Romain Bey

Benoit Coasne

Cyril Picard

Probing the concept of line tension down to the nanoscale

A novel mechanical approach is developed to explore by means of atom-scale simulation the concept of line tension at a solid-liquid-vapor contact line as well as its dependence on temperature, confinement, and solid/fluid interactions. More precisely, by estimating the stresses exerted along and normal to a straight contact line formed within a partially wet pore, the line tension can be estimated while avoiding the pitfalls inherent to the geometrical scaling methodology based on hemispherical drops. The line tension for Lennard-Jones fluids is found to follow a generic behavior with temperature and chemical potential effects that are all included in a simple contact angle parameterization. Former discrepancies between theoretical modeling and molecular simulation are resolved, and the line tension concept is shown to be robust down to molecular confinements. The same qualitative behavior is observed for water but the line tension at the wetting transition diverges or converges towards a finite value depending on the range of the solid/fluid interactions at play.

I. INTRODUCTION

The contact line between three phases is a particular locus conducive to physical couplings between the macroscopic and the molecular scales. Diverse phenomena are intrinsically bound to the presence of a contact line, such as heterogeneous nucleation [START_REF] Guillemot | Activated drying in hydrophobic nanopores and the line tension of water[END_REF][START_REF] Remsing | Pathways to dewetting in hydrophobic confinement[END_REF][START_REF] Tinti | Intrusion and extrusion of water in hydrophobic nanopores[END_REF] , formation of nanovesicles from a membrane [START_REF] Satarifard | Nanodroplets at Membranes Create Tight-Lipped Membrane Necks via Negative Line Tension[END_REF] , dynamical wetting [START_REF] De Gennes | Wetting: statics and dynamics[END_REF][START_REF] Bonn | Wetting and spreading[END_REF][START_REF] Lhermerout | Contact angle dynamics on pseudo-brushes : Effects of polymer chain length and wetting liquid[END_REF] , and as a last example among others stabilisation and pinning of nanoinclusions at an interface (bubbles, droplets, colloids, etc.) [START_REF] Lohse | Surface nanobubbles and nanodroplets[END_REF][START_REF] Bresme | Computer Simulation Study of the Wetting Behavior and Line Tensions of Nanometer Size Particulates at a Liquid-Vapor Interface[END_REF][START_REF] Tan | Resolving the Pinning Force of Nanobubbles with Optical Microscopy[END_REF] . To better understand these phenomena, which play a key role in several applicative fields such as biotechnology (nanoemulsion, encapsulation) [START_REF] Singh | Nanoemulsion : Concepts , development and applications in drug delivery[END_REF] , chemical engineering (catalysis, electrochemistry) [START_REF] Debe | Electrocatalyst approaches and challenges for automotive fuel cells[END_REF] or process engineering (boiling, condensation) [START_REF] Karayiannis | Flow boiling in microchannels : Fundamentals and applications[END_REF] , a challenge remains in deciphering the effects due to the presence of a contact line. At the micron scale, the wedge that is formed in the vicinity of a solid/liquid/vapor contact line may be responsible for enhanced heat and mass transfer at the origin for instance of the well known coffee ring effect [START_REF] Deegan | Capillary flow as the cause of ring stains from dried liquid drops[END_REF] . At the nanometer scale, such a wedge has been identified to give rise to specific molecular interactions close to the three-phase contact line, at the origin of a specific free energy contribution: the line tension [15][16][START_REF] Weijs | Origin of line tension for a Lennard-Jones nanodroplet[END_REF] . This specific thermodynamical quantity was first mentioned by Gibbs 18 , who introduced the line tension τ as an excess free energy per unit length of contact line or a tangential force along this line. Unlike surface tension of planar fluid/fluid interfaces, line tension can be either positive or negative as there is no thermodynamical argument to predict its sign [START_REF] Rowlinson | Molecular Theory of Capillarity[END_REF] . From simple scaling arguments, the order of magnitude of τ for water is expected to be |τ | ∼ γ lv σ ∼ 20 pN with γ lv the liquid/vapor surface tension and σ the molecular size [START_REF] Guillemot | Activated drying in hydrophobic nanopores and the line tension of water[END_REF] . Such a scaling implicitly suggests that the impact of line tension is limited to the molecular scale 16 . Nevertheless, in the case of nanostructured materials, the effect of line tension can be scaled up a) Electronic mail: benoit.coasne@univ-grenoble-alpes.fr b) Electronic mail: cyril.picard@univ-grenoble-alpes.fr and impact macroscopic phenomena. For instance, it has been recently shown that line tension could control the macroscopic bulk pressure required to induce capillary drying within hydrophobic nanoporous material [START_REF] Guillemot | Activated drying in hydrophobic nanopores and the line tension of water[END_REF][START_REF] Tinti | Intrusion and extrusion of water in hydrophobic nanopores[END_REF] .

Despite its wide range of possible contributions, the understanding of line tension is still limited. Available measurements, either from experiments [START_REF] Wang | Line tension effects near first-order wetting transitions[END_REF][START_REF] Pompe | Three-phase contact line energetics from nanoscale liquid surface topographies[END_REF][START_REF] Checco | Nonlinear Dependence of the Contact Angle of Nanodroplets on Contact Line Curvature[END_REF][START_REF] Kameda | Size-induced sign inversion of line tension in nanobubbles at a solid/liquid interface[END_REF][START_REF] Berg | Impact of Negative Line Tension on the Shape of Nanometer-Size Sessile Droplets[END_REF][START_REF] Mcbride | Influence of line tension on spherical colloidal particles at liquid-vapor interfaces[END_REF][START_REF] Heim | Measurement of line tension on droplets in the submicrometer range[END_REF] or based on numerical simulations [START_REF] Weijs | Origin of line tension for a Lennard-Jones nanodroplet[END_REF][START_REF] Werder | On the water-carbon interaction for use in molecular dynamics simulations of graphite and carbon nanotubes[END_REF][START_REF] Hirvi | Molecular dynamics simulations of water droplets on polymer surfaces[END_REF][START_REF] Winter | Monte carlo test of the classical theory for heterogeneous nucleation barriers[END_REF][START_REF] Zhang | Influence of Contact-Line Curvature on the Evaporation of Nanodroplets from Solid Substrates[END_REF] , lead to mostly negative but also positive values for the line tension with magnitude spanning from 10 -6 to 10 -12 N, this dispersion being probably due to the diversity of methods and systems under investigation [START_REF] Law | Line tension and its influence on droplets and particles at surfaces[END_REF] . Moreover, from analytical predictions of Joanny and De Gennes, a divergence of line tension towards infinite positive values is expected for Lennard-Jones fluids at the wetting transition 15 . From this variability of τ , one must admit that estimating accurately line tension remains a delicate task with longstanding debates about the role of competing effects, such as line pinning [START_REF] Checco | Nonlinear Dependence of the Contact Angle of Nanodroplets on Contact Line Curvature[END_REF] or surface curvature corrections [START_REF] Joswiak | Sizedependent surface free energy and tolman-corrected droplet nucleation of tip4p/2005 water[END_REF][START_REF] Kanduč | Going beyond the standard line tension: Sizedependent contact angles of water nanodroplets[END_REF][START_REF] Das | Do the contact angle and line tension of surface-attached droplets depend on the radius of curvature?[END_REF] . Up to date, no consensus has been met on the dependence of line tension on physical parameters such as temperature, substrate hydrophilicity or fluid molecular structure.

