3.3.5

Discussion monoterpenol composition of wines after 12 months .............

3.3.6

Essential outcomes for monoterpenols and their precursor molecules ....

3.3.8

Essential outcomes for C 13 -norisoprenoids and their precursor molecules128

General Introduction

The grape varieties Vitis vinifera L. cv. Riesling and Vitis vinifera L. cv. Sauvignon blanc are considered to be two noble grape varieties. White wines made from these varieties are highly appreciated upon their distinctive aromatic bouquet.

Since about 200 years Riesling grapes are grown traditionally in the vine growing region of the Rheingau Valley in Germany, producing wines of superior quality. It is considered that the famous wine style Spätlese, which is produced from over ripe and partially botrytised grapes originally comes from this region or rather from the domain of Schloss Johannisberg.

Sometimes fully botrytised wines, labelled as Auslese and Beerenauslese, or the worldfamous icewines are produced from this variety as well. Today about 79% of the grape vines planted in the Rheingau Valley are Riesling vines.

To a similar extent the variety of Sauvignon blanc represents the traditional white vine variety of the Bordelais. It is used in combination with the grape varieties of Sémillon and Muscadelle to produce the recognised dry white wines from Bordeaux, but it is also elaborated as the famous sweet wines from botyrised grapes of Sauternes, Loupiac or Sainte-Croix du Mont.

Riesling wines' aromatic expression is very versatile and manifold fruity and floral odours, as well as vegetative and mineral aromatic nuances are associated with its varietal characteristic (Fischer and Swoboda, 2005). Despite several works were conducted on Riesling wines' aroma, there is still a lack of knowledge towards the impact of the aroma compounds considered to be imparted in Riesling wines' aromatic expression.

Riesling is a variety, which is known to be highly capable to reflect the climatic conditions, the soil, and viticultural practices applied during a year in its wines' aroma and taste (Fischer and Swoboda, 2005). Different projects showed the influence of terroir, in its geological and geographical factors, on aromatic expression and some volatile compounds of Riesling wines [START_REF] Böhm | Terroir Hessen. Vielfalt erleben! Gesellschaft für Rheingauer Weinkultur mbH / Weinbauverband Hessische Bergstraße e[END_REF][START_REF] Bauer | Terroirausprägung bei der Rebsorte Riesling: Korrelation sensorischer, chemischer, bodenkundlicher und klimatischer Parameter[END_REF]. But none of these works considered the concept of typicality in the notion of the French term typicité.

Typicality [la typicité] includes the sensorial, technical and environmental dimensions and can be defined as a set of properties of distinction as well as properties of affiliation (Casabianca and Sylvander et al. (2005), cited by Cadot et al., 2010). [START_REF] Dubourdieu | La valeur du vin entre nature et culture réflexions sur le goût mondial et la typicité des vins in Oeno 2011 -9 e Symposium International d[END_REF] defines typicality [la typicité] as reflecting originality, being identifiable, being associated to a terroir, and reflecting a contemporary image. It also integrates all human choices at all stages of vine growing and winemaking. For [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF] it is also linked very close to the notion of terroir -especially for single varietal vines [les vins de cépage].

As typicality is linked closely to terroir and terroir was shown to influence Riesling wines' aromatic expression, it is likely, that Riesling wines' aromatic typicality is impacted when single or multiple factors of terroir change.

Since a decade or two, the global warming scenario has become more and more evident [START_REF] Iccp ; Field | Managing the risks of extreme events and disasters to advance climate change adaption. A special report of working groups I and II of the intergovernmental panel on climate change[END_REF]) and the regional consequences of probable regional climate effects are studied since then [START_REF] Iccp ; Field | Managing the risks of extreme events and disasters to advance climate change adaption. A special report of working groups I and II of the intergovernmental panel on climate change[END_REF]. For the wine growing region of the Rheingau, regional models predicted a higher probability for extreme drought events, which could lead to an increased number of water stress situations for grape vines grown in vineyards showing low water holding capacity [START_REF] Hofmann | Inklim2012IIplus: Einfluss der Klimaentwicklung auf den Wasserhaushalt von Rebstandorten -Möglichkeiten der Modellierung von Steillagenregionen[END_REF].

Grape vines' water status was identified to be an important factor of terroir (van Leeuwen et al., 2004;van Leeuwen and Seguin, 2006) and therefore Riesling wines' aromatic typicality probably gets impacted directly by the predicted climate effects.

Only little is studied about the impact of water deficit on biosynthesis of aroma compounds and their precursor molecules in grape berries and finished wines, especially regarding the grape variety Riesling.

Therefore, in order to get deeper knowledge on those possible consequences, the opportunity of the collaboration between two research institutions in the Federal State of Hesse, namely the 'Forschungsanstalt Geisenheim' in cooperation with the 'Justus Liebig Universität Gießen', and in the Region of Aquitaine, namely the 'Institute des Sciences de la Vigne et du Vin' associated with the 'Université Bordeaux Segalen', was taken for this present study.

After a first Chapter of bibliography, in the Chapter 2, the concept of Riesling wines' typicality was studied using sensory and instrumental analytical methods by confrontation to Bordeaux white, Sauvignon blanc-style wines.

In the Chapter 3, consequences of water deficit and micro climate manipulation on precursor molecules and aroma compounds considered to be imparted in Riesling wines' typicality perception were studied.

Finally, the Chapter 4 describes the identification of a new marker molecule considered to impact Riesling wines' typicality using a comparative study with the better understood varietal aroma of wines from Vitis vinifera L. cv. Sauvignon blanc.

Chapter 1

1 Bibliography

1.1

The grape variety Riesling

History of the grape variety Riesling

The origin of the variety Riesling is discussed to be situated in Germany. Suggestions are made, Riesling being a descendent of a variety described by the roman writer Plinius . Others suggest King Ludwig the German (843 -876 AD) to be responsible for the first plantings on river banks of the Rhine. Also discussed is its development in the Rhine region from the wild variety Vitis vinifera L. cv. Silvestris, being as speculative as former suggestions (Anonymous, 1982;[START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Genetic analysis conducted by the group of F. Regner implicates the origin of Riesling as a interbreeding of a small berry providing and frost resistant autochthonic variety, which was cultivated by German tribes and

Traminer, brought by the Romans to the Rhine region. Interbreeding with Heunisch is discussed as a further step of development to bring consistency, vitality and acid potential into Riesling [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF].

In the German Viticulture lexicon of 1930 Vitis vinifera L. cv. Riesling is clearly originated from Germany, probably in the Rheingau valley. First white grape varieties' plantings are documented for 1392 AD at Geisenheim, replacing dominant red grape varieties' plantings.

In that period of time especially the Cistercian abbey Eberbach pushed white wines' plantings to face the competition of French red wines on the Cologne wine market through typical regional white wines of high quality. Despite there is no documentation concerning the exact specification of the grape variety Riesling, one can consider these wines were produced from a close Riesling progenitor, due to first documentation findings for rießlingen in wine cellar accounting documents from March 13 th , 1435 addressed to the Earl of Katzenelnbogen in 'Rüsselsheim am Main'. Probably not coincidently, the members of the house of Katzenelnbogen were usually buried in the Eberbach abbey [START_REF] Staab | Zur Herkunft der Rieslingrebe -die Geschichte einer Rebsorte, PRO RIESLING[END_REF].

Generally clerical structures led to spreading of the variety Riesling through ordinances, as for vineyards of Schloss Johannisberg since 1716 AD and at the Mosel region since 1787 AD. By the end of the 19 th century, German Riesling wines were highly appreciated and valued with extremely high prices (Anonymous, 1982;[START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF].

Ampelographic and viticultural characteristics of Riesling vines

Vitis vinifera L. cv. Riesling grape vines' shoots are characterised by long distanced internodes. They show medium secondary shoot growth. Grape cluster are small, dense and generally cylindrical (shouldered). Riesling produces small to medium sized, round, greenishyellow (golden yellow in the case of sun exposure), black spotted berries. Phenological stages are characterised mostly as being late to very late during growing season [START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF][START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF].

Cultivation of the variety Riesling is favoured by moderate or cool climate. Despite being favoured through cool climate, Riesling needs a sufficient quantity of warmth during the ripening season, especially in September (for Germany), to achieve full ripeness. In warmer wine growing regions, hot weather causes problems in production of high quality wines, often leading to non-fruity wines of low quality [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Being frugal concerning its demands from soil, Riesling can be grown on a broad range of soils, from flat grounded, weathered rocky soils to deep grounded, loamy soils. In dry, flat grounded, rocky south exposed steep slope vineyards, robustness distinguishes Riesling vines (Kerridge and Antcliff, 2004;[START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Riesling generally is not highly endangered by pests and diseases, like Peronospora, Oidium, or Esca. Concerning noble rot (Botrytis cinerea), grapes are not super sensible in comparison to other varieties, whereas pedicel rot as primary or secondary infection seems to be more frequent. In years of early maturity and humid and warm climatic conditions, Riesling berries are highly susceptible to bursting berries, which favours putrefaction [START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF][START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Clone selection led to good yield quantity potential. Selected Riesling clones today permit constant yields from 60 and 110 hl/ha, depending on viticultural practices. Grape maturity is generally estimated regarding sugar concentration in grape juice measured in °Brix (in Germany in °Oe). Riesling grapes show good maturity from 15.9 °Brix to 17.1 °Brix for simple wine qualities (Kabinett). Late Vintages (Spätlese, Vendange tardive) and sweet dessert wines are made from >19 °Brix and >21.3 °Brix respectively [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF].

Economical importance of Riesling in viticulture

World-wide an estimated area of 34 209 ha are planted with Riesling. Major Riesling producing countries are Germany, Australia and France (Table 1-1). In Germany an area of 22 601 ha was planted with Riesling in 2010, representing 22.1% of the total vineyard surface in Germany (DWI, 2011). As the major variety in six of the 13 wine growing areas in Germany, with a share of up to 79 % (Rheingau Valley) (3125 ha), Riesling is an important factor in German viticulture in general and especially for the regional Hessian viticulture (DWI, 2011b).

Organoleptic attributes of Riesling wines

Riesling wines' aromatic quality is highly dependent on vineyard characteristics and yield.

Riesling wines show high capability to reflect the concept of terroir, including soil, climatic conditions, viticulture and oenological practises [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]Kerridge and Antcliff, 2004;Fischer and Swoboda, 2005).

A Riesling wine is always considered to have pronounced acidity. It is designated to be the Riesling wines spine, bearing its fruity and fresh character and permitting long storage and bottle aging [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]Fischer and Swoboda, 2005). Taste and aromatic properties of young Riesling wines can include versatile fruitiness, including grapefruit, lemon, lime, apple, peach, passion fruit, pineapple, mango, melon and quince. In addition to this, they can also show distinctive aromatic properties like flowers as rose or vegetative as fresh cut grass, hey, straw and herbs, but also mineral aromatic nuances like the smell of wet rocks, smoke, empyromatic, crustacean shell or iodine aroma. It is evident that fermentation derived aromas, such as esters or higher alcohols, show responsibility for some fruity or even cooling sensory expressions (Kerridge and Antcliff, 2004;[START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]Fischer and Swoboda, 2005). During the aging of wines, the aromatic profile of Riesling wines changes towards less fruity to more mineral or 'ripe', aromatic properties like honey, orangepeel, walnut and the for aged Riesling wines well known 'kerosene' or 'petrol' aroma, which corresponds to the odour of linseed oil [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]Fischer and Swoboda, 2005).

1.2

The grape variety Sauvignon blanc

History of the grape variety Sauvignon blanc

The cultivation of Sauvignon blanc was reported to happen simultaneously for the regions le Berry (today's Departements Cher and Indre) and the Bordelais (today's Departement Gironde) in the first century AD. This gets explained by kinship or trading relations between the Gallican people Bituriges Vivisques (Bourges) and Bituriges Cubi (Bordeaux) (Garrier, 2008). Ampelogists indicate strong morphological similarities to Chenin de Loire. The name is referred to originate from forest (silva). In the sixth century Sauvignon blanc was mentioned by Grégoire de Tours and in the twelveth century it is cited in La Bataille des vins of Henri d'Andéli (1225 AD) to produce the wine of Pouilly-sur-Loire and Sancerre. Victor

Pulliat already indicated in 1879 the 'finesse et [sa] saveur spéciale' of Sauvignon blanc wines (Garrier, 2008).

Ampelographic and viticultural characteristics of Sauvignon blanc vines

Vitis vinifera L. cv. Sauvignon blanc grape vines' shoots are characterised by short to long distance internodes. They show strong vigour [START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF]Kerridge and Antcliff, 2004;[START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Grape cluster are small, dense and generally conical (shouldered). Sauvignon blanc produces small to medium sized, ovoide, yellow (golden yellow at maturity), and thickskinned berries. Phenological stages are characterised as being timed averagely during the growing season [START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF]Kerridge and Antcliff, 2004;[START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Due to late lignification in the growing period, Sauvignon blanc vines can suffer from a lack of winter hardiness, if they are exposed to unfavourable climatic conditions during the growing season.

Therefore, moderate or warmer climatic regions are favourable [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Sauvignon blanc vines can be grown on a wide range of soil types. Generally poor soils suit more than heavy loamy grounds, although they achieve good performance on rich deep grounded soils.

Vigour can be controlled by selection of a suitable rootstock for soil conditions. Same as for Riesling, Sauvignon blanc is generally endangered by pests and diseases like oidium, black rot, grey rot and eutypa [START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF]. Concerning berry rot or noble rot (Botrytis cinerea), grapes are more sensible at the stage of inflorescence in comparison to other varieties, as it is to grape leaf hoppers [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Like for Riesling, clone selection led to Sauvignon blanc clones permitting constant yields from 50 and 70 hl/ha [START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF].

1.2.3

Economical importance of Sauvignon blanc in viticulture World-wide an estimated area of 45 000 ha is planted with Sauvignon blanc. Major Sauvignon blanc producing countries are France, Chile, USA, South Africa, Italy and Australia (Table 12. France, with its close to 20 000 ha of Sauvignon blanc, grows 44.4% of the worlds' Sauvignon blanc vines. From these stocks about 8082 ha are grown in the South West of France, in the Region of Aquitaine, and represent with the red Bordeaux varieties an enormous economical factor, especially for the biggest appellation in the Bordeaux region 'Entre deux mers' [START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF].

Organoleptic attributes of Sauvignon blanc wines

Sauvignon blanc wines are generally assigned to wines of great aromatic diversity. Their varietal aroma is defined by spicy odours, with an aromatic expression of green capsicum, when grapes were not mature at harvest, and by fruity odours like blackcurrant and citrus fruit [START_REF] Darriet | L'arôme et les précurseurs d'arôme du Sauvignon[END_REF][START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF]. Especially the characteristic boxtree odour, reminding sun heated blackcurrant buds and grapefruit or passion fruit odours are appreciated in wines produced from fully ripened crop of grapes [START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF][START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF].

1.3

Possible impact of 'Climate Change' on viticulture

Promotive climatic conditions are basic requirements for agricultural and viticultural production. Geographic suitability of grape varieties in regions is qualified according to climatic factors, e.g. mean temperature during the wine growing season [START_REF] Huglin | Biologie et ècologie de la vigne[END_REF][START_REF] Gladstone | Viticulture and environment[END_REF]. This kind of categorisation always reflects certain socio-historically emerged 'climatic optimum' for grape varieties, which, in a way is also reflected in the French AOCs and the notion of terroir.

The equilibrium of climatic conditions with other factors of 'terroir' and 'typicité' could get disequilibrated by the prognosted 'climate change', which is likely to impact general wine quality (Mira de Orduna, 2010). Meanwhile the global rise of mean temperature is undoubted [START_REF] Iccp ; Field | Managing the risks of extreme events and disasters to advance climate change adaption. A special report of working groups I and II of the intergovernmental panel on climate change[END_REF]. Jones and co-workers predicted, on the basis of wine spectator ratings for wines from different regions, world-wide changes in quality ratings towards positive ratings for 25 of 30 grapevine growing regions (Jones et al., 2005). The applied model took only the effects of temperature into account, but not the effects of higher sugar accumulation, rising pest risks or drought events. Therefore such a model would be insufficient.

Temperature changes also would impact the distribution of extreme weather situation during a year, like frequencies of extreme cold or extreme hot weather, which therefore is likely to interact with the distribution of precipitation during a year on global as well as regional level (IPCC, 2012). According to the results of a regionalised predicting model for the Hessian region, it is likely that the precipitation pattern will change during summertime, the growing period for grapevines, in a range up to 20 % less precipitation [START_REF] Hofmann | Inklim2012IIplus: Einfluss der Klimaentwicklung auf den Wasserhaushalt von Rebstandorten -Möglichkeiten der Modellierung von Steillagenregionen[END_REF].

Less precipitation and increasing frequency of drought periods could impact vineyard sites showing low water holding capacity, which in Germany are commonly situated in areas of steep slope viticulture, like the upper Rheingau Valley and the Middle Rhine Valley. The probable consequences of these scenarios on grapevines' water status were predicted on the base of well established grapevine water status and soil water status relations [START_REF] Lebon | Modelling the seasonal dynamics of the soil water balance of vineyards[END_REF][START_REF] Schultz | Modelling the effets of climate change on grapevine water relations[END_REF][START_REF] Gruber | Coupling of plant soil water status at different vineyard sites[END_REF][START_REF] Pineau | Spécifité aromatique des vins rouges de Bordeaux -étude de leurs nuances de fruit rouges et fruits noirs[END_REF] for two representative types of vineyards in the Rheingau Valley showing an increasing number of drought induced water deficit events until the year 2100 [START_REF] Hofmann | Inklim2012IIplus: Einfluss der Klimaentwicklung auf den Wasserhaushalt von Rebstandorten -Möglichkeiten der Modellierung von Steillagenregionen[END_REF].

These results indicate that vineyard sites showing low water holding capacity, could have to deal every second to third year with 31 and more days of water deficit (Ψ (pd) = <-0.3 MPa) in the future. Therefore, the challenge for the future will be to handle these probable consequences in an economical way and to keep up a high quality level in wines.

1.4

Effects of climate-dependent environmental parameters on vines and fruits

Effect of temperature

The effect of temperature has extensively been reviewed by Mira de Orduna (2010). Warmer temperatures extend the period of physiological activity of vines and increase metabolic rates and metabolites' accumulation [START_REF] Coombe | Influence of temperature on composition and quality of grapes[END_REF]Mira de Orduna, 2010). Therefore, dates for budbreak, flowering and fruit maturity are affected through climatic conditions (Mira de Orduna, 2010). At temperatures of 30 °C and higher, it is reported that grapevines react with reducing berry size and weight and sugar accumulation may be stopped [START_REF] Coombe | Influence of temperature on composition and quality of grapes[END_REF]Kriedemann and Smart, 1971, cited by Mira de Orduna, 2010). Even if higher temperatures accelerate grape maturation, temperature effects on final sugar amounts are reported to be not very large [START_REF] Coombe | Influence of temperature on composition and quality of grapes[END_REF]Mira de Orduna, 2010). High sugar accumulation in berries, resulting in more than 24 -25 °Brix, is considered to occur through evaporative loss at high temperatures (Keller, 2010;Mira de Orduna, 2010).

Amino acid concentrations in berries were not considered to be influenced by temperature [START_REF] Buttrose | Effect of temperature on the composition of 'Cabernet Sauvignon' berries[END_REF]Mira de Orduna, 2010), whereas total acidity shows lower levels with higher temperatures, especially through a decrease of malic acid [START_REF] Buttrose | Effect of temperature on the composition of 'Cabernet Sauvignon' berries[END_REF]Mira de Orduna, 2010).

Temperature as well, affects polyphenol synthesis, but in most studies it is considered to be difficult to separate light from temperature effect [START_REF] Reynolds | Fruit maturation of four Vitis vinifera cultivars in response to vineyard location and basal leaf removal[END_REF].

1.4.2

Effect of sun exposure -temperature and radiation

The indirect effect of sun exposure -increasing temperature in exposed grapes -leads to lower total acidity in must [START_REF] Reynolds | Fruit maturation of four Vitis vinifera cultivars in response to vineyard location and basal leaf removal[END_REF]. However, the quantity of radiation through sun exposure can be controlled through canopy management, whereas the quality of radiation is influenced by climatic factors such as atmospheric and stratospheric gas composition (Mira de Orduna, 2010). Therefore, the effects of different levels of e.g. UV-B radiation on plants and vines were studied. Plants responded with decreases in leaf expansions, fresh and dry weight, total biomass and photosynthetic capacity [START_REF] Schultz | Is grape composition affected by current levels of UV-B radiation ?[END_REF][START_REF] Schultz | Climate change and viticulture: A European perspective on climatology, carbon dioxide and UV-B effects[END_REF]. A biochemical reaction to UV-B radiation is an upregulation of enzymes, which are involved in the metabolisation of UV absorbing compounds such as polyphenols as well as for antioxidants like Glutathione. Furthermore an influence on carotenoids' degradation and amino acid formation was observed [START_REF] Schultz | Is grape composition affected by current levels of UV-B radiation ?[END_REF][START_REF] Schultz | Climate change and viticulture: A European perspective on climatology, carbon dioxide and UV-B effects[END_REF].

1.4.3

Effect of water deficit and nitrogen uptake Grape vines are often grown under sub-optimal conditions. Especially limited water supply is a key factor for vines' physiological and biochemical responses, leading to enhanced winemaking potential of the grape [START_REF] Pineau | Examples of perceptive interactions involved in specific 'red-' and 'black-berry' aromas in red wines[END_REF].

Water deficit was shown to reduce shoot growth, berry weight and yield, as well as it increases berry anthocyanin and tannin content [START_REF] Hardie | Response of grapes to water-deficit stress in particular stages of development[END_REF][START_REF] Matthews | Fruit ripening in Vitis vinifera L.: Responses to seasonal water deficits[END_REF][START_REF] Matthews | Reproductive development in grape (Vitis vinifera L.): Responses to seasonal water deficits[END_REF]van Leeuwen and Seguin, 1994;[START_REF] Koundouras | Influence of vineyard location and vine water status on fruit maturation of non-irrigated cv. Agiorgitiko (Vitis vinifera L.). Effects on wine phenolic and aroma components[END_REF][START_REF] Pineau | Examples of perceptive interactions involved in specific 'red-' and 'black-berry' aromas in red wines[END_REF]. A mild to moderate deficit in the first phase of the rapid berry expansion led to limited berry growth and reduced canopy density [START_REF] Dry | Factors influencing grapevine vigour and the potential for control with partial rootzone drying[END_REF][START_REF] Dry | Strategic irrigation management in Australian vineyards[END_REF]Keller, 2005). Berries grown under mild water deficiency were smaller and often showed higher sugar concentration (Keller, 2005). A decrease in photosynthesis and sugar transport from the leaves under more severe water deficit could lead to a reduction in berry sugar accumulation [START_REF] Quick | The effect of water stress on photosynthetic carbon metabolism in four species grown under field conditions[END_REF][START_REF] Rogiers | Irrigation, nitrogen, and rootstock effects on volume loss of berries from pottet Shiraz vines[END_REF]Keller, 2005).

Pre-veraison as well as post-veraison water deficiency was shown to reduce berry size (Kennedy et al., 2002;Ojeda et al., 2002;Keller, 2005). Generally, water stress should be avoided before fruit set, whereas the time between fruit set and veraison is the period when shoot growth and berry size can be most effectively controlled by water deficit (Keller, 2005).

Another factor coupled to the water status is the uptake and inner plant delocalisation of nitrogen compounds. Nitrogen uptake is realised through an active nitrate transporter, which is driven by boron cations, and therefore boron deficiency decreases nitrate uptake in roots (Camacho-Cristobal et al., 1999;Keller, 2005). When there is no sufficient soil moisture, nitrogen cannot be uptaken by the roots (Keller, 2005). Moreover, if vines suffered long-term water deficit, abscisic acid was increased and cytokinin contents were reduced. This accelerated leaf aging and finally led to senescence of older leaves (Jackson, 1997;[START_REF] Yang | Abscisic acid and cytokinins in the root exudates and leaves and their relationship to senescence and remobilization of carbon reserves in rice subjected to water stress during grain filling[END_REF]Keller, 2005). 'Senescence is accompanied by a decline in chlorophyll and remobilisation of carbon, proteins, and nutrients from these leaves and followed by leaf abscission' (Keller, 2005). Some of the sugars, amino acids and mineral nutrients could be recycled to the fruit (Keller, 2005).

1.5

Aroma compounds in Riesling wines' aroma and their genesis 1.5.1

Alcohols and esters

Volatile higher alcohols and the corresponding acetic esters as well as ethyl acetates of fatty acids are considered to be the major volatile fraction to aroma of all kinds of fermented beverages (Nykänen, 1986). Among other volatile compounds, they were identified in Riesling wines' aroma extracts (Schreier and Drawert, 1974a;[START_REF] Schreier | Identification of volatile constituents from grapes[END_REF]. Being omnipresent in all fermented wines, many of the esters and alcohols were not considered to make significant contributions to distinctive flavour and aroma perception and therefore also not in varietal aromatic expression (Ebeler and Thorngate, 2009). Considered as most significant for wine aroma are ethyl acetate (fruity, solvent like), 3-methylbutyl acetate (iso-amyl acetate, banana), 2-methylpropyl acetate (iso-butyl acetate; pear-drops), ethyl hexanoate (ethyl caproate, apple), and 2-phenylethyl acetate (honey, fruity, floral), which are produced in variable amounts by commercial yeast strains (Swiegers et al. 2005).

Produced quantities are influenced by yeast selection, especially through mixed culture fermentations with wild yeast strains as Hanseniaspora guilliermondii or Pichia anomala and Saccharomyces cerevisiae, which led to higher acetate ester concentrations [START_REF] Rojas | Acetate ester formation in wine by mixed cultures in laboratory fermentations[END_REF]. In spontaneous fermented Riesling wines, showing high share in Hanseniaspora uvarum during fermentation, ethyl acetate concentrations were elevated (Gerhards et al., 2012).

Esters are considered to impact the typical fruity character of red wines, mainly through synergetic effects and perceptive interactions (Escudero et al., 2007;[START_REF] Pineau | Examples of perceptive interactions involved in specific 'red-' and 'black-berry' aromas in red wines[END_REF].

Especially ethyl esters of fatty acids as butanoic acid, hexanoic acid, octanoic acid (caprylic acid), decanoic acid (capric acid), and to a lesser extent dodecanoic acid are implicated as perceptive interactors with other aromatic compounds as β-damascenone (Escudero et al, 2007;[START_REF] Pineau | Which impact for β-damascenone on red wines aroma?[END_REF]), β-ionone (Escudero et al., 2007) and dimethyl sulfide [START_REF] Segurel | Contribution of dimethyl sulfide to the aroma of Syrah and Grenache noir wines and estimation of its potential in grapes of these varieties[END_REF]Escudero et al., 2007), even if these are present below their odour detection threshold (Escudero et al., 2007;[START_REF] Pineau | Which impact for β-damascenone on red wines aroma?[END_REF]. Ethyl butanoate, ethyl hexanoate and ethyl octanoate were shown to participate in the aromatic expression of 'fresh fruit' and 'red fruit', whereas ethyl propionate was shown to participate in the notion of 'candied fruit' and 'black fruit' [START_REF] Pineau | Examples of perceptive interactions involved in specific 'red-' and 'black-berry' aromas in red wines[END_REF].

Ethyl esters of fatty acids as well as acetic acid esters of higher alcohols, like Acetic acid esters are degraded through hydrolysis during bottle aging (Rapp et al., 1985), whereas ethyl esters of branched acids like ethyl 2-methylpropionate (ethyl iso-butyrate), ethyl 2-methylbutanoate, ethyl 3-methylbutanoate (ethyl iso-valeriate), and ethyl phenylacetate are formed through chemical esterfication (Ferreira et al., 2001;[START_REF] Diaz-Maroto | Formation pathways of ethyl esters of branched short-chain fatty acids during wine aging[END_REF]. Same was observed for mono-and diethyl succinate, diethyl glutarate and diethyl malate (Rapp et al., 1985).

Despite being strongly related to fermentation, some esters were identified and considered to impact varietal aroma of grape varieties. In wines of Pinot noir methyl anthranilate, ethyl anthranilate (sweet-fruity, grape-like), ethyl cinnamate (cinnamon-like, sweet-balsamic, sweet-fruity, plum and cherry-like), and ethyl 2,3-dihydrocinnamate were identified exhibiting distinctive varietal aroma (Moio and Etiévant, 1995). Ethyl cinnamate is influenced by oenological practices such as 'macération carbonique', which favours the formation of this ester [START_REF] Bitteur | Carbonic anaerobiosis of Muscat grapes. I. Changes in the profiles of free and bound volatiles[END_REF]. As others, ethyl cinnamates' aromatic properties are influenced by β-damascenone [START_REF] Pineau | Which impact for β-damascenone on red wines aroma?[END_REF] or show synergistic effects with those of other aroma compounds [START_REF] Loscos | Release and formation of varietal aroma compounds during alcoholic fermentation from non-floral grape odorless flavor precursors fractions[END_REF].

Another group of esters contributing to fruity odours, mostly in red wines, are hydroxylated ethylesters like ethyl 3-hydroxybutyrate [START_REF] Pineau | Contribution à l'étude de l'arôme fruité spécifique des vins rouges de Vitis vinifera L. cv. Merlot noir et Cabernet-Sauvignon[END_REF][START_REF] Pineau | Examples of perceptive interactions involved in specific 'red-' and 'black-berry' aromas in red wines[END_REF], ethyl 4-hydroxybutyrate (Ugliano and Moio, 2005), ethyl 2-hydroxyhexanoate, ethyl 6-hydroxyhexanoate [START_REF] Pineau | Contribution à l'étude de l'arôme fruité spécifique des vins rouges de Vitis vinifera L. cv. Merlot noir et Cabernet-Sauvignon[END_REF], and ethyl 4-oxopentanoate [START_REF] Pineau | Contribution à l'étude de l'arôme fruité spécifique des vins rouges de Vitis vinifera L. cv. Merlot noir et Cabernet-Sauvignon[END_REF].

Recently 2-hydroxy-4-methylpentanoate was identified and demonstrated to be involved in blackberry aroma (Falcao et al., 2012). The organoleptic impact of its enantiomers and their distribution in wine subsequently was studied [START_REF] Lytra | Distribution and organoleptic impact of ethyl 2-hydroxy-4-methylpentanoate enantiomers in wine[END_REF].

In general, fermentation derived esters have been classified as less important for aroma prediction of Riesling wines than grape derived aroma compounds [START_REF] Smyth | The compositional basis of the aroma of Riesling and unwooded Chardonnay wine[END_REF], whereas for Croatian Riesling, esters were found to be the most odoriferous aroma compounds [START_REF] Komes | Characterization of odor-active compounds in Croatian Rhine Riesling wine, subregion Zagorje[END_REF].

Terpenes

Until now more than 30 000 terpenes are known in literature, filling several books and reviews (Breitmeier, 2006). Since the finding of the isoprene rule by Otto Wallach in 1887, natural compounds built up from isoprene subunits (C 5 ) n are specified as terpenes [START_REF] Ruzicka | Perspektiven der Biogenese und der Chemie der Terpene[END_REF], but are nevertheless denoted as isoprenoids (Breitmeier, 2006). The terpenes get differentiated into subgroups of hemi-(C5), mono-(C10), sesqui-(C15), di-(C20), sester-(C25), tri-(C30), tetraterpenes (C40) and polyterpenes (C5) n with n>8. The isopropyl part of 2-methylbutane is defined as the head, the ethyl residue is defined as the tail. Whereas isoprene units in mono-, sesqui-, diand sesterterpenes usually are exclusively linked from head-to-tail, the triand tetraterpenes do contain a centered tail-to-tail linkage (Breitmeier, 2006).

The biosynthesis of activated isoprene (isopentenyldiphosphate (IPP)) can either occur via the acetate mevalonate pathway as well as via activated acetaldehyde and glyceraldehydes-3-phosphate forming 1-deoxypentulose-5-phosphate as precursor for IPP [START_REF] Davis | Cyclization enzymes in the biosynthesis of monoterpenes, sesquiterpenes, and diterpenes in Biosynthesis[END_REF]Breitmeier, 2006). It is reported that terpenoid biosynthesis in plants is compartmentalised with the sesquiterpenes (and triterpenes) being produced in the cytosol via the acetate-mevalonate pathway, and the monoterpenes and diterpenes (and tetraterpenes) getting produced in the plastids via the still incompletely understood mevalonate independent pathway [START_REF] Davis | Cyclization enzymes in the biosynthesis of monoterpenes, sesquiterpenes, and diterpenes in Biosynthesis[END_REF].

Isomerisation of IPP produces

Terpenes of greatest interest regarding wines' organoleptic properties are mainly monoterpenes and sesquiterpenes (extensively reviewed in [START_REF] Marais | Terpenes in the aroma of grapes and wine: A review[END_REF]Rapp andMandery, 1986 and[START_REF] Mateo | Monoterpenes in grape juice and wines[END_REF][START_REF] Mateo | Monoterpenes in grape juice and wines[END_REF], recently elucidated triterpenes [START_REF] Marchal | Recherches sur les bases moléculaires de la saveur sucrée des vins secs -approches analytique et sensorielle[END_REF] and, indirectly via degradation, tetraterpenes (carotenoids).

Monoterpenes

Grape varieties are classified regarding their monoterpene concentrations into 'muscat varieties' (e.g. diverse Muscat varieties, Gewürztraminer) showing free monoterpene concentrations as high as 6 mg/L, 'non-muscat aromatic varieties' (e.g. Riesling, Scheurebe, Müller-Thurgau, Sylvaner, Kerner) showing a concentration range of 1 -4 mg/L and 'neutral varieties' (e.g. Aryan, Sauvignon blanc, Semillon, Chardonnay, Viognier, Bacchus) with a concentration range between the first to classes [START_REF] Rapp | Gaschromatische Untersuchungen über die Aromastoffe von Weinbeeren ii. Möglichkeiten der Sortencharakterisierung[END_REF]Rapp and Güntert, 1985a;Rapp et al., 1985b;Günata et al., 1985a;[START_REF] Rapp | Untersuchung flüchtiger Inhaltsstoffe des Weinaromas: Beitrag zur Sortencharakterisierung von Riesling und Neuzüchtungen mit Riesling-Abstammung[END_REF][START_REF] Mateo | Monoterpenes in grape juice and wines[END_REF].

Most abundant terpenes in grapes and wines are the monoterpene alcohols (monoterpenols) linalool, geraniol, nerol, α-terpineol (van Wijk, 1967a;van Wijk, 1967b;Schreier et al., 1974a;[START_REF] Ribéreau-Gayon | Aroma of Muscat grape varieties[END_REF][START_REF] Schreier | Identification of volatile constituents from grapes[END_REF] and hotrienol [START_REF] Schreier | Identifizierung von 3,7-dimethyl-1,5,7octatrien-3-ol als flüchtige komponente des Trauben-und Weinaromas[END_REF].

Some of them form isomeric oxides like linalool oxide (cis-, transin pyranoide and furanoide form), cisand trans-rose-oxide and nerol oxide [START_REF] Ribéreau-Gayon | Aroma of Muscat grape varieties[END_REF]Schreier and Drawert, 1974a;[START_REF] Simpson | Aroma composition of aged Riesling wine[END_REF]Rapp et al., 1985a;Rapp et al., 1985b). In addition to these major terpenes also monoterpenediols were identified in wines [START_REF] Rapp | 3,7-dimethyl-okta-1,5-dien-3,7-diol -eine neue terpenoide Verbindung des Trauben-und Weinaromas[END_REF][START_REF] Rapp | Neue Monoterpendiole in Traubenmosten und Weinen und ihre Bedeutung für die Genese einiger cyclischer Monoterpenäther[END_REF]Rapp and Mandery, 1986;Versini et al., 1991).

For Vitis vinifera L. cv. Riesling the principal free monoterpenes in grapes and wine are linalool, α-terpineol, geraniol and nerol and the isomeric linalool oxides (Rapp et al., 1985a;Rapp et al., 1985b;[START_REF] Chisholm | Comparison of some french-american hybrid wines with white Riesling using gas chromatographyolfactometry[END_REF]. However, other monoterpenes were considered to contribute to the distinctive Riesling aroma, such as nerol oxide [START_REF] Simpson | Aroma and compositional changes in wine with oxidation, storage and ageing[END_REF], hotrienol (Rapp et al., 1985a;Rapp et al., 1985b), 2-carene and ocimene [START_REF] Skinkis | Comparison of monoterpene constituents in Traminette, Gewürztraminer, and Riesling winegrapes[END_REF].

Terpene esters are also considered to impact on wines' aroma (Feddrizzi et al., 2011). [START_REF] Williams | Novel monoterpene disaccharide glycosides of Vitis vinifera grapes and wines[END_REF][START_REF] Schneider | Monoterpenic and norisoprenoidic glycoconjugates of Vitis vinifera L. cv. Melon B. as precursors of odorants in Muscadet wines[END_REF] as it was already suggested by Cordonnier and Bayonove earlier [START_REF] Marais | Terpenes in the aroma of grapes and wine: A review[END_REF].

Monoterpenes

This fact directly implicates the influence of winemaking practices as alcoholic fermentation by yeasts on free monoterpenes concentration in the wine, whereas an influence of yeast strains on the release potential by glycosidical enzymatic activity during the alcoholic fermentation was more and less significantly established [START_REF] Grossmann | Enzymatische Freisetzung gebundener Aromastoffe[END_REF][START_REF] Delcroix | Glycosidase activities of three enological yeast strains during winemaking: Effect on the terpenol content of muscat wine[END_REF][START_REF] Zoecklein | Effect of native yeasts and selected strains of Saccharomyces cerevisiae on glycosyl glucose, potential volatile terpenes, and selected aglycones of White Riesling (Vitis vinifera L.) wines[END_REF]Zoecklein et al., 1999).

Free and bound monoterpenes are indifferently distributed in grape berries. For Vitis vinifera L. cv. Muscat d'Alexandria 94% of free geraniol and 96% of free nerol is located in the berry skin, whereas linalool is almost equally distributed between the juice (50%) and skin (26%)

and cellular debris (24%), which was shown by Bayonove and co-workers in 1974 [START_REF] Marais | Terpenes in the aroma of grapes and wine: A review[END_REF]. For Vitis vinifera L. cv. Riesling, similar results were obtained, even though showing 60% of the linalool located in the grape skins. Linalool oxides showed equal distribution between mesocarp and berry skin (Versini et al., 1981). For total (free and bound) monoterpenols, these results were either confirmed by showing higher concentration in berry skins (Günata et al., 1985;[START_REF] Wilson | The distribution of free and glycosidically-bound monoterpenes among skin, juice, and pulp fractions of some white grape varieties[END_REF] or not by showing higher values in the mesocarb (Park et al., 1991) of Vitis vinifera L. cv. Muscat of Alexandria (and Vitis lambrusca L. cv. Frontignac and Vitis vinifera L. cv. Traminer). Higher concentrations in berry skins are also reported in a Vitis vinifera L. cv. Chardonnay clone comparison study, which showed differing monoterpenol concentrations regarding the clones (Duchêne et al., 2008).

Therefore pressing conditions, maceration and must heat treatment alter monoterpene concentrations in wine, leading to higher terpene concentrations or alternating concentration pattern of single terpenic compounds in grape must and wine [START_REF] Williams | Novel monoterpene disaccharide glycosides of Vitis vinifera grapes and wines[END_REF]Versini et al., 1981;[START_REF] Marais | Terpene concentration and wine quality of Vitis vinifera L. cv. Gewürztraminer as affected by grape maturity and cellar practices[END_REF].

Monoterpenes are accumulated in the berry in the end of the ripening period and are not coupled to sugar accumulation, whereas in over-ripe berries the terpene concentration pattern alters towards oxidised forms [START_REF] Hardy | Changes in volatiles of Muscat grapes during ripening[END_REF]Günata et al., 1985;[START_REF] Marais | Terpene concentration and wine quality of Vitis vinifera L. cv. Gewürztraminer as affected by grape maturity and cellar practices[END_REF]Park et al., 1991;Kalua and Boss, 2010).

Linalool addition to Botrytis cinerea cell cultures led to tertiary linalool diol isomers and was also found in grape must and wines (Rapp et al., 1986b). A study concerning 'Amarone' style wines' aroma composition showed increased monoterpenediol and monoterpenol oxide concentrations with increasing percentage of botyrized berries (Fedrizzi et al., 2011).

Monoterpene's composition of Riesling wines from different vine growing regions (South Africa, Germany, and Northern Italy) was shown to be a discriminating factor in a comparison study, implicating the influence of climatic conditions like temperature, quantity of sunlight and water availability (Marais et al., 1992a). [START_REF] Reynolds | Fruit maturation of four Vitis vinifera cultivars in response to vineyard location and basal leaf removal[END_REF] showed that total terpene concentrations in grape juice were elevated under warmer conditions as well as for vines with applicated basal leaf removal. Same was shown for Chilean muscat grape cultivars, whereas free and bound terpenes' concentrations were highest in juice from 50% sun exposed grape cluster in comparison to 20% and 100% sun exposure [START_REF] Belancic | Influence of sun exposure on the aromatic composition of Chilean Muscat grape cultivars Moscatel de Alexandria and Moscatel rosada[END_REF]. Similar results were obtained for Croatian Riesling, with the exception of contrary results for linalool oxides' concentrations, which decreased with an increasing number of removed leaves [START_REF] Kozina | Influence of basal leaf removal on the chemical composition of Sauvignon blanc and Riesling wines[END_REF].

The influence of water supply of grape vines during the growing period on the monoterpene concentration in must and wine is little studied.

For [START_REF] Britton | Functions of carotenoid metabolites and breakdown products in Carotenoids[END_REF].

'In most cases enzymatic processes co-exist with non-enzymatic chemical reactions that form the same compounds' [START_REF] Fleischmann | Enzymic pathways for formation of carotenoid cleavage products in Carotenoids[END_REF]. There is a high structural diversity within this group of compounds and they show chemical and sensory properties which make them important contributors to perfume and aroma or other specific functions, e.g. signalling molecules in nature. Examples include sensory signalling of plants to attract insects and other animals to ensure pollination and seed dispersal, pheromone properties of insects, repellent effects against insects, like it is observed for grasshopper keton, and hormone-like growth regulation in plants through abscisic acid [START_REF] Britton | Functions of carotenoid metabolites and breakdown products in Carotenoids[END_REF].

The most widespread -and most abundant in grapes and wine -volatile carotenoid metabolites show a C 13 -carbon skeleton -the so called C 13 -norisoprenoids -which are derived through oxidative cleavage between position C(9) and C(10). Among others, C 13 -norisoprenoids were isolated from a broad range of biological material as leaf products (tobacco, tea and mate), essential oils (rose), fruits (grapes, passion fruit, star fruit, quince, apple and nectarine), vegetables (tomato, melon), spices (saffron, red pepper) and other processed products, such as wine, rum, coffee, oak wood, honey and seaweeds [START_REF] Winterhalter | Carotenoid-Derived Aroma Compounds: An introduction in Carotenoid-Derived Aroma Compounds[END_REF].

C 13 -norisoprenoids can be divided chemically into megastigmanes and non-megastigmanes, referring to their megastigmane carbon skeleton, which can be oxidised in different carbon positions either resulting in the ionone (C9) or damascenone (C7) family [START_REF] Ribéreau-Gayon | Multivariate analysis of conventional profiling data: A comparison of a British and a Norwegian trained panel[END_REF]. Traditionally, C 13 -norisoprenoids lacking an oxygen function in the side chain are referred to megastigmanes. Beside these families, many other structures are identified showing spiroether, acetal and benzofuran properties [START_REF] Winterhalter | Carotenoid-Derived Aroma Compounds: An introduction in Carotenoid-Derived Aroma Compounds[END_REF].

'Although present at only trace levels, sensory thresholds of most norisoprenoids are very low' like 700 ng/L for β-ionone, 200 ng/L for β-damascenone (Ebeler and Thorngate, 2009), 2 µg/L for 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) [START_REF] Sacks | Sensory threshold of 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) and concentrations in young Riesling and non-Riesling wines[END_REF] and 40 ng/L for 1,2,4-trimethylphenyl-3-butadiene (TPB) [START_REF] Janusz | E)-1-(2,3,6-trimethylphenyl)buta-1,3-diene: A potent grape-derived odorant in wine[END_REF]. In the case of TDN, an odour threshold of 20 µg/L was considered to show an undesirable petroleum note in aged Riesling wines [START_REF] Simpson | Aroma composition of aged Riesling wine[END_REF]. TDN concentration below 20 µg/L were suggested to have a positive contribution to varietal aroma of younger Riesling wines and to general Riesling wine quality up to a maximum concentration of 4 µg/L [START_REF] Sponholz | Einfußfaktoren von Klonenematerial und verwendetem Hefestamm auf die Alterung von Riesling Weinen[END_REF].

In grapes and wines a range of norisoprenoids have been identified, whereas some seem to be ubiquitous abundant in a wide range of varieties and others less abundant in just a few varieties.

The potent odorous compounds β-damascenone and β-ionone are found in a wide range of white and red varieties, such as Vitis vinifera L. cv. Riesling, Müller-Thurgau and Scheurebe (Schreier and Drawert, 1974a), Vitis labruscana L. cv. Concord and Catawba (Acree et al., 1981), Vitis vinifera L. cv. Muscat (Etiévant et al., 1983), Chardonnay [START_REF] Sefton | The volatile composition of Chardonnay juices: A study by flavor precursor analysis[END_REF], Melon de Bourgogne [START_REF] Schneider | Monoterpenic and norisoprenoidic glycoconjugates of Vitis vinifera L. cv. Melon B. as precursors of odorants in Muscadet wines[END_REF], Fiano (Ugliano and Moio, 2008), Merlot and Cabernet Sauvignon [START_REF] Sefton | Hydrolytically-released volatile secondary metabolites from a juice sample of Vitis vinifera grape cv. Merlot and Cabernet Sauvignon[END_REF]Ou et al., 2010;[START_REF] Qian | Volatile composition of Merlot wine from different vine water status[END_REF][START_REF] Bindon | Influence of plant water status on the production of C 13 -norisoprenoid precursors in Vitis vinifera L. cv. Cabernet Sauvignon grape berries[END_REF]Lee et al., 2007) and 'Amarone' style wines (Fedrizzi et al., 2011), impacting these wines' aroma. Despite TDN, vitispirane and Riesling acetal are found in several varieties e.g.

Cabernet Sauvignon and Cabernet franc (Eggers et al., 2006;Lee et al., 2007;[START_REF] Bindon | Influence of plant water status on the production of C 13 -norisoprenoid precursors in Vitis vinifera L. cv. Cabernet Sauvignon grape berries[END_REF][START_REF] Sacks | Sensory threshold of 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) and concentrations in young Riesling and non-Riesling wines[END_REF], it is considered that they mainly impact Riesling wines' aroma in young wines as well as in aged wines [START_REF] Simpson | Aroma and compositional changes in wine with oxidation, storage and ageing[END_REF][START_REF] Simpson | Aroma composition of aged Riesling wine[END_REF]Rapp et al., 1985;Marais et al.,1992;[START_REF] Ferreira | Norisoprenoids profile during port wine ageing -influence of some technological parameters[END_REF][START_REF] Sacks | Sensory threshold of 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) and concentrations in young Riesling and non-Riesling wines[END_REF], whereas the direct contribution of the four vitispirane and the two Riesling acetal enantiomers has not been elucidated yet.

