Sandrine Pavoine
email: sandrine.pavoine@mnhn.fr

Michael B Bonsall

Amaël Dupaix

Ute Jacob

Carlo Ricotta

Sandrine Pavoine

From phylogenetic to functional originality: guide through indices and new developments

Keywords: Biodiversity, carnivores, conservation priorities, entropy, simulations, species distinctiveness

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Introduction

 [START_REF] Atkinson | Introduced animals and extinctions[END_REF]recommended that "given two threatened taxa, one a species not closely related to other living species and the other [a] widespread and common species, it seems reasonable to give priority to the taxonomically distinct form". [START_REF] May | Taxonomy as destiny[END_REF] and [START_REF] Vane-Wright | What to protect? Systematics and the agony of choice[END_REF] therefore developed equations to measure how taxonomically distinct a species is compared to a reference set of species. A species was then defined as distinct if it is not closely related to other living species, a concept also known as evolutionary isolation [START_REF] Jensen | I-HEDGE: determining the optimum complementarity sets of taxa for conservation using evolutionary isolation[END_REF]). Following Faith (1992), [START_REF] Pavoine | Is the originality of a species measurable?[END_REF] extended the concept of the isolation of a species on a phylogenetic tree to that of originality. They defined originality as the potential rarity of the species' features, where a feature means a particular state of a character. They also considered 'strict uniqueness' as the number of features possessed by this species yet not those shared with the others. Recently, there have been more studies directed on the functional attributes of species: a finite number of physiological, anatomical, behavioural or life-history traits reflecting the roles that species play within communities and ecosystems (e.g. [START_REF] Petchey | Low functional diversity and no redundancy in British avian assemblages[END_REF][START_REF] Mouillot | Do we protect biological originality in protected area? A new index and an application to the Bonifacio Strait Natural Reserve[END_REF][START_REF] Magnuson-Ford | Rockfish (Sebastes) that are evolutionarily isolated are also large, morphologically distinctive and vulnerable to overfishing[END_REF]Schmera et al., 2009a;[START_REF] Thompson | Little evidence for limiting similarity in a long-term study of a roadside plant community[END_REF][START_REF] Buisson | Toward a loss of functional diversity in stream fish assemblages under climate change[END_REF][START_REF] Mouillot | Rare species support vulnerable functions in high-diversity ecosystems[END_REF][START_REF] Godet | Dissociating several forms of commonness in birds sheds new light on biotic homogenization[END_REF][START_REF] Rosatti | Loss of phylogenetic and functional originalities of woody cerrado species in simulated extinction scenarios[END_REF]. This diversity of approaches led different authors to use the terms distinctiveness, originality and uniqueness in different meanings. Sometimes two expressions have been used to designate the same concept and sometimes a single word was used to mean two different things. Also in the literature there is confusion between the concepts and the methods used to associate quantitative measures to these concepts. Notably originality was used by [START_REF] Pavoine | Is the originality of a species measurable?[END_REF] to design a concept. It was then used again by [START_REF] Buisson | Toward a loss of functional diversity in stream fish assemblages under climate change[END_REF] to designate a measure: the distance, in a functional space, between a species position and the centroid of the space. Generalizing [START_REF] Buisson | Toward a loss of functional diversity in stream fish assemblages under climate change[END_REF] framework, [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF] used the expression "originality" to designate the average phylogenetic (patristic) distance to all other species. The fact of being taxonomically distinct was introduced by Atkinson as a concept but "evolutionary distinctiveness" is often used to name an index also known as the "Fair Proportion" measure [START_REF] Isaac | Mammals on the EDGE: conservation priorities based on threat and phylogeny[END_REF][START_REF] Jensen | I-HEDGE: determining the optimum complementarity sets of taxa for conservation using evolutionary isolation[END_REF]; see also Table 1). The concept associated with "evolutionary distinctiveness" was instead often referred to as evolutionary isolation [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF]).

Hereafter we use originality as the core, unifying concept and strict uniqueness as a special case. As a proposal for a unified semantic framework, we define the originality of a given species in a set of species as the rarity of its biological characteristics. Originality can emanate from any characteristics of the species. Notably, it can integrate the evolutionary history (phylogenetic originality) or the functional traits (functional originality) of species. This definition generalizes the definition [START_REF] Pavoine | Is the originality of a species measurable?[END_REF] initially proposed. We consider originality synonymous to the following expressions: distinctiveness (e.g. [START_REF] Atkinson | Introduced animals and extinctions[END_REF]; isolation (e.g. [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF]; degree of uniqueness (e.g. [START_REF] Brooks | Why and how might genetic and phylogenetic diversity be reflected in the identification of key biodiversity areas?[END_REF][START_REF] Ricotta | Measuring the functional redundancy of biological communities: a quantitative guide[END_REF]. We consider originality antonymous to the concept of redundancy (e.g. [START_REF] Buisson | Toward a loss of functional diversity in stream fish assemblages under climate change[END_REF][START_REF] Ricotta | Measuring the functional redundancy of biological communities: a quantitative guide[END_REF]. We define strict uniqueness as the minimum difference with any other species in a set. We consider strict uniqueness as a special case of originality. From a biodiversity perspective, strict uniqueness is the amount of diversity that is solely supported by the focal species (driven by unshared characteristics of the species). In contrast, originality is the full contribution of the species to the biodiversity of the set [START_REF] Pavoine | Is the originality of a species measurable?[END_REF].

Both phylogenetically original and endangered taxa have recently been the focus of conservation actions [START_REF] Isaac | Mammals on the EDGE: conservation priorities based on threat and phylogeny[END_REF]. Depending on the shape of the phylogenetic tree (imbalance and 'tippiness', [START_REF] Heard | Phylogenetically patterned speciation rates and extinction risks change the loss of evolutionary history during extinctions[END_REF], the loss of entire species-poor clades that contain original species could indeed lead to dramatic loss in taxonomic/phylogenetic diversity [START_REF] Purvis | Non-random extinction and the loss of evolutionary history[END_REF]. In contrast, as far as we are aware, very few conservation actions have focused on functionally original and endangered species. Yet, [START_REF] Mouillot | Do we protect biological originality in protected area? A new index and an application to the Bonifacio Strait Natural Reserve[END_REF], for example, found that protecting the most functionally original species protects high functional fish diversity in the Bonifacio Strait Natural Reserve. In food webs, intermediate species (herbivores) that tend to be more trophically original (they share no or few prey and predators with other species) might be more prone to secondary extinctions. Furthermore, their loss might have great effects on trophic diversity due to their relative originality [START_REF] Petchey | Trophically unique species are vulnerable to cascading extinction[END_REF]. The concept of species originality has also been studied in ecology and associated with key ecological processes, such as community assembly, ecosystem functioning, and species extinction. Original species could be more likely to invade or colonize, and in addition may have less impact on resident species [START_REF] Strauss | Exotic taxa less related to native species are more invasive[END_REF][START_REF] Strayer | Understanding the long-term effects of species invasions[END_REF]. Species original in their functional traits might make a large contribution to ecosystem functions and services, such as gross photosynthetic rate [START_REF] Petchey | How do different measures of functional diversity perform?[END_REF].

Unique functions of original species in their ecosystems reinforce the importance of originality indices for conservation biology. Developing and comparing measures of originality is thus critical for their efficient use in conservation.

As highlighted above, species originality has been primarily measured from phylogenetic trees. Consequently the methods that were first developed to measure species originality from a phylogeny are now being adapted and applied to the analysis of functional traits. This translation raises new issues on the measurement of functional originality. Indices of phylogenetic originality rely on the tree structure of the phylogeny. Adapting these indices to functional originality thus requires the definition of functional trees (or dendrograms) with a risk of distorting the information provided by functional traits. This is exemplified with the clustering approach used to define the functional tree [START_REF] Mouchet | Towards a consensus for calculating dendrogram-based functional diversity indices[END_REF][START_REF] Petchey | A functional guide to functional diversity measures[END_REF]. Among the indices of phylogenetic originality, the quadratic entropy(QE)-based index developed by [START_REF] Pavoine | Is the originality of a species measurable?[END_REF] was defined for (ultrametric) phylogenetic trees, where the distance from tips to root is constant, which also is a property of functional trees obtained by clustering methods. Here, we extend this QE-based approach to any (phylogenetic or functional) dissimilarity matrix among species. We compare these originality indices related to QE to a range of existing indices introduced in the literature in their ability to discriminate species in terms of their functional originality (Table 1; [START_REF] May | Taxonomy as destiny[END_REF]Eiswerth and Haney, 1992;[START_REF] Redding | Incorporating genetic distinctness and reserve occupancy into a conservation priorisation approach[END_REF][START_REF] Ricotta | A parametric diversity measure combining the relative abundances and taxonomic distinctiveness of species[END_REF][START_REF] Redding | Incorporating evolutionary measures into conservation prioritization[END_REF]; see also [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF] for a review). We selected originality indices amongst the most used in the literature. We use numerical simulations and a case study to evaluate the strengths and differences across the range of originality indices. In particular, we evaluate 1) whether measures of phylogenetic originality could serve as a proxy for measures of functional originality in conservation and ecological studies;

2) whether the transformation of functional data into functional trees modifies the way species are ranked according to their measured originalities compared to approaches that directly rely on pairwise functional dissimilarities among species;

3) more generally, whether different indices provide different views on how original species are from each other, hence reflecting the range of ecological and evolutionary processes that generated patterns of originality.

We discuss our results in light of recent developments in the assessment and measurement of a multidimensional view of biodiversity [START_REF] Pavoine | Measuring biodiversity to explain community assembly: a unified approach[END_REF], with the aim to identify (and preserve) the ecological and historical processes that drive biodiversity dynamics.

Methods

A variety of originality indices 2.1.1. Phylogenetic originality indices

Vane [START_REF] Vane-Wright | What to protect? Systematics and the agony of choice[END_REF] were probably the first to define a cladistic (taxonomic) measure of originality. Their measure was defined as inversely proportional to the number of internal nodes between the focal species (tip) and the root of the cladistic tree. An improvement to this originality measure (discussed in an earlier study by [START_REF] May | Taxonomy as destiny[END_REF] has considered the effects of unresolved nodes by counting not simply the number of nodes between tip and root but rather the number of branches descending all such nodes. This improved index of species' originality can be applied to any phylogenetic tree. Hereafter we will refer to it as index M.