Most experimental and molecular simulation measurements of line tension consist of evaluating the dependence of the contact angle θ of a sessile drop on the radius r of its circular contact line. In this approach, a simple decomposition into surface and line free energies reveals that a geometrical scaling, known as the modified Young equation, is expected [START_REF] Boruvka | Generalization of the classical theory of capillarity[END_REF] :

cos θ = cos θ Y - τ γ lv r (1)
where cos θ Y = (γ svγ sl )/γ lv is the Young contact angle defined from the solid-vapor γ sv , solid-liquid γ sl and liquid-vapor γ lv surface tensions. Eq. [1] implicitly assumes that surface and line tensions only depend on the nature of the materials so that changes in cos θ are proportional to 1/r. However, surface and line tensions can vary with the fluid chemical potential as well as with surface and line curvatures [START_REF] Boruvka | Generalization of the classical theory of capillarity[END_REF]36 . In this respect, while curvature seems to have a negligible impact on γ lv (expressed with the so-called Tolman length) down to submolecular sizes, its effect on line tension remains to be established [START_REF] Kanduč | Going beyond the standard line tension: Sizedependent contact angles of water nanodroplets[END_REF][START_REF] Das | Do the contact angle and line tension of surface-attached droplets depend on the radius of curvature?[END_REF] . Moreover, the geometrical approach in Eq. [1] suffers from difficulties in evaluating the shape of the sessile drop. In particular, experimental departures from Eq. [1] 22,24 cast doubt on the relevance of the geometrical scaling methodology to measure line tensions τ [START_REF] Das | Do the contact angle and line tension of surface-attached droplets depend on the radius of curvature?[END_REF]36,[START_REF] Marmur | Line Tension and the Intrinsic Contact Angle in Solid-Liquid-Fluid Systems[END_REF] . Even in molecular simulation approaches, the position of interfaces and lines is ambiguous at the molecular scale so that line tensions estimated numerically are subjected to large error bars.

In this paper, a molecular simulation methodology is developed to estimate line tensions τ without geometrical scaling. The effects of temperature, confinement, solid/fluid interactions, and chemical potential are investigated for any dispersive fluid modeled by a Lennard-Jones potential (LJ) and for water. In the spirit of the seminal work of Tarazona [START_REF] Tarazona | A statistical mechanical theory for line tension[END_REF] and recent approach of Shao et al 39 , statistical mechanics expressions are used to determine τ from the stress anisotropy in the vicinity of a triple line. While the approach of Shao et al 39 is mostly applicable to three fluid systems with limited interface curvature, our approach addresses the case of two fluids confined between solid walls (Fig. 1) without any restriction on the curvature of the fluid/fluid interface, that is for any contact angle and any confinement. In this approach, a liquid in contact with its vapor is confined, at a temperature T , in a slit pore of a width h formed by two solid planar walls perpendicular to the z direction (Fig. 1). The system is infinite in the x and y directions thanks to the use of periodic boundary conditions (see methodological details in Materials and Methods and Supplementary Information). Our approach avoids the delicate computation of local stresses or pressures at the vicinity of the contact line.

The value of τ is directly extracted from the measurement of total forces Σ x , Σ y and Σ z in the three space directions. This approach is used to probe the line tension of the contact line of a Lennard-Jones fluid or water within various confinements.

II. MATERIAL AND METHODS

A. A mechanical route to measure line tension

At mechanical equilibrium the total force Σ x exerted on the fluid system through a yz plane does not depend on the x location of the plane. For a plane within the vapor phase far from the liquid phase, Σ x relies on the vapor pressure P v and the solid-vapor surface tension γ sv while for a plane within the liquid phase far from the vapor phase it relies on the liquid pressure P l and the solid-liquid surface tension γ sl :

Σ x = L y (-P v h + 2γ sv ) = L y (-P l h + 2γ sl ) (2)
Due to translational invariance the force Σ y exerted on a slice of fluid (vapor + liquid) in the y direction does not depend on the location of the cutting plane. It arises from the three surface tensions γ lv , γ sl and γ sv , the liquid and vapor pressures P l and P v , and the line tension τ :

Σ y = -P v A v -P l A l + l sv γ sv + l sl γ sl + l lv γ lv + 4τ (3)
where A v and A l are the surface areas of the vapor and liquid phases in xz plane, l sv , l sl and l lv the lengths corresponding to the intersections of respectively solid/vapor, solid/liquid and liquid/vapor interfaces with xz plane.

To facilitate the determination of τ from Eq. [3] we introduce the algebraic area A m of each meniscus region (dark blue regions in Fig. 1), from which the liquid and vapor areas write respectively A l = hl sl /2 + 2A m and

A v = h(L x -l sl /2) -2A m .
The algebraic area A m , of the same sign as P l -P v , is positive for contact angle θ > π/2 and negative for θ < π/2. Replacing A l and A v by their respective expressions and using the mechanical balance in the x direction Eq. [2], the force in the y direction simplifies without the solid/fluid surface tensions :

Σ y = L x L y Σ x -2A m (P l -P v ) + l lv γ lv + 4τ (4)
As P l , P v and γ lv are considered as uniform, the radius of curvature R, of the liquid/vapor interface, is constant. The role of the line tension τ is precisely to take into account the molecular interactions between the three phases at the vicinity of the contact line that may alter locally this uniformity 15 . From the circular geometry of the liquid vapor interface, A m = R 2 (βsin(2β)/2) and l lv /2 = 2Rβ with β = θπ/2 standing for half the angle of the arc formed by a cut in a zx plan of the confined liquid/vapor interface (blue lines in Fig. 1). In these expressions the radius of curvature R = h/(2 sin β) is an algebraic quantity the same sign as β. Replacing A m , l lv and R by their expressions and using Laplace's law of capillarity, P l -P v = 2γ lv /R, the force Σ y further simplifies without pressures:

Σ y = L x L y Σ x + γ lv h sin(2β) + 2β 2 sin(β) + 4τ (5)
Isolating τ from Eq. [5] leads to the central relation of the paper:

τ = 1 2 Σ m -γ lv hK(θ) (6)
where the force Σ m = (Σ y -Σ x L x /L y )/2 corresponds to the total force in the y direction acting on each meniscus region (dark blue regions, blue lines and red dots in Fig. 1). The function K(θ) is a combination of trigonometric functions, which weakly depends on the contact angle (see Fig. 2(a)):

K(θ) = sin(2β) + 2β 8 sin(β) = 1 4 sin(θ) - θ -π/2 cos(θ) (7)
The function K is symmetric with respect to the angle θ = π/2 (or β = 0). The line tension τ given by Eq.

[6] is thus obtained from the difference of half the total force applied on a meniscus region in the y direction, that is the total force Σ m /2 based on line, surface and bulk contributions, minus the term γ lv hK(θ) which stands for the force due to bulk and surfaces only.

The forces Σ x and Σ y are computed using the virial expression of anisotropic stresses at an unstructured solid surface from the positions of the N fluid particles [START_REF] Schofield | Statistical mechanics of inhomogeneous fluids[END_REF][START_REF] Thompson | General formulation of pressure and stress tensor for arbitrary many-body interaction potentials under periodic boundary conditions[END_REF] :

Σ α = - N k B T L α + W α (8)
with α = x, y and k B Boltzmann's constant. W α is the energy derivative relative to a homogeneous affine expansion of all the fluid atomic positions and the system boundaries in the direction α.

Unlike the forces Σ x , Σ y and Σ m , line tension τ depends on the geometrical parameterization of the system. This dependence underlines that line tension is not an intrinsic parameter [START_REF] Schimmele | Conceptual aspects of line tensions[END_REF] except in the special case of a straight triple line formed by three fluids at the same pressure [START_REF] Rowlinson | Molecular Theory of Capillarity[END_REF] . This 1D exception is analogous to the 2D case of the intrinsic surface tension characterizing a planar interface that separates two phases at the same pressure. In the absence of pressure uniformity (as encountered here), line and surface tensions depend on the definition of interface position 36 . This is the case if interfaces are curved or in the presence of a solid phase under non-isotropic stress for which the concept of scalar pressure must be replaced by an elastic stress tensor. Surface and line tensions are therefore dependent on the choice made to define the position of the surface and contact angle as it appears in Eq. [6] where the value of τ depends on the geometrical quantities h and θ that may be defined according to various conventions at the molecular scale.

