	663 ef	68 def
	D9	21	20	2.26	700	-	160 a	779 d	58 fg
	D10	19	20	1.56	700	-	159 a	883 c	63 ef
	D11	19	20	1.56	500	-	140 d	721 de	86 c
	D12	19	20	1.56	300	-	130 f	567 gh	124 a
					Dense samples
			Extruder configuration B and die configuration D
			Operating conditions			Measured variables
	E1	31	20	6	350	130	122 b	39 b	5 a
	E2	35	20	8	300	120	115 c	47 ab	10 a
	E3	28	20	5	300	135	129 a	53 a	5 a
	E4	26	20	4	300	135	129 a	55 a	5 a

Table 2 .

 2 Physico-chemical characteristics of some extruded samples

		SEI	Densit
	Trial	c	y a	Starch properties a			Protein solubility b						Color a
				WSI	WSI	WA			Non-
			*	(%)	(%)	I	SDS-	DTE-	extr.	SDS-soluble protein fractions	L* a* b*
							sol.	sol.
			(kg/m 3 ) solids	starch		(%)	(%)	(%)	S1 S2 S3 S4a S4b S5
							Expanded samples
		10.				3.8				0.					20.	57.	11.	36.
	C1	3	120	46.1		6	35.3	38.5	26.2	6 2.2 4.7 3.6 3.9	3	9	8	5
		11.				3.4				0.					20.	61.	33.
	C2	2	116	46.3	37.0	3	43.1	45.9	11.0	7 4.0 5.9 4.2 8.0	3	8 8.8	4
						3.5				0.					21.	64.	35.
	C4 9.1	167	47.9	43.9	7	45.4	38.7	15.9	7 4.9 7.9 5.1 5.2	8	0 8.1	8
						3.4				2.	13.	12.		12.	20.	69.	34.
	C5 7.6	234	47.5		4	68.6	31.2	0.3	3	0	9	7.6	4	3	2 5.0	3
										3.	17.	22.	10.		21.	74.	41.
	C6 4.9	450				82.9	15.7	1.4	0	4	4	5	8.1	5	1 4.4	0
						4.1				3.	15.	21.			19.	75.	39.
	C7 3.5	659	28.1	30.1	2	77.3	20.2	2.5	1	4	7	9.9 7.5	7	8 3.2	9
						3.4				2.	14.	18.			20.	72.	38.
	C9 7.3	197	50.4	54.9	8	72.8	23.2	4.1	2	9	4	9.1 7.4	8	4 4.1	6
						3.0				0.					20.	68.	34.
	C10 6.4	191	45.4		8	45.0	34.9	20.2	6 4.3 6.5 4.6 8.5	5	3 7.6	0
										1.	11.	13.			21.	70.	36.
	C11 7.4	195				62.3	30.7	7.0	3	4	5	7.5 6.7	9	3 6.0	7
						3.4				2.	15.	21.	10.		21.	73.	40.
	C12 4.5	439	44.9	32.5	0	77.9	18.5	3.6	3	7	0	1	7.8	0	4 4.8	7
		15.				4.0				1.		12.			22.	69.	36.
	D1	0	85	44.9	35.6	3	58.7	29.4	12.0	3 9.9	3	6.9 6.2	0	6 6.6	6
		14.				3.0				2.	14.	17.			22.	72.	39.
	D2	5	109	43.6		8	71.7	25.3	3.0	0	3	1	8.8 7.4	2	1 5.0	1
						3.2				2.	16.	21.	10.		21.	73.	40.
	D3 6.8	452	47.0		8	80.9	17.4	1.7	8	7	6	3	8.1	4	4 4.0	8
						4.5				2.	14.	22.			18.	76.	42.
	D6 3.9	818	27.2	26.8	6	75.2	20.5	4.2	9	4	4	9.4 7.1	9	4 3.6

1 Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea a Three repetitions b Two repetitions c Thirty-five repetitions

Table 3 .

 3 Insignificant effect of extrusion variables on protein solubility (one-way ANOVA, p<0.05)

		Factor	F-value	Critical F-value
	SDS-soluble protein fraction (%) Temperature
	S4b		2.825*	3.682
	S5		0.394*	3.682
	SDS-soluble proteins (%)	Moisture content	0.750*	3.682
	DTE-soluble proteins (%)		0.873*	3.682
	Non-extractable proteins (%)		0.490*	3.682
	SDS-soluble proteins (%)	Die geometry	2.053*	4.494
	DTE-soluble proteins (%)		2.774*	4.494
	Non-extractable proteins (%)		0.915*	4.494

Acknowledgements

Authors are thankful to Joëlle Bonicel (INRA-IATE) for protein SE-HPLC analysis, Roselyne Desirest and Bruno Pontoire (INRA-BIA), and Kerstin Sauther and Andrea Butterbrodt (KIT) for excellent technical assistance.

Comment citer ce document : Kristiawan, M., Micard, V., Maladira, P., Alchamieh, C., Maigret, J.-E., Réguerre, A.-L., Emin, M., Della Valle, G. (2018). Multi-scale structural changes of starch and proteins during pea

Graphical abstract

The design of high-protein expanded foods is still a challenge, likely due to the reactivity of protein components under thermomechanical treatment and its effect on extrudate structure and texture. Material temperature governs concomitant starch and protein changes during pea flour extrusion. Protein insolubilization, mainly due to S-S bonds, is triggered at T≈125°C, and contributes to expansion by morphology changes. CSLM micrographs of two samples extruded under similar conditions show different expansion (density *) and morphology of amorphous starch/protein aggregates. These differences are probably due to slight variations in specific mechanical energy (SME), moisture content (MC) or strain at the die.