More recently, other measures have been suggested that consider branch lengths on the phylogenetic tree (Table 1; Fig. 1):

i) The pendant edge (PE, e.g. [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF] index is defined as the length of the branch that connects a species to the rest of the tree.

ii) The fair proportion index (FP, [START_REF] Redding | Incorporating genetic distinctness and reserve occupancy into a conservation priorisation approach[END_REF] distributes the phylogenetic diversity (sum of branch lengths) contained within a tree uniquely among the species at the tips. This is achieved by dividing the shared evolutionary history represented by a branch equally among its daughter species at the tips.

iii) The Equal-Split index (ES, [START_REF] Redding | Incorporating evolutionary measures into conservation prioritization[END_REF]) also distributes the phylogenetic diversity contained within the tree uniquely among the species at the tips. However, it achieves this by dividing the shared evolutionary history represented by a branch equally among its daughter branches.

Insert Fig. Considering a set of N species, Eiswerth and Haney (1992) and [START_REF] Ricotta | A parametric diversity measure combining the relative abundances and taxonomic distinctiveness of species[END_REF] suggested an alternative measure that allowed genetic and taxonomic distances to be included directly in measures of originality. It consists of computing pair-wise genetic or taxonomic distances among species and then obtaining the average distance between a focal species and all others (N-1 species) in the set. We refer to this measure as the average distance index (AV). It is clear that this index has broader applications: it can be applied to any distances among species be they genetic, taxonomic, phylogenetic, or functional. Index AV is related to Schmera et al. (2009b) functional value of a species (FV): FV=[(N-1)*AV]/N. The conclusions we obtain below for AV also applies to FV because these two indices similarly order species from the least to the most original one. Below, we compare AV to the shortest distance between the focal species and all others in the set (hereafter referred to as the 'nearest neighbour' index, NN).

The special case of the QE-based index framework

To define the QE-based index (hereafter referred to simply as Qb), [START_REF] Pavoine | Is the originality of a species measurable?[END_REF] considered a matrix D=(d ij ) 1≤i≤N,1≤j≤N of dissimilarities among N species. The dissimilarity d ij between any two species i and j was calculated on an ultrametric, phylogenetic tree as the sum of branch lengths between each of them and their most recent ancestor. These dissimilarities are ultrametric as they satisfy the following property:

d ij ≤max(d ik ,d jk ) for all i,j,k.
Let p=(p 1 , ..., p i , ..., p N ) be a vector of species' relative abundance (

1 1 N i i p   
) in an hypothetical assemblage. The average dissimilarity among individuals from this assemblage is an established measure of diversity [START_REF] Rao | Diversity and dissimilarity coefficients: a unified approach[END_REF][START_REF] Pavoine | Hierarchical partitioning of evolutionary and ecological patterns in the organization of phylogenetically-structured species assemblages: application to rockfish (genus: Sebastes) in the Southern California Bight[END_REF]:

  , N N i j ij i j Q p p d    p D .
The index Qb of species' originality is the value of p i a species i should have to maximize Q (Table 2). The value of p i that leads to the maximum possible value of Q reflect the originality of species i. Indeed, to a certain extent, the more abundant original species are compared to redundant species, the more diversity there is in a set of species. However, this index Qb is critically dependent on the use of dissimilarities derived from an ultrametric tree (Table 2).

Table 2

Details on how to calculate the originality indices Qb and Rb.

Diversity index Originality index

Q

Consider that D is a matrix of patristic distances between species derived from a phylogenetic or functional tree (Fig. 2). The value of p i that lead to the maximum possible value of Q applied to D is equal to

N N N i ij ij j i j Qb     
where δ ij is the value at the ith row and jth column of the inverse of D. [START_REF] Pavoine | Is the originality of a species measurable?[END_REF] restricted Qb to ultrametric dissimilarities in D.

Indeed without this property, the vector p that maximizes Q may not be unique and could take null values (zeros) for several species.

R

Consider a given matrix D=(d ij ) 1≤i≤N,1≤j≤N of dissimilarities among N species with the only conditions that d ij =d ji for any i,j, d ij >0 for any i≠j, and d ii =0 for any i. The maximum of R over p is the first eigenvalue of D.

Its unique maximizing vector is the squared first eigenvector of D (proofs in Appendix A). This maximizing vector is our index Rb.

The new index

Originality can thus be defined as the amount of abundance a species should have in a theoretical community to provide the maximally, theoretically possible biodiversity to this community. Such a reasoning however means that the measurement of species originality depends on how biodiversity itself is measured. In their study, [START_REF] Pavoine | Is the originality of a species measurable?[END_REF] used Q as the reference biodiversity index. A particularity of Q is that it preferentially weights common species over rare species. However, recent studies have focused on profiles of diversity indices where rare versus common species are weighted with more or less importance [START_REF] Jost | Entropy and diversity[END_REF][START_REF] Pavoine | Hierarchical partitioning of evolutionary and ecological patterns in the organization of phylogenetically-structured species assemblages: application to rockfish (genus: Sebastes) in the Southern California Bight[END_REF][START_REF] Chao | Phylogenetic diversity measures based on Hill numbers[END_REF][START_REF] Leinster | Measuring diversity: the importance of species similarity[END_REF]. Changing the relative importance given to rare versus common species in functional or phylogenetic diversity measurements has an impact on the amount of abundance a species should have to provide the maximally, theoretically possible biodiversity to a community.

Most of these studies rely on the Hill numbers [START_REF] Hill | Diversity and evenness: a unifying notation and its consequences[END_REF]:

    1 1 , 0, 1 N q q q i i D p q q          p
where q modifies the relative importance given to rare versus common species: the sensitivity of q D to rare species decreases with q [START_REF] Patil | Diversity as a concept and its measurement[END_REF]. The limiting case (q→1) serves as a reference where species are weighted directly by their relative abundances (p i 's)

without favoring either rare or common species [START_REF] Jost | Entropy and diversity[END_REF]. In the case where the d ij 's are defined in the range [0,1], 1/(1-Q) is a generalization of 2 D that includes (functional or phylogenetic) distances among species [START_REF] Ricotta | Diversity partitioning of Rao's quadratic entropy[END_REF]. The fact that the quadratic diversity (Q) gives high weight to abundant species compared to rare species can be viewed as a weakness when rare species are considered as key drivers of biodiversity of conservation interest. Developing this, we propose an index to contrast quadratic diversity (Q) by weighing rarity over commonness (see Appendix A):

  1 1 , N N i j ij i j R p p d      p D
In the particular case where the d ij 's are defined in the range [0,1], R-1 is a generalization of Hill number 0.5 D that includes functional or phylogenetic dissimilarities among species (Appendix A).

Our new index, R, complements Q, both by the similarity of their formulas and by their relatedness to the Hill numbers. Both these indices (Q & R) are anchored within the broader literature on entropy, species diversity, and functional and phylogenetic diversity (see details in Appendix A). For example, when species have even relative abundances, i.e. p i =1/N for all i, then R equals MFAD, an index of diversity introduced by Schmera et al. (2009a):

  1 1 1 N N ij N i j MFAD d      D .
As for index Q, the values of p i that lead to the maximum possible value of R also reflect species originalities. Increasing the abundance of original species compared to redundant species to a certain extent increases the diversity of the set of species (see Appendix A for a simple example). Using the vector of p i 's that maximizes R, instead of Q, should however provide an alternative view on species' originalities (Table 2). We refer to this vector as Rb.

Compared to Qb, an advantage of Rb is that it can be applied to any dissimilarities (even those that are not ultrametric). However, whether Rb provides novel interpretation to species' originality will be analyzed below.

Case studies

We use both simulation studies and an empirical dataset (on European carnivores) to investigate the measurement of functional originality. For each case (simulation or empirical dataset), we computed all the indices introduced in Table 1 as specified in Fig. 2. We calculated functional dissimilarities among species from raw data using the Euclidean distance metric with quantitative traits in the first case study; and Gower distance [START_REF] Gower | A general coefficient of similarity and some of its properties[END_REF] with a mix of quantitative and nominal traits in the second case study. We obtained functional trees from functional distances using UPGMA and Ward methods (R function hclust, parameter "average" and "ward.D2", respectively; R Core Team 2016).

Insert Fig. 2. Single-column fitting image

Simulations

For the simulation case study, our objective was to analyze functional originality when traits evolved under a Brownian motion model. Indeed, the Brownian model of trait evolution assumes constant rates of trait changes through time. Under this model, trait-based distances between species are expected to be strongly correlated with phylogenetic distances. We thus chose the Brownian model to evaluate whether, in this extreme, simplified scenario, measures of phylogenetic originalities effectively acted as proxies for measures of functional originalities. If phylogenetic and functional originalities are different even when traits are simulated under a Brownian model of evolution, then the use of phylogenetic originality measures as proxies for functional originality measures would be poor. We also wanted to evaluate whether the correlations between phylogenetic originality measures and functional originality measures depended on methodological choices such as the originality index chosen, the method used to obtain functional dendrograms, the number of traits considered.

Our a priori hypothesis was that, using Rb, AV and NN, functional originality measures would better reflect phylogenetic originality measures. Indeed, these indices are calculated using raw functional data with minimal methodological assumptions and thus minimal data distortion. In (iv) asymmetric nonultrametric trees (NU model, where the distance from tips to root is not constant). In the asymmetric trees the topology was generated by splitting randomly the edges (function "rtree" in ape package in R, [START_REF] Paradis | APE: analyses of phylogenetics and evolution in R language[END_REF]) and branch lengths were simulated using a log-normal distribution (with LogN(0,1)). Nonultrametric trees represent unequal evolutionary rates in different parts of the phylogeny. They led to asymmetric distributions of species' originalities with many redundant species and a few original ones. We simulated 1000 trees per model with 2 7 =128 tips. One, 25 or 50 traits were simulated for each phylogenetic tree, according to a Brownian model with parameters σ=1 and θ=0 (function "rTraitCont" in ape package).