To adopt a definition of the distance h that is based on physical parameters, we consider the surface excess Γ l of fluid at the solid-liquid interface. The conservation of fluid mass in a vertical slab located in the liquid phase writes 2Γ l + hρ l = n l with ρ l the bulk liquid density (see Supplementary Information and Fig. 3) and n l the average number of molecules per unit of solid surface area in a slab perpendicular to the x direction taken within the liquid (inset of Fig. 3). Using the Gibbs convention, that is a zero fluid adsorption Γ l = 0, leads to the definition of h that verifies h = n l /ρ l .

The second geometric parameter, the contact angle θ, is then deduced from Laplace's law of capillarity:

cos θ = - (P l -P v )h 2γ lv = h l 1 2γ lv L y Σ z + P v L x L y -1 (9)
where Σ z , the force exerted by the fluid on the bottom solid surface, subdivides into volume and surface contributions Σ z = L y [2γ lv -P l l -P v (L x -l)]. This definition is self consistent with the establishment of Eqs. [6] and [7]. The so obtained contact angle incorporates disjoining pressure effects which are not, for simplicity reason, substracted to the pressure in the expression of Σ z (see Supplementary Information 5.2). Such a definition, fully agrees with macroscopic contact angle for large pores (see Fig. 3) but leads to an effective deviation of the contact angle for strong confinement (see Fig. 4(b)). Nevertheless, it turns out that this definition leads to an efficient way to parameterize the line tension at least for LJ fluids as shown in Fig. 5.

In the end, the numerical values of γ sl and γ sv are not needed to extract τ as these quantities simplify in the derivation. The distance l between the two vapor/liquid menisci is defined through the zero adsorption criterion at the liquid-vapor interface:

l = [n m -ρ v L x ]/[ρ l -ρ v ]
where n m is the average number of fluid molecules per unit of surface area in a slab perpendicular to the z direction at the center of the slit (inset Fig. 3). The vapor pressure P v is determined from the mean vapor density ρ v in the middle of the dry pore region using the ideal gas law, P v = ρ v k B T . Liquid-vapor surface tension γ lv is measured in an independent simulation of an infinite planar liquid-vapor interface following the classical mechanical route (see Supplementary Information). The definition Eq. [9] of the contact angle was used as it is relevant for any confinement h and solid-fluid interaction ε s .

B. Lennard-Jones fluid

The Lennard-Jones fluid involves repulsive and dispersive interactions with a total energy given by

U = i<j u f ij + i s u s i ( 10
)
where u f ij is the pair additive fluid interaction

u f ij = 4ε σ r ij 12 - σ r ij 6 (11)
and u s i is the fluid-wall interaction

u s i = ε s 2 15 σ s |z i -z s | 9 - σ s |z i -z s | 3 (12)
with s referring to the lower or upper solid plates located at z s (s = l, u), r ij the distance between fluid particles i and j, z i the z-position of fluid particle i and (ε, σ) and (ε s , σ s ) respectively the LJ fluid-fluid and solid-fluid interaction parameters (unless stated otherwise, σ s = 2σ). The fluid-wall 9-3 interaction Eq. [12] corresponds to the regular LJ potential integrated over a half space infinite solid. A truncation cutoff radius of r c = 4σ is used for fluid-fluid interactions. The temperature T is constrained using a Nosé-Hoover thermostat with a damping time t damp = 100∆t. In our simulation, the number of particles N varies between 560 and 18900. Each molecular dynamics simulation runs at constant volume V adjusted according to the number of particles, 42σ < L x < 90σ, L y = 21σ and L z = 80σ. The simulations consist of 10 8 timesteps with ∆t = 0.005 σ m/ε (m is the mass of the particle). The forces Σ α (α = x, y) expressed in Eq. [8] of the main article are computed every 100∆t. For post analysis, the configurations are stored every 10 4 ∆t. Error bars are computed using the block averaging method on blocks of size 9 × 10 6 ∆t, and are of the order of the symbol size in Fig. 5.

C. Water

Water molecular dynamics simulations were carried out with 480 to 3960 rigid SPC/E molecules in simu-lation boxes of dimensions [12, 24] nm L y = 4 nm L z = [3.35, 3.45, 3.55, 3.65, 3.75, 3.85, 4.85, 6.15] nm The confinement parameter h defined through the zero fluid adsorption condition at the solid-liquid surface varies between 1 and 5 nm. The line tensions shown in Fig. [7] correspond to the case L z = 3.75 nm and h = 2.6 nm. In the SPC/E model, fluid-fluid dispersive interactions are modeled using a Lennard-Jones potential with a cutoff radius of 9 Å. Electrostatic forces are computed using a cutoff radius of 9 Å coupled to a long-range correction computed through the PPPM algorithm. To avoid interactions between periodic images in the z direction, the methodology exposed in [START_REF] Yeh | Ewald summation for systems with slab geometry[END_REF] is applied, inserting 3 empty boxes between the periodic images in z direction. The motion of the water molecules is integrated using a rigid-body integrator with a timestep of ∆t = 2 fs. The temperature is constrained to T = 300 K using a Nosé-Hoover thermostat with a characteristic damping time t damp = 1 ps. Configurations are stored every 2 ps for post-analysis. Simulations are run for a total duration of 50 ns. Error bars are computed using the block averaging method on blocks of 450 ps.

L x =
The interaction between water and the solid is either chosen to be dispersive or to involve hydrogen-bonding. In the dispersive case, only oxygen atoms interact with the solid. To model this interaction, using Eq. [12], we choose σ s = 3 Å and ε s is varied between 1.57 and 7.22 kJ/mol to scan a broad range of hydrophilicities. In the hydrogen-bonding case, we model the water-solid interactions through a potential:

u s i = ηε s n -m m σ s |z i -z s | n -n σ s |z i -z s | m (13)
with [n, m] = [12, 6], σ s = 3.85 Å and ε s = 1.05 kJ/mol for oxygen atoms and [n, m] = [12, 8], σ s = 2.14 Å and ε s = 6.36 kJ/mol for hydrogen atoms. The parameter η is varied between 1 and 5.25 to scan a broad range of hydrophilicities. This would correspond, for real polar sites, to a variation of site density on the solid surface. The interaction potential with η = 1 is shown in Fig. 2(b). This interaction potential is inspired by similar potentials calibrated in the case of atomically structured solids to model H-bonding. Yoshida et al. [START_REF] Yoshida | Molecular dynamics simulation of electrokinetic flow of an aqueous electrolyte solution in nanochannels[END_REF] proposed the potential described by Eq. [13] to model the interatomic interactions between the atoms of the first solid layer and the water molecules using a parameter η = 2.34.

III. RESULTS

Molecular dynamics simulations were performed using LAMMPS [START_REF] Plimpton | Fast Parallel Algorithms for Short-Range Molecular Dynamics[END_REF] . We considered the strategy above to determine τ for the prototypical LJ fluid (parameters ε and σ). Full details regarding the molecular simulations can be found in Materials and Methods and Supplementary Information. As shown in Fig. 3, cos θ determined using Eq. [9] follows the expected linear dependence on ε s 46 and, for large h, agrees with contact angles measured through the shape regression technique of fluid density maps. The contact angle as defined by Eq. [9] is however not only dependent on the wall/fluid interaction strengths but also on other physical and geometrical parameters such as the confinement (Fig. 4(b)). This variation emerges from the dependence of solid/vapor and solid/liquid surface tensions on the separation h due to solid-fluid-solid interactions and adsorption effects (see Supplementary Information). In particular, solid-fluid-solid interactions induce a significant increase of the contact angle when perfectly wetting surfaces are brought together.