Numerous research works have been carried out on the formation of these compounds.

Carotenoids were suggested to be precursors and therefore research on this chemical class was done concerning the grape varieties, their localisation in berries and changes during ripening, showing β-carotene and lutein to be the principal carotenoids present in the berries' skins. Decreasing concentrations during maturation have been effected to climatic conditions and shading [START_REF] Razungles | Etude des caroténoides du raisin à maturité[END_REF][START_REF] Razungles | Grape carotenoids: Changes during the maturation period and localization in mature berries[END_REF][START_REF] Marais | Carotenoid levels in maturing grapes as affected by climatic regions, sunlight and shade[END_REF][START_REF] Kwasniewski | Timing of cluster light environment manipulation during grape development affects C 13 -norisoprenoid and carotenoid concentrations in Riesling[END_REF].

Lutein was shown to be a possible precursor for TDN via chemical thermal degradation in sulfuric acid media [START_REF] Marais | 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN): A possible degradation product of lutein and beta-carotene[END_REF]. Vitispirane, TDN and β-damascenone precursors were shown to increase during maturation [START_REF] Strauss | Development of precursors of C 13 -norisoprenoid flavorants in Riesling grapes[END_REF]. Among other C 13 -norisoprenoids, vitispirane isomers and TDN were generated by hydrolytical cleavage from megastigm-4ene-3,6,9-triol and megastigm-4,7-diene-3,6,8-triol and their presence in grape must, possibly bound as glycosides, was suggested [START_REF] Strauss | Studies on the hydrolysis of two megastigma-3,6,9-triols rationalizing the origins of some volatile C 13 -norisoprenoids of Vitis vinifera grapes[END_REF], which was supported by droplet counter-current chromatography (DCCC) with subsequent GC-MS analysis after hydrolysis (Winterhalter et al., 1990a). Further, the presence of various precursors for isomeric vitispiranes, TDN and β-damascenone from the glycoside fraction were elucidated (Winterhalter et al., 1990b). With the identification of 2,6,10,10-tetramethyl-1oxaspiro [4.5]dec-6-ene-2,8-diol, after enzymatic hydrolysis of a glycoside fraction from a Riesling grape must, a possible precursor for TDN was proposed [START_REF] Winterhalter | of 2,6,10,10-tetramethyl-1-oxaspiro[4.5]dec-6-ene-2,8-diol rationalizing the origin of TDN and related C 13 -norisoprenoids in Riesling wine[END_REF].

In combination to previous work concerning quince fruit [START_REF] Winterhalter | Free and bound C 13 -norisoprenoids in quince (cydonia oblonga, mill.) fruit[END_REF] and the elucidation of 1-(3-hydroxybutyl)-6,6-dimethyl-2-methylene-3-cyclohexen-1-ol as a possible precursor of vitispirane isolated from Riesling wine (Waldmann and [START_REF] W Waldmann | Identification of a novel vitispirane precursor in Riesling wine[END_REF], an integrated pathway was proposed for the genesis of vitispirane, Riesling acetal and TDN, with a hypothetic triol as key intermediate [START_REF] W Waldmann | Identification of a novel vitispirane precursor in Riesling wine[END_REF] (Fig. 1-1). Other studies implicated at least one additional precursor (Versini et al., 1996) and the transformation of Riesling acetal into TDN [START_REF] Daniel | Riesling acetal is a precursor to 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) in wine[END_REF].

Regarding the stereochemistry of enantiomeric Riesling acetals, nearly racemic distribution was shown for leafs of Vitis vinifera L. cv. Riesling and for Riesling wines, whereas enantiomers showed different sensory properties [START_REF] Dollmann | Synthesis and enantiodifferentiation of Riesling acetals[END_REF]. Volatile vitispirane in grape juices showed differing proportions for its four enantiomers, but sensory properties were not reported in this work [START_REF] Herion | Enantiodifferentiation of isomeric vitispiranes[END_REF].

However, C 13 -norisoprenoid levels in grapes and therefore in wines were clearly shown to be dependent on enzymatic activities during berry maturation [START_REF] Baumes | Biogeneration of C 13 -norisoprenoid compounds: Experiments supportive for an apo-carotenoid pathway in grapevines[END_REF][START_REF] Mathieu | A carotenoid cleavage dioxygenase from Vitis vinifera L.: Functional characterization and expression during grape berry development in relation to C 13 -norisoprenoid accumulation[END_REF][START_REF] Mathieu | Biotransformation of C 13 -norisoprenoids and monoterpenes by a cell suspension culture of cv. Gamay (Vitis vinifera L.)[END_REF]. Labelling experiments evidenced that carotenoids were produced from berry set to veraison and that they degrade during the ripening period and are stored as glycosidical bound compounds [START_REF] Baumes | Biogeneration of C 13 -norisoprenoid compounds: Experiments supportive for an apo-carotenoid pathway in grapevines[END_REF]. Furthermore it was shown, that Bortrytis cinerea bioconverted C 13 -norisoprenoids (α-damascenone) into several oxidation products [START_REF] Schoch | Bioconversion of α-damascenone by Botrytis cinerea[END_REF]. In a study concerning different levels of botrytised grapes, an increase in 3-oxo-α-ionol was observed, regarding an increasing percentage of botrytis infection (Fedrizzi et al., 2011). A comparative evaluation of C 13 -norisoprenoid concentrations in Riesling wines from different vine growing regions with different climatic conditions showed higher concentrations of TDN in wines from warmer regions (Marais et al., 1992;Marais et al., 1992a). Nitrogen fertilisation during the growing period was shown to decrease TDN concentrations, whereas it increased β-damascenone concentrations in Riesling wines [START_REF] Linsenmeier | Changes in norisoprenoid levels with long-term nitrogen fertilisation in different vintages of Vitis vinifera var. Riesling wines[END_REF].

Furthermore, grape vine clones as well as yeast strains during fermentation influenced the aging behaviour of Riesling wines regarding their TDN concentrations [START_REF] Sponholz | Einfußfaktoren von Klonenematerial und verwendetem Hefestamm auf die Alterung von Riesling Weinen[END_REF]. Another factor considered is the oxygen uptake during bottling and bottle storage, due to different closure systems [START_REF] Silva | Effet de l'obturateur sur l'évolution de la qualité sensorielle du vin[END_REF].

Few studies were carried out on micro climates' influence on norisoprenoid concentrations.

In Riesling and Chenin blanc an increase of vitispirane and TDN has been observed regarding grape maturity and natural sun exposure (without canopy manipulation) (Marais et al., 1992c). Another study showed increased levels of the C 13 -norisoprenoids TDN and Riesling acetal in white Riesling grapes, but recognised that leaf removal decreased TDN in the berries, albeit being extensively sunlight exposed [START_REF] Gerdes | Effect of sunlight exposure on norisoprenoid formation in White Riesling grapes in Carotenoid-Derived Aroma Compounds[END_REF]. These results

were confirmed in a study on Cabernet Sauvignon, which was defoliated at berry set, showing increasing TDN and vitispirane concentrations with increasing sunlight exposure but a decrease with defoliation (Lee et al., 2007). The influence of leaf removal timing on TDN and vitispirane concentrations in Riesling grapes and wines was elucidated, showing highest concentrations for the treatment defoliated after berry set in comparison to the treatment being defoliated at veraison [START_REF] Kwasniewski | Timing of cluster light environment manipulation during grape development affects C 13 -norisoprenoid and carotenoid concentrations in Riesling[END_REF].

The observed effects of grape vines' water status on C 13 -norisoprenoid concentration in berries of Cabernet Sauvignon, using partial root zone drying (PRD) to establish differences in water status, were observed higher TDN concentrations for PRD modalities, which were correlated with carotenoid concentrations for lutein and β-carotene [START_REF] Bindon | Influence of plant water status on the production of C 13 -norisoprenoid precursors in Vitis vinifera L. cv. Cabernet Sauvignon grape berries[END_REF].

Merlot wines from grapes grown under deficit irrigation showed higher vitispirane concentrations, whereas TDN was not detectable [START_REF] Qian | Volatile composition of Merlot wine from different vine water status[END_REF]. Another study of the same group showed higher β-damascenone concentrations in Merlot wines from deficit irrigated grapes (Ou et al., 2010).

1.5.3

Thiols 'Among chemicals, sulfur-containing molecules and especially thiols are probably the most famous key flavour compounds in many foods and beverages. They are often characterised by sensorial thresholds as low as the ppt [ng/L or ng/kg] level. ' (Vermeulen et al., 2005) Chemically, thiols are sulfur analogues of alcohols, characterised by their functional group, a -SH moiety, which is responsible for their name being derived from the Greek word for sulfur -theion (Vollhardt, 1990). Due to precipitating as salts with low solubility in presence of mercury, thiols are traditionally named mercaptans, originating from the Latin expression corpus mercurium captans [START_REF] Beyer | Lehrbuch der Organischen Chemie[END_REF]. According to today's IUPAC nomenclature rules the functional group should be named with the prefix sulfanyl-, even though the ancient prefix mercaptois still widely used in actual literature.

The role of thiols for the aroma of food and beverages is extensively reviewed in Vermeulen et al. (2005).

A wide range of thiol compounds has been identified in these products being grouped into sulfanyl -acids, -alcohols, -ketones, -esters, -ethers, aliphatic and aromatic thiols, terpenic thiols, acyclic bisulfurous thiols or heterocyclic thiols. Thiols are reported to be abundant in all kinds of products from vegetables (e.g. onion, garlic, and asparagus), beverages (e.g. brewed coffee, beer, wine, orange juice) and fruits (grapefruit, blackcurrant) to other food, such as meat, brooth and dairy products like cheese (Vermeulen et al., 2005).

In the aroma of wine, the group of thiols is subdivided into varietal thiols and non-varietal thiols [START_REF] Ribéreau-Gayon | Multivariate analysis of conventional profiling data: A comparison of a British and a Norwegian trained panel[END_REF][START_REF] Roland | Varietal thiols in wine: Discovery, analysis and applications[END_REF]. Varietal thiols have been suggested

to participate in guava aroma in form of 4-methyl-4-sulfanylpentan-2-one (4MSP) of Chenin blanc and Colombard wines, without proof of its identity in wines from these cultivars [START_REF] Du Plessis | Initial study on the guava aroma of Chenin blanc and Colombar wines[END_REF]. Later, this compound was identified by Bordeaux researchers in wines from Sauvignon blanc contributing to characteristic box tree and broom like aroma of this variety [START_REF] Darriet | L'arôme et les précurseurs d'arôme du Sauvignon[END_REF][START_REF] Darriet | Identification of a powerful aromatic component of Vitis vinifera L. var. Sauvignon wines: 4-mercapto-4-methylpentan-2-one[END_REF]. Additional thiol compounds as 3-sulfanylhexan-1-ol acetate (A3SH) (Tominaga et al., 1996), 4-methyl-4-sulfanylpentan-2-ol (4MSPOH) and 3-sulfanylhexan-1-ol (3SH) and 3-methyl-3-sulfanylbutan-1-ol (3M3SB) (Tominaga et al., 1998a;Tominaga et al., 1998b;Tominaga et al., 2000a) contributing to the characteristic aromatic expressions of Sauvignon blanc wines, were identified subsequently by this research group. Additionally 2-methyl-3-sulfanylbutan-1-ol (2M3SB), 3-sulfanylpentan-1-ol (3SPOH) and 3-sulfanylheptan-1-ol (3SHP) were characterised as impact compounds in sweet wines from botrytised Sauvignon blanc [START_REF] Sarrazin | Odorous impact of volatile thiols on the aroma of young botrytized sweet wines: Identification and quantification of new sulfanyl alcohols[END_REF].

In addition to these compounds, 3-sulfanylpropan-1-ol (3SP), 2-sulfanylethyl acetate (AE2S) [START_REF] Lavigne | Identification et dosage de composés soufrés intervenant dans l'arome 'grillé' des vins[END_REF], ethyl 2-sulfanylpropionate (E2SP), ethyl 3-sulfanylpropionate (E3SP) (Tominaga et al., 2003b), 2-furanmethanethiol (2FM) (Tominaga et al., 2000b;Tominaga and Dubourdieu, 2006), 2-methyl-3-sulfanylfuranthiol (2M3SF) (Tominaga et al., 2006) and benzenemethanethiol (BMT) (Tominaga et al., 2003) were identified in wines, but not considered to be varietal impact compounds [START_REF] Roland | Varietal thiols in wine: Discovery, analysis and applications[END_REF], Lately [START_REF] Nikolantonaki | Identification of ethyl 2-sulfanylacetate as an important off-odor compound in white wines[END_REF] identified ethyl 2-sulfanylacetate (E2SA) as compound to cause off-flavour in Sauvignon blanc wines.

After being identified in Sauvignon blanc wines, varietal thiols have been identified in wines of other white varieties as Scheurebe [START_REF] Guth | Identification of character impact odorants of different white wine varieties[END_REF]), Gewürztraminer, Pinot Gris, Riesling, Muscat, Pinot blanc, Sylvaner (Tominaga et al., 2000a), Sémillon, Petit Manseng (Tominaga et al., 2000a), Bacchus, Melon de Bourgogne [START_REF] Schneider | Quantitative determination of sulfur-containing wine odorants at sub parts per billion levels. 2. Development and application of a stable isotope dilution assay[END_REF] Petite Arvine [START_REF] Fretz | 3-mercaptohexanol: An aroma impact compound of Petite Arvine wine[END_REF]), Albarino, Malvasia, Parellada, Verdejo (Campo et al., 2005), Maccabeu (Escudero et al., 2004), andKoshu (Kobayashi et al., 2010). They were also found in red variety wines from Merlot, Cabernet Sauvignon (Bouchilloux et al., 1998;[START_REF] Murat | 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[END_REF], Grenache (Ferreira et al., 2001) as well as in rosé wines from the Provence region [START_REF] Masson | Key compounds of Provence rosé wine flavor[END_REF].

In Alsatian Riesling wines the most abundant varietal thiol was shown to be 3SH in a concentration range of ~400 -~1000 ng/L, exceeding its perception threshold by the factor of 7 to 16, (Tominaga et al., 2000a). In that work, two late harvested wines showed 4MSP concentrations, exceeding its perception threshold of 0.8 ng/L (determined in ethanolic model solution) (Tominaga et al., 2000a).

Three biogenesis pathways are considered to participate in the formation of 3SH during fermentation, whereas each of them also can act as one step in a multistep pathway. These pathways also seem to be partly valid for 4MSP, while A3SH formation is automatically linked to these pathways, due to being an esterfication product of 3SH and acetate during fermentation [START_REF] Roland | Varietal thiols in wine: Discovery, analysis and applications[END_REF].

The first precursors identified, and therefore the first pathway, were cysteinylated precursors bound as thioether in γ-position to an alcohol-, keto-or aldehyde group, which can release free thiols 3SH, 4MSP and 4MSPOH by means of β-lyase activity (Tominaga et al., 1998c).

As another type of precursors glutathionylated precursors, also bound as thioether γ-position to electrophilic alcohol (3SH) or keto group (4MSP), were identified (Peyrot des Gachons et al., 2002a;Fedrizzi et al., 2009). Furthermore, the degradation of 3-S-glutathionylhexan-1-ol (GSH-S-3SH) by γ-glutamyl transpeptidase showed increasing concentrations of 3-S-L-cysteinylhexan-1-ol (cys-S-3SH) in grape must samples, concluding that γ-glutamylcysteinylated and cysteinylglycinylated precursors for 3SH (glucys-S-3SH and cysgly-S-3SH) are present in grape must (Peyrot des Gachons et al., 2002b).This was confirmed by identification of 3-S-cysteinylglycinylhexan-1-ol in grape juice (Capone et al., 2011a;[START_REF] Capone | Effects on 3-mercaptohexan-1-ol precursor concentrations from prolonged storage of Sauvignon blanc grapes prior to crushing and pressing[END_REF]. In addition to this, it was shown that cys-S-3SH was formed from GSH-S-3SH in grape vine cell cultures (Thibon et al., 2011). These authors hypothesised that GSH-S-3SH acts as a pro-precursor for cys-S-3SH, and therefore for 3SH by means of a plant tissue detoxification process for cell toxic substances (Peyrot des Gachons et al., 2002b;Thibon et al., 2011), whereas others indicated GSH-S-3SH as a direct precursor of 3SH, which corresponds to the second biogenesis pathway (Kobayashi et al., 2010;[START_REF] Roland | Evolution of Scysteinylated and S-glutathionylated thiol precursors during oxidation of Melon B. and Sauvignon blanc musts[END_REF][START_REF] Grant-Preece | Synthesis of wine thiol conjugates and labeled analogues: Fermentation of the glutathione conjugate of 3-mercaptohexan-1-ol yields the corresponding cysteine conjugate and free thiol[END_REF]. The role of stereochemistry of GSH-S-3SH has not been elucidated yet, despite some studies did monitor proportions of (S)and (R)-configured GSH-S-3SH and did show the (S)-configured stereoisomer as the most abundant in grape must, but a nearly racemic distribution of free 3SH in wines (Capone et al., 2010a). The racemic distribution of 3SH was observed also in Sauvignon blanc wines and Semillon wines by Tominaga et al. (2006a). A third alternative pathway implicating direct thiol group transfer on C 6 unsaturated compounds like trans-2-hexen-1-al during double binding hydration. Until now, no sulfhydryl donor could be pointed out, but H 2 S is supposed to be involved or any other compound showing a free thiol function [START_REF] Schneider | Evidence for an alternative biogenetic pathway leading to 3-mercaptohexanol and 4-mercapto-4methylpentan-2-one in wines[END_REF][START_REF] Roland | Varietal thiols in wine: Discovery, analysis and applications[END_REF].

Maturity was found to favour the precursor (cys-S-3SH) concentration in berries of Sauvignon blanc grapes from Bordeaux (Peyrot des [START_REF] Peyrot Des Gachons | Measuring the aromatic potential of Vitis vinifera L. cv. Sauvignon blanc grapes by assaying S-cysteine conjugates, precursors of the volatile thiols responsible for their varietal aroma[END_REF]. Similar results

were observed for Sauvignon blanc grapes from Sancerre and Tours in a study also including GSH-S-3SH [START_REF] Roland | Evolution of Scysteinylated and S-glutathionylated thiol precursors during oxidation of Melon B. and Sauvignon blanc musts[END_REF]. Overripening of grape berries led to 10 fold higher cys-S-3SH concentrations in Sauvignon blanc grapes from Bordeaux (Thibon et al., 2009).

The biogenesis of the thiol precursor is likely to be linked to nitrogen assimilation in the vineyard. Glutathione and cys-S-3SH increased with assimilable nitrogen content in the grape berries [START_REF] Choné | Effect of vine nitrogen status on grape aromatic potential: Flavor precursors (S-cysteine conjugates), glutathione and phenolic content in Vitis vinifera L. cv. Sauvignon blanc grape juice[END_REF][START_REF] Lacroux | Effect of foliar nitrogen and sulphur application on aromatic expression of Vitis vinifera L. cv. Sauvignon blanc[END_REF].

Botrytis cinerea was shown to impact cys-S-3SH concentrations in grape berries, by increasing them in the beginning of the grape berries infection (Thibon et al., 2009). Similar results were obtained for Petite Arvine affected by rot [START_REF] Lott | Quantification of cysteine S-conjugate of 3-sulfanylhexan-1-ol in must and wine of Petite Arvine vine by stable isotope dilution analysis[END_REF] and for Koshu, Chardonnay and Merlot vines under laboratory conditions (Kobayashi et al., 2011). In addition to this, it was shown that wines obtained from botrytised grapes showed a modified ratio on absolute configuration concentration of (R)and (S)forms of 3SH (Thibon et al., 2009).

Only little data is available concerning the effect of microclimate on berries' thiol precursor concentrations. The work of Japanese researchers on seedlings of Koshu, Chardonnay and Merlot grape vines under laboratory conditions, indicated an increasing effect of UV-C irradiation on precursor (GSH-S-3SH and cys-S-3SH) concentrations in grape vine berries as well as in grape vine leaves (Kobayashi et al., 2011).

Moderate water deficiency is considered to favour thiol aromatic potential (Peyrot des [START_REF] Peyrot Des Gachons | Influence of water and nitrogen deficit on fruit ripening and aroma potential of Vitis vinifera L. cv. Sauvignon blanc in field conditions[END_REF]. Water deficiency also was observed to increase GSH-S-3SH and cys-S-3SH in Koshu, Chardonnay and Merlot grape vines under laboratory conditions (Kobayashi et al., 2011).

'Typicité' and 'typicalité'

When it comes to the terminology of typicité, typicalité in the French language it becomes quite confusing, due to both get translated into English by the word typicality. One has to consider that each expression is originating from different languages as well as from the different fields oenology and cognitive psychology.

Development of the term typicité

In the context of oenology the French term typicité was introduced in the years 1979/1980 by French researchers as a neologism for better characterisation of experimental vines derived from differrent terroirs by sensory analysis at the INRA research center in Angers [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF]. The proposition to introduce the concept into AOC regulations was effectuated in 2001 when typicité was introduced as a criterion for organoleptic testing for AOC wines (Ministère de l'Agriculture et de la Pêche, 2001).

At the same time, the term Typizität was introduced into the German language in analogism to the French expression of typicité in the wine sector and found its way into the regulations based on the German wine law according to sensory examinations of wines and as a criterion for labelling the grape variety (BGBL, 1994). On the semantic level, typicité is defined according to the French dictionary 'Le Petit Robert' as the 'totality of characteristics [of a wine], coming from the variety, the land, and the vinification practices' for the domain of oenology (Robert, 1993). In the German equivalent 'Duden' the definition is made as -'characteristic originality; exemplary peculiarity' (Duden, 2010), whereas it does not define the term according to its use in the domain of wine language.

Meanwhile, the concept of typicité is no more limited to the wine sector; it got its universal importance in the whole field of food products, e. g. for the label 'Protected Designation of Origin' [START_REF] Maitre | Sensory typicality of wines: How scientists have recently dealt with this subject[END_REF].

Whereas the French term is more related to terroir, including the grape variety, the German terms' application is mostly limited to the grape varietal expression of a wine. But what kind of concept can be found behind this definition?

The word typicité was formed as a neologism from the word 'typique' like the words 'élasticité' from 'élastique' or 'spécifité' from 'spécifique' [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF]. The same can be concluded analogeously for the German word Typizität from 'typisch' ('Elastizität' from 'elastisch', 'Spezifität' from 'spezifisch'), which corresponds more or less to the French expression typicité. Being originated in the French language, the concept of typicité will be discussed focussing on its French interpretation.

Definition of 'typicité'

i) Nature of similarity

The concept of typicité is the determination of whom or what corresponds to a (predefined) type [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF]. Salette defines the type as the model, the reference, the ideal form, which unifies its properties, its design, its essential characters of a class of being or things of (Salette, 1997).

This can be interpreted in accordance to a well known cognitive psychological concept for categorisation, based on the so called family resemblance, introduced by Rosch and Mervis [START_REF] Rosch | Family resemblances: Studies in the internal structure of categories[END_REF][START_REF] Mervis | Categorization of natural objects[END_REF]). Salette's idéo-type is in correspondence to Rosch's prototype, and his oscillating individual variations can be seen as Rosch's inner categorical gradients of representativeness [START_REF] Mervis | Categorization of natural objects[END_REF]). Salette's definition of type is already the product of an abstraction process in the sense of [START_REF] Mervis | Categorization of natural objects[END_REF], which gets underlined by his remark that typicité can only be defined and recognised through memorised experiences and through precise references routed to the notion of the sensorial image ('La typicité qui ne peut être définie et reconnue qu'à partir d'expériences mémorisées et de références précises conduit à la notion d'image sensorielle [...]' [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF]).

'Typicality' [...] is usually defined as the degree to which an item is perceived to represent a category' and is positive correlated to family resemblance [START_REF] Loken | Alternative approaches to understanding the determinants of typicality[END_REF].

According to these definitions, it was established that typicité, in the domain of oenology, and typicality, as it is used in cognitive psychology, they both refer to the idea of being representative or being typical for a category or a concept and can be used synonymously dependent on their domain of application [START_REF] Ballester | Mise en évidence d'un espace sensoriel et caractérisation des marqueurs relatifs à l'arôme des vins issus du cépage Chardonnay[END_REF].

i) Nature of dissimilarity -role of 'quality' and 'terroir'

In addition to this corresponding sense, Salette points out that typicité is a characteristic value of a product, which allows to differenciate, to identify and to recognise ('La typicité, [...] est une donnée caractéristique du produit: elle permet de le différencier, de l'identifier et de le reconnaître'). This suggests an existing discriminating nature of the notion of typicité in addition to its assigning nature, which itself indicates the concept of typicité to be based on dissimilarities as well as it is based on similarities at the same time. Therefore, a wine presenting a certain typicité would have to to show differenciating properties (dissimilarities)

and assigning properties (similarities) regarding other wines of the same category.

In the concept of typicité, the role of sensory properties is highlighted upon their importance for type determination and their use in the process of attachment of a certain typicité to a certain sample ('L'analyse sensorielle est un outil privilégié pour definir les types, pour déterminer le caractère typique de tel ou tel échantillon et, par conséquent, pour attributer la possession d'une typicité à un échantillon donné') [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF]. According to the above described process, the attachment of typicité would in fact be a measure of quality, due to evaluating a sensory profile of a sample. This interpretation is also used by other authors, which state, that the notion of typicité includes implicitly a judgement of value and that it is a synonym of quality for agricultural food products [START_REF] Sauvageot | Le sciences de l'aliment et le concept de typicité ou le chercheur en sciences de la nature a-t-il quelque chose à declarer sur la typicité d'un produit alimentaire ?[END_REF].

According to Sylvander and Lassaut (cited in Trognon, 2005), there are two types of quality for agricultural products:

• the quality, which is absolute and embodies the conformity of a product to an expected level, regulatory or not regulatory (social consensus; good manufacturing practices). The products can be rated and have to satisfy a minimum standard regarding these fixed parameters of this quality for all consumers.

• a quality, which is relative and expressed by quality-specification and product profile and embodies the presence of specifities or not and the conformity to a particular quality profile. A product profile is somehow its record of characteristic techniques used in elaboration and is characteristic for a certain product. The typicité of a product translates through its particular sensory profile, which distinguishes the product of another.

The latter, the relative, quality approach either embodies or is emodied in the concept of typicité and its distinguishing nature mentioned by [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF], in which the product profile and quality-specifications function as objectifying tools (Trognon, 2005).

Another dimension of typicité, reflected in that relative quality approach, is its relation to the concept of terroir, which can also be defined as a part of the product profile. As Trognon (2005) figures out, the association typicité-terroir is a postulate for the totality of authors ('Pour l'ensemble des auteurs l'association typicité-terroir est un postulat'). In fact the terroir concept is essential, due to being the origin of the concept of typicité [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF].

A terroir itself is defined as a characterised agricultural system, able to produce particular products, to which it grants a certain originality and an own character ('[...] un agrosystème caractérise, dote d'une capacité à donner des produits particuliers auxquels il confère une originalité et un caractère propre') (Salette, 1998, cited in Trognon, 2005).

The French 'Institut National de l'Origine et de la Qualité' (INAO) defines terroir as a defined geographical area, in which a human community gains over the time of its history a collective know how of production, based on the system of interactions between the physical and biological environment and a totality of the human factors. , 2011). This leads to the situation, that terroir cannot exist without typicité and typicité cannot exist without terroir. Furthermore, within a category of products it implicates a distinguishing factor, a nature of dissimilarities, for both, terroir and typicité.

In conclusion, the concept of typicité reflects the notion of wines regarding five parameters:

the originality, the association with a difficult-to-copy terroir, the recognition for professionals (and amateurs) with reflection to a contemporary product image and the taste, and the ability of its conservation. It also integrates the human decisions for all levels of vine growing and vinification and elaboration [START_REF] Dubourdieu | La valeur du vin entre nature et culture réflexions sur le goût mondial et la typicité des vins in Oeno 2011 -9 e Symposium International d[END_REF].

This conclusion merges the factors mentioned above and is consistent to other interpretations [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF][START_REF] Perrin | Contribution méthodologique á l'analyse sensorielle du vin[END_REF]Cadot et al., 2010;Cadot et al., 2012a).

Complementary concepts of 'typicality' and 'typicité'

In international literature typicité is often translated as typicality, leading to a confusing interpretation being limited to its dimension of representativeness derived from the category structure theory, which in the French language is translated as typicalité. As Parr et al.

(2007) mentioned ' [...] the term typicality [is employed] as the best, albeit imperfect, translation of the French notion of typicité [.]' and therefore it could be considered that describing its differentiating nature by the concept of a category's gradient of representativeness maybe is not sufficient. This problem also got pointed out by several researchers from the marketing and consumer science and choices of pragmatical solutions for this problem were proposed for these sectors.

For Giraud (cited in [START_REF] Perrin | Contribution méthodologique á l'analyse sensorielle du vin[END_REF] typicité is a notion which persists between the world of production, where it is originated, and the world of consumption, where it operates. ('[…] la typicité est une notion qui hésite entre le monde de la production, dont elle est originaire, et celui de la consommation, où elle opère'). This leads to a double positioning of typicité:

• from the point of view of the production, it is a feature of a distinctive character of a product, based on a link to a geographic place (typicité) (in the French context the regulations of the 'appelations' will be implicated; generally the concept of terroir would impact)

• from the point of view of the consumer, it can be considered as the degree of representation for an object of a category (typicalité)

In the marketing sector Passebois-Ducros et al. ( 2012) also distinguishes typicality (typicalité) and typicité from the point of view of either professionals or consumers. They conclude that the point of view is determined by either extrinsic or intrinsic factors. She states, that in any case the gustative qualities of a wine are determining factors of the perceived typicality [in the sense of cognitive psychology], but that experts (wine professionals) do not talk about typicality but about typicité, due to taking into account, that a typical wine from a sensory point of view possesses several intrinsic characteristics, which are related to its terroir. Further she points out, that for consumers typicité is simply determined with the place of production (as an extrinsic information) and not to perceived sensory properties and, that the consumer's prototype gets more precise (in intrinsic factors)

the more a consumer gets into the complexity of the concepts of terroir and typicité. She forms the hypothesis, that a consumer estimates wine's intrinsic typicité through extrinsic estimation of typicality (e. g. packaging, production place) for a purchase decision, and that perceived typicité then gets influenced by these (e.g. packaging).

Fig. 1-2 Position of products S1, S2, S3 regarding a categorical prototype P with vectors indicating inter product typicité (Δ) relations (black), product-prototype typicité (Δ) relations (orange), both based on dissimilarities, and product-prototype typicality (Θ) relations (green), based on similarities, in a categorical space defined on similarities (black ellipse) (modified after Trognon, 2005) Trognon ( 2005) presented a theoretical model of product positioning on a market. He distinguishes a product's typicality (typicalité) and typicité in a certain product category based on:

• their similarities, a certain typicality is attached to a product, which, if present at a high degree, acts as a factor of security

• their differences, a certain typicité is attached to a product, which, if present at a higher degree, acts as a factor of originality

Legend :

These two measurements towards a prototype are interacting and lead to different positioning of similar categorical products in a categorical space (Fig. 12).

Inspired by this approach, which was presented by Trognon for a categorical space of a product from the perspective of marketing relevant properties, an adaption for the categorical space of a product from the perspective of sensory properties could open a new dimension of information, which might be helpful to characterise the importance of dissimilarities within a sensory space of a product category. It could be considered that a measure focused on dissimilarities could deliver valuable information on a sensory space of a product's category.

1.7

Measurement of typicality -sensory methodical aspects

When it comes to the question how to determine typicality, it is important to figure out what aspect of this concept exactly should be determined and by whom [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF].

As outlined in the former paragraph, sensory properties are key aspects to the concept of typicality in the sense of typicité in the oenological sector. So how is sensory characterisation of categorical members of a group done so far?

A quite simple approach of typicality measurement is the determination of distinctiveness of various members of various categories, as it can be carried out for wines obtained from different varieties by wine professionals [START_REF] Winton | Relative distinctiveness of varietal wines estimated by the ability of trained panelists to name the grape variety correctly[END_REF]. Such an experiment is, in fact, a measurement of typicality in the sense of similarities, which means a comparative measure towards different prototypes or exemplar models, on predefined categories -the varietal aromatic properties of wines of a certain variety. A direct measure of typicality was presented for Chardonnay wines from the Bourgogne area [START_REF] Moio | Description de la typicité aromatique des vins de Bourgogne issus du cépage Chardonnay[END_REF]. Experienced tasters were asked to rate the presented wines as not typical, medium typical and very typical. In addition, wine tasters were asked to name a maximum of five free chosen descriptors linking citation frequency of descriptors to the degree of typicality. Intentional typicality rating, respecting cognitive psychological fundamental considerations, has been carried out by [START_REF] Ballester | The role of olfaction in the elaboration and use of the Chardonnay wine concept[END_REF] as well as by Parr et al. (2007). Taking into account inner categorical gradients of representativeness with their work on Chardonnay wines from the Bourgogne region as well as for Sciaccarelo wines from Corsica, typicality was characterised (Candelon et al., 2004;[START_REF] Ballester | The role of olfaction in the elaboration and use of the Chardonnay wine concept[END_REF][START_REF] Ballester | Conceptual vs. perceptual wine spaces: Does expertise matter?[END_REF][START_REF] Lorrain | Selection of potential impact odorants and sensory validation of their importance in typical Chardonnay wines[END_REF][START_REF] Jaffré | The Chardonnay wine olfactory concept revisited: A stable core of volatile compounds, and fuzzy boundaries[END_REF]. Typicality was measured on an unscaled bar, which was anchored by 'very poor example' and 'very good example' on the left and the right end respectively. Panellists had to respond to the question if a presented sample is considered to be a good or a bad example for a wine of the category of Chardonnay de Bourgogne. All panellists were highly experienced wine tasters and no further information was asked regarding a sensory profile [START_REF] Ballester | Mise en évidence d'un espace sensoriel et caractérisation des marqueurs relatifs à l'arôme des vins issus du cépage Chardonnay[END_REF][START_REF] Ballester | The role of olfaction in the elaboration and use of the Chardonnay wine concept[END_REF]. Similar procedures were carried out to identify representative botrytised wines from the Sauternes appelation [START_REF] Sarrazin | Recherches sur l'arôme des vins liquoreux de pourriture noble issus des cépages Sémillon et Sauvignon blanc -characterisation de composés clés et étude de leur genese[END_REF], representative red wines from the Bordelais, which was carried out in combination with descriptive analysis [START_REF] Pineau | Spécifité aromatique des vins rouges de Bordeaux -étude de leurs nuances de fruit rouges et fruits noirs[END_REF], Sauvignon blanc wines from New Zealand, France and Austria (Parr et al., 2007;[START_REF] Parr | Evaluation of French and New Zealand Sauvignon wines by experienced French wine assessors[END_REF][START_REF] Green | Sensory and chemical characterisation of Sauvignon blanc wine: Influence of source of origin[END_REF][START_REF] Pineau | Influence of fruit ripeness and juice chaptalisation on the sensory properties and degree of typicality expressed by Sauvignon blanc wines from Marlborough, New Zealand[END_REF], Chenin varietal wines from the central Loire valley in France [START_REF] Perrin | A methodology for the analysis of sensory typicality judgments[END_REF], Cabernet franc wines from the Loire region (Cadot et al., 2010;Cadot et al., 2012a;Cadot et al., 2012b), and also for Italian olive oil [START_REF] Caporale | Consumer expectations for sensory properties in virgin olive oils[END_REF].

In most cases, the total strategy included sorting tasks, in order to verify global distinctiveness of the sample sets [START_REF] Ballester | The role of olfaction in the elaboration and use of the Chardonnay wine concept[END_REF]Parr et al. 2007;[START_REF] Parr | Evaluation of French and New Zealand Sauvignon wines by experienced French wine assessors[END_REF][START_REF] Green | Sensory and chemical characterisation of Sauvignon blanc wine: Influence of source of origin[END_REF][START_REF] Perrin | A methodology for the analysis of sensory typicality judgments[END_REF] and/or descriptive tasks for the characterisation of the most typical samples specifities [START_REF] Moio | Description de la typicité aromatique des vins de Bourgogne issus du cépage Chardonnay[END_REF]Parr et al., 2007;[START_REF] Parr | Evaluation of French and New Zealand Sauvignon wines by experienced French wine assessors[END_REF][START_REF] Green | Sensory and chemical characterisation of Sauvignon blanc wine: Influence of source of origin[END_REF][START_REF] Pineau | Spécifité aromatique des vins rouges de Bordeaux -étude de leurs nuances de fruit rouges et fruits noirs[END_REF][START_REF] Pineau | Influence of fruit ripeness and juice chaptalisation on the sensory properties and degree of typicality expressed by Sauvignon blanc wines from Marlborough, New Zealand[END_REF][START_REF] Perrin | A methodology for the analysis of sensory typicality judgments[END_REF]Cadot et al., 2010;Cadot et al., 2012a;Cadot et al., 2012b;[START_REF] Caporale | Consumer expectations for sensory properties in virgin olive oils[END_REF].

Quantitative Descriptive Analysis (QDA) based approaches

Since the introduction of quantitative descriptive analysis (QDA) into the field of food sensory [START_REF] Stone | Sensory evaluation by quantitative descriptive analysis[END_REF], it was considered as the most appropriate tool for sensorial characterisation of wines' sensory spaces also. This technique was often used for varietal characterisation or terroir and/or establishment of appellations, mostly in the new world, in combination with univariate and multivariate statistical analysis. For example it was applied to characterise these aspects for Cabernet Sauvignon [START_REF] Heymann | Descriptive analysis of commercial Cabernet Sauvignon wines from California[END_REF], Pinot noir [START_REF] Guinard | Descriptive analysis of Pinot noir wines from Carneros, Napa, and Sonoma[END_REF], Chardonnay (McCloskey et al., 1996), Riesling (Fischer et al., 1999) and Sauvignon blanc [START_REF] Lund | New Zealand Sauvignon blanc distinct flavor characteristics: Sensory, chemical, and consumer aspects[END_REF]. Anyway, with this approach, perceptual typicality is measured by forming cluster of similar aromatic profiles, and not by comparison to a categorical prototype. This means, that a degree of typicality is analysed into the data sets' of the samples mostly including analytical data for aroma compounds also, but without any information wether the wines are good or bad examples of the concerning category.

As an extension of the QDA, the 'Just about Right Analysis' (JAR) emerged, taking a prototype into account and measuring the deviation between perceived and conceptual prototypical ideal intensity for each chosen descriptor, positive as well as negative. This method was applied for Dornfelder and Beaujolais, towards a exemplary model, which was defined as the expectations of an ordinary consumer, supposing being represented by an average quality product found in the supermarket (Fischer et al., 2005). In another study Cabernet franc wines from the Loire Valley were evaluated towards wine professionals prototype from the Loire Valley region (Cadot et al., 2010;Cadot et al., 2012a;Cadot et al., 2012b). These researchers both applied a combination of direct typicality measurement according to [START_REF] Ballester | The role of olfaction in the elaboration and use of the Chardonnay wine concept[END_REF] on an unscaled bar, JAR -analysis and QDA.

Citation frequency as an alternative to QDA Several characterising tasks have been carried out using citation frequency to describe sensory spaces of wines e.g. for Chardonnay wines from Bourgogne [START_REF] Moio | Description de la typicité aromatique des vins de Bourgogne issus du cépage Chardonnay[END_REF], Pinot noir and Aglianico wines [START_REF] Piombino | Selection of products presenting given flavor characteristics: An application to wine[END_REF], sweet Fiano wines [START_REF] Genovese | Sensory properties and aroma compounds of sweet Fiano wine[END_REF], various Spanish white wine varieties (Campo et al., 2008) and Grechetto wines (Esti et al., 2010). They used either trained panels or oenology students and wine professionals.

A citation frequency-based descriptive method, performed by a well trained panel, turned out to be a convenient alternative to conventional descriptive analysis for odour profiling of Burgundy Pinot noir wines (Campo et al., 2010). When comparing conventional profiling results of a trained panel with results, obtained using free profiling by wine experts, it was demonstrated, that free profiling with a free descriptor generation step can identify wine characteristics that were not considered using a conventional method [START_REF] Perrin | Comparison of conventional profiling by a trained tasting panel and free profiling by wine professionals[END_REF].

The use of panellists having a specialised expertise on the product was shown to favour reliability of results. It was shown, that expert wine consumers matched wine descriptions better to a set of wines than non-expert wine consumers [START_REF] Lawless | Flavor description of white wine by "expert" and non-expert wine consumers[END_REF] and that a panel of wine professionals performed better in replicating descriptive terms and distinguishing wine samples than a trained panel of non-wine professionals (Zamora ang Guirao, 2004). These authors also figured out, that experts perceived the samples with reference to their remembered specific features, or, as pointed out by [START_REF] Brochet | Wine descriptive language supports cognitive specificity of chemical senses[END_REF], towards a prototype, which is constructed on the experts' personal experiences and preferences.

'A Not-A' discrimination methodology

Testing differences of general sensory properties in food, is mostly carried out by direct confrontation of confusable products or samples in various variations from triangle testing or duo -trio testing [START_REF] Lawless | Sensory evaluation of food -principles and practices[END_REF]. As an alternative to these methods, the same different methodologies are considered (Lee et al., 2007a;Lee et al., 2007b;[START_REF] Hautus | Variants of A Not-A and 2AFC tests: Signal detection theory models[END_REF]Min-A Kim et al., 2012;[START_REF] Santosa | Roc curve analysis to determine effects of repetition on the criteria for same -different and A Not-A tests[END_REF]. Representing one variation in this category of tests, the A Not-A testing methodology was introduced to food science by [START_REF] Pfaffmann | Variables affecting difference tests in Food acceptance testing methodology[END_REF]. The test does not have a standard form and many different versions of the A Not-A test are reported [START_REF] Lawless | Sensory evaluation of food -principles and practices[END_REF]Lee et al., 2007b). Generally, the term A Not-A test applies to any procedure, where the judge undertakes a familiarisation phase to build a memory of the product A at the beginning of a testing session, and then a set of unknown products is given, of which some are A, and others are not. The task of the judge is to report whether each product presented was A or Not-A (Lee et al., 2007b).

Chapter 2

2 Concept of Riesling wines' typicality

Introduction

Tasted among other wines, Riesling wines are highly recognised by wine tasters regarding their aromatic expression. Multiple aroma active compounds were shown to be present in Riesling wines and were already correlated with their aromatic expression (Schreier and Drawert, 1974a;[START_REF] Rapp | Gaschromatische Untersuchungen über die Aromastoffe von Weinbeeren ii. Möglichkeiten der Sortencharakterisierung[END_REF][START_REF] Simpson | Aroma composition of aged Riesling wine[END_REF]Rapp andGüntert, 1985a: Chisholm et al., 1994;Tominaga et al., 2000a;[START_REF] Smyth | The compositional basis of the aroma of Riesling and unwooded Chardonnay wine[END_REF][START_REF] Skinkis | Comparison of monoterpene constituents in Traminette, Gewürztraminer, and Riesling winegrapes[END_REF].

In that way Riesling wines' terpenes pattern was used for differentiation from other varieties (Rapp and Güntert, 1985a),C 13 -norisoprenoids were identified to be imparted in the bottle aging aroma of Riesling wines also known as 'kerosene aroma' [START_REF] Simpson | Aroma and compositional changes in wine with oxidation, storage and ageing[END_REF] and powerful thiols were identified in Riesling wines also (Tominaga et al., 2001a).

Until now, no systematic study was carried out to relate 'what is typical for a Riesling wine' from a sensory point of view with analytical data considering such a broad range of aroma compounds like acetic acid esters, ethyl esters, terpenols, terpenol oxides, C 13 -norisoprenoids, low boiling sulfur compounds and varietal thiols.

As a tool, the concept of typicality was chosen in order to select good examples of Riesling wines and to distinguish them from bad examples, using the methodology proposed by [START_REF] Ballester | The role of olfaction in the elaboration and use of the Chardonnay wine concept[END_REF].

Additionally, it is considered, that the A Not-A test procedure, even if not in accordance with the family resemblance theory of Rosch, could be used for sensory typicality determination, as a kind of sorting task. The question, a judge would have to respond to when a wine gets presented is: 'Is the wine part of a certain conceptual category (in this case typical Riesling wine), or not?' This test represents a categorical In/Out test, when the familiarisation procedure in the beginning of the session is replaced by sufficient experience of the panelists with knowledge of the product, like wine professionals have.

The global objective of this survey is to study the universality of the Riesling wines' aromatic concept in a German-French binational study, using two different panels of wine experts performing both two different methods and then link these results to instrumental analytical data regarding aroma active compounds.

In the sensory part of this study: i) both panels and their performances on the sensory task were monitored and were evaluated.

ii) an alternative testing method was applied and compared to the standard method for typicality testing.

iii) both panels' results were confronted and the validity of an universal aromatic typical Riesling wine concept was validated by comparison of the data.

Results of the instrumental analytical part were linked to the results of the sensory part of this study by different univariate and multivariate statistical methods, in order to point out aroma compounds involved in perception of Riesling wines' typicality.

2.2

Material and methods

Chemicals and consumables

All solvents used for the purpose of extraction, were from HPLC graded purity (99.9%) or were freshly destilled. Acetonitrile for analysis of cysteinylated and glutathionylated precursors were suitable for high resolution mass spectrometry. They were purchased at different suppliers upon laboratories geographic situation (Carl Roth Laborbedarf, Karlsruhe, Germany; VWR, Darmstadt, Germany; VWR, Fonteney sur bois, France). Gases used for gas chromatography (Hydrogen; Helium, Nitrogen) have been purchased from Air Liquide (France) or Linde Gas (Germany) upon Laboratory's situation. Water indicated as H 2' O in the methods was from ultra-pure quality (Millipore ® / MilliQ ® Quality).

Standard compounds and other chemical products

Standard compounds and other chemical products are presented in the tables 2-1 to 2-6 sorted by analytical methods.

Wine samples

In total 41 commercial mostly monovarietal white wines from different geographic origins and varieties were analysed regarding their sensory and chemical attributes (Table 234567).

2.3

Chemical analysis

General wine composition

A range of parameters in wines were measured by means of a FTIR-inferometer using an 'OenoFoss TM ' (Foss, Hilleroed, Denmark). Parameter included, were total soluble solids (TSS) in °Brix, reducing sugars in g/L, pH, total acidity as g tartaric acid/L for berry extracts and grape juice (must) and ethanol concentration in vol. %, reducing sugars in g/L and total acidity as g tartaric acid/L for wines. Samples were analysed at the Department Wine Chemistry and Beverage Research at the Geisenheim Research Center.

