# Effect of local temperature variability on vine phenology in the Saint-Emilion area (Bordeaux, France)

L. DE RESSEGUIER¹, H. QUENOL², R. LEROUX², C. VAN LEEUWEN¹*

¹Bordeaux Sciences Agro, Univ. Bordeaux, ISVV, Ecophysiology and functional genomics of grapevines, UMR 1287, F-33140 Villenave d'Ornon, France

²Laboratoire COSTEL, UMR 6554 LETG du CNRS, Université Rennes 2-Haute Bretagne, Rennes, France

Terroir – temperature variability – Saint-Emilion area – phenology – grape ripening

## Introduction

Terroir plays an important role in grape composition as well as in wine quality and typicity. Key factors in terroir expression are soil, climate and grapevine variety [1]. Over the past decades, soils of most winegrowing areas have been mapped at different scales. Studying climate variability, however, is a more recent practice. Thanks to the development of new technologies, especially the miniaturization of reasonably priced sensors, it has become possible to improve our knowledge of spatial climate variability, particularly with regard to temperature, at a fine scale. Knowing the importance of temperature on vine development [1-3] and wine quality [4], it has become of utmost importance to improve our assessment of this parameter for a better adaptation of plant material or training systems. A previous study, published in 2007, described the climatic variability in the wine growing area of Bordeaux [5]. It was based on the development of private and public weather stations. The study showed great variability in terms of temperature and modeled precocity for maturity in this area. The objective of this study is to assess climate variability at a higher spatial resolution. A network of temperature sensors was set up within a set of sub-appellations of the Bordeaux area, including the famous Saint-Emilion and Pomerol winegrowing areas. The first results show great temperature variability. Consequences on precocity, vine development and maturity are discussed.

## Materials and methods

### Temperature monitoring

In order to characterize temperature variability in this area of 12,200 ha of vineyards, a network of 90 temperature sensors was set up at the end of 2011. This corresponds to a density of 1 sensor for 240 ha. At this local scale, it is important to take into account the relief (exposition, slope, altitude) but also local parameters, such as rivers, urban areas, vegetation, and soil types, which can have an influence on the spatial distribution of temperature. The diversity of this area, both in terms of relief, local parameters and soil types, is particularly interesting for studying fine-scale temperature variations. The temperature sensors used in this project are Tinytag Talk2 (Gemini Data Loggers, UK). These sensors can be easily installed on vine posts inside the plot at 1.2 m in height. The data loggers have been parameterized in order to record both minimum and maximum hourly temperatures.

### Vine development and grape ripening monitoring

To measure the effect of temperature on vine development and wine quality, phenological stages (bud break, flowering and veraison) and grape maturity dynamics have been monitored on 18 reference plots of Merlot. Their position has been determined by taking into account all the local parameters which can have an influence on temperature variability, so as to have the greatest possible amplitude in precocity. Phenological stages are recorded for the specific day when 50 percent of vine organs reach C stage for bud break; I stage for flowering; M stage for veraison [6]. Every week, starting at veraison, major grape metabolites are measured and, prior to harvest, phenolic compounds (anthocyanin, total polyphenols, seed maturity) are also analyzed.
## Bioclimatic indexes

In order to implement climatic zoning in viticultural areas and to measure the climatic variability, several bioclimatic indices have been developed over the years. One of them, the Winkler degree days [7], is presented here. This index is based on the sum of temperatures above 10°C, from April 1st to October 31st.

# Results and discussion

## Temperature is highly variable, in particular for minimum temperatures

Our results show greater amplitude on the minimum daily temperature compared to the maximum temperature (Figure 1). During 2012, the amplitude of maximum day temperature was mostly around 3°C, while amplitude of minimum day temperature was about 4°C, but this fluctuates up to a maximum of 10°C. The type of weather has an impact on this spatial distribution, and some weather types, like anticyclonic clear sky conditions without wind, enhance thermal amplitude.

<figure><img src="image_28.png" /><figcaption>Fig. 1 - Daily temperature amplitude for maximum and minimum temperatures over the study area.</figcaption></figure>

A 1.5°C difference between the warmest (14.6°C) and coolest (13.1°C) sensors was recorded for mean temperature in 2012. During the vegetative season from April to October the mean temperature ranges from 17.9°C to 19.2°C (amplitude of 1.3°C). There is a difference of 3°C between the extreme sensors (6.2°C and 9.2°C) for minimum mean temperature. This difference is 1.4°C (19.1°C and 20.5°C) for maximum mean temperature. These differences are close to the results of the temperature variability in the overall Bordeaux winegrowing area which was, for the period of 2001-2005, about 2.9°C for minimum temperature and 1.9°C for maximum temperature [5].

<table><caption>Table 1 - Winkler Index and amplitudes between 2012 and 2014</caption><thead><tr><th></th><th>Winkler Index 2012</th><th>Winkler Index 2013</th><th>Winkler Index 2014</th></tr></thead><tbody><tr><th>Minimum</th><td>1622</td><td>1617</td><td>1704</td></tr><tr><th>Maximum</th><td>1889</td><td>1855</td><td>2019</td></tr><tr><th>Amplitude</th><td>268</td><td>238</td><td>315</td></tr></tbody></table>

## Great variation in temperature sum and spatial distribution for Winkler Index

Winkler index, which is well adapted to show the influence of temperature on vine development, has been calculated. The result (Table 1) shows a great amplitude of over 250°C.days in average in the years 2012 to 2014. Given these temperature ranges, vine development could be delayed by 30 days in the latest ripening plots, compared to early ripening plots.

Spatial distribution of Winkler index (Figure 2) shows the temporal variations which correspond to the vintage effect. 2014 was warmer than 2012 and 2013. These maps also highlight a spatial structure which is similar during the 3 years. The limestone plateau of Saint-Emilion and its south facing slopes are the
warmest area. The North East of the area, the South East and the bottom of the valleys are cooler. Another early area, not specifically linked with the topography, is the western part of the area around the town of Libourne, including Pomerol.

<figure><img src="image_29.png" /><figcaption>Fig. 2 - Maps of Winkler Index in the years 2012 to 2014 calculated on each temperature sensor.</figcaption></figure>

### *Vine response to climate variability*

Phenology observations carried out in 2012 and 2014 are presented in Table 2. These show, in particular, how important the vintage effect was: the warmer climatic conditions of 2012 and 2014 induced more spatial variability of temperature in this area and induced differences in the timing of phenological stages. We recorded a window of about 8 days for flowering, 15 days for veraison. The influence in terms of maturity is even more pronounced, with more than 20 days of difference between the earliest and the latest ripening plot.

<table><caption>Table 2 - Phenology and sugar maturity (2012-2014)</caption><thead><tr><th></th><th>Year</th><th>Period</th><th>Mean date</th><th>Duration (days)</th></tr></thead><tbody><tr><td rowspan="3">Flowering</td><td>2012</td><td>30/05 - 08/06</td><td>4 June</td><td>10</td></tr><tr><td>2013</td><td>15/06 - 20/06</td><td>17 June</td><td>6</td></tr><tr><td>2014</td><td>31/05 - 07/06</td><td>3 June</td><td>8</td></tr><tr><td rowspan="3">Veraison</td><td>2012</td><td>31/07 - 18/08</td><td>9 August</td><td>19</td></tr><tr><td>2013</td><td>16/08 - 26/08</td><td>21 August</td><td>11</td></tr><tr><td>2014</td><td>30/07 - 16/08</td><td>7 August</td><td>18</td></tr><tr><td rowspan="3">Sugar maturity (day of the year sugar concentration reaches 200g/l)</td><td>2012</td><td>22/08 - 12/09</td><td>1 September</td><td>22</td></tr><tr><td>2013</td><td>05/09 - 4/10</td><td>21 September</td><td>30</td></tr><tr><td>2014</td><td>31/08 - 22/09</td><td>10 September</td><td>23</td></tr></tbody></table>
Conclusion

Climate is an important factor in wine production. Wine quality depends on the vintage. Vintage typicity is essentially related to the inter-annual variability of the climate. Soil parameters also participate in wine characteristics, but they are generally constant over time. It is also important to study the intra-annual variability of climate inside a given region, since this has an influence on vine development and grape ripening. Precise knowledge on local temperature variation is a key factor for better adaptation of plant material and viticultural practices, especially in a context of climate change.

The great variability in terms of temperature, due to the local parameters, and the consequence on vine behavior has been investigated on this paper. Spatial variability in minimum and maximum temperature was measured, as well as its impact on vine phenology. The creation of temperature maps over the area by means of spatial modeling is under progress. Phenology models can be coupled to temperature models to assess spatial variability of the timing of phenology with greater accuracy over the area.

Acknowledgements

Jean-Pascal Tandonnet and Marc Legault participated in data collection and data processing. The study was funded by the Conseil Interprofessionnel du Vin de Bordeaux, the European Union Life Adviclim project (LIFE 13 ENV/FR/001512), the Conseil des Vins de Saint-Emilion and the GDON du Libournais.

References

1. van Leeuwen C, Friant P, Choné X et al (2004) Influence of climate, soil and cultivar on terroir. *Am J Enol Vitic* **55**: 207-217.

2. Huglin P (1978) Nouveau mode d'évaluation des possibilités héliothermiques d'un milieu viticole. *CR Acad Agric* **64**: 1117-1126.

3. Jones GV, White MA, Cooper OR et al (2005) Climate change and global wine quality. *Clim Change* **73**: 319-343.

4. Neethling E, Barbeau G, Bonnefoy C et al (2012) Change in climate and berry composition for grapevine varieties cultivated in the Loire Valley. *Clim Res* **53**: 89-101.

5. Bois B (2007) Cartographie agroclimatique à méso-échelle : méthodologie et application à la variabilité spatiale du climat en Gironde viticole. *PhD Thesis*, Université de Bordeaux.

6. Baggiolini M (1952) Les stades repères dans le développement annuel de la vigne et leur utilisation pratique. *Rev Rom Agric Vitic* **8**: 4-6.

7. Winkler AJ, Cook JA, Kliewer WM et al (1974) *General Viticulture, 2nd ed.* University of California Press.
# Influence du Rapport Feuille/Fruit sur le profil sensoriel et la composition aromatique de vins issus du cépage Cabernet franc en Val de Loire

J. BEGUIN<fnref n="1" />*, E. FORTIN<fnref n="1" />, L. GUERIN<fnref n="1" />, R. SYMONEAUX<fnref n="2" />

## Cabernet franc – rapport feuille/fruit – profil sensoriel – composés aromatiques

## Introduction

Cette étude vise à établir les rapports existant entre les itinéraires de production de raisins de Cabernet franc (leurs effets sur le Rapport Feuille/Fruit) et la composition aromatique et le profil sensoriel des vins qui en sont issus. Elle se situe dans le cadre des travaux de caractérisation de la typicité des vins du Val de Loire menés par l'UMT Vinitera (Unité Mixte Technologique) [1]. Elle devait dans un premier temps identifier et quantifier des marqueurs aromatiques dans les vins de Cabernet franc, afin, à terme, de mettre en évidence les relations entre les produits (raisins et vins), d'une part et les terroirs et itinéraires de production d'autre part [2].

## Matériel et méthodes

### Parcelles et traitements

L'étude est réalisée sur un réseau de 6 parcelles mis en place en Anjou et en Touraine. L'étude comporte un volet viticole orienté sur la gestion du Rapport Feuille/Fruit (RFF).

Sur chaque parcelle, pendant 3 millésimes, l'objectif est d'obtenir 2 lots de vendanges différents en faisant varier le Rapport Feuille/Fruit du simple au double entre les modalités RFF bas (RFFB) et RFF hauts (RFFH) grâce aux deux principales techniques de l'éclaircissage (majoritairement) et de la modulation de la hauteur de rognage. Sur 2 des parcelles, trois différentes dates de récolte viennent compléter le dispositif. La date de récolte est fixée en fonction de la date de mi-véraison, du titre d'alcool potentiel et de l'acidité totale (mesurés lors du contrôle maturité) et de l'état de la parcelle (pourriture, grains prêts à tomber, etc.).

### Vinifications et analyses

Tous les lots de 50 kg de raisin (issus de 4 blocs réunis) sont vinifiés de façon identique selon un schéma de vinification dit « classique » avec une macération de 9 jours avec des pigeages légers, à une température de 25°C. Une fois mis en bouteilles, les 20 vins obtenus subissent des analyses physico-chimiques classiques, de polyphénols et aromatiques. Les molécules aromatiques analysées ont été choisies d'après le travail bibliographique de M. Maestrojuan sur les composés aromatiques des vins rouges [3-5]. Enfin les analyses sensorielles sont réalisées par le jury expert de l'Unité de Recherche GRAPPE du Groupe ESA.

## Résultats et discussion

Les mesures de Rapport Feuille/Fruit obtenues sur le réseau durant les trois années d'étude se situent entre 1,25 et 3,60 pour les hauts et entre 0,81 et 1,93 pour les bas (exprimés en m<fnref n="2" />/kg) selon les parcelles et les millésimes. Il est considéré de manière générale qu'il faut un RFF supérieur à 1,4 pour élaborer des vins rouges structurés. La parcelle 211 possédait initialement un RFF plutôt élevé, supérieur à ce seuil. Néanmoins, même si parfois le rapport n'est pas tout-à-fait de 1/2, les RFF bas et hauts obtenus sont toujours bien différentiés et devraient permettre d'obtenir des récoltes différentes.

<footnote n="1">¹Institut Français de la Vigne et du Vin (IFV), 509 avenue de Chanteloup, 37400. Amboise, France</footnote>

<footnote n="2">²Ecole Supérieure d'Agriculture d'Angers (ESA), 55 rue Rabelais, 49007. Angers, France</footnote>
Concernant les critères physico-chimiques sur vins (éthanol, acidité totale, pH, Indice Polyphénols Totaux, Intensité Colorante) sur les trois années d'essai, les facteurs statistiquement discriminants peuvent être classés par ordre d'importance de la manière suivante : millésime > parcelle > date de récolte > rapport feuille/fruit. Le millésime, donc le climat, apparaît comme le facteur le plus discriminant de tous, devant l'effet parcelle. La combinaison climat/sol-sous-sol offre sans surprise la plus grande source de variation. L'effet date de récolte joue aussi un rôle important sur les maturités technologique et phénolique. Enfin, un RFF plus élevé favorise l'avancement de la maturité, il entraîne un degré alcoolique et un pH supérieurs et un plus grand Indice de Polyphénols Totaux (IPT).

Concernant les analyses sensorielles des vins, pour les millésimes 2010 et 2012, les notes attribuées aux vins pour les différentes variables générées par le jury expert (plus d'une quarantaine) ont été reliées à leur valeur de RFF à l'aide d'une régression linéaire multiple (régression PLS). Par cette méthode, aucune corrélation entre RFF et descripteurs n'a été montrée et les valeurs de R² sont même quasiment toutes très proches de 0. Le RFF n'influence donc pas directement les différentes composantes des vins. L'intérêt s'est donc ensuite porté sur la comparaison entre les RFF hauts et bas. Les analyses de variance permettent de mettre en évidence l'importance relative des différents facteurs discriminants, le seuil α de 10% est retenu pour cette étude.

Le tableau 1 présente les 5 critères significativement différents en 2010 parmi les 21 testés. La date de récolte n'a eu aucun effet sur les aspects visuel et olfactif des vins. L'effet parcelle ne s'est manifesté que sur l'aspect visuel, avec des couleurs plus intenses pour les vins issus des parcelles de Touraine. Enfin, les RFF hauts présentent une plus grande intensité de la couleur et une teinte plus rouge. Au nez, le caractère animal ressort de ces vins. En bouche, la seule différence observée concerne la sensation de chaleur due à l'alcool : la date de récolte plus tardive (date D3) a un côté plus « chaud » que la date plus précoce (date D1). Les RFF hauts présentent en rétro-olfaction des notes légèrement plus marquées de fruits macérés. Aucun effet parcelle n'est observé.

<table><caption>Tableau 1 - Critères significativement différents à l'analyse sensorielle sur les vins du millésime 2010</caption><thead><tr><th rowspan="2">Probabilité<br>effet</th><th colspan="2">Oeil</th><th colspan="2">Nez</th><th colspan="2">Rétro-<br>olfaction</th></tr><tr><th>Intensité<br>Couleur</th><th>Teinte</th><th>Animal</th><th>Chaleur<br>alcool</th><th>Fruits<br>macérés</th></tr></thead><tbody><tr><td>Parcelle</td><td>0,007</td><td>0,116</td><td>0,703</td><td>0,945</td><td>0,925</td></tr><tr><td>Date</td><td>0,213</td><td>0,243</td><td>0,954</td><td>0,097</td><td>0,621</td></tr><tr><td>Modalité</td><td>0,001</td><td>0,093</td><td>0,089</td><td>0,811</td><td>0,068</td></tr><tr><td>H / B</td><td>H > B</td><td>H > B</td><td>H > B</td><td></td><td>H > B</td></tr></tbody></table>

Pour 2011 et 2012, les dégustations se sont concentrées exclusivement sur l'aspect olfactif (23 critères). L'effet millésime est le plus discriminant. Il n'y a pas d'effet de la date de récolte et il existe une différence inter-parcellaire seulement sur le descripteur « cassis frais », avec la parcelle 207 qui se démarque sur ce critère. Enfin, la seule différence existant pour le RFF concerne le descripteur « musc ». L'ensemble des variables significativement différentes sont présentées dans le tableau 2.

<table><caption>Tableau 2 - Critères significativement différents à l'olfaction des vins des millésimes 2011 et 2012</caption><thead><tr><th rowspan="2">Probabilité<br>effet</th><th colspan="2">Animal</th><th colspan="2">Floral</th><th colspan="2">Fruits cuits</th><th colspan="2">Fruits frais</th><th colspan="2">Végétal</th><th colspan="2">Boisé</th><th>Autres</th></tr><tr><th>Cuir</th><th>Musc</th><th>Violette</th><th>Prune cuit</th><th>Cassis frais</th><th>Cerise<br>griotte<br>frais</th><th>Prune frais</th><th>Herbe<br>coupée</th><th>Poivron</th><th>Boisé</th><th>Ethanol</th></tr></thead><tbody><tr><td>Millésime</td><td>0,003</td><td>0,669</td><td>0,044</td><td>0,018</td><td>0,996</td><td>0,061</td><td>0,039</td><td>0,082</td><td>0,008</td><td>0,08</td><td>0,056</td></tr><tr><td>Parcelle</td><td>0,869</td><td>0,793</td><td>0,369</td><td>0,435</td><td>0,02</td><td>0,277</td><td>0,628</td><td>0,459</td><td>0,453</td><td>0,311</td><td>0,761</td></tr><tr><td>Date</td><td>0,654</td><td>0,56</td><td>0,318</td><td>0,54</td><td>0,147</td><td>0,299</td><td>0,817</td><td>0,828</td><td>0,157</td><td>0,587</td><td>0,283</td></tr><tr><td>Modalité</td><td>0,632</td><td>0,089</td><td>0,979</td><td>0,374</td><td>0,373</td><td>0,766</td><td>0,597</td><td>0,168</td><td>0,691</td><td>0,951</td><td>0,833</td></tr><tr><td>H/B</td><td colspan="2">H < B</td><td colspan="2"></td><td colspan="2"></td><td colspan="2"></td><td colspan="2"></td><td colspan="2"></td></tr></tbody></table>
De nombreuses molécules aromatiques ont été dosées sur tous les vins élaborés lors de cette étude. L'ensemble des molécules analysées constitue le tampon aromatique d'un vin. Prises individuellement, toutes ne possèdent pas d'odeur associée permettant de les reconnaitre, mais elles jouent un rôle dans la matrice aromatique de chaque vin.

Les 30 molécules dosées appartiennent aux familles des alcools, acides, composés carbonylés, esters, phénols volatils, thiols et autres tels que la 3-isobutyl-2-méthoxypyrazine (IBMP), la β-damascénone, etc.

Parmi toutes ces molécules dosées, l'unique effet discriminant du RFF est celui observé sur les teneurs en benzèneéthanol : des RFF hauts les augmentent significativement. A l'inverse l'effet millésime est de nouveau le plus discriminant puisqu'il influence 25 des 30 molécules étudiées, c'est-à-dire toutes sauf le 1-octanol, l'acide 3-méthylbutanoïque, le phényléthanal, le 4-éthylgaïacol et le 4-éthylphénol.

Les tableaux 3 et 4 présentent uniquement les critères significativement différents (autres que ceux mentionnés dans le texte) pour les alcools, composés carbonylés, phénols, thiols et autres, d'une part et les esters, d'autre part. Les odeurs associées indiquées dans ces deux tableaux sont celles mentionnées dans la littérature.

<table><caption>**Tableau 3** - Critères significativement différents en fonction des parcelles et de la date pour les composés aromatiques autres que les esters</caption><thead><tr><th rowspan="2">Probabilité<br>effet</th><th colspan="3">Alcools</th><th colspan="2">Composés carbonylés</th><th rowspan="2">Ph. Volatils</th><th rowspan="2">Thiols</th><th colspan="3">Autres</th></tr><tr><th>1-Octanol</th><th>2-<br>Ethylhexanol</th><th>3-Hexène 1-<br>ol</th><th>2,3-<br>Butanedione</th><th>Ethanal</th><th>Phénol</th><th>3MH (ng/L)</th><th>Furanéol</th><th>IBMP</th><th>Damascénone</th></tr></thead><tbody><tr><td>Parcelle</td><td>0</td><td>0,03</td><td>0,08</td><td>0</td><td>0,09</td><td>0,01</td><td>0,01</td><td>0,04</td><td>&lt; 0,0001</td><td>&lt; 0,0001</td></tr><tr><td>Date</td><td>0,36</td><td>0,78</td><td>0,18</td><td>0,55</td><td>0,84</td><td>0,02</td><td>0,02</td><td>0,73</td><td>0,55</td><td>0,71</td></tr><tr><td>Odeur<br>associée</td><td></td><td></td><td></td><td>beurre</td><td>pomme</td><td>encre,<br>phénolé</td><td>fruit de la<br>passion</td><td>grillé</td><td>poivron vert</td><td>fruit exotique</td></tr></tbody></table>

Concernant les alcools, qui vont apporter des notes plutôt désagréables, l'effet millésime est très saillant tandis que l'effet parcelle l'est un peu moins. Aucun effet n'est observé concernant la date de récolte. Enfin, un RFF haut augmente significativement la teneur en benzèneéthanol.

Pour les acides et les composés carbonylés (notes vineuses et parfois désagréables), l'effet millésime est encore très discriminant, tandis que l'effet parcelle ne s'observe que pour le 2,3-butanedione et l'éthanal. La date de récolte, ainsi que le RFF n'ont pas d'incidence sur ces composés aromatiques. Par ailleurs, concernant les phénols volatils, aucun effet n'est observé sur le 4-éthylgaïacol et le 4-éthylphénol. En effet ces composés sont produits par les levures *Brettanomyces* et une bonne hygiène de cave permet d'éviter leur développement. La date de récolte influe seulement sur la teneur en phénol.

Comme pour tous les composés, l'effet millésime apparaît comme le facteur déterminant les teneurs des composés « autres ». L'effet parcelle est aussi un facteur discriminant excepté pour le diméthyle sulfure (DMS) et la β-ionone. La date de récolte joue un rôle sur le 3-mercapto-hexanol (3MH), avec des concentrations supérieures pour la date D3. Enfin, aucune différence n'est induite par le RFF. Il faut noter que pour ces composés « autres », les teneurs rencontrées se situent en dessous des seuils de recouvrement (concentration à laquelle 50% des dégustateurs perçoivent et identifient un composé odorant spécifique), en particulier pour la β-damascénone, composé reconnu comme exhausteur des arômes fruités dont les teneurs sont très faibles. Seul le DMS est présent à des concentrations dix fois supérieures à son seuil de recouvrement. Le DMS jouerait un rôle d'exhausteur d'arômes fruits rouges dans les vins rouges.