Different wall/fluid interaction strengths ε s , confinements h and temperatures T were considered to probe the value of the line tension τ on a broad range of parameters for the LJ fluid. At the higher considered temperature, of the order of 0.7 times the critical temperature, the error on the vapor pressure P v given by the perfect gas law is smaller than 5% [START_REF] Schlaich | Dispersion truncation affects the phase behavior of bulk and confined fluids: Coexistence, ad-sorption, and criticality[END_REF] . We checked for each parameter set, that the magnitude of τ is significantly larger than the fluctuations on each of the two terms used in the difference in Eq. [6] to extract τ (see Supplementary Information and Fig. S3). Moreover, as shown in Fig. 4(a), in most considered cases τ is larger than 10% of the last term of Eq. [6] which fully legitimizes its measurement from the difference between the two terms of Eq. [6]. Among the various considered cases, an important variability in the line tension values is observed. However, as shown in Fig. 5, all line tension values almost collapse on a single master curve when plotted according to the contact angle θ extracted for each set of parameters. Despite the large range of values explored for each parameter the limited departure from this general trend is particularly unexpected. The collapse of τ on a single curve for different ε s , σ s , T and h suggests that, to first order, the line tension can be estimated using θ only. This parameterization is possible when using the zero adsorption definition for h and the corresponding definition for θ given in Eq. [9].

The line tension plotted according to the contact angle demonstrates a non monotonic behavior with a minimum negative value for τ around θ = 90°and a divergence towards positive values close to the wetting transition. This behavior makes the bridge between nonlocal Density Functional Theory (DFT) calculations 17 (dashed line in Fig. 5) and Interface Displacement Model (IDM) by Joanny and de Gennes 15 (solid line in Fig. 5) at the wetting transition. At the dewetting transition θ → 180°, the vapor wedge separating the liquid from the solid vanishes together with its contact line and its associated free energy τ . For intermediate solid/fluid interaction strengths 0°< θ < 180°, the line tension is driven by a combination of microscopic effects that arise from the competition between the different molecular interactions but also potentially from fluid layering at interfaces. Here, analytic sums over molecular interactions do not allow estimating τ as it corresponds to a free energy contribution that also includes an entropy term [START_REF] Getta | Line tension between fluid phases and a substrate[END_REF] . For θ = 90°, τ can be seen as a correction of the liquid-vapor surface tension which accounts for the progressive vanishing of pressure anisotropy close to the solid surface. This reduced pressure anisotropy lowers the free energy cost related to the liquid-vapor interface so that τ is negative (as discussed in Supplementary Information, τ (90°) ∼ -γ lv σ = -0.74ε/σ). At the wetting transition θ → 0°, liquid-vapor and solid-liquid interfaces become parallel and close to each other in the vicinity of the contact line. In this configuration, the line tension τ is mainly controlled by the disjoining pressure which arises from the interaction between these two interfaces. In this case, the IDM 15 predicts that the line tension diverges as τ = γ lv a(ln(1/θ) -1) with a a solid-fluid interaction length (see Supplementary Information). The molecular simulation data in Fig. 5 are consistent with the divergence predicted at the wetting transition by the IDM (solid line in Fig. 5). Figure 5. Line tension τ for a LJ fluid confined in slit pores of width h ranging from 2 to 21 σ. For a given h, different interaction strengths εs are considered (same color code as in Figs. 3 and4 ). For a given color, the intensity from opaque to transparent indicates increasing h (see inset showing τ as a function of h for different Different T were considered: kBT /ε = 0.7 , 0.75 , 0.85 , 0.9 , 0.95 , and 1.0 . The dashed line represents a nonlocal DFT model in a wedge [START_REF] Weijs | Origin of line tension for a Lennard-Jones nanodroplet[END_REF] . The solid line corresponds to the Interface Displacement Model at the wetting transition 15 . Simulations with σs = σ lead to a similar behavior (black circles). Right axis: same τ but in real units using LJ parameters for argon ( σ = 3.4 Å, ε/k b = 120 K).

For wetting surfaces θ < 90°, the effect of confinement on line tension provides evidence for the limitation of the scaling methodology based on Eq. [1] (inset of Fig. 5). Line tensions are sometimes assumed to correspond to the curvature dependence of the liquid-vapor surface tension described through the Tolman length [START_REF] Kanduč | Going beyond the standard line tension: Sizedependent contact angles of water nanodroplets[END_REF][START_REF] Das | Do the contact angle and line tension of surface-attached droplets depend on the radius of curvature?[END_REF] . Yet, a major difference between effects arising from the stress anisotropy close to the contact line and curvature effects lies in the the spatial distribution of the excess free energy. While τ corresponds to effects localized in the vicinity of the contact line, curvature effects are distributed over the whole liquid-vapor interface (meniscus). Fig. 6(a) shows an estimate of the distribution of local stress anisotropy p yp x and local excess free energy ϕ(x, z) with respect to the bulk and surface value for a representative example θ ∼ 90°(local stresses were obtained from post-processing of the simulation following the Irving-Kirkwood convention 49 ). Fig. 6(b) shows that the excess free energy φ(z), obtained from the integration of ϕ(x, z) along the x direction, is strongly localized close to the triple lines, therefore supporting the line tension concept (see Supplementary Information for computation details). The novel strategy presented here was also used to determine the line tension τ for water (SPC/E water model) in the vicinity of structureless solid surfaces which interact with water through dispersive interactions or through homogeneously distributed hydrogen bonding [START_REF] Yoshida | Molecular dynamics simulation of electrokinetic flow of an aqueous electrolyte solution in nanochannels[END_REF] (see Materials and Methods and 44 ). Measurements are done at room temperature T = 300 K at which the water vapor is well modeled as a perfect gas. Wall-induced polarization effects, ignored with the first type of interaction, are taken into account with the second type of interaction which mimics proton-acceptor sites of real surfaces. Fig. 7 shows τ for water as a function of θ for both solid surfaces to investigate the effect of the molecular interactions at play. The two data sets feature a non monotonic behavior similar to that observed for the Lennard-Jones fluid. In both cases τ is minimum around 90°and vanishes at the dewetting transition θ → 180°. This general non monotonic behavior suggests that the unifying formalism, described earlier for the LJ fluid, can be used for various fluids and solid/fluid interactions.

However, an important difference is observed at the wetting transition θ → 0°. The line tension τ for water close to dispersive surfaces becomes positive and diverges while it converges to a finite, seemingly negative, value for hydrogen-bonding surfaces. In view of the difference between the two interaction types, it is tempting to qualitatively relate such a behavior to the theoretical predictions of Indekeu 15,[START_REF] Indekeu | Line tension near the wetting transition: results from an interface displacement model[END_REF] in the framework of the IDM. In the dispersive case, characterized by z -3 attractive interactions between the solid and oxygen atoms of water, like for the LJ fluid, a divergence of the line tension at wetting is predicted. In the hydrogen-bonding case, water interactions with the solid differ in terms of oxygen/solid and hydrogen/solid interactions. Attractive interactions of oxygen and hydrogen atoms with solid plates scale respectively as z -6 and z -8 (see Fig. 2(b)). In both cases, these interactions decay faster than those corresponding to Van der Waals interactions (see Fig. 2(b)) so that they can be referred to short-range interactions according to Indekeu's formalism. The IDM model predicts for such short-range fluid/solid interactions that the line tension converges towards a finite and positive value. The fact that a finite line tension is measured at the wetting transition in the hydrogen bonding case suggests that it is indeed mainly controlled by these so called short-range interactions when θ → 0°. Figure 7. Line tension τ for water confined at room temperature (T = 300 K) in a slit pore of a width h = 2.6 nm between dispersive (circles) and hydrogen bonding (triangles) surfaces. For dispersive surfaces, the hydrophilicity is controlled by the solid-liquid interaction strength εs. For hydrogen bonding surfaces, the hydrophilicity is controlled by the parameter η (see Materials and Methods).