2.3.2

Analysis of aroma compounds ('Kaltron-method'): higher alcohols, esters and terpenols

Sample preparation for 'Kaltron' extracts

According to Rapp et al., 1994 modified by Fischer and[START_REF] Rauhut | Pulse flame photometric detection: An innovative technique to analyse volatile sulfur compounds in wine and other beverages in State-of-the-art in flavour chemistry and biology[END_REF] (not published):

10 mL of the sample (wine) were given into a 10 mL falcon tube (orange cap) using a piston-driven air displacement pipette (Eppendorff). 2 g of sodium chloride (NaCl) were added. 5 µL of the internal standard solution from 2,6-dimethylhept-5-en-2-ol (DMH) and cumene (c (DMH) = 1188 µg/L; c (cumene) = 107 µg/L) were added to each sample using a 10 µL micro syringe (Thermo-Fischer). 100 µL of 1,1,2-trichloro-1,2,2-trifluoroethan (Kaltron) was added using a piston-driven air displacement pipette and agitated for 20 min on an agitation device (Intelli-Mixer; NeoLab, Germany). After centrifugation (3000 rpm; 1700 x g; 8 min) (Megafuge 1.0, Heraeus Instruments) the organic phase was removed using a glass capillary pipette and dried by 50 mg sodium sulfate deposited on glass wool in an Eppendorff pipette tip. For gas chromatography 2 µL were injected. Ions (m/z) and equation for identification and quantification are indicated in Appendix 15.

Instrumental settings for 'Kaltron' extracts analysis

Instrumental settings are given in Table 2-8:

2.3.4

Analysis of low boiling sulfur compounds

Sample preparation for low boiling sulfur compound analysis

The sample preparation was carried out according to [START_REF] Rauhut | Pulse flame photometric detection: An innovative technique to analyse volatile sulfur compounds in wine and other beverages in State-of-the-art in flavour chemistry and biology[END_REF], modified by Irmler et al. (2008). Compounds analysed and calibration parameters for quantification are listed in Appendix 17.

Chromatographic conditions for low boiling sulfur compound analysis

Chromatographic conditions were applied according to [START_REF] Rauhut | Pulse flame photometric detection: An innovative technique to analyse volatile sulfur compounds in wine and other beverages in State-of-the-art in flavour chemistry and biology[END_REF], modified by [START_REF] Inao Irmler | Cloning and characterization of two Lactobacillus casei genes encoding a cystathionine lyase[END_REF].

2.3.5

Analysis of varietal thiols

Sample preparation for thiol extract analysis

For selective extraction of volatile thiols from wine the method described by Tominaga and Duburdieu (2006) was applied.

Preparing anion exchange resin column

To prepare the anion exchange column DOWEX ® 1x2 (50 -100 mesh; 1,5 x 3 cm) was reactivated with 0.1 M HCl and washed with H 2 O until the eluate showed pH 6. The activated resin was transferred to a flash chromatography glass column (20 cm x 1 cm ID; upside:

NS 14; bottom: Teflon rotation tap) to build a 5 cm column bed. This column was rinsed two times with 10 mL H 2 O.

Selective extraction of volatile thiols

To 50 mL of centrifuged wine (3000 rpm; 1600 x g; 10 min) containing 50 µL of internal standard solution 100 µg/L 1-methoxy-3-methyl-3-sulfanylbutane (MMB) and 1000 µg/L 6-sulfanylhexan-1-ol (6SH), 7.5 mL of the solution containing p-HMB (2.3.5.2.2) was added and stirred for 1 min using a magnetic stirr bar on a multi agitation plate (600 rpm; 1 min).

After that, the pH was adjusted to pH 7 by drop wise addition of the pH adjusting solution (2.3.5.2.1) and the pH-meter. This mixture was agitated to form the thiol-p-HMB-complex at pH 7 for 10 min at 600 rpm.

After agitation the sample was percolated through the anion exchange resin column (2.3.5.3) to fix the thiol-p-HMB-complex on the resin. Then the column was washed with 50 mL of an acetate buffer solution (2.3.5.2.3) before releasing the volatile thiols from the column by replacing them in the thiol-p-HMB-complex with L-cysteine through percolating of 60 mL of an elution solution (2.3.5.2.4).

This aqueous solution of selective enriched volatile thiols was extracted twice by liquid-liquid extraction using dichloromethane (4 mL, 3 mL) and using 500 µL of ethyl acetate as mediator

during the first extraction. The organic phases were reunified and dried over anhydreous disodium sulfate (~ 1 g) and concentrated under a nitrogen gas stream to 50 µL. 2 µL of this extract were injected for gas chromatography. Ions (m/z) and equation for identification and quantification are indicated in Appendix 18.

Chromatographic conditions for thiol extract analysis

Instrumental settings are given in Table 2-10:

2.3.6

Analysis of free and bound terpenes and C 13 -norisoprenoidspotentially volatile terpenens and norisoprenoids (PVTN)

For the analysis of free and bound monoterpenes and C 13 -norisoprenids in berry extracts a modified solid-phase extraction (SPE) approach using XAD-2 resin equivalent SPE cartridges (Günata et al., 1985) and following gas chromatography coupled to mass spectrometry was adapted by replacing the enzymatical release of aglycones by acid hydrolysis using the procedure described by [START_REF] Kotseridis | Quantitative determination of free and hydrolytically liberated β-damascenone in red grapes and wines using a stable isotope dilution assay[END_REF].

Sample preparation of must and berry extracts for potentially volatile terpenes and C 13 -norisoprenoids (PVTN) analysis

Frozen must samples and berry extracts were defrosted gently at room temperature over night prior to analysis and were centrifuged (Megafuge -Hereaus, Germany) (3000 rpm; 1600 x g; 10 min) in 50 mL falcon tubes (VWR, Germany).

50 mL and 10 mL of musts and berry extracts respectively, were spiked with octan-3-ol and 2,6-dimethylhept-5-en-2-ol (DMH) as internal standards (c (octan-3-ol) = 50 µg/L and c (DMH) =25 µg/L), for free monoterpenes and C 13 -norisoprenoid analysis before being loaded on to solid phase extraction cartridges containing 500 mg styrene-divenylbenzene polymer.

SPE cartridges (Phenomenex © , Strata SDB-L © ) were preconditioned with 5 mL pentane/dichloromethane (2/1; v/v), 10 mL of methanol, 10 mL of methanol/H 2 O (1/1; v/v) and 10 mL of H 2 O. After washing with 10 mL of H 2 O the cartridge was dried under nitrogen flow (~100 ml/min) prior to the elution of free monoterpenes and C 13 -norisoprenoids using 5 mL of pentane/dichloromethane (2/1; v/v). The eluate was dried by means of anhydrous disodium sulfate and concentrated to the final volume of 50 µL under a gentle nitrogen flow.

2 µL of that extract were injected for gas chromatographic analysis.

For bound monoterpenes and C 13 -norisoprenoids the cartridge was eluted using 10 mL of ethyl acetate. This fraction was evaporated to dryness under vacuum using a rotary evaporator (BÜCHI, Switzerland) (water bath temperature 40 °C; p = 138 kPa). The residue was resolved in 5 mL 0. ,121,136,139,142,157,172,175,190,121,135,142,149,157,164,172,177,

2.4

Sensory analysis

Sensory panel

The German panel comprised 11 wine professionals and researchers (5 female and 6 male), who were highly experienced in wine sensory analysis, due to their participation in weekly tastings with descriptive tasks at the Geisenheim Research Center, which are often related to research projects concerning white wines, especially Riesling wines.

The French panel comprised 10 wine professionals and researchers (3 female; 7 male) who were highly experienced in wine sensory analysis also, due to regularly tastings with descriptive tasks for red and white wines, especially for Sauvignon blanc style wines, at the ISVV Bordeaux.

No special training on descriptors was carried out prior tasting sessions for none of the both panels.

Methodology

A Not-A test

A set comprising 30 wines (wine choice for each panel given in Table 2.7) was evaluated in a first session by the panelists in 5 randomised batches comprising 6 wines by each panel. In each batch of 6 wines a minimum of one non-Riesling wine was presented. Every wine was assessed one time. The wines were presented in dark tasting glasses (ISO, 1977) covered with petri dishes in an air-conditioned (20 °C) tasting room equipped with individual booths. 20 ml of each wine was served at 14 °C in randomised manner to obtain different sample order for each panelist to avoid order effects. The assessors were asked to answer the question, whether the sample tested orthonasally is a Riesling wine or not.

Measurement of typicality and free choice descriptor frequency

According to a modified procedure of [START_REF] Ballester | The role of olfaction in the elaboration and use of the Chardonnay wine concept[END_REF] the same sets of wines tested in the first session (2.4.2.1) were presented the same way to the judges in 2 additional tasting sessions on two different days. The panellists therefore were asked to rate typicality regarding Riesling wines after othonasal testing on an unstructured 10 cm anchored scale with 'not typical' on the left end and 'very typical' on the right end. In addition to this, the panellists were asked to name descriptors for each wine. Though a list of Riesling descriptors was provided, the assessors were free in descriptor choice. Descriptors were given in German by the German panel and in French by the French panel.

2.4.3

Statistical methodology

Data transformation -descriptor families

The free chosen descriptors from both panels were translated from German and French into English descriptors by the panel leader. 19 major descriptor families were formed deducted from the 'aroma wheel for German white wines' (DWI, 2008), Fisher andSwoboda (2005), Campo et al., (2008);Campo et al., (2010) and [START_REF] Jaffré | The Chardonnay wine olfactory concept revisited: A stable core of volatile compounds, and fuzzy boundaries[END_REF] upon discussion with the panellists (Appendix 1). Citation frequencies were calculated on these descriptor families.

Analysis of panel performance

2.4.3.2.1 A Not-A test -Chi-square (χ 2 )

and Fishers exact test

Chi-Square (χ 2 ) proportions and Fishers exact test were calculated to evaluate the panels' and the single judges' performances respectively. A recognition frequency was calculated for each sample over the two assessments.

Typicality rating -data normalisation

Relative typicality values (T) were computed by normalising each value on each judge's personal scale with:

Mean values of T from each judge of both repetitions were used to compute the means and the standard deviation for each sample. This method of normalisation was used for further statistical calculations in order to respect the importance of normalisation, which is reported to be important for multivariate statistical methods (McEvan and Schlich, 1991).

Principal Component Analysis -panels' homogeneity

Principal Component Analysis (PCA) was carried out on panelists' typicality ratings for both panels including both repetitions using the R-software [START_REF] Lê | FactomineR: An R package for multivariate analysis[END_REF].

Repeatability of typicality ratings

Repeatability r im of the panel was calculated with:

1 using:

1 / 1 /

Descriptor family reproducibility

Descriptor family repeatability in both repetitions for each panellist in both panels was calculated using the average reproducibility index (R i ) (Campo et al., 2008;Campo et al., 2010):

1 2 / 2.4.3.3 Panel comparison 2.4.3.3.1 Generalised Procrustes Analysis (GPA)
In order to compare the sensory concepts of the two panels a Generalised Procrustes Analysis (GPA) was carried out with the 'Commandeur Method' using XLStat ® (Addinsoft, Andernach, Germany) on the total citation frequencies of the two sessions, relative typicality ratings (T) ,and the A Not-A test derived recognition frequencies for the 18 intersecting wine samples from both panels' data sets. CCA was applied on both total (Riesling and non-Riesling wines) as well as on both inner categorical (only Riesling wines) data sets from the 2 panels with user defined settings using XLStat TM (Addinsoft). Wine samples were defined as 'sites' and descriptor family citation frequency and Riesling wines recognition frequencies (from A Not-A test) were specified as 'objects', whereas volatile compounds' concentrations and relative typicality ratings (T) were computed as quantitative data. Factors' filter were set to a minimum of 80%. The variables used for CCA were chosen in the PLS section (2.4.3.5.2.1). For the permutation statistics, the number of permutations was set at 1000 with a significance level of 5% (α = 0.05).

Interpretation of the results was done according to ter Braak and Vandenschot (1995).

Results and discussion

To obtain reliable sensory product characterisation, two essential requirements are obviousa good panel performance and an adequate methodology.

In order to ensure these requirements in this study, an evaluation of both panels' performances regarding the global aromatic typicality appreciation of dry Riesling wines and regarding the applied descriptive tasks was done.

In order to verify the methodical approach, two methods of typicality determination, based on different principles, were compared by means of linear correlation.

2.5.1

Panel Performance -measurement of typicality

Repeatability of measures

Regarding dry Riesling wines direct typicality rating, the panels' repeatability was characterised by means of the average of all r in (r im ), which itself represents the deviation of the mean from the mean normalised typicality rating of a sample.

For the German panel r im is 0.16, whereas for the French panel it is 0.37. A value of 0 is interpreted as a very good repeatability, whereas a value of 1 represents a very poor repeatability.

Despite both panels show generally good repeatability for direct Riesling' wines typicality ratings (Fig. 2-1.), single wines were rated differently in both panels. Whereas the German panel showed no good repeatability for the wines RIPF and RINZ the French panel showed higher variation in the rating of the typicality of the wines GTAL, RIAL1, RIAL2, RIAUT1, RINA2, RIRH10. For the German panel RIAL7 was assessed only once, due to strong corky off-flavour for the bottle used in the second session. Problems like this could explain why some wines were rated not in the same way in two sessions. Being assessed from different bottles, differences apart from off-flavours can occur from one bottle to another, due to transport conditions or closure issues (e.g. cork quality or leak tightness of screw caps).

Most of the wines showing great variability were purchased through retailers and therefore storage and transport conditions were not monitored personally. To evaluate the two panels inter individual consistency for Riesling wines' typicality principle component analysis (PCA) was carried out separately on the two panels' data sets, containing relative typicality scores for the two panels for all wines. The first two principal components (PC) explained 65.87% and 43.53% for the German and the French panel respectively. This difference in explained variance suggests a greater agreement in the German panel than in the French panel, which is presented graphically in Fig. 2-2. However, in both cases, the panellists all rate the wines' typicality not inverse along the first dimension. For the French panel Judges B and H rated typicality differently on the second and the third dimension of the PCA, whereas these two dimensions explained only 15.6 % and 12.08 % of the total variance). These results show that the German panel ratings were homogenous, whereas differences between the ratings of the French panel were more important, as already deduced from the PCA in 2.5.1.2.1. In this alternative sensory task to direct typicality rating, both panels were able to distinguish Riesling wines from non-Riesling wines to a highly significant degree.

2.5.1.3

The German panel members showed slightly higher agreement of 'what' is a Riesling wine like, than the French panel members. This verifies the results of the direct typicality ratings (2.5.1.3.1). Additionally χ 2 -values could function as statistical characteristic for the ability of a single subject or a whole panel to differentiate categories.

RIRH1 RINA1 RIAUT1 RIMO1 RIRH6 RIRH4 RIAL1 RINA2 RIAL3 RINZ RIAL5 RIRH3 SBBX GTAL RIAL6 RIRH2 RIRH5 RIAL2 PGAL RIAL7 RIAL4 RIRH7 RIRH11 RIRH10 RIRH9 SBNZ SBAL RIRH8 RIAUT2 RIAUT2 RIRH8 SBAL SBNZ RIRH9 RIRH10 RIRH11 RIRH7 RIAL4 RIAL7 PGAL RIAL2 RIRH5 RIRH2 RIAL6 GTAL SBBX RIRH3 RIAL5 RINZ RIAL3 RINA2 RIAL1 RIRH4 RIRH6 RIMO1 RIAUT1 RINA1 RIRH1 RIRH1 RINA1 RIAUT1 RIMO1 RIRH6 RIRH4 RIRH13 RIRH12 RIAL3 SBSA2 RIMO2 RIRH3 SBBX CHAUS RINZ RIAL8 RIRH2 RIRH5 SBBX2 RIPF RIAL7 SBSA1 RIMO3 RIRH11 RIRH14 RIRH9 SBNZ CHRCH RIRH8 RIAUT2 RIAUT2 RIRH8 CHRCH SBNZ RIRH9 RIRH14 RIRH11 RIMO3 SBSA1 RIAL7 RIPF SBBX2 RIRH5 RIRH2 RIAL8 RINZ CHAUS SBBX RIRH3 RIMO2 SBSA2 RIAL3 RIRH12 RIRH13 RIRH4 RIRH6 RIMO1 RIAUT1 RINA1 RIRH1 a) b) 2

2.5.2

Discussion on panel performance and methodology comparison concerning the measurement of typicality Two different sensory methodogical approaches led to the deduction of a clear evidence of a varietal sensory space for Riesling wines at a very high level of significance for the German panel and a little less significant for the French panel.

The observed higher agreement on Riesling wines typicality within the German panel in comparison to the French panel might be explained according to the theory of family resemblance (Rosch and Mervis, 1975). The German panels' high agreement on Riesling wines' typicality can result from the formation of a distinctive prototype (idéo-type). In comparison to that, the prototype for the French panellists was less pronounced and showed more fuzzy borders than the category, which was formed by the German panel, which is more often exposed to Riesling wines. This would be confirmed by hypothesis of refining a prototype and adjustment of category boundaries depending on the habitual exposure to a product [START_REF] Brochet | Wine descriptive language supports cognitive specificity of chemical senses[END_REF].

Furthermore, this would be in accordance to the results from earlier studies, where panellists, which frequently were exposed to the concerned product, generally showed a better performance on typicality ratings on a certain product than those being not frequently exposed to that product [START_REF] Ballester | Conceptual vs. perceptual wine spaces: Does expertise matter?[END_REF][START_REF] Yusop | Sensory evaluation of chinese-style marinated chicken by Chinese and European native assessors[END_REF]. The German panellists are likely to be more frequently exposed to Riesling wines, than the panellists from Bordeaux, as they participate in far more sensory tasting sessions concerning Riesling wines than the French panellists do.

Anyway, the introduction of Pinot gris and Gewürztraminer wines might influenced the total rating behaviour of the French panel regarding Riesling wines' typicality rating, as the same Riesling wines tested orthonasally were presented in a different context, which can be seen as a different olfactory setting. The influence of the setting and the context on typicality rating of a product was already observed in another more general study on packaging [START_REF] Blijlevens | The importance of being 'well-placed': The influence of context on perceived typicality and esthetic appraisal of product appearance[END_REF].

The results of the Pearson product-moment correlations between the results obtained by the applied methods could be interpreted also in this way. For the German panel inner categorical differences are much more evident than for the French panel. The correlation for the total data set is stronger for the German panel and is still strong, after removing the non-Riesling wines, whereas it is not significant for the French panels' data. For the French panel it can be imagined that the panellists associate Riesling wines' typicality to those wines, whose sensory concept they are not that familiar with. For example, the Bordeaux panel will have more expertise on Sauvignon blanc style white wines and on red wines. Therefore it could be considered that the strategy of the French panellist was, to check first, if the wine to be rated, is a member of those better known categories or not. And if it is not, it would probably be a Riesling wine, due to being in a sensory testing session, which is asking for Riesling wines' typicality. This could explain the lack of correlation between direct and frequency based measurement results for the data sets only containing Riesling wines, but

showing correlation if non-Riesling wines, especially Sauvignon blanc style wines are included.

Panel performance on descriptive task

Regarding the descriptive task of describing aromatic expression of the wines by free chosen descriptors, it is essential to monitor the panels' performances on this task for a reasonable interpretation of the obtained results. Therefore the inter panel semantic diversity and the inner panel repeatability of descriptor citation was evaluated.

Descriptor families -choice of descriptors

The German panel used 154 different descriptors, whereas the French panel used 134 different descriptors. In total 173 single descriptors were applied by both panels, 111 of these were commonly applied. These descriptors were grouped into 19 families shown in Appendix 1. Slightly different descriptor numbers were used in some of the odour families, depending on the panel.

Whereas in the German panel the descriptors blackcurrant, elderberry and gooseberry were named regarding the fruits of these plants, the French panel used the descriptor blackcurrant with respect to the vegetative parts of the plant (e.g. blackcurrant wood, blackcurrant bud)

and the descriptors elderberry and gooseberry not at all. For the descriptor family citrus fruit, the German panel applied less different descriptors than the French panel, which used a broader range of descriptors. A similar effect was observed for the descriptor family dried / candied fruits, when the French panel used more different discriptors than the German panel. Inversely, the German panel used more terms for the descriptor family fermentative aroma.

In conclusion, there was a high agreement among applied descriptors of both panels.

However, some variability was observed for single descriptor families.

Descriptor families -average reproducibility index (R i )

To monitor individual panelists' and total panel performance, applied descriptor families' average reproducibility indices (R i ) were calculated for single judges representing single measurement units as well as for the total panel considered to be one unit of measurement (Table 23456789101112). In contrast to Campo et al. (2008), discrimination was undertaken neither for descriptors and descriptor families nor for single judges concerning further data exploitation.

Individual reproducibility for judges, expressed as R i , ranged from 0.1 to 0.36 in the German panel and from 0.02 to 0.39 in the French panel, representing a mean of 0.2 for the German panel and a mean of 0.28 for the French panel. Therefore, the shown individual repeatability was relatively low for individual judges from both, the German and the French panel.

Interestingly, the French panellists generally showed higher reproducibility, than the German panelists did.

Regarding the two panels as one unit of measurement, R i 's were 0.59 and 0.68 for the German and the French panel respectively, higher reproducibility is reflected for the performance of the French panel. Parr et al., (2007).

Generally, there was a good consistency between the two panels concerning the applied descriptors. However, results also showed some differences in the use of descriptors.

The use of different descriptors could be associated with a different 'odour-library' which often is dependent on geographic origin of the panelists. This would be reasonable, due to 'odours frequently evoke idiosyncratic, autobiographical memories, which are often learned in childhood' (Chu and Downes, 2000; cited by Parr et al., 2002). Also semantic memory is assumed to be based on a person's general knowledge and experience with an odourant (Savic and Berglund, 2000; cited by Parr et al., 2002).

Especially the fact, that the German panel was more limited for citrus fruit descriptors and that in another way the French panel did not use elderberry and gooseberry as descriptors, can be discussed in that direction. From a German point of view, elderberries and gooseberries are more abundant in domestic gardens than lemon trees in various variations are.

In fact, it could be shown in intercultural studies that odourants which are not particularly familiar to panelists are difficult to identify and that shifts in odour category boundaries might be explained by cultural factors, such as familiarity with specific odours [START_REF] Chrea | Semantic, typicality and odor representation: A cross-cultural study[END_REF].

Another study observed 'richness of language' as an influential factor to explain differences in the sensory characterisation of jellies between two countries [START_REF] Blancher | French and Vietnamese: How do they describe texture characteristics of the same food? A case study with jellies[END_REF].

However, it can be considered, that this should not be a major factor between German and French panels. It has to be remarked that these factors were revealed in studies comparing Asian and western cultures (Vietnamese, French, North Americans), but to a smaller extent comparable effects can exist between western cultures (Risvik et al. 1992).

Lower mean R i observed for the Geisenheim panel did reflect less good reproducibility for the descriptors citations in comparison with the French panel. However, the German panels' mean value was still considered above the exclusion criterion for individual panellists proposed by Campo et al. (2008). It has to be mentioned that both panels have not undergone a specific training and that therefore the use of descriptors was surprisingly stable.

Even if single judges' repeatability was shown to be relatively poor, the global R i 's for both panels were shown to be 0.59 and 0.68, corresponding to 59% and 68% of descriptor family repeatability for the named descriptors for the German and the French panel respectively.

This suggests that, when working with highly experienced wine tasters, a common sense of vocabulary is available, especially within a panel, which is used to work together for a longer period of time, which was the case for both panels in this study.

This would be a practical implication of the assumption that 'wine professionals working with similar products [...] There was a high agreement in the products' characterisation on a semantic level, but it was observed, that in some cases different descriptors seemed to be attached to a certain odour.

Regarding each panel's repeatability for descriptor usage, relatively poor repeatability was observed for individual judges, but good repeatability was observed for the whole panels' performances, showing tendentially better performance for the French panel (2.5.3.2).

Both sensory panels were qualified to fulfil the demanded tasks, as both methods to rate typicality in combination with the demanded descriptor task turned out to be suitable for characterisation of the sensory concept of typical dry Riesling wines.

2.5.6

General sensory concept of typical Riesling wines

German panels' and French panels' concept of typical Riesling wines

A very simple way of comparing the sensory concept of Riesling wines' typicality of two panels, and therefore if the same Riesling wine is appreciated as a typical Riesling wine, is to plot the results of Riesling wine typicality ratings of wines tested by both panels. Both panels were able to hierarchize the wines being presented according to their typicality and both panels discriminated non-Riesling wines, especially Sauvignon blanc style wines, from Riesling wines. Even if rated at a different typicality level, two out of three Riesling wines rated as most typical in one panel were rated among the three most typical Riesling wines in the other panel as well (Fig. 2345). For the German panel, descriptor families' frequencies vegetal (r=-0.764; p<0.0001), sauvignon (r = -0.755; p < 0.0001), Ribes ssp. / Sambucus ssp. (r = -0.675; p < 0.0001), fruity (r = 0.631; p = 0.0001), white fruit (r = 0.479; p = 0.007), yellow fruit (r = 0.658; p < 0.0001) and minerality (r = 0.595; p = 0.001) showed significant correlation to relative typicality ratings in the total data set (Appendix 5). Correlations observed in an exclusively Riesling wines containing set, were fruity (r = 0.590; p = 0.003), citrus fruit (r = 0.556; p = 0.006), yellow fruit (r = 0.476; p = 0.022), sulfur (r = -0.588; p = 0.003), and off-flavour (r = -0.459; p = 0.027) (Appendix 6).

For the French panel, descriptor families' frequencies vegetal (r = -0.504; p = 0.005), sauvignon (r = -0.612; p = 0.0001), citrus fruit (r = 0.692; p < 0.0001) correlated significantly with typicality ratings in the total data set (Appendix 6), whereas for the Riesling set descriptor families citrus fruit (r = 0.492; p = 0.015), MLF (r = -0.456; p = 0.025), and off-flavour (r = -0.479; p = 0.018) were significant (Appendix 8).

For German panelists Riesling wines' typicality was shown to be associated with fruity, white and yellow fruit odours. Including non-Riesling wines, which show distinctive varietal aroma such as Sauvignon blanc wines do, Riesling wines typicality is also associated to minerality.

The French panel mostly detected citrus fruit descriptors in Riesling wines' with high typicality ratings.

Comparing the obtained results, German and French panelists agreed that the abundance of citrus fruit odours increased with Riesling wines' typicality, if tested wines were compared to Riesling wines only. Additionally, the German panelists did smell more fruity and yellow fruit odours, like peach or apricot, in wines being rated as more typical. Both panels clearly associated vegetal and Sauvignon blanc related descriptors to wines showing poor Riesling wines' typicality.

Multivariate methodology -Generalised Procrustes Analysis (GPA)

As a multivariate tool to compare sensory data of different panels, concerning their sensory concept of a product, Generalised Procrustes Analysis (GPA) can be used and interpreted regarding three statistical characteristics, the so called 'transformations': scaling, translation and rotation (Table 2345678910111213). Despite being optimised for quantitative sensory data (from Quantitative Descriptive Analysis or Free Choice Profiling), it can also be applied for frequenced data as obtained in this study, due to lacking accessible alternative. The resulting visualisation might not be optimal for this kind of data but it can provide a good overview of the two sensory spaces anyway.

To compare the sensory concepts described by both panels, GPA was applied on the two data sets of mean sensory values of the intersecting samples (18 out of 30 wines) evaluated by both panels. The first two dimensions of the consensus model explained 71.5% (56.9% and 14.5% respectively) of the total variance.

All three transformations performed in the GPA showed a significant effect. Significance for the scaling transformation (p < 0.001) uncovered the panels' usage of different ranges of the measurement scale (Risvik et al., 1992), which in this case means a differing citation frequency range for single descriptor families by the whole panel. For example it was observed that in the German panel's data for the family sauvignon the range was 0 -22 and in the French panel's it was 0 -10. In an opposite way, the descriptor family citrus fruit ranged from 0 -4 for the German panel and from 0 -8 for the French panel, the descriptor family floral ranged from 0 -5 for the German data and from 0 -10 for the French data respectively. The second significant effect was observed for the translation transformation (p < 0.0001) explaining that both panels used different levels of the measurement scale (Risvik, 1992), which indicates in this case differing citation frequency levels of single descriptor families for the whole panel. This effect can be demonstrated by the descriptor family fruity which ranged from 1 -10 for the German panel and from 4 -16 for the French panel. For wines RIAUT1 and RIAUT2 the descriptor family frequencies were rated at 7 and 10 by the German panel whereas the French panel rated them at 15 and 16. For the sample SBNZ the descriptor family frequency for this descriptor was 1 for the German panel and 4 for the French panel respectively. Finally the rotation transformation was significant (p = 0.006), which means that the panels were using different expressions and descriptors to describe the same samples. It was expected, that due to the sorting of descriptors, some variance in the semantic descriptor choice was already removed. Even though, this value uncovered a difference in the usage of descriptors for certain odours between the two panels. From the bi-plot of the visualisation for the first two dimensions of GPA and its correlation table, it becomes evident that there is a good agreement for the descriptor families vegetal, sauvignon, yellow fruit, floral, aging notes and for relative typicality ratings.

However, disagreement was observed for the descriptor families herbs, Ribes ssp. / Sambucus ssp., citrus fruit, tropical fruit, minerality and off-flavour (Fig. 2-6 / Table 234567891011121314).

The most abundant differences in the descriptor family's correlation ( projection, whereas German typicality ratings co-correlated also with minerality and the French typicality ratings did additionally co-correlate with the citrus fruit descriptor family.

In the samples plot (Fig. 234567) it got evident that both panels discriminated the non-Riesling wines SBBX and SBNZ from the Riesling wines. Generally, Riesling wines accumulated, but the distincitive aromatic profiles of single wines were characterised by both panels in a similar way as it was observed for the the wines RINZ, RIAL7, RIRH6, or RIMO1, by their positions in samples plot.

These results are not exactly the same as obtained from univariate comparison (2.5.6.2), which can be considered to be caused by the fact that both sets of data is only partially the same, due to GPA being based only on 18 samples out of the 30, which were used for the univariate procedure. Both panels agreed to a high degree on Riesling wines' typicality appreciation. This got evident through both, univariate and multivariate data comparison (2.5.6.1; 2.5.6.2; 2.5.6.3).

In addition to that, both panels' sensory data revealed a consistent sensory concept for typical dry Riesling wines, which is mainly characterised by citrus fruit, fruity and yellow fruit aromatic expression. Typical sauvignon like or vegetal odours are inversely associated with Riesling wines' typicality (2.5.6.2; 2.5.6.3). However, some inter panel differences in descriptor -odour fitting got obvious, especially in the Generalised Procrustes Analysis.

2.5.8

Chemical base of Riesling wines' typicality For the German panel's total data set significant correlations with dimethyl sulfide (DMS) (r = -0.440; p = 0.015), 2-methylpropan-1-ol (r = -0.373; p = 0.042), 3-methylbutanol (r = -0.480; p = 0.007), 2-methylbutanol (r = -0.378; p = 0.039), trans-linalool oxide (r = 0.596; p = 0.001), cis-linalool oxide (r = 0.450; p = 0.013), α-terpineol (r = 0.411; p = 0.024), nerol oxide (r = 0.553; p=0.002) and nerol (r = -0.369; p = 0.045) were observed. For the French panel's total data set significant correlation were observed with methanethiol (r = 0.394; p = 0.035), hexanoic acid (r = 0.370; p = 0.048), cis-linalool oxide (r = 0.421; p = 0.023), nerol oxide (r = 0.396; p = 0.033), ethyl 2-sulfanylacetate (r = -0.559; p = 0.002), 4-methyl-4-sulfanylpentan-2-one (r = -0.398; p = 0.032), ethyl 2-sulfanylpropionate (r = -0.504; p = 0.005) and ethyl 3-sulfanylpropionate (r = -0.627; p < 0.001). When removing all non-Riesling wines from the data set, for the German panel, 3-methyl-1-butanol ( r = -0.434; p = 0.038), 2-methyl-1-butanol (r = -0.486; p = 0.019), ethyl 2-methylpropanoate (r = -0.524; p = 0.010), ethyl butanoate (r = -0.502; p=0.015), 2phenylethanol (r = -0.507; p = 0.014), diethyl succinate (r = -0.699; p = 0.0001), nerol (r = -0.426; p = 0.041), geraniol (r = 0.530; p = 0.009), β-ionone (r = 0.415; p = 0.049) and 3-sulfanylhexan-1-ol (r = 0.498; p = 0.015) correlated significant with typicality ratings.

When removing all non-Riesling wines, data for the French panel correlations to relative typicality ratings were observed for methanethiol (r = 0.417; p = 0.043), carbon disulfide (r = -0.554; p = 0.005), ethyl acetate (r = -0.528; p = 0.008), diethyl succinate (r = -0.441; p = 0.031), ethyl 2-sulfanylpropionate (r = -0.579; p = 0.003), ethyl 2-sulfanylacetate ( r = -0.600; p = 0.002), ethyl 3-sulfanylpropionate (r = -0.557; p < 0.005), benzenemethanethiol (r = -0.711; p < 0.0001) and 3-sulfanylhexan-1-ol (r = 0.429; p < 0.036).

2.5.8.1.2 Pearson product-moment correlation -Riesling wines' typicality correlated aroma compounds vs. total frequency of descriptor families

A common correlation was identified with the total frequency of a descriptor family for both panels' data, neither for concentrations of terpenol oxides cis-linalool oxide and nerol oxide (Table 2-17), nor for those of the polyfunctional thiol 3-sulfanylhexan-1-ol (Table 2-18). 1995).

An interesting feature of interpretation for sensory results could be the analogism to that of an 'ecological niche' for certain species in ecology (ter Braak and Verdonschot, 1995). Due to the complex nature of odour, it is known that sensory properties do not change linearly with changes in aroma compounds' concentrations and only appear if certain aroma compounds are present in certain concentration ranges and combinations -a 'sensorial niche' in this sense. Therefore CCA is considered to be a useful tool to relate several factors and their importance for an odours perception. Furthermore it can be regarded as a logical extension of Correspondence Analysis. Similar approaches were presented for the correlation of sensory and analytical chemistry data by plotting additional variables into Correspondence Analysis plots (Torres and van de Velden, 2007). This also demonstrates the need of alternatives to Principle Component Analysis (PCA) and Corespondence Analysis (CA) for the combinated presentation of metric and non-metric data.

General properties of the CCA

The CCA-map (Fig. 2345678) was calculated on the German data set comprising only Riesling wines. This data set was chosen, due to showing more significant variation in global typicality ratings within Riesling wines (2.5.1.3.1). The CCA explained 83.11% of the constrained inertia (ci). The first five factors corresponded to 59.12% of the total inertia (ti), which was mostly explained by the first three factors (67.16% and 47.77% cumulative constrained and total inertia respectively). The eigenvalues of F1 (horizontally) and F2 (vertically) are 0.23 and 0.13, respectively; the eigenvalue of F3 (not displayed in Fig. 2345678) is 0.13.

Factor composition

Whereas the first factor (34.08% constrained inertia (ci); 24.24% total inertia (ti)) is dominated by wines showing high values for the off-flavour descriptor family, which can be seen by its contributions (con) (con 0.79) and is slightly influenced by wines showing higher descriptor family frequencies for floral (con 0.04), yellow fruit (con 0.03) and fruity (con 0.03) descriptors, the second factor (19.37% ci; 13.78% ti) is determined by wines showing high ratings for floral (con 0.59) descriptors and those of the families sulfur (con 0.15), aging notes (con 0.09) and vegetal odours (con 0.06). The third factor (13.72% ci; 9.76% ti) is determined by wines showing aging notes (con 0.45), tropical fruit (con 0.10), citrus fruit (con 0.07), white fruit (con 0.06), off-flavour (con 0.06) and minerality odours (con 0.05).

Explanation of sensory descriptor families by factors

The sensory properties' (descriptor family appearance) explanation by the factors can be observed regarding the cos 2 values for each descriptor family and each factor.

Therefore, the first factor explains the cited descriptor families off-flavour (cos 2 0.942), fruity For Canonical Correspondance Analysis (CCA) the wines were defined as sites in an ecological point of view. In these sites (in this study represented by the wines) several descriptors were detected by several panel members, leading, when taking descriptors as species in ecological analogism, to a nominal data pattern for each wine sample, which is comparable to environmental data. In such a model, the metric variables aroma compound concentrations are seen as metric environmental variables. Most variance for each metric variable is observed along the vector with the mean represented in the origin of the plot.

Vectors are forming bi-plots either with the wines or the descriptor families.

Information on favouring conditions for the appearance of a sensory descriptor can be obtained by interpretation of the data by means of a CCA analogously to the ecological niche as a sensorial niche.

Interpretation of wine samples

Regarding the wines, the CCA map (Fig. 2345678) can be interpreted reflecting the wines on the typicality vector. It is observed that wines like RIRH8, RIRH6, RIMO1, RIRH13, RIRH9, RIRH11, RIRH2, RIRH3, RIAUT1, RIPF, RINZ, RIAL3, RIRH4, RIRH14, RIRH1, and RIRH5

showed higher typicality than RIRH12, RINA1, RIAUT2, RIAL8, RIAL7 or than RIMO3, RIMO2.

In the CCA map, RIRH8, RIRH6 and RIMO1 were positioned with increasing 3-sulfanylhexan-1-ol or cis-linalool oxide concentrations, whereas RIRH13, RIRH9 with increasing 3-sulfanylhexan-1-ol concentrations only. The wines RIRH11, RIRH2, RIRH3

were grouped with ethyl butanoate and trans-linalool oxide concentrations. RIRH4 was grouped closer to the vector of nerol oxide concentrations. RIAUT1 grouped with 3-sulfanylhexan-1-ol and cis-linalool oxide.

Despite approximately equal typicality levels for the wines RIPF, RIAUT2, RIRH1, RIRH5, RINZ, RIAL3 and RIRH14, they were all positioned differently. On the one hand for RINZ, RIAL3, RIRH5 and RIRH14, this could be related to increasing nerol oxide, TDN and vitispirane concentrations, on the other hand it could be related to increasing linalool and cis-linalool oxide concentrations for RIAUT2 and RIPF, whereas RIRH1 seemed to be impacted by benzenemethanthiol and dimethyl sulfide concentrations.

The wines RIAL7, RIAL8, RIRH12 were grouped with diethyl succinate and 3-methyl-1-butanol, whereas RINA1 was more related to α-terpineol. RIMO3 and RIMO2

were positioned with high linalool concentrations showing both lower typicality values than the mean value.

Interpretation for descriptor families

Regarding the descriptor families, it can be extracted clearly from the CCA map (Fig. 2345678), that increasing typicality corresponds to increasing general fruity descriptor families such as citrus fruit, white fruit, and dried / candied fruit. Descriptor families like aging notes and tropical fruits were more likely to be present in wines showing higher typicality than the mean value of the data set, as fermentative aroma and yellow fruit did as well. The descriptor families herbs, others, vegetal, sulfur, and floral inversely were shown to be associated with lower typicality ratings under certain conditions.

The interpretation of correlations between the descriptor families and single aroma compounds' concentrations should be done attentionously. It can be considered, that certain concentration ranges of different, maybe multiple aroma compounds are beneficial to the perception of odours and therefore to the naming of a descriptor of a descriptor family and could create a sensorial niche. Following this approach, the CCA can provide some helpful information by including nominal data in contrast to a PCA, which itself is strictly limited to decoupling of linear relations of metric data. Vegetal descriptors have been cited with higher frequency in wines showing higher α-terpineol concentrations, whereas floral descriptors in wines were showing high linalool concentrations. Another example is the odour family of aging notes, which was associated with higher TDN and nerol oxide concentrations in the wines.

The origin of the vectors of a CCA map (Fig. 2345678) is presenting the mean value of each metric variable and therefore certain information is also obtained on the quantity of a variable. So, if the descriptor families are correlated to higher aroma compounds' concentration, the corresponding odours are more likely to appear at a concentration higher than the mean value of a metric variable for that data set, depending on its position in the CCA map.

Co-correlations of metric variables

Regarding the vectors for aroma compounds concentrations in relation to the typicality vector, it can be deduced that typicality is impacted by 3-sulfanylhexan-1-ol and ethyl butanoate, dimethylsulfide and trans-linalool oxide concentrations and is disfavoured by diethyl succinate, 3-methyl-1-butanol, α-terpineol and high linalool concentrations, whereas nerol oxide, benzenemethanethiol, TDN, vitispirane and cis-linalool oxide were positioned indifferently towards typicality.

2.5.9

Discussion on aroma compounds contribution to Riesling wines typicality 2.5.9.1 Univariate methodology

When correlating typicality ratings and aroma compounds' concentrations using the Pearson product-moment method, the concentrations of the monoterpenol oxides cis-linalool oxide and nerol oxide showed significant correlations in the German data set, containing Riesling wines and non-Riesling wines. In the data sets, from which non-Riesling wines were eliminated, a weak, but significant correlation was observed for 3-sulfanylhexan-1-ol, independently for both panels.

The descriptor family of citrus fruit was shown to correlate with Riesling wines' typicality for both panels (2.5.8.1). For the German panel, Pearson product-moment correlation showed a significant correlation between geraniol concentrations and the citrus fruit descriptor family frequency. For the French panel, ethyl butanoate and ethyl hexanoate concentrations did correlate with that descriptor family, but no common correlation was observed for both panels.

Multivariate methodology

Like for the univariate approach of comparing results of two different panels, multivariate tools for pointing out aroma compounds being related to typicality ratings were applied on both panels' total data sets, in order to select common aroma compounds.

Some of these 15 selected aroma compounds, which were considered to impact Riesling wines' typicality, were also observed to correlate within the univariate procedure.

Among the other aroma compounds selected by using PLS regression, higher alcohols (2methyl-1-butanol and 3-methyl-1-butanol), ethylic esters (ethyl butanoate, diethyl succinate), terpenols and terpenol oxides (linalool, α-terpineol and trans-linalool oxide), sulfur compounds (dimethyl sulfide, 4-methyl-4-sulfanylpentan-2-one, and benzenemethanethiol), and norisoprenoids (vitispiranes and TDN) were considered to be important for modelling the

Riesling wines' typicality values, upon their VIP values (Table 2-20).

A major difficulty of aroma compounds concentrations correlation to sensory characteristic is the non-linear nature of flavour perception [START_REF] Meilgaard | Sensory evaluation techniques[END_REF] and the complexity of aroma compounds involved in a certain odour through synergistic effects (Campo et al., 2005). Therefore it was considered to be useful to apply a novel methodology to explore the nature of odour.

A possible implication of the aroma compounds, which were selected upon showing high variation in aromatic expression of typical Riesling wines, was illustrated by applying Canonical Correspondence Analysis (CCA) on the data set of the German panel containing only Riesling wines, with the aroma compounds selected by a comparative PLS regression procedure. It can be considered that such an approach could help to overcome the concerns regarding strong linear correlation of single aroma compounds' concentration and the odour qualities' intensity, which is evoked by some authors (Campo et al., 2005;[START_REF] Meilgaard | Sensory evaluation techniques[END_REF][START_REF] Benkwitz | Identifying the chemical composition related to the distinct aroma characteristics of New Zealand Sauvignon blanc wines[END_REF]. Being interpreted analogously to the ecological niche approach used in ecological science (ter Braak and Verdonschot, 1995) it can be considered to be a sensorial niche. By all means, this approach resulted in similar results compared to univariate data analysis, especially concerning the contribution of 3-sulfanylhexan-1-ol to Riesling wines' typicality. Neverless, it could not answer the question of the contribution of TDN and linalool concentrations towards perceived Riesling wines' typicality, but allowed to picture the context. The descriptor family aging notes, which was strongly associated with increasing concentrations of TDN, showed no tendency to be detected at a higher typicality level, than the mean typicality value of the data set, whereas the descriptor family floral, which was strongly associated to increasing linalool concentrations, showed a tendency to be detected at lower typicality level than the mean typicality value. Both aroma compounds' variations were detected in a concentration range above their sensory thresholds (Darriet et al., 2012;[START_REF] Sacks | Sensory threshold of 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) and concentrations in young Riesling and non-Riesling wines[END_REF], but no direct link was observed to typicality.

Observations for selected aroma compounds' concentrations regarding typicality

Grouping wines regarding their typicality ratings into four groups of atypical (typicality score 0.0 -0.2), less typical (0.2 -0.4), typical (0.4 -0.6) and very typical Riesling wines (>0.6) (Table 2-21) for the German panels' total data set, it was observed that the mean concentration of 3-sulfanylhexan-1-ol was highest in the group of atypical wines, which comprised Sauvignon blanc style wines samples. But the concentration of 3-sulfanylhexan-1-ol increased with the level of typicality from the groups of less typical and typical Riesling wines to the group of very typical Riesling wines, indicating an impact of this compound for typical Riesling odour. For linalool, a very low mean concentration was observed within the group of atypical wines.

The group of less typical wines showed a broad range of variation in linalool concentrations (n.q. (<1 µg/L) to 147 µg/L), whereas the mean concentrations increased with the level of typicality, when the outlier sample containing 147 µg/L linalool was removed. Interestingly, it was observed, that the inner group variation of the linalool concentration diminished with increasing typicality (Fig. 23456789). However, no significant relation was observed between perceived typicality and linalool concentrations. Another interesting observation was made for the compound dimethyl sulfide, which slightly increased with the level of typicality and showed a mean concentration of 13 µg/L in the group of very typical wines. Dimethyl sulfide was reported to create synergistic effects for fruity odours at sub-threshold concentrations of 10 µg/L in mixtures, which contained fruity esters, C 13 -norisoprenoids, and linalool (Escudero et al., 2007;[START_REF] Pineau | Which impact for β-damascenone on red wines aroma?[END_REF][START_REF] Loscos | Release and formation of varietal aroma compounds during alcoholic fermentation from non-floral grape odorless flavor precursors fractions[END_REF].

When computing ANOVA on the single groups for the single variables, no statistical significant difference was observed.

Essential outcomes regarding aroma compounds and Riesling wines' typicality

The data analysis using different tools, from simple linear correlation to multivariate approaches (PLS), led to the conclusion that several groups of aroma compounds impact Riesling wines' aroma and that especially 3-sulfanylhexan-1-ol impacts the perception of dry Riesling wines' typicality. In addition to that, cis-linalool oxide and nerol oxide were shown to correlate to Riesling wines' typicality related descriptors.

The multivariate methodology of applying PLS and subsequently a CCA, in order to extract important aroma compounds and link them to parametric data, as obtained from frequency based descriptive tasks in sensory science, gave interpretable and useful results. This approach was shown to be helpful for the interpretation of complex sensory data and could provide an useful tool in the characterisation of sensory spaces in the future.

However, the role of the monoterpenol linalool and the C 13 -norisoprenoid TDN still remains unclear. Their concentrations showed variation above the sensory odour thresholds and were highly correlated to the descriptor families floral and aging notes. Trognon (see also Paragraph 1.6 and Trognon, 2005), each property of an object can be classified as either a factor of similarity or a factor of dissimilarity.

In such a model, a super-category is defined as a group of objects with common properties.