Our analysis proceeds by first analyzing the effect of the clustering approach (either UPGMA or Ward) on functional originalities using Spearman correlations for each originality index. Next we analyzed the Spearman correlations between indices and detailed the correlations between Rb and the other indices calculated with functional data (using one, 25 or 50 traits) for each different trait evolution modes (BIRTH, ROOT, TIPS, or NU models of trait evolution) under different functional (UPGMA vs Ward) dendrograms. For tree-based metrics, correlations with Rb were analyzed with centred Principal Component Analysis using the number of traits, the model of trait evolution and the method for tree construction as supplementary variables (using package 'ade4' in R; Dray and Dufour, 2007). Then we analyzed the Spearman correlations between phylogenetic originality measures and functional originality measures for each originality index and simulation case. We used Spearman correlations in all cases as the high number of simulations restricted checking the shape of the relationships between phylogenetic and functional originality measures for each scenario, each originality index and between originality indices.

Functional and phylogenetic originalities of carnivore species in Europe

We investigated the phylogenetic and the functional originalities of European carnivores. We based our study on [START_REF] Temple | The status and distribution of European mammals, Office for Official Publications of the European Communities[END_REF] who identified 38 European Carnivora species.

Among these species, four were introduced into Europe after 1500 A.D. (Herpestes javanicus, Neovison vison, Nyctereutes procyonoides and Procyon lotor), and seven were defined as marginal in Europe (Cystophora cristata, Erignathus barbatus, Martes zibellina, Odobenus rosmarus, Pagophilus groenlandicus, Felis chaus and Mustela sibirica). The qualification of marginal occurrence was attributed to these latter species as less than 1% of their population or of their range lies in Europe [START_REF] Temple | The status and distribution of European mammals, Office for Official Publications of the European Communities[END_REF]. We took phylogenetic data from the Carnivora phylogeny established by [START_REF] Nyakatura | Updating the evolutionary history of Carnivora (Mammalia): a new species-level supertree complete with divergence time estimates[END_REF]. Trait data were obtained from the PanTHERIA database [START_REF] Jones | PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals[END_REF]. Among the 53 traits present in the database, we eliminated those for which values were missing for more than a quarter of the species. To avoid circularity in our reasoning, we also discarded geographic traits. Indeed, we made a difference in originality between marginal and non-marginal species, marginality being defined by the geographic distribution of species. Among remaining variables, we removed missing values by using alternative data (MacDonald, 2009;[START_REF] Myers | The Animal Diversity Web[END_REF]. As the trait database was still incomplete (due to missing values) we

could not analyze all traits individually. We thus combined traits for this illustration, in order to measure the global functional originality of each species. We provide however in Appendix B a guide on how to deal with individual traits, particularly when some species have identical values for those traits. We discuss also in Appendix B on potential impact of trait selection.

Before combining the traits we removed redundancy by excluding six of the traits with high correlations with body mass (Appendix B). We ended with 9 traits with only 6 missing nominal traits we used [START_REF] Maddison | Null models for the number of evolutionary steps in a character on a phylogenetic tree[END_REF]. We first analyzed the effect of the clustering approach (either UPGMA or Ward) using Spearman correlations for each originality index. Next, we analyzed the Spearman correlations among indices calculated with phylogenetic and functional data. Then, we analyzed the Spearman correlations between phylogenetic originality measures and functional originality measures for each originality index.

We complemented these analyses with some more specific questions related to the conservation of Carnivora species. We distinguished introduced from native species. Among natives, we distinguished species whose occurrence is marginal in Europe. We first assessed which species were more original using the median of originality values for each index and group of species. For non-marginal native species only, we used an index of extinction risk defined by the International Union for Conservation of Nature (IUCN) European Red List where species are ranked as follows: 1=Least Concern, 2=Near Threatened, 3=Vulnerable, 4=Endangered and 5=Critically Endangered (IUCN 2015). We calculated a Spearman correlation between the (functional or phylogenetic) originality and the extinction risk index.

Results

Simulations

When only one trait was used the correlations between measured functional and phylogenetic originalities were always low (Fig. 3). When the number of traits increased, correlations increased. They were especially high with PE and related indices (ES and FP, [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF] when the pure birth model was used to simulate phylogenies (with or without the speciation events moved towards tips). When the speciation events were concentrated close to the root only the three indices PE, ES and FP led to correlations between measured functional and phylogenetic originality. The impact of the method used for tree construction (i.e. Ward versus UPGMA) on originality depended on the model used to whereas those with the tb-AV, tb-Rb, Qb and M were higher with UPGMA and when the speciation events occurred close to tips (Fig. 4c, PCA Axis 2).

Functional and phylogenetic originalities of carnivore species in Europe

Compared to the simulation case study, the phylogenetic signal in functional traits was not known a priori. Although phylogenetic signal was significant in all traits except activity cycle (see details in Appendix B), we found low Mantel correlation between phylogenetic and functional distances when using all combined traits (r=0.08, P=0.071). As expected from the low Mantel correlation, correlations between the functional and the phylogenetic originalities were also low (Table 4a). The correlation between the originality values obtained from the two methods of tree construction (Ward and UPGMA) were high (Table 4b), which suggests that the chosen clustering method had only a small impact on the originality estimates in this case study. The highest correlations among originality indices were between FP, Qb, AV, Rb, tb-AV and tb-Rb (Table 3). More precisely, our new index Rb was correlated with all indices in our case study but particularly strongly with AV (Table 3).

Introduced species generally had higher phylogenetic and functional originalities than native species (Fig. 5). Among native species whether the marginally European or the other species were the least phylogenetically and functionally original depended on the index used.

There was no evidence for a correlation between the phylogenetic originality of native species and their extinction risk (Table 4c). Correlations with functional originality were higher but still moderate (Table 4d). The highest correlations were obtained with PE and NN, both characterizing strict functional uniqueness. In this case study, using the clustering approaches decreased the correlation between strict uniqueness and extinction risk and its significance (P=0.068 using PE but P=0.039 with NN). All other correlations were not significant (P>0.1).

Discussion

Is phylogenetic originality a proxy for trait-based originality?

The concept of species originality for conservation has been effectively applied to define conservation priority most successfully through the Evolutionarily Distinct and Globally Endangered (EDGE) program (http://www.edgeofexistence.org/conservation/; [START_REF] Isaac | Mammals on the EDGE: conservation priorities based on threat and phylogeny[END_REF]. Within the EDGE program, [START_REF] Isaac | Mammals on the EDGE: conservation priorities based on threat and phylogeny[END_REF] proposed focusing on those species that are both phylogenetically original and threatened with extinction. To date, mammals, amphibians, birds and reef coral species have been assessed through this method [START_REF] Isaac | Mammals on the EDGE: conservation priorities based on threat and phylogeny[END_REF][START_REF] Isaac | Phylogenetically-informed priorities for amphibian conservation[END_REF]Collen et al., 2011;[START_REF] Huang | Threatened reef corals of the world[END_REF][START_REF] Jetz | Global distribution and conservation of evolutionary distinctness in birds[END_REF]. The approach is known to depend only on a single originality index (FP) and different priority schemes would be expected when using other indices [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF]. The use of phylogenies to measure species originality was justified by the assumption that phylogenetic originality reflects how many character states (including observed and unobserved characters) species share (Faith, 2002;[START_REF] Pavoine | Is the originality of a species measurable?[END_REF][START_REF] Isaac | Mammals on the EDGE: conservation priorities based on threat and phylogeny[END_REF][START_REF] Cadotte | Phylogenetic diversity metrics for ecological communities: integrating species richness, abundance and evolutionary history[END_REF].

Using a phylogeny to predict diversity has been particularly important for establishing broad-scale prioritizing schemes in conservation biology (e.g. [START_REF] Barker | Phylogenetic diversity: a quantitative framework for measurement of priority and achievement in biodiversity conservation[END_REF][START_REF] Isaac | Mammals on the EDGE: conservation priorities based on threat and phylogeny[END_REF]. In more fundamental ecological studies, for example, [START_REF] Strauss | Exotic taxa less related to native species are more invasive[END_REF] showed that invaders are more likely to be successful if they are phylogenetically distinct from the natives in the assemblage. According to [START_REF] Strauss | Exotic taxa less related to native species are more invasive[END_REF], not specifying traits might be useful, in this context, because of the large diversity of mechanisms that underpin invasion success.

However, in community or evolutionary ecology, we might be interested in an identified, finite set of traits that confer functions to species, in relation, for instance, with biotic interactions or abiotic filters [START_REF] Hooper | Effects of biodiversity on ecosystem functioning: a consensus of current knowledge[END_REF][START_REF] Violle | Let the concept of trait be functional![END_REF]. Variation in these focal traits may be more or less predicted by the phylogenetic distances between species [START_REF] Losos | Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species[END_REF]Faith, 2015b) depending on the traits.

In our simulations of Brownian trait evolution, correlations between phylogenetic and trait-based strict uniqueness (as measured by NN and PE) were generally high. However, correlations obtained with other originality indices varied more according to the type of phylogenetic tree simulated and according to the clustering approach applied to traits. Our simulations suggest that a topological index (M) should be avoided when the aim is to use phylogenetic originality as a proxy for functional originality. However, it should be noted that the applicability of alternative indices depends on the quality of branch length estimations.

While we might expect that strict phylogenetic uniqueness can act as a proxy for strict functional uniqueness, more generally phylogenetic originalities may rarely act as proxies for trait-based originalities in real case studies. We obtained moderate to high correlations between phylogenetic and trait-based originalities only when several traits were simulated.

This latter point supports previous arguments that phylogeny-based approaches in ecology are integrative: they are applicable in a macroevolutionary context to model many traits or features [START_REF] Webb | Phylogenies and community ecology[END_REF]. They are less likely to be applicable to specific species' functions associated with community assembly (e.g. Gerholds et al., 2015). We indeed found low correlations between phylogenetic and functional originalities in the real case study where traits revealed low (although significant) phylogenetic signals. Functionally but not phylogenetically strictly unique Carnivora species tended to be the most threatened in Europe.

These species were notably the nearly threatened Lutra lutra (European otter), the vulnerable Ursus maritimus (polar bear) and Gulo gulo (wolverine), and the critically endangered Mustela lutreola (European mink) and Monachus monachus (Mediterranean monk seal).

How to choose an index of functional originality?

In some respects the problem of choosing an index of functional originality is a simple extension of choosing an index of phylogenetic originality. However, indices of functional originality are more complex in that traits do not have the intrinsic tree structure on which most current originality indices rely. Our case study on European carnivores highlights that the choice of an originality index can alter the conclusions of a study such as whether original, native species are threatened with extinctions. We found low correlations between part of the indices in the simulation and Carnivora case studies. There is thus no one single way to define and codify originality. This highlights that the choice of an originality index is critically dependent on the research question under scrutiny.