The line tension tension in the case of water confined between either of the two types of surfaces is found to be about -5 pN for a contact angle close to 90°. This value, measured at room temperature, is comparable with the value of -11 pN extracted by Tinti et al from a simulation of a bubble nucleation within a hydrophobic cylindrical nanopore corresponding to a contact angle of 119°3. The similarity between these two line tension values is remarkable given the strong difference between the two numerical approaches. Here we study a straight contact line at equilibrium, while Tinti et al study an out of equilibrium nucleation during which the contact line is presumably submitted to strong variations in term of geometry and curvature. The factor of 2 between the two numerical values could reflect a sensitivity of the line tension to curvature. It could also be a due to the difference between the solid (smoth flat wall versus atomistic cylindrical wall) and the numerical water model (SPC/E versus TIP4P) at play in the tow studies. Our results with SPCE/E water suggest indeed that the nature of the solid may have an impact on the line tension. Although the negative extremum value of the line tension is similar for the two solids we considered, the extremal values are obtained at different contact angles. Nevertheless a factor of 2 between our value and Tinti's value is not so large when considering the range of values, covering several order of magnitude, that is found in the literature. Even more striking is the proximity of these values with the experimental value of -25 pN deduced from the experimental measurement of the extrusion pressure of pure real water out from hydrophobic nanopores (silica grafted cylinders) having a similar contact angle 1 . Again the difference in the nature of the solid and of the liquid as well as the nature of the system, straight contact line versus curved out of equilibrium contact line, could explain the difference between the three measured values.

IV. CONCLUSION

This study sheds light on the concept of line tension. It unravels a generic behavior, with in the case of dispersive fluids, a main dependence on the contact angle only. Using a novel strategy relying on a mechanical measurement at the molecular scale, our data for the Lennard-Jones fluid and water provide robust line tensions which depend on the wetting properties of the solid surface by the liquid phase. Our line tension values are found to be consistent with a series of theoretical, numerical and experimental data.

The generic behavior emerging from our data, established on a full range of contact angles, allows unifying the different, sometimes conflicting, pictures in the literature. Far from the wetting transition, the line tensions inferred from our analysis suggest that this concept is robust down to the molecular scale with a simple dependence on confinement, temperature and solid-fluid interaction encompassed in the contact angle. For a contact angle about 90°, the line tension for water at room temperature is consistent with that inferred from out of equilibrium numerical and experimental measurements based on water extrusion from hydrophobic porous materials. Beyond measuring line tension values, the computational approach is particularly useful to identify the molecular structures, which are not accessible experimentally, such as layering, adsorption, presence of chemical groups such as OH -responsible for the measured line tension. While the present study is limited to a single liquid/vapor system at equilibrium on unstructured solid surfaces, additional physical features are to be expected for structured and thermalized surfaces, fluid mixtures, and out of equilibrium processes such as bubble nucleation.

Figure 1 .

 1 Figure 1. Set-up consisting of a liquid in contact with its vapor confined between two solid walls (perpendicular to the z direction). Solid/fluid interfaces are separated by a distance h. Periodic boundary conditions are applied along the x and y directions which are parallel and perpendicular to the red contact lines. The line tension τ of these straight contact lines is estimated from the forces Σx, Σy and Σz exerted along x, y and z.

Figure 2 .

 2 Figure 2. (a) Trigonometric function K(θ) accounting for bulk and surface contributions to the meniscus free energy Σm. (b) Interaction potentials of the hydrogen-bonding solid used in the water simulations. The hydrogen of water is strongly attracted towards the solid, therefore mimicking a hydrogen bond interaction.

Figure 3 .

 3 Figure 3. Contact angles θ obtained for a Lennard-Jones fluid from Eq.[9] for large confinements (filled circles) or from shape regression for large hemicylinders (empty squares, right insets, see Supplementary Information). Contact angles are plotted according to the ratio of the fluid/solid to the fluid/fluid interaction strengths εS/ε (values increasing from purple to red). The top inset shows the density of the structured fluid in blue with the yellow and red areas denoting the regions used to define the confinement h and the meniscus separation l (these regions contain n l and nm molecules, respectively, see text).

Figure 4 .

 4 Figure 4. (a) Dimensionless ratio of the line tension τ over the total force hγ sl K due to bulk and surface contributions for several fluid/solid to fluid/fluid interaction strength ratio εs/ε increasing from purple to red. For a given color, the intensity from opaque to transparent indicates increasing h. (b) Dependence of the contact angle θ on the relative confinement h/σ according to the interaction strength ratio (colors).

ε/σ 3 pFigure 6 .

 36 Figure 6. (a) Local pressure anisotropy px -py and excess free energy ϕ(x, z) for a LJ fluid confined in a slit pore. The solid-fluid interaction strength εs was chosen so that θ = 96°. (b) Distribution of the excess free energy φ(z) obtained as the integral along x of ϕ(x, z) . Each color plot corresponds to a different h which increases from purple to green. The colored areas, which represent the integral of the excess free energy along the z direction, correspond to 2τ .

εs = 7

 7

ACKNOWLEDGMENTS

This work was supported by the French Research Agency (ANR TAMTAM 15-CE08-0008 and LyStEn 15-CE06-0006). We thank E. Charlaix for fruitful discussions and NVIDIA Corporation for the donation of a Tesla K40 GPU used for this research.


Marine Börlin

Cécile Miot-Sertier

Emmanuel Vinsonneau

Stéphane Becquet

Franck Salin

Marina Bely

Patrick Lucas

Warren Albertin

Jean-Luc Legras

Isabelle Masneuf-Pomarède
email: isabelle.masneuf@agro-bordeaux.fr

The "pied de cuve" as an alternative way to manage indigenous fermentation: impact on the fermentative process and Saccharomyces cerevisiae diversity

Keywords: pied de cuve, diversity, Saccharomyces cerevisiae, microsatellites, wine

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

The "pied de cuve" as an alternative way to manage indigenous fermentation: impact on the fermentative process and Saccharomyces cerevisiae diversity

INTRODUCTION

Winemaking implies the presence of various and successive populations of microorganisms, like fermentative yeasts, to conduct alcoholic fermentation. The use of Active Dry Yeast (ADY) as a fermentation starter is widely recommended to secure the process and avoid sluggish or stuck fermentation. In an opposite direction, there is an increasing demand, mainly from organic wine producers, to use indigenous S. cerevisiae strains from their own vineyards with the aim of limiting oenological inputs during the process and to try to increase specificities associated with the local "terroir". Indeed, the selection of yeast strains from indigenous populations for industrial development has been the subject of different studies (Di Maro et al., 2007;Settanni et al., 2012;Tofalo et al., 2009;Tofalo et al., 2014;Garofalo et al., 2018a;Garofalo et al., 2018b). However, in some cases, spontaneous fermentations could lead to irregular wine quality due to lack of alcoholic fermentation control, thus resulting in potential aromatic deviations or alterations to the final products. Thus, there is a need for new developments and guidelines to improve technological processes for exploiting indigenous microorganisms.

Besides the classical method of directly using ADY, some wineries traditionally elaborate wines with "pied de cuve" (PdC) (Clavijo et al., 2011, Li et al., 2012;Moschetti et al., 2016). By promoting the growth of fermentative strains in a small volume, this method is used to trigger alcoholic fermentation and control its progression, especially for the first vats filled at the beginning of the harvest period. The PdC is based on a small volume of fermented musts prepared a few days before harvest and used to inoculate the subsequent batches of grape juice. The technique consists in collecting grapes a few days before harvest and obtaining, after grape crushing, a fermenting fresh juice that will be subsequently used as a preculture. To avoid possible off-flavours, several grapes are harvested and processed separately in order to select the lot with the best fermentation kinetics and without sensory defects, such as acetic acid or ethyl acetate production. The implementation of PdC can then continue using must from fermenting tanks to inoculate the next batch. This process permits an already adapted yeast population to enter the fresh grape must. Till now, very few studies have reported results on PdC inoculation. Fortified PdC (crushed grapes with the addition of ethanol) has been successfully used to accelerate spontaneous alcoholic fermentation and to influence the sensory profile of red wines (Moschetti et al. 2016). In the case of high sugar concentration fermentation, different inoculum protocols using yeast collected from a fermented must or pre-culture yeast were shown to limit the amount of acetic acid of the resulting wines [START_REF] Bely | Influence of physiological state of inoculum on volatile acidity production by Saccharomyces cerevisiae during High Sugar Fermentation[END_REF]. In a recent study, the successful use of a PdC made with vineyard-derived yeasts was shown to be highly dependent on SO 2 addition and on the microbial composition of the inoculum (Morgan et al., 2019). The authors recommend that the winemakers perform PdC on a small subset of fermentation that can later be used for blending in order to increase wine complexity. Thus, the implementation of the PdC method is still empirical in wineries and knowledge is lacking regarding the impact of PdC on S. cerevisiae diversity during alcoholic fermentation. The main objective of this study was to evaluate the impact of PdC on the microbial, chemical and sensory characteristics of the wine.