Therefore, these properties can be seen as super-categorical factors of similarity. Differing properties of these objects building a super-category can be seen as discriminating properties leading to sub-categories and therefore, they are considered to be super-category factors of dissimilarities. By definition, the sub-category forming group of objects has common properties again. These sub-categorical factors of similarity forming properties can comprise super-categorical factors of similarity as well as super-categorical factors of dissimilarity, which then do not differ in the new group formed by objects of the new sub- category. Differing properties of objects in this new formed sub-category again can be defined as sub-categorical factors of dissimilarity. These sub-categorical factors of dissimilarity, theirselves can comprise super-category factors of dissimilarity and supercategorical factors of similarity, which then differ in the group of objects forming the sub- category. The uncertainty of such an approach would be the question upon which extent a difference of a factor of similarity may differ within a category, until it becomes a factor of dissimilarity of a sub-category. Talking about categories, it also has to be considered, that categories can be formed differently. The question 'What is a Riesling wine?' can either be responded by perceived properties, such as sensory attributes in the answer 'A Riesling wine has to taste/smell like ....', or by substantial, natural attributes in the answer 'A Riesling wine has to be made from grapes of the variety Vitis vinifera L. cv. Riesling' representing either a perceived or a natural category. Perceived categories are build up on similarities with a prototype or idéo-type, an exemplary model, by sharing a maximum of perceived properties with it. Therefore, a measurement of perceived categorical typicality would correlate with the measurement of similarities with a prototype, whereas it would not correlate with the dissimilarities. For that reason it might not be an adequate tool to carve out the not similar properties of a product (the dissimilarities), which 'make the difference' between two samples of similar typicality.

One approach to achieve distinction among properties could be to differentiate them in between samples of a natural category into factors of similarity and factors of dissimilarity.

By using simple statistics, significant differences of perceived properties on natural categories can be elucidated. The following combinatorial design should lead to differentiation of a natural categories' property either into a factor of similarity or a factor of dissimilarity -in the case of this study, the sensory attributes of the natural category Riesling wine. The total data set for the total frequencies of the descriptor families of the objects wines, forming the super-category dry white wines, were analysed for significant differences (chi-square (χ 2 ) proportions; α=0.05). Non-significant differences for total frequencies of a single descriptor family were considered to indicate a factor of similarity in the super-category dry white wine, which are underlying a gradient of representativeness in the category according to [START_REF] Rosch | Family resemblances: Studies in the internal structure of categories[END_REF]. Significant differences for descriptor families' total frequencies in the data set were considered to be identified as a factor of dissimilarity of the super-category dry white wine. Subsequently, the sub-category Riesling wine was formed by removing non-Riesling wines from the data set and re-analysing for significant differences in the frequencies of single descriptor families.

Descriptor families showing no significant differences in their frequencies in the Riesling wines' data set, but have been considered to be factors of dry white wines' dissimilarity, can be considered as factors of Riesling wines' similarity, factors of other variety wines' similarity or as factors of other variety wines' dissimilarity. Affiliation to these groups of properties then was determined by either showing significant differences in the sub-category other variety wines, which would result in a factor of other variety wines' dissimilarity or not. Being not identified as a factor of other variety wines' dissimilarity, it leads subsequently to the classification to be either a factor of Riesling wines' similarity or a factor of other varieties wines' similarity, depending on higher absolute values for the frequencies in the data set. Furthermore, factors of dry white wines' similarity theoretically could act as factors of sub categorical similarity (for Riesling or other variety wines) at the same time.

Those ones considered to be factors of dry white wines' dissimilarities showing significant differences for frequencies in the Riesling wines' data, were considered to be factors of Riesling wines' dissimilarity. Finally, this approach leads to patterns of significant results for each descriptor group, which then allows classifying each descriptor family as a factor of similarity or factor of dissimilarity of a certain group of objects. The German panels' total data set showed significant differences for 13 descriptor families regarding their total citation frequencies, whereas six descriptor families showed no differences.

In the French equivalent, significant different total citation frequencies were observed for nine descriptor families, whereas for ten descriptor families no differences were detected. The groups showing significant differences represent the factors of dry white wines' dissimilarity, whereas those not showing significant differences act as factors of dry white wines' similarity.

Subsequently, further χ 2 -statistics were carried out on selected data sets representing the natural categories Riesling wines and non-Riesling wines resulting in classifying the descriptor families as presented inTable 2-22. C 13 -norisoprenoids concentrations of vitispirane isomers and TDN did significantly correlate with the descriptor family aging notes as monoterpenol's linalool concentration did with the descriptor family floral in both panels' data sets.

Discussion on the Riesling wines' typicality related descriptor families

Comparison of categorical typicality -perceived category vs. natural category Both methods, direct correlation of typicality ratings and discriminant statistics on full and partial data sets in order to determine typicality related descriptor families, led to comparable results, as both approaches revealed the descriptor family of citrus fruit as a factor of similarity. Direct measurement of one categories' typicality can be seen as direct measurement of matching properties towards a prototype, and therefore a property's measurement showing high correlation to typicality, is seen as an important factor of similarity by the assessor. This dimension of implicit measurement does normally not impact an approach of distinguishing measured properties of a natural category in either factors of similarity or factors of dissimilarity by statistical characteristics. Whereas in the Pearson product-moment correlation approach with directly measured typicality, only the descriptor family citrus fruit was shown to be correlated with Riesling wines' typicality for both panels. By means of χ 2 -proportion significance testing in the alternative approach, this descriptor family citrus fruit was identified among others (e.g. RIESLING recognition frequency, fruity, yellow fruit, white fruit, tropical fruit, fermentative aroma) to be a factor of Riesling wines' similarity. This was consistent for both panels' data sets. The descriptor family off-flavour was shown to be a descriptor family relevant as a factor of Riesling wines' dissimilarity, due to some Riesling wines showing odours sorted to this group (e.g. reductive, lactic), these odours were not present in wines from other varieties, but they were not considered to be linked to typicality. The recognition frequency RIESLING and the descriptor families fruity and yellow fruit, which were classified as being a factor of similarity by χ 2 -proportion statistics, showed significant correlation to direct measured typicality for the German panel also, but only did to a lesser extent for the French one.

In conclusion then, both methods could be used for choosing typicality related descriptor families in the sense of being factors of similarity, though it has to be considered that the information behind this is based on different categorical boundaries. Whereas both methods indicate the shared properties of a category, the method based on the natural category does not indicate any importance towards a single property, whereas the correlation with a direct measured perceived typicality implicitly acts as a rating of importance for a certain factor.

Therefore the presence of the descriptor family citrus fruit, and to a lower extent fruity and yellow fruit in Riesling wines, can be considered to be more important for Riesling wines' typicality than for example white fruit and tropical fruit are, due to being directly correlated to the measured perceived typicality.

The descriptor families aging notes and floral were considered to be a factor of Riesling wines' dissimilarity by both panels. However, their impact on perceived typicality still is not well understood.

Essential outcomes regarding an alternative approach to typicality

Classification of descriptor families upon their differences in natural categories is shown to be a complementary tool to direct typicality rating and its correlation to descriptive sensory data.

It does not give inverse conclusions on similarity related properties, whereas it gives additional information on the nature of a category's variation, by pointing out factors of dissimilarity of a category. In this case, the approach allows discussing the consequences of variation in the concentrations of the aroma compounds linalool and TDN in the context of aromatic typicality of Riesling wines. The role of these aroma compounds, which can contribute to Riesling wines' aromatic expression, can not be explained in the context of typicality. The factors of dissimilarity in a categorical sensory space are likely to be important for the position of a single object within a group of objects of a category, and therefore influencing the feature of 'being unique', which is an essential feature in the French notion of typicité [START_REF] Salette | La typicité: Une notion nouvelle au service du produit, de ceux qui l'élaborent et de ceux qui le consomment en l'appréciant[END_REF][START_REF] Dubourdieu | La valeur du vin entre nature et culture réflexions sur le goût mondial et la typicité des vins in Oeno 2011 -9 e Symposium International d[END_REF]. How exactly this impacts the measured perceived typicality is not well understood and needs some further attention.

Conclusion

The concept of aromatic typicality was shown to be a very useful and reliable tool to characterise typical Riesling wines' sensory profile by means of different sensory methods, carried out by two different wine experts' panels (a German and a French one). Both panels were able to distinguish Riesling wines upon their typicality from other wines in a repeatable manner and the concept of Riesling wines' typicality was shown to be similar for both groups of judges. Furthermore, the presented frequented methodology, the A Not-A test, showed to be a novel complementary tool for the measurement of a products' typicality. For the descriptive task, both panels showed good repeatability for citation of descriptors from single descriptor families, whereas some differences were observed on semantic level between both panels. A Riesling wine's typicality was shown to be significantly associated to citrus fruit descriptors for both panels, while for the German panel, it was also associated to fruity and yellow fruit descriptors. The concentrations of the polyfunctional varietal thiol 3-sulfanylhexan-1-ol were shown to increase with increasing ratings for Riesling wines' typicality in both panels.

Multivariate data analysis using a combination of PLS and CCA, led to interesting insights into the sensory and chemical space of Riesling wines typicality. It verified the results from univariate data analysis and provided an interesting view on the complexity of the sensory space of Riesling wines and implicated aroma compounds. The quite theoretical approach of dividing the wines' sensory properties into factors of similarities and factors of dissimilarities led to the consideration that the highly variable concentrations of the aroma compounds linalool and TDN could be implicated in Riesling wines' categorical typicality as a feature of being different.

Introduction

Typicality, in the sense of French typicité and terroir is highly correlated by its definition (see also Paragraph 1.6). Terroir is likely to be changed with climate change within its meteorological dimension and therefore this scenario is likely to affect viticulture (see also Paragraph 1.3 and 1.4). Influences through changes in these conditions were observed for various parameters in vines' phenology and resulting fruit quality, whereas no direct impact on typicality influencing properties like aromatic expression and implicated chemical composition was studied.

Most aroma compounds imparting in aromatic typicality of Riesling wines are considered to belong to the chemical families of monoterpenols, C 13 -norisoprenoids and thiols (Chapter 2).

The aim of this part of the study is, to observe the influence of certain viticultural conditions, which are likely to change upon climatologic variation, e.g. drought, irrigation regime and canopy manipulation. Leaf removal could get nescessary in order to improve microclimate in the fruit zone, and therefore impacts of these viticultural variables on these families of aroma compounds were studied. Furthermore precursors' generation in vines and grape berries and their transformation into volatiles in the winemaking process should be studied as well.

Finally the finished wines were evaluated by sensory and instrumental analysis to link viticultural conditions to aromatic perception and to concentrations of impacting marker molecules for the aromatic typicality of Riesling wines.

The experimental design was focused on establishing differences in vines' water status in a vineyard showing low soil water holding capacity by means of drip irrigation. In addition to this, different leaf removal was conducted to diversify microclimatic conditions, which could become necessary in consequence to application of irrigation in viticulture.

3.2

Material and methods

Vineyard

The experimental vineyard was located in the Rheingau Valley on the banks of the Rhine River in Germany and is owned and managed by the winery 'Hessische Staatsweingüter Kloster Eberbach'. It is characterised as a steep slope vineyard (Table 3-1

Viticultural treatments

The experimental setup was realised by the staff of the Department of Viticulture of the Geisenheim Research Centre. In total four different treatments, containing each three experimental replicates, were conducted during three vintages. Generally irrigation was applied during growing season between May and October when pre-dawn leaf water potential (Ψ (PD) ) dropped below the irrigation threshold of Ψ (PD) < 0.3 mPa [START_REF] Gruber | Coupling of plant soil water status at different vineyard sites[END_REF]. Defoliation was carried out on the eastern side of the canopy by manually removing two primary leafs and secondary leafs in the fruit zone.

3.2.3

Viticultural measurements

Grape vines' water status

Grape vines' water status was determined using three different methods: Pre-dawn leaf water potential (Ψ (PD) ) was measured prior to sunrise with a portable pressure chamber (Soil moisture corporation, Santa Barbara, CA, California) according to [START_REF] Scholander | Sap pressure in vascular plants -negative hydrostatic pressure can be measured in plants[END_REF]. Leaves used for measurements (n=8) were covered with plastic bags shortly before excision. The soil water content was measured using capacitance sensors (Diviner 2000, Sentek, Adelaide, SA, Australia) according to [START_REF] Gruber | Coupling of plant soil water status at different vineyard sites[END_REF] and Ψ (PD) was calculated according to [START_REF] Hofmann | Inklim2012IIplus: Einfluss der Klimaentwicklung auf den Wasserhaushalt von Rebstandorten -Möglichkeiten der Modellierung von Steillagenregionen[END_REF].

Carbon isotope ratio -δ 13 C

The samples were prepared according to van Leeuwen et al ( 2010) and analysed at the James Hutton Institute, Invergowrie, DD2 5DA, United Kingdom.

3.2.4

Temperature -calculation of growing degree days (GDD)

The calculation of GDD days was done according to Wiliams et al. (1985) to a base temperature of 10 °C and a maximum temperature of 30 °C.

Canopy micro-climate -'Point-quadrat' measures

For the description of canopy's fruit zone micro climate prior and after defoliation at veraison and at the end of the growing season 'point-quadrat' measurements were conducted using the transects technique according to [START_REF] Smart | Sunlight into wine -a handbook for winegrape canopy management[END_REF].

Samples

Berry samples for maturity measures

For maturity measures in each experimental unit, 100 berries were sampled randomly (50 berries from west exposed and 50 berries from east exposed cluster) on several dates during the ripening period to determine berry weight. Then the berries got pressed in a small scale press under equal conditions to obtain grape juice for analysis.

Berry samples for berry extracts

For each experimental unit 200 berries were randomly sampled from bunches throughout the fruit zone (100 berries from east exposed and 100 berries from west exposed cluster) on different dates during the ripening period. The berries were cut at the pedicel without damaging the berry skin, transferred into polyethylene plastic containers with a capacity for approximately 50 berries and covered with carbon dioxide before getting sealed. The sealed containers were immediately dumped into liquid nitrogen in order to shock freeze the berries without direct contact to liquid nitrogen. These samples then were stored at -18 °C prior to berry extract preparation.

Grape must

Grape must was sampled after harvested grapes were pressed and racked under cellar conditions prior fermentation and kept frozen at -18 °C until being analysed.

Berry extract preparation

To avoid oxidative processes berries were defrosted under a protective gas (nitrogen) and K 2 S 2 O 5 was added, resulting in a concentration of approximately 100 mg of total SO 2 per L berry extract. The berries were minced in a juice mixer for 10 s at the highest speed and then centrifuged (10,000 rpm, 18100 x g, 15 min, 4 °C). The supernatant was aliquoted and stored at -18 °C prior to analysis.

3.2.8

Chemical analysis

Total soluble solids

Total soluble solids (TSS) was determined in obtained grape juice using a handheld refractometer (MHRW -190 ATC; Müller Optronic; Erfurt; Germany) graded in °Oe and transformed into °Brix according to Jakob (2012).

Reducing sugars

The reducing sugars were calculated in g/L from °Oe values according to Troost (1980).

pH

The pH was determined potentiometrically with a combined electrode using a pH-meter (inoLab ® 7110 Serie, WTW GmbH, Weilheim, Germany).

Total acidity

The total acidity (TA) was determined by titration of 50 mL grape juice with 0.1 M NaOH to pH 8.2 and calculated as tartaric acid equivalents.

Primary bound α-amino nitrogen as o-phthaldialdehyde -N-actetyl-L-cysteine derivates (N-OPA)

The N-OPA concentrations were measured according to Dukes and Butzke (1998) using a spectrophotometer and calculated as iso-leucine equivalents. For 50 samples 100.8 mg OPA were dissolved in 5 mL ethanol.

Sample preparation and analysis

The grape juice samples were prepared as indicated in Table 3-3 in disposable UV/VIS cuvettes. Absorbance was measured at a wavelength of λ 340 nm and an optical pathlength of 1 cm using a spectrophotometer (UV/VIS Spectrometer Lambda 2, PerkinElmer, Rodgau, Germany).

Total nitrogen concentration after KJELDAHL -decomposition detected as ammonia

Chemical decomposition of organic bound nitrogen is based on the standard procedure of KJELDAHL [START_REF] Schaller | Praktikum der Bodenkunde und Pflanzenernährung[END_REF].

5 mL of berry extracts or grape juice (must) were used as sample size. To the sample 5 mL of the incineration mixture, comprising 0.48 g Se (black grounded), 14.0 g Li 2 SO 4 (suprapure), 420 mL H 2 SO 4 (conc.), and 330 mL H 2 O 2 (p.a.) were added and this mixture was refluxed until being cleared (180 °C; approximately 3 hours). After cooling down the reaction mixture was then transferred quantitatively through a filter into a 50 mL volumetric flask and was adjusted with H 2 O to 50 mL. This incineration solution was analysed by means of flow injection analysis using a Foss Tecator FIAstar 5000 Analyser (FOSS, Hilleroed, Denmark) according to [START_REF] Schaller | Praktikum der Bodenkunde und Pflanzenernährung[END_REF]. Measurements were carried out at the Department of Soil Sciences and Plant Nutrition at the Geisenheim Research Center.

Free ammonia in grape juice and grape must

Free ammonia [NH 4 ] + was measured through flow injection analysis using a Foss Tecator FIAstar 5000 Analyser (FOSS) according to [START_REF] Schaller | Praktikum der Bodenkunde und Pflanzenernährung[END_REF]. The injection volume for grape juice was 40 µL, H 2 O acted as carrier solvent, 3 M NaOH acted as pH modifier. The indicator solution was prepared according to the suppliers' manual (FOSS). Wavelengths of λ 590 nm and 720 nm were selected. The standard curves were generated using ammonium chloride solutions. Measurements were carried out at the Department of Soil Sciences and Plant Nutrition at the Geisenheim Research Center.

Reduced glutathione

The reduced Glutathion was analysed according to [START_REF] Lavigne | Assay of glutathione in must and wines using capillary electrophoresis and laser-induced fluorescence detection: Changes in concentration in dry white wines during alcoholic fermentation and aging[END_REF] as a monobromobimane (MBB) thiol conjugate. Modifications were applied concerning the stabilisation of the MBB-thiol conjugate and the principle of separation and detection [START_REF] Pons | [END_REF]unpublished).

For stabilisation purposes 40 µL of 70% of trifluoroacetic acid (TFA) was added to the reaction mixture after the derivatisation procedure and left at least for one hour for equilibration. Then the derivatised samples were analysed by means of a C 18 -RP-HPLC-FLD system (Dionex -Fisher Scientific, Illkirch-Cedex, France) using chromatographic conditions presented in Table 3-4.

Phenolic compounds

The samples were membrane filtered (0.45 µm) and were analysed by means of a C 18 -RP-HPLC-PDA system (Dionex -Thermo Scientific, Fisher Scientific GmbH, Schwerte, Germany) under chromatographic conditions shown in Table 3-5 and Table 3-6.

The wavelengths for the identification of catechins and hydroxybenzoic acid compounds were λ 1 : 280 nm, for hydroxycinnamic acids λ 2 : 320 nm and for flavonol glycosides

3-sulfanylhexan-1-ol

The samples were purified by means of reversed phase solid phase extraction and analysed by means of C 18 -RP-UHPLC-HRMS system (Thermo Scientific, Illkirch-Cedex, France) using chromatographic conditions shown in Table 3-7 andTable 3-

Analysis of aroma compounds

For analysis of the aroma compounds in the finished wines, the methods from Chapter 2 were applied.

Harvest and wine making Harvest

The harvest date was decided by the technical staff of the vineyard's estate. All replicates of the viticultural treatment were harvested manually, keeping separated each viticulture treatment. The yield was determined before pressing. Due to technological reasons replicates of each viticultural treatment were pressed together under comparable conditions (press loading, pressing programme, whole cluster pressing). K 2 S 2 O 5 was added to free run juice (50 mg/kg pressed grapes). The pressed juice was settled for two days and the supernatant was racked prior to fermentation.

Vinification

Racked grape musts were measured for reducing sugars, and the musts from the viticultural treatments showing less sugar concentration were adjusted by adding saccharose, to obtain wines of the same ethanol concentrations after fermentation. The vinification was realised in three fold replicated micro scale fermentations for each viticultural treatment and each used commercial yeast strain. 500 g of the grape juice was aliquoted into 750 mL green glass bottles by means of a silicon tube and weighted on a balance to obtain net weight. After rehydrating the yeast in water, the grape juice was inoculated with Saccharomyces cerevisiae yeast strains, either Oenoferm

Freddo TM or Laffort X5 TM , according to suppliers' recommendation. These inoculated bottles were closed with airlocks and incubated at 17 °C. The fermentation induced loss of carbon dioxide (CO 2 ) was monitored daily by weighing. Two weeks after the fermentation, wines were racked into CO 2 -filled bottles and K 2 S 2 O 5 was added corresponding to 50 mg SO 2 /L.

The bottles were sealed by using screw caps and then stored at 15 °C. One set of samples was stored at -18 °C to conserve the status of a young wine and to become analysed later during the project. For the vintages 2009 and 2010 the same procedure was carried out with an increased fermentation volume (1200 g grape must in 1.5 L bottles).

Sensory analysis

The sensory analysis was carried out on the finished wines 12 months after bottling for the 2009 vintage. The sensory testing took place in an air-conditioned sensory room (20 °C)

equipped with single booths. The wines were presented in ISO standardised glasses and cooled to 10 -14 °C prior tasting. On each indicated date the sensory analysis took place at 11:30 CET.

Triangle test

Twelve panellists, experienced in wine tasting, were asked to point out the different sample by orthonasal testing. The wines were distributed randomly for each panellist.

Quantitative descriptive analysis

Twelve experienced panellists were asked to rate the presented wines for the descriptors apple, lemon, grapefruit, melon, peach, apricot, floral, petrol/kerosene, mineral, oxidative and reductive aroma on an unscaled line anchored with 0 and 9 at the left and right end respectively. Standards were provided before the sensory testing session, to adjust panellists' odour fitting to odour perception. Prepared standard samples were given in (p = 0.01) correct answers for the panel of 12 judges (8 male; 4 female) [START_REF] Lawless | Sensory evaluation of food -principles and practices[END_REF].

ii) QDA -one factorial ANOVA was carried out using Sigma Plot TM (Systat Software GmbH, Erkrath, Germany) with viticultural treatments as factor.

3.3

Results and Discussion

3.3.1

General climatic conditions during the growing season, all the quantities were higher than a 30-year-long-period-mean of 364 mm for the corresponding period (Fig. 3-3) (Source: Deutscher Wetterdienst -Außenstelle Geisenheim).

For 2008 more rainfall occurred in March and July compared to the long-period-mean. Less rain in relation to that indicator was observed in May, September and October.

In 2009 a higher rainfall value towards the long term comparison was only measured in June, whereas low precipitation levels were observed in September and October.

In the month of May, July and August of the vintage 2010 high total rainfall is reflected in high precipitation amounts. Only April showed extremely low rain quantity in relation to the long term mean value.

Water status in three years

For irrigation scheduling, pre-dawn leaf water potential Ψ (PD) was measured, because it reflects the instantaneous plants' water status (van Leeuwen, 2010).

A combination of soil moisture derived pre-dawn leaf water potential Ψ (PD) values [START_REF] Lebon | Modelling the seasonal dynamics of the soil water balance of vineyards[END_REF][START_REF] Gruber | Coupling of plant soil water status at different vineyard sites[END_REF][START_REF] Hofmann | Inklim2012IIplus: Einfluss der Klimaentwicklung auf den Wasserhaushalt von Rebstandorten -Möglichkeiten der Modellierung von Steillagenregionen[END_REF] and an integrated Different water potential trends in the three vintages led to different vines' water status classification concerning vines' phenological stages as listed in Table 3-10. The carbon isotope ratio 12 C/ 13 C (called δ 13 C) can function as an integrated indicator for the average vine water status during grape ripening, when measured on grape sugar at ripeness [START_REF] Pineau | Spécifité aromatique des vins rouges de Bordeaux -étude de leurs nuances de fruit rouges et fruits noirs[END_REF], due to the effect of isotope discrimination of 13 C during the photo assimilation of CO 2 and its reduction as a consequence of plants' water deficiency (Farquhar et al., 1989).

The grape musts showed differences in δ 13 C values regarding different irrigation treatments as well as different vintages (Fig. 34567).

Classifying the vines' water deficit during the ripening period regarding The infection of Botrytis cinerea showed differences in vintages 2009 and 2010, whereas in 2008 botrytis infection did not affect grape quality (< 5% for all viticultural treatments). In 2009 no significant differences were observed between the three irrigated treatments, though the non-irrigated control (C) showed a tendency to lower infection. For 2010 the irrigated treatment (I) showed significant higher infection, than the non-irrigated control (C) and the defoliated (IdB) treatments (Table 3.11).

Development of grapes' maturity Berry weight at harvest

A tendency to lower berry weight was observed for the non-irrigated treatments (C) in all vintages, whereas it showed only a significant difference in the 2010 vintage.

For the vintages 2009 and 2010, berries were sampled and their juice was analysed on five and three dates respectively.

In 2009 the sugar assimilation showed a significant difference between the irrigated and nonirrigated treatments during the second half of the berry ripening period. Total acidity (TA) showed significant differences only directly before harvest, between the non-irrigated control (C) and the irrigated (IdB) treatment (Fig. 3-10). In this time of the ripening period a decrease in TA was observed also for the non-irrigated control (C), which was more important than for the irrigated treatments (I, IdB, IdV).

3.3.3

Monoterpenol and C 13 -norisoprenoid concentrations

Monoterpenols in grape must

In the grape musts, obtained from each viticultural treatment, total terpene alcohols (free and acid hydrolysed terpenols including geraniol, α-terpineol, linalool, cis-linalool oxide, trans-linalool oxide) (Table 3-12) showed significant differences for the non-irrigated treatments, except for the 2010 vintage, when no water deficit was detected.

Significant differences were observed for the vintage 2009 regarding the leaf removal treatments. The treatment, which was irrigated and defoliated at flowering (IdB) showed significant higher total terpenol concentration than the irrigated treatment, which was not defoliated at all (I) (303 µg/L and 224 µg/L respectively). On the other hand, the treatment, which was irrigated and defoliated at veraison (IdV), showed no difference in comparison with the irrigated treatment, which was not defoliated (I) (195 µg/L and 224 µg/L respectively). For the vintage 2010 no significant difference was observed regarding the leaf removal treatment. Results are presented in Table 3-12.

Monoterpenol composition of wines after 12 months

For the vintages 2008 and 2009, α-terpineol and linalool concentrations in wines from the non-irrigated control treatments (C) generally were increased in comparison to the wines obtained from the irrigated treatments, which were not defoliated (I). Linalool concentrations then were significantly higher in wines from the non-irrigated control treatments (C), showing concentrations of 64 µg/L, 51 µg/L and 129 µg/L, 87 µg/L respectively. The concentrations of linalool in the wines from the non-irrigated control treatment (C) also were higher than in those wines from the treatments being irrigated and defoliated (IdB and IdV). This effect was less abundant in 2008. Diferences in the results for α-terpineol were not statistical significant.

For the vintage 2010 no differences were observed for the concentrations of α-terpineol and linalool between the wines from the non-irrigated control treatments (C) and the irrigated treatments without leaf removal (I). No difference in the water status was observed for that growing season.

Interestingly, a difference for geraniol concentrations in the samples was observed only for the vintage 2010. The wines obtained from the viticultural treatment, where leaf removal was carried out at flowering and veraison (IdB) showed higher concentrations than those from the not defoliated treatments (C and I).

For all vintages, linalool and α-terpineol concentrations tended to be higher in wines from viticultural treatments being irrigated and defoliated (IdB, IdV), when getting compared to the wines from the treatments being irrigated, but not defoliated (I).

The wines from the defoliated treatments (IdB, IdV) showed significant higher linalool Globally the concentration level of analysed free monoterpenols was highest in wines from the vintage 2009, whereas the wines from the vintage 2010 showed the lowest free monoterpenol concentration level. Results are shown in Table 3-14.

C 13 -norisoprenoids in grape must

For the vintages 2008 and 2009, significant differences between different viticultural treatments were observed for total concentrations of free and acid hydrolysed norisoprenoids (vitispirane isomers and TDN) in grape musts. No differences were observed for the vintage 2010 (Table 345678910111213For the 2008 vintage, total vitispirane and total TDN were significantly higher in the grape must of the non-irrigated control treatment (C) (42.5 µg/L and 4.5 µg/L respectively) than in the one of the irrigated treatment (I) (40.0 µg/L and 1.9 µg/L respectively). In the vintage 2009, the grape must showed high total vitispirane concentration (125.3 µg/L) for the non-irrigated control (C), whereas the total TDN concentration was low as 1.1 µg/L. In grape musts from irrigated treatments (I, IdB and IdV) total vitispirane concentration was lower (46.5 µg/L, 48.7 µg/L and 42.0 µg/L respectively) than in the one of the non-irrigated viticultural treatment (C). The lowest concentration was observed in the grape must obtained from the treatment, which was irrigated and defoliated at veraison (IdV).

For the concentrations of TDN an inverse pattern was observed, showing higher concentrations for grape musts from irrigated treatments I, IdB and IdV (9.3 µg/L, 6.5 µg/L and 26.6 µg/L respectively) than for the grape must of the non-irrigated control treatment C

(1.1 µg/L). The highest total TDN concentration was analysed in the grape must of the irrigated treatment, which was defoliated at veraison (IdV).

Generally, observed concentration levels of C 13 -norisoprenoids were higher for the vintage 2009, than for the vintages 2010 and 2008, which showed the lowest concentration level.

C 13 -norisoprenoid composition in wines after 12 months

After being bottled for twelve months, vitispirane (the sum of isomeric vitispiranes) concentrations did not show any difference in the wines from the different viticultural treatments for the vintage 2008. The concentrations of TDN in these wines were below the limit of quantification of the analytical method (LoQ 0.1 µg/L). The concentrations of vitispirane in the wines from the vintage 2009 showed similar effects and did not differ.

Statistical significant differences in the wines' TDN concentrations were detected regarding some viticultural treatments. TDN concentrations in the wines of the non-irrigated treatment (C) (0.7 µg/L) were generally lower than in the irrigated treatments (I, IdB, IdV) (1.2 µg/L, 1.9 µg/L, 1.6 µg/L respectively). 1,2,3,4,5 LoD: < 0.1 µg/L; Limit of quantification: 1,2,3,4,5 LoQ: < 1.0 µg/L; 6,7 LoD: < 0.05 µg/L, 6,7

LoQ: < 0.1 µg/L

The wines produced from the irrigated and defoliated treatments (IdB, IdV) generally showed significant higher TDN concentrations in comparison to those from the non-irrigated treatment (C). Within the irrigated viticultural treatments, only wines from the treatment defoliated at flowering (IdB) showed significantly higher TDN concentrations in comparison to those from the treatment not being defoliated at all (I).

In the vintage 2010 no significant differences of total vitispirane and TDN concentrations were observed in the wines within the non-irrigated control treatment (C), and the treatment, which was supposed to get irrigated (I). In fact this treatment was not irrigated due to excessive rainfall during the ripening period. The wines from the viticultural treatment, in which leaves were removed at flowering (IdB) showed significant higher total vitispirane and TDN concentrations.

The concentration levels of vitispirane and TDN were generally different in the wines dependent on the vintage, showing the highest concentration for the vintage 2009 and the lowest concentration for the vintage 2008 (Table 3 -14).

Different yeast strains of Saccharomyces cerevisiae used for fermentation showed no significant impact on vitispirane and TDN concentrations for all vintages.

C 13 -norisoprenoid composition in wines after 22 months

After 22 months of bottle aging the vitispirane concentrations in the wines from the 2008 vintage showed significant lower concentrations in the wines from the non-irrigated field trial (C), than in those from the irrigated treatment, which was defoliated at veraison (IdV) (63.9 µg/L and 99.8 µg/L respectively). No significant difference was observed in the wines from the irrigated treatments with and without leaf removal at veraison. The same was observed for TDN, whereas no statistical significant difference was observed, although wines from the non-irrigated treatment (C) tended to contain lower TDN quantities.

For the wines from the vintage 2009, the results were ambiguous, due to high variability in analysed samples. However, there were significant differences for vitispirane concentrations regarding the viticultural treatments. High concentrations were observed in the wines from the irrigated treatment, which were defoliated at flowering (IdB), showing 125.8 µg/L vitispirane isomers. These wines showed significant higher vitispirane concentrations than those of the irrigated treatment, which was not defoliated (I) resulting in 97.2 µg/L. The vitispirane concentrations in the wines obtained from the non-irrigated viticultural control treatment (C) and the treatment being irrigated and defoliated at veraison (IdV) were in between these concentrations (100.2 µg/L and 114.4 µg/L respectively) and were not statistically significant different.

The concentrations of TDN in these wines showed a tendency to lower concentrations in the wines from non-defoliated modalities (C, I) independently from water status, though this difference was not statistically significant.

As for the wines stored for 12 months, the concentration levels of vitispirane and TDN were generally different in the wines depending on the vintage when being stored for 22 months.

The highest concentration level was observed in the wines from the vintage 2009 and the lowest concentration level in the wines from the vintage 2008 (Table 34567891011121314.

Different yeast strains of Saccharomyces cerevisiae used for fermentation showed no significant impact on vitispirane and TDN concentrations in wines for all vintages.

Discussion on monoterpenols in grape must

The influence of the vineyard management like canopy manipulation on monoterpenol and C 13 -norisoprenoid concentrations in the berries, wines and must was extensively studied, whereas only little data is available with regard to the effect of water stress.

Regarding the summed parameter of free and acid hydrolised monoterpenols in grape must, higher concentrations were observed for the treatments grown under water stress (compare 3.3.1.1 and 3.3.1.2).

These findings should be discussed in three directions:

i) concentration of berry monoterpenols in smaller volume of grape juice, due to a smaller berry size and therefore altered skin-juice ratio ii) increase of monoterpenol synthesis or storage, as a response to the vines' water deficit

iii) indirect influence of water status on the monoterpenol concentration by autodefoliation and thereof higher grape cluster sun exposure and temperatures i) concentration of berry monoterpenols in smaller volume of grape juice, due to a smaller berry size and therefore altered skin-juice ratio

Regarding the concentration effect, it is obvious that in the vintages 2008 and 2009 the berry weight, albeit not being statistical significant, was negatively affected by the water deficit, which is in compliance with earlier reported results [START_REF] Hardie | Response of grapes to water-deficit stress in particular stages of development[END_REF][START_REF] Matthews | Phenologic and growth responses to early and late season water deficits in Cabernet franc[END_REF]Ojeda et al., 2002). Therefore, in the same mass grapes, more berries, and therefore more berry surface -namely berry skin -were present in one batch of pressed grapes. This led to the assumption that there was a concentration effect, due to altered skinjuice ratio [START_REF] Marais | Terpenes in the aroma of grapes and wine: A review[END_REF] and / or altered pressing conditions influencing the monoterpenol extraction capacity (Versini et al., 1981).

For vintage 2010, no such effect was observed, despite the smaller berry size in the control treatment (C). This is in accordance with the results of a study on anthocyanins and tannins in Cabernet Sauvignon grapes, which concluded that the sources of variation on berry size (like environmental factors) are the more important factor to determine the berry composition than the berry size itself [START_REF] Nouveau | Berry size and vine water deficits as factors in winegrape composition: Anthocyanins and tannins[END_REF].

ii) increase of monoterpenol synthesis or storage, as a response to the vines' water status

In published literature, increased monoterpene concentrations were observed for Muscat grapes, grown under post-veraison water deficit, independent from the berry size. However, in that study, analysis was undertaken on the headspace of intact berries and the increase was not significant for most of the analysed compounds (El-Ansary et al., 2005).

For Sauvignon blanc [START_REF] Giorgessi | Variation of the vegetative-productive equilibrium of the vine (cv. Sauvignon b.) according to different water conditionings and consequent effects on grape and wine aroma compounds[END_REF] showed an increase of free and bound monoterpenes in the berry skins with an increasing water deficit.

Similar results were observed in trees from Cupressus sempervirens, when an accumulation of glycosidic bound linalool was observed in leaves peaking short time after an induced water stress [START_REF] Yani | The effect of a long-term water stress on the metabolism and emission of terpenes of the foliage of cupressus sempervirens[END_REF]. These authors mention that terpene compounds may have an important role in the process of drought resistance of trees [START_REF] Yani | The effect of a long-term water stress on the metabolism and emission of terpenes of the foliage of cupressus sempervirens[END_REF]. Other results

regarding the terpenoid emission rates of four different Mediterranean plant species (Rosmarinus officinalis, Cistus Albidus, Quercus coccifera and Pinus halepesis) showed lower emission rates as a response to water stress (Ormeno et al., 2007). The same authors observed the change of percentual contribution for single monoterpenes and sesquiterpenes on the total terpenic emission along the duration of water deficit, showing a shift from high sesquiterpene, but also monoterpenol, emission after four days towards monoterpene emission to the end of the eleventh day of the experiment (Ormeno et al., 2007).

These findings suggest, that even short term and already mild water deficit can directly influence the terpenes' metabolisation and possibly the delocalisation in plants and can increase monoterpenol concentrations in grape musts from water deficit driven vineyards.

iii) indirect influence of water status on the monoterpenol concentration by autodefoliation and thereof higher grape cluster sun exposure and temperatures

Water deficit modulates the vines canopy structure in order to limit transpiration, through vigour reduction in the pre-veraison stage [START_REF] Hardie | Response of grapes to water-deficit stress in particular stages of development[END_REF][START_REF] Matthews | Reproductive development in grape (Vitis vinifera L.): Responses to seasonal water deficits[END_REF]Keller, 2005). Furthermore, senescence of leaves can be induced by long term water deficit at the stage of post-veraison also, including recycling of organic matter into other plant organs like fruits (Keller, 2005). This effect was observed during the vintage 2009, when the non-irrigated control basal leaves showed decolouration and abscission took place three weeks before the harvest. Therefore, grape cluster in the non-irrigated control treatment (C) at harvest showed grape berry cluster sun exposure rates comparable to those treatments, which had been defoliated (IdB, IdV). As grape berry sun exposure was shown to affect terpene concentration in berries [START_REF] Reynolds | Fruit maturation of four Vitis vinifera cultivars in response to vineyard location and basal leaf removal[END_REF][START_REF] Belancic | Influence of sun exposure on the aromatic composition of Chilean Muscat grape cultivars Moscatel de Alexandria and Moscatel rosada[END_REF][START_REF] Kozina | Influence of basal leaf removal on the chemical composition of Sauvignon blanc and Riesling wines[END_REF], higher concentrations of monoterpenols in non-irrigated treatments can possibly be explained by this factor. The fact that monoterpenols' accumulation in grape berries was shown to be not coupled to sugar accumulation and is known to be timed at the end of the ripening period, supports this hypothesis [START_REF] Hardy | Changes in volatiles of Muscat grapes during ripening[END_REF]Günata et al., 1985a;[START_REF] Marais | Terpene concentration and wine quality of Vitis vinifera L. cv. Gewürztraminer as affected by grape maturity and cellar practices[END_REF]Park et al., 1991). In addition to that, an increase in berry temperature -possibly through sun exposure -was observed to be associated with higher monoterpenol concentrations [START_REF] Reynolds | Fruit maturation of four Vitis vinifera cultivars in response to vineyard location and basal leaf removal[END_REF][START_REF] Reynolds | Impact of training system, vine spacing, and basal leaf removal on Riesling vine performance, berry composition, canopy microclimate, and vineyard labor requirements[END_REF].

However, with regard to the leaf removal experiments, results for Muscat, Sauvignon blanc and Riesling grapes and wines showed total terpene levels to decrease, if the sun exposure was 100% [START_REF] Belancic | Influence of sun exposure on the aromatic composition of Chilean Muscat grape cultivars Moscatel de Alexandria and Moscatel rosada[END_REF] or 'highly' leaf removed [START_REF] Kozina | Influence of basal leaf removal on the chemical composition of Sauvignon blanc and Riesling wines[END_REF]. Leaf removal at veraison (IdV) in 2009 and leaf removal at flowering (IdB) in 2010 led to equal or even lower total terpene concentrations in the grape musts compared to their irrigated nondefoliated counterpart (I). Grape berry cluster sun exposure rates of these defoliated treatments showed similar levels to those of the non-irrigated control, but showed lower monoterpenol concentrations. Therefore the increase of monoterpenol concentration in grape berry extracts from non-irrigated treatments is not likely to be indirectly influenced by water stress through auto-defoliation and higher grape cluster temperatures.

Discussion monoterpenol composition of wines after 12 months

Like for monoterpenol concentration in grape must as well, results of single terpenols in the wines after finishing fermentation showed a statistical significant increase for the nonirrigated treatments (C), which were grown under higher water deficiency, than the irrigated treatments (I). In contrast to the results for the total monoterpenols obtained in musts, monoterpenol concentrations, especially free linalool, were higher in the wines from the defoliated treatments, than in those from the non-defoliated treatments grown at the same water status. These results are in conformity to other published data [START_REF] Reynolds | Fruit maturation of four Vitis vinifera cultivars in response to vineyard location and basal leaf removal[END_REF][START_REF] Belancic | Influence of sun exposure on the aromatic composition of Chilean Muscat grape cultivars Moscatel de Alexandria and Moscatel rosada[END_REF][START_REF] Kozina | Influence of basal leaf removal on the chemical composition of Sauvignon blanc and Riesling wines[END_REF]. The contrasting tendency for total terpenols in grape must and free terpenols in corresponding wines already was shown in the data of other studies concerning Riesling and different fertilisation quantities. There, the trend for volatile terpenols was in the opposite direction of that of bound terpenols, showing that even under the same total terpenol concentrations, the quantity of free terpenols can be significantly different [START_REF] Webster | Influence of vineyard nitrogen fertilization on the concentrations of monoterpenes, higher alcohols, and esters in aged Riesling wines[END_REF].

In the vintage 2010, the lowest α-terpineol and linalool concentrations were observed in the wines, but higher linalool oxide concentrations of all vintages were detected. Terpenol oxides were observed to be formed in over-ripe berries [START_REF] Marais | Terpene concentration and wine quality of Vitis vinifera L. cv. Gewürztraminer as affected by grape maturity and cellar practices[END_REF]. An increase of linalool oxides was also observed in presence of Botrytis cinerea (Fedrizzi et al., 2011). Both

Viticultural studies 123 can be considered, due to high soluble solids' concentrations and also relatively high infection with Botrytis cinerea in that year in comparison to the vintages 2008 and 2009.

3.3.6

Essential outcomes for monoterpenols and their precursor molecules

In conclusion both, water status and microclimate manipulations, have an important influence on monoterpenol concentrations and their pattern in grape must and wines.

In white wines' vinification decreased berry size, as an effect of water deficit, is presumably a less important factor, due to short skin contact times of grape must during the vinification process. The influence of water deficit on the biosynthesis and the metabolisation of terpenoide compounds is more likely to account for variations in grape musts and wine monoterpenol concentrations.

On the one hand, the effect of leaf removal and sun-exposure is clearly demonstrated in the grape must and in the finished wines, but on the other hand the transformation during vinification remains unclear. Upon the data from this project, it is likely that the ratio of free and bound terpenes in the wines somehow gets modified through viticultural practices.

3.3.7

Discussion on C 13 -norisoprenoids Growing Degree Days values (GDD). An inverse effect was observed for TDN precursors, which were increased in years with higher GDD values. In the finished wines from these viticultural trials the same trend was shown for the vitispirane concentrations after 12 months of bottle storage, whereas again it was not for TDN concentrations.

Under moderate water deficit the potential of acid hydrolysable vitispirane and TDN in grape musts varied with regard to the timing of defoliation (2009: IdB; IdV). This was observed for wines from these viticultural experiments after 12 months and 22 months also, whereas none of these variations was shown to be statistically significant.

In order to interpret these viticultural effects, such as canopy manipulations, water deficit and environmental effects on C 13 -norisoprenoid concentrations in must and wine, the results in grape musts will be considered before discussing C 13 -norisoprenoid concentrations in Comparing the results with the few published data in respect to the influence of water deficit on C 13 -norisoprenoids, the obtained data were contrary to the results obtained for a Cabernet Sauvignon field trial, where water deficit was provoked by partial root zone drying (PRD) [START_REF] Bindon | Influence of plant water status on the production of C 13 -norisoprenoid precursors in Vitis vinifera L. cv. Cabernet Sauvignon grape berries[END_REF]. In the latter work, the concentrations of acid liberated TDN in berry homogenates increased with water deficit. Water deficit was measured as midday stem water potential (Ψ (S) ) and as midday leaf water potential (Ψ (L) ) in that study. The water deficit indicated (up to Ψ (S) -1.1 MPa for irrigated control and Ψ (S) 1.4 MPa for PRD) can be classified as moderate to severe stress for both -irrigated control and PRD -treatments according to the classification scheme of van [START_REF] Pineau | Spécifité aromatique des vins rouges de Bordeaux -étude de leurs nuances de fruit rouges et fruits noirs[END_REF]. Generally it is difficult to compare data from different methods of water potential measurements, as they reflect different situations in the vines' daily water status. Whereas pre-dawn leaf water potential Ψ (PD) is determined in a situation of a stable equilibrium, Ψ (S) and Ψ (L) represent the dynamic status of a transpiring plant [START_REF] Gruber | Coupling of plant soil water status at different vineyard sites[END_REF]. However, the measurement of the midday stem water potential Ψ (S) was shown to be an accurate and robust estimation of the vine water status [START_REF] Choné | Stem water potential is a sensitive indicator for grapevine water status[END_REF]. In addition to this, it can be assumed that the vines' reaction on PRD is different to 'naturally' occurring water deficit and that different Vitis vinifera varieties show different biochemical reactions at equal water deficit levels.

ii) the effect of micro climate manipulation on C 13 -norisoprenoid precursor concentration It has been shown that C 13 -norisoprenoid precursor concentration in grape juice increased with sun exposure (Marais et al., 1992a;Marais et al., 1992c;Gerdes et al., 2002;Lee et al., 2007), but this was shown also to be dependent on the timing of the leaf removal [START_REF] Kwasniewski | Timing of cluster light environment manipulation during grape development affects C 13 -norisoprenoid and carotenoid concentrations in Riesling[END_REF]. [START_REF] Gerdes | Effect of sunlight exposure on norisoprenoid formation in White Riesling grapes in Carotenoid-Derived Aroma Compounds[END_REF] showed an increase of free and bound TDN and Riesling acetal in sun exposed Riesling grapes which have been defoliated at veraison and then shaded by cloth. They showed also that naturally shaded berries had higher TDN levels than those covered by cloth after leaf removal [START_REF] Gerdes | Effect of sunlight exposure on norisoprenoid formation in White Riesling grapes in Carotenoid-Derived Aroma Compounds[END_REF]. These observations are in accordance with the obtained results from the present study for the 2009 vintage. The irrigated treatment, which was defoliated at veraison (IdV) showed higher acid liberated TDN concentration in grape must than the irrigated treatment without leaf removal (I). Grape juices of grapes from the modality where leaves have been removed at the stage of flowering (IdB) did not show different acid hydrolysable vitispirane and TDN potential level in comparison to the corresponding non-defoliated treatment during 2009 and 2010. In comparable studies for Cabernet Sauvignon and Riesling these observations were made as well (Lee et al., 2007;[START_REF] Kwasniewski | Timing of cluster light environment manipulation during grape development affects C 13 -norisoprenoid and carotenoid concentrations in Riesling[END_REF].

iii) the effect of vintage and temperature An effect of vintage and vineyard site was reported on C 13 -norisoprenoid precursor inclusively on carotenoids in grapes and grape musts [START_REF] Razungles | Etude des caroténoides du raisin à maturité[END_REF]Marais et al., 1992a;[START_REF] Marais | Carotenoid levels in maturing grapes as affected by climatic regions, sunlight and shade[END_REF]Lee et al. 2007), but mostly included the factor sunlight as sunhours or microclimate manipulation of the canopy. Therefore it is difficult to separate these two factors and subsequently this should be considered when interpreting this kind of data.