According to [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF], many originality indices depend on two basic measures: the strict uniqueness (as measured by PE or NN) and the average distance to all other species in a set (as measured by tb-AV or AV). As Faith (2008) highlighted, strict uniqueness might be too restrictive as a measure of originality: the originality of the focal species also depends on how many species share its evolutionary history (and/or its functional trait states). For instance, [START_REF] Strauss | Exotic taxa less related to native species are more invasive[END_REF] found that "the presence or absence of multiple, closely related species and not just a single most closely related species may more effectively limit the success of an invader once it has become established". That said, the originality indices most correlated with species' extinction risks in European carnivores were those measuring strict functional uniqueness. Strict uniqueness might thus be an important criterion to consider when defining priorities of conservation. However, the generality of this result requires further work controlling for the traits selected to measure functional originalities, the taxa considered and the spatial scale. The other indices discussed in this paper combine information on strict uniqueness and the average distance to all other species in a set [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF]. When applied to functional dissimilarity, all these indices rely, however, on the use of clustering approaches.

The question of choosing an originality index for functional data might then be simplified into whether strict uniqueness or average distance is most important for the question at hand, and whether transforming data by a clustering approach is reasonable (i.e., does the transformation allow information in traits to be retained?).

Our hypothesis was that Rb, AV and NN calculated directly on trait dissimilarities should better reflect phylogenetic originalities than indices that require functional trees. This hypothesis failed when traits were simulated from ultrametric trees but was confirmed when traits were simulated from non-ultrametric trees. In the Carnivora case study, correlations between Rb and tb-Rb (and similarly between AV and tb-AV) were high when analyzing all traits together; however these correlations may vary with the traits considered (Appendix B).

Only with ultrametric phylogenies and Brownian evolution, a tree-based approach might better reflect the process(es) that generated traits. However, these assumptions of constant rates of evolution for all species need to be thoroughly verified.

The largest differences between the two clustering approaches (Ward and UPGMA) appeared when species had large amount of independent (compared to shared) evolutionary histories (ROOT model). More generally, the UPGMA approach led to higher correlations between phylogenetic and functional originalities whichever the index of originality was used.

When a tree-based approach is adopted, a UPGMA functional tree could thus be the most appropriate. However, further research is needed specifically comparing a larger range of clustering approaches [START_REF] Mouchet | Towards a consensus for calculating dendrogram-based functional diversity indices[END_REF].

Enlarging the perspectives: measure more than species originality

Other criteria that may influence the choice of an index is the possibility to use other attributes (than phylogeny or traits) to define species originalities. More generally, as dealing with functional originality led us to treat data that are not necessarily connected to a hierarchy (in contrast to phylogenetic trees), the conclusions drawn in this paper have the potential to be extended to assess different types of originality. Indeed the concept of originality can be derived at any scale: using dissimilarities between individuals (measuring data per individual), between populations, between species, or between sites (or assemblages, plots, regions, etc.). The concept of originality could then be adapted for establishing conservation priorities across multiple scales. For example, dissimilarities among communities, even when phylogenetic information is used (e.g. [START_REF] Ives | Phylogenetic metrics of community similarity[END_REF][START_REF] Chiu | Phylogenetic beta diversity, similarity, and differentiation measures based on Hill numbers[END_REF][START_REF] Pavoine | A guide through a family of phylogenetic dissimilarity measures among sites[END_REF], are rarely derived from trees. At the plot and regional scales, our methodology can also be extended to measure the environmental originality of plots within regions, and of regions. This can be done simply by replacing biological with environmental data when calculating dissimilarities between plots and between regions. Our study thus opens the way to new directions of research where the biological originalities of areas will be compared to their environmental originalities.

Conclusions

Originality indices provide critically important but different interpretations to measuring biodiversity. The use of these sorts of indices requires more integrative approaches in both space and/or time. Here we have highlighted methodological similarities between functional and phylogenetic originality. We analyzed alternatives for measuring species originalities that do not depend on the clustering approach. We demonstrated the importance of methodological choices in determining species' originalities. These choices are likely to impact both the probability of observing significantly original species and the chance to understand the local ecological processes driving species originality. Our new index (Rb) strongly correlates with the average distance to all other species in a set, and its framework is closely related to indices based on quadratic entropy (QE). In contrast to Rb, the QE-based index (Qb) is influenced both by the effects of average distance and strict uniqueness. Both these indices (Rb and Qb) are derived from the concepts of diversity (in terms of effective number of species) and entropy. They highlight direct links between originality and the contribution each species has to both diversity and entropy. Applications to field observational and experimental studies, as well extending theoretical models, are still necessary to evaluate the future impact of species originality as a dimension of community structure in conservation ecology. (species) measured along the tree: here, half the sum of branch lengths on the shortest path that connects the two species on the tree. We computed Rb, AV and NN directly on the defined functional dissimilarities among species. We also computed them indirectly from the established functional trees using patristic distances. In this latter case, the indices Rb and AV were named tb-Rb and tb-AV, respectively, where 'tb' stands for 'tree-based' to explicitly specify that their calculation depended on a functional tree. NN computed indirectly on a tree, noted tb-NN, corresponded to PE (the pendant edge). AV and Rb to raw dissimilarities (see Fig. 2).

  contrast, functional dendrograms may distort information obtained from raw traits. Originality indices based on functional dendrograms may thus depart more from the original signal driven by phylogenies.We simulated four general phylogenetic trees: (i) a pure birth model (BIRTH model, with birth rate of 0.1) leading to relatively well-balanced trees (function "sim.bd.taxa" in the R package TreeSim;[START_REF] Stadler | TreeSim: Simulating Phylogenetic Trees. R package version 2[END_REF]; (ii) trees with speciation events close to the root (ROOT model); (iii) trees with speciation events near the tips (TIPS model) (using package geiger in R -function "deltaTree" with δ = 10 and 0.1, respectively,[START_REF] Harmon | geiger: investigating evolutionary radiations[END_REF]; and finally

  values: activity cycle (3 attributes: nocturnal only, diurnal only, others), adult body mass, age at eye opening, diet breadth, habitat breadth, inter-birth interval, terrestriality (2 attributes: fossorial and/or ground dwelling only versus above ground dwelling), trophic level (3 attributes: herbivore, omnivore, or carnivore) and weaning age. Body mass, as a 3dimensional quantitative trait, was log-transformed to avoid extreme originalities. Indeed, we expected extreme originalities to occur because of species with high body mass such as Odobenus rosmarus (walrus). The complete set of functional traits retained for this study is given in Appendix C.We evaluated phylogenetic signal in traits using Mantel correlations for the combined traits[START_REF] Hardy | Assessing phylogenetic signal with measurement error: a comparison of Mantel tests, Blomberg et al.'s K and phylogenetic distograms[END_REF][START_REF] Pavoine | Testing for phylogenetic signal in biological traits: the ubiquity of cross-product statistics[END_REF]; for individual quantitative traits we used Blomberg et al. (2003) K* and Pavoine and Ricotta (2013) Kw while for individual

  [START_REF] Redding | Measuring evolutionary isolation for conservation[END_REF] thus considered the average distance to all other species in a set (AV or tb-AV) as the second basic component of species' originalities. Although derived from the same theory as Qb, our case studies clearly highlight the high correlations between the new index introduced in this paper (Rb) and AV. The advantage of AV and the new index Rb over alternative, tree-based indices is that they can both be applied to any dissimilarity matrix without the need to transform them into ultrametric distances, or into trees. An advantage of AV over Rb is the simplicity of its formula. A drawback of AV however, identified by[START_REF] Pavoine | Is the originality of a species measurable?[END_REF], is that it provides very close values for all species. Rb being linearly related to the square of AV better discriminates among the species: it better distinguishes species with high originality from species with close-to-zero originalities.

Fig. 1 .

 1 Fig. 1. Tree-based indices used in this paper: a) the theoretical tree used in all panels with

Fig. 2 .

 2 Fig. 2. Link between data type (functional or phylogenetic data) and the originality indices

Fig. 3 .

 3 Fig. 3. Box plots of correlations between functional and phylogenetic originalities for each

Fig. 4 .

 4 Fig. 4. Relationships between Rb and the other originality indices used in the simulations. a)

Fig. 5 .

 5 Fig. 5. Carnivore case study: box plots of the relative species originalities grouped into

Table 1

 1 Originality indices discussed in this paper. All indices are measures of originality; but only PE and NN are measures of strict uniqueness.

	Dependence on

Table 3

 3 Median correlations among indices (correlations calculated with phylogeny, traits, and the two clustering approaches) below the diagonal for the Simulation case study and above the diagonal for the Carnivora case study.