MATERIALS AND METHODS

PdC protocol preparation

Two PdC were managed from Ugni blanc and Sauvignon blanc grape varieties in the wine estate Du. Undamaged grapes (15 kg) were manually harvested for each variety 4 days before harvest. The grapes were crushed in clean containers giving for each variety two lots of around 12 litres of must. The lots were kept in the whitewine cellar at a temperature of between 18 and 20 °C. After 2 days of alcoholic fermentation, ammonium phosphate and thiamine were added to reach the level of 200 mg l -1 [START_REF] Bely | Automatic detection of assimilable nitrogen deficiencies during alcoholic fermentation in oenological conditions[END_REF] and 0.60 mg l -1 respectively. The density and temperature of each PdC were monitored daily. The PdC were then kept until around 30-50 % of the alcoholic fermentation was reached. Finally, the PdC were subjected to sensory (panel of three tasters) and chemical analyses to evaluate possible off-flavour deviations and acetic acid content (analytical method described hereafter). If one of the PdC had failed one of these analyses, it would not have been retained for this project.

Analytical and population counting analyses

Total acidity (TA), reducing sugars (g l -1 ), turbidity (NTU -Nephelometric Turbidity Unit) and assimilable nitrogen were measured for each PdC before fermentation and for Sauvignon gris must. Sugar (g l -1 ), acetic acid (g l -1 ) and ethanol concentrations (% vol.) were measured by infrared reflectance (Wine Scan™, FOSS, Hillerod, Denmark) at 30-50 % of fermentation of the PdC modalities and at the end of alcoholic fermentation in barrels. The volatile acidity (expressed in g l -1 acetic acid) was determined chemically by colorimetry (A460 nm) in continuous flux (Sanimat, Montauban, France).

The analyses were performed in accordance with the official methods described by the European Commission (1990). The amount of indigenous yeast population (CFU l -1 -Colony-Forming Unit) was calculated by YPD-plate counting in the PdC before and at 30-50 % of fermentation.

Barrel inoculation

The PdC were transferred into four 225 litre barrels which were filled with Sauvignon gris "cold settled" must (Sugars 231 g l -1 , pH 3.35, Total acidity 6.1, Yeast Assimilable Nitrogen 133 mg l -1 , Turbidity 51 NTU). Yeast Assimilable Nitrogen level was adjusted to 200 mg l -1 [START_REF] Bely | Automatic detection of assimilable nitrogen deficiencies during alcoholic fermentation in oenological conditions[END_REF]. Initial colony counts in Sauvignon gris were 4.10 6 and 9.10 5 UFC ml -1 for total yeast and non-Saccharomyces yeast respectively. PdC inoculum volume ratio was 1/20 of Sauvignon gris must. Two additional barrels were prepared as controls: one was inoculated with the commercial strains Zymaflore X5 at 200 mg l -1 following the industrial recommendations, and the other was spontaneously fermented. The density and temperature of each barrel was monitored every day. At the end of the alcoholic fermentation, samples were taken for chemical analyses and each barrel was judged for tasting criteria.

Microbial sampling

Samples were taken from the PdC must at around 30-50 % of the alcoholic fermentation, just before the barrel's inoculation. They were directly plated onto the media of Total Yeast (TY) and Non-Saccharomyces (NS) at different serial dilutions (10 -4 , 10 -5 and 10 -6 ), and kept at 26 °C on these two media for 5 and 10 days respectively. The TY and NS media were based on YPD (yeast extract, 1 % w/v, peptone, 1 % w/v, glucose, 2 % w/v, agar 2 % w/v), with 100 µg ml -1 of chloramphenicol and 150 µg ml -1 of biphenyl to delay bacterial growth for the TY medium, and an additional 500 µg l -1 of cycloheximide for the NS medium. Microbial sampling was carried out on the Sauvignon gris must before alcoholic fermentation and on the 6 fermented barrels when they reached 75 % of the fermentation. For PdC just before inoculation, 30 randomly chosen colonies were collected. For barrels at 75 %, 10 colonies were collected.

After two sub-cloning on YPD plates, each colony was stored in (30 %, v/v) glycerol at -80 °C. In addition to those fermentation samples, and as a referenced out-group, 33 commercial wine strains (Supplementary data, Table S1) which are widely used as yeast starters were added to the data set.

Molecular methods

For all clones, a small amount of fresh colony was suspended in 50 µl of MilliQ water and 7 µl of this suspension was dropped on a Sigma-Aldrich Whatman® FTA® card for DNA preservation.

The clones were first analysed with PCR amplification of the ITS region with primers ITS1 ( 5' -TCCGTAGGTGAACCTGCGG-3' ) and ITS4 ( 5' -TCCTCCGCTTATTGATATGC- The selected Saccharomyces isolates were then analysed using microsatellites markers. Isolates were genotyped using 2 multiplex PCR reactions of 8 and 7 microsatellites loci for mixes 1 and 2 respectively (Supplementary data, Table S2) [START_REF] Börlin | Cellar-associated Saccharomyces cerevisiae population structure[END_REF]. At least 8 samples were prepared for a volume of 100 µl with 50 µl of 2X QIAGEN Multiplex PCR Master Mix in both mixes. Mix 1 had 8 multiplexed primers and mix 2 the 7 others, each having a specific concentration (specified in Table S2). The PCRs were run in a final volume of 12 μl containing 2 μl of cell suspension. The following routine PCR programme was used: initial denaturation at 95 °C for 15 minutes followed by 35 cycles of 95 °C for 30 seconds, 57 °C for 2 minutes, 72 °C for 1 minute and a final extension at 60 °C for 30 minutes. PCR products were sized on a capillary electrophoresis ABI3730 (Applied Biosystems) using size standard 600LIZ® (GeneScanTM).

Data analyses

ABI3730 genotyping results were read using GeneMarker (V2.4.0, Demo). The presence of OENO One 2020, 3, 435-442

Marine Börlin et al.

a missing value was allowed to a maximum of 4 markers per isolate. GenClone (V2.0) software was used to remove from our dataset strains with exactly the same profiles resulting from potential clonal expansion. Dendrogram was constructed using Bruvo's distance (Bruvo et al., 2004) and neighbour-joining clustering by means of the R programme (V3.2.5) with the following packages: ape (V3.2.5) and poppr (V2.8.0).

Shannon Index (H') was determined using the following equation, with ni as the number of individuals for genotype i and N the total of unique genotypes:

RESULTS

PdC implementation

Sauvignon blanc (SB) and Ugni blanc (UB) (late and early ripening grape varieties respectively) were collected four days before harvest to produce two PdC, with the aim of obtaining PdC from two grape samples with contrasted maturity levels. Indeed, chemical analyses of the juice just after grape crushing showed different maturity levels: sugar content was 182 g l -1 and 135 g l -1 for SB and UB respectively, and total acidity was 5.9 g l -1 and 8.6 g l -1 for SB and UB respectively. The colonies count on both media were higher in Sauvignon blanc juice than in Ugni blanc: 1.10 5 and 1.10 4 UFC/mL respectively for total yeast, and 8.10 4 and 7.10 3 UFC/mL for non-Saccharomyces yeast.