Further discussion was already done under ii).

3.3.7.2

Discussion C 13 -norisoprenoid composition in wines after 12 months and 22 months i) the effect of water status

In this study higher TDN concentrations were analysed in wines obtained from the irrigated viticultural treatments, which were defoliated, whereas a strong tendency towards lower TDN concentrations in the wines from the non-irrigated treatments was observed after 12 months and 22 months of bottle storage. With respect to water deficit in the present Riesling study no significant alternation for volatile vitispirane concentration was detected regarding water deficit in wines after 12 months and 22 months of bottle storage. These results were in contrast to a study of Merlot wines, which were grown under different water status. In that study wines from grapes, grown under a deficit irrigation regime, showed higher concentration for vitispirane, but no results were given for TDN concentrations and the age of the wines was not mentioned in the paper [START_REF] Qian | Volatile composition of Merlot wine from different vine water status[END_REF].

ii) the effect of micro climate manipulation

Regarding the effect of leaf removal, the wines of the vintages 2009 and 2010 showed a significant increase in vitispirane and TDN concentrations for treatments, which were defoliated at flowering (IdB), in comparison to the wines from the non-defoliated treatments.

In 2009 only the treatment defoliated at veraison (IdV) showed no significant higher concentrations of these compounds in the wines compared to those from the non-defoliated treatment (I).

Regarding defoliation the results confirmed the effect of leaf removal on the concentration of free vitispirane and TDN of another study on Merlot wines, when vitispirane and TDN concentrations increased with light exposure, but additionally were influenced by leaf layer number (Lee et al., 2007).

Contrary results to the results from this study were obtained for Riesling wines from eastcoastal Northern America for the consequences of cluster exposure [START_REF] Kwasniewski | Timing of cluster light environment manipulation during grape development affects C 13 -norisoprenoid and carotenoid concentrations in Riesling[END_REF]. In that study grape vines' defoliation was carried out at different phenological stages and was allowed to be compensated by secondary leaf growth, which was evident in the cluster exposure rates. In that study only defoliation at pre-veraison showed higher TDN concentrations in finished wines, which then was not observed for the defoliation at berry set and the defoliation at veraison. In our present study, defoliation treatments were carried out at flowering to be then re-defoliated at veraison (IdB) and at veraison only (IdV). Both showed higher free TDN concentrations in the finished wines in comparison to those, from the not defoliated control treatment (I). Interestingly, absolute TDN concentrations in the two months bottle stored wines from the North American study of Kwasniewski and co-workers were much more elevated (7 -20 µg/L) than the ones in the present study after twelve months of bottle storage in all vintages (<0.1 -1.9 µg/L). This could either be explained by differing storage conditions, which were observed to influence formation and break down of norisoprenoid compounds (Marais et al., 1992), or by general differing aging behaviour depending on the origin of the wine and therefore its composition. It was already observed that the ratio of free TDN and its TDN potential determined in forced aging experiments in wines from east coastal Northern America was increased in comparison to the wines from the Rheingau region in Germany. These findings showed that the concentration of free TDN was more abundant in American wines compared to wines from Germany, whereas the potential of TDN concentration determined by a forced aging experiment was even higher in German Riesling wines [START_REF] Sponholz | Einfußfaktoren von Klonenematerial und verwendetem Hefestamm auf die Alterung von Riesling Weinen[END_REF]. These authors also suggested that a different, structurally only partially identified precursor molecule could be engaged in TDN formation in wine (Versini et al., 1996). The formation via this precursor is suggested to take place in a slower reaction than via the pathway proposed by [START_REF] W Waldmann | Identification of a novel vitispirane precursor in Riesling wine[END_REF]. Therefore, precursor molecules' distribution could be crucial for TDN formation kinetics in Riesling wines and thus be responsible for earlier or later increase in TDN concentration during the aging process.

Comparing the results of the wines after twelve months and after 22 months of bottle storage, this suggestion gets supported, by equalising TDN concentrations with prolonged aging. In addition to this, the fact that measurements of the potential of volatile TDN in grape musts did not reflect the situation in the wines could also be a supporting element for this hypothesis.

iii) the effect of vintage and temperature

The

3.3.8

Essential outcomes for C 13 -norisoprenoids and their precursor molecules

In conclusion it can be stated that C 13 -norisoprenoid concentrations in wines are strongly influenced by viticultural factors, especially by water status. It is considered that the aging behaviour of Riesling wines is significantly influenced by viticultural factors, due to alter C 13 -norisoprenoids concentration pattern and determines the rate of TDN formation.

3.3.9

Thiol concentrations in wines and thiol precursor concentrations in berry extracts and grape must

Observations on thiol precursor molecules and other related metabolites in berry extracts

Cysteinylated and glutathionylated precursor molecules S-3-(hexan-1-ol)-L-cysteine (cys-S-prc) and S-3-(hexan-1-ol)-glutathione (GSH-S-prc) of the aroma compound 3-sulfanylhexan-1-ol (3SH) were assayed in berry samples at different stages of the ripening period. In addition to these compounds, glutathione (GSH), one of its main reaction partners in grape must caftaric acid (CA), and the resulting product S-glutathionylcaftaric acid -the so called Grape Reaction Product (GRP) [START_REF] Singleton | Caftaric acid disappearance and conversion to products of enzymic oxidation in grape must and wine[END_REF] -were analysed in berry extracts during the grape maturation and in musts (Table 3-15 andTable 3-16).

During the vintage 2009 in the early stage of berry ripening (14 days after veraison) only very little quantities of cys-S-prc were measured for all viticultural treatments (1 -2 µg/L berry extracts). The concentrations of the GSH-S-prc, ranging from 68 -134 µg/L were generally higher than those of cys-S-prc. Berry extracts from defoliated vineyard treatments showed significant lower concentrations in comparison to treatments without leaf removal. Regarding the GSH concentrations, berry extracts from non-irrigated vines (C) showed significant higher values than in the samples from the irrigated treatments (I) (33.0 mg/L and 25.5 mg/L respectively). Defoliation manipulation corresponded to an increase of GSH resulting in concentrations of 30.7 mg/L and 28.5 mg/L for the different timing of leaf removal, at flowering and at veraison (IdB and IdV respectively). No GRP was detectable and CA concentrations in the berry extracts ranged from 135.0 mg/L to 147.8 mg/L, without significant differences at this stage of maturity. A tendency to higher CA levels in the berry extracts was observed for the non-irrigated and not defoliated treatment (C) and the irrigated treatment, which was undertaken leaf removal at flowering (IdB). The berries sampled one day before harvest, still did show low concentrations of cys-S-prc of 3 -4 µg/L in the extracts, whereas the concentration of GSH-S-prc was increased in all viticultural treatments, when being compared to the results from the first sample date. The highest concentrations within the treatments were observed for the non-irrigated treatment (C) and the irrigated one, which was defoliated at flowering (IdB), containing 174 µg/L and 180 µg/L respectively. Lower concentrations were observed in the irrigated treatments with leaf removal at veraison and without leaf removal (IdV; I), namely 109 µg/L and 129 µg/L respectively. This concentration pattern was exactly inversed to that of the GSH concentrations, which were lowest in the berry extracts from the non-irrigated control treatment (C) and tendentially showed lower concentration for the irrigated treatment, which was defoliated at flowering (IdB). GSH concentrations generally showed higher values in the berry extracts for the irrigated treatments (I, IdB, IdV) than for the non-irrigated control treatment (C), regardless of microclimate manipulation. For the vintage 2009, GRP was not detected in any of the berry extracts, although CA concentrations decreased in comparison to the first sampling date. CA concentration was shown to be higher in the berry extracts of the irrigated treatment, which was defoliated at flowering (IdB) (123.0 mg/L) than in those ones from the irrigated treatment, which was defoliated at veraison (IdV) (106.8 mg/L).

In 2010, three sampling dates were realised -the first one at veraison + 14 d, the second one at veraison + 22 d and the last one at harvest.

As in 2009, there were very small concentrations of cys-S-prc in all berry samples at all sampling dates ranging from not detectable to 2 µg/L in the berry extracts. The concentrations for GSH-S-prc showed no significant differences for the first date at veraison + 14 d and at harvest, whereas significant lower concentrations were detected in the treatment supposed to be irrigated (I), at the second sampling date at veraison + 22 d.

No general increase of GSH-S-prc in berry extracts was detected with increasing time of ripening. In contrast to that no statistically significant differences were observed for GSH concentrations in the berry extracts regarding the viticultural treatments at all sampling dates, whereas a general increase was observed with increasing time of the berry ripening.

Thiol precursor molecules and related metabolites in grape musts

Different concentrations of cysteinylated and glutathionylated S-bound precursor (cys-S-prc and GSH-S-prc respectively) molecules of the odoriferous thiol 3-sulfanylhexan-1-ol (3SH)

and assimilable nitrogen (sum of N-OPA and Ammonium concentrations) were detected in grape musts from the different experimental treatments in all vintages regarding to viticulture treatments (results compiled in Table 3 -17).

For the vintage 2008, a difference was observed for the concentration of GSH-S-prc and assimilable nitrogen (N). Assimilable nitrogen showed higher proportions in the must from the non-irrigated control treatment (C) in comparison to the must from the irrigated treatment without defoliation (I) (GHS-S-prc: 216 µg/L and 193 µg/L; N: 345 mg/L and 271 mg/L respectively). At the same time, no significant difference was observed for the concentration of cys-S-prc in these samples (10 µg/L and 4 µg/L).

In the vintage 2009, the GSH-S-prc concentrations were significantly different in the musts from all viticulture experimental trials, showing lower values for the non-irrigated control treatment (C) (214 µg/L), whereas the irrigated treatments (I, IdB, IdV) generally showed higher concentrations, independent from leaf removal. The highest concentration of GSH-Sprc within these treatments was observed in grape must of the irrigated not defoliated In the vintage 2010, the concentrations of GSH-S-prc in musts of the -in that year two -nonirrigated and not defoliated treatments C and I were surprisingly statistically significantly different (205 µg/L and 232 µg/L respectively). Anyway, both grape musts showed a significant lower GSH-S-prc concentration in comparison to the one obtained from the defoliated treatment (IdB), which was showing a concentration of 267 µg/L. The same was observed for the cys-S-prc, whose concentration was lowest in grape musts from the nonirrigated control treatment, without leaf removal (C) (17 µg/L) in comparison to all others (21 µg/L and 22 µg/L). For the concentrations of assimiliable nitrogen an equivalent pattern was observed (C: 215 mg/L; I: 267 mg/L; IdB: 254 mg/L).

Comparison of berry extracts and grape musts composition

Regarding the composition of the berry samples at harvest and the corresponding grape musts, significant differences could be observed in both, vintage 2009 and vintage 2010. For the vintage 2009, the GRP was not detected in any of the berry samples, whereas it was abundant in obtained grape musts at concentrations between 5.6 mg/L and 15 mg/L. The concentrations differed significantly for all viticultural treatments. The non-irrigated control treatment (C) showed significant higher GRP concentration than the irrigated treatment without defoliation (I) containing 9.9 mg/L and 5.6 mg/L respectively. The irrigated treatments, which were leaf removed (IdV; IdB), theirselves contained significant higher concentrations of the GRP than the not defoliated treatments (C: 11.9 mg/L and I: 15 mg/L respectively).

ii) for GSH-S-prc and cys-S-prc Interestingly, an increase by factors from 16 to 31 was observed for concentrations of cys-S-prc, when comparing berry extracts and the grape musts. For the vintage 2009 and the vintage 2010 for none of the grape extracts, a cys-S-prc concentration higher than 4 µg/L and 1 µg/L was detected at harvest respectively. In contrast to that, concentration ranges between 55 µg/L to 123 µg/L and 17 µg/L to 22 µg/L were analysed in the grape musts for the vintages 2009 and 2010 respectively.

In the same time GSH-S-prc concentrations were observed to increase only up to factor 5, depending on the viticultural treatment.

In

Free thiol concentrations in young wines

Concentrations of the thiol 3-sulfanylhexan-1-ol (3SH) were analysed in the finished wines from fermented grape musts of the viticulture experiments. In all vintages significant differences were observed in the concentrations of 3SH regarding viticultural treatments (Table 34567891011121314151617

Discussion on observations on thiol precursor molecules and other related metabolites in berry extracts

Regarding the biogenesis of cysteinylated and glutathionylated precursor molecules the biochemical process has to be reminded (Fig. 3-13) as well as the effects of environmental factors on several metabolites which are involved in this process. Therefore possible effects of environmental conditions on i) the concentration of glutathione ii) the precursor GSH-S-prc and cys-S-prc will be discussed. Generally, an increase of reduced GSH during the berry ripening is in accordance with previous findings, which showed an increase of reduced GSH with the onset of berry ripening and that this increase correlated linearly with soluble solids concentrations, which also increases with berry ripening (Adams et al., 1983).

Lower reduced GSH level in berry extracts obtained from vines showing higher water deficit could be explained by the fact of changing reduced GSH to oxidised GSSG ratio as general plants stress response (reviewed in [START_REF] Foyer | The functions of inter-and intracellular glutathione transport systems in plants[END_REF] or could occur due to increased glutathionylation of cell xenobiotics as hexenal (reviewed in [START_REF] Foyer | The functions of inter-and intracellular glutathione transport systems in plants[END_REF]in Noctor et al., 2011).

For example, soybean showed decreasing GSH and homoGSH concentrations in leaves under drought conditions, whereas leaves approaching senescence showed altered GSH and homoGSH concentrations (Noctor et al., 2011). Anyway, this effect was not observed in grape vine leaves for water deficit, which did not increase reduced GSH concentration (Kobayashi et al., 2011), whereas this author showed significant effects on GSH through UV-C induced stress on leaves and berries (Kobayashi et al., 2011).

ii) the precursor GSH-S-prc and cys-S-prc

In the 2009 vintage, lower concentrations of reduced GSH in berries at harvest correlated with higher concentrations of the GSH-S-prc. Inversely, tendentious higher reduced GSH concentrations coincidenced with lower GSH-S-prc concentrations 14 days after defoliation. This can support the hypothesis of the metabolism of the 3SH precursor molecules as a part of the pathway of a relatively dynamical process of detoxification in the berry, due to berries being exposed to excessive sun light. However, results for the vintage 2010 were less significant and therefore did not confirm the 2009 results, but one has to take into consideration that both vintages showed completely different climatic and viticultural conditions.

The concentrations of cysteinylated precursor molecules of 3SH were surprisingly low in the berry extracts, which were obtained by a very reductive sampling procedure.

No significant GSH-S-prc accumulation was observed in the berries during the ripening period.

Therefore it can be considered, that higher GSH-S-prc in berries at the stage of maturity would be more or less coincidently related to stress conditions. This would suggest that every moment of sampling is just one snapshot in a highly dynamic and complex process.

Discussion on comparison of berry extracts and grape musts composition

For the observation of the influence of the passage from berry to must, berries were sampled carefully under reductive conditions to avoid oxidation processes and shock frozen in liquid nitrogen in order to preserve the status of the berry as it was in the vineyard. GRP, which is known to form from caftaric acid under oxidative conditions by conjugation of GSH [START_REF] Singleton | Caftaric acid disappearance and conversion to products of enzymic oxidation in grape must and wine[END_REF], was measured as a marker of grape extract's and grape must's oxidation.

For 2009, the berry extracts at harvest showed no GRP and thus were not undergone visible and measurable oxidation process. Only very small quantities of the cys-S-prc were detectable in the berry extracts. After pressing, the grape musts of the corresponding treatments showed highly increased cys-S-prc concentrations and similar pattern to GSH-S-prc in the berry extracts. Moreover, GSH-S-prc in grape must increased proportionally to the GSH concentrations in the berry extracts. Same was observed during the 2010 vintage. GRP formation and caftaric acid's decrease were not observed to be linked to precursor formation.

These results confirm earlier findings on the effect of must oxidation [START_REF] Roland | Evolution of Scysteinylated and S-glutathionylated thiol precursors during oxidation of Melon B. and Sauvignon blanc musts[END_REF][START_REF] Mattivi | Development of reliable analytical tools for evaluating the influence of reductive winemaking on the quality of Lugana wines[END_REF], on the effect of travelling berries over long distances and harvest procedures regarding concentrations of GSH-S-prc (Capone and Jeffery, 2011;[START_REF] Allen | Influence of grape-harvesting steps on varietal thiol aromas in Sauvignon blanc wines[END_REF]. Capone and co-workers demonstrated in an experiment of grapes' enzymatic activity inhibition by liquid nitrogen, that the concentration of cys-S-prc then was constant. They concluded that the formation of this metabolite is berry endogen, whereas the main part of the GSH-S-prc was formed through berry crushing (Capone and Jeffery, 2011). In the present study, the hypothesis that cys-S-prc is formed by enzymatic processes of the berry endogenously could be supported. However, it seems that cys-S-prc is endogenously formed in the berry, but accumulates only in post-harvested berries. When comparing the sampling procedures, it can be observed that rending inert the berry samples with liquid nitrogen was not done before the grapes arrived in the laboratory and therefore the biological tissue could possibly still be active after being picked (Capone et al., 2011), whereas in the present study inertness and therefore enzymatic reaction inhibition, was achieved directly after berry sampling in the vineyard. This could lead to the assumption that cys-S-prc is formed as an intermediate metabolite whose concentration is maintained constant in the plant tissue as long as the berry is connected to sap flow and transport systems. Only after being disconnected from the sap flow, the cys-S-prc starts to accumulate due to not being delocalised. The data from 2010 confirmed the 2009 results. They also showed very little cys-S-prc constantly at all sampling dates for all viticulture treatments and independent from GSH-S-prc concentrations, but showed an increase in pressed grape must. Cys-S-prc concentrations in grape must seemed to be highly dependent on endogen GSH-S-prc concentrations in berries.

Discussion on thiol precursor molecules and related metabolites in grape musts

Generally, results from grape musts for cys-S-prc and GSH-S-prc indicated an influence of the water status on GSH-S-prc, whereas no significant difference was observed for the cys-S-prc.

In 2008, when the water status of the vine during the growing period was classified as weak to moderate water deficit for the non-irrigated control (C), grape musts GSH-S-prc concentration was significantly higher in comparison to the irrigated treatment (I), for which the water status was classified from weak water deficit to no water deficit at all. In 2009, the vines' water status for the non-irrigated treatment was determined to show moderate to severe water deficit, whereas the irrigated vines (I; IdB; IdV) showed weak to moderate water deficit. In that vintage, the grape musts of the irrigated treatments showed higher GSH-S-prc concentrations than those obtained from the non-irrigated treatments. This, in fact, is in accordance with results deduced from the aroma potential, measured as enzymatically liberated volatiles, for 4-sulfany-4-methylpentan-2-one and 3-sulfanylhexan-1ol in Sauvignon blanc grapes. These volatile thiols showed a maximum in grape musts of vines facing mild water stress in the ripening period (Peyrot des [START_REF] Peyrot Des Gachons | Measuring the aromatic potential of Vitis vinifera L. cv. Sauvignon blanc grapes by assaying S-cysteine conjugates, precursors of the volatile thiols responsible for their varietal aroma[END_REF][START_REF] Choné | Effect of vine nitrogen status on grape aromatic potential: Flavor precursors (S-cysteine conjugates), glutathione and phenolic content in Vitis vinifera L. cv. Sauvignon blanc grape juice[END_REF][START_REF] Peyrot Des Gachons | Influence of water and nitrogen deficit on fruit ripening and aroma potential of Vitis vinifera L. cv. Sauvignon blanc in field conditions[END_REF]. Another study, carried out on grape vine fruiting cuttings, also showed that the GSH-S-prc concentrations increased as a reaction to water deficit in the varieties Chardonnay, Koshu and Merlot, but in this study the precursor were detected in vine leaf extracts (Kobayashi et al., 2011).

In this context, it can be considered that the water status of the non-irrigated vines, especially in the vintage 2009, was not favourable for an increased biosynthesis of GSH-S-prc concentrations in the grape must. In 2009, regarding defoliation treatments on precursor molecules cys-S-prc concentrations, an increase was observed with increased time of defoliation, whereas inversely a decrease was observed for GSH-S-prc concentrations. For 2010, grape must of the treatment being defoliated at flowering showed higher precursor concentration, but a slightly lower concentration of assimilable nitrogen concentration, in comparison to the not defoliated treatments.

Higher assimilable nitrogen concentrations were observed in the grape musts obtained from treatments showing lower water status especially for the vintage 2009.

As indicated earlier, this could either be caused by smaller berry size or by advanced maturity and senescence (Keller, 2005). In the case of distribution of nitrogen compounds into the berries on a per berry ratio, this would lead to a concentration of nitrogen compounds in the berries, due to observed smaller berry size. As senescence and leaf abscission was observed late in the ripening period for the vintage 2009, it seems to be more likely that this effect is caused by redistribution of nitrogen from the leaves into the berries, due to senescence as outlined in Keller (2005). The amount of assimilable nitrogen was not directly correlated to precursor concentrations, which could indicate that different viticultural parameters, such as water status, leaf removal and mould are likely to interact in precursor's biosynthesis.

Furthermore, one has also to consider that precursor concentrations in grape must can undergo changes due to pre-fermentative steps between the vineyard and the fermentation tank. It is reported that harvest technology [START_REF] Allen | Influence of grape-harvesting steps on varietal thiol aromas in Sauvignon blanc wines[END_REF], grape transport (Capone et al., 2011), pressing conditions [START_REF] Allen | Influence of grape-harvesting steps on varietal thiol aromas in Sauvignon blanc wines[END_REF]Nikolantonaki et al., 2012a;[START_REF] Mattivi | Development of reliable analytical tools for evaluating the influence of reductive winemaking on the quality of Lugana wines[END_REF] and must oxidation [START_REF] Roland | Evolution of Scysteinylated and S-glutathionylated thiol precursors during oxidation of Melon B. and Sauvignon blanc musts[END_REF] can impact precursor concentrations. In all these studies, the changes are mostly observed concerning the concentartions of GSH-S-prc but less for cys-S-prc.

Discussion on free thiol concentrations in young wines

In young wines, significant differences were observed with respect to viticultural treatments.

In the vintages 2008 and 2009 significant lower concentrations of 3SH were observed in wines from non-irrigated treatments in comparison to wines from irrigated treatments. The results were repeatable for two different yeast strains for each vintage.

Until now, no information on the effect of the vines' water deficit on free thiols in wines was published. Publications on water stress concerning thiols and their precursor rely on grapes' aromatic potential [START_REF] Peyrot Des Gachons | Influence of water and nitrogen deficit on fruit ripening and aroma potential of Vitis vinifera L. cv. Sauvignon blanc in field conditions[END_REF] or on direct precursor measurement in grapes (Kobayashi et al., 2010). According to these results, one would conclude that more thiols would have been released, when precursor concentrations were elevated in grape musts (Kobayashi et al., 2010). This point already was criticised and alternatively a correlation between free thiols and the proportion of metabolised cysteinylated precursors was considered by different authors (Tominaga, 1998c;[START_REF] Peyrot Des Gachons | Measuring the aromatic potential of Vitis vinifera L. cv. Sauvignon blanc grapes by assaying S-cysteine conjugates, precursors of the volatile thiols responsible for their varietal aroma[END_REF][START_REF] Pinu | Concentrations of the volatile thiol 3-mercaptohexanol in Sauvignon blanc wines: No correlation with juice precursors[END_REF].

In order to contemplate the results for free thiols in wines, which were obtained from grape must of different viticultural treatments and conditions, the two main strands i) formation of free thiols by yeast during fermentation and ii) stability of free thiols in wine after release will be discussed. i) formation of free thiols by yeast during fermentation Grape musts from the viticultural trials were shown to be modified in assimilable nitrogen concentrations by water deficit, likely as a consequence of advanced senescence with abscission. Therefore nitrogen source for yeasts during fermentation is modified through viticultural treatments, especially water deficit.

For the transformation of cys-S-prc into 3SH and A3SH, transformation rates of 0.1% -12% and for GSH-S-prc less than 5% are reported [START_REF] Dubourdieu | The role of yeasts in grape flavor development during fermentation: The example of Sauvignon blanc[END_REF]Masneuf-Pomerade et al., 2006;[START_REF] Howell | Variation in 4-mercapto-4-methyl-pentan-2-one release by Saccharomyces cerevisiae commercial wine strains[END_REF][START_REF] Subileau | New insights on 3-mercaptohexanol (3MH) biogenesis in Sauvignon blanc wines: Cys-3-MH and (E)-hexen-2-al are not the major precursors[END_REF]Thibon et al., 2008).

Conversion rates in synthetic medium were observed to be lower than for real grape must (Masneuf-Pomerade et al., 2006;[START_REF] Howell | Variation in 4-mercapto-4-methyl-pentan-2-one release by Saccharomyces cerevisiae commercial wine strains[END_REF]. Moreover, an increase of transformation from cys-S-MSP to 4MSP and cys-S-3SH to 3SH by yeast was observed, when nitrogen source was suboptimal for yeast metabolism, influenced by the effect of the so called Nitrogen Catabolic Repression (Thibon et al., 2008).

In the vintage 2008, wines from the non-irrigated control treatment (C) showed the lowest 3SH concentrations compared to those from the irrigated treatment (I), but inversely the grape must from the non-irrigated control treatment (C) showed higher assimilable nitrogen concentration than the one from the irrigated treatment (I). The same observation was made in vintage 2009. Microclimate manipulation in this vintage seemed to impact the concentrations of free thiols in wines in the same way.

These results support, that the effect of Nitrogen Catabolic Repression possibly influences metabolism of volatile thiols during fermentation, although no relation between precursor molecules and liberated thiols was observed.

However, it could also be considered that in those musts, which show high free thiol concentration after fermentation, other biosynthesis pathways including other precursor molecules can impact free thiol concentrations in finished wines [START_REF] Subileau | New insights on 3-mercaptohexanol (3MH) biogenesis in Sauvignon blanc wines: Cys-3-MH and (E)-hexen-2-al are not the major precursors[END_REF][START_REF] Pinu | Concentrations of the volatile thiol 3-mercaptohexanol in Sauvignon blanc wines: No correlation with juice precursors[END_REF].

ii) stability of free thiols in wine after release Reductive oenological practice is recommended in order to stabilise volatile thiols in wine and to avoid losses through oxidation and trapping by Michael addition reactions on quinones [START_REF] Ribéreau-Gayon | Multivariate analysis of conventional profiling data: A comparison of a British and a Norwegian trained panel[END_REF]. First, addition of sulfur dioxide to grape must and to wines is one aspect of antioxidative actions applied in oenology. Water deficit was shown to increase phenolic compounds in grapes [START_REF] Nouveau | Berry size and vine water deficits as factors in winegrape composition: Anthocyanins and tannins[END_REF]. Second, phenolic compounds, like hydroxycinnamic acids and catechols, can be oxidised to quinones mostly by means of the grape's polyphenoloxidase and heavy metal catalysed Fenton reactions. These oxidation products theirselves can react with free thiols (Michael addition reaction) and therefore decrease their concentration in wines (Nikolantonaki et al., 2012). These phenol oxidations can be limited by the use of carbon dioxide and sulfur dioxide (Nikolantonaki et al., 2012a).

Therefore water deficit on grape vines could theoretically indirectly lead to scalping of free thiols in corresponding finished wines. Considering the way of wine elaboration, these points should have limited the impact of free thiols stability in wines.

Essential outcomes regarding thiols and their precursor molecules

This part of the project permitted to study effects of viticultural conditions, focused on the water status and the microclimate manipulation, on several metabolites being susceptible to impact volatile thiol concentrations in wines. These observations were done in different stages of the growing period including berry samples, grape must, finished wines, and aged wines.

Concentrations of reduced glutathione in berries generally were shown to increase after veraison, whereas they were shown to decrease, when the grape vines suffered from severe water deficit. No significant effects have been observed on this parameter related to leaf removal in the fruit zone.

Low concentrations of reduced glutathione were correlated to high concentrations of the glutathionylated precursor of 3-sulfanylhexan-1-ol in berries when vines were grown under water stress, compared to berries issued from vines grown under moderate water deficiency.

No statistical significant accumulation of the glutathionylated precursor of 3-sulfanylhexan-1-ol was shown, albeit a tendency to do so can be observed. Surprisingly, very low concentrations of the cysteinylated precursor of 3-sulfanylhexan-1-ol were present in grape berries.

The results of this study indicate that the biosynthesis and accumulation of cysteinylated precursor of 3-sulfanylhexan-1-ol takes place in the berry after harvest and before pressing.

The crucial role of endogenous glutathionylated precursor in the berries as a precursor for the cysteinylated precursor of 3-sulfanylhexan-1-ol is considered, due to matching concentration pattern of these two metabolites in berry extracts and in grape must. During this process the formation of glutathionylated precursor of 3-sulfanylhexan-1-ol seemed to be linked to the concentrations of reduced glutathione in grape berries.

The formation of the Grape Reaction Product (GRP; 2-S-glutathionyl caftaric acid) and the decrease in caftaric acid concentration did not show any relation neither to cys-S-prc nor to GSH-S-prc metabolism.

In grape musts glutathionylated precursor concentrations were higher in grape musts obtained from vines grown under weak to moderate water deficit, whereas severe water deficit and no water deficit at all was not favourable. Defoliation seemed to decrease glutathionylated precursor concentrations, whereas it increased cysteinylated concentrations in grape musts. Moreover, no link was observed between assimilable nitrogen concentrations and concentrations of cysteinylated or glutathionylated precursor molecules, whereas assimilable nitrogen seemed to be linked to free thiols concentrations in wines.

In total this part of the study showed that viticultural conditions like water deficit and microclimate manipulation directly and indirectly impact free thiol concentrations in wines.

Weak to moderate water deficit during the ripening period were considered to favour 3-sulfanylhexan-1-ol formation in wines, whereas effects of microclimate manipulation did impact indifferently.

Sensory aspects

In triangle tests the wines from the non-irrigated treatment (C) were significant different from the irrigated treatment (I) and the one which was irrigated and defoliated at veraison (IdV) at a significance level of α = 0.05 (p < 0.05). Fig. 3-14 Spider web of results of QDA for finished wines of the viticulture experiment from the vintage 2009 after 12 months of bottle storage; with C: non-irrigated control; I: irrigated; IdV: irrigated and defoliated at veraison; no statistical significant differences in ANOVA for single descriptors Then Quantitative Descriptive Analysis (QDA) was carried out on the wines after 12 months of storage in order to clarify the perceived differences in the triangle test. In QDA (Fig. [3][4][5][6][7][8][9][10][11][12][13][14], it was proposed to rank the level of intensity of various descriptors used for describing Riesling wines. No significant different rating for descriptors was observed, whereas the

Discussion on sensory aspects

Varietal character of wines and therefore viticultural influences on wines' aromatic expression is more likely to be observed in wines, which have been bottle stored for a certain period of time than in wines directly tested after finished fermentation. It was observed that acetate esters, which are mainly responsible for the so called 'fermentative aroma', are formed during alcoholic fermentation and degrade during the storage by hydrolysis, due to equilibrating the chemical equilibrium in wines [START_REF] Rapp | Neue Monoterpendiole in Traubenmosten und Weinen und ihre Bedeutung für die Genese einiger cyclischer Monoterpenäther[END_REF]. Then, when fermentative aroma deminuishes and aging aroma has not developed strongly at the same time, varietal character of wines is considered to be perceived more intense than in very young wines, showing intense fermentative aroma, or than in very old wines, showing intense aging aroma.

In twelve months bottle stored wines significant differences were detected orthonasally between wines from the viticulture treatments C and I as well as between wines from C and IdV in their global aromatic expression. Compared to analytical data this coincidenced to significant differences for linalool (129 µg/L, 87 µg/L and 110 µg/L for C, I and IdV respectively), TDN (0.7 µg/L, 1.2 µg/L and 1.6 µg/L) and 3SH (156 µg/L, 328 µg/L and 327 µg/L).

Despite differences for single descriptors have not been significant, it was observed that the defoliated treatment (IdV) showed a tendency towards more pronounced petrol or kerosene like odour, which coincidenced with higher TDN concentrations close to the recently determined odour detection threshold of 2 µg/L [START_REF] Sacks | Sensory threshold of 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) and concentrations in young Riesling and non-Riesling wines[END_REF], which was confirmed during this study at 2.7 µg/L. Moreover, despite lower concentration of 3SH, wines from the non-irrigated control treatment showed a tendency to more pronounced grapefruit and lemon odour.

In conclusion, the present study shows the impact of viticultural conditions and practices on the final olfactory properties of the product wine. Through influence of these factors on final concentrations of typicality related aromatic compounds in Riesling (compare chapter 1), the overall aromatic perception changes and interacts with typicality appreciation of Riesling wines.

3.4

Conclusion on viticultural influence on Riesling wines' aromatic aromatic expression

Following to a number of works, this study helps to demonstrate the impact of changes in viticultural conditions on modifications on the aromatic expression of finished wines, which could impact varietal typicality, by both chemical and sensory analysis.

Particularly, through the establishment of a sampling procedure which allowed to monitor changes of aroma compounds and precursor molecules concentrations at several levels of production (during grape maturation, during the pre-fermentative operations, after wine elaboration and aging) this research led to valuable insights.

Regarding terpenols and C 13 -norisoprenoids, an effect of grape vines water status on their concentrations in the finished wines was clearly demonstrated. Especially in the case of the C 13 -norisoprenoid 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN), the influence of viticultural practices is considered to play an important role in the formation kinetic of this compound during bottle aging, highlighting also the interest of integrating bottle aging of experimental wines into these kind of studies. This got more obvious as the value of an aromatic potential regarding these aroma compound classes, obtained from grape must, did not picture the situation in the finished wines sufficiently.

Regarding the powerful aroma compound 3-sulfanylhexan-1-ol, it was demonstrated that the production step between harvest and pressing is likely to influence concentrations of the cysteinylated precursor molecules of 3-sulfanylhexan-1-ol, and that its concentration in grape must is somehow linked to its glutathionylated precursor in the grape berries. However, in the finished wines concentrations of 3-sulfanylhexan-1-ol were shown to be related to viticultural conditions, whereas the mechanism of the influence still remains unclear. A possible indication of yeast assimilable nitrogen concentrations in grape musts on 3-sulfanylhexan-1-ol concentrations in wines is considered.

Introduction

In chapter 1, it was shown by a targeted study that several aroma compounds are likely to influence Riesling wines aromatic typicality. In chapter 2 some of their concentrations in wine were shown to be influenced by environmental factors in the vineyard.

Generally it should be considered, that other aroma compounds than those included in the targeted approach, are involved in the typical aroma of Riesling wines.

In order to progress on this subject, various analytical techniques such as wine extract fractionation associated with sensory analysis, hyphenated gas chromatographic technique coupled to both, mass selective (GC-MS) and olfactory detection (GC-O) can be used. In the past, GC-O approaches were used to characterise odour active compounds in Riesling wines from North America and Croatia. As results, mainly odoriferous compounds as ethyl and acetate esters, terpenols and higher alcohols were evidenced [START_REF] Chisholm | Comparison of some french-american hybrid wines with white Riesling using gas chromatographyolfactometry[END_REF][START_REF] Komes | Characterization of odor-active compounds in Croatian Rhine Riesling wine, subregion Zagorje[END_REF]. These compounds were included in the targeted approach, which was applied in chapter 1. But, it should be noted that while Chisholm and co-workers used a comparative analysis between Riesling and French-American hybrid wines, they did not develop an approach based on the concept of typicality.

In this study, it was demonstrated that under these conditions wines from the variety Riesling and Sauvignon blanc style wines differed extremely in their perceived typicality. So, it is considered that in order to decrypt typical Riesling wines' aroma compounds a comparative sensory approach between representative wines from those two varieties (Riesling and Sauvignon blanc) through all the steps of wine extraction, fractionation and analysis (particularly GC-O and GC-MS) can be used as a novel strategy.

For example, this approach was successfully applied to elaborate aroma compounds abundant in sweet dessert wines from the appellation of Sauternes in comparison to dry white wines from the Bordelais [START_REF] Sarrazin | Odorous impact of volatile thiols on the aroma of young botrytized sweet wines: Identification and quantification of new sulfanyl alcohols[END_REF][START_REF] Sarrazin | Correlation between sensory typicality and aromatic composition in Sauternes botrytised wines in Expression of multidisciplinary flavour science -proceedings of the 12 th Weurmann Symposium[END_REF].

It is considered that this comparative strategy, implicating sensory analysis at all stages, would facilitate the identification of new marker compounds implicated in Riesling wines' typical aroma.

4.2

Material and methods

4.2.1

Global aroma extracts 200 mL (500 mL; or 750 mL) of the wines (see Table 4-1) were extracted successively with 30 mL, 30 mL and 20 mL (50 mL, 50 mL and 30 mL; or 70 mL, 70 mL and 50 mL respectively) of dichloromethane using magnetic stirring (at 500 rpm) in flasks and decantation in a separation funnel. The combined organic phases were dried using anhydrous sodium sulfate and then got gently concentrated to a volume of approximately 20 mL using a rotary evaporator (waterbath 20 °C; 500 kPa). Subsequently, the aroma extract was concentrated under a gentle nitrogen streem (~ 100 mL/min) to 0.2 mL (0.5 mL;

1 mL) and stored at -18 °C for further use.

Thiol selective aroma extracts

Thiol selective aroma extracts were prepared according to the method previously described (Tominaga et al., 1998b).

4.2.3

Fractioning global aroma extracts by means of high pressure liquid chromatography (HPLC) according to Ferreira et al. (1999) and [START_REF] Pineau | Examples of perceptive interactions involved in specific 'red-' and 'black-berry' aromas in red wines[END_REF] 200 µL (250 µL) of the global aroma extract (4.2.1) were injected on a C 18 -semi preparative column and separated along a H 2 O -ethanolic gradient. After passing the column, the effluent was collected changing the recipient (capped vials preloaded with nitrogen as inert gas to avoid oxidation) every minute. In total 60 fractions were collected and kept at -18 °C in the dark until further usage (conditions shown in Table 4-2 and Table 4-3)

Sensory analysis of aroma extract fractions

The fractions obtained were poured into wine tasting glasses (ISO, 1977), and evaluated in batches of ten glasses by a sensory panel consisting of 3 trained panelists for differences between extracts from Riesling wines and Sauvignon blanc style wines.

The fractions obtained in 4.2.3 were diluted using H 2 O resulting in 8.7 mL of 12% (v/v) hydroalcoholic solutions. These solutions were poured into wine tasting glasses (ISO, 1977), and evaluated in batches of 10 glasses by a sensory panel consisting of 3 trained panelists for differences between extracts from Riesling wines and Sauvignon blanc style wines.

4.2.5

Triangle These solutions were presented in wine tasting glasses (ISO, 1977) in form of triangle test.

These triangle tests were conducted in order to detect differences in the global aromatic expression by 22 and 16 experienced judges for i) and ii) respectively. Statistical significance was evaluated according to [START_REF] Lawless | Sensory evaluation of food -principles and practices[END_REF].

4.2.6

Quantitative Descriptive Analysis (QDA) of aroma extract fractions and reconstituted aroma extracts

In the descriptive task, the solution prepared in 4.2.5 were presented in wine tasting glasses (ISO, 1977) and the panels were asked to rate the solutions for the descriptors fruity and floral on a non-segmented scale of 10 cm length anchored with 'not' and 'very' at the left and right end respectively. One factorial ANOVA was carried out using Sigma Plot TM (Systat Software GmbH, Erkrath, Germany) on the results.

4.2.7

Liquid-liquid micro extraction of aroma extract fractions

The fractions (4.2.3) were diluted using H 2 O resulting in 8.7 mL of 12 vol.% alcoholic solutions. These solutions were re-extracted successively three times with 1 mL of dichloromethane. The organic phases were unified and dried over anhydrous sodium sulfate and then got concentrated under a gentle nitrogen stream to 200 µL. These extracts were stored at -18 °C until further usage.

4.2.8

Gas chromatography coupled to olfactometric detection (GC-O)

For gas chromatography olfactory analysis 2 µL of the organic aroma extract or aroma extract fraction micro-extract were injected and were sniffed by 3 trained panelists using chromatographic conditions according to Table 4.5 on two capillary columns of different polarity. The detection was performed at the exit of the capillary column by trained panelists.

The sniffing port ODO 1 allows olfactory sniffing of a cooled and humidified gaseous effluent thanks to both, a Venturi effect and the bubbling of nitrogen in distilled water. Capillary column comes just at the upper limit of the ODO 1 installation and there is no necessity of make up gas. The flow of nitrogen used for the Venturi effect is close to 600 mL/min and for humidification, the nitrogen flow bubbling through water is close to 90 mL/min. The flows are controlled by needle valves. This strenuous exercise can be performed for more than forty minutes [START_REF] Darriet | Caractérisation de l'arôme variétal des vins de Sauvignon par couplage CPG-Olfactométrie[END_REF]. Each panelist sniffed for 30 Minutes. They were asked to indicate a detected stimulus and name a descriptor. Stimuli detected by 2 of 3 panelists were considered as odouriferous zones (OZ). The odoriferous zones obtained by GC-O on a polar (SGE BP-20) and a non-polar stationary phase (Agilent DB-5) are given in Table 4-7.

The reproducibility in the temperature range of > 200 °C (LRI > 1900 (SGE BP-20)) was generally poor, between the 3 panelists as well as it was for the global extracts, and therefore differences were difficult to verify.

One major problem seems to be the complexity of the aroma extracts' aromagram in the GC-O and the high number of OZ which lead to fatigue especially at the end of the 30 minutes sniffing time.

From these preliminary GC-O results, it cannot be deduced that there are specific odoriferous zones in the aromagrams of the wines obtained by GC-O of global organic aroma extracts of typical Riesling wines in comparison to those of non-typical Riesling wines (Table 4567). Although wine styles from the varieties Riesling and Sauvignon blanc style wines showed highly different aromatic expression, the number of AEF showing no clear differences was surprisingly high.

Anyway, these results led to the confirmation of the hypothesis that some AEF of typical Riesling wines showed different aromatic expression in comparison to the corresponding AEF obtained from typical Sauvignon blanc style wines.

Especially fractions 54 and 55 in Riesling wines extracts showed odours reminiscent to Riesling wines.

Prior to selection for GC-O analysis, these fractions were tested by a bigger sensory panel in order to verify these preliminary results. were not statistically significant (α = 0.05). showed a tendency to lower ratings for the descriptors 'fruity' and 'floral' than total reconstituted aroma extract solutions. Doubling these fractions led to higher ratings for 'fruity' also, but inversely led to lower ratings for the descriptor 'floral' (Fig. 4-2).

According to these results it can be concluded that the AEF 54 and AEF 55 likely impact Riesling wines' aromatic expression. Therefore, the aroma compounds in these AEF should be considered to have an influence on Riesling wines' aromatic typicality. For the fraction 55 of typical Riesling and typical Sauvignon blanc style wines in total 27 OZ were detected by means of GC-O on polar polyethylene glycol stationary phase (BP20).

Typical Riesling wines AEF 55 showed 20 OZ, whereas those of typical Sauvignon blanc style wines showed 19 OZ on polar polyethylene glycol stationary phase (SGE BP20) (Table 4-10).

Whereas most powerful OZ were detected in AEF 55 of both wine styles (e.g. OZ 3,4,6,10,12,18 and 23) only one powerful OZ was detected in AEF 55 obtained from Riesling wines (OZ 27) and exhibited a strong odour described as 'floral' and 'fruity'.

OZ 27

As on the equivalent column used in paragraph , the selected OZ 27 was identified at similar LRI 2064 using a Agilent DB-Wax capillary column. In the total ion chromatogram (TIC) of the mass spectrometric detection a small signal could be attached to the OZ.

The correspondant full scan mass spectrum (m/z 30 -m/z 250) was evaluated showing most abundant mass fragments at m/z 181, 176, 151, 147, 146, 121, 105, 104, 91, 73, 59, 45 and 43. In addition to this, the mass spectrum was quite noisy, which did not favour a reliable mass spectra comparison to a mass spectra data base (NIST ® data base) and/or a calculation of molecular formula.

Two-dimensional heart-cut GC-GC-O/HR-TOF-MS

As the next step in the identification of responsible odoriferous compounds in OZ 27 two-dimensional heart-cut GC-GC-O/HR-TOF-MS was applied using a polar polyethylene glycol stationary phase (Agilent DB-WAX) as a first separation step and a non-polar dimethyl siloxane stationary phase (Supelco SPB-1) in the second separation step after heart cutting.

Both separations were monitored by means of an olfactometric port. Sauvignon blanc style wines analysed resulting in a mean concentration of 0.7 µg/L with a standard deviation of 0.1 µg/L. These concentrations of trans-ethyl cinnamate were significantly different (p<0.001) according to 'Mann-Whitney Rank Sum Test' at a confidence interval of 95 % (Fig. 4-5), and showed that this compound is more likely to impact Riesling wines' aroma, due to higher concentrations.

trans-ethyl cinnamate

The odour detection threshold was determined twice in both, wine-like model solution and neutral Riesling wine. In a wine-like model solution, the detection threshold was at 0.9 µg/L and 1.2 µg/L respectively (Fig. 456) whereas in a neutral Riesling wine, the odour detection threshold was determined at 1.6 µg/L and 2.4 µg/L respectively (Fig. 4567). This data confirmed that trans-ethyl cinnamate concentrations were lower in Sauvignon blanc style wines (up to 0.8 µg/L) while they were usually higher in wines from Riesling (up to 6.4 µg/L) and for Chardonnay (up to 2.7 µg/L) (Fig. 4-8 and Fig. 456789). For both panels, data show that there is no direct linear correlation between trans-ethyl cinnamate concentrations and Riesling wines' typicality ratings. With the German panel, Riesling wines were found to be quite typical (typicality ratings from 0.5 to 0.7), when concentration ranges passed 1 µg/L, but also very typical Riesling wines (typicality ratings > 0.7) showed lower concentrations than that. The effect that for three wines, particularly one, Riesling wines' typicality increased with increasing trans-ethyl cinnamate concentration, whereas it decreased for another wine with increasing concentration, led to the assumption that the effect of trans-ethyl cinnamate on Riesling wines' aromatic typicality depends on the wine's matrix [START_REF] Hoppe | Einfluss von (E)-Zimtsäureethylester auf die Typizität von Rieslingweinen[END_REF]).

This could be explained by synergistic or antagonistic effects with other volatile compounds as described earlier in published works. Previous studies revealed interaction effects with other compounds. [START_REF] Pineau | Which impact for β-damascenone on red wines aroma?[END_REF] showed that the presence of β-damascenone at subthreshold levels decreased the detection threshold of trans-ethyl cinnamate and Escudero et al. ( 2007) demonstrated that the addition of 1.22 µg/L trans-ethyl cinnamate among other compounds showed an effect towards stronger ripe fruit, honey and sweet descriptors in neutral wine. Also, [START_REF] Loscos | Release and formation of varietal aroma compounds during alcoholic fermentation from non-floral grape odorless flavor precursors fractions[END_REF] showed that the addition of a mixture of trans-ethyl cinnamate and ethyl dihydrocinnamate to a synthetic wine showed no significant difference towards a control, but did, when being added in combination with other goups of aroma compounds like terpenes, lactones and/or vanillins, which showed no significant difference themselves before.