Concernant les esters, molécules apportant beaucoup de fruité aux vins (excepté l'acétate d'éthyle), l'effet millésime influence toutes leurs teneurs. L'effet parcelle est lui aussi très discriminant, avec 11 molécules impactées sur les 16 dosées. L'effet date de récolte est bien moins marqué, avec seulement 4 molécules impactées. Enfin, la modification du RFF n'influence pas les teneurs en esters des vins. En outre, les niveaux de concentrations de ces composés se situent également bien en deçà des seuils de recouvrement. Seul l'éthyl hexanoate se trouve à des concentrations trois fois supérieures à son seuil de recouvrement.
<table><caption>**Tableau 4** - Critères significativement différents en fonction des parcelles et de la date pour les esters</caption><thead><tr><th rowspan="2">Probabilité<br>effet</th><th colspan="10">Esters</th></tr><tr><th>3-<br>Méthylbutyl<br>acétate</th><th>Butyl<br>acétate</th><th>Ethyl 2-<br>hydroxy<br>propanoate</th><th>Ethyl 2-<br>méthyl<br>butanoate</th><th>Ethyl 2-<br>méthyl<br>propanoate</th><th>Ethyl 3-<br>méthyl<br>butanoate</th><th>Ethyl 6-<br>hydroxy<br>hexanoate</th><th>Ethyl<br>acétate</th><th>Ethyl<br>butanoate</th><th>Ethyl<br>hexanoate</th><th>Ethyl<br>octanoate</th><th>Hexyl<br>acétate</th></tr></thead><tbody><tr><th>Parcelle</th><td>0</td><td>0,01</td><td>0</td><td>&lt; 0,0001</td><td>0,01</td><td>&lt; 0,0001</td><td>0,06</td><td>&lt; 0,0001</td><td>0</td><td>0,7</td><td>0</td><td>0,07</td></tr><tr><th>Date</th><td>0,04</td><td>0</td><td>0,01</td><td>0,73</td><td>0,28</td><td>0,44</td><td>0,3</td><td>0,23</td><td>0,44</td><td>0,03</td><td>0,85</td><td>0,65</td></tr><tr><th>Odeur<br>associée</th><td></td><td>banane,<br>fruité</td><td></td><td>fraise</td><td>mûre</td><td></td><td></td><td>ascence</td><td>fraise<br>tagada</td><td>confiture<br>de fraise</td><td>fruits<br>rouges,<br>framboise</td><td>Poire,<br>banane</td></tr></tbody></table>

## Conclusion

Faire varier le RFF permet, comme prévu, d'obtenir 2 lots de vendanges aux caractéristiques distinctes, sur toutes les parcelles.

D'un point de vue physico-chimique, les vins issus du RFF haut ont des degrés alcooliques et des pH supérieurs, ainsi qu'une concentration en polyphénols et une intensité colorante plus fortes (signes d'une maturité plus importante). Cependant, le RFF reste le facteur le moins impactant, derrière le millésime, le sol (la parcelle) et la date de récolte.

Concernant les molécules aromatiques, leurs teneurs sont notablement influencées par le millésime et le sol. La date de récolte fait varier la concentration de quelques molécules comme le 3MH (thiol) et certains esters. Par contre, le RFF n'a d'impact sur aucun des composés dosés exception faite du benzèneéthanol.

Enfin, les profils sensoriels générés par le jury expert ne font quasiment apparaître que des différences liées au millésime. Même l'effet parcelle n'est pas discriminant. L'« espace produit » est tellement restreint que les différences sont très minces et difficilement détectables. Il est vrai que le Cabernet franc n'est pas un cépage réputé aromatique mais, par exemple, sa particularité à donner des goûts de poivron est connue. Or, seul le millésime semble influer sur ces notes végétales.

## Remerciements

Nous tenons à remercier FranceAgrimer, la Région Centre, ainsi que InterLoire pour leur aide financière. Nous remercions également la Chambre d'Agriculture d'Indre-et-Loire, le Laboratoire de Touraine, les syndicats des vins de Bourgueil, St Nicolas de Bourgueil et Chinon, sans qui cette étude n'aurait pu être menée à bien.

## Références

1. Lebret J (2010) *L'expression aromatique des vins issus du Cabernet Franc en Val de Loire*. Rapport de stage « Recherche et Innovation ».

2. Nicou A (2008) *Influence des pratiques viticoles sur la maturation des baies de Cabernet Franc dans le Val de Loire*. Rapport de stage de licence 3ème année « Sciences de la vigne ».

3. Maestrojuan M (2009) *Les arômes dans le vin et leur perception*.

4. Escudero A, Campo E, Farina L et al (2007) Analytical characterization of the aroma of five premium red wines. *Insights into the role of odor families and the concept of fruitiness of wines. J Agric Food Chem* **55**: 4501-4510.

5. Pineau B, Barbe JC, van Leeuwen C et al (2009) Étude des arômes spécifiques des fruits rouges et fruits noirs des vins rouges de Bordeaux. « 9ème Journée Technique du CIVB ».
# Impact du porte-greffe sur les composés phénoliques du cépage Marselan en climat méditerranéen

M. NADAL*, A. SANCHEZ-ORTIZ

Dep. Bioquímica i Biotecnologia, Facultat d'Enologia, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona, Spain

Changement climatique – Grenache noir – composition des vins – anthocyanes

## Introduction

L'adaptation de cépages méditerranéens type Grenache noir ou de cépages importés type Cabernet sauvignon au changement climatique est de plus en plus nécessaire pour obtenir des vins rouges de qualité dans les zones vitivinicoles de la méditerranée comme par exemple la Catalogne. L'importance du porte-greffe et du cépage est primordiale en relation à son adaptation au terroir [1] et au changement climatique actuel pour obtenir des vins rouges de qualité. L'objectif de cette étude est donc d'évaluer l'effet du porte-greffe (Richter-110, 140-Ruggeri, 41B et Fercal) sur le rendement et la composition phénolique des vins de Marselan pour en déterminer leur adaptation au terroir [2].

## Matériel et méthodes

### Parcelle d'étude

La parcelle d'étude se situe dans le vignoble de l'Université Rovira i Virgili sur le territoire de Tarragone (Espagne), qui jouit d'hivers tempérés et d'étés humides et chauds, climat typique des régions méditerranéennes. Le sol est de texture franc-argileuse et calcaire (pH 8.2 et carbonates 56%) avec une réserve hydrique moyenne. La plantation réalisée en 2009 est conduite en espalier avec une taille Royat sur des rangs 2.4 m x 1.1 m. Les combinaisons cépage/porte-greffe sont distribuées au hasard en 3 blocs de répétition et comprenant 17 souches par parcelle élémentaire. Pendant les années 2012 et 2013 des mesures du potentiel hydrique ont été réalisées pendant l'été. Le poids de récolte et l'efficacité de l'usage de l'eau (WUE) ont aussi été déterminés [3].

### Analyses

La composition phénolique des vins issus de chaque traitement a été analysée par HPLC-DAD/FLD. Les résultats ont été traités par ANOVA (P<0.05) et les différences entre traitements ont été calculées en utilisant le test de Tukey (package SPSS v21.0).

## Résultats et discussion

Les principaux résultats montrent que le porte-greffe Fercal est le moins résistant à la sécheresse (Tableau 1), avec une forte contrainte hydrique en 2012. Le Fercal a eu les valeurs de ¹³C (δ¹³/¹²C vs PDB) à maturité les plus faibles en accord avec les résultats de Gaudillere et al. [4]. Par contre, 140-Ruggeri et 41B ont eu les WUE et une production de raisins les plus élevées. Le ¹³C a révélé beaucoup plus de stress pendant l'année chaude (2012) par rapport à l'année la plus tempérée (2013). Ce stress à la véraison a influencé négativement la concentration des anthocyanes retrouvée dans les vins (Figure 1). Le porte-greffe vigoureux 140-Ruggeri fut le plus productif et donc les teneurs en anthocyanes dans les vins furent les plus faibles en année chaude.
<table><caption>**Tableau 1** - Production par souche, WUE (efficacité de l'eau), discrimination isotopique δ¹³/¹²C des raisins (¹³C) et potentiel hydrique de base (Ψhb) (Vé=véraison ; Ma=maturité ; s=stress)</caption><thead><tr><th></th><th>Production (Kg/s)</th><th>WUE</th><th>Ψhb M</th><th>δ¹³/¹²C Vé</th><th>δ¹³/¹²C Ma</th></tr></thead><tbody><tr><td colspan="6"><strong>2012</strong></td></tr><tr><td>110R</td><td>2.16 ± 0.28<sup>b</sup></td><td>4.06 ± 0.56<sup>bc</sup></td><td>-0.86</td><td>-27.33<sup>s</sup></td><td>-24.91</td></tr><tr><td>140Ru</td><td>3.24 ± 0.27<sup>a</sup></td><td>6.35 ± 0.54<sup>a</sup></td><td>-0.88</td><td>-28.82<sup>s</sup></td><td>-26.37</td></tr><tr><td>41B</td><td>3.21 ± 0.39<sup>a</sup></td><td>5.33 ± 0.78<sup>ab</sup></td><td>-0.80</td><td>-28.54<sup>s</sup></td><td>-25.86</td></tr><tr><td>Fercal</td><td>2.83 ± 0.66<sup>b</sup></td><td>3.78 ± 1.31<sup>b</sup></td><td>-0.89</td><td>-27.48<sup>s</sup></td><td>-27.30<sup>s</sup></td></tr><tr><td colspan="6"><strong>2013</strong></td></tr><tr><td>110R</td><td>2.46 ± 0.46<sup>c</sup></td><td>4.48 ± 0.86<sup>b</sup></td><td>-0.85</td><td>-25.60</td><td>-23.83</td></tr><tr><td>140Ru</td><td>4.19 ± 0.67<sup>c</sup></td><td>6.77 ± 1.24<sup>ab</sup></td><td>-0.89</td><td>-25.49</td><td>-25.58</td></tr><tr><td>41B</td><td>4.22 ± 1.34<sup>a</sup></td><td>3.32 ± 2.63<sup>ab</sup></td><td>-0.72</td><td>-26.5</td><td>-24.54</td></tr><tr><td>Fercal</td><td>3.62 ± 1.31<sup>b</sup></td><td>8.39 ± 2.92<sup>a</sup></td><td>-0.83</td><td>-25.85</td><td>-23.78</td></tr></tbody></table>

<figure><img src="image_30.png" /><figcaption>**Fig. 1** - Evolution de la concentration en anthocyanes et de l'IPT en fonction des porte-greffes et de l'année.</figcaption></figure>

Il est aussi à noter que les degrés alcooliques, les concentrations en anthocyanes et les IPT (indice de polyphénols totaux) des vins sont toujours les plus élevés pour le Richter-110 lors des deux années d'étude (Tableau 2).

En ce qui concerne la composition phénolique des vins de Marselan, une proportion relativement plus élevée en anthocyanes était présente dans les vins de Richter-110 (Tableau 3). Par contre, les vins de 140-Ruggeri avaient des pourcentages plus faibles en anthocyanes et plus élevés en proanthocyanidines et en acides hydroxycinnamiques. Ces variations parmi les porte-greffes seulement sont appréciées l'année chaude (2012). En condition plus tempérée (2013), nous n'observons qu'une augmentation relative des proanthocyanidines.

<table><caption>**Tableau 2** - Composition chimique des vins : titre alcoolétrique volumique (TAV. %, v/v), pH, acidité totale (ATT, g/l tartrique), anthocyanes totales (ANT, mg/l) et indice de polyphénols totaux (IPT)</caption><thead><tr><th></th><th>2012</th><th>TAV (%, v/v)</th><th>ATT (g Tartrique/l)</th><th>pH</th></tr></thead><tbody><tr><td>110R</td><td>14.6 ± 0.1<sup>a</sup></td><td>5.92 ± 0.07<sup>b</sup></td><td>3.70 ± 0.00<sup>b</sup></td></tr><tr><td>140Ru</td><td>13.7 ± 0.1<sup>b</sup></td><td>5.71 ± 0.01<sup>c</sup></td><td>3.80 ± 0.01<sup>a</sup></td></tr><tr><td>41B</td><td>13.6 ± 0.1<sup>b</sup></td><td>6.23 ± 0.02<sup>a</sup></td><td>3.56 ± 0.02<sup>c</sup></td></tr><tr><td>Fercal</td><td>13.0 ± 0.1<sup>c</sup></td><td>5.09 ± 0.02<sup>d</sup></td><td>3.70 ± 0.01<sup>b</sup></td></tr><tr><td>2013</td><td></td><td></td><td></td></tr><tr><td>110R</td><td>13.3 ± 0.3<sup>a</sup></td><td>6.28 ± 0.01<sup>b</sup></td><td>3.48 ± 0.04<sup>b</sup></td></tr><tr><td>140Ru</td><td>12.2 ± 0.1<sup>c</sup></td><td>6.86 ± 0.08<sup>a</sup></td><td>3.64 ± 0.06<sup>a</sup></td></tr><tr><td>41B</td><td>12.7 ± 0.1<sup>b</sup></td><td>6.21 ± 0.13<sup>b</sup></td><td>3.53 ± 0.01<sup>b</sup></td></tr><tr><td>Fercal</td><td>12.1 ± 0.4<sup>c</sup></td><td>5.90 ± 0.10<sup>c</sup></td><td>3.65 ± 0.01<sup>a</sup></td></tr></tbody></table>
<table><caption>**Tableau 3** - Composition relative (%) des acides hydroxybenzoiques et hydroxycinnamiques, flavonoles, proanthocyanidines et anthocyanes des vins de Marselan pour les deux années d'études 2012 et 2013</caption><thead><tr><th></th><th>110 R</th><th>140Ru</th><th>41B</th><th>Fercal</th></tr></thead><tbody><tr><td colspan="5"><strong>2012</strong></td></tr><tr><td>Hydroxybenzoiques</td><td>8.9</td><td>16.2</td><td>15.4</td><td>17.5</td></tr><tr><td>Hydroxycinnamiques</td><td>15.2</td><td>20.2</td><td>17.2</td><td>17.3</td></tr><tr><td>Flavonoles</td><td>8.9</td><td>8.2</td><td>7.1</td><td>6.0</td></tr><tr><td>Proanthocyanidines</td><td>8.1</td><td>12.3</td><td>8.1</td><td>5.6</td></tr><tr><td>Anthocyanes</td><td>58.8</td><td>43.1</td><td>52.1</td><td>53.7</td></tr><tr><td colspan="5"><strong>2013</strong></td></tr><tr><td>Hydroxybenzoiques</td><td>7.8</td><td>8.4</td><td>7.1</td><td>7.7</td></tr><tr><td>Hydroxycinnamiques</td><td>14.6</td><td>19.7</td><td>19.0</td><td>15.3</td></tr><tr><td>Flavonoles</td><td>11.7</td><td>9.5</td><td>9.2</td><td>9.4</td></tr><tr><td>Proanthocyanidines</td><td>12.6</td><td>12.1</td><td>13.8</td><td>15.2</td></tr><tr><td>Anthocyanes</td><td>51.9</td><td>50.3</td><td>50.9</td><td>52.4</td></tr></tbody></table>

## Conclusion

Les vins issus des porte-greffes Richter-110, Fercal et 41B ont les proportions en anthocyanes les plus élevées dans les vins de Marselan surtout dans l'année de stress hydrique (2012) qui, en général, correspond aussi à une concentration plus élevée. La vigueur excessive et les hauts rendements observés pour le porte-greffe 140-Ruggeri entraîne une diminution des anthocyanes et une augmentation des proportions en proanthocyanidines. De plus, toujours en année sèche et chaude le Richter-110 et le 41B donnent les concentrations en composés phénoliques totaux les plus élevées.

L'effet de l'élévation des températures provoquée par le changement climatique conduit sûrement à une synthèse modulée des composés phénoliques, constatée par une variation des espèces phénoliques trouvées selon le porte-greffe et l'année d'étude.

## Remerciements

Nous tenons à remercier N. Rozès pour son aide dans la traduction. Cette étude a été financée par un projet national CICYT (Ref. AGL 2011-30408-C04-02).

## Références

1. Dry N (2005) *Grapevine Rootstock Evaluation and Breeding in Germany, France and California*. Grape and Wine Research & Development Corporation, PGI 05/01.

2. Yan-Xia L, Qiu-Hong P, Guo-Liang Y et al (2010) Changes of flavan-3-ols with different degrees of polymerization in seeds of ‘Shiraz’, ‘Cabernet Sauvignon’ and ‘Marselan’ grapes after veraison. *Molecules* **15**: 7763-7774.

3. Cabrera-Bosquet L, Molero G, Bort J et al (2007) The combined effect of constant water deficit and nitrogen supply on WUE, NUE and δ¹³C in durum wheat potted plants. *Ann Appl Biol* **151**: 277-289.

4. Gaudillere JP, van Leeuwen C, Ollat N (2002) Carbon isotope composition of sugars in grapevine, an integrated indicator of vineyard water status. *J Exp Bot* **53**: 757-763.
# Contribution to confirm the existence of a Secondary Domestication Centre of *Vitis vinifera* subsp. *vinifera* in the south-east of France (Languedoc area)

G. MARSAL¹, J.M. MATEO-SANZ², J.M. CANALS¹, F. ZAMORA¹*, F. FORT¹

¹Grup de Tecnologia Enològica (TECNENOL), Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Facultat d'Enologia de Tarragona, Campus Sescelades, C/ Marcel lí Domingo nº1, 43007-Tarragona, Spain

²Group CRISES, Departament Enginyeria Química, Universitat Rovira i Virgili, Escola Tècnica Superior d'Enginyeria Química, Campus Sescelades, Av. Països Catalans 26, 43007-Tarragona, Spain

Secondary Domestication Centre – *Vitis vinifera* – SSR or Microsatellites – populations

## Introduction

From the classification of Negrul [1] to studies by Arroyo-Garcia et al. [2], it was postulated that different secondary domestication centres (SDC) existed in the Mediterranean basin. Clearly in the westernmost part of the Mediterranean basin were grown ecotypes of *Vitis vinifera* ssp *sylvestris*, which were very different from those defined by Negrul [1] in the easternmost part (*Vitis vinifera* ssp *sylvestris* var. *aberrans*, *Vitis vinifera* ssp *sylvestris* var. *typica*, etc.). This is postulated by different authors such as Forni [3] and Marsal et al. [4].

The existence of SDC in France is a controversial topic. While authors such as Arroyo-García et al. [2] and Bacilieri et al. [5] joined the French and central Europe areas in a single zone, Negrul [1] defined the *sub-proles gallica* in the French area. Meanwhile, Forni [3] did not describe any SDC in France, but the extension of its fifth SDC corresponding to northern Italy (1st millennium BC) covers almost the entire Languedoc area. Terral et al. [6] hypothesize SDC located in the Languedoc area based on phenotypic studies (geometrical analysis of seeds). Finally, the hypothesis of the existence of two single SDC in France was only described by Böhm [7] and Marsal et al. [4].

## Materials and methods

### Grapevine accessions and SSR analysis

A set of 338 grapevine accessions (*Vitis vinifera*) were obtained from the Bodegues Sumarroca germplasm (Subirats, AOC Penedés, Spain). This grapevine collection came from 23 different countries. Leaves were collected in spring and immediately stored at -20°C. DNA was extracted according to our method, which was improved for leaves [8]. The grapevine gene pool was genotyped at 20 simple sequence repeat (SSR) markers, which were selected for quality and polymorphism (VVS2, VVS3, VVS29, VVMD5, VVMD6, VVMD7, VVMD27, VVMD28, VVMD36, VrZAG21, VrZAG47, VrZAG62, VrZAG64, VrZAG79, VrZAG83, scu06vv, VvUCH11, VvUCH12, VvUCH19, and VChr19a). Microsatellite amplifications were performed by means of polymerase chain reaction (PCR) analysis. Amplification products were separated by capillary electrophoresis with an ABI PRISM 3730® Genetic Analyzer (Applied Biosystems, Foster City, CA). Amplified fragments were sized with the Peak Scanner Software (Applied Biosystems, New Jersey, USA). Each cultivar was analyzed twice to prevent possible errors. The geographical origin assignation for each accession was conducted from existing bibliographical references on the subject matter.

### Data analysis

The GenAIEx 6.5 software was used for data analysis: cultivars matching, the Frequency-based Assignment Test (Fst) and Principal Coordinate Analysis (PCoA) were employed to further examine the genetic relationships among the detected populations on the basis of the same SSR data.

<footnote>*Corresponding author: fernando.zamora@urv.cat</footnote>
**Results and discussion**

Forty-three samples (of the 338 initial accessions) displayed exactly the same SSR profiles. These samples were therefore excluded from the analysis, as they were identical cultivars with synonymous names, resulting in a population of 295 unique genomic profiles.

The strategy of this study deals with getting the best Genetic Structure for our population when the geographical origin is the criterion of the formation of subpopulations. The groups of samples will be classified by areas because some of the countries have a low number of accessions. According to the literature, 9 subpopulations are defined: CAU (Armenia and Georgia), NE (Cyprus, Egypt and Lebanon), GRE (Greece), BALK (Bosnia-Herzegovina, Bulgaria, Slovenia, Montenegro, Serbia, and Croatia), ITA (Italy), CE (Germany, Austria, Switzerland, and Hungary), FRA (France), PI (Spain and Portugal), and NW (Argentina, United States, South Africa). But some authors have considered the existence of several SDC [2, 3] apart from those described in the Anatolian-circum Mesopotamia regions (6th-5th millennium BC) and Transcaucasus (6th-4th millennium BC) [3]. For that reason, it was considered the possibility of fragmenting certain geographical areas classically, as described previously in other works. The following divisions were therefore proposed:

1) the Italian Peninsula into two area, one covering the south-central (IT-CS) [3, 9] and another one covering the north (IT-N) [3]

2) France into two areas, one in the south (FR-S), more specifically in the Languedoc area [6, 7], and the other in the north-central area (FR-CN) [7]

3) the Iberian Peninsula into three areas, the west (PI-CSW-CS), which also covers the south, the north (PI-N-NW), and finally the east Peninsular (PI-NE-E). These areas have been already hypothesized by De Andrés et al. [10], Böhm [7] and Forni [3].

It should be highlighted that three subpopulations have kept fixed without reassigning (CAU, NE, NW). Based on all these considerations, 13 subpopulations were proposed (Figure 1) with relevant representatives located in each population, consistent with the literature (references not shown). These proposed classifications present an allocation percentage (55%). However, when some subpopulations are reallocated, a goodness of 92% was achieved that can reach 98% when the fixed areas (CAU, NE and NW) are not included. Consequently, this new hypothesis allows classifying in a more reliable way the origin of the studied variety populations.

<figure><img src="image_31.png" /><figcaption>Fig. 1 - Map of the location of the 13 subpopulations of the study.</figcaption></figure>

Figure 2 shows the principal coordinates for the 13 subpopulations. Firstly, Coordinate 1 divides among the 13 subpopulations, forming two sectors according to the chronology of apparition (antiquity) of the different SDC. On the right sector, 4 clusters (IT-N, CE, FR-S and FR-N-C) are located. This sector includes the subpopulations IT-N and CE, which were described by Forni [3] as the most recent (dating from the first millennium BC and from the contemporary period to Roman Empire, respectively) and the subpopulations FR-S and FR-N-C, which have also been described as very recent by Böhm [7]. Coordinate 2, which is highly influenced by the vestiges of wild *Vitis*, divides the diagram in two sectors. The top
sector includes subpopulations related with the Ia SDC (Anatolian Region-circum Mesopotamia) described by Forni [3]. This SDC corresponds roughly to the area of the subpopulation NE, which is dated between the 6th and 5th millennium BC, being therefore the oldest. Moreover, the 66.66% of the varieties which belong to NE perfectly preserved the traits of wild vine in their genomic profile. This sector also includes IT-N (the farthest; 100% of accessions with wild traits), IT-CS (heavily influenced by GRE; 30.1% of accessions were assigned to wild vine group) and PI-NE-E (influenced by BALK and GRE; 68.75% of accessions with wild traits). The subpopulations situated on the bottom sector are under the influence of CAU and GRE (which are dated in the 6th-5th millennium and in the 5th-4th millennium BC, respectively, according to Forni [3]). These subpopulations have some wild traits, with the exception of PI-CSW-CS (28.57%) and BALK (42.1%). The subpopulations CE, FR-S and FR N-C are situated on the right bottom quadrant. Their location in relation to Coordinate 1 may suggest that these clusters are not influenced by CAU-GRE, probably because they are chronologically the most modern and also the most mixed. However, their location in this graphic in relation to Coordinate 2 suggests that they might have some reminiscences of CAU and GRE genomes.

<figure><img src="image_32.png" /><figcaption>**Fig. 2** - Representation by Principal Coordinates of the 13 subpopulations of the study.</figcaption></figure>

In general, the Fst value is very low for all subpopulations, indicating that the gene flow is very high and the genetic drift very low among these subpopulations (Figure 3). These results are quite logical considering that the analyzed varieties are from the same species and from geographical areas relatively nearby. However, the pairwise most far apart are (in this order) CAU and NE, IT-N and IT-C-S, and FR-C-N. These are followed by FR-S, CE-BALK and the three PI regions (PI-CSW-CS, PI-N-NW and PI-NE-E). The GRE and specially NW areas have the lowest Fst values.

<figure><img src="image_33.png" /><figcaption>**Fig. 3** - Matrix Fst values for the 13 subpopulations of the study.</figcaption></figure>

Focusing on the French populations, concretely in southern France, the FR-S population was characterized by having varieties like Aboriou, Marsanne, Tannat, Schiava grossa, Counoise, Cot, Viognier, Petit Verdot, Mondeuse noir, Manseng noir, Merlot noir, Cabernet franc, Chasselas blanc, Mauzac blanc and Syrah, as well as others. In central and northern France, the FR-CN population was characterized by having the
members of the Pinot family, as well as varieties like Teinturier, Bequignol noir, Chenin blanc, Vioshino, Sauvignon blanc, Cabernet sauvignon, Carmenère, Petit Manseng blanc, and others.