Chemical and microbial analyses were then performed just before the inoculation of the barrels to evaluate the fermentation stage, and to infer if the PdC were good potential starters (Table 1).

The sugar consumption of the Sauvignon blanc PdC was between 34 and 38 %, whereas it was between 42 and 50 % for the Ugni blanc PdC. The acetic acid content was similar whatever the modality considered, ranging from 0.35 to 0.40 g l -1 . Just before the inoculation of the barrels, the different PdC modalities had similar population levels, from 2.10 7 to 6.10 7 UFC/mL for TY and 1.10 7 to 3.10 7 for NS, thus suggesting that the non-Saccharomyces yeast population was the dominant one.

The possibility of using the PdC to inoculate the barrels was further confirmed by sensory analysis, since no defect was detected.

From the TY medium, 30 yeast isolates obtained from the 4 fermented PdC before inoculation and 10 isolates at 75 % of alcoholic fermentation of the 6 barrels were analysed by ITS-PCR-sequencing (Table 2). From the different PdC, only five isolates out of 120 were identified as S. cerevisiae, whereas the remaining 115 isolates were identified as Hanseniaspora uvarum. S. cerevisiae was only isolated from the SB PdC (Table 2). Isolates collected from the six barrels were all identified as S. cerevisiae, thus resulting in a total number of 65 Saccharomyces isolates analysed through microsatellites markers. Only strains with less than 4 missing values were retained in the data set, which resulted in 59 S. cerevisiae isolates for further analysis (Table 2).

FIGURE 1.

Neighbor joining tree clustering 59 strains from PdC and barrels fermentations and 33 commercial strains. The tree was constructed from Bruvo's distance between strains based on the polymorphism at 15 loci.

Color code: black; commercial strains, red; S. cerevisiae isolated from PdC, purple and green; isolates from Sauvignon blanc PdC barrels, orange and light blue; isolates from Ugni blanc PdC barrels, brown; barrels inoculated with commercial strain X5, blue; isolates from barrels from spontaneous fermentation. Black narrows indicated S. cerevisiae isolates collected from PdC.

The genetic diversity of the 59 S. cerevisiae isolates was analysed through a neighbour-joining tree, including 33 commercial starters (Figure 1). It was possible to observe that the four S. cerevisiae isolates originating from the PdC were spread over the tree (black arrows, Figure 1). Thus, none of the 4 strains isolated from the PdC were recovered at mid-fermentation in the barrels.

Moreover, isolates collected from barrels inoculated with the same PdC variety clustered in different groups. A cluster of almost identical isolates resulting from clonal expansion was observed, especially for the Ugni blanc PdC (UgB_PDC_B) grouping 9 out of the 10 strains analszed with the lower diversity index (Table 2). To a lesser extent, similar clusters of almost identical isolates resulting from clonal expansion can be noticed for strains isolated from PdC Sauvignon blanc (SB PDC B) and PdC Ugni blanc (UgB PDC A), grouping 4 out of 8, and 4 out of 10 strains analysed respectively. As expected, 8 isolates collected in the inoculated barrel with the industrial starter X5 clustered with the X5 strain. Surprisingly, one S. cerevisiae isolate originated from the PdC (2duSBp(-)16) grouped in the same cluster. No clonal cluster was observed for the 8 isolates of the spontaneous fermentation, this sample showing the higher diversity (Shannon index, Table 2).

Wine analyses and fermentation time

The chemical analyses and fermentation time of the samples collected at the end of the alcoholic fermentation of the six modalities (four barrels fermented with the PdC, plus two controls; one with spontaneous fermentation and one directly inoculated with X5 commercial strain fermentation) are given in Table 3. The fermentation kinetics were similar for the inoculated modality and for the Sauvignon blanc PdC (Table 3 and Figure S1). However, fermentation time of the PdC Ugni blanc B modality was longer than for the spontaneous fermentation modality with 18 and 17 days respectively. Volatile acidity level (0.44 to 0.57 g l -1 acetic acid) was similar for all the modalities, except for SG/UB_PDC_B for which volatile acidity was high (0.61 g l -1 acetic acid), probably due to longer fermentation duration. Finally, a sensory analysis was performed by a panel of 15 professional tasters using black ISO glasses (NF V09-110, 1971), who gave a descriptive analysis of the wines. No significant differences were detected between all the modalities (results not shown).

DISCUSSION

There is an increased demand, especially for organic wine producers, to limit inputs and to better use the microbiological diversity present in their vineyards. Two methods are possible to achieve this goal: i) the selection of high fermentative S. cerevisiae yeasts from the indigenous population, followed by small scale industrial production, following organic production rules in the case of organic producers (Settanni et al., 2012;Liu et al., 2015), or ii) the production of a home-made yeast inoculum from selected grape juice a few days before harvest or from the first spontaneous fermented vat. This latter method has been reported to have some positives impacts on fermentation and the final product [START_REF] Bely | Influence of physiological state of inoculum on volatile acidity production by Saccharomyces cerevisiae during High Sugar Fermentation[END_REF]Santamaría et al., 2005;[START_REF] Börlin | Cellar-associated Saccharomyces cerevisiae population structure[END_REF].

In this study, modalities using two grape varieties were prepared to evaluate the impact of the PdC on S. cerevisiae diversity, fermentation management and wine composition. The use of PdC to manage alcoholic fermentation was compared with the traditional use of ADY and spontaneous fermentation. With the exception of one modality, the fermentation times of PdC inoculated barrels were similar to those observed for the ADY inoculated control fermentation. In this trial, and in terms of alcoholic fermentation kinetics, the use of the PdC method has provided results which are comparable to the classical use of commercial strains. However, more tests are required in order to assess the success rate of such an approach. It is noteworthy that the barrels inoculated with the Ugni blanc PdC and the spontaneous fermentation modality had longer fermentation duration and higher acetic acid content. Except for the two latter modalities the use of the fresh PdC must was as efficient as ADY in terms of chemical and sensory analyses of the resulting wines. However, the grapes with higher maturity level were those leading to a PdC containing higher frequency of S. cerevisiae, suggesting that this factor might be important, even though Saccharomyces are rarely found in significant numbers on healthy grapes (Mortimer and Polsinelli, 1999). No significant differences were found between the wines as a result of the descriptive sensory analysis. Thus, in our experimental conditions, the use of PdC did not lead to distinct wines according to the origin of the yeast strains in the vineyard.

The microbiological analysis of the PdC revealed surprising results. First of all, the alcoholic fermentation of the PdC mainly occurred through non-Saccharomyces yeast; H.uvarum and S. cerevisiae were particularly rare, especially when using the culture method. It was not possible to isolate S. cerevisiae strains in the 2 Ugni blanc PdC, probably due to the lack of ripening for the grapes when they were collected. Food Microbiol. Nov 20;285:7-17. doi:10.1016/j. ijfoodmicro.2018.07.004 Li E., Liu C., and Liu Y., 2012. Evaluation of yeast diversity during wine fermentations with direct inoculation and pied de cuve method at an industrial scale. J Microbiol Biotechnol. Jul;22( 7 Moschetti G., Corona O., Gaglio R., Squadrito M., Parrinello A., Settanni L., Barone E.and Francesca N., 2016. Use of fortified pied de cuve as an innovative method to start spontaneous alcoholic fermentation for red winemaking. Australian J of Grape andWine Research, 22, 36-45. doi:10.1111/ajgw.12166 Settanni L., Sannino C., Francesca N., Guarcello R. andMoschetti G., 2012. Yeast ecology of vineyards within Marsala wine area (western Sicily) in two consecutive vintages and selection of autochthonous Saccharomyces cerevisiae strains. Journal of Bioscience and Bioengineering, 114(6), 606-614. doi:10.1016/j. jbiosc.2012.07.010 Tofalo R., Chaves-López C., Di Fabio F., Schirone M., Felis G.E., Torriani S., Paparella A. and Suzzi G., 2009. Molecular identification and osmotolerant profile of wine yeasts that ferment a high sugar grape must. Int J Food Microbiol. Apr 15;130(3):179-87. doi:10.1016/j. ijfoodmicro.2009.01.024 Tofalo R., Perpetuini G., Fasoli G., Schirone M., Corsetti A. and Suzzi G., 2014. Biodiversity study of wine yeasts belonging to the "terroir" of Montepulciano d'Abruzzo "Colline Teramane" revealed Saccharomyces cerevisiae strains exhibiting atypical unique 5.8S-ITS restriction patterns. Food Microbiol. May 39: 7-12. doi:10.1016/j.fm.2013.10.001.