4.3.9

Discussion on the role of trans-ethyl cinnamate in wine aroma

Trans-ethyl cinnamate is an odoriferous ester formed during alcoholic fermentation from cinnamic acid. This latter compound is originated in the grape berry and is formed via the phenylpropanoid pathway by the action of PAL enzyme (Phenylalanine Ammonia Lyase) on phenylalanine (Versini et al., 1983). The contribution of this compound to wine aroma was considered at the end of the 1970's, due to the observation being made that concentrations of this ester increased in red wine which were fermented by carbonic maceration, in comparison with red wines obtained by a classical crushing protocol (Versini et al., 1983;Flanzy, 1987;[START_REF] Bitteur | Carbonic anaerobiosis of Muscat grapes. I. Changes in the profiles of free and bound volatiles[END_REF]. During the 1990's, Etievant and co-workers in Dijon [START_REF] Moio | Ethyl anthranilate, ethyl cinnamate, 2,3-dihydrocinnamate, and methyl anthranilate: Four important odorants identified in Pinot noir wines of Burgundy[END_REF][START_REF] Aubry | Quantitative determination of potent flavor compounds in Burgundy Pinot noir wines using a stable isotope dilution assay[END_REF] [4][5][6][7][8][9][10][11].

Other studies showed alternating concentrations of trans-ethyl cinnamate in wines obtained from grapes harvested at different maturity. Concentrations decreased with higher maturity in wines from Pinot Noir (Fang and Qian, 2006) as they did also in Canadian ice wines from Riesling grapes [START_REF] Bowen | Elucidation of odour-potent compounds and sensory profiles of Vidal blanc and Riesling icewines from the Niagara peninsula: Effect of harvest date and crop level[END_REF]. It can be considered that impacted by the level of maturity, the content of trans-ethyl cinnamate in wine should be impacted by water deficiency and Rapp et al. (1985), whereas [START_REF] Gijs | How low pH can intensify β-damascenone and dimethyl trisulfide production through beer aging[END_REF] showed an increase of trans-ethyl cinnamates' flavour dilution value in the Aroma Extract Dilution Analysis (AEDA) in aged beer in comparison to fresh beer. [START_REF] Loscos | Release and formation of varietal aroma compounds during alcoholic fermentation from non-floral grape odorless flavor precursors fractions[END_REF] also showed an increase for trans-ethyl cinnamate during an accelerated ageing experiment in wines, which were obtained by fermentation of model solutions supplemented with flavour extracts obtained from different grape varieties.

Conclusion

The applied comparative approach of a sensory guided selection of organic aroma extract fractions and subsequent comparative gas chromatography, coupled to olfactometry, led to the identification of the compound trans-ethyl cinnamate. This compound is a well known compound originating from the esterification of trans-cinnamic acid from grapes.

Interestingly, the quantification showed significant higher concentrations of this compound in Riesling wines in comparison to Sauvignon blanc style wines.

General conclusion and perspectives

Aromatic perception is a major factor for the quality of wines. A wine embodies a whole bunch of intrinsic factors through its aromatic expression, but in the first place, a good wine always represents the knowledge and skills of grape vine growers and winemakers to cope with climatic conditions and to carve out varietal and wine style characteristics by their actions. Ideally, a wine shows to a high degree a characteristic flavour and taste for its category, which should be accompanied by a certain complexity as an element of originality.

The concept of this ideal is the base of aromatic typicality [french typicité].

The aim of this thesis was to find answers to the initial question, whether probable changes in climate would impact the contemporary aromatic typicality of wines in general and specifically for those made from Vitis vinifera L. cv. Riesling.

This study provided deeper insights on aromatic expression of typical Riesling wines from a sensory, chemical and viticultural point of view. to be important variables for modelling typicality ratings by means of PLS, their concentrations were not directly correlated to the wines' typicality ratings. From the CCA map it could be deduced that for these compounds the presence of concentrations below the mean concentrations of the data set seem to favour higher typicality ratings. The role of linalool and TDN and the strongly associated odours of the descriptor families 'floral' and 'ageing notes', was elucidated by an alternative, complementary conceptional approach of dividing typicality into factors of similarity and factors of dissimilarity. This rather theoretical perspective, adapted from fundamental considerations of an economical model, led to the conclusion that these odours and these aroma compounds could also act as important factors of perceived typicality and that this approach as well as the used multivariate aproach in this study can function as a helpful tool in typicality research in the future.

2) The viticultural part of this project permitted to study the impact of environmental and viticultural factors on Riesling wines' typicality influencing aroma compounds and their precursor molecules at three stages of wine production (berries during the ripening period, the grape must, and the finished wines) over three years with different climatic conditions.

Thanks to the installed drip irrigation system in the experimental vineyard in the Rheingau

Valley in Germany, it was possible to study the impact of different water status of the vines and micro climate variation decoupled from a number of interacting factors, which often complicate studies, such as geological and geographical variation between vineyards, clonal diversity, regional climatic variations, and variations in canopy and phytosanitary actions.

Moreover the integrated approach, 'from berry set to aged wine', allowed numerous insights into the relations between viticultural conditions during the growing season, especially the ripening season of the berries, and the finished and bottle aged wines.

It was shown that sensory properties of wines differed in their holistic perception, depending on grape vines' water status and micro climate manipulations during the growing period. effects were observed to a degree likely to impact sensory properties of the wine.

A major effort of this study is the valuable insight, which was obtained regarding the biogenesis of 3SH and its cysteinylated and gluthationylated precursor molecules (cys-S-prc and GSH-S-prc). Upon results from this study, it can be hypothesised, that cys-S-prc accumulated in the time from harvest to pressing, as long as the berries are not crushed.

Another observation was that the concentration of cys-S-prc in grape must is highly dependent on GSH-S-prc in grape berries. Therefrom, it could be concluded, that GSH-S-prc formed during grape crushing does not get metabolised into cys-S-prc and does finally not contribute to cys-S-prc concentration in grape must. This observation could be used to influence the generation of cys-S-prc in the berries with consequently controlling the grape musts' aroma potential regarding 3SH by variation of the post-harvest berry storage times before pressing.

The survey over all steps of the wine production also permitted to observe the limits of the analytical methodology. Regarding the analysis of bound monoterpenols and C 13 -norisoprenoids, results of the aroma potential of these molecules in grapes and must and observed concentrations in finished wines did not comply. For single viticultural treatments the measured aroma potential for linalool underestimated the concentrations of the free compound in the finished wines, whereas it overestimated these for TDN at the same time.

This is considered to be due to chemical transformation caused by the harsh conditions of the hydrolysis step for the bound molecules' analysis.

3) The third goal of this project was to gain deeper insights into Riesling wines' aroma. In order to decrypt Riesling wines' aromatic expression, other aroma compounds than pointed out in the targeted approach (a) should be identified. The approach of confronting the wine extracts of typical varietal Sauvignon blanc style and Riesling wines in all steps of wine extraction, fractioning and analysis (sensory, GC-Olfactometry and GC-Mass Spectrometry) resulted in the identification of the aroma compound trans-ethyl cinnamate, a well known compound from the esterification of trans-cinnamic acid from grapes. The concentrations of this compound were significantly higher in Riesling wines than in Sauvignon blanc style wines. Surprisingly, there was not much information about the role of trans-ethyl cinnamate on wine aroma available, although it is an aroma compound, which is frequently analysed in wines. Additions to Riesling wines showed that this compound is likely to impact Riesling wines' typicality, although no correlation between concentrations of this compound and perceived typicality was observed. It can be considered that the effects are highly dependent on the matrix. Results from the wines of the viticultural part of this project demonstrated, that this compound is also affected by viticultural factors and that it increases during bottle aging.

Upon these results it is considered that trans-ethyl cinnamate impacts the aroma of bottle aged wines, but that this effect is strongly affected by viticultural conditions during the growing period.

In Tominaga, T., Darriet, P. and Dubourdieu, D. (1996), Identification of 3-mercaptohexyl acetate in Sauvignon blanc wine, a powerful aromatic compound exhibiting box-tree odor.

  Discussion on C 13 -norisoprenoids ............................................................. 3.3.7.1 Discussion on C 13 -norisoprenoids in grape must ...................................... 3.3.7.2 Discussion C 13 -norisoprenoid composition in wines after 12 months and months ......................................................................................................

3. 3 . 9

 39 Thiol concentrations in wines and thiol precursor concentrations in berry extracts and grape must ........................................................................... 3.3.9.1 Observations on thiol precursor molecules and other related metabolites in berry extracts ............................................................................................ -1-(2,3,6-trimethylphenyl)-buta-1,3-diene TRIZMA 2-amino-2-(hydroxymethyl)-

  are shown to accumulate as glycosidic bound non-volatile conjugates in grape berries in form of β-D-glucopyranosides, 6-O-(α-L-rhamnopyranosyl)-β-D-glucopyranosides, 6-O-(α-L-arabinofuranosyl)-β-D-glucopyranosides and 6-O-(β-D-apiofuranosyl)-β-D-glucopyranosides

Fig. 1 - 1

 11 Fig. 1-1 Proposed pathway for vitispirane formation in Riesling wine and the potential role of hypothetic triol as key intermediate in vitispirane and TDN genesis (reproduced after Waldmann and[START_REF] W Waldmann | Identification of a novel vitispirane precursor in Riesling wine[END_REF]

  typicité relation Δ product-prototype typicité relation Δ product-prototype typicality relation Θ

1

 1 Sample preparation for C 13 -norisoprenoid analysis 10 mL of the wine sample were given into a 10 mL head space vial using a piston-driven air displacement pipette (Eppendorf). 5 µL internal standard solution of cumene and 2,6-dichloroaniline (DCA) (c (cumene) = 100.1 mg/L; c (DCA) = 100.0 mg/L) were added to each sample using a 10 µL micro syringe (Thermo-Fischer) and a polydimethylsiloxane coated stir bar (length 10 mm; film-thickness 0.5 mm) was added. The vial was crimped and stirred for 60 min at 1000 rpm for extraction on a multi agitation plate.Then the loaded stir bars were removed and rinsed properly with H 2 O (MilliQ), dried with lint free tissue and transferred into desorption tubes. Ions (m/z) and equation for identification and quantification are indicated in Appendix 16.

  2 M citric acid (pH=2.5), transferred into a 10 mL head space vial, sealed, and heated for 60 min at 100 °C in a laboratory oven. After cooling down in iced water, octan-3-ol and DMH were added resulting in concentrations of 50 µg/L and 25 µg/L related to the initial sample volume. Afterwards the reaction mixture was extracted 3 times by liquid-liquid extraction with pentane/dichloromethane (2/1; v/v) (2 mL, 1 mL, 1 mL). The recombined organic extracts were dried by means of anhydrous disodium sulfate and concentrated under nitrogen flow to a final volume of 50 µL. 2 µL of these extracts were injected for gas chromatographical analysis. Ions (m/z) and equation for identification and quantification are indicated in Appendix 19. Listed equations for the calibration curves were used for free volatile C 13 -norisoprenoids and terpenes as well as for acid hydrolised volatile C 13 -norisoprenoids and terpenes.

1 2 . 4 . 3 . 5

 12435 Typicality ratings -Analysis of Variance (ANOVA) A 3-factorial ANOVA was carried out on relative typicality ratings for each sample including both repetitions with Holm-Sidak post hoc significance test at a significance level of α = 0.05 using Sigma Plot TM (Systat Software GmbH, Erkrath, Germany). The factors wines, judges and repetition were considered.2.4.3.4.2 Descriptor family citation frequencies -Chi-square (χ 2 ) proportions A chi-square (χ 2 ) analysis on the citation frequencies (two repetitions) of each descriptor family was carried out for both sets of samples to evaluate significant descriptor families using the k proportions test with 'Monte Carlo simulation' (n=5000) at a significance level of α = 0.05 in XLStat TM (Addinsoft). The same was conducted on the data sets separated in the natural categories of Riesling wines and non-Riesling wines in order to distinguish wines of one natural category by single descriptor proportions. Correlation of sensory and analytical data 2.4.3.5.1 Univariate Analysis -Pearson product moment correlation Linear Pearson product-moment correlations were calculated between i) the relative typicality and the descriptor frequencies ii) the relative typicality and the volatile aroma compounds iii) the descriptor frequencies and the volatile compounds using Sigma Plot TM (Systat Software GmbH, Erkrath, Germany). out in XLStat TM (Addinsoft) on both sets of data, including Riesling and non-Riesling wines for the two panels using 'automatic' settings, in order to optimise the model. Relative typicality ratings were chosen as quantitative dependent variable (Y) and the aroma compounds' quantitative data as explanatory variables (X), which were normalised, centered and reduced before. Components were added according to the Q 2 criterium explained byTenenhaus et al. (2005), while the confidence interval was set at 95%. Due to the model-fit expressed through Q 2 (cum) = 0.398; R 2 Y (cum) = 0.636; R 2 X (cum) = 0.125) and Q 2 (cum) = 0.411; R 2 Y (cum) = 0.737; R 2 X (cum) = 0.119 respetively, the model was not satisfying. Therefore indicated outliers were removed and the procedure was repeated on the new set (Q 2 criterium in results). Important variables showing values bigger than 0.8 in the 'Value of Importance in Projection' (VIP) tables were considered to be useful for interpretation(Addinsoft, Andernach, Germany; personal communication)

Fig. 2 - 1

 21 Fig. 2-1 Riesling wines typicality ratings for total wine sets tested by the a) German (GH) and b) French (BX) panel in two sessions on two different days; error bars indicate standard errors; wine samples according to Table 2-7.

Fig. 2 - 2

 22 Fig. 2-2 Correlation cycles of PCA for relative typicality scores (German panel (a); French panel (b))

Fig. 2 - 3

 23 Fig. 2-3 Multiple dot-plot with dots indicating significant different typicality ratings for wines (ANOVA; Holm-Sidak post-hoc test; α = 0.05; p< 0.05) for a) the German panel (Geisenheim) and b) the French panel (Bordeaux)

  .5.1.3.3 Comparison of the two applied methods: Pearson product-moment correlation -Typicality ratings vs. A Not-A test derived dry Riesling wines' recognition frequencies Two methods of typicality rating were presented, a direct measurement by means of a scale and an indirect measurement by means of a frequency based approach.In order to compare both results, Pearson product-moment correlations were computed between recognition frequencies for dry Riesling wines and direct measured typicality ratings at a significance level of α = 0.05 for both panels' total data sets (Appendix 5 and Appendix 6) as well as the data sets comprising only Riesling wines. Pearson productmoment correlation tables for the data sets consisting only Riesling wines are shown in Appendix 7 and Appendix 8 for the German and French panel respectively.For the German panel, direct relative typicality ratings showed good correlation with the A Not-A test derived recognition frequencies for Riesling wines (r = 0.738; p < 0.001) in a data set only containing Riesling wines. This was not verified by the French panels results (r = 0.338; p = 0.106), but in the total data sets, correlations were strong and highly significant for the German (r = 0.935; p < 0.0001) and the French panel (r = 0.671; p < 0.0001).

Fig. 2 - 4

 24 Fig. 2-4 Correlation of direct typicality ratings and A Not-A derived recognition frequencies for Riesling wines for the total data sets including non-Riesling wines for a) the German panel (Geisenheim) with r=0.935, p<0.0001 and b) the French panel (Bordeaux) with r=0.671, p<0.0001

Fig. 2 - 2

 22 Fig. 2-5 Average Riesling wines' typicality ratings of both panels, for the 18 wines tested by both, German (GH) and French (Bx) panel (Session 1 respectively). * indicating the three wines appreciated as the most typical by both panels; N.a.N. sample was not assessed in both panels; sample names indicated inTable 2-7; SBNZ SBBX RIAL3 RINA1 N.a.N. RIRH4 RIRH5 RINZ RIAUT1 RIRH1 RIRH2 RIRH11 RIRH6 RIMO1 RIAUT2 RIRH9 RIRH3 RIRH8

Fig. 2 -

 2 Fig. 2-6 General Procrustes Analysis: Correlation circle of the descriptor family frequencies and the relative typicality ratings for the German and the French panel (German (GH) = blue and French (BX) = green) obtained in sensory analysis

  Fig 2-5) to the sensory concept like Ribes ssp. / Sambucus ssp., citrus fruit, and minerality can be traced to the raw descriptor data (2.5.3.1 and Appendix 1).

Fig. 2 -

 2 Fig. 2-7 General Procrustes Analysis: Positioning of wines (samples plot) regarding the descriptor family frequencies and the relative typicality ratings for the German and the French panel (German (GH) = blue and French (BX) = green) obtained in sensory analysis as well as a consensus configuration (Consensus = red))

Fig. 2 -

 2 Fig. 2-8 Map of Canonical Correspondence Analysis (CCA) using PLS chosen aroma compounds' concentrations (Variables (red)), wines (Sites (green)) and descriptor family frequencies (Objects (black)) on the German panels' data (Riesling wines); not shown wines RIAl7 (-1.456; -0.208); RIAl8 (-1.179; -0.055) and descriptor family frequency off-flavour (-2.102; -0.237); BMT: benzenemethanethiol; DMS: dimethyl sulfide; 3SH: 3-sulfanylhexan-1-ol; TDN: 1,1,6-trimethyl-1,2-dihydronaphthalene; MLF: malo-lactic fermentation; wine samples are indicated in Table2-7

Fig. 2 -

 2 Fig. 2-9 Boxplots of linalool concentrations for German panels' total data set after grouping into different levels of typicality atypical (0.0-0.2), less typical (0.2-0.4), typical (0.4-0.6), very typical (>0.6); box plots show median, Q 0.25 and Q 0.75 ; Whiskers showing minimum and maximum respectively

2. 5 .

 5 11 Consideration of an alternative approach: taking into account dissimilarities 2.5.11.1 Differentiation into factors of similarity and factors of dissimilarity of a category 2.5.11.1.1 Principle Following the distinction concerning the concept of typicality [french typicité] made by

  2.5.11.1.3 Pearson product-moment correlation -total frequency of descriptor families vs. aroma compounds' concentrations To obtain a more profound insight into factors of dissimilarity related aroma compounds, a Pearson correlation was computed (α = 0.05) on the sets of Riesling wines, regarding commonly by the German and the French panels' data classifying factors of Riesling wines' dissimilarity -the descriptor families aging notes and floral (Table 2-23).

  ). The experiments have been conducted during the vintages 2008, 2009 and 2010.

Fig. 3 - 1

 31 Fig. 3-1 Experimental vineyard located in Rüdesheim (Germany) -Berg Schlossberg. Viticultural treatments were carried out in the same design for the years 2008, 2009 and 2010; 1,2,3 indicate experimental units in single treatments

2

 2 Fraction of transpirable soil water (FTSW) derived pre-dawn leaf water potential Ψ (PD)

λ 3 :

 3 360 nm. Concentrations of caftaric acid and glutathionylcaftaric acid were calculated as caffeic acid equivalents. The analysis was carried out at the Department of Wine Chemistry and Beverage Research at the Geisenheim Research Center.

3. 3 . 1 . 1

 311 Temperature and precipitationFrom a meteorological point of view the vintages 2008, 2009 and 2010 showed very different conditions during each growing season. This can be shown with the measure of growing degree days (GDD), which is a measure for temperature favouring photosynthetic activity of a plant[START_REF] Williams | Validation of a model for the growth and development of the Thompson seedless grapevine. I. Vegetative growth and fruit yield[END_REF] (Fig.3-2).The vintage 2008 (1724 GDD) showed relatively cool weather during March and April and high temperatures from May to August, contributing highly to total GDD during that vintage.Therefore early phenological stages as inflorescence, flowering and fruit development were advanced. Declining temperatures during September favoured a long ripening period and an early harvest date in October. For the vintage 2009 (1988 GDD) early phenological stages of the growing season were positively influenced by mild temperatures from April to June. Hot weather in July and August and relatively high temperatures in September and October led to an extremely long ripening period from early August to mid-October. With relatively warm temperatures in March and April early phenological stages were promoted in the vintage 2010 (1694 GDD). Due to cold weather in May and early June during flowering there was no good fertilisation to develop fruits. High temperatures during June and July favoured early veraison. The ripening of the berries was slowed down by relatively cool temperatures during August and September. Due to high pest pressure, the grapes were harvested at the beginning of October. Although the total precipitation quantities during the observed growing period were relatively stable, the precipitation pattern during the growing season of the three vintages showed high variability. Showing a rainfall of 458 mm in 2008, 408 mm in 2009 and 508 mm in 2010

Fig. 3 - 2 Fig. 3 - 3

 3233 Fig. 3-2 Monthly (bars) and accumulated growing degree days (lines) of the three single seasons 2008, 2009 and 2010

  measure of δ 13 C (van[START_REF] Pineau | Spécifité aromatique des vins rouges de Bordeaux -étude de leurs nuances de fruit rouges et fruits noirs[END_REF] was applied to compare vintages and viticultural treatments and determine their water status level over the ripening periods.3.3.1.2.1 Pre-dawn leaf water potential Ψ (PD)For the vintages 2008 and 2009 significant differences in plants' pre-dawn leaf water potentials could be established during the ripening period by drip irrigation. Due to excessive rainfall from July to October in 2010 no water deficit was observed, therefore irrigation was not applied.3.3.1.2.2 Fractionated Transpirable Soil Water (FTSW) derived Ψ (PD)Comparing the non-irrigated control treatments of the concerned vintages, different trends in vines' water status during the growing periods were observed.In 2008 the pre-dawn leaf water potential (Ψ (PD) ) dropped below the irrigation threshold (Ψ (PD-IT) = -0.3 MPa) early as in the mid of June until late July. Strong rainfall favoured a backfill of the soil water reservoir and therefore water availability. The vines Ψ (PD) dropped below irrigation threshold again at late August and were kept stable for a month before dropping to the growing seasons' minimum of Ψ (PD) = -0.8 MPa in late September.

Fig. 3 - 4

 34 Fig. 3-4 Vintage 2008: pre-dawn leaf water potential Ψ (PD) (n = 8) trend of the non-irrigated control treatment (C) in relation to daily mean temperature and rainfall

Fig. 3 -

 3 Fig. 3-7 δ 13 C values for grape musts from viticultural treatments of the three vintages 2008, 2009, 2010 for the grape variety Riesling. Musts' δ 13 C values indicating different water deficit levels during ripening period for vintages and viticultural treatments; with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison; error bars indicate standard deviation (n=3)

3 4

 34 Fig. 3-8 'Box Plots' for the percentage of grape cluster sun exposure (n = 6) in vintage 2009 in Riesling vines (with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison)

Fig. 3 -Fig. 3 -

 33 Fig. 3-10 Berry weight [g/berry] of different treatments at harvest of the three vintages 2008, 2009 and 2010 (with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison) Noticeable in this context, was a decline of the TSS slope for the non-irrigated treatment (C) between the second (01.09.2009; JD 244) and the third (15.09.2009; JD 258) sampling date. Irrigated treatments (I, IdB, IdV) showed an uniform increase in TSS values during this period.

Fig. 3 -

 3 Fig. 3-12 α-Amino bound nitrogen (N-OPA) concentration and berry weight development during the ripening period for the vintage 2009 (with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison) Regarding the viticultural treatments of 2010, no differences were observed concerning TSS and TA in the berry extracts during the ripening period. In 2009 the non-irrigated control treatment (C) showed higher organically bound α-amino nitrogen concentrations in the berry extracts after veraison than the irrigated treatments (I, IdB, IdV) at the same time. This effect coincidenced with lower berry weight for the non-irrigated control treatment in comparison to irrigated ones (Fig. 3-12).

  concentrations than the corresponding treatment without leaf removal (I) for the vintage 2009 (104 µg/L; 110 µg/L and 87 µg/l respectively) as well as for the vintage 2010 (22 µg/L and 29 µg/L respectively). In wines from the vintage 2008 the differences in concentrations were not statistical significant but the same tendency was observed (51 µg/L and 57 µg/L). For α-terpineol a similar pattern was observed. α-Terpineol concentrations in the wines of the vintages 2008 and 2010 were 37 µg/L and 24 µg/L for the defoliated treatments (IdV in 2008, IdB in 2010) and 19 µg/L and 30 µg/L for the not defoliated irrigated treatments (I). The same tendency was observed for 2009, despite differences were not significant.

C 13 -

 13 norisoprenoids vitispirane and TDN free and acid liberated quantities differed upon different viticultural treatments in grape must. The water status seemed to influence vitispiranes' and TDN's concentrations, favouring both vitispirane and TDN precursor formation in musts obtained from berries grown under weak to moderate water deficit levels during the warmer vintage 2009 (compared within 2008: C and 2009: I). In grape must obtained from the treatment grown at a moderate to severe water deficit level, the potential of vitispirane increased, whereas at the same time the potential of TDN decreased (compared within 2009: C and 2009: I).Similar observations were made for the finished wines after 12 months and after 22 months of bottle storage for free C 13 -norisoprenoids. Interestingly no differences for vitispirane and TDN concentrations were observed between the wines from the non-irrigated control (C) and the irrigated treatment (I) within the 2009 vintage regarding the water deficit level after 12 months, and then after 22 months.In grape musts from the viticultural treatments, which showed only weak or no water deficit during the ripening period (2008: I; 2010: C, I) vitispirane concentrations formed from precursors after acid hydrolysis were lower in the warmer vintage 2008, which showed higher

3 . 3 . 7 . 1

 3371 concern the following possibly influencing factors on the potential of C 13 -norisoprenoid concentration in grapes and volatile C 13 -norisoprenoid concentrations analysed in aged wine i) the effect of water status ii) the effect of micro climate manipulation iii) the effect of vintage and temperature Discussion on C 13 -norisoprenoids in grape must i) the effect of water status

  effect of vintage generally is ambivalent. Concentrations of vitispirane and TDN in the wines from treatments of the same water status (2010: C, 2008: I and 2008: C, 2009: I) were linked differently to temperatures during the growing season expressed as GDD. For viticultural treatments showing no or weak water deficit, vitispirane and TDN concentrations were found to be elevated in the wines of the colder vintage 2010, whereas for the treatments showing weak to moderate water deficit higher vitispirane and TDN concentrations were analysed in the wines for the warmer vintage 2009 by means of GDD. In fact, this would suggest that the vines' water status can alter the effect of temperature during the growing season on free C 13 -norisprenoid concentrations in wines either due to direct precursor metabolisation or due to secondary factors as substrate delivery for vitispirane and TDN formation, which could be used in the transformation reaction during fermentation and bottle aging.

  treatments (I) (679 µg/L). The concentrations decreased upon the timing of leaf removal, showing lower GSH-S-Prc concentration in grape must from the treatment already defoliated at flowering (IdB) in comparison to the must of the treatment defoliated at veraison (IdV) (492 µg/L and 603 µg/L respectively). Grape musts' concentrations of cys-S-prc only showed a significant difference for the irrigated treatment, which was defoliated at flowering (IdB) (123 µg/L). This concentration was elevated in comparison to the musts from all other treatments (C: 64 µg/L; I: 55 µg/L and IdV: 67 µg/L). The non-irrigated control treatment (C) showed the highest assimilable nitrogen content (226 mg/L) in grape must within all viticultural treatments (I: 193 mg/L; IdB: 167 mg/L; IdV: 206 mg/L), with the lowest value observed for the treatment, which was irrigated and defoliated at flowering (IdB).

  i) for GSH, caftaric acid and GRP Compared to the berry extracts, lower GSH concentrations were measured in grape musts, corresponding to a decrease by the factor 30 -50. In the vintage 2009, the berry extracts from the non-irrigated control treatment (C) showed at harvest date a concentration of 25.7 mg/L GSH. At the same stage, GSH concentrations ranging from 33.6 mg/L to 37.8 mg/L were observed in the berry extracts of the irrigated viticultural treatments (I, IdB, IdV). After pressing, no grape must from the corresponding viticultural trials was shown to exceed GSH concentration of 1 mg/L. The same effect was observed for the vintage 2010, when the concentration of GSH in berry extracts ranged from 47.5 mg/L to 51.1 mg/L and did not exceed 1.3 mg/L in grape musts after pressing.Caftaric acid (CA) concentrations decreased in 2009 from berry samples to grape must by factors of 1.8 to 5.1. The strongest decrease was observed for the irrigated treatment, which was not defoliated (I), leading to lowest CA concentrations in grape must (23.2 mg/L) within all viticultural treatments (C: 50.8 mg/L; IdB: 68.9 mg/L; IdV: 54.4 mg/L). For the non-irrigated control (C) and those treatments being irrigated and defoliated (IdB; IdV) the factors of decrease were 2.2, 1.8 and 2.0 respectively and led to the same concentration pattern like in the berry extracts, but at a lower level.

  the vintage 2009, GSH-S-prc concentrations in the berry extracts from the non-irrigated control treatment (C) were 174 µg/L. In the corresponding grape must, the GSH-S-prc concentration was at 214 µg/L. For irrigated treatments (I; IdV; IdB) GSH-S-prc concentrations were shown to range from 106 µg/L to 180 µg/L in the berry extracts and 492 µg/L to 679 µg/L in the corresponding grape musts. In the vintage 2010 the concentrations for this parameter ranged from 111 µg/L to 150 µg/L in berry extracts and 205 µg/L to 267 µg/L in the corresponding grape musts.

  ). For 2008, wines showed significant lower 3SH concentration in those from the non-irrgated treatment (C) (206 ng/L) in comparison to those from the irrigated treatment without leaf removal (I) (313 ng/L). In wines from the irrigated and defoliated treatment (IdV) 3SH concentrations were observed to be lower in comparison to those from the irrigated treatment without leaf removal (I) (275 ng/L and 313 ng/L respectively). In the vintage 2009, low 3SH concentrations were observed in wines from the non-irrigated control treatments (C) (156 ng/L). Within the irrigated treatment of the vintage 2009, the one, which was defoliation at veraison (IdV), was not shown to result in lower 3SH concentration in comparison to wines from the non-defoliated treatment (I) (328 ng/L and 327 ng/L respectively). Interestingly wines obtained from the viticultural treatment, which was irrigated and then defoliated at flowering (IdB) showed higher 3SH concentrations (412 ng/L) in comparison to the two other irrigated treatments (I: 327 ng/L; IdV: 328 ng/L), whereas this difference was not statistically significant. In 2010, the non-irrigated treatment (C) produced wines showing significant lower 3SH concentration than the 'irrigated' treatment (I), which in fact was not irrigated in that year (326 ng/L and 984 ng/L respectively). Defoliation at flowering (IdB) corresponded to lower 3SH concentrations in the finished wines regarding the non-defoliated irrigated treatments (I) (287 ng/L and 984 ng/L respectively).

Fig. 3 -

 3 Fig.3-13 Hypothetical S-3-(hexan-1-ol)-glutathione (GSH-S-prc) and S-3-(hexan-1-ol)cysteine (cys-S-prc) formation pathway in grapevines, induced by abiotic or biotic (B. cinerea) stressors. Free 3-sulfanylhexan-1-ol (3SH) in wine is produced during alcoholic fermentation (reproduced afterThibon et al., 2011)

  treatments C and I were less pronounced in petrol / kerosene attribute than IdV. Grapefruit and lemon aroma were tendencially strongest in C, whereas IdV had tendencially strongest minerality character and was less pronounced in floral and fruity attributes as abricot, peach and melon.

4. 3 . 2

 32 Comparison of the odoriferous zones in thiol selective aroma extracts (TSAE) of typical Riesling and typical Sauvignon blanc style wines by means of GC-O As the complexity of global organic aroma extracts was causing problems in the reliability of detecting odours at higher oven temperatures during GC-O, preparing selective extracts by enrichment of molecules showing a certain chemical property or functional group (e.g. thiol) can be a way to eliminate complexity in the aromagram during GC-O. Sauvignon blanc style wines were shown to express poor Riesling wines typicality (chapter 1) and the thiols 4MSP, A3SH and 3SH are well understood to be aromatic marker molecules for Sauvignon blanc style wines. Therefore it was expected that thiol selective aroma extracts of representative Riesling wines would show different odoriferous zones during GC-O analysis, than representative Sauvignon blanc style wines. In total 57 OZ were detected by means of GC-O on polar polyethylene glycol stationary phase (BP20) in thiol selective aroma extracts (TSAE) of typical Riesling and typical Sauvignon blanc style wines. Typical Riesling wines TSAE showed 38 OZ, whereas those of typical Sauvignon blanc style wines showed 53 OZ on polar polyethylene glycol stationary phase (BP20) (Table 4-8).

4. 3 . 4

 34 Comparison of the aroma extract fractions (AEF) of typical Riesling wines and typical Sauvignon blanc style wines by means of triangle tests and Quantitative Descriptive Analysis (QDA) -Fractions 54 and 55 Hydroalcoholic solutions of AEF 54 and 55 of a typical Riesling and a typical Sauvignon blanc style wine, representing an equivalent of 180 mL of wine, were tested orthonasally in triangle tests by 22 judges. These fractions were judged to be different at a significance level of 1%, verifying the results from 4.3.3. The hydroalcoholic solutions containing AEF 54 and AEF 55 showed tendencially stronger fruity and floral odours for Riesling wines aroma extract fractions (Fig. 4-1), although results

Fig. 4 - 1

 41 Fig. 4-1 Boxplots showing QDA results for descriptors 'fruity' and 'floral' for 12.7%vol model solutions of fractions 54 and 55 from one typical Riesling (RI) and one typical Sauvignon blanc style wine (SB) (wines 1 and 8; Table 4-1); judgements done on non-segmented scale, normalised to 100 in the figure 4.3.5 Comparison of the aroma fraction reconstitution for typical Riesling wines and typical Sauvignon blanc style wines by means of triangle tests and Quantitative Descriptive Analysis -Fractions 54 and 55 Hydroalcoholic solutions of total reconstituted aroma extracts (RI), partial aroma extract reconstitution (RI-F54/F55) and total aroma extracts reconstitution supplemented with the fractions 54 and 55 (RI-F54/F55) of a typical Riesling wine, representing an equivalent of 180 mL of wine, were tested orthonasally in triangular tests by 16 judges. Aromatic reconstitution solutions RI and RI+F54/F55 were rated to be significantly different from aromatic reconstitution solution RI-F54/F55 at a significance level of (α = 0.05).

Fig. 4 - 2

 42 Fig. 4-2 Boxplots showing QDA results for the descriptors 'fruity' and 'floral' for reconstitution experiments with and without fractions 54 and 55 from typical Riesling (R) (wine 1; Table4-1); judgements done on non-segmented scale, normalised to 100 in the figure

1

 1 One-dimensional GC-O/HR-TOF-MSIn order to identify the aromatic compound responsible for OZ 27, one dimensional GC-MS experiments were carried out on AEF 55 using a polar polyethylene glycol stationary phase (Agilent DB-Wax).

Fig. 4 -

 4 Fig. 4-3 TIC of monodimensional GC-O/MS (DB-Wax; 50m*0,22 mm*0,25 µm) of AEF 55 (with RT 41.46 corresponding to LRI 2064)

Fig. 4 - 4

 44 Fig. 4-4 Mass Spectra of trans-ethyl cinnamate a) Peak at LRI 2155 / LRI 1500 from AEF 55 b) NIST ® data base

2

 2 Determination of the odour detection threshold of

Fig. 4 -Fig. 4 - 3

 443 Fig. 4-6 Determination of the odour detection threshold of trans -ethyl cinnamate in model wine solutions

Fig. 4 -Fig. 4 -

 44 Fig. 4-8 Data set from the German panel showing trans-ethyl cinnamate concentrations in relation to their perceived Riesling wines' typicality (Chapter 1)

Fig. 4 -

 4 Fig. 4-10 Proportions of Judges indicating wines as being a Riesling wine for four different wines being supplemented with trans-ethyl cinnamate resulting in sub-odour detection threshold (c (sub-threshold) 0.2 µg/L), odour detection threshold (c (threshold) 1.5 µg/L) and super-odour detection threshold concentration (c (super-threshold) 3.0 µg/L); error bars indicating standard errors; Ri indicating Riesling wine 1 to 3; WB indicating Pinot blanc (Weissburgunder) wine

4. 3 .Fig. 4 -

 34 Fig. 4-11 Concentrations of trans-ethyl cinnamate in finished wines depending on the vintage, water status of grape vines and grape berries' sun exposure. (C Control; not irrigated and not defoliated experimental plot, I irrigated experimental plot, IdB experimental plot of vines, which is irrigated and defoliated at flowering and at veraison, IdV experimental plot of vines, which is irrigated and defoliated at veraison) Despite being relatively small, significant differences -except for 2008 vintage -in trans-ethyl cinnamate concentrations were detected in wines after 12 months of storage. Wines obtained from the viticultural experimental plots being not irrigated (C) showed lower concentrations in comparison to their irrigated pendants (I) (Fig. 4-11). Furthermore, wines from plots being defoliated showed significant lower concentrations in comparison to those from not defoliated experimental plots for the vintages 2009 and 2010, resulting in lowest trans-ethyl cinnamate concentrations in wines from vineyard plots being defoliated at flowering (Table[4][5][6][7][8][9][10][11].

  Fig. 4-1 experim Error ba

  wines was shown by

  conclusion this work clearly demonstrated that predicted climate change scenarios are likely to impact Riesling wines' aromatic typicality. This was observed by sensory as well as by instrumental analytical methods. Moreover this work gave new insights into the concept of typicality [french typicité] and applied novel sensory and statistical approaches, which open up new perspectives in aromatic typicality related scientific questions. The importance of perceived citrus fruit, floral, and aging related odours for the Riesling wines' aromatic concept was demonstrated and the importance of the marker molecules 3-sulfanylhexan-1-ol (3SH), linalool and TDN were pointed out. From the viticultural studies, new questions arise towards environmental impacts on bottle aging behaviour of Riesling wines concerning the development of the 'kerosene' odour. This represents a very important aspect to study in the future. Due to this study's contribution to the increase of knowledge about the biosynthesis of the precursor molecules of 3-sulfanylhexan-1-ol, a new perspective is opened for managing grape musts aromatic potential regarding this highly potent aroma compound. Being able to manage these factors of wine aroma would clearly help winemakers to maintain and improve the production of wines with a high degree of typicality in the future. Moreover, the identification of trans-ethyl cinnamate as an impacting molecule of Riesling wines' aromatic typicality was realised. This compound showed to be influenced by both, viticultural conditions and bottle storage, leading to the conclusion that it can impart presumably mostly in bottle age aroma of wines. 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P., Vila, B., Bousquet-Mélou, A., Greff, S., Bonin, G. and Fernandez, C. (2007), Water deficit stress induces different monoterpene and sesquiterpene emission changes in mediterranean species. Relationship between terpene emissions and plant water potential. Chemosphere 67 2 276-284 Ou, C., Du, X., Shellie, K., Ross, C. and Qian, M. C. (2010), Volatile compounds and sensory attributes of wine from cv. Merlot (Vitis vinifera L.) grown under differential levels of water deficit with or without a Kaolin-based, foliar reflectant particle film Journal of Agricultural and Food Chemistry 58 24 12890-12898 P Park, S. K., Morrison, J. C., Adams, D. O. and Noble, A. C. (1991), Distribution of free and glycosidically bound monoterpenes in the skin and mesocarp of Muscat of Alexandria grapes during development. Journal of Agricultural and Food Chemistry 39 3 514-518 Parr, W. V., Heatherbell, D. and White, K. G. (2002), Demystifying wine expertise: Olfactory threshold, perceptual skill and semantic memory in expert and novice judges. Chemical Senses 27 747-755 Parr, W. V., Green, J. A., White, K. G. and Sherlock, R. R. (2007), The distinctive flavour of New Zealand Sauvignon blanc: Sensory characterisation by wine professionals. Food Quality and Preference 18 6 849-861 Swiegers, J. H., Pretorius, I. S., Allen I. Laskin, J. W. B. and Geoffrey, M. G. (2005), Yeast modulation of wine flavor in Advances in applied microbiology; (Eds); Academic Press, pp. 131-175 Symoneaux, R., Perrin, L., Wilson, D., Maitre, I. and Jourjon, F. (2010), La typicité sensorielle des vins d'appellation : Comment la mesurer avec les professionels, comment l'aborder avec les consommateurs ? Qualité et Environment 142 94-101 T Tenenhaus, M., Pages, J. R. M., Ambroisine, L. and Guinot, C. (2005), PLS methodology to study relationships between hedonic judgements and product characteristics. Food Quality and Preference 16 4 315-325 Ter Braak, C. J. F. and Verdonschot, P. F. M. (1995), Canonical Correspondence Analysis and related multivariate methods in aquatic ecology. Aquatic Sciences 57 3 255-289 Thibon, C., Cluzet, S., Mérillon, J. M., Darriet, P. and Dubourdieu, D. (2011), 3-sulfanylhexanol precursor biogenesis in grapevine cells: The stimulating effect of Botrytis cinerea. Journal of Agricultural and Food Chemistry 59 4 1344-1351 Thibon, C., Marullo, P., Claisse, O., Cullin, C., Dubourdieu, D. and Tominaga, T. (2008), Nitrogen catabolic repression controls the release of volatile thiols by Saccharomyces cerevisiae during wine fermentation. FEMS Yeast Research 8 7 1076-1086 Thibon, C., Dubourdieu, D., Darriet, P. and Tominaga, T. (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 Chemistry 114 4 1359-1364 Tominaga, T. and Dubourdieu, D. (2006), A novel method for quantification of 2-methyl-3furanthiol and 2-furanmethanethiol in wines made from Vitis vinifera grape varieties. Journal of Agricultural and Food Chemistry54 1 29-33

  sodium salt p-hydroxymercuribenzoate sodium salt S-3-(hexan-1-ol)-glutahione-d5 S-3-(hexan-1-ol)-glutahione-6-trimethyl-10-methylidene-1-oxaspiro[4.5]dec-8-ene

  Total nitrogen concentration after KJELDAHL -decomposition detected as ammonia ..................................................................................................... Free ammonia in grape juice and grape must ............................................ Reduced glutathione ................................................................................... Phenolic compounds ................................................................................ Analysis of aroma compounds ..................................................................3.2.10Harvest and wine making ......................................................................... 3.2.11 Sensory analysis ....................................................................................... Results and Discussion ............................................................................ General climatic conditions ....................................................................... Temperature and precipitation ..................................................................

	3.2.8.7
	3.2.8.8
	3.2.8.9
	3.2.8.10
	3.2.8.11	Cysteinylated and glutathionylated precurser of 3-sulfanylhexan-1-ol .....
	3.2.9
	3.3
	3.3.1
	3.3.1.1

3.3.1.2 Water status in three years ....................................................................... 3.3.1.2.1 Pre-dawn leaf water potential Ψ (PD) ........................................................... 3.3.1.2.2 Fractionated Transpirable Soil Water (FTSW) derived Ψ (PD) .................... 3.3.1.2.3 δ 13 C -isotope Ratio ................................................................................. 3.3.1.3 Canopy micro-climate -effects of defoliation ............................................ 3.3.1.4 Infection by Botrytis cinerea at harvest ..................................................... 3.3.2 Development of grapes' maturity .............................................................. 3.3.3 Monoterpenol and C 13 -norisoprenoid concentrations ............................... 3.3.3.1 Monoterpenols in grape must ................................................................... 3.3.3.2 Monoterpenol composition of wines after 12 months ............................... 3.3.3.3 C 13 -norisoprenoids in grape must ............................................................. 3.3.3.4 C 13 -norisoprenoid composition in wines after 12 months .......................... 3.3.3.5 C 13 -norisoprenoid composition in wines after 22 months .......................... 3.3.4 Discussion on monoterpenols in grape must ............................................

Table 1 -

 1 1 Riesling vineyard surface world-wide (Data fromDWI, 2011a)

	Country	total Riesling vineyard area in [ha] [%]
	Germany	22601	61.4
	Australia	4256	12.1
	France	3407	9.9
	USA	1700	4.9
	Austria	1643	4.8
	New Zealand	636	2.5
	Canada	440	1.3
	Chile	293	0.8
	South Africa	276	0.8
	others	193	1.5

Table 1 -

 1 2 Sauvignon blanc vineyard area world-wide (Data from[START_REF] Galet | Cépages et vignobles de France. ii. L'ampélographie française[END_REF] *Data from Lott et al.,

	2010)
	Country	total Sauvignon blanc vineyard area in [ha] [%]
	France	19974	44.4
	Chile	5572	12.4
	USA	5181	11.5
	South Africa	3900	8.7
	Italy	2947	6.5
	Australia	1725	3.8
	Hungary	1200	2.7
	New Zealand	857	1.9
	Austria	582	1.3
	Germany*	434	1.0
	others	2609	5.8

  farnesyl diphosphate as sesquiterpene, whereas reaction of farnesyl diphosphate with IPP results in geranylgeranyl pyrophosphate as diterpene. Tail-to-tail connection of either two units farnesyl pyrophosphate or either two units of geranylgeranyl pyrophosphate lead to squalene as triterpene or 16-trans-phytoene as tetraterpene

γ,γ-dimethylallyl pyrophoshate as electrophilic reaction partner for the nucleophilic methylene group of IPP. Connection in this position leads to geranyl pyrophosphate as monoterpene. Subsequent head-to-tail reaction of geranyl diphosphate with IPP yields (carotenoid).