		M	PE ES	FP	Qb tb-AV tb-Rb AV Rb NN
	M		0.60 0.88 0.74 0.92 0.63 0.63 0.60 0.62 0.65
	PE	0.36	0.83 0.84 0.77 0.56 0.56 0.60 0.62 0.96
	ES	0.69 0.78	0.96 0.95 0.75 0.75 0.75 0.75 0.85
	FP	0.61 0.76 0.89		0.96 0.84 0.84 0.84 0.84 0.81
	Qb	0.93 0.52 0.79 0.78	0.83 0.84 0.76 0.78 0.80
	tb-AV 0.69 0.23 0.42 0.55 0.77	1.00 0.93 0.90 0.55
	tb-Rb	0.70 0.24 0.43 0.56 0.78 1.00	0.93 0.90 0.55
	AV	0.55 0.24 0.42 0.54 0.62 0.72 0.73	0.99 0.59
	Rb	0.54 0.24 0.42 0.54 0.62 0.70 0.71 1.00	0.62
	NN	0.36 0.99 0.77 0.78 0.53 0.25 0.25 0.25 0.25
				Insert Fig. 4. 1.5-column fitting image

Table 4

 4 Spearman correlations obtained with the Carnivora data set: a) between originality measures obtained using phylogenetic data and those obtained using functional data; b) between

	functional originality measures obtained with Ward algorithm indices and those obtained with
	UPGMA; c) between phylogenetic originality measures and IUCN status; d) between
	functional originality measures and IUCN status. When functional originality is measured, we
	indicated for each row of the table whether we used raw dissimilarities (noted 'Raw'), Ward
	trees, or UPGMA trees (see Fig. 2). The notations "(PE)NN", "(tb-)AV" and "(tb)-Rb" mean
	that we applied indices PE, tb-AV and tb-Rb to trees (phylogenies, Ward and UPGMA
	functional trees), and indices NN, AV and Rb to raw dissimilarities (see Fig. 2).
		M	(PE)NN	ES	FP	Qb	(tb-)AV (tb-)Rb
	a) cor(phylogenetic originality, functional originality)
	Raw	-	0.19	-	-	-	0.11	0.06
	Ward	0.06	0.14	0.30	0.26	0.20	0.21	0.21
	UPGMA	-0.19	0.15	0.30	0.24	0.20	0.19	0.19
	b) cor(Ward functional originality, UPGMA functional originality)
	Ward-UPGMA	0.72	1.00	0.92	0.99	0.94	0.96	0.96
	c) cor(phylogenetic originality, extinction risk)
	Phylogeny	0.01	0.14	0.14	0.08	0.05	-0.12	-0.13
	d) cor(functional originality, extinction risk)
	Raw		0.40				0.26	0.29
	Ward	0.24	0.36	0.32	0.26	0.27	0.12	0.13
	UPGMA	0.18	0.36	0.24	0.27	0.22	0.14	0.14

  For example, Faith (2008, 2015a),[START_REF] Rosauer | Phylogenetic endemism: a new approach for identifying geographical concentrations of evolutionary history[END_REF],[START_REF] Cadotte | Phylogenetic diversity metrics for ecological communities: integrating species richness, abundance and evolutionary history[END_REF] modified the FP index by weighting species by probabilities of extinction, range size and abundance, respectively. Whether these modified measures of phylogenetic originalities can be applied to functional trees is questionable. Indeed they were developed for rooted phylogenetic trees with branch lengths representing shared evolutionary histories. Further research is needed on how to include additional information such as threat, endemism and/or abundance into indices of functional originality (See[START_REF] Ricotta | Measuring the functional redundancy of biological communities: a quantitative guide[END_REF] first developments in this direction).

Acknowledgements

We thank Owen Petchey for useful comments on a previous version of the paper. U.J. is supported by the German Centre for Integrative Biodiversity Research (iDiv), funded by the German Research Foundation (FZT 118) and funded by the Ministry for Science and Culture of Lower Saxony (BEFmate).

simulate the phylogeny on which traits evolved. Correlations varied from ≈0.30 with M, Qb, tb-AV, and tb-Rb when 50 traits were simulated with the ROOT model to ≈1.00 with PE, ES and FP (details in Appendix D). In general, correlations were higher with UPGMA than Ward trees. When the simulated phylogenetic trees were not ultrametric (NU model), AV and Rb led to the highest correlations between functional and phylogenetic originalities. UPGMA and Ward transformations on functional distances thus decreased the connections between the information within functional traits and the model used to simulate them.

Insert Fig. 3. 1.5-column fitting image

On average, the highest correlations (median>0.90) among originality indices were between AV and Rb, between tb-AV and tb-Rb, between Qb and M, and between PE and NN (Table 3). High correlations (>0.70) were also obtained between Qb, ES and FP, between ES, FP and PE, and between AV, Rb, tb-AV and tb-Rb. Correlations between our new index Rb and the other originality indices were moderate to high, with close-to-1 correlations with AV (Fig. 4). The link between the square root of Rb and AV was close to linear (Fig. 4a). The lowest correlations with Rb were obtained with PE, NN, and ES (Table 3 and Fig. 4b; see also Appendix E for more details on these correlations).

Correlations between Rb and tree-based metrics tended to be higher when a single trait was used and when traits were simulated using the NU model (Fig. 4c). The increase in correlation with only one trait was especially high with PE, and related indices (FP and ES) (Fig. 4c, PCA Axis 1). Correlations of Rb with PE, ES and FP were higher with Ward trees and when speciation events were moved close to the root (compared to the pure birth model),


Coline Martin
email: coline.martin@supagro.fr

Marie-Hélène Helene Morel

Adrien Reau

Bernard Cuq

Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects

Keywords: Durum wheat pasta, glutenin insolubilisation, gluten protein, extrusion

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

rested for 120 minutes at 20, 30 or 40°C prior drying at high temperature (90°C). Glutenins insolubilisation induced by resting and drying was assessed from the SE-HPLC elution profiles of the SDS-soluble proteins from fresh, rested and dried pasta. Final pasta were characterized for their organoleptic (color, surface roughness) and physical (diameter, cooking time, viscoelasticity index) properties, before and after cooking. Pasta quality is discussed in relation with the gluten network structure and the impact of resting time. Resting of freshly extruded pasta extrusion leads to spontaneous insolubilisations of glutenins by creation of weak interactions. High temperature drying induces a strong drop of solubility of all gluten protein fractions by creation of covalent bonds, impacting equally rested and not rested pasta. Dry and cooked pasta organoleptic and physical properties are not significantly impacted by a resting time.

Introduction

Durum wheat pasta is a traditional and world-wide consumed cereal food. Pasta structure relies on physical and chemical interactions that are established in between starch and proteins during pasta making. Pasta processing consists in a succession of several unit operations: hydration, mixing, extrusion, and drying. Durum wheat semolina is first hydrated with a specific amount of water and mixed in order to obtain crumble dough of wet agglomerates. The agglomerates are structured into pasta by single screw extrusion at low temperature. Fresh pastas are stabilized by drying, which can be either carried out at high (70-90°C) or low (40-55°C) temperature. Cooking, the final food preparation step before pasta eating, is assigned to the consumer [START_REF] Sicignano | From raw material to dish: Pasta quality step by step[END_REF].

It is commonly accepted that the wheat components and their changes in structure during processing and cooking control pasta final organoleptic qualities. During the first mixing step, the wet agglomerates of semolina undergo shear deformation, that induces protein hydration and unfolding allowing for the formation of a continuous gluten network enclosing the starch granules [START_REF] Guerrero | FTIR characterization of protein-polysaccharide interactions in extruded blends[END_REF].

Gluten in its hydrated form behaves like a viscoelastic cohesive mass stabilized by weak hydrogen, ionic and hydrophobic bonds. Wheat gluten proteins (12 to 15% of pasta dry weight) are constituted of monomeric gliadins and polymeric glutenins [START_REF] Shewry | Cereal seed storage proteins: structures, properties and role in grain utilization[END_REF]. Both are soluble in sodium dodecyl sulfate (SDS) buffer, fully for the former and partly for the latter.

Process temperature above 55°C impact gluten network structure by triggering the formation of covalent links [START_REF] Joubert | Fate of SDS-insoluble glutenin polymers from semolina to dry pasta[END_REF][START_REF] Lagrain | The impact of heating and cooling on the physico-chemical properties of wheat gluten-water suspensions[END_REF][START_REF] Lamacchia | Changes in pasta proteins induced by drying cycles and their relationship to cooking behaviour[END_REF][START_REF] Morel | Mechanism of heat and shear mediated aggregation of wheat gluten protein upon mixing[END_REF][START_REF] Singh | Changes in proteins induced by heating gluten dispersions at high temperature[END_REF]Wagner et al., 2011;Weegels & Hamer, 1998).

When pasta extrusion is conducted above 50°C, it causes a marked decrease in the solubility of salt-soluble proteins fractions (albumin, globulin). Above 96°C, extrusion results in a dramatic increase of the SDS-insoluble protein fraction [START_REF] Dexter | Changes in semolina proteins during spaghetti processing[END_REF][START_REF] Ummadi | Changes in solubility and distribution of semolina proteins due to extrusion processing[END_REF].

The impact of pasta drying temperature on gluten proteins aggregation and solubility loss in SDS buffer has been extensively studied. Above 55°C for glutenins and 70°C for gliadins, proteins initiate disulfide/sulphydryl exchange reactions. Above 90°C, glutenin and gliadin crosslink together through new disulfide bonds [START_REF] Dexter | Changes in semolina proteins during spaghetti processing[END_REF][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]Wagner et al., 2011). When reticulated during drying, the gluten protein network allows pasta to resist to starch swelling mechanisms that are promoted by the final cooking stage and promote a firmer texture and a better surface aspect of cooked pasta [START_REF] Cubadda | Influence of gluten proteins and drying temperature on the cooking of durum wheat pasta[END_REF]

ACCEPTED MANUSCRIPT

-4 - [START_REF] Lamacchia | Changes in pasta proteins induced by drying cycles and their relationship to cooking behaviour[END_REF][START_REF] Matsuo | Effect of gluten on the cooking quality of spaghetti[END_REF]. Viscoelastic index of cooked pasta correlates well with native semolina gluten protein content and with gluten network ability to resist to mechanical stresses [START_REF] Baiano | Influence of the drying temperature on the spaghetti cooking quality[END_REF]. When compared to low temperature drying, high or very high temperature drying diagrams.

Recently, [START_REF] Joubert | Fate of SDS-insoluble glutenin polymers from semolina to dry pasta[END_REF] indicated that the drying step of pasta making process is not the only stage during which gluten protein can be insolubilized. When freshly extruded pasta is rested at ambient temperature after extrusion, gluten proteins tend to spontaneously insolubilize. The largest fractions of glutenin polymers are more impacted than the smallest fractions. Gliadin fractions are not impacted during the resting stage. The insolubilisation mechanisms of the glutenins fractions during resting at ambient temperature followed first order kinetics. We aim to investigate the potential macroscopic differences in pasta characteristics generated either by spontaneous insolubilisation reactions of gluten proteins at ambient temperature in freshly extruded pasta or protein aggregation during drying step.

The objective of the present study is to investigate the impact of time during a resting period after extrusion and during drying stage, on protein insolubilisation kinetics in extruded pasta.

The resting period was conducted under different conditions of temperature (20-40°C) and followed by a drying stage conducted under low (55°C) or high (90°C) temperatures. The extraction of SDS-soluble and SDS-insoluble proteins and the analyze by size exclusion high performance liquid chromatography (SE-HPLC) allowed to describe the mechanisms of protein reactions throughout the resting period and drying stage. The measured characteristics of dried pasta (color, diameter, and cooking time) and cooked pasta (color, diameter, surface aspect, and texture) were discussed in relation to the mechanisms of protein insolubilisation during pasta making process, in order to evaluate the specific impact of the resting period.