Furthermore, after the observation and interpretation of Figures 2 and 3, it can be concluded that both locations in the graphic (so far from the rest) and their Fst (quite high compared to the rest) indicate these French populations could be considered SDC. Terral et al. [6] hypothesized a SDC located in the Languedoc area (based on phenotypic studies). Furthermore, they described Pinot noir as one of the oldest cultivars, considering it is parent of more than 46 current cultivars. Regner et al. [11] proposed that one parent of Pinot was the variety Savagnin blanc, whose best-known synonymy is Traminer. In addition, he also exposed two theories on the origin of the Pinot family: 1) due to their morphological traits (ampelographic) it is assumed a close relationship with the wild vine and 2) the Romans were responsible for the expansion thereof. Myles [12] proposed as progeny of the variety Savagnin blanc, among others, varieties such as Pinot noir, Chenin blanc, Sauvignon blanc, Bequignol or Petit Manseng blanc, and curiously all of them are part of the subpopulation FR-NC. Terral [6], in turn, also described a relationship between Savagnin blanc and Pinot noir and emphasized once again the hypothesis of hybridization between the wild vine and an imported viniferous from Rome (which in this case could be the variety Traminer (Savagnin blanc)).

Finally we conclude that: 1) the hypothesis of the existence of two SDC (Languedoc area and northern France), might be confirmed, and 2) to carry out studies based on geography, it is necessary to reallocate their individuals to obtain reliable results.

## References

1. Negrul AM (1946) Origin and classification of cultured grape, pp. 159-216. *In The Ampelography of the USSR, Vol. 1*. A Baranov, YF Kai, MA Lazarevski, AM Negrul, TV Palibin & NN Prosmoserdov (eds), Moscow: Pischpromizdat.

2. Arroyo-García R, Ruiz-García L, Bolling L et al (2006) Multiple origins of cultivated grapevine (*Vitis vinifera* L. ssp. *sativa*) based on chloroplast DNA polymorphisms. *Mol Ecol* **15**: 3707-3714.

3. Forni G (2012) The origin of the "Old World" viticulture. *In Caucasus and Northern Black Sea Region Ampelography. Vitis*, Special Issue **51**: 27-38.

4. Marsal G, Mateo JM, Canals JM et al (2015) *Tree Genet Genomes* (enviado, aún por publicar).

5. Bacilieri R, Lacombe T, Le Cunff L et al (2013) Genetic structure in cultivated grapevines is linked to geography and human selection. *BMC Plant Biol* **13**: 25.

6. Terral JF, Tabard E, Bouby L et al (2010) Evolution and history of grapevine (*Vitis vinifera*) under domestication: new morphometric perspectives to understand seed domestication syndrome and reveal origins of ancient European cultivars. *Ann Bot* **105**: 443-455.

7. Böhm J (2013) *Beginnings of Viticulture*. Vine to Wine Circle, http://www.vinetowinecircle.com/en/ (accessed in 2015).

8. Marsal G, Boronat N, Canals JM et al (2013) Comparison of the efficiency of some of the most usual DNA extraction methods for woody plants in different tissues of *Vitis vinifera* L. *J Int Sci Vigne Vin* **47**: 227-237.

9. Grassi F, Labra M, Imazio S et al (2003) First evidence of a secondary grapevine domestication centre detected by SSR analysis. *Theor Appl Genet* **107**: 1315-1320.

10. De Andrés MT, Benito A, Perez-Rivera G et al (2012) Genetic diversity of wild grapevine populations in Spain and their genetic relationships with cultivated grapevines. *Mol Ecol* **21**: 800-816.

11. Regner F, Stadlbauer A, Eisenheld C et al (2000) Genetic relationships among Pinots and related cultivars. *Am J Enol Vitic* **51**: 7-14.

12. Myles S, Boyko AR, Owens CL et al (2010) Genetic structure and domestication history of the grape. *Proc Natl Acad Sci USA* **108**: 3530-3535.
# Effect of trellising system on volatile compounds of red wines in Mediterranean climate

M. KYRALEOU<fnref n="1" />*, S. KALLITHRAKA<fnref n="1" />, S. KOUNDOURAS<fnref n="2" />, S. HAROUTOUNIAN<fnref n="3" />, Y. KOTSERIDIS<fnref n="1" />

Trellising system – wines – volatile compounds – DMS

## Introduction

Several factors such as soil, climate, variety [1] and viticulture practices [2] may influence the aromatic potential of grapes and hence the volatile compounds of the corresponding wines. To improve the quality of red wines, various viticultural practices have been applied in vines, such as training systems [3]. Each training system involves specific growing conditions, including the berry exposure to sunlight, foliage orientation, vine density and vine size [4] and as a consequence affects the grape and wine composition including volatile compounds and sensory parameters [2, 3, 5]. *Vitis vinifera* c.v. Xinomavro is the main red grape variety cultivated in Northern Greece. The wines produced from this variety are characterized by “hard”, “rustic” and “sharp” tannins and have a unique aromatic character consisting of fruity and vegetal aromas. In previous studies, high levels of dimethyl sulphide (DMS) were reported in Xinomavro wines after ageing period [6, 7]. The aroma of DMS was described as corn and cabbage [8] and it is an important compound for this variety [7].

The aim of the present work was to investigate the effect of the vine trellising system on the volatile composition of the corresponding wines. For this purpose, three different training systems, one divided (Lyre) and two vertical (Royat and Guyot), were applied in a vineyard of Naoussa.

## Materials and methods

### *Trellising system treatments*

The study was carried out during the 2011 season in a 7-year-old commercial vineyard in Naoussa, northern Greece (40°39'32"N 22°4'21"E, 250 m), planted with *Vitis vinifera* L. cv. Xinomavro (clone V6) and grafted onto 110R rootstock. The vineyard was located on a clay loam soil (pH 7.8) and rows were east-west oriented. Vines were trained according to three different trellis systems, one horizontally divided (Lyre) and two vertically positioned, Royat and Guyot, at 2970 (2.30 × 1.45 m), 3970 (2.30 × 1.10 m) and 3970 (2.30 × 1.10 m) plants/ha, respectively. In the Lyre treatment, vines were pruned to 10 spurs of 2 buds per vine. The Royat system was composed of a double spur-pruned permanent cordon with 5 spurs of 2 buds per vine, while for the Guyot system, a single cane of 10 buds and one spur of 2 buds were retained. The three treatments were replicated 3 times in a randomized block design, with 20 vines per replication. All treatments were equally irrigated, receiving 42 L per vine during the season. Harvest was conducted simultaneously for the three treatments on 28/08/2011 according to technological maturity surveys (must °brix). Three red wine vinifications took place under similar conditions in triplicates.

### *Volatile compound analysis*

Aroma components were analyzed by GC-MS using the Head-Space Solid Phase Micro Extraction (HS-SPME) methodology. A volume of 25 mL of wine spiked with the internal standards, 2.5 µg [²H]₆-DMS and 25 µg 3-octanol, were placed into a 40-mL vial, then supplemented with 3 g NaCl, a magnetic

<footnote n="1">¹Department of Food Science & Human Nutrition, Laboratory of Enology,
Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece</footnote>

<footnote n="2">²Laboratory of Viticulture, School of Agriculture, Aristotle University of Thessaloniki,
54124 Thessaloniki, Greece</footnote>

<footnote n="3">³Department of Animal Sciences and Aquaculture, Agricultural University of Athens,
75 Iera Odos, 11855 Athens, Greece</footnote>
stir bar and sealed with a screw-top cap with a silicon septa. The vial was placed on a heating stir plate and the solution was equilibrated by magnetic stirring at 750 rpm for 5 min at 30°C. Then the SPME needle was inserted manually through the vial septum and the fiber (DVB/CAR/PDMS, 75 µm) was exposed to the headspace of the sample for 30 min at 30°C. The fiber then was retracted, the SPME device removed from the vial and inserted into the injector of GC for thermal desorption for 10 min. [²H]₆-DMS was used as an internal standard for the quantification of DMS [7, 9] and 3-octanol as an internal standard for all the other volatile compounds.

Analysis was performed using an Agilent 7890A GC equipped with an Agilent 5873C MS detector. The column used was an HP-5 capillary column (30 m × 0.25 mm i.d., 0.25 µm film thickness) and the gas carrier was helium with a flow rate of 1 mL min⁻¹. The injector and MS-transfer line were maintained at 250°C and 260°C, respectively. Oven temperature was held at 30°C for 5 min and raised to 160°C at 4°C min⁻¹ and then to 240°C at 20°C min⁻¹. The selective ion monitoring (SIM) mode was applied and as quantifiers ions were used for DMS (m/z 62), [²H]₆-DMS (m/z 68), ethyl isobutyrate (m/z 43), ethyl butyrate (m/z 71), ethyl 2 methyl butyrate (m/z 102), isoamyl acetate (m/z 43), 3-octanol (m/z 59), ethyl hexanoate (m/z 88), ethyl octanoate (m/z 88), and 2 phenyl ethyl acetate (m/z 104), respectively.

## Data analysis

Data were subjected to one-way analysis of variance (ANOVA) using Statistica V.7 Software (Statsoft Inc., Tulsa, OK). Comparison of mean values was performed using Tukey's HSD test when samples were significantly different after ANOVA (p < 0.05).

## Results and discussion

The concentrations, the odor thresholds and the odor activity values of aromatic compounds in relation with the trellising system are shown in Table 1. Odor threshold values were found in the literature [8, 9] and the odor descriptors were based in pure standard compounds compared to the literature [8]. Significant differences were observed in the mean concentration values of most compounds as far as the three trellising systems are concerned.

<table><caption>**Table 1** - Concentrations of aromatic compounds of the three trellising systems and odor description. Values with different letter are significantly different (Tukey's test, p < 0.05)</caption><thead><tr><td>Aromatic compound</td><td>Lyre</td><td>Royat</td><td>Guyot</td><td>Odor description</td></tr></thead><tbody><tr><td>dimethyl sulphide</td><td>28.27 ± 1.5a</td><td>26.22 ± 1.3a</td><td>27.8 ± 1.7a</td><td>corn, cabbage</td></tr><tr><td>ethyl isobutyrate</td><td>18.2 ± 0.7a</td><td>15.07 ± 0.5b</td><td>20.5 ± 1.2a</td><td>strawberry</td></tr><tr><td>ethyl butyrate</td><td>67.79 ± 2.1a</td><td>52.5 ± 1.3b</td><td>66.5 ± 33.7a</td><td>fruity</td></tr><tr><td>ethyl 2 methyl butyrate</td><td>3.43 ± 0.6a</td><td>2.39 ± 0.3b</td><td>3.48 ± 0.6a</td><td>apple</td></tr><tr><td>isoamyl acetate</td><td>31.69 ± 2.5a</td><td>20.84 ± 3.2b</td><td>34.62 ± 1.6a</td><td>banana</td></tr><tr><td>ethyl hexanoate</td><td>20.10 ± 1.1a</td><td>11.26 ± 2.4b</td><td>20.35 ± 1.5a</td><td>pineapple, apple</td></tr><tr><td>ethyl octanoate</td><td>97.41 ± 3.3b</td><td>126.46 ± 3.7a</td><td>92.9 ± 9.8b</td><td>pear, pineapple</td></tr><tr><td>2 phenyl ethyl acetate</td><td>31.45 ± 2.3a</td><td>30.40 ± 3.7a</td><td>30.46 ± 2.8b</td><td>rose, honey</td></tr><tr><td>sum esters</td><td>298.41 ± 10.3a</td><td>285.11 ± 2.7b</td><td>296.72 ± 5.8a</td><td></td></tr></tbody></table>

Wines from the Royat system showed lower values in ethyl isobutyrate, ethyl butyrate, ethyl 2 methyl butyrate, isoamyl acetate, ethyl hexanoate and ethyl octanoate known to confer fruity notes (Table 1). However, Guyot resulted in wines with the lowest content of 2 phenyl ethyl acetate (rose nuances). Higher concentrations of total ethyl esters were observed for Lyre (298 µg L⁻¹) and Guyot (297 µg L⁻¹).
These results are in agreement with previous studies, where it was studied the effect of training system on the ethyl ester content of wines [3, 5]. However, another study pointed out that trellising system might have an impact on flavor but not on wine aroma [2]. Finally, no differences were observed among wine DMS contents (Table 1).

As shown in Table 1, most compounds were present at higher concentrations than their corresponding odor thresholds. To evaluate the contribution of aroma compound to wine, the odor activity value (OAV) was introduced (Table 2). Odor activity values (OAV) = Cv / OTH, where Cv is the mean value of each volatile compound and odor threshold (OTH) is its odor threshold [3, 8]. Volatile compounds with OAV > 1 have an active contribution to the odor of the wine [3, 8]. According to the OAV, the most important odorant of Xinomavro wines was ethyl octanoate (OAV > 18), especially in Royat wines (OAV = 25.29). Ethyl 2 methyl butyrate and 2 phenyl ethyl acetate might not contribute to wine aroma since their OAV were lower than 1. Isoamyl acetate and ethyl hexanoate OAV values were also found to be lower than 1. However, compounds with OAV < 1 might contribute to the aroma indirectly through synergy with other compounds [10].

<table><caption>**Table 2** - Odor threshold (OTH) and odor activity value (OAV) of aromatic compounds</caption><thead><tr><th rowspan="2">Aromatic compound</th><th rowspan="2">OTH<br>(µg/L)</th><th colspan="3">OAV</th></tr><tr><th>Lyre</th><th>Royat</th><th>Guyot</th></tr></thead><tbody><tr><td>dimethyl sulphide</td><td>25</td><td>1.13</td><td>1.05</td><td>1.11</td></tr><tr><td>ethyl isobutyrate</td><td>15</td><td>1.22</td><td>1</td><td>1.37</td></tr><tr><td>ethyl butyrate</td><td>20</td><td>3.39</td><td>2.62</td><td>3.33</td></tr><tr><td>ethyl 2 methyl butyrate</td><td>18</td><td>0.19</td><td>0.13</td><td>0.19</td></tr><tr><td>isoamyl acetate</td><td>30</td><td>1.06</td><td>0.69</td><td>1.15</td></tr><tr><td>ethyl hexanoate</td><td>14</td><td>1.44</td><td>0.8</td><td>1.45</td></tr><tr><td>ethyl octanoate</td><td>5</td><td>19.48</td><td>25.29</td><td>18.58</td></tr><tr><td>2 phenyl ethyl acetate</td><td>250</td><td>0.13</td><td>0.12</td><td>0.12</td></tr></tbody></table>

## Conclusion

Trellising system may affect the aromatic composition of the wines. The Royat system resulted in wines with lower concentrations of total ethyl esters, which confer fruity notes. No differences were observed regarding the concentration of DMS, which confers cassis to vegetative nuances depending on its concentration.

## References

1. Ferreira V, López R, Cacho JF (2000) Quantitative determination of the odorants of young red wines from different grape varieties. *J Sci Food Agric* **80**: 1659-1667.

2. Zoecklein BW, Wolf TK, Pélanne L et al (2008) Effect of Vertical Shoot-Positioned, Smart-Dyson, and Geneva Double-Curtain training systems on Viognier grape and wine composition. *Am J Enol Vitic* **59**: 11-21.

3. Nan L, Liu L, Zhao X et al (2013) Effect of alternative new pruning system and harvesting times on aroma compounds of young wines from Ecolly (*Vitis vinifera*) in a new grape growing region of the Weibei Plateau in China. *Sci Hort* **162**: 181-187.

4. Howell GS, Miller DP, Edson CE et al (1991) Influence of training system and pruning severity on yield, vine size, and fruit composition of Vignoles grapevines. *Am J Enol Vitic* **42**: 191-198.
5. Fragasso M, Antonacci D, Pati S et al (2012) Influence of training system on volatile and sensory profiles of Primitivo grapes and wines. *Am J Enol Vitic* **63**: 477-486.

6. Anocibar Beloqui A, Kotseridis Y, Bertrand A (1996) Détermination de la teneur en sulfure de diméthyle dans quelques vins rouges. *J Int Sci Vigne Vin* **30**: 167-170.

7. Kyraleou M, Garde-Cerdan T, Tarantilis P et al (2012) Dimethyl sulfide: an enhancer or an important compound of varietal aroma? *In The International Scientific Symposium Horticulture-Science, Quality, Diversity, Harmony*. Iași, Romania.

8. Ferreira V, Ortín N, Escudero A et al (2002) Chemical characterization of the aroma of Grenache rosé wines: aroma extract dilution analysis, quantitative determination, and sensory reconstitution studies. *J Agric Food Chem* **50**: 4048-4054.

9. Segurel MA, Razungles AJ, Riou Ch et al (2004) Contribution of dimethyl sulfide to the aroma of Syrah and Grenache noir wines and estimation of its potential in grapes of these varieties. *J Agric Food Chem* **52**: 7084-7093.

10. López R, Ortín N, Pérez-Trujillo JP et al (2003) Impact odorants of different young white wines from the Canary Islands. *J Agric Food Chem* **541**: 3419-3425.
# Multidisciplinary approach of the regulation of the biosynthetic pathway of tartrate in *Vitis vinifera* L. Ugni blanc grape berries

C. CHOLET¹*, O. CLAISSE¹, S. CLAVEROL², A. RABOT¹, A. LI-MALLET¹, A. OSOWSKI¹, V. DUMOT³, G. FERRARI³, L. LURTON³, L. GENY¹

¹Université de Bordeaux, Institut des Sciences de la Vigne et du Vin, EA 4577, Unité de Recherche Œnologie, INRA, USC 1366 Œnologie, 210 Chemin de Leysotte, CS 50008, F-33882 Villenave d'Ornon, France

²Université de Bordeaux, Plateforme Génomique Fonctionnelle, Pole Protéomique, France

³BNIC - Station viticole, 69 rue de bellefonds, BP 18, 16101 Cognac cedex, France

*Vitis vinifera* – tartrate biosynthesis – grape berries – Ugni blanc

## Introduction

The acid component of grape berries, malate and tartrate, plays an important role in both biochemical and sensory quality of berry [1]. Whereas the primary metabolism of the grape berry and the malate pathway relating to grape maturity have been studied in depth [2, 3], few studies relate to the metabolism of tartrate [4, 5], and particularly to the control of this metabolism [6]. In *Vitis vinifera*, the synthesis of tartrate occurs in the early stages of grape berry development [2] and is the result of L-ascorbic acid (or vitamin C) catabolism *via* the conversion of 5-keto-D-gluconate to L-idonate under the action of L-idonate dehydrogenase (L-IdnDH), the only enzyme of this pathway known to date [4]. Recent studies on climate change in the French region of Cognac showed a significant increase of temperatures [7]. Many studies performed on grape varieties have demonstrated that one of the main consequences of this change for the grapes is a decrease of acidity [8], making harder wine preservation and storage [9]. It is especially true for wine distillation, such as Ugni blanc wine for Cognac, because these wines are kept in tanks without sulfites until distillation (decree n° 2011-685 of 16 June 2011), and they must have high acidity to avoid microbiological spoilage or development of olfactory default after distillation. In the last several years, the acid contents in berries have decreased steadily, but the control of these pathways is not yet assessed. Our study proposes to use a global approach with genetic (Q-PCR), proteomic (Label-Free), metabolomic (HPLC) and enzymatic aspects of the biosynthetic pathway of tartaric acid to explain the evolution of tartaric acid content in Ugni blanc grape berries from floral bud to maturity and its regulation process.

## Materials and methods

### Plant material

10 grape clusters (*Vitis vinifera* L. cv Ugni blanc) were collected in 2011, from a Cognac vineyard (France), at 6 developmental stages [10] (beginning of flowering (BF)= stage 19= 0DAA; pea-sized (PS)= stage 31= 10DAA; berry touch (BC)= stage 33= 31DAA; 10% ripe berries (VB)= stage 35= 61DAA; 80% ripe berries (VE)= stage37= 78DAA; maturity (H)= stage 38= 106DAA), from 10 vines, 3 times over and immediately frozen in liquid nitrogen. Berries were ground in liquid nitrogen using Mixer Mill MM400 (Retsch) and powders were stored at -80°C until analysis.

### Biochemical assay

Organic acids were extracted and analyzed by HPLC [11].

### Enzymatic study and proteomic analysis

After extraction of proteins, the enzymatic activity of L-IdnDH was analyzed by spectrophotometry and proteins were precipitated for Label-free analysis [12, 13].
## Gene expressions

DNAc were analyzed by Q-PCR (analysis of *VvGME*, *VvVTC2*, *VvL-GalDH*, *VvGLDH*, *VvL-IdnDH* genes) after RNA extraction [14], DNase treatment, quality controls (PCR, electrophoresis) and RT-PCR.

## Statistical data treatment

All analyses were performed in triplicate, and all data were performed with non-parametric tests (α= 0.05): Friedman test for the statistical significance of differences marked in the figures with asterisks; correlation matrix of Spearman (R software; packages: RColorBrewer; psych; corrplot).

# Results and discussion

## Organic acid contents and enzymatic activity of L-IdnDH during grape berry development (Table1)

The accumulation of tartrate, as the accumulation of total ascorbate, increased regularly up to VB, remained stable until VE and tended to increase anew until H. The evolution of contents of these two acids is highly and positively correlated, which confirms a strong link between tartaric acid and its precursor. The comparative analysis of patterns in tartrate levels and in the activity of L-IdnDH showed that the first peak of enzymatic activity (at PS) is followed by an accumulation of tartrate content, which reflects and confirms a link between enzyme activity and the final product. In the same way, the second accumulation phase of tartrate, during maturation, is in accordance with the evolution profile of enzyme activity for which an increase is observed at the end of maturation. This resumption of activity might be due to a vintage effect due to wet weather conditions during August 2011.

<table><caption>**Table 1** - Experimental data of biochemical, enzymatic, genetic and proteomic analysis.
(*) : significant difference with the Friedman test (α= 0.05)</caption><thead><tr><th></th><th>FB</th><th>PS</th><th>BC</th><th>VB</th><th>VE</th><th>H</th></tr></thead><tbody><tr><td>Mean of Tartrate content ± SD (µmol/berry)</td><td>1,48<br>±0,05*</td><td>24,78<br>±1,44</td><td>106,25<br>±5,47</td><td>190,86<br>±70**</td><td>188,9<br>±15,42</td><td>227,51<br>±31,78**</td></tr><tr><td>Mean of Tartrate content ± SD (mmol/gFW)</td><td>0,22<br>±0,01</td><td>0,22<br>±0,01</td><td>0,21<br>±0,01</td><td>0,2<br>±0,07</td><td>0,1<br>±0,01</td><td>0,11<br>±0,02</td></tr><tr><td>Mean of Ascorbate content ± SD (µmol/berry)</td><td>0,021<br>±0,01*</td><td>0,37<br>±0,06</td><td>0,77<br>±0,11</td><td>1,2<br>±0,06</td><td>1,03<br>±0,06</td><td>2,35<br>±0,96**</td></tr><tr><td>Mean of Ascorbate content ± SD (µmol/gFW)</td><td>3,12<br>±1,24*</td><td>3,33<br>±0,51*</td><td>1,42<br>±0,28</td><td>1,14<br>±0,06</td><td>0,56<br>±0,03**</td><td>1,18<br>±0,48</td></tr><tr><td>Mean of L-IdnDH enzymatic activity ± SD (µkat/berry)</td><td>0,01<br>±0,02</td><td>1,05<br>±0,75</td><td>0,52<br>±1,04</td><td>1,09<br>±1,40</td><td>4,17<br>±2,57*</td><td>1,27<br>±1,79</td></tr><tr><td>Mean of L-IdnDH enzymatic activity ± SD (µkat/gFW)</td><td>2,22<br>±3,14</td><td>9,47<br>±6,78*</td><td>1,04<br>±2,11</td><td>1,09<br>±1,32</td><td>2,25<br>±1,39*</td><td>0,63<br>±0,89</td></tr><tr><td>normalized RQ (/0DAA) of VvGME ± SD</td><td>1*</td><td>0,9<br>±1,58</td><td>1,5<br>±1,22*</td><td>0,12<br>±0,03</td><td>0,25<br>±0,42</td><td>0,02<br>±0,02**</td></tr><tr><td>normalized RQ (/0DAA) of VvVTC2 ± SD</td><td>1*</td><td>0,01<br>±0,02**</td><td>0,85<br>±0,69</td><td>0,18<br>±0,16</td><td>0,1<br>±0,15</td><td>0,01<br>±0,01**</td></tr><tr><td>normalized RQ (/0DAA) of VvL-GalDH ± SD</td><td>1</td><td>0,25<br>±0,23</td><td>2,84<br>±1,72*</td><td>0,76<br>±0,52</td><td>0,47<br>±0,62</td><td>0,2<br>±0,19**</td></tr><tr><td>normalized RQ (/0DAA) of VvGLDH ± SD</td><td>1*</td><td>0,53<br>±0,85**</td><td>0,87<br>±0,57*</td><td>0,13<br>±0,04</td><td>0,14<br>±0,25</td><td>0,02<br>±0,02***</td></tr><tr><td>normalized RQ (/0DAA) of VvL-IdnDH ± SD</td><td>1</td><td>7,01<br>±4,55</td><td>4,86<br>±4,70*</td><td>0,14<br>±0,09**</td><td>0,6<br>±0,27</td><td>0,49<br>±0,63</td></tr><tr><td>Relative proteomic expression of GME (F6HTR2) ± CV%</td><td>25176<br>±9%*</td><td>31778<br>±47%</td><td>56871<br>±19%**</td><td>38099<br>±29%</td><td>25767<br>±15%*</td><td>19115<br>±41%*</td></tr><tr><td>Relative proteomic expression of L-GalDH (D7T3I7) ± CV%</td><td>459522<br>±16%</td><td>981369<br>±35%*</td><td>674765<br>±31%</td><td>390920<br>±18%**</td><td>304876<br>±63%**</td><td>803123<br>±55%*</td></tr><tr><td>Relative proteomic expression of L-IdnDH (Q1PSI9) ± CV%</td><td>672065<br>±7%</td><td>719228<br>±3%</td><td>897675<br>±9%*</td><td>392115<br>±5%</td><td>289722<br>±16%**</td><td>298119<br>±20%**</td></tr></tbody></table>
Relative mRNA expression levels and translation of organic acid precursors during grape berry development (Table 1)

Profiles of expression of the coding genes in the Smirnoff-Wheeler pathway (*VvGME*, *VvVTC2*, *VvGLDH*, *VvLGalDH*) were comparable and characterized by a first phase of overexpression during herbaceous growth up to a peak of maximal expression synchronized at BC. The expression then decreased until the end of the maturation phase (H). The evolution of relative expression of these genes is positively and more or less highly correlated (Fig. 1), which confirms a strong link between these genes. We have noticed that the profile of protein expression of GME is comparable and positively correlated with the profile of *VvGME* (Fig. 1). However, the profile of protein expression of L-GalDH is not comparable and not correlated with the profile of *VvL-GalDH* (Fig. 1). The expression profile obtained for *VvL-IdnDH* differs from that of the previous 4 genes in that it shows a strong overexpression at PS until BC, followed by a significant decrease until VE, which tended to remain stable until H. The profile of protein expression of L-IdnDH is comparable and positively correlated with the profile of *VvL-IdnDH* (Fig. 1). The synthesis of tartrate seems to be regulated in a different way from that of ascorbate, especially as the evolution of relative expression of *VvL-IdnDH* is not correlated with that of the previous 4 genes of the Smirnoff-Wheeler pathway (Fig. 1). We have highlighted two interesting correlations (Fig. 1): tartrate contents vs genetic expression of *VvL-IdnDH* were positively (mmol/gFW) or negatively (µmol/berry) correlated; tartrate contents vs protein expression of L-IdnDH were positively (mmol/gFW) or negatively (µmol/berry), and strongly correlated. And we have noticed that these correlations also appear between ascorbate content vs genetic expression of *VvL-IdnDH*, or between ascorbate content vs protein expression of L-IdnDH. Thus, a strong link between tartaric acid, total ascorbic acid, *VvL-IdnDH* and protein expression of L-IdnDH has appeared.