Table 2

 2

	-1 Applied standards in analysis of compounds by means of the 'Kaltron'-method, purity and suppliers; (IS) indicates compounds used as internal standard
	Compound	Purity	Supplier
	ethyl acetate	>99%	Sigma-Aldrich, Seelze, Germany
	2-methylpropan-1-ol (iso-butanol)	>99%	Sigma-Aldrich, Seelze, Germany
	ethyl propanoate	99%	Sigma-Aldrich, Seelze, Germany
	3-methyl-1-butanol (iso-amyl alcohol)	99%	Sigma-Aldrich, Seelze, Germany
	2-methyl-2-butanol (tert-amyl alcohol)	99%	Sigma-Aldrich, Seelze, Germany
	ethyl 2-methylpropanoate (ethyl iso-butyrate)	99%	Sigma-Aldrich, Seelze, Germany
	ethyl butanoate (ethyl butyrate)	>98%	Sigma-Aldrich, Seelze, Germany
	ethyl 2-hydroxypropanoate (ethyl lactate)	>99%	Sigma-Aldrich, Seelze, Germany
	hexan-1-ol	>99%	Sigma-Aldrich, Seelze, Germany
	3-methylbutyl acetate (iso-amylacetate)	>98%	Sigma-Aldrich, Seelze, Germany
	2-methylbutyl acetate (amylacetate)	99%	Sigma-Aldrich, Seelze, Germany
	caproic acid (hexanoic acid)	>98%	Sigma-Aldrich, Seelze, Germany
	ethyl hexanoate (ethyl caproate)	>99%	Sigma-Aldrich, Seelze, Germany
	hexyl acetate	>98%	Sigma-Aldrich, Seelze, Germany
	trans/cis-linalool oxide	>99%	Sigma-Aldrich, Seelze, Germany
	linalool	95%	Sigma-Aldrich, Seelze, Germany
	2-phenylethanol	>99%	Sigma-Aldrich, Seelze, Germany
	octanoic acid (caprylic acid)	>99%	Sigma-Aldrich, Seelze, Germany
	diethyl succinate (diethyl butanedioate)	>99%	Sigma-Aldrich, Seelze, Germany
	ethyl octanoate (ethyl capryloate)	>99%	Sigma-Aldrich, Seelze, Germany
	α-terpineol	>99%	Sigma-Aldrich, Seelze, Germany
	ethyl 2-phenylacetate (ethyl benzeneacetate)	>98%	Sigma-Aldrich, Seelze, Germany
	2-phenylethylacetate (benzylethyl acetate)	>99%	Sigma-Aldrich, Seelze, Germany
	decanoic acid (capric acid)	>98%	Sigma-Aldrich, Seelze, Germany
	ethyl decanoate (ethyl capriate)	>99%	Sigma-Aldrich, Seelze, Germany
	DMH (2,6-dimethylhept-5-en-2-ol) (IS)	98%	Carl Roth, Karlsruhe, Gemany
	cumene (IS)	99%	Sigma-Aldrich, Seelze, Germany

Table 2

 2

	-2 Applied standards in analysis of C13-norisoprenoids, purity and suppliers; (IS) indicates compounds used as internal standard
	Compound	Purity	Supplier
	cumene (IS)	>99%	Sigma-Aldrich, Seelze, Germany
	DCA (dichloroaniline) (IS)	>99%	Sigma-Aldrich, Seelze, Germany
	vitispirane isomers	95% 1	gifted by Dr. A. Rapp, Sieberdingen, Germany
	TDN (1,1,6-trimethyl-1,2-dihydronaphthalene)	98% 1	Faculté d'Oenologie, Bordeaux, France
	β-damascenone	>99.9% gifted by Firmenich, Geneva,Switzerland
	β-ionone	>99%	Sigma-Aldrich, Seelze, Germany
	TPB (1,2,4-trimethylphenyl-3-butadiene)	98% 1	Faculté d'Oenologie, Bordeaux, France
	trans-ethyl cinnamate	99.9%	Sigma-Aldrich, Seelze, Germany
	1 purity determined by means of total ion chromatogram peak areas oft the pure standard

Table 2

 2

	-3 Applied standards in volatile sulfur low boiling sulfur compounds, purity and suppliers; [ ] indicates the compound used for standard curve; (IS) indicating compounds used as internal standard
	Compound	Purity	Supplier
	[sodium sulfide]	>99%	Sigma-Aldrich, Seelze, Germany
	methanethiol	>99%	Sigma-Aldrich, Seelze, Germany
	methyl sulfide	>97%	Alfa Aeser, Karlsruhe, Germany
	carbon disulfide	>99%	Acros Organics, Geel, Belgium
	methylthioacetate	>99.9%	Acros Organics, Geel, Belgium
	methyl disulfide	>98%	Alfa Aeser, Karlsruhe, Germany
	ethyl thioacetate	>99.5%	Alfa Aeser, Karlsruhe, Germany
	diethyl disulfide	>99%	Sigma-Aldrich, Seelze, Germany
	dimethyl trisulfide	>98%	Acros Organics, Geel, Belgium
	butylmethyl sulfide (IS)	>98%	Lancaster, Ward Hill, MA, USA
	methyl-iso-propyl sulfide (IS)	>96%	Alfa Aeser, Karlsruhe, Germany

Table 2

 2

	-4 Applied standards in analysis of varietal and polyfunctional thiols, purity and suppliers; (IS) indicates compounds used as internal standard
	Compound	Purity	Supplier
	benzenemethanethiol	>98%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	2-furanylmethanethiol	>98%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	3-sulfanylhexan-1-ol	>98%	Lancaster, Bischheim, France
	3-sulfanylhexyl acetate	>98%	Interchim, Montlucon, France
	4-methyl-4-sulfanylpentan-2-one	>98%	Interchim, Montlucon, France
	ethyl-2-sulfanyl acetate	>98%	Alfa Aesar, Schiltigheim, France
	ethyl-2-sulfanylpropionate	>98%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	ethyl-3-sulfanylpropionate	>98%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	1-methoxy-3-methylsulfanylbutane (IS)	>98%	Oxford Chemicals, Hartlepool, Great Britain
	6-sulfanylhexan-1-ol (IS)	>98%	Interchim, Montlucon, France

Table 2

 2

	-5 Applied standards in analysis of bound and free terpenes and C13-norisoprenoids, purity and suppliers; (IS) indicates compounds used as internal standard
	Compound	Purity	Supplier
	geraniol	>98%	Sigma-Aldrich, Seelze, Germany
	linalool	95%	Sigma-Aldrich, Seelze, Germany
	nerol	>98%	Sigma-Aldrich, Seelze, Germany
	β-citronellol	>95%	Sigma-Aldrich, Seelze, Germany
	trans/cis-linalool oxide	>99%	Sigma-Aldrich, Seelze, Germany
	nerol oxide	>95%	Interchim, Montlucon, France
	α-terpineol	>99%	Sigma-Aldrich, Seelze, Germany
	β-damascenone	>99%	Firmenich, Geneva,Switzerland
	α-ionone	>98.5%	Sigma-Aldrich, Seelze, Germany
	β-ionone	>98.5%	Sigma-Aldrich, Seelze, Germany
	vitispirane isomers	95% 1	gifted by Dr A. Rapp, Sieberdingen, Germany
	TDN (1,1,6-trimethyl-1,2-dihydro-naphthalene)	98% 1	Faculté d'Oenologie, Bordeaux, France
	TPB (1,2,4-trimethylphenyl-3-butadiene)	98% 1	Faculté d'Oenologie, Bordeaux, France
	octan-3-ol (IS)	>98%	Sigma-Aldrich, Seelze, Germany
	DMH (2,6-dimethylhept-5-en-2-ol) (IS)	>98%	Carl Roth, Karlsruhe, Gemany

Table 2

 2

	-6 Applied chemical products, others than volatile standard compounds for Gas Chromatography analysis
	Chemical Product	Purity	Supplier
	resins and cartridges
	Dowex resin 1x2		Acros Organics, Noisy-le-Grand, France
	SPE -LC-18 (500 mg, 6 mL)		Supelco France, Saint Germain-en-Laye Cedex, France
	SPE -SDBL (500 mg, 6 mL)		Phenomenex, Darmstadt, Germany
	other products
	n-alcanes mixture (C6-C23)		Sigma Aldrich, Seelze, Germany
	caffeic acid	>99%	Sigma Aldrich, Seelze, Germany
	CHES	>99%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	citric acid	>98%	Carl Roth, Karlsruhe, Germany
	L-cysteine chloride	>98%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	formic acid	>99%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	hydrochloric acid (conc.)	38%	VWR, Fontenay sous Bois, France
	monobromobimane	>93%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	p-hydroxymercuribenzoate sodium salt	>99%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	S-3-(hexan-1-ol)-glutahione-d5		Faculté d'Oenologie, Bordeaux, France 1
	S-3-(hexan-1-ol)-glutathione		Faculté d'Oenologie, Bordeaux, France 1
	S-3-(hexan-1-ol)-L-cysteine		Faculté d'Oenologie, Bordeaux, France 1
	sodium acetate	>99%	Sigma-Aldrich, Saint-Quentin Fallavier, France
	sodium sulfate (anhydreous)	>99,9% Sigma-Aldrich, Saint-Quentin Fallavier, France
	trans-ethylcinnamate-d5		Faculté d'Oenology, Bordeaux, France 2
	tartaric acid	>99,5% VWR, Fontenay sous Bois, France
	trifluoroacetic acid	>99,5% Sigma-Aldrich, Saint-Quentin Fallavier, France
	Trizma-base	>99,8% Sigma-Aldrich, Saint-Quentin Fallavier, France
	1 synthesized by C. Thibon; 2 synthesized by G. Antalick

Table 2

 2

	-7a Wines used in the present study; x indicates, which wine was tested in which location by which panel (GH: Geisenheim, Hesse, Germany; BX: Bordeaux, Aquitaine, France)
	wine-						panel
	no.	identifier	variety	origin	winery -wine	vintage	GH	BX
	1	RIRH1	Riesling	D -Rheingau	Stefan Breuer -Riesling trocken		x	x
	2	RIRH2	Riesling	D -Rheingau	Schloss Vollrads -Kabinett trocken		x	x
	3	RIRH3	Riesling	D -Rheingau	Weingut der Forschungsanstalt Geisenheim -Von Lade QbA trocken		x
	4	RIRH4	Riesling	D -Rheingau	Schloss Vollrads -Kabinett trocken		x	x
	5	RIRH5	Riesling	D -Rheingau	Schloss Johannisberg -Rotlack Kabinett trocken		x	x
	6	RIRH6	Riesling	D -Rheingau	Schloss Johannisberg -Rotlack Kabinett trocken		x	x
	7	RIRH7	Riesling	D -Rheingau	Weingut Georg Breuer -Riesling Estate Rüdesheim			x
	8	RIRH8	Riesling	D -Rheingau	Schloss Johannisberg -Riesling Grünlack Spätlese		x	x
	9	RIRH9	Riesling	D -Rheingau	Weingut der Forschungsanstalt Geisenheim -Von Lade QbA trocken		x	x
	10	RIRH10	Riesling	D -Rheingau	Hessische Staatsweingüter -Kloster Eberbach -Berg Rottland			x
	11	RIRH11	Riesling	D -Rheingau	Schloss Johannisberg -Riesling Grünlack Spätlese		x	x
	12	RIRH12	Riesling	D -Rheingau	Weingut Robert Weil, Rheingau -QbA trocken		x
	13	RIRH13	Riesling	D -Rheingau	Schloss Vollrads -Edition QbA		x
	14	RIRH14	Riesling	D -Rheingau	Schloss Vollrads -Edition QbA		x
	15	RIAL1	Riesling	F -Alsace	Domaine Bernhard Reibel -Hahnenberg			x
	16	RIAL2	Riesling	F -Alsace	Paul Ginglinger -Grand Cru Pfersichberg			x
	17	RIAL3	Riesling	F -Alsace	Domaine Frédéric Mochel -G.C. Altenberg de Bergbieten -Cuvée Henriette		x	x
	18	RIAL4	Riesling	F -Alsace	Domaine Hugel			x
	19	RIAL5	Riesling	F -Alsace	Domaine Josmeyer -Grand Cru Hengst			x
	20	RIAL6	Riesling	F -Alsace	F.E. Trimbach -Riesling Reserve			x
	21	RIAL7	Riesling	F -Alsace	Domaine Albert Mann -Rosemberg		x	x

Table 2 -

 2 7b Wines used in the present study; x indicates, which wine was tested in which location by which panel (GH: Geisenheim, Hesse, Germany; BX: Bordeaux, Aquitaine, France)

	wine-
	no.	identifier	variety	origin	winery -wine

Table 2 -

 2 8 Instrumental settings for 'Kaltron' extract analysis

	Autosampler	MSP4 (Gerstel, Mühlheim a.d.R., Germany)
	Injector	Cooled Injection System CIS 3 (Gerstel, Germany)
	CIS-Parameter	Splitless (1 min)
	Temperatures (CIS)	30 °C (0.01 min) -230 °C at 12 °C/s; Hold 4 min
	Gas Chromatograph	GC 5890 Series II (Hewlett Packard, USA)
	Capillary Column	Varian VF-5MS (5% phenyl methyl siloxane)
		(60m x 320 µm ID x 1 µm FT)
	Carrier Gas	Helium; constant flow (1 mL/min); Initial pressure 41.5 kPa;
		Average velocity 27 cm/s; Outlet pressure vacuum
	Oven Program	40 °C (1 min) -125 °C at 3 °C/min; 125 °C -200 °C at 6 °C/min;
		Hold 14.2 min
	Detector	5972 Mass Selective Detector (Hewlett Packard, USA)
	Temperatures	Transfer line 210 °C ; MS Quad 150 °C; MS Source 230 °C
	Aquisition Mode	Scan
	Ionisation	70 eV
	SCAN parameters	m/z 35 -250; 3.43 Scans/sec
	Data acquisition	Agilent Chemstation (Agilent Technologies, USA)

Table 2 -

 2 Chromatographic conditions for C 13 -norisoprenoid analysis Instrumental settings are given in Table 2-9: 9 Chromatographic conditions for C 13 -norisoprenoid analysis

	Autosampler	MSP4 (Gerstel, Mühlheim a.d.R., Germany)
	TDU	Transfer temperature fixed (300 °C); splitless; sample remove
	Temperatures (TDU)	20 °C (0.01 min) -280 °C at 120 °C/min; Hold 4 min
	Injector	Cooled Injection System CIS 4 (Gerstel, Germany)
	CIS-Paramter	solvent vent; cryo cooling used
	Temperatures (CIS)	-150 °C (0.01 min) -280 °C at 12 °C/s; Hold 5 min
	Gas Chromatograph	GC 6890 (Agilent Technologies, USA)
	Capillary Column	J & W Scientific HP-5 capillary column (5% Phenyl Methyl
		Siloxane) (60m x 320 µm ID x 0.25 µm FT)
	Carrier Gas	Helium; constant flow (1.1 mL/min); Initial pressure 41.5 kPa;
		Average velocity 27 cm/s; Outlet pressure vacuum
	Oven Program	60 °C (
	Detector
	Temperatures
	Aquisition Mode
	Ionisation
	SCAN parameters
	SIM parameters
	Data aquisition

2.3.3.2 1 min) -110 °C at 5 °C/min; 110 °C -170 °C at 3 °C/min; 170 °C -230 °C at 30 °C/min; Hold 9.33 min MSD 5973 N (Agilent Technologies, USA) Transfer line 280 °C ; MS Quad 150 °C; MS Source 230 °C Scan/SIM EM voltage 2141.2 eV m/z 35 -250; Sample # 2 A/D Samples 4 listed in Appendix 16 Agilent Chemstation (Agilent Technologies, USA)

  Solutions for sample preparation2.3.5.2.1 Solution for pH adjustmentFor adjusting the pH of the solution and of the samples during sample preparation 10 M sodium hydroxide solution was prepared using H 2 O.

	2.3.5.2.2 Solution for complex formation
	2 mM of p-hydroxymercuribenzoate sodium salt (p-HMB) were disolved in a 0.1 M 2-amino-
	2-(hydroxymethyl)-propan-1,3-diol (TRIZMA ® ) aqueous buffer solution to result in 1 L
	solution, which then was adjusted to pH 10.
	2.3.5.2.3 Acetate buffer solution

2.3.5.2 50 mL of 0.1 M sodium acetate buffer solution was prepared for each sample using H 2 O and was then adjusted to pH 7. 2.3.5.2.4 Solution for analyte elution 60 mL of 35 mM L-cysteine chloride in H 2 O was prepared for each sample and adjusted to pH 7.

Table 2 -

 2 10 Chromatographic conditions for thiol extract analysis

	Autosampler
	Injector
	Mode
	Temperature
	Gas Chromatograph
	Capillary Column
	Carrier Gas
	Oven Program
	Detector
	Temperatures
	Aquisition Mode
	Ionisation
	SIM parameters
	Data aquisition

MSP4 (Gerstel, Mühlheim a.d.R., Germany) Split -splitless Injector (Agilent technologies, USA) Splitless (1 min); constant temperature 230 °C GC 5890 Series II (Hewlett Packard, USA) SGE -BP20 (SGE Europe Ltd, UK) (50m x 250 µm ID x 0.22 µm FT) Helium; constant flow (1 mL/min); Initial pressure 151 kPa; Average velocity 27 cm/s; Outlet pressure vacuum 45 °C (10 min) -230 °C at 3 °C/min; Hold 15 min 5973 Mass Selective Detector (Hewlett Pacckard, USA) Transfer line 250 °C ; MS Quad 150 °C; MS Source 230 °C SIM 70 eV see Appendix 18 Agilent Chemstation (Agilent Technologies, USA)

Table 2 -

 2 Chromatographic conditions for potentially volatile terpenes and C 13 -norisoprenoids (PVTN) analysis Instrumental settings are given in Chromatographic conditions for free and bound terpenes and C 13 -norisoprenoids extract analysis

	Autosampler	Tri Plus Autosampler (Thermo Fisher Scientific, USA)
	Injector	Programmable Temperature Vaporizing (PTV) Injector (Thermo
		Fisher Scientific, USA)
	Mode	PTV Splitless (splitless time 1.5 min)
	Temperatures	35 °C -180 °C at 14.5 °C/s
	Transfer temperature	180 °C
	Transfer time	1 min
	Gas Chromatograph	Trace GC Ultra (Thermo Fisher Scientific, USA)
	Capillary Column
	Carrier Gas
	Oven Program
	Detector
	Temperatures
	Aquisition Mode
	Ionisation
	SIM parameters
	Data aquisition

2.3.6.2 Agilent DB-Wax (Agilent Technologies, USA) (30 m x 250 µm ID x 0.5 µm FT) Helium; constant flow (1.4 mL/min); Initial pressure 151 kPa; Average velocity 27 cm/s; Outlet pressure vacuum 40 °C (1 min) -60 °C at 10 °C/min; 60 °C -200 °C at 3 °C/min; 200 °C -220 °C at 10 °C/min; Hold 10 min ITQ 900 Ion Trap MS (Thermo Fisher Scientific, USA) Transfer line 240 °C; MS Source 200 °C SIM 70 eV Segment 1 (9 -18 min): m/z 81, 91, 121, 136, 139, 154 Segment 2 (18 -20.5 min): m/z 69, 139, 154 Segment 3 (20.5 -22.5 min): m/z 83, 95, 101, 105, 112, 121, 136, 169 Segment 4 (22.5 -26 min): m/z 79, 83, 93, 109, 124, 137, 152, 155 Segment 5 (26 -34 min): m/z 93, 121, 136, 177, 192 Segment 6 (34 -36.5 min): m/z 91, 93, 108, 109, 121, 123, 138, 142, 157, 172 Segment 7 (36.5 -38 min): m/z 104, 108, 119, 121, 139 Segment 8 (38 -39 min): m/z 93

Table 2

 2

-7. 2.5.1.2 Panels' homogeneity -Principle Component Analysis (PCA) and Analysis of Variance (ANOVA) 2.5.1.2.1 Typicality ratings -Principle Component Analysis (PCA)

Table 2 -

 2 12 Average reproducibility indices (R i ) (n=2) for single judges and total panels of the German panel (Geisenheim) and French panel (Bordeaux) regarding descriptor family frequencies

		German panel	French panel
		judges	R i	judges	R i
		A	0.16	A	0.29
		B	0.10	B	0.38
		C	0.17	C	0.20
		D	0.36	D	0.39
		E	0.12	E	0.29
		F	0.16	F	0.28
		G	0.15	G	0.02
		H	0.29	H	0.30
		I	0.24	I	0.33
		J	0.17	J	0.33
		K	0.24
		total panel	0.59	total panel	0.68
	2.5.4	Discussion on panel performance for the descriptive task
	Good consistency between the two panels concerning odour vocabulary was expected. Due
	to working with similar products, wine professionals would be assumed to develop similar
	linguistic structures concerning the specific product facilitating within-group communication
	(O'Mahoney, 1991; cited by

Table 2 -

 2 13 Transformations conducted in General Procrustes Analysis (GPA)

	source	DF	sum of squares mean squares F	Pr > F
	residuals after scaling	149	224.00	1.50
	scaling	1	46.08	46.08	30.649 < 0.001
	residuals after rotation	150	270.08	1.80
	rotation	190	422.15	2.22	1.478	0.006
	residuals after translation 340	692.22	2.04
	translation	20	407.45	20.37	13.551 < 0.001
	corrected total	360	1099.68	3.05

DF: degrees of freedom; F: f-value; Pr > F: indicating significance at α<0.05 for difference between 'before' and after 'transformation'

Table 2 -

 2 14 Correlation factors r for each descriptor family and each panel for the first two dimensions (F1 and F2) in the General Procrustes Analysis for 18 intersecting wines from sensory analysis (Correlation factor r indicates correlation with the Factor (F), if for both panels the correlation factors are similar there is good compliance regarding the concerning descriptor family; values are interpretable as for classical Pearson product-moment correlations)

		correlation factor r
	descriptor family	German panel		French panel
		F1	F2	F1	F2
	vegetal	0,942	0,015	0,904	-0,049
	sauvignon	0,978	-0,012	0,918	-0,039
	spicy	0,187	-0,200	0,659	-0,138
	herbs	0,173	0,201	0,829	-0,056
	Ribes ssp. / Sambucus ssp.	0,921	-0,001	0,000	0,000
	fruity	-0,321	-0,574	-0,704	-0,262
	citrus fruit	-0,007	-0,437	-0,646	-0,200
	white fruit	-0,345	-0,510	-0,019	-0,143
	yellow fruit	-0,392	-0,449	-0,366	-0,283
	tropical fruit	0,415	0,548	-0,239	0,160
	dried / candied fruit	0,280	-0,158	0,073	0,090
	floral	-0,314	-0,417	-0,344	-0,445
	aging notes	-0,300	0,782	-0,243	0,781
	minerality	-0,414	-0,464	-0,029	0,689
	fermentative aroma	-0,306	-0,451	0,213	-0,278
	sulfur	-0,100	0,284	0,022	0,400
	MLF	-0,085	0,252	-0,170	-0,171
	off-flavour	-0,086	0,559	0,203	-0,060
	others	-0,307	0,492	-0,135	0,450
	typicality	-0,857	-0,278	-0,817	-0,046

Descriptor families showing similar correlation factors for the first to factors of GPA are indicated in bold; Descriptor families showing differing correlation factors for the first two factors of GPA are indicated in bold, italic and underlined for the differing factor; MLF: malolactic fermentation

2.5.7

Essential outcomes regarding universality of Riesling wines' typicality

Table 2 -

 2

	Variable	r	German -typicality p correlation	r	French -typicality p correlation
	Alcohols
	3-methyl-1-butanol	-0.480	0.007 slightly negative	nc	ns	-
	2-methyl-1-butanol	0.378	0.039 slightly positive	nc	ns	-
	Monoterpenols
	α-terpineol	0.411	0.024 slightly positive	nc	ns	-
	nerol	-0.369	0.045 slightly negative	nc	ns	-
	Monoterpenol oxides
	cis-linalool oxide	0.450	0.013 slightly positive	0.421	0.023	slightly positive
	trans-linalol oxide	0.596	0.001	positive	nc	ns	-
	nerol oxide	0.553	0.002	positive	0.396	0.033	slightly positive
	Sulfur compounds
	dimethyl sulfide (DMS)	-0.440	0.015 slightly negative	nc	ns	-
	methanethiol	nc		ns	-	0.394	0.035	slightly positive
	ethyl 2-sulfanylacetate	nc		ns	-	-0.559	0.002	negative
	4-methyl-4-sulfanylpentan-2-one	nc		ns	-	0.398	0.032	slightly positive
	ethyl 2-sulfanylpropionate	nc		ns	-	-0.504	0.005
	ethyl 3-sulfanylpropionate	nc		ns	-	-0.617 <0.001	negative

15 Significant Pearson product -moment correlations (α = 0.05) between relative typicality ratings and aroma compounds' concentrations for both panels including all wines (Riesling and non-Riesling) nc: no correlation; ns: not significant; variables showing significant correlation for both panels indicated in bold

Table 2

 2

	-16 Significant Pearson product-moment correlations (α = 0.05) between relative typicality ratings and aroma compounds' concentrations for both panels including only Riesling wines
	Variable	r	German -typicality p Correlation	r	French -typicality p Correlation
	Alcohols
	3-methylbutanol	-0.434	0.038 slightly negative	nc	ns	-
	2-methylbutanol Ethylester	-0.486	0.019 slightly negative	nc	ns	-
	ethyl 2-methylpropanoate	-0.524	0.010	negative	nc	ns	-
	ethyl butanoate	-0.502	0.015	negative	nc	ns	-
	diethyl succinate	-0.699 <0.001	negative	nc	ns	-
	miscellaneous
	2-phenylethanol	-0.507	0.010	negative	nc	ns	-
	Monoterpenols
	nerol	-0.426	0.041 slightly negative	nc	ns	-
	geraniol	0.530	0.009	positive	nc	ns	-
	Norisoprenoids
	β-ionone	0.415	0.049 slightly positive	nc	ns	-
	Sulfur compounds
	3-sulfanylhexanol	0.498	0.015 slightly positive	0.429	0.036	slightly positive
	benzenemethanethiol	nc		ns	-	-0.711 <0,001 strongly negative
	methanethiol	nc		ns	-	0.417	0.043	slightly positive
	carbon disulfide	nc		ns	-	-0.554	0.005	negative
	ethyl 2-sulfanylacetate	nc		ns	-	-0.600	0.002	negative
	ethyl 2-sulfanylpropionate	nc		ns	-	-0.579	0.003	negative
	ethyl 3-sulfanylpropionate	nc		ns	-	-0.600	0.002	negative

nc: no correlation; ns: not significant; variables showing significant correlation for both panels indicated in bold;

Table 2 -

 2 17 Pearson product-moment correlations (α = 0.05) between concentrations of cis -linalool oxide, nerol oxide and the total descriptor family frequencies for both panels including all wines (Riesling and non-Riesling)

			German			French
	descriptor group		cis -linalool oxide		cis -linalool oxide
		r	p	correlation	r	p	correlation
	fruity	0.503	0.005	slightly positive	nc	ns	-
	citrus fruit	0.445	0.012	slightly positive	nc	ns	-
			neroloxide		neroloxide
		r	p	correlation	r	p	correlation
	aging notes	0.507	0.004	slightly positive	nc	ns	-

nc: no correlation; ns: not significant at a significance level α = 0.05; variables showing significant correlation for both panels are indicated in bold;

Table 2 -

 2 Fruity aroma descriptors were slightly correlated to 3-methylbutyl acetate for both panels.Neither total frequency for citrus fruit descriptors nor for yellow fruit descriptors showed common correlations in both panels (Table2-19).

			German			French
	descriptor group	3-sulfanylhexan-1-ol		3-sulfanylhexan-1-ol
		r	p	correlation	r	p	correlation
	yellow fruit	0.488	0.031	slightly positive	nc	ns	-
	nc: no correlation; ns: not significant at a significance level α = 0.05; variables showing significantt correlation for both
	panels are indicated in bold

18 Pearson product-moment correlations (α = 0.05) between 3-sulfanylhexan-1-ol concentration and the total descriptor family frequencies for both panels on Riesling wines only nc: no correlation; ns: not significant at a significance level α = 0.05; variables showing significant correlation for both panels are indicated in bold;

Table 2 -

 2 20 Common contributing variables for each panel, the German (GH) and the French (Bx) in Partial Least Square regression models for the prediction of relative typicality ratings with Variable Importance in the Projection (VIP) values; The VIP value is indicating the importance of the variable for the PLS model to fit, values >0.8 are considered to have a major impact (personal Communication of Addinsoft, Andernach, Germany)

	variable	German VIP	French VIP
	trans-linalool oxide	2.191	1.435
	linalool	2.186	0.849
	nerol oxide	2.109	0.960
	cis-linalool oxide	2.079	1.600
	3-methyl-1-butanol	1.611	0.982
	DMS	1.556	1.006
	2-methyl-1-butanol	1.237	1.002
	TDN	1.073	0.800
	diethyl succinate	0.958	1.519
	β-ionone	0.951	1.091
	4-methyl-4-sulfanylpentan-2-one	0.937	1.568
	3-sulfanylhexan-1-ol	0.921	0.909
	vitispirane	0.897	0.934
	ethyl butanoate	0.864	1.316
	benzenemethanethiol	0.802	1.449
	DMS: dimethyl sulfide
	TDN: 1,1,6-trimethyl-1,2-dihydronaphthalene
	2.5.8.2.2 Canonical Correspondence Analysis (CCA) on common variables
	from both panels

Canonnical Correspondence Analysis (CCA) allows combining metric and non-metric data in a multivariate method. It is widely used in ecological research (ter Braak and Verdonschot,

  (cos 2 0.510), yellow fruit (cos 2 0.446), dried / candied fruit (cos 2 0.287) or fermentative aroma (cos 2 0.231). The descriptor families floral (cos 2 0.797), sulfur (cos 2 0.475), and vegetal (cos 2 0.408) are explained by the second factor, whereas the third factor explains the descriptor families tropical fruit (cos 2 0.686), aging notes (cos 2 0.646), citrus fruit (cos 2 0.305) and minerality (cos 2 0.290).

	The A Not-A test derived recognition frequency RIESLING gets explained mostly by the
	second factor (cos 2 0.442).

Table 2 -

 2 21 Mean concentrations and OAVs for typicality related aroma compounds for the German panels' total data set after grouping into different levels of typicality (with relative

	typicality rating ranges: atypical 0 -0.2; less typical 0.2 -0.4; typical 0.4 -0.6; very typical >0.6)
		mean	min	max	SD	CV [%]	SEM	n	OAV mean	SD
	atypical
	typicality	0.11	0.09	0.15	0.03	25	0.01	6	-	-
	3SH [ng/L]	1160	697	1898	425	37	173	6	19.34	7.08
	linalool [µg/L]	1	nq	6	2	152	1	6	0.07	0.11
	TDN [µg/L]	0.5	0.0	1.1	0.4	83	0.2	6	0.26	0.21
	DMS [µg/L]	27.7	8.9	65.9	19.4	70	7.9	6	0.92	0.65
	less typical
	typicality	0.39	0.21	0.49	0.09	23	0.03	7	-	-
	3SH [ng/L]	457	218	779	190	42	72	7	7.89	3.51
	linalool [µg/L]	41	0	147	46	113	17	7	2.57	2.83
	TDN [µg/L]	3.8	0.0	9.4	3.0	79	1.1	7	1.78	1.11
	DMS [µg/L]	11.4	7.2	19.2	4.5	39	1.7	7	0.39	0.15
	typical
	typicality	0.54	0.53	0.56	0.01	2	0.01	5	-	-
	3SH [ng/L]	643	247	1189	332	52	148	5	9.42	4.94
	linalool [µg/L]	36	15	68	20	55	9	5	1.63	0.96
	TDN [µg/L]	2.4	1.6	3.3	0.7	31	0.3	5	1.51	1.26
	DMS [µg/L]	11.3	8.5	17.6	3.4	30	1.5	5	0.38	0.12
	very typical
	typicality	0.69	0.61	0.80	0.06	9	0.02	12	-	-
	3SH [ng/L]	739	253	1558	379	51	110	12	12.31	6.32
	linalool [µg/L]	33	8	60	14	43	4	12	1.65	0.71
	TDN [µg/L]	4.7	0.9	22.1	5.5	117	1.6	12	2.33	2.73
	DMS [µg/L]	13.2	5.3	22.5	5.0	38	1.5	12	0.44	0.17
	3SH : 3-sulfanylhexanol; TDN: 1,1,6-trimethyl-1,2-dihydronaphthalene; DMS: dimethyl sulfide; nq: not quantifiable;
	SD : standard deviation; CV : coefficient of variation; SEM: standard error on means; n: sample number; OAV: odour

activity value; OAV > 1 indicated in bold; OAVs based on thresholds: 3SH: 60 ng/L a , linalool: 20 µg/L a , TDN: 2 µg/L b , DMS: 30 µg/L c ; a Darriet et al., 2012; b Sacks et al., 2012; c Anocibar-Beloqui, 1995

Table 2 -

 2 22 Differentiation of descriptor families into factors of similarity or factors of dissimilarity of the natural categories Riesling wines and non-Riesling wines for the German and the French sensory panel

	Riesling wines'	Riesling wines'	non-Riesling wines'	non-Riesling wines'
	factor of dissimilarity	factor of similarity	factor of dissimilarity	factor of similarity
	German	French	German	French	German	French	German	French
	off-flavour	off-flavour	RIESLING	RIESLING	others	-	-	others
	MLF	-	-	others	-	floral	-	sulfur
	sulfur	-	-	MLF	Ribes ssp./ Sambucus ssp.	-	-	fermentative aroma
	-	minerality	-	sulfur	sauvignon	sauvignon	minerality	-
	aging notes	aging notes	fermentative aroma	fermentative aroma	vegetal	vegetal	-	-
	floral	floral	minerality	-	-	-	dried/candied fruit	-
	-	dried/candied fruit	tropical fruit tropical fruit	-	-	-	tropical fruit
	vegetal	-	yellow fruit	yellow fruit	-	-	-	yellow fruit
	-	-	white fruit	white fruit	-	-	-	white fruit
	-	-	citrus fruit	citrus fruit	-	-	citrus fruit	citrus fruit
	-	-	fruity	fruity	-	-		fruity
	-	-	herbs	-	-	-	herbs	herbs
	-	-	-	spicy	-	-	spicy	spicy
	the same differentiation for descriptor family on both panels' data sets are indicated in bold italic

Table 2 -

 2 ) between factors of Riesling wines' dissimilarity related descriptor family frequencies and aroma compounds for both panels on Riesling wines

			German		French
	variable		ageing notes		ageing notes
		r	p	correlation	r	p	correlation
	monoterpenoloxides
	trans-linalool oxide	0.558	0.006	positive	nc	ns	-
	cis-linalool oxide	0.452	0.030 slightly positive	nc	ns	-
	nerol oxide	0.577	0.004	positive	nc	ns	-
	norisoprenoids
	vitispirane	0.648	0.001	positive	0.698 <0.001	positive

TDN 0.

768 <0.001 strongly positive 0.835 <0.001 strongly positive

	β-damascenone	nc	ns		-	0.536	0.007	positive
	Sulfur compounds
	dimethyl sulfide (DMS)	0.450	0.031	slightly positive	nc	ns	-
	variable	r	p	floral correlation	r	p	floral correlation
	monoterpenols
	linalool	0.826 <0.001 strongly positive 0.523	0.009	positive
	norisoprenoids
	α-ionone	0.479	0.021 slightly positive	nc		ns	-
	β-ionone	nc	ns		-	0.477	0.018	slightly positive

nc: no correlation; ns: not significant at a significance level α<0.05; Variables showing significant correlation for both panels are indicated in bold;

Table 3

 3

	-1 Vineyard characteristics according to Hessisches Landesamt für Umwelt und Geologie (http://weinbaustandort.hessen.de/viewer.html (29.05.2012)) for the chosen experimental plot: Rüdesheim (Germany) -Burgweg -Berg Schlossberg (Eiseninger)
	geographical characteristics
	geo-coordinates	49°58'29.05''N; 7°53'00.44''
	altitude	120 m NHN
	surface area	0.71 ha
	planting characteristics
	year of planting	1996
	rootstock	Börner
	variety	Vitis vinifera L. cv. Riesling -estate own clone selection
	number of rows	51
	row spacing	2.50 m
	vine spacing	1.10 m
	irrigation system	drip irrigation
	soil cover	permanent -whole surface permanent sward
	geological characteristics
	soil	hortic anthrosol on quartzite debris over quartzite weathered slate
	carbonate	carbonate free to poor carbonate content
	water holding capacity	poor (nFK : 66.32 mm to 2 m max)
	slope	60 -90% slope / south exposed
	drought stress risk	class IV ->50% years below water stress threshold
	climatic characteristics
	total direct sunlight radiation between April and October	177 -181 [KJoule/cm 2 ]
	mean daylight temperature during Riesling ripening period	14.8 -14.9 [°C]

Table 3

 3

		-2 Viticultural treatments in the experimental vineyard
		experimental
	treatment description	units n	vintages
		(vines per unit)
	C	control (non-irrigated, not defoliated)	3 (>20)	2008, 2009, 2010
	I	irrigated	3 (>20)	2008, 2009, 2010
	IdB	irrigated, defoliated at flowering and redefoliated at veraison	3 (>20)	2009, 2010
	IdV	irrigated, defoliated at veraison	3 (>20)	2008, 2009

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 quantity of vines 46 45 45 44 44 44 44 43 41 42 42 43 42 41 41 41 41 40 42 43 40 40 40 40 39 39 39 38 38 38 38 37 36 36 36 36 35 34 34 33 33 33 33 32 31 31 31 31 31 30 30 C: non-irrigated control I: irrigated treatment

	Number 1 2 3 4 5 6 7 8 9

Table 3 -

 3

	solution	blind	volume [mL]	sample
	buffer solution (3.2.8.5.1)	2.9		2.9
	NAC solution (3.2.8.5.2)	0.1		0.1
	H 2 O	0.05		-
	sample	-		0.05
	1) 2 min after mixing, measurement of absorbance 1 (A 1 )
	2) immediately after measurement, addition of OPA-Solution
	OPA-solution (3.2.7.8.3)	0.1		0.1
	mixing and measurement of absorbance 2 (A 2 ) after 15 min
	3.2.8.6 Analysis by means of Fourier transform infrared spectroscopy
	(FTIR)
	A range of parameters in berry extracts, grape juice (must) and wines were measured by
	means of a FTIR-inferometer using an OenoFoss TM (Foss, Hilleroed, Denmark). Parameter
	included, were total soluble solids as BRIX [°Brix], reducing sugars [g/L], pH, total acidity [g

3 Preparation scheme for N-OPA analysis tartaric acid/L] for berry extracts and grape juice (must) and for the wines ethanol [%vol], reducing sugars [g/L] and total acidity [g tartaric acid/L]. Samples were analysed at the Department of Wine Chemistry and Beverage Research at the Geisenheim Research Center.

Table 3 -

 3 4 Chromatographic conditions for analysis of reduced glutathione

	Auto sampler
	Injection Volume	5 µL
	Flow	0.8 mL/min
	Gradient	Isocratic ; 100% Solvent A
	Detector	Dionex FLD -3400 RS
	Excitation λ Emission λ	Em 1: 390 nm; Em 2: 260 nm Em 1: 482 nm; Em 2: 400 nm
	Sensitivity	Em 1: 2; Em 2: 3
	Flow Cell Temperature	40 °C
	Column	Supelco Inc; LiChrospher SI-60; 5 µm; 250 mm x 4.6 mm
	Temperature	25 °C
	Solvent A	methanol / H 2 O (10/90; v/v); (2.5% glacial acetic acid)

Table 3

 3

	-5 Chromatographic conditions for analysis of phenolic compounds
	Injection Volume	2 µL
	Pump	Dionex LPG 3000 HPLC Pump
	Flow	0,19 mL/min
	Gradient	see gradient Table 3-6
	Detector	Thermo Scientific Finnigan Surveyor PDA Plus
	Wavelength λ	λ 1 : 280 nm; λ 2 : 320 nm; λ 3 : 360 nm
	Column	NEOS Comp. Ltd.; Fluofix 120E; 5 µm; 2x125 mm
		(NEOS Company Ltd., Kobe, Japan)
	Pre-Column	NEOS Comp. Ltd.; Fluofix 120E, 5 µm; 10x4 mm
	Temperature	20 °C
	Solvent A	H 2 O / 85% o-phosphoric acid (995/5; v/v)
	Solvent B	Acetonitril / H 2 O / 85% o-phosphoric acid (500/495/5; v/v/v)

Table 3

 3

	-6 Solvent gradient programme phenolic compound analysis
	runtime t [min]	solvent A [%]	solvent B [%]
	0	100	0
	2.5	100	0
	22.5	75	25
	32.5	25	75
	35	0	100
	35.1	100	0
	45	100	0

  8.

	Solid phase extraction
	SPE Cartridges (LC-18 500 mg 6 mL, Supelco France, Saint Germain-en-Laye Cedex,
	France) were preconditioned by rinsing with 5 mL methanol, 4 mL H 2 O / methanol (50/50;
	v/v) and twice with 2 mL of H 2 O.
	1 mL of grape juice, 1 mL of H 2 O and 25 µL of the internal standard solution containing the
	deuterated	glutathionylated	precursor	of	3-sulfanylhexan-1-ol
	dissolved again by adding succesively 400 µL and 300 µL H 2 O (0.1% formic acid), resulting
	in a volume of 700 µL. The solutions were filtered using a membrane filter (0.45 µm) prior
	injection to HPLC.
	Table 3-7 Chromatographic conditions for the analysis of cysteinylated and glutathionylated precursor of 3-sulfanylhexan-1-ol
	Auto sampler		Thermo Scientific Autosampler
	Injection Volume		5 µL
	Pump		Thermo Scientific Accela Pump
	Flow		0.6 mL/min
	Gradient		see gradient Table 3.8
	Detector		Exactive Plus Orbitrap LC-MS
	Settings MS		R: 25000; positive mode
	Heater temperature	302 °C
	Capillary voltage		35.5 V
	Tubelens Voltage		85 V
	Skimmer voltage		18 V
	Column		Agilent Technologies; Zorbax Eclipse AAA; 5 µm; 4.6 x 150 mm
	Pre-Column		Phenomenex; Seurity Guard; AJO-4492
	Temperature		20 °C
	Solvent A		H 2 O (0.1% formic acid)
	Solvent B		Acetonitrile (0.1% formic acid)

(3-S-(hexan-1-ol)-glutathione-d 3 ) was added, resulting in a concentration of 200 µg/L. This solution was transferred to the reservoir of the SPE cartridge. After the adsorbing step, the SPE packing was washed twice using 1 mL of H 2 O and then got dried for two minutes by vacuum augmentation (180 MPa). Precursor molecules got eluted with 3 mL of H 2 O / methanol (70/30; v/v) and were collected into glass tubes. The eluate was evaporated to dryness by means of a RapidVap Vertex Dry Evaporators (Labconco, Kansas City, MO, USA) (speed 60 -75%; temperature 50 °C; pressure 4 -10 mbar). The residues got

Table 3

 3

	-8 Solvent gradient programme analysis of cysteinylated and glutathionylated precursor of 3-sulfanylhexan-1-ol
	runtime t [min]	solvent A [%]	solvent B [%]
	0	97	3
	1.2	97	3
	3.5	87	13
	4	86	14
	4.4	80	20
	4.7	2	98
	5.7	2	98
	5.8	97	3
	6.8	97	3

Table 3 -

 3

9.