  Marine Börlin, Cécile Miot-Sertier, Emmanuel Vinsonneau, Stéphane Becquet, Franck Salin, Marina Bely, Patrick Lucas, Warren Albertin, Jean-Luc Legras, Isabelle Masneuf-Pomarède To cite this version: Marine Börlin, Cécile Miot-Sertier, Emmanuel Vinsonneau, Stéphane Becquet, Franck Salin, et al..The "pied de cuve" as an alternative way to manage indigenous fermentation: impact on the fermentative process and Saccharomyces cerevisiae diversity.OENO One, 2020, 54 (3), pp.435-442. 10.20870/oeno-one.2020.54.3.3105. hal-02990584

  ):960-6. doi:10.4014/jmb.1111.11013 Morgan S.C., McCarthy G.C., Watters B.S., Tantikachornkiat M., Zigg I., Cliff M.A., Durall D.M., 2019. Effect of sulfite addition and pied de cuve inoculation on the microbial communities and sensory profiles of Chardonnay wines: dominance of indigenous Saccharomyces uvarum at a commercial winery, FEMS Yeast Res. Aug 1;19(5). doi:10.1093/femsyr/foz049 Mortimer R. and Polsinelli M., 1999. On the origins of wine yeast. Research in Microbioly;50:199-204 doi:10.1016/S0923-2508(99)80036-9

TABLE 1 .

 1 Chemical and microbial analyses of PdC musts before barrels inoculation. SB and UB meant respectively Sauvignon blanc and Ugni blanc and PcA and PcB represented the duplicats. For yeast population counts, values in brackets represent standard deviation (n=3).

	Origin	Samples	Number of isolates analyzed by ITS	Number of S. cerevisiae isolates analyzed by microsatellites	Number of strains with less than 4 missing markers	Shannon Index H'
		SB PA	30	3	2
	PdC	SB PB UB PA	30 30	2 0	2 -
		UB PB	30	0	-
		SG/SB_PDC_A	10	10	8	1.74
		SG/SB_PDC_B	10	10	10	1.90
		SG/UB_ PDC_A	10	10	10	1.83
	Barrels	SG/UB_ PDC_B	10	10	10	1.00
		SG Spontaneous fermentation	10	10	9	2.04
		SG inoculation with ADY	10	10	8	-
	Total		180	65	59

TABLE 2 .

 2 Summary of samples collected with PdC or barrel origin, indication of the samples code, number of yeast isolates analyzed by ITS PCR, microsatellites, final number of S. cerevisiae profiles after removing all strains with more than 3 missing markers values and Shannon index (H').

TABLE 3 .

 3 Chemical analyses of the barrel musts at the end of the alcoholic fermentation (or total sugar consumption). SB, UB and SG meant respectively grape varieties Sauvignon blanc, Ugni blanc and Sauvignon gris. OD is for Optical density. Pc, Spo and LSA represented the pied de cuve modalities, spontaneous fermentation and direct inoculated fermentation with X5 commercial strain.

  Zarazoso B., Belloc C., Uruburu F. and Querol A., 1999. identification of yeasts by RFLP analyses of the 5.8 S rRNA gene and the two internal transcribed spacers. Int of System Bacteriology, 49, 329-337. doi:10.1099/00207713-49-1-329 Garofalo C., Berbegal C., Grieco F., Tufariello M., Spano G. and Capozzi V., 2018a. Selection of indigenous yeast strains for the production of sparkling wines from native Apulian grape varieties. Int J Food Microbiol. Nov 20;285:7-17. doi:10.1016/j. ijfoodmicro.2018.07.004 Garofalo C., Berbegal C., Grieco F., Tufariello M., Spano G., and Capozzi V., 2018b Selection of indigenous yeast strains for the production of sparkling wines from native Apulian grape varieties. Int J

	Marine Börlin et al.
	revealed high-level diversity and perennial persistence	differed from one modality to another, and
	at sauternes wine estates. Appl Environ Microbiol. May 2;82(10):2909-18. doi:10.1128/AEM.03627-15	to the S. cerevisiae population that occurred during spontaneous fermentation in the cellar.
	Bruvo R., Michiels N.K., D'souza T.G. and	A dominant population, in line with what could
	Schulenburg H., 2004. A Simple method for the	be obtained by using ADY, may process alcoholic
	calculation of microsatellite genotype distances	fermentation. The results seem to be uncertain
	irrespective of ploidy level. Mol Ecology 13 (7). doi:10.1111/j.1365-294X.2004.02209.x	since one modality failed in terms of fermentation kinetics and a high acetic acid level in the resulting
	Clavijo A., Caldero ń I.L. and Paneque P., 2011. Yeast	wine. The preparation of different PdC modalities
	assessment during alcoholic fermentation inoculated	should thus lead to a more secure process.
	with a natural "pied de cuve" or a commercial yeast strain. World J Microbiol Biotechnol 7:1569-77.	A question still remains to be answered.
	doi:10.1007/s11274-010-0609-y	It was shown here that the different PdC,
	Di Maro E., Ercolini D. and Coppola S., 2007. Yeast dynamics during spontaneous wine fermentation of the Catalanesca grape. Int J Food	apart from one Ugni blanc modality, showed well monitored fermentations with proper final product characteristics similar to the direct
	Microbiol. Jun 30;117(2):201-10. doi:10.1016/j.	ADY inoculation ones. Despite the very low
	ijfoodmicro.2007.04.007	frequency of S. cerevisiae yeast identified out
	Esteve-	of the 30 S. cerevisiae analysed for each PdC, the fermentations were completed. It has been
		shown that S. cerevisiae is capable of attaining
		from 0.1 to 99.9 % of overall yeast population
		growth in only a few days (Goddard, 2008).
		S. cerevisiae colonises the medium by producing
		a high amount of alcohol and heat through the
		Crabtree effect, and this latter trait provides a 7 %
		fitness advantage over the other members of the
		community (Goddard, 2008). The fitness advantage
		of S. cerevisiae over non-Saccharomyces yeast
		could explain the short lag-phase and complete
		fermentation of 3 out of 4 PdC modalities, despite
		very low S. cerevisiae population levels in the
		PdC before barrel inoculation.
	In our experimental
	conditions, due to the low S. cerevisiae population
	level in the PdC, more colony analyses, or an
	estimation of Saccharomyces sp. population
	level through quantitative PCR, would have
	been required to provide a better estimation
	of the S. cerevisiae frequency. Regarding the
	barrels, spontaneous fermentation showed high
	S. cerevisiae diversity, indicating that various
	strains grew leading to polyclonal populations
	during these fermentations, in contrast to ADY
	inoculation. For PdC inoculated barrels, clonal
	expansion of S. cerevisiae was highlighted during
	fermentation, especially for the Ugni blanc PdC,
	and to a lesser extent for the other modalities, with
	less than 50 % of the strains clustering together.
	The use of PdC seemed to enable the winemakers
	to select indigenous S. cerevisiae strains which
		OENO One 2020, 3, 435-442

© 2020 International Viticulture and Enology Society -IVES

Acknowledgements:

This study was supported by the CASDAR Project "LevainsBIO". The authors would like to thank Vignoble Boudon which kindly provided fermented samples, and the Syndicat des Vignerons Bio de Nouvelle Aquitaine for collecting samples and managing the PdC experiment.

https://oeno-one.eu/article/view/3105