<figure><img src="image_34.png" /><figcaption>**Fig. 1** - Correlation matrix of some genes and proteins of interest in the tartaric-acid pathway.
The disks are the significant p-values (p<0.05) and the colors represent the rho in the Spearman test.</figcaption></figure>
**Conclusion**

The existence of two distinct pathways was confirmed: one upstream of ascorbate, corresponding to the *VvGME*, *VvVTC2*, *VvL-GalDH*, *VvGLDH* genes, with one phase of genetic and protein activity (during the herbaceous phase). The other downstream of ascorbate, leading to the synthesis of tartrate and corresponding to the *VvL-IdnDH* gene, with maximum genetic and protein expression towards the beginning of the growth phase, and in correlation with the enzymatic activity profile. This study highlights a strong link between tartrate, ascorbate, *VvL-IdnDH* and protein expression of L-IdnDH. Further studies seem indispensable to complete these first results, by taking into account the vintage effect.

**Acknowledgements**

This study was supported by France AgriMer and the Poupelain foundation (Javrezac, France). The authors would like to thank Dr W. Albertin for expertise in statistical analysis.

**Abbreviations**

FB, flowering beginning; PS, pea size; BC, bunch closed; VB, beginning of veraison; VE, end of veraison; H, harvested; DAA, day after anthesis.

**References**

1. Ribereau-Gayon G (1968) Etude des mécanismes de synthèse et de transformation de l'acide malique, de l'acide tartrique et de l'acide citrique chez *Vitis vinifera* L. *Phytochemistry* **7**: 1471-1482.

2. Iland PG, Coombe BG (1988) Malate, tartrate, potassium, and sodium in flesh and skin of Shiraz grapes during ripening: concentration and compartimentation. *Am J Enol Vitic* **39**: 71-76.

3. Etienne A, Génard M, Lobit P et al (2013) What controls fleshy fruit acidity? A review of malate and citrate accumulation in fruit cells. *J Exp Bot* **64**: 1451-1469.

4. Debolt S, Cook DR, Ford CM (2006) L-Tartaric acid synthesis from vitamin C in higher plants. *Proc Natl Acad Sci USA* **103**: 5608-5613.

5. Melino VJ, Soole KL, Ford CM (2009) Ascorbate metabolism and the developmental demand for tartaric and oxalic acids in ripening grape berries. *BMC Plant Biol* **9**: 145.

6. Melino VJ, Hayes MA, Soole KL et al (2011) The role of light in the regulation of ascorbate metabolism during berry development in the cultivated grapevine *Vitis vinifera* L. *J Sci Food Agric* **91**: 1712-1721.

7. Boitaud L, Dumot V, Ferrari G et al (2010) Constat et incidence du changement climatique dans la région de Cognac. *O.I.V. 33ème Congrès Mondial de la Vigne et du Vin*, Géorgie.

8. Neethling E, Barbeau G, Bonnefoy C et al (2012) Change in climate and berry composition for grapevine varieties cultivated in the Loire valley. *Clim Res* **53**: 89-101.

9. Mira de Orduña R (2010) Climate change associated effects on grape and wine quality and production. *Food Res Int* **43**: 1844-1855.

10. Eichhorn KW, Lorenz DH (1977) *Der deutsche Weinbau*, 1.

11. Melino VJ, Soole KL, Ford CM (2009) A method for determination of fruit-derived ascorbic, tartaric, oxalic and malic acids, and its application to the study of ascorbic acid catabolism in grapevines. *Aust J Grape Wine Res* **15**: 293-302.

12. Lanotte P, Perivier M, Haguenoer E et al (2013) Proteomic biomarkers associated with *Streptococcus agalactiae* invasive genogroups. *PLoS ONE* **8**: e54393.

13. Käll L, Canterbury JD, Weston J et al (2007) Semi-supervised learning for peptide identification from shotgun proteomics datasets. *Nat Methods* **4**: 923-925.

14. Reid KE, Olsson N, Schlosser J et al (2006) An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development. *BMC Plant Biol* **6**: 27.
# Etude des facteurs influençant la synthèse de géosmine dans le raisin – Recensement des connaissances acquises et présentation sous la forme d'un modèle conceptuel

S. DUPIN<fnref n="1" />, L. GUERIN<fnref n="1" />*, J. WERY<fnref n="2" />

Géosmine – flore microbienne – élicitation des savoirs experts – modèle conceptuel

## Introduction

Le [1,10-trans-dimethyl-trans-9-decalol], couramment appelé géosmine, est un composé présentant une odeur terreuse et moisie [1] et constitue un défaut organoleptique du vin appelé goût moisi-terreux (GMT). En France, sur le raisin, le composé a été mis en évidence dès le début des années 1990. Des travaux sur le sujet ont commencé au début des années 2000 et se poursuivent encore aujourd'hui. C'est pourquoi, il a semblé intéressant de faire un bilan des connaissances sur le sujet. Celles-ci ont été inventoriées dans la bibliographie ou par élicitation des savoirs experts.

Un bilan des études réalisées sur le problème a été réalisé et a permis d'identifier (i) les conditions de production de la molécule, (ii) l'état de la végétation favorable à la production, (iii) les méthodes permettant d'éviter l'apparition du composé dans le raisin et (iv) les leviers d'action curatifs à la cave. Afin de schématiser le bilan des connaissances réalisé, la méthode de modélisation conceptuelle a été utilisée.

## Matériel et méthodes

### Elaboration du modèle conceptuel

La modélisation conceptuelle d'un agroécosystème est une méthode itérative avec comme produit final un modèle fourni sous la forme d'une représentation graphique associée à une base de connaissances apportant les justifications de chaque composant et relation [2]. Le modèle conceptuel est mis en place grâce à une démarche d'élicitation des savoirs experts. La bibliographie ainsi que des entretiens avec des experts permettent de définir (i) les composants de la plante, (ii) les composants de l'environnement et (iii) les relations entre composants intervenant dans le problème étudié.

Des entretiens avec des experts ont permis de recenser leurs connaissances et d'éprouver et valider les hypothèses mises en place à partir de la bibliographie et des conclusions des entretiens avec d'autres experts.

Une liste de 54 facteurs pouvant avoir une influence sur la synthèse de géosmine par la flore productrice a ensuite été soumise à un ensemble d'experts de disciplines variées associée à une description de la problématique étudiée. Chacun devait alors affecter des points, selon leur ordre d'importance, aux facteurs ayant selon lui le plus d'influence. Une classification ascendante hiérarchique a été réalisée sur l'ensemble des facteurs en utilisant la somme des notes reçues et a permis de sélectionner les facteurs les plus influents, qui sont présentés dans cet article.

### Analyse des données

Les analyses statistiques ont été réalisées grâce au logiciel STATlab V3.0 (SLP Infoware, Ivry-sur-Seine, France). Les schémas ont été réalisés à l'aide du logiciel yEd version 3.11.1 (yWorks GmbH, Tübingen, Germany).

<footnote n="1">¹IFV, 509 Avenue de Chanteloup, 37400 Amboise, France</footnote>

<footnote n="2">²UMR System, Montpellier SupAgro, Bâtiment 27, 2 place Viala, 34060 Montpellier, France</footnote>
# Résultats et discussion

## Description du mécanisme de production

La géosmine est produite sur un milieu riche en azote ou en sucres. Sur le raisin, elle est principalement produite par certaines souches de *Penicillium expansum* [3, 4]. La figure 1 met en avant les étapes nécessaires, sans pour autant être suffisantes, pour que de la géosmine soit produite dans le raisin.

<figure><img src="image_35.png" /><figcaption>Fig. 1 - Etapes clefs menant à la production de géosmine.</figcaption></figure>

*Penicillium expansum* ne possède pas d'enzymes pectolytiques leur permettant d'altérer la pellicule de la baie de raisin. Ils ne peuvent donc contaminer la baie qu'après qu'un élément perturbateur (principalement le vers de la grappe et le champignon *Botrytis cinerea*), provoquant des blessures sur la baie leur ait donné accès à la pulpe [4]. Même si la baie est déjà blessée, la germination et le développement du mycélium de *Penicillium expansum* n'ont lieu qu'après la véraison. Cela s'explique par le passage, au moment de la véraison, de la baie d'un organe chlorophyllien à un organe puits se chargeant en sucre.

*Penicillium expansum* synthétise la géosmine lorsque les conditions extérieures et l'équilibre du microbiote sont favorables [4, 5]. Deux voies de production ont été proposées et peuvent co-exister. Une première voie de production possible est la voie directe pour laquelle dès que les conditions de synthèse sont atteintes, les microorganismes synthétisent la molécule en détournant a priori une des molécules produites lors de la glycolyse [3]. D'autres auteurs émettent l'hypothèse que la synthèse de géosmine par *Penicillium expansum* se fait sur un substrat préalablement carencé par *Botrytis cinerea*, notamment en azote, minéraux ou vitamines [4].

## Facteurs influençant la production

Les conditions extérieures (température, hygrométrie, rayonnement solaire, pression partielle de dioxygène ou de dioxyde de carbone) ont un effet sur la capacité des microorganismes à germer, se développer, sporuler et produire différents métabolites.

L'activité photosynthétique de la plante permet de fournir aux microorganismes producteurs le substrat nécessaire à la synthèse du composé. Le franchissement de la véraison nécessite qu'un certain cumul de températures ait été atteint. Au sein de chaque cep, les conditions extérieures ne sont pas directement transmises aux baies. Elles sont traduites en microclimat du feuillage ou de la grappe. Un feuillage plus dense et / ou des grappes plus compactes favorisent un microclimat plus frais et plus humide que les conditions extérieures. Cela explique l'effet favorisant des entassements de végétation sur la sensibilité des baies de raisin à la géosmine. La figure 2 schématise ces interactions.
<figure><img src="image_36.png" /><figcaption>**Fig. 2** - Schéma bilan des interactions entre composants influents sur la production de géosmine présentés dans cet article.</figcaption></figure>

Les techniques culturales permettent d'agir sur la forme du feuillage, sa densité, l'entassement de la végétation, le nombre de grappes et leur entassement. Elles agissent ainsi sur le microclimat ce qui a une influence sur les mécanismes de production décrits ci-avant. La classification réalisée pour déterminer les facteurs les plus influents sur la production a mis en avant une influence primordiale de l'effeuillage, de la mise en place d'un enherbement compétitif, de la lutte chimique et de l'ébourgeonnage pour permettre de lutter contre la production de géosmine. Il y a une forte composante cépage dans la détermination de la sensibilité à la géosmine.

### Bilan des travaux et proposition d'expérimentations pour valider le modèle

L'application de la méthode de modélisation conceptuelle d'un agroécosystème nous a permis de recenser l'essentiel des connaissances acquises sur la problématique depuis 15 ans : flore productrice, mécanismes de production, méthodes prophylactiques, méthodes curatives, interaction avec l'environnement ...

Ce travail nous a permis de relever les points de la problématique manquant encore de consensus. Des expérimentations ont ainsi pu être proposées. Elles devraient permettre de (i) déterminer l'effet de *B. cinerea* dans la production de géosmine, (ii) mettre en avant de nouveaux modes de lutte contre la flore productrice et (iii) élucider les éléments déclencheurs de la synthèse.

## Conclusion

La problématique de la production de géosmine sur raisin nous a semblée bien connue. D'importantes connaissances sont disponibles sur les microorganismes producteurs, des méthodes prophylactiques ainsi que des méthodes curatives. Ces connaissances nous ont semblé moins nombreuses à propos du cycle de développement de *Penicillium expansum* et des raisons précises déclenchant la production du composé par ce champignon. Toutefois, d'un point de vue strictement technique, la problématique semble bien circoncise en France et grâce à l'application des règles prophylactiques conseillées, il ne devrait plus y avoir de GMT dans les prochains millésimes.

## Références

1. Darriet P, Pons M, Lamy S et al (2000) Identification and quantification of geosmin, an earthy odorant contaminating wines. *J Agric Food Chem* **48**: 4835-4838.

2. Lamanda N, Roux S, Delmotte S et al (2012) A protocol for the conceptualisation of an agro-ecosystem to guide data acquisition and analysis and expert knowledge integration. *Eur J Agron* **38**: 104-116.

3. Behr M, Serchi T, Cocco E et al (2014) Description of the mechanisms underlying geosmin production in *Penicillium expansum* using proteomics. *J Proteomics* **96**: 13-28.

4. La Guerche S, De Senneville L, Blancard D et al (2007) Impact of the *Botrytis cinerea* strain and metabolism on (-)-geosmin production by *Penicillium expansum* in grape juice. *Antonie van Leeuwenhoek* **92**: 331-341.

5. Morales-Valle H, Silva LC, Paterson RRM et al (2011) Effects of the origins of *Botrytis cinerea* on earthy aromas from grape broth media further inoculated with *Penicillium expansum*. *Food Microbiol* **28**: 1048-1053.
# Application of UV-light in the vineyard to increase the content of phytochemicals in grapes

E. ELEJALDE¹*, I. LÓPEZ-DE-ARMENTIA¹, S. QUINTELA¹, M.C. VILLARÁN¹, S. ARINA²

¹TECNALIA Research & Innovation, Health Division, Technological Park of Álava, 01510 Miñano, Spain

²BODEGAS BAIGORRI, Ctra. Vitoria-Logroño, km 53, 01307 Samaniego, Spain

Grape – UV-light – phytochemical – ripening

## Introduction

Plants require sunlight exposure to provide energy for the photosynthetic activity. In response to elevated doses of solar radiation, including UV radiation, plants have evolved a number of protective mechanisms. One effective strategy is the accumulation of phenolic compounds that selectively absorb UV in the plant. Phenolic compounds in grape berries not only determine the mouth-feel, storage period, color and biochemical stability of wines [1] but also have health benefits, such as antioxidant and anticancer properties, protection against cardiovascular disease and so on [2]. Nowadays, there is much interest in studying the potential health benefits of dietary polyphenols as antioxidants, but also of other phytochemicals present in grapes such as carotenoids and dietary fiber. The beneficial health-related effects of dietary phytochemicals in grapes are of importance to consumers, grape producers and the wine industry.

The aim of this work was to study the influence of different types and doses of UV-light radiation on the quality and content of bioactive molecules in grape berries during the ripening until harvest. Resveratrol, β-carotene and fiber content were determined in grape berries at harvest time after the vine was irradiated with both UV-B and UV-C light at different intensities and doses. Tempranillo variety grapes were selected for the study. The study was carried out in 2013 harvest.

## Materials and methods

### UV treatments

The experiments were conducted in 2013 in a vineyard of Bodegas Baigorri, grown on trellises. The vineyard was planted in 2001 and the grapes were of Tempranillo red variety. The vineyard was divided into five different treatments: one being used as control, two exposed to UV-B radiation and the other two to UV-C. The difference between the same types of irradiation was based on the dose. Some grapes were irradiated from veraison until harvest and other grapes only some weeks before harvest.

The radiation to the grape was supplied by UV-B and UV-C lamps. The UV-B lamp (wavelength range 280-315 nm) had the emission spectrum energy concentrated at 311 nm and the UV-C lamp (wavelength range 200-280 nm) had the emission spectrum energy concentrated at 254 nm. The grapes were exposed daily to the UV irradiation for some seconds. The control sample was not exposed to any UV irradiation by lamps.

### Grape phytochemical analysis

All the grape samples were hand-harvested at harvesting time. The samples were protected from light to avoid light induced reactions during sample treatment. One hundred berries of each sample were randomly taken from different places on 5 clusters, freeze-dried and stored at -20°C until extraction.

The resveratrol extraction and determination was realized based on Romero-Pérez et al. [3] and the β-carotene extraction and analysis on Oliveira et al [4]. The fiber content was determined by the AOAC Official Method [5]. Besides, other parameters were analyzed in grape berries like pH, acidity, organic acid content and color-related parameters (color intensity, hue, CIELab).
**Results and discussion**

The concentration in resveratrol, β-carotene and fiber in response to the different UV exposure were examined in the grape berries at harvest time. The levels of these molecules are shown in Figures 1-3. The content varied depending on the type of irradiation and the applied dose.

<figure><img src="image_37.png" /><figcaption>Fig. 1 - β-carotene content in grape berries at harvest time.</figcaption></figure>

<figure><img src="image_38.png" /><figcaption>Fig. 2 - Resveratrol content in grape berries at harvest time.</figcaption></figure>

<figure><img src="image_39.png" /><figcaption>Fig. 3 - Total fiber content in grape berries at harvest time.</figcaption></figure>
In grape berries treated in the vineyard with different UV types and doses, the highest levels of resveratrol were detected when the irradiation began at maturity. Besides, UV-B produced higher resveratrol content in grape berries than UV-C. The results show that the final resveratrol content is reduced if the grape berries are irradiated since veraison. In berries of the field experiment, the highest levels in resveratrol were obtained when the grape berries were irradiated during the maturity stage. These results show that in this case it is enough to irradiate from the maturity stage to harvest to obtain 6-times higher resveratrol content in comparison to the non-additional UV irradiated grapes.

Regarding β-carotene, in grape berries the presence of this carotene is abundant before veraison, and subsequently decreases dramatically. Cultivar, viticulture region, exposure to sunlight and ripening stage all affect carotenoid concentrations in grapes [6].

The irradiation with UV light decreased this reduction. The grape irradiated with UV-C presented the highest final content in β-carotene in comparison to the grape irradiated with UV-B. Regarding the dose, the grapes more irradiated maintained the highest concentration.

According to the fiber content, the experimental results showed that UV-B and UV-C irradiance caused the reduction of the content of total fiber. Significant decrease in total fiber content was observed in grape berries when irradiated since veraison. The reduction was by 31% with UV-C and by 36% with UV-B. This reduction was lower when the radiation was applied since the maturity stage with reductions in UV-B and UV-C treated grape berries by 25% and 23%, respectively. The results show no significant differences in the parameters related to grape quality (pH, total acidity, organic acids). Nevertheless, differences were found in color-related parameters (color intensity, hue, CIELab) depending on the type of UV light and the applied doses.

## Conclusion

According to our results, it seems that UV stimulates the biosynthesis of UV absorbing compounds and carotenoids, which both perform a photoprotective function, in accordance with the results of other authors [7]. The results suggest that the use of this technology to increase the amount of different bioactive molecules is feasible considering also that it does not interfere with other important quality parameters in wine like acidity or color. Therefore, UV radiation is a promising emerging technology for increasing bioactive molecule content in grape berries, which would provide also an added value to wine.

## Acknowledgements

This work is supported by funding from Centre for the Development of Industrial Technology (CDTI) and the winery BODEGAS BAIGORRI. CDTI is a Public Business Entity, answering to the Ministry of Economy and Competitiveness, which fosters the technological development and innovation of Spanish companies.

## References

1. Vidal S, Francis L, Guyot S et al (2003) The mouth-feel properties of grape and apple proanthocyanidins in a wine-like medium. *J Sci Food Agric* **83**: 564-573.

2. Skerget M, Kotnik P, Hadolin M et al (2005) Phenols, proanthocyanidins, flavones and flavonols in some plant materials and their antioxidant activities. *Food Chem* **89**: 191-198.

3. Romero-Pérez AI, Lamuela-Raventós RM, Andrés-Lacueva C et al (2001) Method for the quantitative extraction of resveratrol and piceid isomers in grape berry skins. Effect of powdery mildew on the stilbene content. *J Agric Food Chem* **49**: 210-215.

4. Oliveira C, Barbosa A, Silva Ferreira AC et al (2006) Carotenoid profile in grapes related to aromatic compounds in wines from Douro region. *J Food Sci* **71**: S1-S7.

5. AOAC Official Method 991.43 (1995) *Total, soluble, and insoluble dietary fiber in foods*. Enzymatic-gravimetric method, MES-TRIS buffer.

6. Razungles A, Bureau S, Bayonove C et al (1998) Effect de l'ensoleillement sur les teneurs en précurseurs d'arômes des baies de Syrah, pp. 382-388. *In 23ème Congrès Mondial de la Vigne et du Vin*.

7. Campos JL, Figueras X, Pinol MT et al (1991) Carotenoid and conjugated polyamine levels as indicators of ultraviolet-C induced stress in *Arabidopsis thaliana*. *Photochem Photobiol* **53**: 689-693.
# Effect of rootstock on berry and wine composition of new red grapevine cultivars

M. MICHLOVSKÝ*, A. KHAFIZOVA

Vinselekt Michlovský a.s., Rakvice, Czech Republic

Phenolic compounds – rootstock – berry and wine composition – resistant grape cultivar

## Introduction

In the past few decades, several new resistant grape cultivars were bred and introduced in Czech Republic. However, the effect of different factors, such as rootstocks and vineyard sites, on primary and secondary metabolite composition is still unknown. The main directions of grape breeding programs in the region are to obtain grape cultivars with complex resistance to powdery and downy mildew and of high wine and grape quality. The importance of those new resistant cultivars in ecological and sustainable farming systems is very high. The use of those varieties helps to reduce environmental pollution risks (less pesticide application) and the related production costs [1].

The choice of rootstock is a pre-planting decision that lasts for the life of the vineyard, and so should not be taken without careful consideration. Rootstocks allow vines to perform better in soils of a particular type (e.g. high pH or very deep and fertile) or in those with an undesirable infestation (e.g. phylloxera or nematodes) [2]. Numerous studies confirm that rootstocks significantly affect vegetative growth [3], scion phenology [4], leaf area and canopy development [5] as well as yield [6] and grape quality [7]. Research that concerns secondary metabolites gives controversial results. Most authors agree that rootstock does not influence or have minor influence on secondary metabolites and phenolic compounds in particular [8, 9]. Although the interactions between rootstock and scion are very complex, current work could contribute to their better understanding.

The most widespread rootstocks in Czech Republic, SO4 and K5BB, belong to the *V. berlandieri x V. riparia* family, therefore it is very important to study rootstocks from a different origin that suit best to the local conditions.

It is known that phenolic compounds, in particular stilbenes, play major role in disease resistance of vines [10]. Therefore the choice of suitable rootstock could help in reducing the incidence of major grape diseases and in supporting natural resistance of vines along with grape and wine quality via direct and indirect mechanisms. The aim of the present study was to evaluate the influence of different rootstocks on the grape and wine composition along with the phenolic compounds of two resistant red cultivars. The experiments were conducted for three consecutive years with field-grown plants.