Table 3

 3

	-9 Preparation of standard samples for descriptors for QDA
	descriptor	preparation
	apple	a piece of fresh cut apple was placed into a neutral wine the evening before sensory session
	lemon	a piece of fresh cut lemon was placed into a neutral wine the evening before sensory session
	grapefruit	wine spiked with an equivalent of 1 µg/L 3SH
	melon	wine spiked with 200 µL of kitchen melon aroma (www.aromazone.com)
	peach	wine spiked with 200 µL of kitchen peach aroma (www.aromazone.com)
	apricot	wine spiked with 200 µL of kitchen apricot aroma (www.aromazone.com)
	floral	wine spiked with an equivalent of 250 µg/L linalool
	petrol/kerosene	wine spiked with an equivalent of 10 µg/L TDN
	mineral	a piece of schist was placed into a neutral wine the evening before sensory session (~ 0,5 cm*2 cm*3 cm / 200 mL)
	oxidative	wine was saturated with oxygen by passing through compressed air two days before sensory analysis
	reduced	neutral white wine, with reductive off-flavour

Table 3

 3

	-10 Vines' water status classification at different phenological stages for non-irrigated treatments (Control), based on FTSW derived pre-dawn leaf water potential Ψ (PD) values (according to van Leeuwen et al., 2010)
	phenological		vine water deficit level
	stage	vintage 2008	vintage 2009	vintage 2010
	inflorescence / flowering	no water deficit	weak water deficit	no water deficit
	fruit development	weak water deficit	no water deficit	weak water deficit
	veraison	no water deficit	moderate water deficit	no water deficit
	berry ripening (beginning / end)	moderate to severe water deficit / moderate water deficit	moderate to severe water deficit / severe water deficit	no water deficit / weak water deficit
	harvest	moderate water deficit	moderate water deficit	weak water deficit
	3.3.1.2.3 δ 13 C -isotope Ratio

Table 3 -

 3 11 Infection of the grape cluster by Botrytis cinerea at harvest for the vintages 2008, 2009 and 2010 of the different viticultural treatments. Description of Botrytis cinerea

	infection: frequency: percentage of infected clusters, strength: percentage of berries in one cluster, total: frequency * strength; n = 200 cluster. Viticultural treatments are C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison
	Botrytis cinerea infection	C [%]	I [%]	IdB [%]	IdV [%]
		frequency	23 (5)	24 (6)	nt	22 (8)
	2008	strength	16 (2)	15 (2)	nt	15 (2)
		total	4 (1)	4 (1)	nt	3 (2)
		frequency	40 (12)	61 (15)	58 (22)	53 (11)
	2009	strength	15 (2)	21 (6)	29 (9)	23 (10)
		total	6 (2)	14 (7)	19 (11)	13 (8)
		frequency	92 (4)	98 (1)	90 (1)	nt
	2010	strength	30 (4)	54 (6)	37 (5)	nt
		total	27 (3)	53 (6)	33 (4)	nt

nt: no treatment established in that vintage

Table 3 -

 3 12 Total terpenols

	vintage	treatment	total terpenols* [µg/L]
	2008	C I	162 (5) a 143 (8) b
	2009	C I IdB IdV	511 (29) a 224 (6) b 303 (25) c 195 (6) b
	2010	C I IdB	227 (5) a 226 (13) a 195 (30) a

* in grape must obtained from the viticulture experiments; with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison *total terpenols: sum of free and acid hydrolysed terpenols including geraniol, αterpineol, linalool, cis-linalool oxide, trans-linalool oxide; n = 3; standard deviation is indicated in parenthesis; differing letters indicate statistical significance within a vintage (Holm-Sidak method; p<0.05)

Table 3 -

 3 13 Total vitispirane* and total TDN** concentrations in grape musts [µg/L] obtained from the viticulture experiments, as sum of from free and acid hydrolysed vitispiranes and TDN; with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison

	vintage	treatment	total vitispirane	total TDN
	2008	C I	42.5 (0.2) a 40.0 (0.3) b	4.5 (0.6) a 1.9 (0.8) b
	2009	C I IdB IdV	125.3 (1.7) a 46.5 (0.5) b 48.7 (3.3) b 42.0 (0.7) c	1.1 (0.2) a 9.3 (0.6) b 6.5 (2.5) b 26.6 (2.4) c
	2010	C I IdB	67.0 (1.9) a 70.8 (2.6) a 64.9 (2.8) a	1.0 (0.4) a 1.0 (0.1) a 0.7 (0.3) a
	*total vitispirane include free and acid hydrolised vitispirane isomers; **total TDN include
	free and acid hydrolised TDN; n = 3; standard deviation is indicated in parenthesis; differing
	letters indicate statistical significance within a vintage (Holm-Sidak method; p<0.05);

Table 3 -

 3 14 Monoterpene (after 12 months) and C 13 -norisoprenoid concentrations in Riesling wines (after 12 months and 22 months) from viticulture experiments fermented with yeast A (Saccharomyces cerevisiae); with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at

	flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison
	vintage	treatment geraniol 1	α-terpineol 2	linalool 3	cis-linalool oxide 4	trans-linalool oxide 5	12 months	22 months
								vitispirane 6	TDN 7	vitispirane 6	TDN 7
		C	8 (0) a	33 (4) a,b	64 (7) a	nd	nd	17 (0.0) a	nd	63.9 (15.0) a	7.8 (5.1) a
	2008	I	9 (0) b	30 (2) a	51 (2) b	nd	nd	16.9 (0.1) a	nd	82.4 (1.9) a,b 16.0 (0.8) a
		IdV	9 (0) b	37 (2) b	57 (0) a,b	nd.	nd	17.2 (0.4) a	nd	99.8 (17.2) b 17.5 (8.2) a
		C	12 (4) a	41 (1) a	129 (9) a	1 (2) a	nd	26.5 (2.4) a	0.7 (0.3) a 100.2 (7.8) a,b 25.8 (4.5) a
	2009	I IdB	9 (1) a 9 (1) a	31 (6) a 35 (8) a	87 (5) b 104 (3) c	2 (0) a 2 (0) a	nd nd	26.9 (0.9) a 32.3 (6.5) a	1.2 (0.1) a,b 97.2 (5.0) a 1.9 (0.6) c 125.8 (14.7) b 34.3 (11.4) a 29.2 (2.9) a
		IdV	10 (1) a	37 (9) a	110 (8) c	2 (1) a	nd	28.6 (1.4) a	1.6 (0.5) b,c 114.4 (8.0) a,b 35.7 (6.6) a
		C	11 (0) a	21 (1) a	24 (2) a	8 (1) a	23 (2) a	23.7 (1.9) a	1.1 (0.3) a	na	na
	2010	I	11 (0) a	19 (1) a	22 (1) a	9 (0) a	23 (0) a	25.3 (0.7) a	1.0 (0.1) a	na	na
		IdB	13 (1) b	24 (1) b	29 (2) b	8 (2) a	26 (1) a	28.5 (1.9) b	1.9 (0.1) b	na	na

Results obtained with yeast A (Oenoferm Freddo); n = 3; standard deviation is indicated in parenthesis; differing letters indicate statistical significance within a vintage (Holm-Sidak method; p<0.05); nd: not detectable; na: not analysed; Limit of detection:

Table 3 -

 3 15 Concentrations of S-3-(hexan-1-ol)-L-cysteine (cys-S-prc) , S-3-(hexan-1-ol)gluthatione (GSH-S-prc), glutathione, S-glutathionylcaftaric acid and caftaric acid in berry extracts and grape must for the 2009 vintage; with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison

	sample date	treatment cys-S-prc	GSH-S-prc	GSH	GRP	caftaric acid
			[µg/L]	[µg/L]	[mg/L]	[mg/L]	[mg/L]
		C	2 (2) a	134 (42) a	33.0 (2.6) a	nd	145.6 (7.7) a
	veraison + 14	I	1 (0) a	119 (20) a	25.5 (2.7) b	nd	135.8 (7.8) a
	days	IdB	1 (0) a	68 (10) b	30.7 (2.2) a,b	nd	147.8 (2.9) a
		IdV	1 (0) a	71 (5) b	28.5 (1.3) a,b	nd	135.0 (5.5) a
		C	4 (2) a	174 (10) a	25.7 (3.1) a	nd	113.2 (8.3) a,b
	harvest	I IdB	3 (1) a 4 (1) a	129 (4) b 180 (23) a	36.7 (3.9) b 33.6 (2.6) a,b	nd nd	118.2 (2.5) a,b 123.0 (1.3) a
		IdV	4 (1) a	109 (0) b	37.8 (4.2) b	nd	106.8 (5.8) b
	must	C	64 (21) a	214 (8) a	1.0 (0.1) a	9.9 (0.2) a	50.8 (1.1) a
		I	55 (0) a	679 (21) b	1.1 (0.1) a	5.6 (0.6) b	23.2 (1.5) b
		IdB	123 (10) b	492 (1) c	0.9 (0.2) a	11.9 (0.3) c	68.9 (3.5) c
		IdV	67 (26) a	603 (8) d	1.0 (0.1) a	15.0 (1.2) d	54.4 (0.9)

a n = 3; standard deviation is indicated in parenthesis; differing letters indicate statisticalll significance (Fisher LSD p<0.05); nd: not detectable

Table 3 -

 3 16 Concentrations of S-3-(hexan-1-ol)-L-cysteine (cys-S-prc), S-3-(hexan-1ol)glutathione (GSH-S-prc), glutathione, S-glutathionylcaftaric acid and caftaric acid in berry extracts and grape must for the 2010 vintage; with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison

	sample date	treatment	cys-S-prc	GSH-S-prc	GSH	GRP	caftaric acid
			[µg/L]	[µg/L]	[mg/L]	[mg/L]	[mg/L]
	veraison + 14 days	C I IdB	1 (1) a 2 (1) a 2 (2) a	146 (34) a 140 (13) a 123 (20) a	33.4 (2.6) a 25.0 (8.8) a 11.4 (9.3) a	na na na	na na na
	veraison + 22 days	C I IdB	1 (0) a 1 (1) a 2 (2) a	120 (1) a 85 (7) b 138 (20) a	37.6 (5.0) a 43.9 (3.7) a 42.4 (0.8) a	na na na	na na na
		C	1 (0) a	111 (26) a	47.5 (4.1) a	na	na
	harvest	I	1 (0) a	150 (22) a	47.6 (1.5) a	na	na
		IdB	0 (0) a	150 (25) a	51.1 (9.0) a	na	na
	must	C	17 (0) a	205 (10) a	0.9 (0.1) a	5.2 (0.2) a	19.2 (0.9) a
		I	21 (0) b	232 (3) b	1.3 (0.3) a	5.7 (0.4) a	21.2 (1.2) a
		IdB	22 (3) b	267 (5) c	1.0 (0.2) a	6.6 (0.3) b	18.8 (2.1) a

na: not analysed; n = 3; standard deviation is indicated in parenthesis; differing letters indicate statistical significance

(Fisher LSD; p<0.05)

Table 3 -

 3

	vintage	treatment cys-S-prc	GSH-S-prc	3SH in wines	assimilable N
			[µg/L]	[µg/L]	[ng/L]	[mg/L]
		C	10 (1) a	216 (1) a	206 (65) a	345
	2008	I	4 (5) a	193 (13) b	313 (55) b	271
		IdV	na	na	275 (45) a,b	na
		C	64 (21) a	214 (8) a	156 (56) a	226
	2009	I IdB	55 (0) a 123 (10) b	679 (21) b 492 (1) c	328 (69) b 412 (168) b	193 167
		IdV	67 (26) a	603 (8) d	327 (68) b	206
		C	17 (0) a	205 (10) a	326 (41) a	215
	2010	I	21 (0) a,b	232 (3) b	984 (18) b	267
		IdB	22 (3) b	267 (5) c	287 (12) a	254
	na: not analysed; standard deviation is indicated in parenthesis; differing letters indicate
	statistical significance (Fischer LSD method; p<0.05)

17 3SH-precursor and assimilable nitrogen (N) concentration (sum of N-OPA and free ammonium concentrations) in grape must (n=3) and free 3SH in corresponding finished wines (n=3); with C: non-irrigated control; I: irrigated; IdB: irrigated, defoliated at flowering and defoliated at veraison; IdV: irrigated and defoliated at veraison

Table 4 -

 4 1 Wines used for obtaining global aroma extracts

	no.	wines	variety	origin	winery	vintage
					Weingut der
	1	Von-Lade QbA trocken	Riesling	D-Rheingau	Forschungsanstalt	2009
					Geisenheimm
					Weingut der
	2	Von-Lade QbA trocken	Riesling	D-Rheingau	Forschungsanstalt	2010
					Geisenheimm
					Hessische
	3	Berg Rottland	Riesling	D-Rheingau	Staatsweingüter -	2009
					Kloster Eberbach
					Hessische
	4	Berg Rottland	Riesling	D-Rheingau	Staatsweingüter -	2010
					Kloster Eberbach
	5	Château Moutin	Sauvignon blanc (90 %), Semillon (10 %)	F-Bordeaux (Graves)	Vignobles Darriet	2008
	6	Domaine de la Maroutine, Bordeaux blanc sec	Sauvignon blanc	F-Bordeaux (Loupiac)	Vignobles Darriet	2010
	7	Château Bonnet blanc	Sauvignon blanc (55 %), Muscadelle (10 %) Semillon (35 %),	F-Bordeaux Mers) (Entre Deux	Château Bonnet	2009
			Sauvignon blanc	F-Bordeaux
	8	Château Bonnet blanc	(65 %),	(Entre Deux	Château Bonnet	2010
			Semillon (35 %)	Mers)

Table 4 -

 4 2 Chromatographic conditions for the fractionation of global aroma extracts

	Auto sampler	Dionex Ultimate 3000 Autosampler
	Injection Volume	200 µL (250 µL)
	Pump	Dionex Ultimate 3000 Pump
	Flow	1 mL/min
	Gradient	see gradient table 4-3
	Fraction collector	Dionex Ultimate 3000 Autosampler
	Column	Waters Nova-Pak ® HR C18, 6 µm 60 Ǻ, 7.8 x 300 mm
	Pre-Column	Varian MetaGuard 4.6 mm, Polaris C18-Ether 5 µm
	Temperature	20 °C
	Solvent A	H 2 O
	Solvent B	ethanol (distilled freshly)

Table 4 -

 4 3 Solvent gradient programme for the fractionation of global aroma extracts

	runtime t [min]	solvent A [%]	solvent B [%]
	0	100	0
	2	100	0
	19	76	34
	85	0	100
	95	0	100
	96	100	0
	106	100	0

Table 4

 4 Using a polar polyethylene glycol stationary phase (SGE BP-20), a total of 56 odoriferous zones (OZ) were detected in the global Riesling wines' aroma extracts, when sniffed by one panelist. Typical Riesling wines' aroma extracts showed a total of 51 OZ, whereas not typical Riesling wines' aroma extracts showed only 43 OZ. In total 40 OZ were abundant at the

	-5 Chromatographic conditions for 1D-GC-O
	Autosampler	manual Injection
	Injector	split -splitless Injector (Agilent technologies, USA)
	Mode	splitless (1 min); constant temperature
	Purge Flow	50 mL/min
	Temperature	230 °C
	Liner	SGE Flow Gooseneck
	Gas Chromatograph	GC 5890 Series II (Hewlett Packard, USA)
	Capillary Column	SGE -BP20 (SGE Europe Ltd, UK)
		(50m x 250 µm ID x 0.22 µm FT)
		Agilent-DB-5 (Agilent technologies, USA)
		(50m x 250 µm ID x 0.25 µm FT)
	Carrier Gas	Hydrogen; const. pressure 250 kPa; 3 bar forepressure
	Oven Program	45 °C (1 min) -230 °C at 4 °C/min; Hold 15 min
		45 °C (1 min) -280 °C at 4 °C/min; Hold 15 min
	Detector	olfactometric port ODO-1 -SGE -Ringbow, Australia

Table 4 -

 4 8 Odoriferous Zones (OZ) for thiol selective aroma extracts (TSAE) from typical Riesling wines and from typical Sauvignon blanc style wines on a polar and non-polar stationary phase (SGE BP-20, Agilent DB-5)

	LRI OZ BP-20	DB-5	compound	typical Riesling	odour descriptor typical Sauvignon blanc
	1 2 3 4 5 6 7 8 9 10 11 12 13	888 863 911 891 970 861 861 988 909	ethyl pentanoate 1-hepten-3-one 4-methoxy-2-methyl-2-sulfanylbutane ethyl-2-sulfanylpropionate 4-methyl-4-sulfanylbutan-2-one 2-methyl-3-sulfanylfurane 4-methyl-4-sulfanylpentan-2-one 2-furfuryl thiol / 2-furanmethanthiol	fresh / fruity yeast / metallic / beer bread crust / yeast / broth broom / leach / onion orange / floral / spicy / herbs citrus metallic / onion broom bread crust / meaty / yeast chicken broth / coffee broom / floral	sulfurous reduced beer / beer in green bottles bread crust boxtree / sweat / broom fruity onion yeast / metallic / brewery box tree / broom meaty / broth / reduced roasted chicken floral / hey cabbage
	14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57	1067 944 998 1193 1244 1169	4-methyl-4-sulfanylpentan-2-ol methional 2-methyltetrahydrothiophen-3-one 2,3-diethyl-5-methylpyrazine 3-sulfanylhexanyl acetate 3-sulfanylhexan-1-ol	cats pee brewery / beer spicy / box tree brewery / beer bread crust grilled onions / coffee / breadcrust yellow fruit mineral / slate empyromatic / flinty empyromatic / flinty floral / violet broom lactic / cheese / sweat sweat / animal / cheese anis / broom / grapefruit spicy / broom / celery / leach roasted onion yellow fruit fruity / melon earthy / thiol citrus cest grapefruit grapefruit grapefruit herbal / onion candied fruit fruity	popcorn cats pee box tree / grapefruit beer / yeast / bread crust / leach broth metallic bread crust meaty / roasted chicken bread crust mineral / flinty / brewery fruity melon / papaya / spicy metallic spicy / broth metallic / mineral / vegetal roasted coffee honey / acacia leach sweat / cheese roasted onion / cheese anis / broom anis / animal / onion animal / bread crust fruity passion fruit leach / onion potato chips orange extract candied fruit / grapefruit fruity grapefruit fruity / mango / passion fruit flinty honey / quince yelly celery / maggi spicer vegetable soup spicy fruit jam cooked carrots fresh fruit / candied fruit
			compounds tentatively identified by LRI on BP-20, LRI on DB-5 and odour quality in GC-O
	On a non-polar (5%-Phenyl)-methylpolysiloxane stationary phase (DB-5-MS) only a total of
	25 OZ were detected in GC-O analysis. In typical Riesling wines TSAE 22 OZ were detected,
	whereas 21 OZ were obtained in typical Sauvignon blanc style wines' TSAE.
	TSAE of typical Sauvignon blanc style wines showed a higher number of OZ than TSAE from
	typical Riesling wines. This observation was more abundant using the polar stationary phase
	(SGE BP-20) than using the non-polar stationary phase (Agilent DB-5-MS). With the polar
	configuration, especially in the regions from LRI's 1522 to 1580, LRI's 1930 -1984, and

Table 4 -

 4 9 Odour descriptors for aroma extract fractions of typical Riesling and typical Sauvignon blanc wines

	Fraction	typical Riesling	Odour descriptor	typical Sauvignon blanc
	19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60	fruity -soapy / fruity / floral -terpenic soapy / -/ citrus fruit -/ caramel -butter / cheese -champignon -/ fatty acids / cheese -champignon plastic / methional / dust -/ fatty acids / citrus fruit -/ biscuit -meaty / ethylacetate ethyl acetate / ethyl acetate / ethyl acetate candy floss / caramel -biscuit / --/ biscuit -caramel -butter / citrus fruit fruity / fruity -melon / red fruits -strawberry -cherry caramel / fruity -peach / sweaty caramel / -/ --/ fatty acids / fruity iso-amyl alcohol / iso-amyl alcohol / iso-amyl alcohol iso-amyl alcohol / cheese -sweaty feet / rose rose / floral -lemon /rose lemon / fruity / greenish -/ -/ spicy fruity / heavy / -vanille / -/ fruity herbal / torrified coffee / caramel mint / fruity -phenol / -mint / fruity -passion fruit / fruity fruity -mint / fruity -melon -peach / buttery herbal / lemon / -floral -sugar / anis -mint / plastic herbal / lime / -floral / grapefruit / greasy fruity -linalool -geraniol / lime anis / citrus fruit fresh fruit -lemon / fennel / fruity -apple -/ lemon / iso-amylacetate -/ -/ fruity fruity / floral / -fruity -floral / fruity -floral / -fruity / lemon -fruity / -fruity / fruity / lemon candied / candied fruit / terpenic ripe fruit / fruity / terpenic herbal / -/ --/ -/ --/ -/ -	lemon -grapefruit / fruity -passionfruit -citrus fruit / lemon -mineral -/ -/ -floral / -/ butyric acid -/ -/ --/ -/ --/ -/ -plastic / methional / herbal -/ vegetal / cheese -/ -/ -tomato leaf / caramel -butter / heavy fruity / melon / ethyl acetate -/ -/ champignon -/ -/ --/ -/ fruity lemon -mint / lactic -yoghurt -lemon / lemon iso-amyl alcohol / iso-amyl alcohol / sweaty -candy floss-iso-amyl alcohol -/ -/ -lemon / grapefruit / spicy -/ -/ --/ meaty -chicken brooth / --/ phenol / citrus fruit spicy / -/ -butter / -/ -fruity / grapefruit / -fruity -pear / fruity -melon -peach / caramel fruity / -/ --/ anis -mint / --/ lime / --/ lemon / -lemon / anis / phenol plastic -spicy / fruity / fruity -spicy -mint -/ fruity -floral / iso-amylacetate herbal / -/ -fruity / herbal -lemon / herbal -thiol floral / floral / phenol -/ floral / --/ floral / -acetoin / fruity / lemon -linalool fresh fruit / fruity / terpenic fruity / -/ terpenic -/ -/ --/ -/ -

fractions indcated in bold show differences; Fractions indicated in italics and bold show similar odours

Table 4 -

 4 10 Odoriferous Zones (OZ) for aroma extracts from AEF 55 obtained from typical Riesling and typical Sauignon blanc style wines on a polar stationary phase (SGE BP-20) OZ in bold indicating similar odours by 3 panelists; OZ in bold and italic indicating differing odours by 3 panelists Therefore, the hypothesis, which suggested different OZ in differing aroma extract fractions of typical Riesling wines in comparison to typical Sauvignon blanc style wines, could be confirmed for the AEF 55.

	OZ	LRI BP-20	typical Riesling	odour descriptor	typical Sauvignon blanc
	1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27	855 882 890 894 956 1029 1132 1153 1222 1234 1245 1258 1283 1304 1319 1385 1413 1552 1564 1665 1741 1816 1866 1910 2007 2020 2048	solvent ethyl acetate ethyl acetate ethyl acetate, fruity -metallic, beer -onion -garlic sweet, burnt sugar fruity, orange green, old cut grass -beer, metallic -herbal, dusty, hey reduced garlic --flint stone cheese fruity fried potato floral, rose -floral-fruity		solvent -ethyl acetate ethyl acetate, fruity reduced, metallic metallic, beer onion dusty, metallic burnt, caramel reduced, sulfurous -fruity, box tree -leach beer, metallic, yeast melon, fresh peach burnt leach, onion -flint stone -broom, fruity fruity -floral pine tree -

  NIST ® data base resulted with a 98.2% propability that the compound sought after is trans-ethyl cinnamate. This then was verified by spike experiments. Quantification of trans-ethyl cinnamate in Riesling wines andSauvignon blanc style winesIn order to verify that the concentrations of trans-ethyl cinnamate were higher in Riesling wines, wines from different grape varieties (16 Riesling wines and 13 wines made from Sauvignon blanc style wines) were analysed for trans-ethyl cinnamate by means of stable isotope dilution analysis according to[START_REF] Antalick | Development, validation and application of a specific method for the quantitative determination of wine esters by headspace-solidphase microextraction -gas chromatography -Mass Spectrometry[END_REF]

	4.3.8	Impact of trans-ethyl cinnamate on Riesling wines' aromatic
	expression
	50 Area (1396) 70.0738 a) 4.3.8.1 Fig. 4-5 Box-Plots showing concentration ranges of trans-ethyl cinnamate in Riesling (n 16) 100 150 200 0 1000 131.0463 176.0797 103.0470 77.0337 147.0861 104.0538 b) trans-ethyl cinnamate and Sauvignon blanc / Sémillon blended wines (n 13). Different letters indicate statistical difference in median values (Mann-Whitney Rank Sum Test, Confidence Intervals 95%, p < 0.001)
		m/z	m/z	m/z
	The 16 Riesling wines analysed showed a concentration range from 0.6 µg/L to 4.5 µg/L
	resulting in a mean of 1.8 µg/L and a standard deviation of 1.3 µg/L. On the other hand,
	trans-ethyl cinnamate concentrations ranged from 0.5 µg/L to 1.1 µg/L for those 13

typicality Wines Gewürz- traminer Pinot gris Sauvignon blanc

  In contrast to the German panels' data, in the French data set, the most typical Riesling wines (typicality ratings from 0.5 to 0.7) showed relatively high concentrations of trans-ethyl cinnamate (2.1 µg/L to 4.6 µg/L), whereas generally no correlation could be established between Riesling wines' typicality and trans-ethyl cinnamate concentrations.Results showed that additions of trans-ethyl cinnamate can impact Riesling wines' typicality appreciation measured as proportion of the judges who indicate wines as a Riesling wine, but the effects were not shown to be significant in chi-square (χ 2 ) statistics (α = 0.05).

	4.3.8.4 Effect of trans-ethyl cinnamate additions on Riesling wines'
	typicality
	In order to evaluate shifts in perceived Riesling wines' typicality, depending on different
	trans-ethyl cinnamate concentrations, four wines, naturally showing sub-threshold
	concentrations of this compound, were spiked with trans-ethyl cinnamate resulting in different
	concentration levels. These wines were orthonasally evaluated by a sensory panel of wine
	experts according to the A Not-A method as described previously (chapter 1).

  reconsidered the organoleptic impact of trans-ethyl cinnamate and three other esters (ethyl dihydrocinnamate, methyl anthranilate and ethyl anthranilate) in Pinot noir wines through the development of a Stable Isotope

	Dilution Assay. With regards to trans-ethyl cinnamate concentrations ranged from 500 ng/L
	to 1.6 µg/L (average of 800 ng/L) a content lower than the olfactory perception threshold of
	this compound. Thus, the evidence for concentrations of this compound in Riesling wine, at
	levels it can contribute to these wines' aroma, directly or more presumably through

perceptual interaction phenomena is quite original, surprising and illustrative of the interest to correlate sensory analysis approaches to analytical chemistry.

1 )

 1 Using the concept of typicality, not only a sensory space of typical Riesling wines was demonstrated, moreover, thanks to adopting novel methodical elements, the sensory space was characterised in its descriptive dimensions. During this sensory part of the project, fundamental aspects of typicality, as what it is defined in oenology, were highlighted and have been demonstrated. Especially the possibility to work in two locations, having two panels with great expertise on different wine styles, led to valuable insights into intercultural consensus on varietal aromatic spaces of wines. This got clearly evident by including a confrontation of Riesling wines to Bordeaux white wines, which are aromatically dominated by the varietal character of Sauvignon blanc.It got obvious that a panel of wine experts, whether experienced with the wine style or not, works highly reproducible on the task of product categorisation and description, when being considered as one unit of measurement. Not surprisingly, it was clearly demonstrated, that Riesling wines' typicality was associated with citrus fruit odours, whereas vegetal odours, including box tree odour, were more associated with Sauvignon blanc style wines. Regarding the odour naming, some differences were detected between both panels, which leads to the consideration that cultural differences in odour perception of wine experts can already occur within a European context. The application of the frequency based recognition task in form of the A Not-A test proved to be a suitable tool for typicality judging when working with a panel, which is highly trained on a product.Upon results from this sensory study and quantitative analysis of aroma compounds, marker molecules for aromatic typicality of Riesling wines were pointed out by different statistical tools. In this part, a novel multivariate approach was used to link frequented descriptive data to metric quantitative data and gave valuable information on relations between aroma compounds concentrations and odour perception. It was demonstrated for the results of both panels by means of Pearson product -moment correlation, that the concentration of 3-sulfanylhexan-1-ol, which is also an important marker molecule in Sauvignon blanc style wines' aroma, correlates positively to Riesling wines' typicality. Surprisingly, it did not correlate with the descriptor family of citrus fruit. The utilisation of a novel combination of two

	multivariate methodologies, including Partial Least Square Regression (PLS) with
	subsequent application of a Canonical Correspondence Analysis (CCA), verified these
	observations concerning 3-sulfanylhexan-1-ol and Riesling wines' typicality appreciation and
	the lacking correlation to citrus fruit descriptors. Further it provided interesting observations
	concerning	other	aroma	compounds	such	as	linalool	and
	1,1,6-trimethyl-1,2-dihydronaphthalene (TDN). Despite both aroma compounds were shown

  Furthermore, monoterpenol concentrations, especially for linalool, were shown to increase in the finished wines as a consequence of the grape vines' water deficit and, to lesser importance, of canopy micro climate manipulation. C 13 -norisoprenoid concentrations, namely vitispirane isomers and TDN, in the finished wines were strongly influenced by the grape vines' water status and the canopy micro-climate manipulations, as fruit zone leaf removal at flowering or at veraison. Taking bottle aged wines into account, it is hypothesised from the results of this work that viticultural factors, such as grape vines' water status, influence the metabolism of C 13 -norisoprenoids in grape berries. As a result this can lead to differences in aging behaviour of Riesling wines regarding this molecule class. Consequently, the moment of appearance of the 'kerosene' odour during bottle aging of Riesling wines is considered to be highly influenced by grape vines' water status. The concentrations of the thiol 3-sulfanylhexan-1-ol (3SH) in wines was demonstrated to be highly influenced by the grape vines' water status as it was by canopy micro climate manipulations. It was demonstrated that 'weak to moderate' water deficit favoured elevated 3SH concentrations in wines, whereas 'severe' water deficit was shown to decrease 3SH concentrations in wines. Both

  Vitis 35 207-210 207Zoecklein, B. W., Hackney, C. H., Duncan, S. E. and Marcy, J. E. (1999), Effect of fermentation, aging and thermal storage on total glycosides, phenol-free glycosides and volatile compounds of White Riesling (Vitis vinifera L.) wines. Journal of Industrial Appendix 1b Discriptors applied in the German and French sensory panel in the descriptive task, and their grouping into descriptor families.Appendix 1c Discriptors applied in the German and French sensory panel in the descriptive task, and their grouping into descriptor families. Discriptors applied in the German and French sensory panel in the descriptive task, and their grouping into descriptor families.

					Appendix Appendix
	Microbiology descriptor family descriptor Appendix 1d descriptor family family spicy yellow fruit aging notes herbs Ribes ssp. Sambucus ssp. fruity tropical fruit dried / candied fruit fermentative minerality higher alcohols iso-butanol [mg/L] iso-amyl alcohol [mg/L] tert-amyl alcohol [mg/L] hexan-1-ol [µg/L] acetic acid ester ethylacetate [mg/L] iso-amylacetate [µg/L] amylacetate [µg/L] hexylacetate [µg/L] 2-phenylethylacetate [µg/L] monoterpenols linalool [µg/L] α-terpineol [µg/L] β-citronellol [µg/L] nerol [µg/L] geraniol [µg/L] monoterpenol oxides trans-linalool oxide [µg/L] cis-linalool oxide [µg/L] nerol oxide [µg/L] C 13 -norisoprenoids vitispirane isomers [µg/L] TDN [µg/L] β-damascenone [µg/L] methanethiol [µg/L] dimethyl sulfide [µg/L] carbon disulfide [µg/L] ethyl 2-sulfanylpropionate [ng/L]	/	& descriptors (English -translated) Biotechnology original descriptors 22 (French) descriptors original descriptors descriptors original descriptors (English -translated) (French) (English -translated) (French) spicy pepper white pepper clove saffron anise menthol broth épicé poivre Poivre blanc clou de girofle safran anis menthe bouillon fond yellow fruit fruit jaune aging notes notes de vieillissement peach pêche evolved evolué herbs herbaceous hay herbal tea aroma pine tree herbes verveine feuilles sèches foin-paille blackcurrant elderberry gooseberry fruity strawberry fruité fraise white peach apricot nectarine quince melon pêche blanche abricot nectarine coing melon tropical fruit exotic fruit exotic passion fruit lychee mango guava figs fruits tropicaux fruit exotique exotique fruit de la passion litchi mangue goyave figues dried / candied fruit candied sweet quince jelly candied quince confit de fruit sec confit sucre pate de coing fermentative aroma arômes fermentatifs confit de coing oxidation ripe petroleum kerosene TDN ATA wax caramel honey oxidation mûr pétrole kérosène TDN UTA cire caramel miel mineral shell oyster shell limestone wet stone dusty metallic flintstone mineral coquillage coquillage d'huitre pierre humide poussiéreux metallique silex 27 17 18 26 40 17 37 21 22 31 23 148 104 110 136 134 116 171 124 127 134 93 28 19 20 25 34 21 36 33 27 29 27 1766 2178 885 1672 646 1238 1875 1641 752 907 1741 1507 1035 2058 1163 1645 968 1457 1525 966 1452 1017 1749 941 615 1827 1298 751 1233 417 2 100-107 original descriptors original descriptors original descriptors (German) (German) (German) würzig gelbe Früchte Alterungsnoten Suppe Aprikose firn Maggi Ingwer Pfeffer Gewürznelke Minze kräutig krautig Heu Teearoma Pinie schwarze Johannisbeere (Frucht) Holunder (Frucht) Stachelbeere (Frucht) fruchtig Erdbeere Pfirsich Marille tropische Früchte exotische Früchte tropisch Passionsfrucht Litschi Guave fermentatives Aroma getrocknete/ eingemachte Früchte süß Marmelade oxidativ Reife wachsig Schuhcreme Petrolton TDN UTA Honig mineralig steinig nasser Fels nasser Stein Feuerstein 17 33 22 29 15 13 22 22 19 23 15 16 16 25 28 9 23 20 107 152 122 152 108 78 114 95 125 139 93 96 53 104 93 72 114 115 20 38 27 29 23 14 21 18 18 25 15 19 10 17 18 11 26 32 116 73 79 151 79 67 59 73 150 34 168 31 246 107 168 140 1 142 43 172 226 132 40 40 101 65 34 157 168 593 580 1294 237 1 1051 1262 222 92 1 300 743 55 807 1391 161 779 497 141 25 1008 264 127 1 819 555 1143 1011 274 659 28 23 57 14 1 29 60 20 16 5 36 31 17 43 61 17 45 26 5 4 52 16 12 3 30 26 57 70 25 91 106 125 58 13 72 95 53 24 17 97 90 24 122 87 41 96 80 40 27 99 55 45 29 41 165 200 95 43 14 15 23 33 22 43 187 30 35 16 18 36 91 28 22 18 10 9 16 16 13 19 8 17 14 14 24 19 11 110 83 150 79 57 152 268 582 65 52 85 102 81 584 280 82 156 51 30 37 69 83 75 25 83 101 158 256 80 80 0 3 0 0 6 0 0 147 38 21 13 16 50 68 16 40 15 42 21 39 56 8 24 31 28 60 43 37 26 24 10 11 8 11 14 10 9 124 73 51 23 31 96 58 22 81 20 47 61 29 36 21 66 59 35 53 32 35 94 37 0 1 0 0 0 2 2 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 1 0 1 0 0 1 2 0 3 2 2 2 0 3 2 2 0 2 0 2 2 2 2 0 0 0 2 0 0 3 0 0 0 0 2 0 10 9 10 8 10 10 10 7 10 8 8 9 9 9 9 9 9 8 12 9 10 9 9 11 9 10 10 9 10 10 0 21 1 0 20 0 0 69 53 55 28 35 0 40 30 67 29 35 56 61 27 39 65 83 40 27 22 31 79 44 0 9 1 0 13 0 0 71 25 23 13 18 0 14 13 31 14 16 28 34 15 21 32 69 27 14 14 19 36 22 5 7 4 9 8 3 3 36 24 19 13 18 26 1 14 30 27 14 21 32 15 20 30 43 17 21 10 17 27 21 24 25 20 26 25 20 21 31 33 31 25 21 49 25 26 32 27 29 29 77 28 32 4 30 27 33 27 23 44 30 0.5 1.0 0.0 0.5 1.1 0.0 0.0 3.5 5.9 4.8 1.6 1.2 9.4 2.3 1.6 3.3 1.6 3.2 3.3 22.1 1.6 3.4 4.9 3.1 1.7 3.8 2.0 0.9 6.6 2.5 2.0 3.0 3.0 3.0 3.0 2.0 3.0 3.0 3.0 3.0 3.0 2.0 7.3 13.3 50.4 6.7 9.2 11.9 5.1 9.1 14.7 5.8 11.9 7.9 7.3 6 8 9.9 22.9 13.4 23.9 6.4 4.7 16 8.1 8.2 16.9 24.9 9.5 0 1 0 6.1 0 5.5 1 0 0 0 1 6.3 0 5.3 0 1 1 5.5 1 5.3 5.5 4.8 0 0 1 4.6 5.3 1 0 1 18.7 34 8.9 29.2 9.7 65.9 19.2 7.2 11.2 8.6 17.2 8.9 7.7 12.1 8.5 17.6 8.9 9.3 18.2 22.5 15.6 12.9 18 8.8 9.4 5.3 17.6 9.9 13.4 7.1 2 1.6 1.9 1.8 3.2 1.3 2.7 6.1 1.8 2.4 20.1 7.2 6.5 3.2 2.2 2.4 2.3 1.5 2.2 4.6 14.7 1.3 2.4 3 7.2 1 1.6 3.4 3.9 5.4 3.0 18.1 7.7
	aroma		fruit syrup candied grape berries artificial	sirop de fruit confit de raisin savonneux	Steinfrucht künstlich
			coconut candied lemon ester	noix de coco confit de citron banane	Ester
	citrus fruit		citrus fruit dried apricot fruity ester	agrumes abricot sec ananas	Zitrusfrüchte Fruchtester
	floral white fruit		dry grape berries soapy grapefruit floral banana lemon white flowers pineapple lemon zest muscaté candy aroma bergamot terpenic glacial ice candies orange white fruit lily mandarine acacia flower gummy bears	pamplemousse raisin sec bonbon orange floral bergamotte fleurs blanches citron muscate mandarine terpenique fruits blancs lis fleur d'acacia	Limette seifig Pampelmuse floral Banane Zitrone blumig Ananas weiße Blüten Bonbonaroma Muskat Eisbonbon weisse Früchte parfümiert süßliche Blumen Gummibärchen
			pear apple jasmine rose	poire pomme rose jasmin	Rose Apfel grüner Apfel Akazie
					Birne
					v vi

  Aroma compound's concentrations in the wines assessed in sensory studies by the French panel: miscellaneous, monoterpenols, monoterpenol oxides by means of the "Kaltron method", C 13 -norisoprenoids by means of SBSE and GC-MS; values 0 indicates concentration below limit of quantification for the concerning aroma compound

	Appendix 13 typicity	SBBX	SBAL	SBNZ	RIAL4	RIAL3	GTAL	PGAL	RINA1	RIAL5	RIRH4	RIAL2	RIAL1	RIRH1	RIRH8	RIRH3	RINZ	RIRH2	RIAL7	RIAUT2	RIRH5	RIRH6	RIAL6	RIMO1	RIRH11	RIRH9	RIRH7	RINA2	RIAUT1	RIRH10
	miscellaneous
	2-phenylethanol [mg/L]	27		14	14		49		27		13		53	14	27		15	20		30		11		10	16	14		16		31		14	8		14	19		12	7		24	36		18	13	18
	2-phenylethylacetate [µg/L]	31		60	52		72		24		26		103	50	26		81	50		27		47		45	52	24		43		43		104	20		46	33		60	16		134	60		140	42	39
	monoterpenols
	linalool [µg/L]	1		1	1		1		8		26		10	8	11		10	38		19		3		15	18	1		16		26		37	13		17	23		42	16		20	6		13	42	61
	α-terpineol [µg/L]	12		15	11		31		40		65		12	21	52		22 18	24 74	32 64	13 18	16 33	29 81	16 25	22 58	29 77	17 30	16 53	15 30	28 70	18 49	10 49	40	26 32	19 26	20 34	37 44
	hexan-1-ol [µg/L] β-citronellol [µg/L]	591 2044 2330 3 5 7	451 0	856 2	354 8	291 1685 2 12	836 1094 0 1	441 0	996 4	952 68	430 1166 55 5	899 1715 0 6	445 1655 1457 0 4 4	275 1166 1837 0 3 10	969 10	0	490 1247 1295 1 3 10	422 0
	acetic acid ester nerol [µg/L]	0		4	2		2		2		2		3	2	3		2	0		2		10		3	2	2		2		0		3	2		2	3		3	3		2	3		2	3	2
	ethylacetate [mg/L] geraniol [µg/L]	50 11	148 12	99 12	106 0	62 10	72 35	178 9	122 12	152 10	62 12	256 9	193 10	92 90	80 14	135 15	112 12	90 15	162 9	82 15	18 12	63 9	27 12	64 14	19 13	11	38 8	13 10	165 16	87 12
	iso-amylacetate [µg/L] monoterpenol oxides		1	526	255		1		1	162	229	54		1	421		1		1	55	265	91		1		1		1	778		1	371		1	267		1			1	422	581	339
	amylacetate [µg/L] trans-linalool oxide [µg/L]	1	1	19 1	1	9	54	1	54	1	67	8	27 23	17 33	68	1	20 30	56	1	65	1	39	5	19 51	17 78	57	1	68	1	1	1	40 1	62	1	14 40	67	1	12 33	91	1	48	57	1	31 35	31 30	35 56
	hexylacetate [µg/L] cis-linalool oxide [µg/L]	10 1	87 1	62 1	13 21	10 23	21 31	19 15	55 16	35	9	50 19	17 26	29	9	33 19	23 25	28 36	18 30	27 28	14 1	133 1	25 26	25 29	18 30	100 17	18 73	23	15 25	76 17	66 15	30 31
	ethylester nerol oxide [µg/L]		5	6		9	20	12	10	10	8	16	9	24	19		6	10	18	15	18	25	9	14	20	15	9	33	11	25	10	11	17
	3-sulfanylhexan-1-ol [µg/L] ethyl propanoate [µg/L] C 13 -norisoprenoids	88		102	92		128	75		104	68	60	76		61	110	1		57		64	83	107	79		62		46	78		59	140	52	20		107	43		33	71	106
	ethyl iso-butyrate [µg/L] vitispirane isomers [µg/L]	68 28	31 26	47 29	44 40	84 40	54 25	41 18	81 32	84 51	57 30	122 31	87 55	47	0	35 39	73 75	52 112	100 48	81 41	27 31	61 44	37 26	102 52	86 39	36 39	53 38	122 45	49 25	37 29	84 66
	ethyl butyrate [µg/L] TDN [µg/L]	133 0.6	242 0.7	246 0.7	315 5.0	156 5.0	265 0.0	232 0.0	246 1.3	200 4.9	220 0.9	147 4.2	191 5.6	201 0.0	216 2.8	261 5.9	307 17.2	222 3.4	166 4.9	313 1.3	347 2.6	316 1.3	245 5.9	344 2.8	177 2.4	325 2.1	212 8.1	137 1.4	283 1.4	235 6.2
	ethyl lactate [µg/L] β-damascenone [µg/L]	25		19	22		138	27		73		22	19	228	148	17		193	76		13	71	22		56		24		14	43		144	34		22	77		33	25		17	15	35
	ethyl caproate [µg/L]	400	658	594	855	486	673	652	611	646	588	452	427	509	515	635	836	663	563	754	817	642	704	764	381	912	545	355	656	448
	diethyl succinate [µg/L]	6205 2197 1670 3520 5989 3023 1661 2215 4985 1019 3389 6612 1597 501 2626 2838 2061 3348 690 2641 1327 5483 1725 1831 3897 322 1248 3380
	ethyl capryloate [µg/L]	766 1160 818 1279 971 1289 1306 886 1031 1039 839	773	894	745	997 1427 1064 1098 1039 1109 1108 1181 1296 576 1013 733 1043 749
	ethyl capriate [µg/L]	181	329	218	194	263	363	307	226	227	280	180	206	294	180	195	423	305	281	283	221	278	252	322	107	278	307	192	300	150
																																												xx

  Aroma compound's concentrations in the wines assessed in sensory studies by the French panel: sulfur compounds by means of GC-PFPD 1 and according toTominaga et al., (2006) 2 ; value 0 indicates concentration below limit of quantification for the concerning aroma compound

	Appendix 14 Typicity	SBBX	SBAL	SBNZ	RIAL4	RIAL3	GTAL	PGAL	RINA1	RIAL5	RIRH4	RIAL2	RIAL1	RIRH1	RIRH8	RIRH3	RINZ	RIRH2	RIAL7	RIAUT2	RIRH5	RIRH6	RIAL6	RIMO1	RIRH11	RIRH9	RIRH7	RINA2	RIAUT1	RIRH10
	Sulfur compounds
	hydrogen sulfide [µg/L]	13	14.8	7.7	14	5.4	4.5	3.6	10	10	6	3.6	8.1	20.6	7.7	22.9	14.8	5.8	5.3	5.2	8.9	9.1	7.8	8.6	4.3	19	5.3	3.7	11.5	11.5
	methanethiol [µg/L]	0	7.1	0	4.5	0	0	0	0	0	0	0	0	0	4.6	5.8	5.6	0	4.3	4.7	0	5.2	4	4.8	0	5.8	0	10.1	0	17.5
	dimethyl sulfide [µg/L]	9.7	48.6	20.6	9.5	7.1	7.4	10.4	14.2	7.2	6.8	7	5.5	8.6	6	11	17.3	15	6.4	12.7	12.3	7	6.1	4.2	6	8.8	7.1	5.1	12.7	6.4
	carbon disulfide [µg/L]	3.2	3.1	1.9	4	4.2	4.3	8	15.8	2.1	4.2	16.1	25.6	4.5	4.5	5.6	5.3	5	3.8	2	6.1	7.3	1.3	1.8	2.5	4.1	3.1	6.4	18.3	13.8
	ethyl 2-sulfanylpropionate [ng/L]
		0.0	1.3	0.2	0.0	0.0	0.2	0.2	0.2	0.1	0.4	0.2	0.0	0.0	0.7	0.0	0.3	0.4	0.3	0.5	0.3	0.2	0.0	0.7	0.0	0.0	0.2	0.0	0.4	0.6
																												xxi

purity determined by means of total ion chromatogram peak areas oft the pure standard

Acknowledgements

First of all I would like to thank my supervisor Prof. Dr. Philippe Darriet, Professor at the Faculté d'OEnologie and director of the Unité de rechérche OEnologie, EA 4577 -Université Bordeaux Segalen -INRA OEnologie for his supervision, helpful advice and support during the whole time of my thesis. I highly appreciated to get introduced into the universe of OEnologie and aroma chemistry during my time as his doctoral student. I want to thank for his patience with and his confidence in me and his sympathetic guidance not only in scientific

Multivariate methodology

A combination of Partial Least Square Regression (PLS) and Canonical Correspondence Analysis (CCA) regarding Riesling wines' typicality ratings was applied as a multivariate approach, to gain insights into implied descriptor families as well as into possible contributions of aroma compounds. Typicality ratings, as global judgements, were explained as product characteristics by the variables 'aromatic compound concentration' using PLS (Tenenhaus et al., 2005). The most contributing variables in the received model, from both panels' data sets, have then been introduced into the CCA as metric variables. 2.5.8.2.1 Partial Least Square Regression (PLS) Typicality vs. aroma compounds -total Partial Least Square regression was applied on the German and French panels' data sets to extract volatile compounds implicated in the perception of Riesling wines' typicality.

German data set

The resulting PLS regression of the relative typicality ratings (Y's) on the volatile compounds concentrations (X's) showed good quality on one component (Q 2 (cum) = 0.521; R 2 Y (cum) = 0.690, R 2 X (cum) = 0.141). The most important variables in the PLS model were chosen by the Variable Importance in the Projection table by choosing variables with minimum values of 0.8 on the first component .

French data set

For the French panel PLS regression of relative typicality ratings (Y's) on the volatile compounds concentrations (X's) also showed good model quality on three components (Q 2 (cum) = 0.738; R 2 Y (cum) = 0.972, R 2 X (cum) = 0.375). Like for the German panel, the most important variables in the PLS model were chosen by the Variable Importance in the Projection table by choosing variables with higher values than 0.8 on the first component (Table 2 -20).

Common important variables

To choose the aroma compounds most likely being involved in typicality related sensory properties, intersecting aroma compounds of both panels' regression models were chosen.

The resulting 15 aroma compounds, presented in Table 2-20 were used for further multivariate analysis. Chapter 4 4 Aroma compound identification

4.2.9

Two-dimensional heart-cut gas chromatography coupled to olfactometric detection and high-resolution mass-spectrometry (GC-GC-O-HRMS)

The chromatographic setup and conditions are presented in Table 4-6:

Calculation of lineary retention indices (LRI)

Lineary Retention Indices (LRI) were calculated according to the method proposed by [START_REF] Kovats | Gas chromatographische Charakterisierung organischer Verbindungen[END_REF]. The LRI is a characteristic, which allows comparing volatile compound seperation behaviour on a stationary phase, towards a series of n-alcanes. This function as a characteristic, which allows comparing LRI's of single compounds independendly from instrumental setups. To calculate LRIs a solution of n-Alcanes is injected at the same condition as the aroma extract. Using the retention times of the single n-alcanes a compound LRI is calculated as:

GC-MS

The preparation of the sample and the chromatographic conditions were applied as described previously by [START_REF] Antalick | Development, validation and application of a specific method for the quantitative determination of wine esters by headspace-solidphase microextraction -gas chromatography -Mass Spectrometry[END_REF]. Quantification was done by calculating the response factor to the isotopically labelled trans-ethyl cinnamate-d 5 . Analysis was carried out in the Laboratory of Professor Dr. Gilles de Revel at the ISVV in Bordeaux. Concentration levels in wine like model solution (MS) and in Riesling wine (RW) were 0 µg/L (MS) 0.2 µg/L (RW), 0.5 µg/L, 1.0 µg/L, 2.5 µg/L, 5.0 µg/L, 7.5 µg/L and 10 µg/L.

4.2.12

The odour detection threshold was calculated as the concentration, when 50% of panelists detected a difference between the sample and the sample's matrix above chance level.

According to [START_REF] Lawless | Sensory evaluation of food -principles and practices[END_REF] the calculated percentage of detected differences in the applied design was should be p req 75%. Generally, the hypothesis which suggests different OZ in TSAE of typical Riesling wines in comparison to typical Sauvignon blanc / Semillon blended wines could be confirmed.

Albeight there was no OZ reminding specificly typical Riesling wines' aromatic expression and which then was not abundant in Sauvignon blanc style wines' TSAE.

4.3.3

Comparison of the aroma extract fractions (AEF) of typical

Riesling wines and typical Sauvignon blanc style wines

Following an alternative approach in order to compare varietal wines' aroma, global organic aroma extracts were fractioned using a semi preparative HPLC configuration (RP-C 18 , H 2 O -ethanol gradient), resulting in an order of elution from polar compounds in the earlier fractions and less polar compounds in the late fractions. Developed by Ferreira et al. (1999), and then adapted by [START_REF] Pineau | Examples of perceptive interactions involved in specific 'red-' and 'black-berry' aromas in red wines[END_REF], this approach has been used with success in the work group in some following published works, in order to evidence odoriferous compounds contributing to qualitative aspects of wine flavour or off-odours [START_REF] Pons | Recherches sur l'arôme de vieillissement prèmaturé des vins[END_REF][START_REF] Pineau | Examples of perceptive interactions involved in specific 'red-' and 'black-berry' aromas in red wines[END_REF][START_REF] Sarrazin | Elucidation of the 1,3-sulfanylalcohol oxidation mechanism: An unusual identification of the disulfide of 3-sulfanylhexanol in Sauternes botrytized wines[END_REF][START_REF] Nikolantonaki | Identification of ethyl 2-sulfanylacetate as an important off-odor compound in white wines[END_REF].

After fractionation, the obtained fractions of the wines' aroma extracts (AEF) were evaluated Geisenheim, den 12.11.2012