Material and methods

Raw material

Industrial durum wheat semolina (Panzani, France) was used as raw material. Semolina was stored at 4°C. Semolina water content (13.87 (±0.12) g water/100 g wet semolina) was determined according to AACC method 45-15.02. Semolina total nitrogen content was determined by Kjeldahl method, and the crude protein content (12.41 (± 0.26) g proteins/100 g dry semolina) was calculated according to TN-5.7 (AFNOR NF V03-050 method). Particle diameter distribution of semolina were measured by a laser particle size analyzer (Coulter

Pasta making

Semolina was transformed into pasta using a laboratory pasta making machine (AFREM-BASSANO, France, [START_REF] Abecassis | Influence of extrusion speed, temperature and pressure in the extruder on pasta quality[END_REF]. Semolina (7.0 kg) was weighed and introduced in the mixer tank. The double water-jacket of the mixing tank temperature was maintained at 40°C. Tap water was added to obtain a final water content of 47.0 g water / 100 g dry matter.

Tap water was equilibrated to prior its spreading over the mixed semolina layer. Mixing was continued for 20 min, at atmospheric pressure. The wet agglomerates of semolina were extruded at constant temperature (35°C) under vacuum (59 MPa). Fresh spaghettis were extruded vertically from the die. Extrusion temperature and pressure were recorded along extrusion.

Pasta drying was conducted using a laboratory pasta drying machine (AFREM, France, [START_REF] Abecassis | Improvement of cooking quality of maize pasta products by heat treatment[END_REF]. Extruded fresh spaghettis were immediately placed in the dryer that was previously equilibrated at 35°C and 88% relative humidity (RH To investigate the effect of a rest period between the extrusion and drying stages, freshly extruded pasta were rested in the dryer at 20, 30 or 40°C and 88% RH up to 120 minutes prior to the drying phase. It was verified that at the end of the resting time no weight loss had occurred.

Pasta samples were collected for SE-HPLC analysis immediately after the mixing and extrusion steps and after different resting and drying times. Samples were immediately frozen using liquid nitrogen and stored at -18°C. The frozen samples were freeze-dried, milled and kept under argon until characterization.

Characterization of dried pasta

Diameters of dried spaghetti were manually determined using a caliper (Mituyo, CD-15DC).

For each product, 8 measurements were done on 8 spaghettis.

Cooking behavior of pasta

Pasta cooking was conducted in boiling water according to the French Standard NF ISO 7303.

Optimum cooking time for dried pasta was determined according to AACC Method 66-50.01.

Pasta were cooked at the optimum cooking time + 1 minute. After cooking, spaghetti sample was drained and rinsed with large amount of tap water. Pasta strands were kept under Petri boxes at room temperature under saturated relative humidity conditions before characterization.

Characterization of cooked pasta

Water content of cooked pasta was determined in triplicate according to the approved AACC Method 45-15.02. Results are expressed in g water / 100 g dry matter.

Color characteristics (L*, a*, and b*) of cooked past was measured for each product. 40 g of cooked spaghetti were arranged inside the specific black box to form a homogenous layer of product (2 cm height). Color was measured in triplicate.

Diameters of cooked spaghetti were manually determined using a caliper (Mituyo, CD-15DC).

For each product, 8 measurements were done on 8 spaghettis.

Surface roughness of cooked pasta was evaluated according to ISO 7304-1:2016. Cooked pasta were disposed on a white plate and compared to standardized pictures. A grade (1 to 8 scale) was given by three different individuals after visual inspection.

Viscoelasticity and tensile strength of cooked pasta were measured using a texturometer TA-XT Plus (Stable Micro Systems, UK). For viscoelasticity, a flat probe (SMS P/35) was used to squeeze a 2 cm cooked spaghetti sample under 0.5 N for 40 sec, before stress relaxation (20 sec). Thickness values (mm) were measured: initial diameter (E), diameter after 40 sec under a 0.5N compression (e 1 ), and diameter after 20 sec of load release (e 2 ). Viscoelasticity index (IV)

was calculated using equation 1. For each product, five measurements were performed.

(Eq 1) IV = For tensile strength measurement cooked spaghettis were fixed to the tensile grips (A/SPR).

The tensile test was performed at constant deformation rate (3 mm.s -1 ) until pasta rupture. The strain and stress values were calculated considering the thinning of the sample diameter and constant sample volume between the grips (equations 2, 3). (Eq 2)

𝑆𝑡𝑟𝑎𝑖𝑛 = 𝐿 𝑡 -𝐿 0 𝐿 0 × 100 (Eq 3) 𝑆𝑡𝑟𝑒𝑠𝑠 = 𝐹 𝑡 𝜋 𝐷 2 0 × 𝐿 0 4 × 𝐿 𝑡
With L 0 , sample length between the two jaws (mm); L t , the same after time t of extension (mm); D 0 , initial sample diameter (mm); F t , measured force at time t of extension (N). Rupture stress (MPa) and strain (%) were recorded from the stress-strain curves at the breaking point. Stressstrain curves were plotted and elastic modulus was identified as being curves' slope. Four to seven measurements were recorded for each product.

Gluten protein size distribution

SDS-soluble and SDS-insoluble proteins from freeze-dried and milled pasta samples were extracted and analyzed by size exclusion high performance liquid chromatography (SE-HPLC) according to [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]. SDS-soluble protein (Fs) were extracted in sodium phosphate buffer (pH 6.9) containing 1% SDS. SDS-insoluble proteins (F i ) were extracted by sonication of the residue re-suspended in the previous buffer supplemented with dithioerytritol (20 mM).

Chromatogram of SDS-soluble proteins was divided into 5 fractions: SDS-soluble large glutenin polymers (F 1 ); medium range glutenin polymers (F 2 ); ω-type sulfur-poor prolamins (F 3 ); sulfur-rich -, and ɣ-gliadins (F 4 ); albumin and globulins (F 5 ). Areas from fractions F1 to F5 were expressed in % of the corresponding area from freshly extruded pasta, unless otherwise noted. In percent of total protein, fractions F 1 to F 5 of the freshly extruded pasta were: 5.7 ±1.1 % (F 1 ); 26.7 ±2.1 % (F 2 ); 8.6 ±0.2 % (F 3 ); 37.0 ±1.5 % (F 4 ) and 13.1 ±0.4 % (F 5 ).

Model fitting and statistical analysis

Apparent first order kinetic model (Eq. 4) was used to fit the solubility changes as a function of time observed during pasta resting and drying. Areas F 1 to F 5 from extracts Fs were considered, after their normalisation to the corresponding area obtained from the freshly extruded pasta sample.

(Eq. 4)

𝑦 = 𝑦 0 + 𝑎(1 -𝑒 -𝑏𝑥 ) Comment citer

Results

Impact of drying

Impact on protein insolubilisation -Extruded pasta were dried at low (55°C) or high (90°C) temperature. Solubility changes for each gluten protein fraction as a function of drying time were quantified to follow protein insolubilisation dynamics (figure 1). Pasta drying promotes gluten protein insolubilisation reactions.

Regardless of the drying temperature, non-linear solubility decreases of all SDS-soluble gluten protein fractions (F 1 to F 5 ) were observed and were successfully fitted using an exponential decay model, except for low molecular weight fractions (F 3 to F 5 ) that are only slightly impacted by the LT drying. Low temperature (LT) drying led to specific decreases of relative solubility depending on gluten protein fraction (figure 1). Fractions F 1 and F 2 underwent a fast (C Time = 12.2-50.0 min) and large (27.5-34.8%) loss of solubility. LT drying mainly impact the glutenin polymers fractions (F 1 and F 2 ).

High temperature (HT) drying was conducted into two phases: a heating phase from 35 to 88°C in 45 min, and a high temperature treatment phase at 90°C for 255 min. HT drying led to a strong decrease of protein solubility, specific to each fraction (figure 1). During the heating phase, fractions F 1 and F 2 drops according to kinetic very similar to the one observed for LT drying (C Time = 14.2-50.0 min) but of larger (52.0-50.0%) amplitude. For fractions F 3 , F 4 and Impact on pasta characteristics -As expected, drying temperature impacts pasta characteristics (table 1). Compared to LT drying, HT drying had a significant impact on pasta color. HT drying significantly increased redness (a*) and decreased yellowness (b*) for both dried and cooked pasta. On the other hand, opposite impacts of HT drying on brightness (L*) were observed for dried pasta (L* increase) and cooked pasta (L* decrease). Compared to LT drying, HT drying had a significant impact on pasta diameter, with a significant decrease for dried pasta and a significant increase for cooked pasta. Dried pasta cooking time was not impacted by drying temperatures. Compared to LT drying, HT drying significantly improved cooked pasta surface aspect (from 6 to 8) and texture properties, with an increase of elastic modulus, breaking stress, breaking strain, and viscoelasticity index. It is admitted that compared to LT, HT drying led to pasta characterized by a higher red hue due to Maillard reaction, a firmer texture and a better surface aspect [START_REF] Cubadda | Influence of gluten proteins and drying temperature on the cooking of durum wheat pasta[END_REF][START_REF] Lamacchia | Changes in pasta proteins induced by drying cycles and their relationship to cooking behaviour[END_REF].

Protein insolubilisation during resting of freshly extruded pasta

The impact of resting for 120 min at different temperatures (20, 30 or 40°C) on protein solubility and pasta characteristics was investigated. Soluble gluten proteins were quantified for time related to resting and HT drying.

Impact on protein solubility in SDS buffer -Resting led to specific solubility decrease of protein fractions F 1 and F 2 (figure 3) while fractions F 3 , F 4 and F 5 were slightly impacted (data not shown). Resting decreased the extractability of protein in SDS buffer by about 6 to 10% as the temperature rose from 20 to 40°C. In accordance with [START_REF] Joubert | Fate of SDS-insoluble glutenin polymers from semolina to dry pasta[END_REF], only glutenin polymers were impacted, and large polymers from fraction F 1 reacted faster than those from fraction F 2 , suggesting that solubility loss resulted from an increase in the size of glutenin polymers. The rate of protein solubility loss roughly followed a first order kinetics, but a 16 minutes delay 16 min was noticed for samples rested at 20°C, before any significant drop.