## Materials and methods

### Plant material and experimental conditions

Field experiments were conducted in a commercial vineyard “Terasy” (PB 8803/4), at Vinselekt Michlovsky a.s., Czech Republic, during three growing seasons (2009, 2010 and 2011). The vineyard is located on slope with 10.3° inclination. The slope orientation is south and south-west. The average altitude is 282.6 m. Soil is heavy and represented by black soils, brown soils, slightly gleyed eroded soils, and limy soils according to carbonate content. The vineyard was planted in 2004 with new red wine cultivars (Laurot and Nativa) that have high resistance level to downy and powdery mildew and that are highly suitable for organic viticulture. The wines are of high quality, with a dense color and distinct St. Laurent-Merlot aromas. The genealogical analysis showed that the heritage basis of both cultivars included 9% of six American species (*Vitis rupestris*, *Vitis lincecumi*, *Vitis aestivalis*, *Vitis cinerea*, *Vitis berlandieri*, *Vitis labrusca*) and 91% of *Vitis vinifera*. Lemberger, St. Laurent and Merlot contributed 25% each, further 16% of the heritage basis was contributed by other *V. vinifera* cultivars. Laurot was grafted onto rootstocks

<footnote>*Corresponding author: khafizova@michlovsky.com</footnote>
V. berlandieri x V. rupestris (Paulsen 1103), V. berlandieri x V. riparia (SO4, Binova, Teleki 5C, Kober 125AA, 8B, Craciunel 2), and V. riparia x V. cinerea (Börner). The second interspecific hybrid (Nativa) was grafted onto rootstocks Paulsen 1103, SO4, Kober 125AA, 8B, Binova, Craciunel 2 and Börner. The grapevines were spaced 2.4 m between rows and 0.9 m within rows. The plants were cane-pruned to 8-10 buds. Vineyard is managed in the system of ecological farming. Rootstock SO4 was used as a control. For each cultivar*rootstock combination, 10 plants were chosen by means of complete randomization method for small plot winemaking and berry sampling [11]. Among studied agrobiological indexes were yield and cluster weight.

### Standard analysis of must and wine

Must chemical analysis (sugar content, total acidity and pH) was performed according to standard techniques [12] in Vinselekt Michlovský a.s. laboratory. Wine chemical analysis (alcohol content, total acidity, residual sugar, pH, malic acid, tartaric acid, glycerol, citric acid, lactic acid, volatile acidity and non-reducing extract) was performed on Foss WineScan FT 120 in the laboratory of Vinselekt Michlovský a.s. Wine sensory assessment was based on altered tasting method of UKZUS [13].

### Analysis of phenolic compounds

The concentrations of certain groups of phenolic compounds in berries and wine were measured by means of spectrophotometer (total phenols, total flavanols, antiradical activity, anthocyanin content). The content of 22 individual phenolic compounds in grape berries (gallic, caftaric, coutaric and fertaric acids; trans-resveratrol, trans-piceid, cis-piceid, trans-piceatannol and trans-astringin; rutin, quercetin-3-β-D-glucoside, quercetin, quercetin, kaempferol and myricetin; catechin, epicatechin; delphinidin-3-glucoside, cyanidin-3-glucoside, petunidin-3-glucoside, peonidin-3-glucoside, malvidin-3-glucoside) was measured by means of HPLC. The methods were developed in the laboratory of Mendel University, department of viticulture and enology, Lednice [14].

### Statistics

Data were analyzed using STATISTICA software. Means and standard deviations were evaluated using ANOVA with subsequent Tukey's test at P>0.95 significance level. The mean-centered and scaled data were subjected to PCA and hierarchical cluster analysis.

## Results and discussion

Fig. 1 shows the average yield and S/A ratio of studied rootstock*cultivar combinations. The average values of total phenols, total flavanols, antiradical activity and anthocyanin content in berries are shown in Fig. 2. Though the significant differences between the majority of studied indexes and parameters were established, the influence of year was found to be more prominent when compared to the influence of the selected factor (rootstocks).

2010 was the year when the temperature during maturation was lowest, while the rainfall was higher than usual, which probably led to higher pathogen pressure. The eruption of the Eyjafjallajökull volcano in Iceland in 2010 probably led to those climatic changes. Higher TA of grape juice and wine along with lower sugar content and higher malic acid content in wines were observed in 2010. It is known that resistant grape varieties tend to produce higher amounts of phytoalexins when compared to sensitive varieties [10]. That situation was observed in grape berries of studied varieties. In particular, the content of phenolic acids, stilbenes and flavanols in grape berries was significantly higher. Content of rutin decreased in 2010, which was probably due to the decreased number of sunny days during maturation. It was found that the ratio of rutin and quercetin-3-β-D-glucoside changed through the years, and in 2010 the proportion of quercetin-3-β-D-glucoside increased while that of rutin decreased in studied varieties up to 10 times. It seems that this ratio correlates with disease resistance, as it correlated with the rate of grey rot (Botrytis cinerea) infection of berries. However, further investigation is needed to confirm that hypothesis. A decrease in selected spectrophotometric indexes in grape berries of red varieties was observed in 2010 (e.g. TP of Laurot grape juice on Börner was 6739.6 mg kg⁻¹, 19% lower than in 2009), as well as an increase in the proportion of delphinidin-3-glucoside and a decrease in the proportion of malvidin-3-glucoside in the anthocyanin profile of red varieties, which probably explain the color of red wines. Thus, the decrease of malvidin-3-glucoside in the anthocyanin profile could be an indicator of stressful growing conditions. However, further investigation is needed here.
<figure><img src="image_40.png" /><figcaption>Fig. 1 - Average yield (kg m⁻²) and S/A ratio (°NM / g l⁻¹ in tartaric acid).</figcaption></figure>

<figure><img src="image_41.png" /><figcaption>Fig. 2 - Average values of total phenols (TP), total flavanols (TF), antiradical activity (AA) and anthocyanin content (Ant) in berries (g kg⁻¹ GAE).</figcaption></figure>

In 2011 the temperature during maturation was higher, while the rainfall was lower and the number of sunny days was higher than usual, which was probably the reason of the decreased content of malic acid in wines. It is known that flavonol synthesis is light induced, and that flavonols play one of the major roles in protection from UV radiation [15]. Our results showed that rutin content in grape berries had significantly increased.

The whole dataset covering all rootstocks was subjected to PCA to verify correlations between different biological replicates and to identify the main sources of metabolic variations for the different rootstock genotypes tested. The first two PC explained 61.35% of overall variation. The first PC is strongly correlated with caftaric acid (0.885), coutaric acid (0.940), fertaric acid (-0.813), rutin (0.809), quercetin-3-β-D-glucoside (0.938), quercetin (0.849), petunidin-3-glucoside (0.931), sugar content in must (0.902), alcohol in wine (0.800) and malic acid in wine (0.801), and explains 40.95% of the total variance, while gallic acid (-0.856), epicatechin (-0.776), anthocyanins in berries (-0.751), pH of must (-0.767) and TA of wine (0.784) contribute more to the second principal component, which explains 20.4% of the total variance. In Fig. 3, the rootstocks are plotted on the plane defined by the two PC. Rootstock T5C is plotted separately probably due to the fact that it was used only for the Laurot variety, whereas the other two groups were formed by rootstocks of different origin. The variation is probably caused by the indirect effect of rootstock vigor on secondary metabolites.
<figure><img src="image_42.png" /><figcaption>Fig. 3 - PCA.</figcaption></figure>

When analyzing the rootstock*year variance, the first PC explained 54.8% of overall variation. The first PC is strongly correlated with *trans*-resveratrol (-0.946), *trans*-piceatannol (-0.839), delphinidin-3-glucoside (-0.853), TF in berries (-0.783), TP in wine (0.780), anthocyanins in wine (0.848), sugar content (0.848), must TA (-0.949), alcohol (0.882), pH in wine (0.762), and malic acid in wine (0.929), and explains 34.2% of the total variance, while *trans*-piceid (0.963), *cis*-piceid (0.842), rutin (0.618), quercetin (-0.705), peonidin-3-glucoside (0.672), malvidin-3-glucoside (0.745), antiradical activity in wine (-0.880) and pH of must (0.918) contribute more to the second PC, which explains 20.6% of the total variance. The rootstock*year combinations are plotted on the plane defined by the two PC. The combinations of the “good years” (2009 and 2011) appear on the right side of the plane, grouped by the year of harvest, while the combinations of the “bad year” (2010) are plotted on the left side of the plane. The second PC mainly differentiates between two good harvests (2009 and 2011).

Fig. 4 shows the dendrogram obtained after the application of cluster analysis to the 38 parameters analyzed in the three years for 8 rootstocks and 2 cultivars (STATISTICA program). This analysis was used to classify the individual rootstocks into groups showing similar properties; the contents of studied parameters were used as variables. The dendrogram shows the classification of rootstocks on two main groups based on the scion. Each of cultivar*rootstock interaction has its own particularities, but it is interesting to note that control rootstock SO4 stands apart in both groups. The main distinction between the studied cultivars seems to be due to the differences in anthocyanin profiles (Fig. 5), whereas the distinction between rootstocks is less obvious but could also be due to the differences in vigor.

<figure><img src="image_43.png" /><figcaption>Fig. 4 - Cluster analysis.</figcaption></figure>
<figure><img src="image_44.png" /><figcaption>Fig. 5 - Anthocyanin profile of studied varieties.</figcaption></figure>

Some of the studied rootstocks showed similarities in phenolic compound accumulation for both studied cultivars:

- SO4 has higher concentration of anthocyanins in wine and higher concentration of gallic acid in grapes

- 8B tends to have higher concentration of anthocyanins in wine

- 125AA tends to have lower concentration of catechin in grapes

- 1103 Paulsen tends to have lower concentrations of studied flavanols in grapes

- CR2 have higher organoleptic evaluation of wines and higher antiradical activity of must

- Börner tends to have higher content of rutin, quercetin-3-β-D-glucoside and catechin in grapes. It was also noticed that rootstock Börner had higher content of most of the studied phenolic compounds in grapes of Laurot cultivar, suggesting that rootstocks other than V. berlandieri x V. riparia, V. berlandieri x V. rupestris crosses (e.g. V. cinerea, V. cordifolia etc.) could have a positive effect on the accumulation of phenolic compounds. Although further investigation is needed, similar results could be observed in other studies [12, 16].

## Conclusion

The field performance of two new resistant red wine cultivars (Laurot and Nativa) was evaluated on eight rootstocks in the South Moravia region, Czech Republic for three years. For the most part the variation of studied parameters (agrobiological, must and wine chemical analysis, content of chosen phenolic compounds) was dominated by scion cultivar and climatic variation among years. Nevertheless, PCA highlighted the main source of metabolic variation: the origin of the rootstock. As a result, the most suitable rootstocks for Laurot and Nativa cultivars in given conditions were: CR2 and SO4 based on studied parameters and sensory wine evaluation. Rootstock 1103 Paulsen had lower content of studied phenolic compounds in both cultivars, which was probably due to its higher vigor in given conditions. Interestingly, Börner rootstock on the Laurot cultivar had higher concentrations of most of the studied phenolic compounds, although those results were not confirmed on cultivar Nativa. Both cultivars had higher concentrations of most of the studied phenolic compounds when compared with Lemberger cultivar. Studied cultivars do not contain anthocyanin diglucosides. The anthocyanin profile of Nativa is closer to the V. vinifera profile when compared to Laurot. Further research is needed in order to understand the scion-rootstock interaction and its influence on phenolic content in berries and other parts of vine plant, along with its possible effect on the incidence of main fungal and bacterial diseases, and positive effect of final products (wine, juices, concentrates) on human health.

## Abbreviations

TP, total phenols; TF, total flavanols; AA, antiradical activity; Ant, anthocyanins; S/A ratio, sugar content to total acidity ratio; PCA, principal component analysis; TA, total acidity.

## References

1. Michlovský M (2004) Разработка научно-прикладных основ селекции винограда на устойчивость и система биологического виноградарства в чешской республике. Doctor of Science thesis, Timiryazev Academy in Moscow.
2. Creasy GL, Creasy LL (2009) *Grapes*. Crop production science in horticulture, CABI.

3. Soar CJ, Dry PR, Loveys BR (2006) Scion photosynthesis and leaf gas exchange in *Vitis vinifera* L. cv. Shiraz: mediation of rootstock effects via xylem sap. *Aust J Grape Wine Res* **12**: 82-96.

4. Whiting R (2004) *Grapevine rootstocks*. Ashford.

5. Koundouras S, Tsialtas IT, Zioziou E et al (2008) Rootstock effects on the adaptive strategies of grapevine (*Vitis vinifera* L. cv. Cabernet-Sauvignon) under contrasting water status: leaf physiological and structural responses. *Agric Ecosyst Environ* **128**: 86-96.

6. Stevens RM, Pech JM, Gibberd MR et al (2010) Reduced irrigation and rootstock effects on vegetative growth, yield and its components, and leaf physiological responses of Shiraz. *Aust J Grape Wine Res* **16**: 413-425.

7. Tandonnet JP, Cookson SJ, Vivin P et al (2010) Scion genotype controls biomass allocation and root development in grafted grapevine. *Aust J Grape Wine Res* **16**: 290-300.

8. Keller M, Mills LJ, Harbertson JF (2012) Rootstock effects on deficit-irrigated winegrapes in a dry climate: vigor, yield formation, and fruit ripening. *Am J Enol Vitic* **63**: 29-39.

9. Berdeja M, Hilbert G, Dai ZW et al (2014) Effect of water stress and rootstock genotype on Pinot noir berry composition. *Aust J Grape Wine Res* **20**: 409-421.

10. Roubelakis-Angelakis K (2009) *Grapevine molecular physiology and biotechnology*, 2nd edition. Springer.

11. Khafizova A (2012) The study of individual phenolic compounds with antioxidant properties in grape berries and wine produced from new interspecific varieties under the conditions of South Moravia, Czech Republic. *PhD thesis*, Mendel University in Brno.

12. O.I.V. (1990) *Recueil des méthodes internationales d'analyse des vins*. Office international de la vigne et du vin, Paris.

13. Ludvikova I (2009) *Metodika UKZUS pro zkoušky užitně hodnoty odrůd*, UKZUS.

14. Baroň M, Kumšta M (2012) Comparison of north Italian and south Moravian wines on the base of their antioxidant activity, phenolic composition and sensory quality. *Acta Univ Agric Silvic Mendel Brun* **60**: 9-18.

15. Cortell JM, Kennedy JA (2006) Effect of shading on accumulation of flavonoid compounds in (*Vitis vinifera* L.) Pinot noir fruit and extraction in a model system. *J Agric Food Chem* **54**: 8510-8520.

16. Scienza A, Failla O, Espen L (2014) *Progetto Ager-serres. Strategie innovative per la seleyione di Noovi portainnesti di vite*. Edizioni l'informatore agrario.
# Influence de la botrytisation dans la genèse des composés associés à des nuances typiques de l'arôme des vins liquoreux de pourriture noble

P. STAMATOPOULOS<fnref n="1" />,<fnref n="2" />*, C. THIBON<fnref n="1" />,<fnref n="2" />, P. REDON<fnref n="1" />,<fnref n="2" />, P. DARRIET<fnref n="1" />,<fnref n="2" />

*Botrytis cinerea* – vins liquoreux – lactones – précurseurs S-conjugués – arôme

## Introduction

Des travaux récents ont établi le rôle de certaines lactones et du 3-sulfanylhexan-1-ol (3SH) dans l'expression aromatique de fruits confits des vins liquoreux de pourriture noble [1, 2]. *B. cinerea* accélère le phénomène de passerillage et il modifie aussi la composition des baies en produisant à la fois des composés odorants, dont les lactones et en induisant une augmentation de précurseurs d'arômes de nuances zestées, comme les précurseurs cystéinylés et glutathionylés [3-5]. Ces composés étant en partie formés au cours de la botrytisation des raisins, une étude a été réalisée dans le vignoble du Sauternais avec pour objectif de préciser les modalités de leur biogenèse en fonction du stade de développement de la pourriture noble. Complétant les travaux de Sarrazin [3], le but de ce travail est de considérer aussi la confrontation de la surmaturation sur deux types de sol et deux millésimes différents. Ainsi l'étude a été menée, avec le cépage Sémillon (clone 315, porte greffe 101-14 Millardet, Grasset), au cours de deux millésimes (2012, 2014), à 4 stades de maturité et surmaturité des raisins (raisins sains à maturité, stade pourri plein, stade pourri rôti, stade pourri rôti + 15jours) en considérant deux parcelles d'un cru classé de Sauternes présentant des caractéristiques pédologiques différentes.

## Matériel et méthodes

### Prélèvement des échantillons

Les baies ont été ramassées sur les parties hautes, moyennes, basses, ensoleillées et ombragées des grappes. Les prélèvements ont été réalisés à quatre stades de développement de *B. cinerea* : 1) Stade sain : baies à maturité non atteintes par botrytisation. 2) Stade pourri plein : baies dont la surface a entièrement été colonisée par *B. cinerea*. Les baies prennent une couleur brun-chocolat mais ne sont pas encore concentrées. 3) Stade pourri rôti : baies entièrement colonisées par *B. cinerea* et déshydratées. Du fait de la dessiccation, les baies sont très riches en sucres, ce qui augmente la pression osmotique à l'intérieur de celles-ci et empêche le champignon de poursuivre son développement. 4) Stade pourri vieux : baies marquées au stade pourri rôti et ramassées 15 jours après. Les prélèvements ont été effectués à deux millésimes différents (2012, 2014) et dans deux types des sols différents (parcelle 44.2 : Calcosol ; parcelle 51 : Peyrosol).

### Extraction et quantification des lactones dans le moût

Un volume de 100 mL de moût est supplémenté avec 100 µL de 3-octanol et de 2-octanol en solution hydroalcoolique (1/1, V/V) à 10 mg/L. Puis les composés organiques sont extraits par le dichlorométhane (8,8 et 5 mL) sous agitation magnétique à 600 r.p.m. pendant 10 minutes. Les phases organiques sont récupérées et rassemblées pour être séchées sur Na₂SO₄ anhydre, puis concentrées sous flux d'azote inerte, jusqu'à un volume de 500 µL. L'analyse des extraits est réalisée par la chromatographie en phase gazeuse couplée avec la spectrométrie de masse. La chromatographie est réalisée sur colonne capillaire en silice fondue, avec une phase stationnaire polaire de type carbowax 20M (BP20, 50m-0,22mm-0,25µm, SGE, Australie).

<footnote n="1">¹Univ. de Bordeaux, ISVV, EA4577 Œnologie, F-33140 Villenave d'Ornon, France</footnote>

<footnote n="2">²INRA, ISVV, USC 1366 Œnologie, F-33140 Villenave d'Ornon, France</footnote>

<footnote>*Auteur principal : panagiotis.stamatopoulos@u-bordeaux.fr</footnote>
## Quantification des précurseurs du 3SH dans le moût

Les précurseurs cystéinylés et glutathionylés du 3SH ont été quantifiés par une adaptation de la méthode de Capone et al. [6]. Brièvement, le dosage de l'ensemble des précurseurs d'arômes du 3SH nécessite une purification de l'échantillon par SPE, associé à un système de vide (Vac Elut 20 Manifold, Varian). L'élution des composés d'intérêt est réalisée avec 3 mL de méthanol/eau 30/70 (V/V) à 1 mL/min. Les échantillons sont ensuite évaporés à sec au Rapidvap (Labconco, France). Enfin l'extrait concentré a été injecté à un système UPLC-FTMS.

## Résultats et discussion

Les résultats de quantification des lactones dans les moûts à différents stades de botrytisation montrent des teneurs variables selon le composé, le stade de botrytisation, la parcelle étudiée et le millésime étudié. Pour les γ-octalactone et γ-décalactone, des teneurs très faibles sont mesurées quelque soit la parcelle ou le stade de botrytisation (Figures 1 & 2).

<figure><img src="image_45.png" /><figcaption>**Fig. 1** - Evolution des teneurs en lactones saturées dans les jus de raisins des deux parcelles en fonction du stade de botrytisation (millésime 2012).</figcaption></figure>

<figure><img src="image_46.png" /><figcaption>**Fig. 2** - Evolution des teneurs en lactones saturées dans les jus de raisins des deux parcelles en fonction du stade de botrytisation (millésime 2014).</figcaption></figure>

Les γ-nonalactone et δ-décalactone présentent, quant-à-elles, des valeurs plus élevées. D'abord, une augmentation est notée selon le stade de botrytisation, puis, une différence marquante est observée dans les teneurs en γ-nonalactone entre les deux parcelles. La parcelle 51 présente des concentrations plus élevées en γ-nonalactone par rapport à la parcelle 44.2, tandis que pour la δ-décalactone une tendance inverse est notée. Par ailleurs, selon le millésime une différence dans le niveau de concentration de ces lactones est observée, les teneurs des lactones étant plus élevées pour le millésime 2012.
L'étude a aussi permis de relever des informations importantes concernant les concentrations en 2-nonen-4-olide et en massoia lactone, deux lactones présentant la particularité de posséder une double liaison sur leur hétérocycle. Ainsi, les résultats de quantifications dans les moûts ont montré une évolution différente des teneurs de ces lactones au cours de la botrytisation par rapport à la γ-nonalactone et la δ-décalactone. En effet, ces dernières présentent des valeurs plus importantes au stade « pourri vieux », alors que la massoia lactone et le 2-nonen-4-olide ont toujours leur pic d'accumulation au stade « pourri rôti », qui est le stade le plus qualitatif pour l'élaboration des vins liquoreux de pourriture noble (Figures 3 & 4). Notons que la même tendance dans les teneurs de lactones insaturées est observée pour les deux millésimes. La différence d'évolution de concentrations entre le 2-nonen-4-olide et la massoia lactone, la γ-nonalactone et la δ-décalactone respectivement, pourrait être due à un processus de limitation de biosynthèse de lactones insaturées avec l'évolution du stade du développement de la pourriture noble. Ainsi, nous formulons l'hypothèse que la massoia lactone et le 2-nonen-4-olide puissent être considérés comme marqueurs moléculaires de la qualité de la pourriture noble due à B. cinerea.

<figure><img src="image_47.png" /><figcaption>Fig. 3 - Evolution des teneurs en lactones insaturées dans les jus de raisins des deux parcelles en fonction du stade de botrytisation (millésime 2012).</figcaption></figure>

<figure><img src="image_48.png" /><figcaption>Fig. 4 - Evolution des teneurs en lactones insaturées dans les jus de raisins des deux parcelles en fonction du stade de botrytisation (millésime 2014).</figcaption></figure>

Concernant les expériences de quantification des précurseurs du 3-sulfanylhexan-1-ol, les résultats ont aussi montré des différences selon le millésime, le stade de botrytisation et la parcelle (Figures 5 & 6). D'abord, en fonction du stade du développement de la pourriture noble, une augmentation de la teneur en précurseurs est observée associé à l'impact de *B. cinerea*. Cet effet a déjà été étudié par Thibon et al. [4, 5]. Aussi, s'agissant du millésime, les teneurs en précurseurs sont plus élevées au cours du millésime 2014 par rapport au millésime 2012. Enfin, comme pour les lactones, selon la nature du sol, les teneurs des précurseurs sont différentes avec dans le cas présent, des teneurs plus élevées pour la parcelle 51 (peyrosol).
<figure><img src="image_49.png" /><figcaption>**Fig. 5** - Evolution des teneurs en précurseurs cystéinyles du 3SH dans les jus de raisins des deux parcelles en fonction du stade de botrytisation</figcaption></figure>

<figure><img src="image_50.png" /><figcaption>**Fig. 6** - Evolution des teneurs en précurseurs glutathionylés du 3SH dans les jus de raisins des deux parcelles en fonction du stade de botrytisation.</figcaption></figure>

## Conclusion

En accord avec les travaux par Miklósy & Kerényi [7] et Sarrazin [3], ces travaux ont permis de confirmer le rôle majeur de la botrytisation, avec des fluctuations selon le millésime, sur l'évolution des concentrations dans le raisin en composés d'impact organoleptique ou en leur précurseurs (lactones, précurseurs du 3SH). En particulier, nos observations montrent une évolution qui n'est pas similaire selon la structure moléculaire des lactones, des lactones insaturées voyant leur concentration diminuer au dernier stade de botrytisation (pourri rôti + 15jours). Alors que les concentrations en γ-nonalactone continuent d'augmenter au cours du dernier stade (pourri rôti + 15jours), les teneurs en 2-nonen-4-olide et en massoia lactone, lactones insaturées, atteignent leur maximum au stade pourri rôti. En outre, ces travaux révèlent des niveaux et modalités d'accumulation contrastés pour un matériel végétal identique (Sémillon clone 315, greffé sur porte-greffe 101-14) et planté dans les 2 cas il y a plus d'une trentaine d'année, en fonction du sol viticole. Ils contribuent par une approche scientifique à démontrer un effet *terroir* bien connu empiriquement des praticiens et à l'origine de la grande palette aromatique des vins liquoreux de pourriture noble.

## Remerciements

Nous tenons à remercier Madame Sandrine Garbay et Monsieur Francis Mayer, les étudiants Maude Tinot et Jordan Vignaud ainsi que le Conseil Régional d'Aquitaine, le CIVB, France Agrimer et le Château d'Yquem pour leur soutien financier.
## Abréviations

S, stade sain ; pp, pourri plein ; pr, pourri rôti ; pv, pourri vieux ; 3SH, 3-sulfanylhexan-1-ol.

## Références

1. Stamatopoulos P, Frérot E, Tempère S et al (2014) Identification of a new lactone contributing to overripe orange aroma in Bordeaux dessert wines via perceptual interaction phenomena. *J Agric Food Chem* **62**: 2469-2478.

2. Stamatopoulos P, Tempère S, Darriet P (2014) Perceptive interactions on Bordeaux dessert wines fruity aroma. *In Proceedings of the XIV Weurman Flavor Research Symposium*, AJ Taylor & DS Mottram (eds).

3. Sarrazin E (2007) Recherches sur l'arôme des vins liquoreux de pourriture noble issus des cépages Sémillon et Sauvignon blanc. *Thèse de Doctorat*, Université Victor Segalen Bordeaux 2.

4. Thibon C, Dubourdieu D, Darriet P et al (2009) Impact of noble rot on the aroma precursor of 3-sulfanylhexanol content in *Vitis vinifera* L. cv Sauvignon blanc and Semillon grape juice. *Food Chem* **114**: 1359-1364.

5. Thibon C, Cluzet S, Mérillon JM et al (2011) 3-sulfanylhexanol precursor biogenesis in grapevine cells: the stimulating effect of *Botrytis cinerea*. *J Agric Food Chem* **59**: 1344-1351.

6. Capone DL, Sefton MA, Hayasaka Y et al (2010) Analysis of precursors to wine odorant 3-mercaptohexan-1-ol using HPLC-MS/MS: resolution and quantitation of diastereomers of 3-*S*-cysteinylhexan-1-ol and 3-*S*-glutathionylhexan-1-ol. *J Agric Food Chem* **58**: 1390-1395.

7. Miklósy E, Kerényi Z (2004) Comparison of the volatile aroma components in noble rotted grape berries from two different locations of the Tokaj wine district in Hungary. *Anal Chim Acta* **513**: 177-181.
# Phenotyping berries from the grapevine
## *Vitis vinifera* L. by means of Fourier Transform
## Infrared Spectroscopy

A. DESTRAC IRVINE*, C. RENAUD, E. MORIN, L. DURAND, S. DELROT, C. VAN LEEUWEN

UMR EGFV, INRA, Bordeaux Sciences Agro, ISVV, 210 Chemin de Leysotte,
33883 Villenave d'Ornon, France

Grape berries – phenotyping – analyses – FTIR – calibration

## Introduction

Grape berry composition has been a centre of interest ever since Louis Pasteur in the middle of the XIXth century. Viticulturists need this information to assess the impact of environmental factors and management practices. Enologists and winemakers need to know berry composition to guide their winemaking practices. In viticultural research, recent complex experimental set-ups which investigate the genotype*environment relationship yield an increasing number of samples of grape berries which then must be analyzed. These analyses are generally performed on the grape juice obtained by pressing or squeezing the berries. Grape juice is a complex solution, containing primary (sugars, organic acids) and secondary metabolites (aroma precursors, phenolic compounds) as well as cations (potassium). Specific analysis methods have been developed for each particular compound. Protocols for reference methods are accessible through the web site of the International Organization of Vine and Wine [1]. Some of these compounds are easily accessible, like Total Soluble Solids or Brix. Others are not, like tartrate, malate or potassium. When a large number of samples of grape berries must be characterized, implementing specific methods for each compound is constraining and often time consuming. Multiparameter approaches allowing the determination of several parameters in a single analysis exist. They can also reduce dramatically the time and cost of analyses. Among different multiparameter approaches, Fourier Transform Infrared Spectroscopy (FTIR) is widely used in food science in general and in enology in particular [2]. This method is a spectroscopic method that uses the mid intra-red of the electromagnetic spectrum (from about 2500 to 10000 nm) and is based on the absorption related to the analyzed matrix. An FTIR spectrometer simultaneously collects high spectral resolution data over a wide spectral range. A complex data set is acquired which needs calibration with multivariate statistical analyses (Multiple Linear Regression, Partial Least Square) against reference analyses. It has the advantage that no other sample preparation is needed other than a careful filtration or centrifugation of the grape juice [3]. Hence, it can be considered as an accurate, reliable, rapid, non-destructive, and inexpensive way of analysing samples of grape juice. However, an important question raised in FTIR analyses is whether the calibration is universal or whether a specific calibration is needed for each sub-set of samples (per vintage, per grapevine variety, per maturity level; [4]). This question was investigated in this study through a trial where the grape juices of 52 grapevine varieties were analyzed from veraison to harvest over successive years. Values for Brix, total acidity (TA), tartrate, malate, pH and Yeast Assimilable Nitrogen (YAN) were compared with reference analyses.

## Materials and methods

*Mode and frequency of sampling*

The berries from the 52 different grape varieties were collected weekly from mid-veraison (phenological stage BBCH 85) to harvest. The samples were taken in an experimental plot (INRA campus of Villenave d'Ornon, France) with 5 blocks (replicates), designed for statistical analysis of the obtained data for each variety (eliminating intra plot variability). The 5 replicates for each variety were composed of 10 vines on which each sample was collected. Depending on the variety and berry size, each sample contained 50 to 75 berries.
## Juice extraction

The berry samples were counted and weighed in the laboratory to determine berry weight. The juice was extracted by pressing the berries between two metal blades (Bagmixer 400W - Interscience, France) and then filtered (Lateral BagFilter - Interscience, France) before being centrifuged at 20°C for 10 minutes at 10,000 rpm. The supernatant recovered (minimum volume: 12 mL) was then analyzed.

## Reference analyses

For Brix determination, the juices were manually analyzed by an electronic refractometer (Digital Refractometer, Ningbo Gamry Optical Instrument Co., Ltd.). For the total acidity, the juices were diluted 1/4 or 1/8 depending on the stage of maturity and analyzed by titration with sodium hydroxide using an automatic titrator (Cog étude, France). For malate and tartarate, juices were analyzed on a continuous flow analyzer (800 trAAcs BRAN-LUBBE). Malate was analyzed by enzymatic assay (adaptation of the method OIV-MA-AS313-12A) and tartrate by colorimetric assay (OIV-OENO 391-2010 FR). YAN was evaluated by formol titration (Sørensen formol titration).

## Procedure of FTIR analyzer

Once centrifuged, the grape juices (12 mL) were analyzed using a WineScan™ Auto analyzer (FOSS FRANCE, 92000 Nanterre) according to the method "Must" provided and calibrated by the manufacturer. Each sample was analyzed twice through two successive determinations.

# Results and discussion

Brix values measured with FTIR are highly correlated to Brix measured with an electronic refractometer (Figure 1A, R² > 0.97). No vintage effect is observed. Correlation remains valid through a wide range of maturity levels, from 7 to 27°Brix. The equation y = 1.11x – 1.16 indicates that Brix levels measured with FTIR are slightly overestimated for low Brix levels and slightly underestimated for high Brix levels. When the data is plotted for a sub sample of 4 varieties (2 red and 2 white varieties, 3 vintages), no variety effect is graphically shown. This means that no variety-specific calibration is needed (Figure 1B).

<figure><img src="image_51.png" /></figure>

<figure><img src="image_52.png" /><figcaption>**Fig. 1** - Correlation between °Brix obtained by FTIR analysis and by electronic refractometer. A, data obtained from 52 grapevine varieties in three vintages. B, data obtained from Assyrtiko, Merlot, Rkatsiteli and Touriga nacional in three vintages.</figcaption></figure>

Total acidity values measured with FTIR are highly correlated to TA measured by titration (Figure 2A, R² > 0.98). No vintage effect is observed. Correlation remains valid through a wide range of maturity levels, from 2 to 22 g H₂SO₄/L. The equation y = 1.02x + 0.02 indicates that values measured with FTIR are very close to values measured by titration. When the data is plotted for a sub sample of 4 varieties (3 red and 1 white varieties, 2 vintages), no variety effect is graphically shown. This means that no variety-specific calibration is needed (Figure 2B).
<figure><img src="image_53.png" /><figcaption>**Fig. 2** - Correlation between Total Acidity (TA) obtained by FTIR analysis and by titration. A, data obtained from 52 grapevine varieties in two vintages. B, data obtained from Castets, Grenache, Sangiovese and Sémillon in two vintages.</figcaption></figure>

Malate values measured with FTIR are highly correlated to malate values measured with enzymatic analysis (Figure 3A, R² > 0.98). No vintage effect is observed. Correlation remains valid through a wide range of maturity levels, from 1 to 26 g/L. The equation y = 1.02x - 0.29 indicates that values measured with FTIR are very close to values measured by titration. When the data is plotted for a sub sample of 4 varieties (2 red and 2 white varieties, 2 vintages), no variety effect is graphically shown. This means that no variety-specific calibration is needed (Figure 3B).

<figure><img src="image_54.png" /><figcaption>**Fig. 3** - Correlation between malate obtained by FTIR analysis and by enzymatic analysis. A, data obtained from 52 grapevine varieties in three vintages. B, data obtained from Grenache, Petit Verdot, Rkatsiteli and Ugni blanc in two vintages.</figcaption></figure>

YAN values measured with FTIR are only moderately correlated to YAN values measured by formol titration (Figure 4, R² = 0.87). The equation y = 0.71x + 33.49 indicates that values measured with FTIR overestimate real values, particularly when YAN is high. Hence, only rough estimates of YAN can be obtained with the calibration provided by the FOSS equipment and specific calibration is needed when a greater precision is desired.

<figure><img src="image_55.png" /><figcaption>**Fig. 4** - Correlation between Yeast Available Nitrogen obtained by FTIR analysis and by formol titration. Data obtained from 52 grapevine varieties in 2012.</figcaption></figure>
Tartrate measured with FTIR is poorly correlated to tartrate measured by colorimetric assay (Figures 5A and 5B, R² = 0.71 in 2011 and 0.87 in 2012). The equation is very different in 2011 (y = 0.96x + 0.09) compared to 2012 (y = 1.23x - 0.47). This means that in 2011 the estimation of tartrate by FTIR was not very precise and that in 2012 values measured by FTIR were largely underestimated. Specific calibration needs to be carried out for tartrate and this calibration seems to be vintage specific.

<figure><img src="image_56.png" /><figcaption>**Fig. 5** - Correlation between tartrate obtained by FTIR analysis and by colorimetric assay. Data obtained from 52 grapevine varieties in 2011 (A) and 2012 (B).</figcaption></figure>

## Conclusion

For Brix, TA and malate, calibration curves provided by the FOSS company were very accurate and remained valid through the complete range of varieties, vintages and maturity levels. This was not, however, the case for tartrate and YAN. For these parameters, only a rough estimation was obtained by FTIR technology with calibration provided by the FOSS Company. Specific calibration is necessary for these parameters and this calibration is vintage specific.

## Acknowledgements

We would like to thank our partners who participated in this project. We thank T. Flutre for his advice on data processing. This study has been carried out in the framework of the Cluster of Excellence COTE. It was financially supported by the Conseil Interprofessionnel du Vin de Bordeaux (CIVB) and the regional council of Aquitaine (Conseil Régional d'Aquitaine). The Unité Expérimentale Viticole Bordeaux (UEV Bordeaux INRA) participated in this research through the management of the experimental plot.

## References

1. OIV (2015) International Methods of Analyses of Wines and Musts (website consulted on 27 February 2015).

2. Dubernet M, Dubernet M (2000) Utilisation de l'analyse infrarouge à transformée de Fourier pour l'analyse œnologique de routine. *Rev Fr Œnol* **181**: 10-13.

3. Urbano-Cuadrado M, Luque de Castro M, Pérez-Juan P et al (2004) Near Infrared reflectance spectroscopy and multivariate analysis in enology: determination or screening of fifteen parameters in different types of wines. *Anal Chim Acta* **527**: 81-88.

4. Bouvier JC (2001) Réflexion sur l'analyse œnologique par spectrométrie infra-rouge. *Rev Fr Œnol* **191**: 17-18.
# Microscopical and biochemical approaches of modifications induced by pulsed electric field treatments on cell-wall total tannins and polysaccharides of Cabernet Sauvignon grape berry skins

C. CHOLET<fnref n="1" />,<fnref n="2" />*, C. DELSART<fnref n="1" />,<fnref n="2" />, M. PETREL<fnref n="3" />,<fnref n="4" />,<fnref n="5" />, E. GONTIER<fnref n="3" />,<fnref n="4" />,<fnref n="5" />, N. GRIMI<fnref n="6" />, R. GHIDOSSI<fnref n="1" />,<fnref n="2" />, E. VOROBIEV<fnref n="6" />, M. MIETON-PEUCHOT<fnref n="1" />,<fnref n="2" />, L. GENY<fnref n="1" />,<fnref n="2" />

Tannins – polysaccharides – pulsed electric field – Cabernet Sauvignon

## Introduction

Pulsed electric field (PEF) is an emerging technology in the winemaking industry recognized for its ability to enhance polyphenol extraction. This process is appealing since it is physical (no use of chemicals), athermal (no aroma degradation), fast and ecofriendly (low energy consumption). Nevertheless, the mechanism remains poorly understood and requests to be further studied.

The aim of this study was to investigate the effects of PEF treatment on grape-skin histo-cytological structures and on the organization of skin cell-wall polysaccharides and tannins, which, until now, have been moderately investigated.

## Materials and methods

### Pulsed electric field treatments

This study related the effects of two different pulsed electric field treatments on harvested berries:

- PEF1 of medium strength (4 kV/cm) and short duration (1 ms);

- PEF2 of low strength (0.7 kV/cm), with a longer duration (200 ms).

### Histo-cytological structures

Berry skins were observed by optical microscopy (MO), after chemical fixation, inclusion and P.A.S. coloration, or under transmission electronic microscopy (TEM) after chemical fixation, inclusion and contrast.

### Polysaccharides and tannins

Polysaccharides and tannins were quantified after extraction of cell-wall fraction and:

- extraction of polysaccharidic fractions of the cell-wall fraction and spectrophotometric analysis;

- extraction of tannins of the cell-wall fraction and analysis by reverse phase HPLC.

<footnote n="1">¹Université de Bordeaux, Institut des Sciences de la Vigne et du Vin, EA 4577, Unité de recherche œnologie, 210 Chemin de Leysotte, CS 50008, F-33882 Villenave d'Ornon, France</footnote>

<footnote n="2">²INRA, ISVV, USC 1366 Œnologie, 210 Chemin de Leysotte, CS 50008, F-33882 Villenave d'Ornon, France</footnote>

<footnote n="3">³Université de Bordeaux, Bordeaux Imaging Center, UMS 3420, F-33000 Bordeaux, France</footnote>

<footnote n="4">⁴CNRS, Bordeaux Imaging Center, UMS 3420, F-33000 Bordeaux, France</footnote>

<footnote n="5">⁵INSERM, Bordeaux Imaging Center, US 004, F-33000 Bordeaux, France</footnote>

<footnote n="6">⁶Sorbonne universités, Université de technologie de Compiègne, laboratoire Transformations Intégrées de la Matière Renouvelable (UTC/ESCOM, EA 4297 TIMR), Centre de recherche Royallieu, CS 60 319, F-60-203 Compiègne cedex, France</footnote>
## Statistical data treatment

All analyses were performed in triplicate. We thus performed non-parametric tests. The statistical significance of differences was determined by the Kruskal and Wallis test (α = 0.05). Experimental data detected as being significantly different were marked in the tables with different letters.

## Results and discussion

PEF1 (4 kV/cm; 1 ms; low energy (4 Wh/kg)) had measureable but relatively limited effect on the structure of phenolic compounds and the pectic fraction. After PEF1, the skin (S) of berries was distended (Fig. 1), with vacuolar polyphenols (VPC) which were less dispersed and more condensed (Fig. 1A vs 1B, 2A vs 2A', 3B vs 3B', Table 2). The organization of the pectic skeleton of skin cell-walls was slightly but measurably affected by further treatment (Table 1). Small spherical structures, which were localized only at the middle lamella level in the control batch (Fig. 4), were observed over a large portion of the hypodermis cell wall thickness.

<figure><img src="image_57.png" /><figcaption>Fig. 1 - Skin modifications under MO. A: Control berry; B: berry + PEF1; C: berry + PEF2.</figcaption></figure>

<table><caption>**Table 1** - Effects of PEF1 and PEF2 on the contents of external polysaccharide fractions (PSE, PSOX), and internal polysaccharide fractions (PSH, PSOH), in berry skins</caption><thead><tr><th></th><th colspan="3">Polysaccharide content<br>(mg/g of skin)</th></tr><tr><th></th><th>Control</th><th>PEF1</th><th>PEF2</th></tr></thead><tbody><tr><td>PSE fractions</td><td>8.80 ± 2.25 a*</td><td>9.71 ± 3.12 a*</td><td>3.88 ± 2.66 b*</td></tr><tr><td>PSOX fractions</td><td>1.32 ± 0.36 a*</td><td>1.57 ± 0.47 a*</td><td>2.54 ± 0.73 b*</td></tr><tr><td>PSH fractions</td><td>0.70 ± 0.07 a*</td><td>0.56 ± 0.07 b*</td><td>0.55 ± 0.16 c*</td></tr><tr><td>PSOH fractions</td><td>2.59 ± 0.50 a*</td><td>1.76 ± 0.74 a*</td><td>1.55 ± 0.63 b*</td></tr></tbody></table>

Values are means ± standard deviations.

(*): Significant difference in Kruskal Wallis test (α = 0.05)

<figure><img src="image_58.png" /><figcaption>Fig. 2 - Vacuolar polyphenols (VPC) of outer hypodermis, under TEM. A: Control berry; A': berry + PEF1; A*: berry + PEF2.</figcaption></figure>

This study demonstrated a strengthening of the phenolic skeleton of skin cell-walls, which has a protective effect, slowing down polyphenol extraction phenomena [1, 2].

PEF2 (0.7 kV/cm; 200 ms; high energy (31 Wh/kg)) profoundly modified the organization of skin cell-walls. Skin was degraded, especially in the deepest layers of the inner hypodermis, with vacuolar polyphenols of the outer cell layers appearing denser and contrasted, and unstructured organelles (Fig. 1A vs 1C, Fig. 2A vs 2A*, Fig. 3A vs 3A*). The tannic skeleton was highly disorganized (Table 2, Fig. 1A vs
1C, Fig. 3A vs 3A*). All pectic organization of cell-walls was significantly affected (Table 1). The middle lamella of cell-walls was unstructured (Fig. 3A vs 3A*, arrowed), with the presence of small spherical structures throughout the whole thickness of the cell-walls (Fig. 4A vs 4A*). After PEF2, the pectic and phenolic skeletons were largely disorganized, facilitating polyphenol extraction [1, 2].

<table><caption>**Table 2** - Effects of PEF1 and PEF2 on the total tannins and mDP of the PS E, PS OX, PS H, PS OH and RP polysaccharide fractions, in berry skins</caption><thead><tr><th colspan="2">Tannins of polysaccharide fractions</th><th>Control</th><th>PEF1</th><th>PEF2</th></tr></thead><tbody><tr><td>T PSE</td><td>total tannins (mg/g of skin)</td><td>0.17 ± 0.11 a*</td><td>0.24 ± 0.17 ab*</td><td>0.42 ± 0.04 b*</td></tr><tr><td>T PSE</td><td>mDP</td><td>3.42 ± 0.88 a*</td><td>2.91 ± 0.49 a*</td><td>3.17 ± 2.78 a*</td></tr><tr><td>T PSOX</td><td>total tannins (mg/g of skin)</td><td>0.29 ± 0.08 a*</td><td>0.20 ± 0.03 a*</td><td>0.14 ± 0.05 b*</td></tr><tr><td>T PSOX</td><td>mDP</td><td>2.43 ± 0.50 a*</td><td>3.26 ± 0.72 a*</td><td>2.79 ± 1.13 a*</td></tr><tr><td>T PSH</td><td>total tannins (mg/g of skin)</td><td>2.81 ± 0.83 a*</td><td>1.13 ± 1.36 a*</td><td>2.17 ± 1.59 a*</td></tr><tr><td>T PSH</td><td>mDP</td><td>15.83 ± 5.07 a*</td><td>58.03 ± 68.84 a*</td><td>13.84 ± 1.22 a*</td></tr><tr><td>TPS OH</td><td>total tannins (mg/g of skin)</td><td>2.57 ± 1.85 a*</td><td>5.19 ± 5.49 a*</td><td>9.29 ± 8.03 b*</td></tr><tr><td>T PSOH</td><td>mDP</td><td>3.59 ± 3.75 a*</td><td>1.63 ± 0.25 a*</td><td>1.64 ± 0.13 a*</td></tr><tr><td>T RP</td><td>total tannins (mg/g of skin)</td><td>0.75 ± 0.15 a*</td><td>0.66 ± 0.64 a*</td><td>1.67 ± 0.87 a*</td></tr><tr><td>T RP</td><td>mDP</td><td>5.79 ± 2.11 a*</td><td>2.64 ± 0.32 a*</td><td>4.79 ± 1.99 a*</td></tr></tbody></table>

Values are means ± standard deviations. (*): Significant difference in Kruskal Wallis test (α = 0.05)

<figure><img src="image_59.png" /><figcaption>**Fig. 3** - Vacuolar polyphenols (VPC) of inner hypodermis, under TEM. B: Control berry; B': berry + PEF1; B*: berry + PEF2.</figcaption></figure>

<figure><img src="image_60.png" /><figcaption>**Fig. 4** - At the middle lamella level (ml) of the outer hypodermis: small spherical structures over a large portion of the hypodermis cell-wall thickness, under TEM. C: Control berry; C': berry + PEF1; C*: berry + PEF2.</figcaption></figure>

## Conclusion

Depending on the parameters of the PEF, cell-wall structure was differently impacted: PEF1 (high strength, short duration, and low energy) had little effect on the structure of phenolic compounds and pectic cell-walls of the skin, whereas PEF2 (higher strength, longer duration, and higher energy) profoundly modified the organization of skin cell-walls. Thus, the choice of treatment modality is of prime importance because this choice can modify the kinetics of polyphenol extraction and, thus, wine quality [1, 2].
**Acknowledgements**

This work was supported by the "Conseil Interprofessionnel des Vins de Bordeaux – 33000 Bordeaux", the "Agence de l'Environnement et de la Maîtrise de l'Energie" and "France Bio-Imaging".

**Abbreviations**

**Microscopy**= eE, external epidermis; oH, outer hypodermis; iH, inner hypodermis; S, skin; VPC, vacuolar phenolic compounds; CW, cell-wall; o, organelles; ml, middle lamella; p, plastid; m, mitochondria; MO, optical microscopy; TEM, transmission electronic microscopy.

**Polysaccharide biochemistry**= PSE, extracting polysaccharide fraction in water; PSOX, extracting polysaccharide fraction in oxalate; PSH, extracting polysaccharide fraction in acid; PSOH, extracting polysaccharide fraction in sodium hydroxide; RP, residual-pellet polysaccharide fractions.

**Tannin biochemistry**= TPSE, tannins of PSE; TSPOX, tannins of PSOX; TPSH, tannins of PSH; TPSOH, tannins of PSOH; TRP, tannins of RP; PEF1, treatment 1 of pulsed electric field; PEF2, treatment 2 of pulsed electric field; C, control berries; mDP, mean degree of polymerization.

**References**

1. Cholet C, Delsart C, Petrel M et al (2014) Structural and biochemical changes induced by pulsed electric field treatments on Cabernet sauvignon grape berry skins: impact on cell wall total tannins and polysaccharides. *J Agric Food Chem* **62**: 2925-2934.

2. Delsart C, Cholet C, Ghidossi R et al (2013) Effects of pulsed electric fields on Cabernet sauvignon grape berries and on the characteristics of wines. *Food Bioprocess Technol* **7**: 424-436.
# Can wine aromas be manipulated by nitrogen applications in the vineyard?

P. HELWI<fnref n="1" />,<fnref n="3" />, A. HABRAN<fnref n="1" />, S. GUILLAUMIE<fnref n="1" />, C. THIBON<fnref n="2" />, G. HILBERT<fnref n="1" />, C. RENAUD<fnref n="1" />, E. GOMES<fnref n="1" />*, P. DARRIET<fnref n="2" />, S. DELROT<fnref n="1" />, C. VAN LEEUWEN<fnref n="1" />,<fnref n="3" />

Wine aromas – soil – nitrogen content – terroir effect

## Introduction

In interaction with climate and genetic or human factors, the soil is a major component of the viticultural terroir. Nitrogen, an essential element that vines pick up from the soil, can be considered as a key contributor to the terroir effect [2, 8]. It has a strong impact on vine performance, grape composition and subsequently wine quality. In addition to its major effect on primary metabolites, nitrogen plays also a decisive role in the secondary metabolism, especially in the production of key compounds for berry and wine quality, like volatile thiols, i.e. 3-sulfanylhexan-1-ol (3SH), and methoxypyrazines, i.e. 3-isobutyl-2-methoxypyrazine (IBMP).