Increase in temperature fasten solubility drop.

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-10 -of 75 to 95 kJ/moles reported for gliadin solubility loss beyond 100°C [START_REF] Lagrain | Kinetics of heat-induced polymerization of gliadin[END_REF] or from the activation enthalpy calculated for the oxidation of the unique thiol of bovine serum albumin thiol (54-59 kJ/moles) [START_REF] Bonanata | The thiol of human serum albumin: Acidity, microenvironment and mechanistic insights on its oxidation to sulfenic acid[END_REF]. It approximates the E a value of 30-40 kJ/moles measured by single-molecule force clamp spectroscopy for protein disulfide bond reduction by free thiol [START_REF] Liang | Kinetic Measurements on Single-Molecule Disulfide Bond Cleavage[END_REF]. Protein disulfide bond reshuffling, mediated by thiol/disulfide exchanges would account for glutenin polymers solubility loss.

Impact of pasta resting on protein crosslinking during drying and on pasta quality attributes

Extruded pasta were sequentially submitted to a resting period (at 30°C for 120 minutes) and an HT drying (90°C). Soluble gluten proteins were quantified along resting and drying stages in order to follow protein solubility variations (figure 3a,3b).

Impact on protein insolubilisation -Resting impacted the kinetic of gluten protein solubility loss kinetics induced by HT drying but not the total amplitude of the phenomenon. During the early drying phase (from 35 to 88°C for 45 min) and compared to non-rested pasta, protein solubility loss remained modest: levels of soluble proteins from rested and non-rested pasta turned out to be equivalent at the end of the first drying step. Further HT drying at 90°C induced large protein solubility loss, regarding all wheat protein classes and in a way similar to the one observed for non-rested pasta (figure 1c-1d).

Impact on pasta characteristics -Compared to non-rested pasta, a resting period before HT drying had significant light impacts on color properties of pasta (table 1). A resting time (120 min) significantly increased dried and cooked pasta yellowness (b*) and redness (a*), and cooked pasta brightness (L*). Resting time also induced a light decrease of dried pasta diameter, but did not significantly change cooked pasta diameter. Resting time did not significantly impact cooking time and texture properties of cooked pasta.

Discussion

Gluten proteins insolubilisation upon high temperature treatment

HT drying is a driving unit operation of changes of protein structure upon pasta processing.

Thermal treatment during HT drying induces a strong drop of solubility of all gluten protein fractions. Glutenins (F 1 and F 2 ) show a stronger loss of solubility (95%) compared to gliadin and cytoplasmic proteins (46-65%). HT drying leads to rapid and strong specific gluten proteins We proposed a phenomenological model to describe the changes in protein solubility during pasta resting and drying (figure 5). Water elimination during pasta drying leads to a significant reduction of pasta diameter. The generated mechanical stress could induce compaction of wheat components. The protein chains get closer and could generate additional interactions. Each additional bond involving glutenins reduces their solubility. The behaviour of gluten proteins under HT has been extensively studied [START_REF] Icard-Vernière | Effects of Mixing Conditions on Pasta Dough Development and Biochemical Changes[END_REF][START_REF] Lamacchia | Changes in pasta proteins induced by drying cycles and their relationship to cooking behaviour[END_REF][START_REF] Lagrain | The impact of heating and cooling on the physico-chemical properties of wheat gluten-water suspensions[END_REF][START_REF] Petitot | Modification of pasta structure induced by high drying temperatures. Effects on the in vitro digestibility of protein and starch fractions and the potential allergenicity of protein hydrolysates[END_REF]Wagner et al., 2011;Zweifel et al., 2003). It is well established that heating glutenins above 55°C and gliadins above 70°C allows disulphide/sulfhydryl exchange reactions and the creation of new disulfide bonds. A LT thermal treatment (55°C) of glutenins leads to the creation of intra-chains and inter-chains disulfide bonds, as indicated by the superposed curves when plotted according to "time*temperature" axis (figure 2). LT drying reinforces to a certain extent pasta protein network. A HT thermal treatment (90°C) allows the creation of numerous disulfide bonds between proteins, thus inducing high levels of insolubilisation. Sulfur-rich α-, and ɣ-gliadins (F 4 ) contain cysteine residues (6 cysteines for α-type and 8 cysteines for γ-type) located at highly conserved positions and all involved in intrachain disulfide bonds. Their quaternary structure might not be altered during mixing and extruding stages. Thiol groups of cysteine residues might not be exposed and are less able to create disulfide bonds.

We hypothesized that glutenin insolubilisation upon resting of extruded pasta could be due to the creation of weak interactions (figure 5). After a thermal treatment during HT drying, proteins insolubilisation rates for rested pasta are not significantly different from those of not rested pasta. The creation of disulfide bonds during thermal treatment drives gluten protein insolubilisation and the influence of weak interactions established during resting is then not significant. HT drying cycle homogenizes the level of SDS-extractible proteins by forcing the insolubilisation and creating large protein aggregates. La [START_REF] Gatta | Evidence for different supramolecular arrangements in pasta from durum wheat (Triticum durum) and einkorn (Triticum monococcum) flours[END_REF] suggested that the architecture and size of protein aggregates created during drying depend on the nature and proportion of the various classes of proteins. The hypothesis was made that supramolecular structures derived from gluten protein aggregation could emerge during pasta drying and their assembling occurs hierarchically. Due to gluten complexity, it is not always possible to predict the formation of supramolecular polymeric structures.

Exchange reaction SS-SH during resting after extrusion at various temperatures

The water content of fresh extruded pasta is high enough (30% wet basis) to allow molecular mobility of protein chains. During pasta extrusion, compression and shear forces would unfold glutenin polymers facilitating their alignment and hydrophobic and H-bond pairing. Such type of weak interactions, even if maintained after sample freeze-drying are going to be disrupted during extraction in the SDS-buffer used here. Only irreversible changes involving covalent bonds like peptide-or disulfide-bonds will be detected.

In this work it was found that resting at 20 to 40°C of freshly extruded pasta coincided with a slight but significant glutenin polymers solubility loss. Polymers of the largest molecular weight (F 1 ) reacted more readily than glutenin from F 2 . In less than 15 min, F 1 area decreased by 33% against a drop of 16.4% in 26.9 min for the smaller glutenin polymers F 2 . An increase in resting temperature (between 20 to 40°C) hastens the reaction from 30.3 min (20°C) to 11.3 min (30°C) and 7.02 min (40°C). The corresponding activation energy (E a =26.4  7.2 kJ/moles) lacks of accuracy and additional experiments would be needed to consolidate it. Nevertheless, it remains far from the E a value reported for the gliadin solubility loss observed during pasta drying [START_REF] Lagrain | Kinetics of heat-induced polymerization of gliadin[END_REF]. It is compatible with the activation energy needed to promote disulfide bond reshuffling by thiol/disulfide exchange, which ranges between 30-40 kJ/moles [START_REF] Liang | Kinetic Measurements on Single-Molecule Disulfide Bond Cleavage[END_REF].

After extrusion, stress relaxation of stretched glutenin polymers would drive this disulfide reshuffling. The reaction also occurs when extruded pasta are directly placed into the temperature monitored drying chamber. It accounts for the modest drop in glutenin polymers observed at the beginning of LT drying. Because during this step temperature remains below 60°C, no further protein solubility loss induced by additional disulfide crosslinking was observed. Indeed, it is well established that heating glutenins above 55°C and gliadins above 70°C allows for the disulphide/sulfhydryl exchange reactions that promote the creation of new disulfide bonds [START_REF] Lagrain | Kinetics of heat-induced polymerization of gliadin[END_REF].

Gluten proteins insolubilisation kinetic during resting at 30°C and HT drying

Resting extruded pasta leads to a specific loss of solubility of gluten protein fractions. Glutenins

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-13 -between adjacent chains (figure 4), thus leading to a loss of solubility. This kinetic insolubilisation of glutenins during resting occurs spontaneously, without mechanical nor thermal stress. The water content of fresh extruded pasta is high (30% wet basis) enough to allow molecular mobility of the protein chains. Glutenins insolubilisation during resting could be due to the creation of hydrophobic interactions between adjacent chains, to form larger aggregates. A slight increase of resting temperature (from 20 to 30°C) speeds up glutenins (F 1 and F 2 ) and gliadins (F 3 and F 4 ) spontaneous insolubilisation (table 1).

An increase of rest temperature might favor molecular mobility of protein chain in fresh pasta and increase probability of efficient interactions. The contribution of covalent disulfide bonds during resting is less probable, as their creation is driven by temperature higher than 55°C for glutenins and higher than 70°C for gliadins [START_REF] Icard-Vernière | Effects of Mixing Conditions on Pasta Dough Development and Biochemical Changes[END_REF]Wagner et al., 2011).

Gliadins (F 3 and F 4 ) and cytoplasmic proteins (F 5 ) are seldomly impacted by a resting period.

They experience very small losses of solubility and low insolubilisation rates during resting.

The sulfur-poor ω-type gliadins (F 3 ) show small losses of solubility while sulfur-rich α-, and ɣ-gliadins (F 4 ) and cytoplasmic proteins (F 5 ), experience no loss of solubility. These low molecular weight proteins are less likely to unfold during mixing and extruding stages.

Compared to glutenins, their open surface could be smaller, giving them few opportunities to create inter-protein weak interactions and to insolubilize during resting (figure 4). Creation of additional intra-gliadins weak interactions does not impact their solubility. The apparent loss of solubility of cytoplasmic protein (F 5 ) might be induced by a linkage of proteins to other components of semolina.

The spontaneous insolubilisation potential of gluten proteins upon resting may be linked to durum wheat variety and gluten protein qualities [START_REF] Joubert | Fate of SDS-insoluble glutenin polymers from semolina to dry pasta[END_REF]. A high glutenin/gliadin ratio might be related to a strong capacity of spontaneous insolubilisation, as glutenins F 1 are able to insolubilize during the resting period. It has been shown that pasta quality increases as low molecular weight glutenins show a greater number of cysteines available for interactions with other glutenins [START_REF] Lee | The low-molecularweight glutenin subunit proteins of primitive wheats. IV. Functional properties of products from individual genes[END_REF].

Impact of a resting time on pasta quality

Cooked pasta quality is not significantly impacted by resting, regardless of resting temperature and time (table 1). HT drying confers identical texture qualities to rested and not rested pasta.