IBMP and 3SH contribute to wine flavor, particularly in the varietal aroma of Sauvignon blanc wines and other white and red varieties. IBMP, responsible for the green pepper aroma, is directly present in the grape berry [1, 5]. However, 3SH, characterized by the grapefruit flavor, is not present in grape berries but is released during fermentation by the action of yeast [10] from odorless precursors whose structure has been identified as being S-conjugates to glutathione or cysteine (Pgsh-3SH and Pcys-3SH) [11]. The biosynthetic pathways of these aromatic compounds are far from being completely elucidated

The present study, in which the nitrogen effect was decoupled from those of vigor and vine water status, investigates the effect of vine nitrogen status on IBMP, Pgsh-3SH and Pcys-3SH levels in berries and in musts, as well as on IBMP and 3SH content in wines.

## Materials and methods

### Location, vine material and experimental set up

This research was conducted in 2013 in a French vineyard (Château Couhins, Pessac-Léognan, Bordeaux). The study plot was planted with Sauvignon blanc vines. This plot was chosen because nitrogen status was low in the previous year (Yeast Assimilable Nitrogen (YAN) < 100 mg L⁻<fnref n="1" />). Two treatments were compared: control (C) without fertilization and Soil N100: 100 kg/ha of nitrogen applied to the soil in two applications. Each treatment was conducted with four randomized replicates of 10 vines each. Vines were irrigated during the whole season and vine water status was assessed several times by means of stem water potential measurements [3]. Similar cultivation practices were adopted during the grape-growing period. One hundred fresh berries were randomly sampled from each bloc at three different stages: bunch closure (veraison (v)-20 days), mid-ripening (v+28 days) and ripeness (v+35 days). All plant materials were frozen immediately in liquid nitrogen, ground and stored at -80°C until implementation of analysis. Analyses were also carried out on grape must at harvest.

### Nitrogen status

Vine nitrogen status was assessed by measuring YAN in grape juice at harvest [7]. YAN was analyzed with a WineScan (FOSS®) [4].

<footnote n="1">¹Bordeaux University, INRA, ISVV, UMR 1287 EGFV, 33882 Villenave d'Ornon, France</footnote>

<footnote n="2">²Bordeaux University, ISVV, USC Œnologie USC 1366, EA4577, 33882 Villenave d'Ornon, France</footnote>

<footnote n="3">³Bordeaux Sciences Agro, Bordeaux University, ISVV, UMR 1287 EGFV, 33882 Villenave d'Ornon, France</footnote>
### Vine vigor

Vine vigor was estimated by measuring primary and secondary leaf areas at shoot growth cessation as described by Mabrouk and Carbonneau [9].

### Extraction and quantification of IBMP and S-conjugate precursors of 3SH

In grape berries and musts, IBMP was extracted and quantified by the method described by Guillaumie *et al.* [6]. S-conjugate precursors of 3SH in berries and musts were purified on C18 columns and then analyzed by liquid chromatography coupled to a mass spectrometry [12].

### Statistical analysis

Statistical analyses were conducted using the statistical package of the R software (R Development Core team, 2010). All the data are expressed as the arithmetic average ± standard error (SE) from four biological replicates. Statistical significance was analyzed with Student's t test. A value of *p* value < 0.05 was considered to indicate statistical significance.

## Results and discussion

### Agronomic results: vine nitrogen status and vigor

Berry nitrogen status was assessed in order to check if the fertilization modified plant nitrogen status and if this mineral was correctly assimilated. Grape must nitrogen content was determined by measuring YAN content just prior to commercial harvest. YAN content was higher in fertilized vines and difference was highly significant between modalities (Table 1). Hence, this demonstrated that applied nitrogen was well assimilated.

Nitrogen supply could enhance vegetative growth referred as vine vigor and, in consequence, leaf areas. To limit an impact of nitrogen supply on vine vigor, the fertilization was fractionated into two doses for the soil N100 treatment and it was applied late in the season (at budbreak and at bloom). Neither primary leaf area nor secondary leaf area were different between the two treatments. Vine vigor was similar among treatments resulting in a comparable microclimate in the bunch zone for all modalities (Table 1). Hence, in the absence of water deficit and with no differences in microclimate in the bunch zone, any modification of aroma compounds in this study would result of a direct effect of nitrogen nutrition.

<table><caption>**Table 1** - Vine nitrogen status determined by YAN content (mg L⁻¹) and nitrogen effect on vigor determined by primary and secondary leaf areas (m²/vine) at shoot growth cessation</caption><thead><tr><th></th><th>Control</th><th>Soil N100</th></tr></thead><tbody><tr><td>Yeast Available Nitrogen (mg L<sup>-1</sup>)</td><td>114.7 <sup>a</sup></td><td>206.2 <sup>b</sup></td></tr><tr><td>Primary leaf area (m<sup>2</sup>/vine)</td><td>1.11 <sup>a</sup></td><td>1.18 <sup>a</sup></td></tr><tr><td>Secondary leaf area (m<sup>2</sup>/vine)</td><td>1.02 <sup>a</sup></td><td>1.30 <sup>a</sup></td></tr></tbody></table>

### Analytic results: Aroma compound contents in grape berries, musts and wines

IBMP levels were maximal at (v-20 days) and decreased dramatically throughout ripening (Figure 1). Level of IBMP was around 60 ng kg⁻¹ of fresh weight (FW) at the earliest point of analysis and decreased to around 20 ng kg⁻¹ FW at harvest (Figure 1A). Samples from fertilized and non-fertilized vines did not show significant differences in IBMP content (Figure 1A). In musts, IBMP content was close to the detection limit. Like in berries, nitrogen fertilization did not have any effect on the level of this methoxypyrazine (Figure 1B). Based on these results, it can be assumed that the postulate of a direct effect of nitrogen on IBMP synthesis cannot be retained.

In grape berries, Pgsh-3SH concentration increased during berry ripening and reached a peak at (v+35 days). It was related to vine nitrogen status. Pgsh-3SH level was higher in the soil N100 treatment compared to the control (Figure 1C). The concentration of Pcys-3SH was relatively low and stable in the subsequent developmental stages. Moreover, the content of this molecule was similar between the control and the soil N100 treatment, indicating that nitrogen fertilization did not influence Pcys-3SH content in Sauvignon blanc grape berries (Figure 1E).
<figure><img src="image_61.png" /><figcaption>**Fig. 1** - Effects of nitrogen supply on the amount of IBMP (ng kg⁻¹ of fresh weight), Pgsh-3SH and Pcys-3SH in grape berries (A, C and E) and in must (B, D and F). Each point is the mean of four replicates. Statistical significance was analyzed with Student's t test (*p* value < 0.05). Error bars indicate SE.</figcaption></figure>

In musts, the fertilization led to a significant increase in the concentration of Pgsh-3SH (Figure 1D). Level of Pgsh-3SH in the control was in the order of 91 µg L⁻¹ and it increased to 178 µg L⁻¹ in the soil N100 treatment. Level of Pcys-3SH was lower compared to Pgsh-3SH. Nitrogen did not affect Pcys-3SH level, and no significant difference was observed between the two treatments (Figure 1F). This observation seems to indicate that in response to nitrogen supply, 3SH could be synthetized from Pgsh-3SH, independently from Pcys-3SH.

Moreover, sensorial analysis of these wines by a jury of experts did not reveal any significant differences between the two modalities, showing that nitrogen supply did not affect any of these aroma compounds in this experience (data not shown).

## Conclusion

These results showed that higher berry nitrogen status did not influence IBMP content in berry and must. However, it stimulated the synthesis of the glutathionylated precursor of 3SH in berries and musts, while the concentration of the cysteinylated precursor was not affected.
Acknowledgements

The work was supported by the interprofessional council of Bordeaux wine (CIVB), FranceAgriMer and Bordeaux Sciences Agro. We are very grateful to Kleopatra Nikolaou, Manon Barron, Claude Bonnet, Warren Albertin, Bernard Douens and members of Château Couhins.

Abbreviations

FW, fresh weight; IBMP, 3-isobutyl-2-methoxypyrazine; SB, Sauvignon blanc; YAN, Yeast Available Nitrogen.

References

1. Bayonove C, Cordonnier R, Dubois P (1975) Study of an aromatic characteristic fraction of Cabernet sauvignon grape variety, identification of 2-methoxy-3-isobutyl-pyrazine. *CR Hebdo Séances Acad Sci Série D* **281**: 75-78.

2. Choné X, van Leeuwen C, Chéry P (2001) Terroir influence on water status and nitrogen status of non-irrigated Cabernet sauvignon (*Vitis vinifera*). Vegetative development, must and wine composition (example of a Medoc top estate vineyard, Saint Julien area, Bordeaux, 1997). *S Afr J Enol Vitic* **22**: 8-15.

3. Choné X, van Leeuwen C, Gaudillère JP (2001) Stem water potential is a sensitive indicator of grapevine water status. *Ann Bot* **87**: 477-483.

4. Destrac A, Flutre T, Renaud C et al (2015) The use of Fourier Transform Infrared Spectroscopy in phenotyping berries from the grapevine *Vitis vinifera* L. *In XIXth International Giesco Meeting, Pech Rouge - Montpellier, France*.

5. Ebeler SE, Thorngate JH (2009) Wine chemistry and flavor: looking into the crystal glass. *J Agric Food Chem* **57**: 8098-8108.

6. Guillaumie S, Ilg A, Réty S et al (2013) Genetic analysis of the biosynthesis of 2-methoxy-3-isobutylpyrazine, a major grape-derived aroma compound impacting wine quality. *Plant Physiol* **162**: 604-615.

7. Van Leeuwen C, Friant P, Soyer JP et al (2000) L'intérêt du dosage de l'azote total et de l'azote assimilable dans le moût comme indicateur de la nutrition azotée de la vigne. *J Int Sci Vigne Vin* **34**: 75-82.

8. Van Leeuwen C, Seguin G (2006) The concept of terroir in viticulture. *J Wine Res* **17**: 1-10.

9. Mabrouk H, Carbonneau A (1996) Une méthode simple de détermination de la surface foliaire de la vigne (*Vitis vinifera* L.). *Prog Agric Vitic* **113**: 392-398.

10. Murat ML, Tominaga T, Dubourdieu D (2001) Assessing the aromatic potential of Cabernet Sauvignon and Merlot musts used to produce rose wine by assaying the cysteinylated precursor of 3-mercaptohexan-1-ol. *J Agric Food Chem* **49**: 5412-5417.

11. Tominaga T, Peyrot des Gachons C, Dubourdieu D (1998) A new type of flavor precursors in *Vitis vinifera* L. cv. Sauvignon Blanc: S-cysteine conjugates. *J Agric Food Chem* **46**: 5215-5219.

12. Helwi P, Thibon C, Habran A et al (2015) Effect of vine nitrogen status, grapevine variety and rootstock on the levels of berry S-glutathionylated and S-cysteinylated precursors of 3-sulfanylhexan-1-ol. *J Int Sci Vigne Vin* **49**.
# Adaptation de méthodes d'immunomarquage aux pépins de raisin (Vitis vinifera L. cv. Cabernet Sauvignon)

A. LI-MALLET¹*, M. PETREL², E. GONTIER², C. CHOLET¹, A. RABOT¹, A. OSOWSKI¹, L. GENY¹

¹Université de Bordeaux, ISVV - EA 4577, Unité de Recherche Œnologie, F-33140 Villenave d'Ornon, France

²Université de Bordeaux, Bordeaux Imaging Center, UMS 3420 CNRS US4 INSERM CS 61292, 33076 Bordeaux, France

Pépins de raisin – high-pressure freezing – freeze-substitution – immunomarquage

## Introduction

La maturité phénolique des baies de raisin se caractérise en grande partie par la teneur et la qualité des tanins, synthétisés dans la baie au cours de son développement et accumulés dans les parties solides du raisin : la pellicule et les pépins. Ces tanins sont extraits durant la fermentation et la macération, et confèrent aux vins l'amertume et l'astRINGence, mais aussi le potentiel de garde. Deux enzymes clés : la leucoanthocyanidine réductase (LAR) et l'anthocyanidine réductase (ANR), impliquées directement dans la biosynthèse des tanins ont été caractérisées et localisées dans la pellicule des raisins [1-4]. En revanche, les techniques de fixation chimique (4% de paraformaldéhyde et 0,25% de glutaraldéhyde dans un tampon phosphate 0,1M, pH 7,2) et d'inclusion PLT (Progressive Low Temperature) utilisées pour la pellicule ne permettent pas de réaliser des coupes ultra-fines sur les pépins à cause de leur structure complexe. Ce travail a consisté donc à mettre au point les techniques alternatives de fixation HPF (High-Pressure Freezing) et d'inclusion FS (Freeze Substitution) aux pépins de raisins afin de localiser les deux enzymes par immunomarquage.

## Matériel et méthodes

### Matériel végétal

L'adaptation du protocole d'inclusion pour les études immunohistologiques a été effectuée sur les pépins de Cabernet Sauvignon issus des parcelles expérimentales de l'INRA de Bordeaux et aux différents stades prélevés en 2013. Pour chaque stade, deux grappillons de 10 baies ont été prélevés au hasard sur deux pieds différents, puis réunis, conservés à 4°C et transportés au Bordeaux Imaging Center (BIC) pour une fixation par HPF.

### High-pressure freezing (HPF)

L'HPF est une technique de cryofixation, à très basse température à -196°C avec l'azote liquide et à très haute pression (2080 bars). Cette technique permet de fixer les tissus ou les cellules dans leur état natif par congélation de l'eau à l'état vitreux, sans déformation des structures cellulaires [5-7].

Après chaque prélèvement des baies de Cabernet Sauvignon, les pépins ont été séparés immédiatement des baies à l'aide d'une pince. 5 pépins, pris au hasard, ont été disséqués avec une lame de rasoir en sections d'une épaisseur d'environ 500 µm et d'un diamètre d'environ 1mm selon le plan de dissection (Figure 1). Deux sections de chaque pépin ont été sélectionnées et placées individuellement dans une coupelle Alu, puis fixées par HPF (Leica, EM HPM 100). A l'issue de la fixation, les échantillons ont été récupérés et conservés dans l'azote liquide.

### Freeze-substitution (FS)

FS est une technique d'inclusion à basse température qui a pour but d'inclure l'échantillon dans une résine hydrophile tout en préservant au maximum les structures cellulaires et afin de faire un immunomarquage par la suite. Les échantillons fixés par HPF ont été transférés dans de l'acétone déshydraté pré-refroidi à
-90°C. La déshydratation et l'inclusion de résines (Lowicryl HM20) ont été réalisées par des bains dans un appareil de cryosubstitution (Leica EM-AFS 2) avec un programme spécifique à l'abri de la lumière :

* acétone déshydraté à -90°C pendant 72h

* acétone déshydraté de -90°C à -50°C pendant 12h (augmentation de température 3°C par 3°C)

* 2 rinçages successifs à éthanol pendant 1h

* éthanol – 20% HM20 à -50°C pendant 24h

* éthanol – 40% HM20 à -50°C pendant 24h

* éthanol – 60% HM20 à -50°C pendant 24h

* éthanol – 80% HM20 à -50°C pendant 24h

* 100% HM20 à -50°C pendant 24h

* 100% HM20 à -50°C pendant 50h

* 100% HM20 à -50°C sous UV pendant 48h

* 100% HM20 de -50°C à 20°C sous UV pendant 12h

* 100% HM20 à 20°C sous UV pendant 48h

Une fois que la résine est polymérisée, les échantillons ont été retirés de l'AFS, et conservés à l'obscurité.

<figure><img src="image_62.png" /><figcaption>Fig. 1 - Etapes de dissection des pépins de raisin pour la fixation chimique (en rouge) et zone d'intérêt pour l'immunomarquage (cadre bleu).</figcaption></figure>

### Réalisation des coupes

Les échantillons ont été coupés sur un ultra-microtome (Ultracut-UCT, Leica Microsystems). Des coupes semi-fines (500 nm) ont été observées au microscope photonique pour repérer la région d'intérêt et en vérifier l'ultrastructure. Puis des coupes ultra-fines (70 nm) ont été récupérées sur grilles Nichel recouvertes de formvar.

### Immunomarquage et observation au MET

L'immunomarquage consiste à l'incubation successive des grilles dans plusieurs bains contenant les anticorps primaires qui se dirigent contre la protéine d'intérêt et des anticorps secondaires couplés à des billes d'or colloïdal (10nm de diamètre) dirigés contre les anticorps primaires. La bille d'or étant dense aux électrons, elle permet de visualiser la localisation de la protéine à l'échelle subcellulaire.

L'immunomarquage a été réalisé avec l'automate d'immunomarquage, IGL (Leica, Microsystems) suivant le programme classique (Tableau 1). Les grilles ont été ensuite observées au microscope électronique à transmission à 120kV (FEI, Teknai 12).

## Résultats et discussion

Les pépins de raisin sont des échantillons très difficiles à préparer pour MET et l'immunomarquage à cause de leur complexité structurale. Les téguments lignifiés à maturité des pépins de raisin empêchent la pénétration des réactifs chimiques. En plus, sous les différentes couches de téguments lignifiés et durs, les tissus parenchymateux et l'albumen qui ont une densité beaucoup moins importante sont plus fragiles, ainsi se dégradent plus pendant le traitement de la déshydratation et de l'inclusion. Les techniques classiques de
la fixation chimique et la substitution par PLT ne permettent pas d'obtenir une inclusion correcte et donc l'obtention des coupes ultra-fines ayant une ultrastructure correcte des tissus.

<table><caption>**Tableau 1** - Programme d'immunomarquage pour l'automate IGL (Leica, Microsystems) adapté aux LAR et ANR de pépins de raisin</caption><thead><tr><td>N° lame</td><td>Réactifs</td><td>Vol goutte (μl)</td><td>Temps (min)</td></tr></thead><tbody><tr><td>1</td><td>PBS 0,05M glycine</td><td>30</td><td>15</td></tr><tr><td>2-3</td><td>PBS 1%BSA</td><td>30</td><td>15</td></tr><tr><td>4</td><td>Wash Incubation Buffer (IB)</td><td>30</td><td>5</td></tr><tr><td>5</td><td>IB</td><td>30</td><td>5</td></tr><tr><td>6</td><td>Anticorps I dans IB</td><td>10</td><td>60</td></tr><tr><td>7-9</td><td>IB</td><td>30</td><td>5</td></tr><tr><td>10</td><td>Anticorps II au 1/40ème dans IB</td><td>10</td><td>90</td></tr><tr><td>11-13</td><td>IB</td><td>30</td><td>5</td></tr><tr><td>14-16</td><td>PBS</td><td>30</td><td>5</td></tr><tr><td>17</td><td>Glutaldéhyde 1% dans PBS</td><td>30</td><td>5</td></tr><tr><td>18-19</td><td>PBS</td><td>30</td><td>5</td></tr><tr><td>20-25</td><td>H2O</td><td>30</td><td>1</td></tr></tbody></table>

*High-pressure freezing et freeze-substitution* ont permis d'optimiser la réalisation des coupes ultra-fines et d'améliorer l'ultrastructure cellulaire des pépins de raisin. Certains tissus et organites ont été identifiés sur les coupes ultra-fines au MET (Figure 2).

<figure><img src="image_63.png" /><figcaption>**Fig. 2** - Observation des pépins de Cabernet Sauvignon au stade "petit pois" (structures cellulaires peu identifiées) après HPF et FS. Abréviations : P : paroi cellulaire ; Vac : vacuole ; Cyt : cytoplasme ; Chlo : chloroplaste ; Comp Vac : composés.</figcaption></figure>

Par contre, bien que la qualité des coupes, ainsi que la préservation de l'état de l'ultrastructure cellulaire soient améliorées, la déchirure des tissus et la perte des organites ont toujours été observées sur des coupes semi-fines au microscope optique (données non présentées). Ainsi, l'immunomarquage des deux enzymes n'a pas donné de résultats satisfaisants. Ce phénomène serait dû à l'épaisseur importante et à la lignification de la paroi cellulaire des pépins de raisin, qui ne permettent pas aux réactifs d'imprégner et faire effet correctement. Ces techniques nécessitent encore des mises au point afin de préserver une meilleure ultrastructure cellulaire globale, ainsi qu'une bonne conservation des enzymes et de limiter la redistribution des protéines solubles correctes, qui sont primordiales par la suite pour l'immunomarquage.

La localisation *in vivo* par immunomarquage de la LAR et de l'ANR pourrait être effectuée après des mises au point de ces techniques, dans le but de mieux comprendre la voie de biosynthèse des tanins dans les pépins de raisin, en combinant d'autres approches biochimique, protéomique et transcriptomique, ainsi de suivre la migration des enzymes et des tanins, et d'évaluer leur extractibilité pour ensuite adapter les techniques de macération et d'extraction en fonction de la maturité des pépins.
Références

1. Kennedy JA, Matthews MA, Waterhouse AL (2000) Changes in grape seed polyphenols during fruit ripening. *Phytochemistry* **55**: 77-85.

2. Bogs J, Downey MO, Harvey JS et al (2005) Proanthocyanidin synthesis and expression of genes encoding leucoanthocyanidin reductase and anthocyanidin reductase in developing grape berries and grapevine leaves. *Plant Physiol* **139**: 652-663.

3. Gagné S, Lacampagne S, Claisse O et al (2009) Leucoanthocyanidin reductase and anthocyanidin reductase gene expression and activity in flowers, young berries and skins of *Vitis vinifera* L. cv. Cabernet-Sauvignon during development. *Plant Physiol Biochem* **47**: 282-290.

4. Lacampagne S (2010) Localisation et caractérisation des tannins dans la pellicule du raisin : Etude de l'impact de l'organisation physico-chimique des parois cellulaires sur la composante tannique, la qualité du fruit et la typicité des raisins de Bordeaux. *Thèse de doctorat*, Université Bordeaux Segalen.

5. Hunziker EB, Herrmann W, Schenk RK et al (1984) Cartilage ultrastructure after high pressure freezing, freeze substitution, and low temperature embedding. I. Chondrocyte ultrastructure--implications for the theories of mineralization and vascular invasion. *J Cell Biol* **98**: 267-276.

6. Moor H (1987) Theory and practice of high pressure freezing, pp. 175-191. *In Cryotechniques in Biological Electron Microscopy*. Steinbrecht RA, Zierold DK (Eds.), Springer, Berlin, Germany.

7. Sartori N, Richter K, Dubochet J (1993) Vitrification depth can be increased more than 10-fold by high-pressure freezing. *J Microsc* **172**: 55-61.
# Relationship between water and nitrogen status of the vine and aroma compounds potentially involved in the tertiary bouquet of red Bordeaux wines

N. LE MENN<fnref n="1" />,<fnref n="2" />*, M. PICARD<fnref n="1" />,<fnref n="2" />, C. VAN LEEUWEN<fnref n="3" />, G. DE REVEL<fnref n="1" />,<fnref n="2" />, S. MARCHAND<fnref n="1" />,<fnref n="2" />

Wine ageing – aroma compounds – soil type – water and nitrogen status

## Introduction

In the early 1980s, bouquet of wine has been described as a qualitative complexification of aroma [1]. Recent studies proposed a sensorial definition of this bouquet and also identified some of the molecules potentially implicated in its development [2]. The diversity of the vocabulary used by professional tasters to define the bouquet leads to search for polymorphic sensorial characters, but wine professionals agree that “bouquet of ageing” concerns “great wine” of Bordeaux, a prestigious appellation presenting high quality potential vineyard as well as oenological practices. The soil type and the physiological response of the vines to the climatic conditions are potential terroir elements influencing vine water and nitrogen status [3]. Recently, some aromas have been identified as belonging to the typical sensory bouquet of Bordeaux red wines such as “undergrowth”, “spicy” and “truffles” related aromas. The truffle aroma is identified in wines presenting significant levels of dimethyl sulfide (DMS). Accumulated with ageing, this compound has already been described in previous studies as being involved in the bouquet expression [4]. Literature quotes many other compounds such as tabanones [5] which could be interesting candidates in the expression of red wine bouquet.

The goal of this work is to study the influence of nitrogen and water status of vines in the development of bouquet after ageing for an example of St Emilion red wine. This hypothesis was investigated by analysing the composition of wines obtained by micro-scale vinifications performed over several vintages from vines of which water and nitrogen status was assessed.

## Materials and methods

### Water and nitrogen status

Microvinifications were conducted on Cabernet franc, Cabernet-Sauvignon and Merlot grapes. These cultivars were grown on three different soil types: sandy, gravelly and clayey. Table 1 lists wines aged from 7 to 18 years with the soil type, vintage and the grape variety available for this study. For each combination (vintage × variety × soil), water and nitrogen status of the vine were determined during the season. Then, a categorization of the water and nitrogen status was carried out according to van Leeuwen et al. [6-7].

### Aroma compound quantification

DMS quantification was performed by HS-SPME-GC/MS according to the method described by Picard et al. [2]. The incubation time for SPME injection was reduced to 5 min. Tabanone quantification was realised by SPME-GC/MS using the method described by Slaghenaufi et al. [5]. Statistics were carried out with the XLSTAT 2010 software (Addinsoft SARL EXCEL, Microsoft).

<footnote n="1">¹Univ. de Bordeaux, ISVV, EA 4577, Unité de recherche OENOLOGIE, F-33882 Villenave d'Ornon, France</footnote>

<footnote n="2">²INRA, ISVV, USC 1366 OENOLOGIE, F-33882 Villenave d'Ornon, France</footnote>

<footnote n="3">³Bordeaux Sciences Agro, UMR EGFV 1287, ISVV, F-33882 Villenave d'Ornon, France</footnote>
<table><caption>**Table 1** - Experimental design according to vintage, cultivar and soil type</caption><thead><tr><th rowspan="2">Cultivar</th><th colspan="9">Vintage</th></tr><tr><th>2007</th><th>2006</th><th>2005</th><th>2004</th><th>2003</th><th>2002</th><th>2001</th><th>1999</th><th>1996</th></tr></thead><tbody><tr><td>Merlot</td><td>C,G,S</td><td>C,G,S</td><td>C,G,S</td><td>C,G,S</td><td>C,G</td><td>C,G,S</td><td></td><td>C,S</td><td>C,G,S</td></tr><tr><td>Cabernet franc</td><td></td><td></td><td>C,G,S</td><td>C,G,S</td><td>S</td><td></td><td>G,S</td><td>C,G,S</td><td>C,G,S</td></tr><tr><td>Cabernet-Sauvignon</td><td></td><td></td><td></td><td></td><td>G</td><td></td><td>C,G,S</td><td>C,G,S</td><td></td></tr></tbody></table>

C, Clayey soil; G, Gravelly soil; S, Sandy soil

## Results and discussion

The principal component analysis (PCA) projection (figure 1) shows a correlation between DMS levels and yeast available nitrogen (YAN) levels in musts, considered as a good indicator of vine nitrogen status [6]. Figure 2 presents the content of DMS in accordance with vine nitrogen status assessed by must YAN content. For the 3 varieties cultivated on the 3 soils, wines made from musts with high YAN levels contain higher contents of DMS after ageing. These results are consistent with de Royer Dupré *et al.* [8], who propose a correlation between DMS precursors (pDMS) and YAN in must. Yeast available amino acid (YAAA) is a component of YAN and a high nitrogen assimilation of vines increases its content [9]. YAAA was not directly quantified in this study, but high nitrogen status should most likely have increased its content. High YAAA may allow a smoother fermentation, beneficial for the protection of pDMS present in the must. Furthermore, in grape berries, high level of YAAA may also induce pDMS synthesis.

<figure><img src="image_64.png" /><figcaption>**Fig. 1** - Correlation circle from principal component analysis of DMS concentration, water and nitrogen status.</figcaption></figure>

<figure><img src="image_65.png" /><figcaption>**Fig. 2** - DMS content in wine in relation to YAN at maturity. Pearson coefficient (R)= 0.823.</figcaption></figure>

The levels of the 4 tabanone isomers have been quantified (tab1, megastigma-4,6Z,8E-triene-3-one; tab2, megastigma-4,7E,9-triene-3-one; tab3, megastigma-4,6E,8E-triene-3-one, tab4, megastigma-4,6E,8Z-triene-3-one and tab5, tab3, megastigma-4,6E,8Z-triene-3-one). As expected, the megastigma-4,7E,9-triene-3-one isomer, which is extracted only from oak wood, was not detected. This can be explained by the fact that microvinifications were carried out without any contact with oak wood. PCA projection shows a strong correlation between tabanone isomer levels and wine age. This confirms the fact that tabanone isomers are liberated during ageing [10] (figure 3). To avoid the effect of age on tabanone content, a new variable, the sum of 4 isomer levels (µg/L) divided by age (years) was created. This result highlights the specific character of the 2003 vintage, in which levels of measured tabanone were about 4 times higher compared to those in a wine having approximately the same age (figure 3). The heatwave and drought of
this vintage considered as atypical may be the cause of these differences. Because of the exceptional conditions of the 2003 vintage, it was excluded for further study and kept as an idea for further investigations.

An effect of strong water deficit was observed on the ratio tabanone/age (table 2). The same result was obtained with another water status indicator (data not shown). A severe water deficit increased the production of tabanone during ageing (2-fold higher in stressed vines).

<figure><img src="image_66.png" /><figcaption>Fig. 3 - Tabanone content in wines related to wine age.</figcaption></figure>

<table><caption>**Table 2** - Effect of vine water status on tabanone/age ratios (Tuckey test (95%)). Water deficits are classified from δ¹³C data and according to van Leeuwen *et al.* [7].</caption><thead><tr><td>Cluster of water stress</td><td>Ratio average</td><td>Similarity</td></tr></thead><tbody><tr><td>No water deficit</td><td>0,335</td><td>B</td></tr><tr><td>Weak water deficit</td><td>0,262</td><td>B</td></tr><tr><td>Moderate to weak water deficit</td><td>0,247</td><td>B</td></tr><tr><td>Moderate to severe water deficit</td><td>0,294</td><td>B</td></tr><tr><td>Severe water deficit</td><td>0,638</td><td>A</td></tr></tbody></table>

## Conclusion

In this study an influence of vine water and nitrogen status on two molecular markers of the bouquet of red Bordeaux wines was shown. DMS levels were shown to increase with vine nitrogen status. An effect of water deficit was noticed on tabanone production during red wine ageing. A highly interesting effect of environmental factors on tertiary aromas in wine is highlighted.

## Acknowledgements

The authors thank Marie-Claire Perelló for technical support in tabanone quantification.

## References

1. Peynaud E (1980) *Le goût du vin*. Paris: Dunod.

2. Picard M, Thibon C, Redon P et al (2015) Involvement of dimethyl sulfide and several polyfunctional thiols in the aromatic expression of the aging bouquet of red Bordeaux wines. *J Agric Food Chem* **63**: 8879-8889.
3. Picard M, Tempere S, de Revel G et al (2015) A sensory study of the ageing bouquet of red Bordeaux wines: a three-step approach for exploring a complex olfactory concept. *Food Qual Prefer* **42**: 110-122.

4. de Mora SJ, Eschenbruch R, Knowles SJ et al (1986) The formation of dimethyl sulphide during fermentation using a wine yeast. *Food Microbiol* **3**: 27-32.

5. Slaghenaufi D, Perello MC, Marchand-Marion S et al (2014) Quantitative solid phase microextraction – Gas chromatography mass spectrometry analysis of five megastigmatrienone isomers in aged wine. *Anal Chim Acta* **813**: 63-69.

6. Van Leeuwen C, Friant P, Soyer JP et al (2000) L'intérêt du dosage de l'azote total et de l'azote assimilable dans le moût comme indicateur de la nutrition azotée de la vigne. *J Int Sci Vigne Vin* **34**: 75-82.

7. Van Leeuwen C, Trégoat O, Choné X et al (2009) Vine water status is a key factor in grape ripening and vintage quality for red Bordeaux wine. How can it be assessed for vineyard management purposes? *J Int Sci Vigne Vin* **43**: 121-134.

8. De Royer Dupré N, Schneider R, Payan JC et al (2014) Effects of vine water status on dimethyl sulfur potential, ammonium, and amino acid contents in Grenache Noir grapes (*Vitis vinifera*). *J Agric Food Chem* **62**: 2760-2766.

9. Lee J, Schreiner RP (2010) Free amino acid profiles from ‘Pinot noir’ grapes are influenced by vine N-status and sample preparation method. *Food Chem* **119**: 484-489.

10. Slaghenaufi D, Marchand-Marion S, Richard T et al (2013) Centrifugal partition chromatography applied to the isolation of oak wood aroma precursors. *Food Chem* **141**: 2238-2245.
# Phenolic contents and antioxidant activity of grape pomace seed and skin edible extracts

I. KY<fnref n="1" />,<fnref n="2" />, G. CROS<fnref n="3" />, A. CROZIER<fnref n="4" />, P.L. TEISSEDRE<fnref n="1" />,<fnref n="2" />*

Grape pomaces – edible extracts – polyphenols – antioxidant activity

## Introduction

Grapes of *Vitis vinifera*, one of the most cultivated fruit crops in the world, are known to be rich in polyphenols. Each year, the wine making industry produces a substantial amount of grape by-products called pomaces which account for about 20% of the weight of the grapes used to make wine [1]. Grape pomace, thus, potentially constitutes a very abundant and relatively inexpensive source of a wide range of polyphenols including monomeric and oligomeric proanthocyanidins and a diversity of anthocyanin glycosides. These compounds can be extracted and may be recovered as functional compounds in foods, cosmetics and pharmaceutical products to enrich their final products. Indeed, dietary intake of polyphenols has been estimated to be about 1 g/day [2]. Their intake is 10 times greater than that of vitamin C and 100 times that of vitamin E or carotenoids [3]. As a result, phenolic compounds are currently receiving much attention because of their favorable health effect related to their antioxidant. To date, grape and wine polyphenols have shown to exert beneficial effects on health [4, 5]. Epidemiological studies have shown an inverse correlation between the consumption of polyphenols enriched diet and reduced risks of cardio vascular diseases (CVDs) [6, 7]. The potential mechanisms of preventing CVDs could be related to the antioxidant activity. Actually, hypertension is the most important of cardiovascular risk factors worldwide. According to the World Health Organization 2013 data, hypertension accounted for approximately 9.4 million deaths a year. The importance of oxidative stress, vascular inflammation and endothelial dysfunction has to be highlighted in the development of CVDs. The knowledge of the process has provided new perspectives to elaborate novel pharmaceutical or dietary strategies to control the development of vascular diseases.

Therefore, the aim of this study was to analyse the remained potential of grape by-products from important Rhône Valley red wine cultivars: Grenache, Syrah, Carignan, Mourvèdre and Alicante. Seeds and skins were extracted using water and water/ethanol 70% in order to develop two types of edible extracts: aqueous extracts (EAQ) and hydro-alcoholic 70% extracts (EA70). We reported herein the total polyphenol, total anthocyanin and total tannin contents along with the determination and quantification of flavan-3-ols (monomers, dimers) using HPLC-Fluo. Moreover, the antioxidant capacity of pomace extracts was assessed using four antioxidant assays (ABTS⁺, DPPH, FRAP and ORAC). *In vivo* activity effects of grape by-products on a chronic disease model with hypertension are given.

## Materials and methods

*Plant materials and sample preparation*

This study was conducted in 2010 grape pomaces from *V. vinifera* L. cv. Grenache (from two different locations [GRE1 and GRE2]), Syrah (from two different locations [SYR1 and SYR2]), Carignan (CAR), Mourvèdre (MOU) and Alicante (ALI), provided from the Rhône Valley area, appellation Châteauneuf-du-Pape. According to previous study [8], samples were selected on the basis of their high content of polyphenols. One hundred grams of GRE1, SYR1 and CAR seeds and GRE2, SYR1, SYR2, CAR, MOU

<footnote n="1">¹ISVV, EA 4577 Œnologie, Univ Bordeaux, 210 Chemin de Leysotte, Villenave d'Ornon, France</footnote>

<footnote n="2">²ISVV, USC 1366 Œnologie, INRA, 210 Chemin de Leysotte, Villenave d'Ornon, France</footnote>

<footnote n="3">³Institut des Biomolécules Max Mousseron (IBMM), UMR CNRS-5247, Universités Montpellier 1 et 2, Ecole Nationale Supérieure de Chimie de Montpellier, BP 14491, 34093 Montpellier Cedex 5, France</footnote>

<footnote n="4">⁴Department of Nutrition, University of California, Davis, CA, United States</footnote>
and ALI skins were extracted in triplicate using 350 mL of distilled water for 1 h under magnetic agitation at 50°C. In parallel, under the same conditions, these samples were also extracted using a 70% hydro/alcoholic (70:30, v/v) solution. The centrifugal supernatants were evaporated and lyophilized to obtain two types of samples: an aqueous sample (EAQ) and a 70% hydro-alcoholic sample (EA70) for each variety and part.

### Chemical analysis

Extracts were solubilized in water/ethanol (90:10, v/v; pH 3.5 with tartaric acid) at appropriate concentrations. Total phenol content (TPC) was determined by the Folin-Ciocalteu assay [9] and the data expressed as mg of gallic acid equivalents (GAE) per g dry weight. Total tannin content was measured by acidic hydrolysis using the method of Ribereau-Gayon and Stonestreet [10]. Anthocyanin content was determined by the SO₂ bleaching procedure [11]. Proanthocyanidins were identified and quantified by HPLC-UV-Fluo-MS as described in previous study [12]. The antioxidant capacity of pomace extracts was assessed by TEAC, DPPH, FRAP and ORAC test and described in previous study [12].

### *In vivo* experiments

To determine the *in vivo* effect of grape pomace extracts and their potential effect on hypertension, an experiment was conducted with male 9-week-old spontaneous hypertensive rats (SHR) and their normotensive control Wistar-Kyoto (WKY) obtained from Janvier laboratory (Le Genest St. Isle, France). All rats were maintained at a constant temperature (23°C), with a 12-h dark/light cycle. Water and standard diet were given *ad libitum*. They were daily treated with grape pomace extract (extracted with hydro-alcoholic 70% solution) by gavage during 6 weeks at a dose of 21 mg/kg/day. Rats were divided in different groups: control group (6 WKY), SHR control group (5 SHR treated with 3% EtOH) and 6 groups of 4 SHR rats treated with pomace extract dissolved in 3% EtOH (SHR1: Grenache seed pomace extract, SHR2: Syrah seed pomace extract, SHR3: Syrah skin pomace extract, SHR4: Carignan seed pomace extract, SHR5: Mourvèdre skin pomace extract and SHR6: Alicante skin pomace extract). Blood pressure was measured by the tail-cuff method. The average of three pressure readings was recorded for each measurement.

### Statistical analysis

All measurements were performed in triplicate. Results are expressed as means ± standard deviation (SD). One-way ANOVA was performed to test the effects of variation factors (different samples) on each variable (TPC, total tannins, total anthocyanins, phenol concentrations, *etc.*). If significant effects were found at a 95% confidence interval, ANOVA was followed by a Tukey's HSD post hoc test to identify differences among groups. These analyses were performed using Statistica V.7 Software (Statsoft Inc., Tulsa, OK, USA).

## Results and discussion

### Grape pomace seed and skin characterisation

Overall, the results showed that the use of a 70% hydro-alcoholic solution allowed a better extraction of phenolic compounds whether in seeds or in skins. Among the seed extracts, seeds from SYR1 and CAR were particularly rich in polyphenols, tannins and anthocyanins in EAQ and EA70 extracts (Table 1). SYR 1 (EA70) contained a higher tannin concentration, up to 455.42 mg/g DW, while CAR (EA70) has a higher quantity in total anthocyanins (57.34 mg/g DW). In both extracts, phenolic contents in GRE1 were low in comparison with other varieties. Our results are in accordance with several studies which have reported a lower amount of total phenol and anthocyanin contents in products derived from Grenache variety compared to other varieties such as Syrah, Mourvèdre and Carignan [13].

For both type of seed extracts, SYR1 was the richest, whether in monomers (8.88 mg/g DW in EAQ and 13.84 mg/g DW in EA70), in dimers (6.87 mg/g DW in EAQ and 7.10 mg/g DW in EA70) as opposed to GRE1 (Table 1). The latter had already appeared to contain low amount of polyphenols in previous total analysis. However, despite this low content, GRE1 still possessed an exploitable potential, especially when extracted with 70% hydro-alcoholic solution.

Concerning skins, results for EAQ extracts revealed that ALI contained the highest phenolic contents for the three tests combined while in EA70, SYR1 skins were predominantly high in phenolic contents (Table 2). The poorest extract was SYR2, whether in EAQ or in EA70.
<table><caption>**Table 1 - Phenolic composition in pomace seed extracts**</caption><thead><tr><th></th><th></th><th>TPC</th><th>Total tan</th><th>Total antho</th><th>Σ Mono</th><th>Σ Dimers</th></tr></thead><tbody><tr><td rowspan="3">Seeds-EAQ</td><td>GRE1<sup>1</sup></td><td>128.2 ± 0.4<sup>a</sup></td><td>157.0 ± 0.6<sup>a</sup></td><td>4.0 ± 0.2<sup>a</sup></td><td>3.0 ± 0.1<sup>a</sup></td><td>2.5 ± 0.1<sup>b</sup></td></tr><tr><td>SYR1<sup>1</sup></td><td>215.9 ± 1.2<sup>c</sup></td><td>266.9 ± 2.6<sup>b</sup></td><td>10.6 ± 0.6<sup>b</sup></td><td>8.9 ± 0.0<sup>b</sup></td><td>6.9 ± 0.0<sup>c</sup></td></tr><tr><td>CAR<sup>1</sup></td><td>186.1 ± 0.3<sup>b</sup></td><td>264.6 ± 2.4<sup>b</sup></td><td>11.4 ± 0.5<sup>b</sup></td><td>3.2 ± 0.0<sup>a</sup></td><td>1.9 ± 0.0<sup>a</sup></td></tr><tr><td rowspan="3">Seeds-EA70</td><td>GRE1<sup>1</sup></td><td>195.7 ± 1.1<sup>a</sup></td><td>302.9 ± 4.9<sup>a</sup></td><td>12.2 ± 0.5<sup>a</sup></td><td>5.1 ± 0.0<sup>a</sup></td><td>3.0 ± 0.0<sup>a</sup></td></tr><tr><td>SYR1<sup>1</sup></td><td>207.4 ± 2.2<sup>b</sup></td><td>455.4 ± 1.8<sup>b</sup></td><td>38.7 ± 4.3<sup>b</sup></td><td>13.8 ± 0.0<sup>c</sup></td><td>7.1 ± 0.0<sup>c</sup></td></tr><tr><td>CAR<sup>1</sup></td><td>215.8 ± 1.5<sup>b</sup></td><td>423.1 ± 15.1<sup>b</sup></td><td>57.3 ± 1.9<sup>b</sup></td><td>7.3 ± 0.0<sup>b</sup></td><td>4.9 ± 0.0<sup>b</sup></td></tr></tbody></table>

¹ GRE1, Grenache; SYR1, Syrah; CAR, Carignan. In units of mg/g DW seed. Data are expressed as the mean of triplicate ± standard deviation. TPC, total phenol content; total tan, total tannins; total antho, total anthocyanins; Σ Mono, Σ Monomers = sum of catechin and epicatechin; Σ Dimer = sum of B₁, B₂, B₃ and B₄.

a, b, c, d, e, f Anova was made to compare values obtain between varieties for the same compound. Same letters indicate no significant differences between the value (Tukey's test, *p* < 0.05).

<table><caption>**Table 2 - Phenolic composition in pomace skin extracts**</caption><thead><tr><th></th><th></th><th>TPC</th><th>Total tan</th><th>Total antho</th><th>Σ Mono</th><th>Σ Dimers</th></tr></thead><tbody><tr><td rowspan="6">Skins-EAQ</td><td>GRE2<sup>1</sup></td><td>109.7 ± 0.2<sup>c</sup></td><td>112.3 ± 2.7<sup>b</sup></td><td>8.7 ± 0.0<sup>c</sup></td><td>1.1 ± 0.0<sup>ab</sup></td><td>1.3 ± 0.0<sup>ab</sup></td></tr><tr><td>SYR1<sup>1</sup></td><td>146.5 ± 1.2<sup>e</sup></td><td>156.6 ± 2.6<sup>c</sup></td><td>16.0 ± 0.0<sup>d</sup></td><td>2.5 ± 0.0<sup>c</sup></td><td>2.0 ± 0.0<sup>bc</sup></td></tr><tr><td>SYR2<sup>1</sup></td><td>71.9 ± 0.1<sup>a</sup></td><td>86.4 ± 1.9<sup>a</sup></td><td>1.8 ± 0.0<sup>a</sup></td><td>0.9 ± 0.1<sup>a</sup></td><td>0.9 ± 0.0<sup>a</sup></td></tr><tr><td>CAR<sup>1</sup></td><td>120.8 ± 1.1<sup>d</sup></td><td>161.6 ± 1.3<sup>c</sup></td><td>14.6 ± 0.8<sup>d</sup></td><td>1.4 ± 0.0<sup>b</sup></td><td>1.5 ± 0.0<sup>ab</sup></td></tr><tr><td>MOU<sup>1</sup></td><td>102.3 ± 0.4<sup>b</sup></td><td>104.8 ± 2.0<sup>b</sup></td><td>5.7 ± 0.0<sup>b</sup></td><td>1.0 ± 0.0<sup>ab</sup></td><td>1.5 ± 0.0<sup>ab</sup></td></tr><tr><td>ALI<sup>1</sup></td><td>196.7 ± 0.4<sup>f</sup></td><td>221.4 ± 3.5<sup>d</sup></td><td>21.4 ± 0.2<sup>e</sup></td><td>3.4 ± 0.2<sup>d</sup></td><td>2.3 ± 0.3<sup>c</sup></td></tr><tr><td rowspan="6">Skins-EA70</td><td>GRE2<sup>1</sup></td><td>195.6 ± 0.3<sup>c</sup></td><td>256.1 ± 3.7<sup>a</sup></td><td>53.7 ± 0.8<sup>a</sup></td><td>1.9 ± 0.0<sup>a</sup></td><td>1.6 ± 0.0<sup>a</sup></td></tr><tr><td>SYR1<sup>1</sup></td><td>224.9 ± 0.2<sup>f</sup></td><td>312.5 ± 10.8<sup>bc</sup></td><td>86.7 ± 1.7<sup>b</sup></td><td>3.7 ± 0.1<sup>c</sup></td><td>2.2 ± 0.0<sup>c</sup></td></tr><tr><td>SYR2<sup>1</sup></td><td>173.6 ± 0.1<sup>a</sup></td><td>250.2 ± 7.1<sup>a</sup></td><td>45.4 ± 0.2<sup>a</sup></td><td>3.2 ± 0.1<sup>b</sup></td><td>2.2 ± 0.1<sup>c</sup></td></tr><tr><td>CAR<sup>1</sup></td><td>203.5 ± 0.8<sup>d</sup></td><td>345.3 ± 4.2<sup>c</sup></td><td>88.4 ± 0.6<sup>b</sup></td><td>1.9 ± 0.0<sup>a</sup></td><td>1.8 ± 0.0<sup>ab</sup></td></tr><tr><td>MOU<sup>1</sup></td><td>219.9 ± 0.2<sup>e</sup></td><td>268.6 ± 11.7<sup>ab</sup></td><td>46.6 ± 0.4<sup>a</sup></td><td>2.2 ± 0.0<sup>a</sup></td><td>2.0 ± 0.0<sup>bc</sup></td></tr><tr><td>ALI<sup>1</sup></td><td>188.9 ± 0.7<sup>b</sup></td><td>232.7 ± 3.1<sup>a</sup></td><td>54.4 ± 2.7<sup>a</sup></td><td>7.7 ± 0.0<sup>d</sup></td><td>4.8 ± 0.0<sup>d</sup></td></tr></tbody></table>

¹ GRE2, Grenache; SYR1 and SYR2, Syrah; CAR, Carignan; MOU, Mourvèdre; ALI, Alicante. In units of mg/g DW skin. Data are expressed as the mean of triplicate ± standard deviation. TPC, total phenol content; total tan, total tannins; Total antho, total anthocyanins; Σ Monomers = sum of catechin and epicatechin; Σ Dimers = sum of B₁, B₂, B₃ and B₄. a, b, c, d, e, f Anova was made to compare values obtain between varieties for the same compound. Same letters indicate no significant differences between the value (Tukey's test, *p* < 0.05).

## Grape pomace seed and skin antioxidant activity evaluation

The antioxidant potential was determined in order to select the most active grape pomace seeds and skins among the studied varieties. In this work, the free radical scavenging potential was evaluated by three spectrophotometric tests: the FRAP, ABTS⁺ and DPPH and a spectrofluorimetric test, the ORAC test.

Concerning seed extracts, the four antioxidant analytical techniques gave the same classification both for EAQ and EA70. The highest antioxidant activities were found in SYR1 for both types of extracts. Results were correlated with previous analysis which evidenced SYR1 as having a substantial amount of flavan-3-ols, procyanidins and anthocyanins. Antioxidant activities of EAQ and EA70 grape pomace seed extracts are shown in Table 3.

In skins, results obtained by the different antioxidant analyses were more disparate, especially in EA70 extracts (Table 4). In aqueous extracts, the highest antioxidant activity was found in SYR1 and ALI. This observation was observed with every test and correlated well with previous results evidencing these extracts as containing high phenolic content. In EA70, different antioxidant tests did not give the same extract classification. Despite this fact, SYR1 skin extract was classified as being the first or second extract showing the highest antioxidant capacity in the four tests.