Gluten protein changes and additional weak interactions created during resting time do not have a significant impact on HT dried pasta quality. Weak interactions contribution to pasta quality

  (e 2 -e 1 ) (E -e 1 ) (E -e 1 ) E Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014

  ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014 ACCEPTED MANUSCRIPT -8 -Where y 0 (=100) is the normalized F i areas at t = 0 min. The calculated coefficients of the model a and b are respectively related to the insolubilisation amplitude and characteristic reaction time (C Time ; 1/b). Coefficients were determined by least-square fitting using Excel 2016 solver (Microsoft, Redmond, USA). Determination coefficients (R 2 ) and the sum of absolute deviations between experimental and calculated values were considered to gauge the goodness of fit. Statistical analysis was carried out with XLSTAT (Addinsoft, NY, 2017) at 95% confidence level by Student tests and p-value. The statistical significance of measured values was verified using single factor analysis of variance (ANOVA) and Tukey test on replicated data.

F

  5 insolubilisation was slower (C Time > 50 min) and less pronounced (8.0-30.0%). During the high temperature phase (90°C), fractions F 1 and F 2 underwent an additional very fast (C Time = 5.0-11.9 min), and large (45.0-65.0%) insolubilisation process. Fractions F 3 , F 4 and F 5 loss of solubility was slower (C Time = 22.2-33.3 min) but more pronounced (38.0-55.0%) than during Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014ACCEPTED MANUSCRIPT-9 -the heating phase. HT drying amplifies gluten protein insolubilisation mechanisms. HT drying is known to increase the amount of SDS-insoluble proteins[START_REF] De Stefanis | Effects of high-temperature drying on technological properties of pasta[END_REF][START_REF] Petitot | Modification of pasta structure induced by high drying temperatures. Effects on the in vitro digestibility of protein and starch fractions and the potential allergenicity of protein hydrolysates[END_REF]. Kinetic and thermal effects on high molecular weight gluten protein (F 1 +F 2 ) insolubilisation mechanisms along drying have been depicted by a curve of protein solubility as a function of 'time*temperature' (figure2). Regardless of drying temperature, protein solubility variations overlap for short duration.

F

  1 and F 2 show a stronger loss of solubility (16.4-33.0%) compared to gliadins F 3 and F 4 (3.24-7.65%) and cytoplasmic proteins F 5 (7.73%). High molecular weight glutenins (F 1 ) show the strongest (33%) and the fastest (C Times = 11.3 min) loss of solubility during the first 60 minutes of rest. Low molecular weight glutenins (F 2 ) have a smaller (16.4%) and slower (C Times = 26.9 min) loss of solubility upon resting. During resting, they become able to build weak interactions Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014

Figure 1 :

 1 Figure 1: Evolution of relative contents of soluble proteins for the different wheat gluten protein fractions (F 1 to F 5 ) in pasta as a function of drying time during LT drying (a-b) or HT drying (c-d). When not displayed (a;b), error bars (relative standard deviation) overlap.

Figure 2 :

 2 Figure 2: Evolution of relative contents of soluble glutenin fractions in pasta as a function of drying time*drying temperature during low temperature drying (LT) or high temperature drying (HT). Error bar (relative standard deviation; not displayed) overlap.

Figure 3 :

 3 Figure 3: Evolution of relative contents of soluble proteins for the different wheat gluten protein fractions F 1 and F 2 in pasta as a function of time during resting at different temperatures (at 20, 30, or 40°C). Error bars (relative standard deviation; not displayed) overlap.

Figure 4 :

 4 Figure 4: Evolution of relative contents of soluble proteins for durum wheat glutenin in pasta as a function of time during successive resting phase at 30°C (0 to 120 min) and HT drying (120 to 420 min). Error bars feature the relative standard deviation.

Figure 5 :Figure 1 :Figure 2 :Figure 3 :

 5123 Figure 5: Mechanistic model of insolubilisation of wheat gluten proteins upon resting and upon high or low temperature drying in pasta.

Figure 4 :

 4 Figure 4: Evolution of relative contents of soluble proteins for durum wheat glutenin in pasta as a function of time during successive resting phase at 30°C (0 to 120 min) and HT drying (120 to 420 min). Error bars feature the relative standard deviation.

Figure 5 :

 5 Figure 5: Mechanistic model of insolubilisation of wheat gluten proteins upon resting and upon high or low temperature drying in pasta.

  . HT drying induces the insolubilisation of 95% of the glutenins, 60% of the gliadins and 40% of the cytoplasmic proteins. Compared to gliadins, higher molecular weight glutenins are highly sensitive to HT treatments. HT drying allows very fast insolubilisation mechanisms, with characteristic times lower than 14 min for the glutenin fractions.

Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014 ACCEPTED MANUSCRIPT -11 -insolubilisation

  Comment citer ce document : Martin, C.,Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014 much lower compared to covalent bonds set up during drying. Dry pasta color and texture is not impacted by a resting time before drying. Resting does not significantly impact enzyme activity in fresh pasta, thus does not allow color changes. Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014 Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014 Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014 Wagner, M., Morel, M.H., Bonicel, J., Cuq, B., 2011. Mechanisms of heat-mediated aggregation of wheat gluten protein upon pasta processing. Journal of Agricultural and Food Chemistry 59, 3146-3154. Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109.

	ACCEPTED MANUSCRIPT ACCEPTED MANUSCRIPT
	Weegels, P.L., Hamer, R.J., 1998. Temperature-induced changes of wheat products. In
	Interaction: The Keys to Cereal Quality; Hamer, R. J., Hoseney, R. C., Eds.; AACC: St.
	5. Conclusion Paul. 95-123.
	Pasta resting after extrusion leads to gluten protein insolubilisation reactions by creation of Zweifel, C., Handschin, S., Escher, F., Conde-Petit, B., 2003. Influence of high-temperature
	weak interactions. This spontaneous insolubilisation follows a first order kinetics and impacts drying on structural and textural properties of durum wheat pasta. Cereal Chemistry 80, 159-
	more glutenins compared to gliadins and cytoplasmic proteins. HT drying induces a strong drop 167.
	of solubility of all gluten protein fractions by creation of covalent bonds, impacting equally
	rested and not rested pasta. Covalent bonds created during drying have a higher contribution to
	cooked pasta quality compared to weak interactions established during resting time.
	-14 --17 -

is , DOI : 10.1016/j.jcs.2019.05.014 -18 -

Table 1 :

 1 Characteristics of dried pasta and cooked pasta produced by HT drying, LT drying, or coupling resting phase (for 120 min at different temperature 20, 30 or 40°C) and HT drying.

	Products	Brightness	Redness	Yellowness	Diameter	Cooking	Surface	Elastic	Rupture	Rupture	Viscoelasticity
		L*	a*	b*		time	aspect	modulus	stress	strain	index
		(N/A)	(N/A)	(N/A)	(mm)	(min)	(N/A)	(MPa)	(Pa)	(N/A)	(N/A)
	Pasta directly dried at low temperature
	Dried pasta	54.1 ±0.1 b	2.39 ±0.03 b	42.4 ±0.1 b	1.48 ±0.04 a	10	N/A	N/A	N/A	N/A	N/A
	Cooked pasta 79.8 ±0.9 d	-0.533 ±0.049 d	38.3 ±0.3 d	2.68 ±0.01 d	N/A	6	86.8 ±8.0 a	153 ±10 b	1.68 ±0.21 b	8.63 ±0.53 b
	Pasta directly dried at high temperature
	Dried pasta	56.0 ±0.3 a	3.43 ±0.14 a	41.9 ±0.2 a	1.53 ±0.02 a	10	N/A	N/A	N/A	N/A	N/A
	Cooked pasta 71.5 ±0.6 c	0.203 ±0.047 a	33.8 ±0.3 c	2.38 ±0.04 c	N/A	8	121.6 ±6.4 b	271 ±38 a	2.44 ±0.32 a	14.4 ±1.0 a
	Pasta rested for 120 min at 20°C before drying at high temperature
	Dried pasta	55.2 ±0.1 a	3.88 ±0.02 a	39.9 ±0.1 a	1.50 ±0.03 a	11	N/A	N/A	N/A	N/A	N/A
	Cooked pasta 81.7 ±1.4 b	0.707 ±0.076 c	38.0 ±0.5 c	2.15 ±0.07 b	N/A	8	159.4 ±9.8 c 342 ±67 a	2.05 ±0.36 a	14.4 ±1.1 a
	Pasta rested for 120 min at 30°C before drying at high temperature
	Dried pasta	55.5 ±1.7 a	5.36 ±0.53 b	43.8 ±0.7 b	1.47 ±0.02 b	10	N/A	N/A	N/A	N/A	N/A
	Cooked pasta 76.3 ±4.6 b	0.803 ±0.290 c		2.50 ±0.04 d	N/A	8	113.2 ±7.0 b	295 ±44 a	2.62 ±0.42 a	13.0 ±1.7 a
	Pasta rested for 120 min at 40°C before drying at high temperature
	Dried pasta	54.9 ±0.8 a	4.29 ±0.57 a	41.6 ±1.4 a	1.47 ±0.03 a	11	N/A	N/A	N/A	N/A	N/A
	Cooked pasta 74.9 ±5.1 c	0.988 ±0.459 c	35.9 ±0.3 c	2.36 ±0.09 d	N/A	8	121.6 ±8.9 b 263 ±63 a 2.09 ±0.38 a	12.4 ±0.5 b
	Rheological measurement and cooking times were carried out in triplicates. Eight measurements were made for color, diameter and surface aspect.
	N/A: Not applicable.

Comment citer ce document : Martin, C., Morel, M. H., Reau, A., Cuq, B. (2019). Kinetics of gluten protein-insolubilisation during pasta processing: decoupling between time-and temperature-dependent effects. Journal of Cereal Science, 88, 103-109. , DOI : 10.1016/j.jcs.2019.05.014 ACCEPTED MANUSCRIPT -19 -

Acknowledgments

The authors kindly acknowledge L. Lhomond, G. Maraval, F. Rodriguez, and A. Reau for their help in pasta making and characterization, J. Bonicel, C. Fabre and T-M. Lasserre for biochemichal analyses, Panzani (Marseille, France) for providing durum wheat semolina. This work was supported by BPI France through the research program "Defi Ble Dur".